SORPTION OF ANTIBIOTICS BY BLACK CARBON SORBENTS AND ITS IMPACT TO TRANSPORT OF ANTIBIOTICS IN SOILS By CHENG - HUA LIU A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Crop and Soil Scienc es Doctor of Philosophy 2018 ABSTRACT SORPTION OF ANTIBIOTICS BY BLACK CARBON SORBENTS AND ITS IMPACT TO TRANSPORT OF ANTIBIOTICS IN SOILS By CHENG - HUA LIU Antibiotics are extensively used in human health care and livestock industry, resulting in rapi d increases in their environmental concentrations. These anthropogenic antibiotics are considered emerging contaminants, and their increased concentrations in the environment have raised serious concerns on the proliferation of antibiotic resistant bacteri a and associated impacts to human and ecosystem health. Therefore, innovative management strategies are needed to manage the risks of antibiotic resistance. Engineered black carbon (BC) materials (e.g., biochars and activated carbon) may be used as sorbent s to sequester antibiotics from contaminated soils and waters in situ , thus decreasing the mobility and bioavailability of antibiotics in the environment. To this end, a better understanding of mechanisms controlling the sorption of antibiotics to BC (spec ifically biochars) is critically needed for developing scientifically - sound mitigation strategies. The first research topic aimed to investigate sorption of lincomycin (one class of antibiotics) to manure - based biochars and their potentials for the long - t erm lincomycin immobilization. Lincomycin sorption to biochars was greater at solution pH (6.0 7.5) below the pKa of lincomycin (7.6) than at pH (9.9 10.4) above its pKa. The enhanced lincomycin sorption at lower pH likely resulted from electrostatic attra ction between the positively charged lincomycin and the negatively charged biochar surfaces. This was corroborated by the observation that lincomycin sorption decreased with increasing ionic strength at lower pH (6.7) but remained constant at higher pH (10 ). Long - term lincomycin sorption was characterized by two - stage kinetics with fast sorption reaching quasi - equilibrium in the first two days, followed by slow sorption over the long term. The fast sorption was primarily attributed to surface adsorption, wh ereas the long - term slow sorption was controlled by slow pore diffusion. Specially, lower - temperature (300°C) biochars had higher sorption capacity and faster sorption kinetics than higher - temperature (400 600°C) biochars. The continuous release of dissolv ed organic carbon (DOC) from the lower - temperature biochars may enhance the lincomycin sorption by decreasing biochar particle size and/or increasing the accessibility of sorption sites initially blocked by DOC. This study further quantified and characteri zed the DOC extracted by deionized water, 0.1 M HCl, and 0.1 M NaOH from 46 biochars produced from diverse feedstocks and pyrolysis conditions. A quick, easy and robust UV - vis spectrometric method was developed to measure the DOC concentrations in diverse biochar samples. Our findings highlight that biochars may have the potential to be used as soil amendment to immobilize antibiotics in situ over the long term. The second research topic was to understand the unintended consequence of BC nanoparticles on t he transport of antibiotics in soils. BC nanoparticles are ubiquitous in nature, and may act as carriers to facilitate the transport of antibiotics. Hence , we investigated the facilitated transport of three veterinary antibiotics (lincomycin, oxytetracycli ne, and sulfamethoxazole) by BC nanoparticles in saturated sand columns at solution pH of 7, and ionic strength of 0.1, 1, or 10 mM. The total transport of antibiotics was enhanced in the presence of BC nanoparticles in low - salinity water, but decreased at high - salinity water, implying that the facilitated transport of antibiotics may occur under rainfall or irrigation that can decrease soil salinity . Copyright by CHENG - HUA LIU 201 8 v This dissertation is dedicated to my supportive parents, Shao - Chih Liu and Sung - Ying Chung, and parents - in - law, Shuang - Jung Chuang and Su - Mei Peng, my brother , Cheng - Wen Liu , my love, Ya - Hui Chuang, and our beloved daughter, Emma Liu. I love you all! vi ACKNOWLEDGEMENTS My dissertation research would not have been possible without the support of numerous pe ople. First and foremost, I am extremely thankful to my academic advisor Professor Wei Zhang for his guidance, prudent advice and mentorship throughout my doctoral study. Without him taking me as one of his graduate students, I cannot fulfill one of my goa ls today; and without his support, p rofessional experience and endless patience, this dissertation would not have been possible or completed. I also express my profound appreciation to my academic committee members, Professor Stephen A. Boyd, Professor Hui Li , and Professor Jay P. Zarnetske , for g enerously offering their time, recommendations, and suggestions to improve this dissertation research. I would like to extend my acknowledgment to all my wonderful lab group members, colleagues, and friends at Mich igan State University : Drs. Yingjie Zhang, Yuan Tian, Haiyan Wang , Shen Qu , Sangho Jeon, Zeyou Chen , Thaisa Pegoraro , J. Brett Sallach, and Yuanbo Li , as well as Mark Bezdek, Sicao Wang, Feng Gao, Gemini D. Bhalsod, Xiaohang Yu , Anping Peng , Jianzhou He , Y ike Shen, Yu Zhang , and many others . I am greatly appreciated for their help, support, brainstorming ideas, friendship , and collaborations. Last but not least, I would like to express my deepest gratitude to my parents Shao - Chih Liu and Sung - Ying Chung , my parents - in - law , Shuang - Jung Chuang and Su - Mei P e ng , and m y brother , Cheng - Wen Liu , for their love, encouragement , and spiritual support in all aspects of my life. My greatest appreciation is to my wife , Ya - Hui Chuang for her love, support, and c ollaboration as well as always being with me throughout my research journey. To my beloved daughter , Emma Liu , in particular, thank you for always being such a sweet and wonderful girl! vii TABLE OF CONTENTS LIST OF TABLE S ................................ ................................ ................................ ........................ x LIST OF FIGURES ................................ ................................ ................................ .................... xii CHAPTER I INTRODUCTION AND OBJECTIVES ................................ ............................. 1 INTRODUCTION ................................ ................................ ................................ ................................ .... 2 OBJECTIVES ................................ ................................ ................................ ................................ ........... 6 CHAPTER II SORPTION OF LINCOMYCIN BY MANURE - DERIVED BIOCHARS FROM WATER ................................ ................................ ................................ ............................ 8 ABSTRACT ................................ ................................ ................................ ................................ .............. 9 INTRODUCTION ................................ ................................ ................................ ................................ .. 10 MATERIALS AND METHODS ................................ ................................ ................................ ............ 12 Biochar Samples and Characterization ................................ ................................ ............................... 12 Sorption Experiments ................................ ................................ ................................ .......................... 14 Chemicals and Exp erimental Setup ................................ ................................ ................................ .... 14 Sorption Kinetics ................................ ................................ ................................ ................................ 15 Effects of Biochar Particle Size and Solid - Water Ratio ................................ ................................ ..... 18 Effects of Solution pH and Ionic Strength ................................ ................................ .......................... 18 LC - MS/MS Analytical Procedure ................................ ................................ ................................ ....... 19 Mathematical Mod eling ................................ ................................ ................................ ...................... 19 RESULTS AND DISCUSSION ................................ ................................ ................................ ............. 20 Properties of Manure - Derived Biochars ................................ ................................ ............................. 20 Two - phase Sorption Kinetics ................................ ................................ ................................ .............. 24 Effects of Biochar Particle Size and Solid - Water Ratio ................................ ................................ ..... 29 Effect of Solution pH and I onic Strength ................................ ................................ ............................ 31 Implications ................................ ................................ ................................ ................................ ......... 36 CHAPTER III QUANTIFICATION AND CHARACTERIZATION OF DISSOLVED ORGANIC CARBON FROM BIOCHARS ................................ ................................ ............. 38 ABSTRACT ................................ ................................ ................................ ................................ ............ 39 INTRODUCTION ................................ ................................ ................................ ................................ .. 40 MATERIALS AND METHODS ................................ ................................ ................................ ............ 43 Biochars ................................ ................................ ................................ ................................ .............. 43 Extraction of Biochar - DOC ................................ ................................ ................................ ................ 48 Fractionation of Biochar - DOC ................................ ................................ ................................ ............ 49 TOC and UV - vis Analyses of Biochar - DOC ................................ ................................ ...................... 49 Solid - state 13 C NMR Analyses ................................ ................................ ................................ ............ 50 Estimation of Biochar - DOC Concentrations ................................ ................................ ...................... 53 RESULTS AND DISCUSSION ................................ ................................ ................................ ............. 54 DOC Concentrations in Biochars ................................ ................................ ................................ ........ 54 Fractionation of Biochar - DOC ................................ ................................ ................................ ............ 57 UV - vis Absorption Spectra Characterization ................................ ................................ ..................... 60 Adva nced Solid - state 13 C NMR ................................ ................................ ................................ .......... 65 Factors Influencing Biochar - DOC. ................................ ................................ ................................ ..... 71 Quick and Easy Method to Estimate DOC Concentrations ................................ ................................ 75 viii Implications ................................ ................................ ................................ ................................ ......... 86 CHAPTER IV LONG - TERM SORPTION OF LINCOMYCIN TO BIOCHARS: THE INTERTWINED ROLES OF PORE DIFFUSION AND DISSOLVED ORGANIC C ARBON ................................ ................................ ................................ ................................ ..... 87 ABSTRACT ................................ ................................ ................................ ................................ ............ 88 INTRODUCTION ................................ ................................ ................................ ................................ .. 89 MATERIALS AND METHODS ................................ ................................ ................................ ............ 92 Chemicals ................................ ................................ ................................ ................................ ............ 92 Sorbents ................................ ................................ ................................ ................................ .............. 92 Sorbent Characterization ................................ ................................ ................................ ..................... 93 Sorption Experiments ................................ ................................ ................................ .......................... 94 Effects of DOC on Lincomycin Sorption ................................ ................................ ........................... 97 Extraction o f Sorbed - lincomycin from Biochars ................................ ................................ ................ 99 Analytical Methods ................................ ................................ ................................ ........................... 100 Mathematical Modeling ................................ ................................ ................................ .................... 101 RESULTS AND DISCUSSION ................................ ................................ ................................ ........... 102 Characterization of Biochars. ................................ ................................ ................................ ............ 102 Long - term Sorption Kinetics ................................ ................................ ................................ ............ 107 Long - term Sorption Isotherms ................................ ................................ ................................ .......... 115 Effects of DOC on Sorption ................................ ................................ ................................ .............. 120 Desorption Hy steresis ................................ ................................ ................................ ....................... 128 Implications ................................ ................................ ................................ ................................ ....... 130 CHAPTER V BLACK CARBON NANOPARTICLES FACILITATED TRANSPORT OF ANTIBIOTICS IN SATURATED SAND ................................ ................................ ............... 131 ABSTRACT ................................ ................................ ................................ ................................ .......... 132 INTRODUCTION ................................ ................................ ................................ ................................ 133 MATERIALS AND METHODS ................................ ................................ ................................ .......... 136 Chemicals ................................ ................................ ................................ ................................ .......... 136 BC Nanoparticles ................................ ................................ ................................ .............................. 137 Porous Medium ................................ ................................ ................................ ................................ . 139 Batch Sorption Experiments ................................ ................................ ................................ ............. 139 Column Transport Experiments ................................ ................................ ................................ ........ 141 Analytical Methods ................................ ................................ ................................ ........................... 144 Mathematical Modeling ................................ ................................ ................................ .................... 146 theory Calculations ................................ ................................ ................................ ....... 149 R ESULTS AND DISCUSSION ................................ ................................ ................................ ........... 151 Characterization of the BC nanoparticles and Sand ................................ ................................ .......... 151 Sorption Isotherms ................................ ................................ ................................ ............................ 153 Transport of BC nanoparticles ................................ ................................ ................................ .......... 156 Transport of Antibiotics ................................ ................................ ................................ .................... 159 Implications ................................ ................................ ................................ ................................ ....... 164 CHAPTER VI CONCLUSIONS AND FUTURE WORK ................................ .................... 165 CONCLUSIONS ................................ ................................ ................................ ................................ ... 166 FUTURE WORK ................................ ................................ ................................ ................................ .. 166 APPENDICES ................................ ................................ ................................ ........................... 168 Appendix A: Sorption Isotherms Data ................................ ................................ ................................ .. 169 ix Appendi x B: Sorption Kinetics Data ................................ ................................ ................................ .... 175 Appendix C: Column Breakthrough Experiments Data ................................ ................................ ........ 180 REFERENCES ................................ ................................ ................................ .......................... 188 x LIST OF TABLE S Table 2.1. Chemical and physical properties of lincomycin ................................ ....................... 14 Table 2.2. Selected physical and chemical proper ties of manure - derived biochars ................... 21 Table 2.3. Fitted parameters of pseudo - first - order, pseudo - second - order, and intraparticle diffusion models for long - term sorption kinetics of lincomycin on manure - derived biochars. ... 27 Table 2.4. Fitted parameters of Langmuir and Freundlich equations for lincomycin sorption on manure - derived biochars. ................................ ................................ ................................ .............. 31 Table 3.1. Feedstock and production details of biochar samples. ................................ ................ 45 Table 3.2. Selected properties of biochar samples. ................................ ................................ ...... 47 Table 3.3 Extrac table DOC concentration of biochar samples. ................................ ................... 56 Table 3.4. UV - vis spectral parameters of AEOC, WEOC, BEOC, BEOC - AS, and BEOC - AP. 63 Table 3.5. Functional groups of the biochars and DOC estimated by quantitative 13 C multiCP/MAS spectra. a ................................ ................................ ................................ ................. 70 Table 3.6. Variation across pyrolysis temperature and feedstock of the WEOC of 20 tested biochars. a ................................ ................................ ................................ ................................ ....... 72 Table 3.7. The correlation coefficient (r) between WEOC and biochar properties (* and ns denote significant at p < 0.05 and not significant , respectively). ................................ ................. 73 Table 4.1. Physicochemical properties of lincomycin. ................................ ................................ 92 Table 4.2. Selected properties of biochar and graphi te samples. ................................ ............... 104 Table 4.3. Fitted parameters of the intraparticle diffusion model for the long - term sorption kinetics of lincomycin by the biochars. a ................................ ................................ ..................... 108 Table 4.4. Fitted parameters of the Freundlich model for quasi - equilibrium sorption isotherms of lincomycin on the biochars at 1, 7, 30, and 365 days. a ................................ ............................... 116 Table 4.5. Fitted parameters of the intraparticle diffusion model for the sorption kinetics of lincomycin by woodchip waste biochar. a ................................ ................................ ................... 121 Table 4.6. Fitted parameters of the intraparticle diffusion mode l for the sorption kinetics of lincomycin by raw - , DI - water - washed, and 0.01M - NaOH - washed biochars. a .......................... 122 xi Table 5.1. Physicochemical properties of lincomycin, oxytetracycline, and sulfamethoxaz ole . 137 Table 5.2. Surface energy components and Hamaker constants used in XDLVO calculations. 151 Table 5.3. Properties for BC nanoparticles and sand colloids. a ................................ ................. 152 Table 5.4. Fitted parameters of the Freundlich model for sorption isotherms of LCM, OTC, or SMX on BC nanoparticles and sand under ionic strength (IS) of 0.1, 1, or 10 mM and pH of 7.0. a ................................ ................................ ................................ ................................ ..................... 155 Table 5.5 . Fitted transport parameters for breakthrough curves of BC nanoparticles with and without LCM, OTC or SMX in saturated sand column. a ................................ ........................... 158 Table 5.6. Effluent mass recovery calculations of breakthrough curves for LCM, OTC, and SMX in the antibiotic - only and co - transport experiments. ................................ ................................ .. 162 Table 5.7. Fitted transport parameters of breakthrough curves for LCM, OTC, and SMX in the antibiotic - only and co - transport experiments. a ................................ ................................ ........... 162 xii LIST OF FIGURE S Figure 2.1. Lincomycin concentration versus time for lincomycin sorption kinetics experiments. Control was the biochar - free lincomycin solution. ................................ ................................ ....... 16 Figure 2.2. Precursor ion scan spe ctra of (a) Control (freshly prepared), (b) Control (180 days), (c) BM600 (180 days), (d) DM600 (180 days), (e) AM600 (180 days), and (f) PM600 (180days). Control was the biochar - free lincomycin solution. No degradation candidates of lincomycin was detecte d in long - term kinetics samples (b, d, f). ................................ ................................ ........... 17 Figure 2.3. Zeta potential of manure - derived biochars as a function of solution pH. ................. 22 Figure 2.4. SEM images of manure - derived biochars: (a) BM600, (b) DM600, (c) AM600, and (d) PM600, prepared from biochar suspensions of 1 - day water exposure. ................................ .. 23 Figure 2.5. (a) Short - term and (b) long - term lincomycin sorption kinetics on manure - derived biochars. The solid lines were fitted with the intraparticle diffusion model. ............................... 26 Figure. 2.6. SEM images of manure - derived bio chars after 1 - day and 180 - day water exposure: (a, b) BM600, (c, d) DM600, (e, f) AM600, and (g, h) PM600. ................................ ................... 28 Figure. 2.7. Sorption of lincomycin on manure - derived biochars with varying (a) par ticle sizes and (b) solid - water ratios. ................................ ................................ ................................ ............. 30 Figure. 2.8. Observed and fitted sorption isotherms of lincomycin on biochars at solution pH 6.0 7.3 and pH 9.9 10.4. The solid lines were fitted wit h the Langmuir model, and the dashed lines with the Freundlich model. ................................ ................................ ................................ ... 34 Figure. 2.9. Sorption of lincomycin on manure - derived biochars at solution pH of 6.1 7.5 and 10 10.3 under varying ioni c strength. ................................ ................................ .......................... 35 Figure 3.1. Dissolved organic carbon (DOC) concentrations (a) and illustrative solution colors (b) of acid - extrac table DOC (AEOC), water - extractable DOC (WEOC), and base - extract able DOC (BEOC) from 46 tested biochars (FP: fast pyrolysis; SP: slow pyrolysis; n/a: not available). ................................ ................................ ................................ ................................ ....................... 55 Figure 3.2. Fractionation of WEOC and BEOC extracted from biochars. ................................ .. 58 Figure 3.3. Effects of the extraction methods (a), pyrolysis conditions (b), and feedstocks(c) on the acid - soluble (AS) and acid - precipitated (AP) fraction ratio of biochar - DOC. (AEOC: acid - extractable DOC; W EOC: water - extractable DOC; BEOC: base - extractable DOC; FP: fast pyrolysis at 500 °C; SP300 - 400: slow pyrolysis at 300 to 400 °C; SP450 - 600: slow pyrolysis at 450 to 600 °C). ................................ ................................ ................................ .............................. 59 xiii Figure 3.4. UV - vis spectra of DOC solutions (bull manure biochar as examples): (a) AEOC, (b) WEOC, (c) BEOC, and (d) the As and AP fractions of BEOC (BM300). ................................ ... 61 Figure 3.5. Box plots of UV - vis spectroscopic analyses of DOC in biochars: (a) E 2 : E 3 ratio and (b) S 275 295 . The box plots showed the first quartile, median, mean, and third quartile of the samples, and the whiskers showed the range of minimum and maximum. The symbols on the left side of box plots showed the distribution of sample values. Detailed data are provided in Table 3.4. (FP: fast pyrolysis; SP: slow pyrolysis; n/a: not available) ................................ ................... 62 Figure 3.6. Solid - state 13 C multiCP/MAS NMR spectra (block black line) and multiCP/MAS after dipolar deph asing (thin red line) of biochar - Raw ((a) to (e)), biochar - DI ((f) and (g)), biochar - NaOH ((h) to (l)), BEOC (m) and dBEOC ((n) to (q)) samples. ................................ ..... 69 Figure 3.7. Box - whisker plot of WEOC concent rations vs pyrolysis temperature (a), pyrolysis type (b) and feedstocks (c). The box plots showed the first quartile, median, mean, and third quartile of the samples, and the whiskers showed the 1.5 times interquartile range. The column charts by the right side of the box plots showed the sample sets for box plots. ........................... 74 Figure 3.8. Linear regressions between decadic absorption coefficient at 254 nm and biochar DOC concentrations in solution for ( a) AEOC, WEOC, and BEOC, and (b) BEOC - AS and BEOC - AP. The dilution factor for AEOC and WEOC was 10 and for BEOC, BEOC - AS, and BEOC - AP was 50. For AEOC, 11 samples with serve matrix interference were excluded. For WEOC, SB500 and SG500 skewed the correlatio n because of the distinct compositional difference with other 44 samples (Figure 3.2), and thus were excluded. For BEOC - AS and BEOC - AP, only 27 fractionable BEOC samples were included. ................................ ................. 82 Figu re 3.9. (a) Experimental data for BM300 as example, (b) boxplot of the E 2 / E 3 ratios of 27 fractionable BEOC samples, and (c) Fitting E 2 / E 3 vs f data with the rational function model. ... 83 Figure 3.10. Measured versus modeled water - extractable DOC (WEOC) by E 2 / E 3 ratio and a 254 . Dashed line represents the 1:1 relationship. Dilution was made by 10 - folds for the WEOC samples. ................................ ................................ ................................ ................................ ......... 84 Figure 3.11. Measured versus modeled DOC for (a) AEOC and (b) BEOC by E 2 / E 3 ratio and a 254 . Dashed line represents the 1:1 relationship. Dilution was made by 10 - and 50 - folds for the AEOC and BEOC samples, respectively. ................................ ................................ ..................... 85 Figure 4.1. Lincomycin concentrations in solution over time in the kinetic sorption experiments for the 17 tested biochars. Control was the biochar - free lincomycin solution. ............................ 96 Figure 4.2. The relationship of (a) total carbon, (b) fixed carbon, (c) volatile matter, and (d) ash contents versus CO 2 - BET specific surface area for biochars. ................................ .................... 105 Figure 4.3. Scanni ng electron microscopy images of raw biochars: (a) BM300 (bull manure biochar produced at 300 °C) and (b) BM600 (bull manure biochar produced at 600 °C). ......... 106 xiv Figure 4.4. Long - term kinetics of lincomycin sorption by biochars. The sorption data were fitted by the intraparticle diffusion model (solid line), and the hollow data were excluded from the fitting because of reaching sorption saturation. ................................ ................................ .......... 111 Figure 4.5. Sorption kinetics (a) and isotherms (b) of lincomycin to graphite. The solid lines were fitted by the pseudo - second - order model and the Freundlich model, respectively. ........... 112 Figure 4.6. The relationship of (a) intraparticle diffusion rate constant ( k id ), (b) initial sorption ( C id ), and (c) interparticle diffusion factor ( R id ) versus pyrolysis temperature for 17 biochars. 113 Figure 4.7. Long - term release of dissolved organic carbon from biochars. .............................. 114 Figure 4.8. Quasi - equilibrium sorption isotherms of lincomycin by bull manure - based biochars produced at different temperature: (a)BM300, (b) BM400, (c) BM500, and (d) BM600. K F ( g 1 N g 1 L N ) is the Freundlich sorption coefficient, and N (dimensionless) is the Freundlich nonlinearity factor. ................................ ................................ ................................ ...................... 117 Figure 4.9. Quasi - equilibrium sorption isotherms of lincomycin to biochars: (a) DM300, (b) DM400, (c) DM600, (d) PM300, (e) PM400, (f) PM500, (g) PM600, (h) RDM500, (i) DDM500, (j) DDM600, (k) CDM500, (l) CDMW500, and (m) WW500. The solid line s were fitted with the Freundlich isotherm model. ................................ ................................ ................................ ........ 118 Figure 4.10. The relationship of Freundlich sorption coefficient ( K F ) and Freundlich nonlinearity factor ( N ) versus pyrolysis temperature for biochars. ................................ ................................ . 119 Figure 4.11. The effect of DOC as co - solutes on sorption kinetics of lincomycin by WW500 biochar (WW500+DI was the control of absence DOC). ................................ ........................... 123 Figure 4.12. Long - term kinetics of lincomycin sorption by raw and DOC - washed biochars. The sorption data were fitted by intraparticle diffusion model (solid line). ................................ ...... 124 Figure 4.13. Long - term kinetics of lincomycin sorption by raw and DOC - washed biochars. The sorption data were fitted by the intraparticle diffusion model (solid line) and the hollow data were excluded because of approaching sorption saturation. ................................ ....................... 125 Figure 4.14. Scanning electron microscopy images of bull manure biochar pyrolyzed at 300°C (BM300): (a) raw BM300 without treatment, (b) BM300 after 1 - d background solution exposure, (c) BM 300 after 365 - d background solution exposure, and (d) BM300 after 1 - d 0.1M NaOH solution exposure. Background solution contained 1000 g L 1 lincomycin, 6.7 mM NaCl, 2.5 mM Na 2 CO 3 , 2.5 mM NaHCO 3 , and 200 mg L - 1 NaN 3 . ................................ ............................ 126 Figure 4.15. Particles size distribution of (a) bull manure biochar pyrolyzed at 300°C (BM300) and (b) bull manure biochar pyrolyzed at 600°C (BM600) suspended in 0.1 M NaCl (upper panel) or in 0.1 M NaOH (lower panel) after on e - day exposure. ................................ ............... 127 xv Figure 4.16. (a) Extraction efficiency of 240 d - sorbed lincomycin in the biochars and (b) the relationship of intraparticle diffusion rate constant ( K id ) versus lincomycin extraction efficiency for biochars. ................................ ................................ ................................ ................................ 129 Figure 5.1. Scanning electron microscopy images of BC nanoparticles prepared from stock suspensions. ................................ ................................ ................................ ................................ 138 Figure 5.2. Sorption kinetics of LCM (a and d), OTC (b and e), SMX (c and f) on BC nanoparticles and sands under ionic strength (IS) of 0.1, 1 or 10 mM and solution pH of 7.0. . 141 Figure 5.3. Linear regressions between UV - vis absorbance at 550 nm and BC nanoparticle concentrations in suspension. ................................ ................................ ................................ ...... 144 Figure 5.4. Measured and fitted breakthrough curve of the bromide tracer through saturated sand column. Symbols are experimental data and lines are fitted result. ................................ ............ 148 Figure 5.5. Aggregation kinetics of BC nanoparticles dispersed in the KCl solution with ion ic strength (IS) of 0.1, 1, or 10 mM at pH 7.0. ................................ ................................ ............... 153 Figure 5.6 Sorption isotherm of LCM (a and d), OTC (b and e), SMX (c and f) on black carbon (BC) nanoparticles and sands under ionic strengt h (IS) of 0.1, 1 or 10 mM and pH of 7.0. ...... 155 Figure 5.7. Measured and fitted breakthrough curves of black carbon nanoparticles (BCN) without (a) and with (b, c and d) of lincomycin (LCM), oxyt etracycline (OTC) or sulfamethoxazole (SMX) in saturated sand columns at solution pH of 7 and ionic strength (IS) of 0.1, 1, or 10 mM KCl. ................................ ................................ ................................ ................. 157 Figure 5.8. XDLVO surface energy profiles for bla ck carbon (BC) nanoparticles interacting with sand surfaces with the energy barrier (a) and the secondary minima (b). ................................ .. 158 Figure 5.9. Measured and fitted breakthrough curves of lincomycin (LCM ), oxytetracyline (OTC) and sulfamethoxazole (SMX) without black carbon nanoparticles (BCN) (a, b and c) and the BCN - associated LCM, OTC and SMX (d, e and f) in saturated sand columns at solution pH of 7 and ionic strengths of 0.1, 1, or 10 mM KCl ................................ ................................ ....... 161 Figure 5.10. Breakthrough curves of LCM (a), OTC (b), and SMX (c) in the presence of black carbon (BC) nanoparticles in saturated sand columns at solution pH of 7 and ionic strengths of 0.1, 1, or 10 mM KCl. The inserts (d, e, and f) showed the x - axis range of 0.0 to 0.1 to better view the released antibiotics in solution. ................................ ................................ .................... 163 1 CHAPTER I INTRODUCTION AND OBJECTIVES 2 Anthropogenic antibiotics have been re cognized as emerging contaminants , and increasing environmental concentrations of antibiotics warrants more attention. Antibiotics are widely used in human and veterinary medicine for disease treatment. In addition to their therapeutic use, antibiotics are also widely used in food animal production for disease prevention and growth promotion. 1 - 3 Because of the extensive use of antibiotics, they are frequently detected in soils, sediments, wastewater, surface water, and groundwater. 4 A nationwide survey on US water resources indicated that 15 different antibiotics were found in 50% of the 139 tested streams. 5 Although the concentrations of antibiotics in environmental waters are generally low (ng L 1 to µg L 1 ), their potential impact on human and ecosystem health has raised serious concerns. 6 The prevalence of antibiotics in the environment may increase selective pressure on bacteria and thus fa cilitate the development of antibiotic resistance in natural systems. 1, 7 Moreover, exposure to antibiotics may elicit acute toxicity to aquatic organisms (algae, invertebrate, fish, and plant) or unknown long - term impact to human and ecosystem heath. 8, 9 Antibiotics can enter the environment via land application of animal manure and sewage sludge, as well as discharge of wastewater treatment plant (WWTP) effluents. Manure a pplication has been considered a major source of anthropogenic antibiotics in the environment. 4 In the US, an estimated 11 . 2 million kg of antibiotics are used eac h year as nontherapeutic additives in animal feeding operations, accounting about 70% of total annual use of antibiotics. 10 A large percentage of administered antibiotics are not fully metabolized within animal bodies, and are thus excreted into manure. 11 Manure is typically land - applied for waste disposal and fertilizer use. Consequently, manure - borne antibiotics are introduced into soils through manure application, and are further transported into surface water and groundwater via surface runoff and leaching, respectively. 12, 13 3 Additionally, conventional WWTPs are not specifically designed for the effective removal of antibiotic s from wastewaters. Thus, antibiotics may be left in the WWTP effluents and sewage sludge, and then introduced into soils through land application of sewage sludge and crop irrigation using WWTP effluents (i.e., reclaimed water). 5, 14 Because increasing environmental concentrations of antibiotics could promote antibiotic resistant bacteria population and the abundance of antibiotic resistance genes, 15, 16 best management pra ctices are critically needed to manage the antibiotics in the environment and mitigate environmental risks associated with antibiotic resistance. When assessing environmental risks of antibiotics, one needs to evaluate the mobility and bioavailability of a ntibiotics rather than their total concentrations. Since soil can be a significant sink for many antibiotics, soil amendment with geosorbents (such as black carbon or biochars, BC) may prove to be a novel management strategy by sequestering antibiotics in - situ in soils and thus reducing their environmental risks. BC includes a variety of pyrogenic carbonaceous materials produced from incomplete fuel combustion or thermal decomposition of biomass under oxygen - free or - limited conditions (i.e., pyrolysis). 17, 18 BC is ubiquitous in the environment and can originate from wild and managed fires, and burning of fossil fuels. 18 - 20 Recently , a particular form of BC (biochars) has be en purposely produced (often as a co - product of syngas and bio - oil production in biomass pyrolysis) and used as a soil amendment for agronomic and environmental benefits, including improving soil fertility, carbon sequestration, and immobilization of conta minants. 21 - 26 Biochars can have vastly different chemical and physical properties, depending on the feedstock biomass and pyrolysis temperature. 24, 26, 27 A numbers of feed stocks could be used, including crop residues, woody biomass, manure, and sewage sludge. In general, biochars produced from crop residues and woody biomass has higher carbon content and lower ash content, whereas biochars produced from manure 4 and sewage sl udge has lower carbon content and higher ash content 28 . Pyrolysis temperature also plays an important role in determining the biochar properties. Typically, surface area increases with in creasing pyrolysis temperature, whereas surface functional group density decreases with increasing pyrolysis temperature. 29 Lower - temperature biochars are characterized by a relatively small number of aromatic ring s, mostly with polar functional group s . With increasing pyrolysis temperature, the percentage of polar functional group and the oxygen/carbon ratio of biochars decrease, with a concomitant increase in aromaticity and graphitic structure. 24 Recent intense interest on soil amendment with biochars is partially due to their potential to immobilize environmental contaminants. 30 Sorption of contaminants in soils is an important process affecting the contaminant fate and transport in the environment. 31 - 34 Biochars with porous structure may be desirable for soil remediati on due to their large capacity to immobilize environmental contaminants. 29, 33, 35 Previous studies have reported that biochars have strong sorption ability for many organic contaminants including antibiotics. 29, 33, 35 - 40 The knowledge on the sorption of antibiotics to biochars is still insufficient. Compar ed to other environmental containments, fewer studies have investigated the sorption of antibiotics to biochars, and t he underlying sorption mechanisms still remain unclear. 41 - 47 Hydrophobic partitioning, electrostatic interaction, hydrogen bonding, pore filling , van der Waals forces, and electro - donor acceptor ( EDA) interacti ons have been proposed as mechanisms responsible for the sorption of antibiotics to biochars. 29, 35 - 37, 48 The sorption of antibiotics to biochars also depends on physicochemical properties of biochars, such as sur face area and surface functional group. In addition, the sorption characteristics of antibiotics to biochars can be also influenced by chemical properties of antibiotics (such as polarity, hydrophobicity, and ionization) and environmental conditions (solut ion pH, ionic strength, temperature, and co - solutes). 29, 33, 35, 49, 50 Most antibiotics are 5 ionizable hydrophilic compounds and the speciation of antibiotics highly depends on solution pH. Liao et al. (2013) inves tigated the sorption of tetracycline and chloramphenicol to bamboo biochar, proposing EDA and hydrogen bonding interactions as the main sorption mechanisms for tetracycline and chloramphenicol. 43 They also reported that hydrophobic interaction and electrostatic interaction were thought to have a minor contribution to tetracycline and chloramphenicol sorption. 43 Ji et al. found that the sorption of sulfamethoxazole to biochars was controlled by micropore filling, whereas the tetracycline sorption was contr olled by surface complexation and/or cation exchange. 41 Wu et al. reported the sorption of sulfamethoxazole to BC increased with increasing pyrolysis temperature, but no significant trend was observed for the sorpt ion of ofloxacin and norfloxacin to biochars. 45 Jia et al. reported that the sorption of o xytetracycline to biochars was enhanced by the coexistence of Cu 2+ and Pb 2+ , 44 probably due to cation bridging. According to the previous studies, strong sorption of many antibiotics to biochars indicates that bioc hars have the potential to effectively immobilize antibiotics in the environment. However, due to the complexity and variability of both biochars and antibiotics, the sorption mechanisms of antibiotics to biochars are still not fully understood, which hind ers our ability to design cost - effective mitigation strategies. Recent studies raised a revived interest on dissolved organic carbon (DOC) originated from biochars because of their important role in soil and water environments. 51 - 56 DOC is often operationally defined as the fraction passed through a threshold pore size of filter membrane (e.g., 0.45 or 0.70 µm), 17 thus including both truly dissolved molecules or submicron - sized BC particles (i.e., BC nanoparticles). The DOC rel eased from BC has been reported to play a significant role in the fate and transport of soil contaminants, 34, 57 microbial activit y in soil and aquatic environments, 55, 58 and plant growth. 59 Furthermore, the DOC fraction in BC is of importance to 6 assessing the carbon turnover, because the DOC fraction is more labile and is more susceptible to photo - and bio - degradation than bulk BC. 56, 60 In addition, the DOC leached from BC could be rapidly transported from soils into nearby s urface and ground waters via surface runoff and infiltration, 61 which is also critical to soil carbon loss and the mobility of other contaminants in soils. Thus, knowledge regarding both qualitative and quantitativ e characteristics of DOC released from biochars would be essential for better accessing the quality of biochars and their impact on agroecosystems. Developing a quick, simple, and robust method for characterizing and quantifying the DOC from the biochars i s key to the quality control of biochar production and application. To do so, a thorough study on both quantification and characterization of DOC in the biochars with different feedstock and pyrolysis condition should be conducted. In addition, the DOC may initially fill up the biochar pores during production, or coated on the biochar surface, thus blocking the sorption sites for antibiotics. The release of DOC from biochars may therefore enhance the sorption of antibiotics to BC. However, the effects of DO C release from biochars on their sorption affinity to antibiotics have not been well studied. Finally, the potential for the co - transport of antibiotics and BC nanoparticles should not be overlooked. Intentional addition and accidental release of BC partic les due to wild and managed fires, crop residue burning, fossil fuel combustion, and carbon black production increased the abundance of BC particles in nature. BC particles that are mobile may facilitate the transport of sorbed antibiotics, especially for BC nanoparticles that are more mobile in soil profiles than micron - sized and bulk BC particles. 62, 63 Therefore, a better understanding of the facilitated transport of antibiotics with BC nanoparticles is essential , but again has not been fully investigated. To fill the knowledge gaps identified above, this dissertation research aimed to: 7 1. Elucidate the sorption mechanisms of antibiotics to BC (specifically biochars). 2. Quantify and characterize the DOC rele ased from biochars as influenced by feedstock type, pyrolysis condition, and extraction procedures; and develop a quick, easy and robust method to characterize and quantify the DOC from biochars. 3. To study the long - term sequestration of antibiotics by bioch ars and the potential effect of the long - term DOC release from biochars on the sorption of antibiotics. 4. To examine the facilitated transport of antibiotics by BC nanoparticles in saturated sand as influenced by solution ionic strength. The following chapte rs address the four objectives of this research. Objective 1 is addressed in Chapter II and IV, Objective 2 in Chapter III, Objective 3 in Chapter IV, and Objective 4 in Chapter V. The dissertation ends with Chapter V I that concludes the findings of this r esearch and provides future research directions. 8 CHAPTER II SORPTION OF LINCOMYCIN BY MANURE - DERIVED BIOCHARS FROM WATER 9 The presence of antibiotics in agroecosystems raises serious concerns about the proliferation of antibiotic resistant bacter ia and potential adverse effects to human health. Soil amendment with biochars pyrolyzed from manures may be a win - win strategy for novel manure management and antibiotics abatement. In this study, lincomycin sorption by manure - derived biochars was examine d using batch sorption experiments. Lincomycin sorption was characterized by two - stage kinetics with fast sorption reaching quasi - equilibrium in the first two days, followed by slow sorption over 180 days. The fast sorption was primarily attributed to surf ace adsorption, whereas the long - term slow sorption was controlled by slow diffusion of lincomycin into biochar pore structures. Two - day sorption experiments were performed to explore effects of biochar particle size, solid - water ratio, solution pH, and io nic strength. Lincomycin sorption to biochars was greater at solution pH (6.0 7.5) below the pKa of lincomycin (7.6) than at pH (9.9 10.4) above its pKa. The enhanced lincomycin sorption at lower pH likely resulted from electrostatic attraction between the positively charged lincomycin and the negatively charged biochar surfaces. This was corroborated by the observation that lincomycin sorption decreased with increasing ionic strength at lower pH (e.g., 6.7), but remained constant at higher pH (e.g., 10). N onetheless, the long - term lincomycin sequestration by biochars was largely due to pore diffusion plausibly independent of solution pH and ionic composition. Therefore, manure - derived biochars had lasting lincomycin sequestration capacity, implying that bio char soil amendment could significantly impact the distribution, transport and bioavailability of lincomycin in agroecosystems. 10 Antibiotics are considered contaminants of emerging concerns, and increasing concentrations of antibiotics in agro ecosystems could lead to the proliferation of antibiotic resistant bacteria and potential adverse impacts on human health . 1, 7, 8 The ubiquitous existence of antibiotics in agroecosystems has been linked to the wid espread and imprudent use of veterinary antibiotics in animal feeding operations as nontherapeutic feed additives 1 . After administration to food animals, a large percentage of veterinary antibiotics are excreted i nto manure as parent compounds or bioactive metabolites, and then released to the environment through manure land applications . 4, 12, 13 Thus, animal manure has been considered a major source of antibiotics in agro ecosystems, and manure - borne antibiotics will likely increase selective pressure on bacteria and facilitate the development of antibiotic resistance . 1, 7 Lincomycin and combination antibiotics containing lincomycin are widely used in food animals for treatment and control of diseases (e.g., dysentery and porcine proliferative enteropathies in pigs, necrotic enteritis in chicken, acute mastitis in dairy cattle, and contagious foot - rot in sheep), as well as for growth promotion . 64 Resultant antibiotic - resistant bacteria often possess macrolide lincosamide streptogramin B (MLSB) cross - resistance . 64 This type of multi - drug resistance poses enormous threat to human and ecosystem h ealth. Therefore, it is essential to reduce the release of lincomycin and other antibiotics to, and their mobility and bioavailability in the environment. However, lincomycin is frequently detected in the environment as a result of veterinary overuse, manu re land application, and limited degradation of lincomycin . 5, 65 - 67 Lissemore et al. found lincomycin concentrations of 0.2 to 355 ng L 1 in 92% of 125 water samples collected from the Grand River in Canada, and ag ricultural husbandry was considered the major source. 68 Kuchta and Cessna reported lincomycin concentrations of 0.08 to 0.84 ng L 1 in 11 snowmelt runoff samples from agricultural land receiving liquid swine manure containing 1 . 12 Although soil is an imp ortant filter media and sink for antibiotics, Watanabe et al. have indicated the high mobility of manure - borne lincomycin from soil to groundwater. 66 Therefore, novel soil amendment is needed for enhancing sequestration of lincomycin and other antibiotics in agricultural soils a nd thus reducing their environmental risks. Biochar as a soil amendment has received increasing attention because of its potential agronomical and environmental benefits such as improving soil quality, carbon sequestration, contaminant immobilization, as w ell as agricultural waste management . 24, 26, 33 Biochars are carbon - rich porous materials typically produced from a variety of feedstock (e.g., manure, woody biomass, crop residues, and sewage sludge) under limited oxygen condition and temperatures less than 700 °C . 24 Depending on feedstock type and pyrolysis temperature, biochars can have vastly differen t chemical and physical properties . 26, 28, 69 Previous studies have shown that biochars typically have strong sorption ability for organic contaminants . 33, 36 - 38 Because so rption of contaminants in soil often decreases their mobility and bioavailability , 31, 34, 70 the addition of biochars to soils may play an important role in controlling transport and bioavailability of antibiotics in agroecosystems. In this study, we proposed an innovative win - win strategy for novel manure management and antibiotics abatement by land application of biochars produced from pyrolysis of manures. Using manure as feedstock to produce biochars could have a number of potential benefits such as inactivation of microbial pathogens and degradation of antibiotics in manure from the thermal treatment (i.e. 300 to 700 °C). Then the manure - derived biochars could be either directly applied to the land or mixed with manures before spreading to reduce the mobility and bioavailability of 12 antibiotics. To develop better strategies of biochar soil amendment for antibiotics sequestration, it is important to understand the behaviors and underlying mechanisms of antibiotics sorption by manure - derived biochars. Therefore, the aim of this study was to assess the potential of biochar soil amendment for in - situ sequestration of antibiotics in agroecosystems through sorption studies. Lincomycin was chosen as a model compound to in vestigate the sorption of antibiotics by manure - derived biochars from water, due to its prevalence, high mobility, and limited degradation in the environment. The sorption kinetics and quasi - equilibrium sorption of lincomycin were evaluated to elucidate th e underlying lincomycin sorption mechanisms by biochars. Biochar samples used in this study were produced by slow pyrolysis of oven - dried manure feedstock at a temperature of 600 °C (Daisy Reactor, Best Energies Inc., Cashton, WI, USA). A detailed description of the biochar production can be found in Enders et al. 28 and Rajkovich et al. 71 Th e produced biochars were ground and passed through sieves to obtain the fractions of 150 850, 75 150, and < 75 m, and then stored in glass vials prior to use. Hereafter these biochars were designated according to feedstock type and pyrolysis temperature a s BM600 (bull manure with sawdust), DM600 (dairy manure with rice hulls), PM600 (poultry manure with sawdust), and AM600 (anaerobically digested dairy manure). The four manure - derived biochars have previously been well characterized . 28, 71 Volatile matter, fixed carbon, and ash content of biochar samples were determined by the modified ASTM D1762 - 84 method. Carbon and nitrogen content were determined by a PDZ Europa ANCA - GSL elemental analyzer interfaced to a PDZ Eu ropa 20 20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK). Hydrogen content was determined by a Hekatech HT Oxygen Analyzer 13 interfaced to a PDZ Europa 20 20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK). Oxygen content was calcul ated by subtracting C, N, H, and ash content from total mass. Cation exchange capacity (CEC) and exchangeable cation concentrations were determined by the ammonium acetate exchange method. More detailed biochar characterization can be found in Enders et al . 28 and Rajkovich et al. 71 Additionally, specific surface area (SSA) of biochar samples was determined from 5 - point CO 2 adsorption isotherms using the Brunauer Emmett Teller (BET) method by a Micromeritics Tristar 3020 analyzer (Micromeritics, USA) at Pacific Surface Science Inc. (Port Hueneme, CA). Zeta potential of the biochars was measured by Malvern Zetasizer Nano - ZS equipped with a MPT - 2 autoti trator (Malvern Instruments, Worcestershire, UK). The isoelectric point (pH IEP ) of biochars was determined by measuring the zeta potential of biochars as a function of solution pH . To generate biochar colloid suspension for isoelectric point (pH IEP ) measur ement, 10 mg biochar sonicated for 30 min. After sonication, top 10 mL of biochar suspension was withdrawn and then titrated with 0.1 M HCl or NaOH titrant fro m pH 10 to 2 using the autotitrator, and the corresponding zeta potential at each pH was measured by the Zetasizer Nano - ZS. The pH IEP value was determined at the pH where the zeta potential is zero. Additionally, zeta potential for biochar suspensions of 1 - day or 180 - day water exposure was also determined by the zetasizer. In order to monitor the change of surface properties and surface morphology of biochar particles, zeta potential measurement and scanning electron microscopy (SEM, JEOL JSM - 7500F, Japan) were performed for biochar samples of 75 - day and 180 - day water exposure. 14 - Aldrich. The chem ical structure and properties of lincomycin are summarized in Table 2. 1. Deionized (DI) water was used for all the solution preparations. Amber borosilicate glass vials covered with aluminum foils were used in the experiments to prevent photodegradation of lincomycin. Batch sorption experiments were conducted in duplicate at room temperature (23 ± 1 °C). Prior to the sorption experiments, lincomycin solution was pre - adjusted to pH of 3 or 10 by 0.1 M HCl or NaOH. Solution pH was not controlled during the so rption experiments, but the final solution pH was recorded. To prevent competitive effect of other salts during lincomycin sorption, no electrolyte was added to control ionic strength unless otherwise noted. The biochar fraction of - water ratio of 1 g L 1 were used, unless mentioned otherwise, to achieve the removal efficiency of lincomycin at about 20% after two - day equilibration in order to better study sorption kinetics over a longer period. More details of the experimental protoco ls are given below. Table 2.1. Chemical and physical properties of lincomycin Properties Lincomycin Molecular structure Molecular Formula § C 18 H 34 N 2 O 6 S Molecular weight § 406.54 pKa § 7.6 log K ow § 0.20 Water solubility § 927 mg L 1 at 25 °C pKa: dissociation constant, K ow : octanol/water partition coefficient; Data from ChemSpider ( http://www.chemspider.com/ ); § Data from TOXNET ( http://www.toxnet.nlm.nih.gov / ) 15 Sorption kinetics experiments were performed to evaluate kinetic sorption rates and the equilibration time required for the subsequent sorption isotherm experiments. Additionally, sorption kinetics can be used to probe underlying sorp tion mechanisms , 38 and are highly complementary to equilibrium sorption isotherm data. Eight mg of each biochar with particle size of 75 150 m were added into amber borosilicate glass vials containing 8 mL lincomycin of 1000 g L 1 at pH 10. The vials were placed on an end - over - end shaker (Glas - Col, USA) and shaken at 30 rpm for duration of 1 hour to 180 days. At pre - determined times, a sub - se t of the sample vials were withdrawn, and the suspensions in the vials were filtered through a 0.45 - µm syringe filter with mixed cellulose esters membrane (Millipore, USA). During filtration, the first 1 mL of filtrate was discarded and the following 1 mL of filtrate was collected so as to avoid the loss of lincomycin to the filter. Lincomycin concentrations in the filtrate were determined by a Shimadzu Prominence high - performance liquid chromatograph coupled to an Applied Biosystems Sciex 3200 triple quadr upole mass spectrometer (LC - MS/MS) . More details of the LC - MS/MS analytical procedure are given below. The data from the biochar - free control experiments indicated a negligible loss of lincomycin via degradation throughout the experiments ( Figure 2. 1). In addition, the filtrates in the 180 - day samples were also examined using the precursor ion scan mode by LC - MS/MS. Based on Calza et al. (2012), 72 no degradation candidates of lincomycin were detected ( Figure 2. 2), suggesting that the disappearance of lincomycin from the aqueous phase was caused by sorption onto biochars instead of degradation. Therefore, the sorbed lincomycin concentration on the biochars was determined by the difference between initial and final lincomycin concentrations in the aqueous phase. 16 Figure 2.1. Lincomycin concentration versus time for lincomycin sorption kinetics experiments. Control was the biochar - free lincomycin solution. 17 Figure 2.2. Precur sor ion scan spectra of (a) Control (freshly prepared), (b) Control (180 days), (c) BM600 (180 days), (d) DM600 (180 days), (e) AM600 (180 days), and (f) PM600 (180days). Control was the biochar - free lincomycin solution. No degradation candidates of lincom ycin was detected in long - term kinetics samples (b, d, f). 18 We investigated the effects of biochar particle size and solid - water ratio to determine desired experimental conditions for the sorption isot herm experiments. To examine the effect of solid - water ratio, 4, 8, 40, and 80 mg of biochar samples were added to 8 mL lincomycin of 1000 µg L 1 at pH 10 to achieve the solid - water ratio of 0.5, 1, 5, and 10 g L 1 . Additionally, to examine the effect of b m were mixed with 8 mL lincomycin of 1000 µg L 1 at pH 10. The suspensions were then shaken at 30 rpm for 2 days, filtered, and the lincomycin concentration in t he filtrate determined. The other sorption experimental procedures were identical to the protocols previously described. We investigated lincomycin sorption mechanisms for the tested biochars through manipulating t he interactions between lincomycin and biochar surfaces by changing solution pH and ionic strength. To determine the sorption isotherm, 8 mg of biochars were mixed with 8 mL lincomycin working solution at initial concentration of 100, 250, 500, 750, or 100 0 g L 1 in the absence of NaCl addition. Conversely, to examine ionic strength effects, 8 mg of biochars were mixed with 8 mL of lincomycin working solution of 1000 g L 1 with the addition of 0, 0.01, 0.05, or 0.1 M NaCl. These experiments were conducted at initial solution pH of 3 and 10. Due to the alkalinity of the biochar samples, the final pH often increased to about 6.7 ± 0.5 for the lower pH tests, and remained unchanged for the higher pH tests (about 10.0 ± 0.2). The other procedures were similar to those previously described. 19 Lincomycin concentrations in the solution were determined by a Shimadzu Prominence high - performance liquid chromatograph coupled to an Applied Biosystems Sciex 3200 triple quadrupole mass spectro meter (LC - was used. The mobile phase consisted of water (A) and 1:1 (v/v) acetonitrile - methanol mixture (B) with A and B both containing 0.3% formic acid. Gradient conditions were 0 % to 40 % B in 0 to 1 minute, 40 % to 70% B in 1 to 2 minutes, 70 % 80 % B in 2 to 3 minutes, 80 % to 100 % B in 3 to 3.5 minutes, and held for 0.5 minutes at a flow rate of 0.35 mL/min. Injection volume was tion (ESI) and positive ion mode. Lincomycin was detected and quantified using a multiple reaction monitoring mode with a precursor/product transition of 407.2/126.2. The retention time and instrument detection limit of lincomycin was 2.37 min and 0.2 pg. The linear forms of pseudo - first - order (Eq. 2. 1), pseudo - second - order (Eq. 2 .2 ), and intraparticle diffusion (Eq. 2. 3) kinetic model s 73, 74 given below were used to fit the experimental data: ( 2. 1) ( 2. 2) ( 2. 3) where q e ( g g 1 ) is the sorbed lincomycin concentration in the solid phase at equilibrium, q t ( g g 1 ) is the sorbed lincomycin concentration at time t , k 1 (day 1 ) is the pseudo - first - order rate constant, k 2 (g g 1 day 1 ) is the pseudo - second - order rate constant, k i ( g g 1 day 0.5 ) is the intraparticle diffusion rate constant, and C ( g g 1 ) reflects the boundary lay er effect. 20 The Langmuir (Eq. 2. 4) and Freundlich (Eq. 2. 5) isotherm models below were fitted to the experimental data: ( 2. 4) ( 2. 5) where C e ( g L 1 ) i s the equilibrium lincomycin concentration in the solution, q max ( g g 1 ) is the maximum lincomycin sorption capacity, K L (L g 1 ) is the Langmuir constant, and K F ( g (1 1/n) g 1 L 1/n ) and 1/ n are the Freundlich constants. The goodness of fit to the model s was evaluated by root mean squared error (RMSE) and coefficient of determination (R 2 ). Physicochemical properties of four manure - derived biochars are shown in Table 2. 2 BM600, DM600, and AM60 0 had high carbon contents (62.8 76.0%), while PM600 had a relatively lower carbon content (28.7%). Conversely, BM600, DM600, and AM600 had relatively lower ash content (10.6 18.8%), while PM600 had a greater ash content (55.8%). The low atomic ratio of H/C, O/C, and (O+N)/C indicate tha t the biochars were highly carbonized, less hydrophilic, and low in polar surface functional group content . 38 The specific surface area (SSA) of BM600, DM600, and AM600 (183 237 m 2 g 1 ) was higher than that of PM600 (47 m 2 g 1 ), and was positively related to the carbon content (R 2 = 0.996), suggesting that the CO 2 - SSA of these biochars was mainly a result of the carbon matrix . 30 Zeta potential measurements indicate that the manure - derived biochars carried net negative surface charge within a wide pH range ( Figure 2. 3). The negative zeta potential remained nearly constant between pH 6 and 10. Within this pH range, the zeta potential of BM600, DM600, and 21 mV). Below pH 6, the zeta potential became progressively less negative with decreasing pH, and the pH IEP was found approximately at 1.9 2.2. Finally, a complex porous structure of the biochars was revealed by the SEM images, and the pore size spanned widely from nanometer level to micrometer level ( Figure 2. 4 ). The macroporous structure was likely preserved from the original feedstock structure, and the nanoporous structure was possibly formed during pyrolysis . 24 Table 2.2. Selected physical and chemical properties of manure - derived biochars Properties BM600 DM600 AM600 PM600 Proximate analyses (%) Volatile matter 30.0 30.7 39.4 44.2 Fixed carbon 59.4 56.6 41.7 0 Ash 10.6 12.6 18.8 55.8 Elemental analyses (%) C 76.0 75.2 62.8 28.7 H 1.8 2.0 nd 0.4 O 14.3 11.6 nd 14.3 N 0.80 1.3 2.2 0.9 H/C 0.28 0.32 nd 0.17 O/C 0.14 0.12 nd 0.37 (O+N)/C 0.15 0.13 nd 0.40 CEC (mmolc kg 1 ) 336 97 151 59 Exchangeable cation (mmolc kg 1 ) Ca 88.3 90.2 291 1098 Mg 67.7 15.6 164 126 K 464 60.5 413 464 Na 54.4 62.8 257 71.8 SSA (m 2 g 1 ) nd nd nd nd 237 221 187 47 250 229 187 37 pH IEP 1.9 2.0 2.0 2.2 Zeta potential (mV) 1 - day 60.4 ± 1.5 64.1 ± 0.4 55.6 ± 3.5 36.3 ± 2.5 180 - day 61.5 ± 3.1 60.8 ± 0.9 56.4 ± 1.2 35.0 ± 1.0 H/C = atomi c ratio of H to C, O/C = atomic ratio of O to C, (O+N)/C = atomic ratio of the sum of O and N to C, CEC = cation exchange capacity, SSA = specific surface area, pH IEP = isoelectric point, Zeta potential was measured at pH 10, nd = not determined. Data fr om Enders et al. 28 and Rajkovich et al. 71 22 Figure 2.3. Zeta potential of manure - derived biochars as a function of solution pH. 23 Figure 2.4. SEM images of manure - derived biochars: (a) BM600, (b) DM600, (c) AM600, and (d) PM600, prepared from biochar suspensions of 1 - day water exposure. 24 Sorption of lincomycin by the biochars was characterized as a two - phase sorption kinetics ( Figure 2. 5 ). Although the physicochemical properties varied greatly among the four biochars, the sorption kinetics showed similar patterns. In the initial sorption phase, the sorbed lincomycin concentration on the biochars increased rapidly duri ng the first several hours of the first day, and then gradually reached a first - stage sorption plateau after 2 days ( Figure 2.5 a). In the longer - term sorption phase, the sorbed lincomycin concentration continuously increased and did not reach equilibrium b y the end of the experimental period (i.e., 180 days) ( Figure 2 .5 b). Typically, the initial fast sorption phase primarily results from surface adsorption between sorbate and sorbent surfaces that often occurs almost instantaneously or at a rapid rate, wher eas the second slow sorption phase was caused by diffusion of sorbate into sorbent pore structures that occurs at a much slower rate (i.e., pore - diffusion process) . 32 Since the biochars have abundant surface sorpti on sites and pore structures, we therefore believed that lincomycin sorption by the biochars was governed by both processes, fast surface adsorption followed by slow pore diffusion. In addition, only 25 34 % of the applied lincomycin was removed from solution after 2 days, but 92 99% of that was removed after 180 days. This result indicated the large lincomycin sequestration potential of biochars and the predominant role of the pore diffusion process in lincomycin sorption over the long - term. Indeed, the intraparticle diffusion model fitted the sorption kinetic data well, whereas the pseudo - first - order and pseudo - second - order kinetic models were less satisfactory in fitting the sorption kinetics indicated by greater RMSE values ( Table 2. 3 ). This kind of two - phase sorption kinetics is consistent with the sorption of other organic compounds by biochars . 38, 75 For example, Kasozi et al. (2010) studied the sorption of catechol on biochars and showed a similar sorption 25 kinetics trend, in which around 59% of total sorption occurred within the first few days and then reached sorption equilibrium after 14 days. Since lincomycin sorption continued to increase over 180 days, it is important to evaluate the potential change of surface properties and surface morphology of biochar particles due to long - term water exposure. There was no significant difference in zeta potentials of biochars upon exposure to water for 1 day and 180 days ( Table 2. 2 ), implying surface functional groups of biochar particles on average did not change significantly during the length of the experiment. However, a close examination of biochar SEM images revealed that biochar surfaces became more eroded and cracked over time ( Figure 2. 6 ). The results implied that fine biochar fragments, minerals such as silica, and soluble elements were potentially detached or dissolved from biochar particle surface after long - term water exposure . 76 - 78 In addition, biochar surface roughness might have increased with subsequent changes to its pore structure. Based on the kinetic sorption results, the short - term (i.e., 2 - day) sorption experiments could be used to characterize lincomycin adsorption to the external surfaces of biochars, whereas the long - term (i.e., 180 - day) sorption experiments could be used to characterize lincomycin sorption to biochar interior spaces only accessible via pore diffusion. Because the underlying mechanisms during short - term surface adsorption have not been previously elucidated, two - day sorption experiments were performed to better understand interactions between lincomycin and biochar external surfaces. 26 Figure 2.5. (a) Short - term and (b) long - term linco mycin sorption kinetics on manure - derived biochars. The solid lines were fitted with the intraparticle diffusion model. 27 Table 2.3. Fitted parameters of pseudo - first - order, pseudo - second - order, and intraparticle diffusion models for long - term sorption kin etics of lincomycin on manure - derived biochars. Biochar Pseudo - first - order q e k 1 R 2 RMSE 1 ) (day 1 ) BM600 937 3.11 × 10 - 2 0.837 175 DM600 855 3.37 × 10 - 2 0.951 187 AM600 851 3.13 × 10 - 2 0.867 203 PM600 860 3.07 × 10 - 2 0.837 197 Pseudo - sec ond - order q e k 2 R 2 RMSE 1 ) 1 day 1 ) BM600 856 9.91 × 10 - 5 0.916 144 DM600 990 1.46 × 10 - 4 0.987 124 AM600 907 1.40 × 10 - 4 0.959 142 PM600 852 1.13 × 10 - 4 0.927 169 Intraparticle diffusion C k i R 2 RMSE 1 ) 0.5 day 0.5 ) BM600 160 52.3 0.973 34.0 DM600 212 66.2 0.965 49.7 AM600 228 54.6 0.963 42.1 PM600 216 47.0 0.972 31.2 28 Figure. 2.6. SEM images of manure - derived biochars after 1 - day and 180 - day water exposure: (a, b) BM600, (c, d) DM600, (e, f) AM600, and (g, h) PM600. 29 Biochar particle size and solid - water ratio significantly affected lincomycin sorption processes. As shown in Figure 2. 7 m to < 75 1 g 1 . The increased 2 - day sorption with smaller biochar particle sizes was likely due to increased extern al biochar surfaces easily accessible by lincomycin at smaller particle sizes. As the SSA values for biochars of larger and smaller particle size were similar ( Table 2. 2 ), the BET - SSA might not be an accurate index for biochar external surface areas. As ex pected, with increasing solid - 1 ( Figure 2. 7 b). These results are in accordance with t he sorption of other organic contaminants by carbonaceous materials including biochars . 79 - 81 For example, Zheng et al. (2010) reported that the sorption of atrazine and simazine on biochars were greater and faster at smaller particle size. In addition, they also observed increased removal efficiency and decreased sorption capacity of biochars for both pesticides with increasing solid - water ratio . 80 30 Figure. 2.7. Sorption of lincomycin on manure - derived biochars with varying (a) particle sizes and (b) solid - water ratios . 31 Two - day sorption isotherms of lincomycin on the biochars at two different pH values are shown in Figure 2. 8 . A no nlinear concave - downward (L - type) shape was observed for all sorption isotherms. Since surface adsorption is considered the dominant process within two days, a nonlinear sorption isotherm was expected because the availability of active surface sorption sit es were limited and thus the sorption became progressively suppressed with increasing lincomycin loading. The fitted isotherm parameters for the Langmuir and Freundlich models are shown in Table 2. 4 . The isotherm data were better fitted to the Langmuir mod el, supported by the lower RMSE values, than to the Freundlich model. However, given the heterogeneous nature of biochar surfaces, the Langmuir model can only be considered as an empirical fitting equation carrying no mechanistic meaning. In fact, the Lang muir model has been frequently used in studying sorption of environmental contaminants by natural geosorbents because it provides the empirical maximum sorption capacities that allow for evaluating the contaminant sequestration potential of the natural geo sorbents such as soils . 82 Table 2.4. Fitted parameters of Langmuir and Freundlich equations for lincomycin sorption on manure - derived biochars. Biochar Langmuir Freundlich q max g g - 1 ) K L (L g - 1 ) R 2 RMSE n 1 K F ( g (1 1/n) g 1 L 1/n ) R 2 RMSE BM600 pH 6.6 555 1.29 × 10 - 2 0.99 15 0.47 28.5 0.98 34 BM600 pH 9.9 299 7.87 × 10 - 3 1.00 5.2 0.44 15.4 0.96 18 DM600 pH 6.5 605 1.40 × 10 - 2 0.99 19 0.48 30.7 0.97 38 DM600 pH 10.0 372 5.6 8 × 10 - 3 0.97 17 0.48 13.4 0.97 13 AM600 pH 6.9 697 6.18 × 10 - 3 1.00 9.3 0.61 13.7 0.99 29 AM600 pH 10.0 436 4.58 × 10 - 3 0.97 18 0.55 10.1 0.95 19 PM600 pH 7.3 576 2.68 × 10 - 3 0.96 15 0.71 4.29 0.96 29 PM600 pH 10.4 424 3.41 × 10 - 3 0.98 12 0.59 6.83 0. 98 11 32 The dissociation constant (pKa) of lincomycin is 7.6 ( Table 2. 1). Hence, the lincomycin in aqueous solution would exist predominantly as cationic species at pH values much lower than 7.6 and as neutral species at pH much greater than 7.6. As shown in Figure 2. 8 , the lincomycin sorption of all four biochars was greater at pH 6.0 7.3 than that at pH 9.9 10.4. As biochar particles were negatively charged at these two pH levels ( Figure 2. 3 ), the enhanced lincomycin sorption at lower pH likely resulted f rom electrostatic attraction between positively charged lincomycin and negatively charged biochar surfaces , 35 similar to the observations for the sorption of tetracycline . 43 To further investigate the possibility of electrostatic interactions (i.e., cation exchange and cation - different ionic strength at two pH levels, i.e., below and above 7.6. The effects of solution pH and ionic strength were interactive as shown in Figure 2. 9. With increasing ionic strength, the lincomycin sorption decreased by 10.5 23.3% at lower solution pH ( 6.1 7.5 ), but remained essentially unchanged at higher s olution pH ( 9.9 10.3) . Likely, sorption competition occurred between the background electrolytes of Na + and positively charged lincomycin at lower solution pH (pH < pKa); conversely, this competition effect would not occur between Na + and neutral species o f lincomycin at higher solution pH (pH >> pKa). Although the four biochars had the same trend for pH and ionic strength effects, the lincomycin sorption capacity of PM600 was lower. This may due to the less negative surface charge of PM600 ( Figure 2. 3 ) and the less cationic fraction of lincomycin at the final solution pH (7.3 or 7.5) of PM600 close to the pKa (7.6). The abovementioned observations suggest that electrostatic interaction was involved in lincomycin sorption on biochar when solution pH was bel ow the pKa of lincomycin. Nonetheless, an appreciable amount of lincomycin could still be adsorbed on the biochars at high solution pH. 33 The Langmuir maximum sorption capacity ( q max ) at pH 9.9 10.4 was 54 74% of that at pH 6.5 7.3 for the four biochars ( Tab le 2. 5 ). For the higher pH at which lincomycin exists as neutral species, electrostatic interaction was unlikely to play a role. Therefore, non - electrostatic interactions were also involved in lincomycin sorption on biochars. Some of the non - electrostatic acceptor (EDA) interaction, hydrogen bonding, and van der Waals forces . 41, 43, 83 Due to the high water solubility and low log K ow value of lincomycin ( Table 2. 1), the hydrophobic partition should not be significant in this study. Moreover - electron - in and the graphite - like biochar surface should not exist. Hence, considering the functional groups, molecular size, and molecular structure of lincomycin, it seems reasonable to infer that the non - electrostatic interactions may include hydrogen bonding an d van der Waals forces. Nonetheless, the proposed mechanisms need to be validated by direct evidences in future studies. 34 Figure. 2.8. Observed and fitted sorption isotherms of lincomycin on biochars at solution pH 6.0 7.3 and pH 9.9 10.4. The solid li nes were fitted with the Langmuir model, and the dashed lines with the Freundlich model. 35 Figure. 2.9. Sorption of lincomycin on manure - derived biochars at solution pH of 6.1 7.5 and 10 10.3 under varying ionic strength. 36 These findings ha ve interesting implications in the application of biochars for sequestration of antibiotics in soils. While natural soils rarely have pH values at 10, the results of lincomycin sorption at higher pH was useful to estimating the contribution of non - electros tatic sorption expected to be operative at all pH ranges. As the electrostatic interaction at lower pH is prone to competition and inhibition from other cations present in soil water , 84, 85 non - electrostatic sorpti on appears to be a more useful index of antibiotics sequestration capacity of biochars, independent of solution pH and ionic strength effect. Moreover, given that lincomycin sorption only decreased by 10.5 23.3 % at the maximum when ionic strength increase d to 0.1 M NaCl ( Figure 2. 9 ) representing the higher end of typical ionic strength in soil water (2 ×10 4 0.18 M) , 86 the competition from monovalent electrolytes in soil water would be limited. It is noted that the effect of divalent cations such as Ca 2+ and Mg 2+ should be further studied. Nonetheless, the presence of Ca 2+ and Mg 2+ in the background solution is expected due to dissolution from the unwashed biochars, as suggested by the exchangeable cation concentrations of the biochars ( Table 2. 2 ). Competition with these divalent cations should be manifested to certa in extent by the sorption results at lower pH. In any case, the decrease in lincomycin sorption due to potential competition with other cations should be less than 26 46% for the four biochars, assuming an unlikely case of complete suppression of electrost atic interaction. The remaining lincomycin sorption would be due to the non - electrostatic interactions such as hydrogen bonding and van der Waals force. Finally, the above discussion was based on the short - term sorption results, excluding the long - term por e diffusion. Over the long - term, the pore diffusion could result in 2.8 3.8 times greater lincomycin sorption than that over the short - term ( Figure 2. 5 ). We hypothesize that the pore diffusion would be minimally influenced by solution pH and ionic composit ion of soil water. 37 Nonetheless, future studies should examine the potential effects of organic molecules competing for the filling of biochar pores. It was noted that biochars had lower lincomycin sorption than humic acids and smectite clays . 84, 87 However, lincomycin sorption to humic acids and smectite clays could be severely affected by solution pH and ionic composition, and pore diffusion might not be important , 84, 87 Mo reover, biochars had much greater lincomycin sorption than whole soils . 85 Therefore, manure - derived biochars may be attractive geosorbents used for in - situ long - term sequestration of antibiotics via soil amendment . After applied to agricultural soils, biochars may provide not only quick immobilization of antibiotics in the short - term by surface adsorption, but also a lasting antibiotics sequestration over the long - term through pore diffusion, thus decreasing bioava ilability and mobility of antibiotics in agroecosystems. 38 CHAPTER III QUANTIFICATION AND CHARACTERIZATION OF DISSOLVED ORGANIC CARBON FROM BIOCHARS 39 Dissolved organic carbon (DOC) in biochars is critical to carbon (C) dynamics and contaminant tran sport in soils. However, a robust and easy method to extract and determine the DOC concentrations in biochars has yet to be developed. This study quantified and characterized the DOC extracted by deionized water, 0.1 M HCl, and 0.1 M NaOH (named water - extr ac t able DOC (WEOC), acid - extrac t able DOC (AEOC), and base - extrac t able DOC (BEOC), respectively) from 46 biochars produced from diverse feedstocks and pyrolysis conditions. BEOC concentrations were the highest (2.3 139 mg - C/g - biochar), followed by WEOC (0.5 40 mg - C/g - biochar) and AEOC (0.2 23 mg - C/g - biochar). In general, fast - pyrolysis biochars had higher DOC concentrations than slow - pyrolysis biochars. DOC concentrations in slow - pyrolysis biochars decreased exponentially with increasing pyrolysis temperatur e from 300 to 600 °C. As revealed by solid - state 13 C NMR, biochar - DOC had abundant small fused - ring aromatics, aliphatic C, and carboxyl C. Biochar - DOC included an acid - precipitated (AP) fraction of higher molecular weight and aromaticity and an acid - solub le (AS) fraction of lower molecular weight and aromaticity. BEOC generally had a greater AP fraction than WEOC and AEOC. Both molecular weight and aromaticity of AEOC and BEOC differed from that of the more environmentally - relevant WEOC, suggesting that th e acid - and base/alkali - extraction may not produce the DOC released under realistic soil conditions. Finally, a quick, easy and robust UV - vis spectrometric method was developed to measure the WEOC concentrations in diverse biochar samples ( R 2 = 0.96 and n = 46). 40 Biochars are carbonaceous porous materials co - produced with syngas and bio - oil from pyrolysis of biomass, and have been promoted as soil amendments for agronomic and environmental benefits. 24, 88 - 91 The potential benefits of soil biochar amendment include increased soil carbon ( C) storage, improved soil characteristics (e.g., improving soil str ucture, reducing bulk density, and enhancing water and nutrient retention), decreased greenhouse gas emission, and in - situ immobilization of contaminants such as excess nutrients, organic pollutants, and trace metals. 29, 33, 91 - 93 During the last several years, dissolved organic C (DOC) in biochars has sparked strong research interest, 51 - 56 because it plays an important role in controlling biochar persistence and mobility, 56, 60, 94, 95 contaminant fate and transport, 34, 57, 96 microbial activities, 55, 58 and plant growth 97 in agroecosystems. Once applied in the field, biochars could release DOC into soil water, and directly alter physicochemical properties of soil DOC. 98, 99 The released DOC from the biochars (hereafter termed as biochar - DOC) could be rapidly transported from soils into receiving surface and ground waters via surface runoff and leaching, 61, 100, 101 thus contributing to soil C loss and the transport of DOC - associated contaminants. More broadly, the release of DOC from pyrogenic C contributes approximately 10% of total DOC in surface water globally. 95 Furthermore, the DOC fraction in the biochars is labile and more susceptible to photo - and bio - degradation than bulk biochars. 56, 60 Thus, both qualitative and quantitative characteristics of biochar - DOC are needed for better assessing the qual ities of biochars and their impact on agroecosystems. DOC is often operationally defined as the organic C fraction smaller than the pores of filter membranes (e.g., 0.45 or 0.75 µm). 94 The biochar - DOC thus includes both truly dissolved molecules and sub - micron sized biochar particles. 54, 100 - 102 Water - soluble organic compounds can 41 be formed by re - condensation and entrapment of volatile organic compounds into the biochar pore structure during pyrolysis, which can be later rele ased as DOC. 103 - 105 In addition, sub - micron biochar particles may initially be present or later produced from physicochemical disintegration of bulk biochars. 54, 102 Biochar - DOC is often extracted by either water or strong alkaline (i.e., sodium hydroxide (NaOH) or potassium hydroxide (KOH)) solutions. 51, 52, 54, 55 The alkaline extraction is adapted from the method of organic matter extraction from soils. 106 - 108 The extracted soil organic matter (SOM) has been traditionally perceived as primarily humic substances, i.e., s t able macromolecules formed by a humification process that are resistant to microbial degradation. However, it is incre asingly recognized that the humification process may not actually occur in soils, and SOM is primarily formed through microbial decomposition, biosynthesis, as well as physical protection by sorption on mineral surfaces and sequestration in soil aggregates . 108 - 110 Furthermore, the alkali - extrac t able SOM may not truly represent organic matter released into soil water because natural soils rarely reach the extreme alkaline and high pH conditions used in the alkaline extraction. 108 Similarly, the alkal i - extrac t able biochar - DOC may not reflect the amount and properties of DOC released into soil water from the added biochars. Indeed, Chen et al. 111 found that the amount of may pr oduce more representative DOC released from biochars under natural soil conditions. 108 Additionally, acid washing is commonly used for de - ashing biochars before analysis 30, 112 and would presumably extract certain fractions of biochar - DOC. However, studies on the difference in the quantity and characteristics of biochar - DOC extracted by water, strong acid solution, and strong base solution are rare. 42 A numbe r of recent studies have characterized biochar - DOC via advanced spectroscopic and mass spectrometry techniques. About 300 2400 unique molecular formulas could be assigned in the spectra of the biochar - DOC (200 800 m/z ) detected by Fourier transform ion cyc lotron resonance mass spectrometry (FTICR - MS). 55 Many small organic compounds in the mass range of 45 500 m/z belonged to phenolic compounds, acids, and bio - oil - like compounds, as revealed by 2D gas chromatography coupled with time of flight mass spectrometer (GC×GC - TOFMS). 55 Qu et al. 54 reported that biochar - DOC was composed primaril y of small aromatic clusters rich in carboxyl functional groups, based on Fourier transform infrared spectroscopy (FT - IR) and solid - state 13 C nuclear magnetic resonance (NMR). Using liquid chromatography - organic C detection (LC - OCD) analysis 51 and fluorescence excitation - emission spectrophotometry with parallel factor analysis (EEM - PARAFAC), 52, 53 biochar - DOC could be characterized by several components (e.g., low - molecular - weight acids and neutrals, and high - molecular - weight compounds) differing in their individual mean molecular weight ( M w ) and fluorescence features. Becaus e these components can have distinct environmental persistence and mobility, their proportion may be used to characterize the biochar - DOC. Many of the aforementioned methods are costly and not routinely available in many laboratories, thus hampering their wide use in quality assessment during biochar production and application. Therefore, developing a quick, easy and robust method for characterizing and quantifying the biochar - DOC is critically needed. Ultraviolet visible (UV - vis) absorption spectroscopy is commonly available and has been successfully used to characterize the biochar - DOC. 53, 56 It was thus selected for developing the new method here. Therefore, this study aimed to: (1) investigate whether the base/a lkali - or acid - extrac t able DOC from biochars is different with the more environmentally - relevant water - extrac t able DOC in 43 terms of their quantities and qualities; and (2) develop a quick, easy and robust method for quantifying the biochar - DOC. To do so, we thoroughly quantify and characterize the DOC extracted with deionized (DI) water, 0.1 M hydrochloric acid (HCl), and 0.1 M NaOH from 46 biochars pyrolyzed from diverse feedstocks and pyrolysis conditions. As the quantities and qualities of biochar - DOC hig hly depend on pyrolysis temperature, 51 - 53, 55, 113 and feedstock type, 51, 52, 113 the relative importance of these factors in determining the biochar - DOC concentrations was also explored here. Additionally, advanced solid - state 13 C NMR spectroscopy was used to provide detailed quantitative structural information of DOC and the structure change of bulk biochars after the extraction treatment. Finally, a quick, easy and robust method was developed to quantify the biochar - DOC by only using the commonly available UV - vis absorption spectroscopy. Details on the feedstocks and production conditions of 46 biochars used in this study are provided in Tab le 3. 1. 28, 71, 114 Briefly, the feedstocks were: (1) animal manures including bull manure with sawdust bedding (BM), dairy manure with rice hulls bedding (DM), poultry manure with sawdust bedding (PM), raw dairy ma nure with sawdust bedding (RDM), digested dairy manure (DDM), composted digested dairy manure (CDM), and composted digested dairy manure mixed with woodchips (CDMW) (note that RDM, DDM, CDM, and CDMW were from the same manure source with various pretreatme nts prior to pyrolysis); (2) woody biomass including oak wood (OW), pine wood (PW), mixed woodchips (WC), mixed hardwood (HW), mixed softwood (SW), Chinese bamboo (CB), and Brazilian pepperwood (BP); (3) herbaceous residues including corn stover (CS), soyb ean (SB), switchgrass (SG), sugarcane bagasse (BG), and yard leaves (YL); and (4) urban wastes including food waste (FW) and paper mill waste (PMW). The feedstocks 44 were pyrolyzed via fast pyrolysis at 500 °C or slow pyrolysis at 300 600 °C. Here fast pyrol ysis had a residence time of < 30 s, whereas slow pyrolysis had a residence time > 15 min. The produced biochars were ground and passed through a 74 - m sieve, and stored in glass vials prior to use. This particle size fraction was selected to represent finer biochars that may have greater potential to release DOC once applied to soils. Hereafter, the biochar samples were named by feedstock and pyrolysi s temperature ( e.g., BM300 for bull manure pyrolyzed at 300 °C ) . These selected different biochars have previously been characterized, and their sel ected physicochemical properties are summarized in Table 3. 2. 28, 71, 114 45 Table 3.1. Feedstock and production details of biochar samples. Biochar ID Feedstock full name and origin Pyrolysis temp. (°C) Pyrolysis co ndition SB500 Soybean. Collected in Pennsylvania. 500 Fast pyrolysis in a fluidized bed reactor under N 2 atmosphere. The residence time was 0.11 second. 115 - 117 SG500 Switchgrass. Collected in Pennsylvania. 500 HW500 Mixed hardwood. Collected from Dynamotive (Canada). 500 Fast pyrolysis in a bubbling fluidized bed reactor (Dynamotive, Canada). The residence time was less than 5 seconds. 28 SW500 Mixed softwood. Collected from Dynamotive (Canada). 500 SG(2)500 Switchgrass. Collected from Texas A&M University (College Station, TX) 500 Fast pyrolysis in an auger reactor. The residence time was 15 30 seconds. 28 PW(2)500 Pine wood. Collected from Texas A&M University (College Station, TX) 500 BM300, BM400, BM500, BM600 Bull manure with sawdust bedding. Collected in Wisconsin 300, 400, 500, 600 Slow pyrolysis in the Daisy Reacto r (Best Energies, Cashton, WI) under N 2 atmosphere. The heating rate was less than 10 °C per minute and the residence time was 15 20 minutes. 28, 71 DM300, DM400, DM600 Dairy manure with rice husks bedding. Collect ed in Wisconsin 300, 400, 600 PM300, PM400, PM500, PM600 Poultry manure with sawdust bedding. Collected in Wisconsin 300, 400, 500, 600 RDM500 Raw dairy manure. Collected from AA Dairy (Candor, NY). Raw dairy manure (with sawdust bedding) did not rece ive any anaerobic digestion or composting pretreatment prior to pyrolysis. 500 DDM500, DDM600 Digested dairy manure. Collected from AA Dairy (Candor, NY). The dairy manure with sawdust bedding was anaerobically digested, and the screw - press - dried solid m anure product was collected for pyrolysis. 500, 600 CDM500 Composted digested dairy manure. Collected from AA Dairy (Candor, NY). The above anaerobically digested, screw - press - dried solid manure product was further composted and then collected for pyroly sis. 500 CDMW500 Composted digested dairy manure mixed with woodchips. The composted digested dairy manure (CDM) was mixed with woodchips in 1:1 ratio just prior to pyrolysis. 500 OW300, OW400, OW600 Oak wood. Collected in Wisconsin 300,400, 600 46 Ta ble 3.1 Biochar ID Feedstock full name and origin Pyrolysis temp. (°C) Pyrolysis condition PW300, PW400, PW600 Pine wood. Collected in Wisconsin 300,400, 600 Slow pyrolysis in the Daisy Reactor (Best Energies, Cashton, WI) under N 2 atmosphere. The heating rate was less than 10 °C per minute and the residence time was 15 20 minutes. 28, 71 WC500 Mixed woodchips. Collected from Cornell University (Ithaca, NY). 500 CS300, CS400, CS600 Corn stover. Collected in Wisconsin 300,400, 600 YL500 Yard leaves. Collected in Ithaca, NY in fall. 500 FW500, FW600 Food waste. Collected from Cornell University dining hall (Ithaca, NY). 500, 600 PMW500, PMW600 Paper mill waste. Collected from Mohawk Paper Company (Wate rford, NY). 500, 600 BG300, BG450, BG600 Sugarcane bagasse. Collected from University of Florida (Gainesville, FL) 300, 450, 600 Slow pyrolysis in a furnace reactor under N 2 atmosphere. The heating rate was 10 °C per minute and the residence time was 120 minutes. 114, 118 BP300, BP450, BM600 Brazilian pepperwood. Collected from University of Florida (Gainesville, FL) 300, 450, 600 CS(2)600 Corn stover. Collected from Best Energies Australia (Australia) 600 Slow pyrolysis, other details not available SM450 Softwood mixture. Spruce, pine, and fir wood waste mixture. Other details not available 450 Slow pyrolysis, other details not available CB500 Chinese Bamboo. Other details not available 500 Details not avail able 47 Table 3.2. Selected properties of biochar samples. Biochar ID Proximate analysis (%w/w) Ultimate analysis (%w/w) Atomic ratios VM a Ash FC b C O H N H/C O/C (O+N)/C SB500 47.0 15.2 37.8 60.4 c n/a d n/a 0.7 c n/a n/a n/a SG500 35.1 41.2 23.7 44.2 c n/a n/a 1.3 c n/a n/a n/a HW500 56.8 4.3 38.9 73.5 c n/a n/a 0.3 c n/a n/a n/a SW500 45.5 5.6 48.9 84.4 c n/a n/a 0.0 c n/a n/a n/a SG(2)500 27.7 16.5 55.8 69.9 c n/a n/a 0.5 c n/a n/a n/a PW(2)500 46.8 46.7 6.5 31.9 16.9 2.2 2.3 0.83 0.40 0.46 CS300 51.9 1 0.7 37.4 59.9 24.8 4.5 1.1 0.90 0.31 0.33 CS400 44.7 12.9 42.4 65.2 20.1 3.3 1.1 0.61 0.23 0.25 CS600 23.5 16.7 59.8 70.7 9.3 2.3 1.1 0.39 0.10 0.11 YL500 40.3 14.5 45.2 60.7 n/a n/a 1.1 n/a n/a n/a BM300 55.5 7.7 36.8 60.6 26.6 4.9 1.3 0.97 0.33 0.35 BM400 37.0 9.4 53.7 68.5 17.4 3.5 1.2 0.61 0.19 0.21 BM500 30.5 10.4 59.2 74.1 17.4 2.6 1.1 0.42 0.18 0.19 BM600 30.0 10.6 59.4 76.0 14.3 1.8 0.8 0.28 0.14 0.15 DM300 45.4 10.1 44.5 61.5 22.6 4.5 1.6 0.88 0.28 0.30 DM400 39.1 11.5 49.5 67.1 16.8 3.3 1 .4 0.59 0.19 0.21 DM600 30.7 12.6 56.6 75.2 11.6 2.0 1.3 0.32 0.12 0.13 PM300 46.8 46.7 6.5 31.9 16.9 2.2 2.3 0.83 0.40 0.46 PM400 43.8 51.7 4.5 32.1 14.3 0.7 1.2 0.26 0.33 0.37 PM500 43.2 52.6 4.2 27.8 17.9 0.5 1.1 0.22 0.48 0.52 PM600 44.2 55.8 0.0 28.7 14.3 0.4 0.9 0.17 0.37 0.40 RDM500 33.0 32.0 35.0 51.2 n/a n/a 2.1 n/a n/a n/a DDM500 42.7 14.7 42.6 59.4 n/a n/a 2.6 n/a n/a n/a DDM600 39.4 18.8 41.7 62.8 n/a n/a 2.2 n/a n/a n/a CDM500 33.0 50.1 16.9 37.8 n/a n/a 2.0 n/a n/a n/a CDMW500 25.7 5 8.5 15.8 74.0 n/a n/a 0.6 n/a n/a n/a OW300 61.1 0.3 38.5 63.9 30.8 4.8 0.1 0.90 0.36 0.36 OW400 40.9 0.8 58.3 78.8 17.1 3.2 0.2 0.49 0.16 0.16 OW600 27.5 1.3 71.2 87.6 8.5 2.5 0.2 0.34 0.07 0.07 PW300 55.3 1.5 43.2 67.2 31.5 4.9 0.1 0.88 0.35 0.35 PW 400 45.5 1.1 53.5 76.3 20.8 3.7 0.1 0.58 0.20 0.21 PW600 27.7 1.1 71.2 91.1 9.5 2.3 0.1 0.30 0.08 0.08 WC500 26.9 10.9 62.1 85.9 n/a n/a 0.4 n/a n/a n/a FW500 33.7 52.7 13.6 42.0 n/a n/a 2.8 n/a n/a n/a FW600 34.5 52.0 13.6 32.0 n/a n/a 1.2 n/a n/a n/a PMW500 42.5 57.5 0.0 19.2 22.7 0.5 0.2 0.31 0.89 0.90 PMW600 40.0 59.1 0.0 19.2 21.2 0.4 0.1 0.25 0.83 0.83 BP300 n/a n/a n/a 59.3 34.1 5.2 0.3 1.05 0.43 0.44 BP450 n/a n/a n/a 75.6 17.2 3.6 0.3 0.57 0.17 0.17 BP600 n/a n/a n/a 77.0 17.7 2.2 0.1 0.34 0.17 0.17 BG300 n/a n/a n/a 69.5 24.5 4.2 0.9 0.73 0.26 0.28 BG450 n/a n/a n/a 78.6 15.5 3.5 0.9 0.53 0.15 0.16 BG600 n/a n/a n/a 76.5 18.3 2.9 0.8 0.45 0.18 0.19 SM450 n/a n/a n/a 55.5 c n/a n/a 0.2 c n/a n/a n/a CS(2)600 25.7 64.2 10.1 29.1 n/a n/a 0 .3 n/a n/a n/a CB500 n/a n/a n/a 62.9 c n/a n/a 0.5 c n/a n/a n/a a VM: Volatile Matter; b FC: Fixed Carbon; c Analyzed by a Costech ECS 4010 elemental analyzer (Costech, USA) in this manuscript; d n/a: not available. 48 Chemicals o f analytical grade and deionized (DI) water (Milli - Q water system, Millipore) were used in all experiments. The dissolved organic carbon (DOC) was extracted with three extraction agents respectively, including DI water, 0.1 M hydrochloric acid (HCl, Merck KGaA), and 0.1 M sodium hydroxide (NaOH, J.T. Baker). The DOC extracted by DI water, 0.1 M HCl solution, and 0.1 M NaOH solution was denoted as water - extractable DOC (WEOC), acid - extractable DOC (AEOC), and base - extractable DOC (BEOC), respectively. Briefl y, 100 mg of the biochars were first mixed with 10 mL of each extraction agent in polypropylene centrifuge tubes. The tubes were tightly closed, sealed with parafilm, and then shaken on an end - over - end shaker (Glas - Col, USA) at 30 rpm for 7 days at room te mperature (23 ± 1 °C). The tubes were wrapped with aluminum foil to prevent light exposure. Afterwards the suspensions in the tubes were vacuum - filtered through a 0.45 - µm mixed cellulose esters membrane (Millipore, USA) that was pre - washed with 50 mL DI wa ter. Since the 0.45 - µm filtrates still contained some nano - or colloidal - sized biochar particles, they were further centrifuged at 10,000 × g for 10 min to minimize the amount of colloidal biochar particles, and the supernatant were then carefully collecte d. The colloidal biochar particles remained in the supernatant, if there was any, should be 3 as biochar particle density 119 ). The final extracts th at passed through a 0.45 - µm filter and remained in the supernatant after the centrifugation at 10,000 × g for 10 min (size limit of 80 nm) are operationally defined as DOC in this study. Thus, the biochar - DOC includes the truly dissolved fraction and the n anoparticle fraction, which represent the most mobile and chemically/biologically reactive components of biochars. The final pH of WEOC solutions of 46 biochars was 8.3 ± 0.5, ranging from 7.2 to 9.5. The final pH of AEOC and BEOC solutions were not determ ined, but could be estimated to be 49 about a pH of 1 and 13, respectively, based on our preliminary test. The collected DOC samples were stored in the dark in a refrigerator until use. In addition, biochar - free blank experiments were also conducted using the same protocol and used for background correction in total organic C (TOC) and UV - vis spectroscopy analyses. The batch DOC extraction experiments were conducted in duplicate. One aliquot of each WEOC and BEOC samples was furth er fractionated into an acid - soluble (AS) fraction and an acid - precipitated (AP) fraction by acidification . After acidification, most high - molecular - weight organic compounds rich in oxygenic functional groups should theoretically be protonated and precipit ated, which allowed for separating biochar - DOC into the AS and AP fractions. First, 2 mL of the WEOC or BEOC sample was acidified to about a pH of 1 by adding 35 or 70 µL of 6 M HCl, respectively, and then allowed to stand in dark for 16 h. The acidified W EOC and BEOC samples were then centrifuged at 10,000 × g for 10 min to obtain the dark - brown precipitates of the AP fraction and the light - yellow supernatant of the AS fraction. After carefully withdrawing the AS fraction (i.e., the supernatant), the AP fr action (i.e., the pellets) was re - dissolved with 2 mL of 0.1 M NaOH and then collected for TOC and UV - vis analyses. The AEOC sample was originally extracted by 0.1 M HCl and was thus assumed to be 100% of the AS fraction. Additionally, the WEOC and BEOC sa mples free of AP fraction were verified by no change of the UV - vis spectra before and after acidification, and were operationally assumed to contain 100% of the AS fraction. Prior to the TOC and UV - vis analyses, all the DOC samples were diluted 10 - fold with DI water to obtain enough sample volume for TOC analysis, and additional 5 - fold dilution (total of 50 50 - fold) were made for some samples of BEOC, the AS fraction, and the AP fraction that still had concentrations too high to perform a reliable UV - vis analysis. The DOC concentrations were measured by a Shimadzu TOC - V CPN TOC analyzer (Shimadzu, Japan) after subtracting the inorganic carbon from the total carbon. The DOC concentrations of each sample were further correct ed by the background concentrations in the blank samples (i.e., 0.95 to 1.04 mg - C L 1 ). The UV - vis absorbance spectra were acquired between 200 to 800 nm with a Varian Cary 50 Bio UV - visible spectrophotometer (Varian, USA) in a 1 - cm quartz cuvette with DI water as the reference blank. There was no further correction of the UV - vis absorbance spectra since the blank samples showed a negligible UV - vis absorbance above a wavelength of 230 nm. For the UV - vis analysis, there was severe matrix interference for AEO C samples in 11 biochars with high ash content (but not for WEOC and BEOC), presumably due to the dissolution of ash. The UV - vis results of these samples were thus excluded. The spectral absorption ratio of 254 to 365 nm ( E 2 / E 3 ratio) and spectral slope co efficient between 275 and 295 nm ( S 275 295 ) were further used to characterize the aromaticity and M w of DOC. T he E 2 / E 3 ratio was calculated as the ratio of decadic absorption coefficient ( a , c m 1 ) at 254 nm and 365 nm. The a was calculated by a = A / l , wher e A is the UV - vis absorbance and l is the path length of 1 cm. The spectral slope coefficients between 275 295 nm ( S 275 295 ) were determined by the slope of natural logarithm of Napierian absorption coefficient against wavelength of 275 to 295 nm. 120 The Napierian absorption coefficient was calculated by 2.303× A / l . Advanced quantitative 13 C multiple cross polarization/magic angle spinning (multiCP/MAS) and multiCP/MAS with dipolar depha sing (multiCP/MAS/DD) solid - state NMR techniques w ere used to further investigate the chemical compositions of DOC and the alteration 51 in biochar compositions after water and base extraction treatments. Five selected biochars and their extracted DOC samples were prepared for the solid - state 13 C nuclear magnetic resonance (NMR) analysis. These biochars included three slow - pyrolysis biochars (BM300, BM600, and DDM500) and two fast - pyrolysis biochars (SB500 and SG500). BM300, DDM500, SB500 and SG500 were chosen to represent the biochars with a high DOC concentration. As a comparison, BM600 was selected to represent the biochar with a low DOC concentration. However, we were unable to collect the NMR spectrum for the DOC samples of BM600 because of its low extract able DOC concentration. For the same reason, we did not conduct the NMR analysis for all other samples because of the difficulty to collect enough amount of DOC from our limited amount of biochar samples. The batch extractions were conducted similarly as d escribed above, but at a higher biochar - water ratio in order to collect enough DOC samples for the NMR analysis. Briefly, one gram of the biochars were mixed with 20 mL of DI water or 0.1 M NaOH and then shaken on the rotary shaker at 30 rpm for 7 days at room temperature in dark. The extraction with 0.1 M HCl was not performed due to the low extractable DOC insufficient for the NMR analysis. The suspensions were then centrifuged at 10,000 × g for 10 min and carefully separated to the extracted DOC (i.e., t he supernatant) and the treated biochars (i.e., the pellets) for further treatment. The biochar precipitates were re - dispersed with 50 mL DI water and re - centrifuged for five times to remove excess salt for reducing sample conductivity, and then freeze - dri ed. The DOC extracts were vacuum - filtered through a 0.45 - g for 10 min to removal any remaining colloidal biochar particles. The filtered and centrifuged DOC supernatants were directly freeze - dried. However, near all collected WEOC and BEOC samples were sticky tar - like substances unsuitable for the NMR analysis. The NMR spectrum was only acquired for the BEOC 52 sample of SB500 because it was the least sticky and more powder - like sample. The phenomenal of sticky freeze - dr ied DOC samples was also observed by Smith et al., 55 suggesting that the stickiness resulted from the presence of some bio - oil - like substances. Therefore, another batch extraction for BM300, DDM500, SB500 and SG500 were conducted by the same protocol, and additional dialysis treatment was included. The filtered and centrifuged DOC supernatants were washed via dialysis (MWCO 100 - 500 Da, Spectrum Labs, USA) against DI water in dark for two days, and the DI water was r eplaced at 2, 4, 18, and 24 hr. We noted that the DOC compounds with molecular weight below 500 Da would be washed out during dialysis. Afterward the DOC samples were freeze - dried. The post - dialysis freeze - dried samples were powder - like substances, but onl y enough amount of BEOC samples were collected for the NMR analysis. The raw, water - extracted and base - extracted biochars, base - extrac t able DOC, and dialyzed base - extrac t able DOC were denoted as biochar - Raw, biochar - DI, biochar - NaOH, BEOC, and dBEOC, respe ctively. The prepared biochar and DOC samples were then analyzed by 13 C multiCP/MAS and multiCP/MAS/DD techniques . 121, 122 Quantitative 13 C multiCP/MAS and multiCP/MAS/DD NMR spectra were acquired on a Bruker Avan ce III 400 spectrometer (Bruker, USA), equipped with a 4 - mm double - resonance probe head, at a 13 C frequency of 100 MHz, a spinning frequency of 14 kHz, and a 90° pulse length s for NMR spectra was 1024. Nonprotonated and mobile carbon fractions of multiCP/MAS spectra were determined by its corresponding multiCP/MAS/DD spectra with a dipolar dephasing time of 68 performed using the TopSpin software (version 3.5pl5). The 13 C multiCP/MAS NMR spectra included all carbon (C) signals and could be divided into following assigned regions: 123 - 125 0 50 ppm to nonpolar alkyl C; 53 50 65 ppm to O/N - alkyl C; 65 95 ppm to O - alkyl C; 95 220 ppm to carbonyl C (C=O) in ketone/aldehyde. The multiCP/MAS/DD spectra further identified t he signals of mobile and nonprotonated carbon moieties, such as CCH 3 2 ) n , OCH 3 , nonprotonated aromatic C C, aromatic C proportion of anomeric C overlapped with the right shoulder of aromatic C in the 95 110 ppm range, and thus could not be determined in this study. Consequently, the proportion of assigned aromatic C was slightly overestimated by about 1 to 3%, assuming a 1:1 ratio of anomeric and aromatic C in this overlapped range. 126 Because most DOC - enriched biochars and their extrac t able DOC samples have relatively large fraction of alkyl C and carboxyl C, the estimation of average aromatic cluster sizes based on the fraction of aromatic edge carbons was not relia ble. Alternatively, the ratio of nonprotonated aromatic C fraction to total aromatic C fraction ( F aN / F a ) was used as a proxy of the condensation of aromatic rings. The F aN / F a ratio has been suggested to increase with increasing average cluster size of fuse d aromatic rings. 122, 124, 127 The decadic absorption coefficient at 254 nm ( a 254 ) was linearly correlated with the concentrations of AEOC, WEOC, BEOC, BEOC - AS, and BEOC - AP to generated linear equations. In addition, based on a 254 , DOC concentrations, and E 2 / E 3 ratio of BEOC - AS and BEOC - AP, we further developed a more universal method to first predict the proportions of AS and AP fractions by measuring E 2 / E 3 ratios and then t o estimate DOC concentrations by a 254 . Detailed derivation of the governing equations is described in the Results and Discussion section . 54 DOC was a significant fraction of the biochars ( Figure 3. 1 a and Table 3. 3), and was up to 5.7%, 6.6%, and 23% of total C in the biochars for the AEOC, WEOC, and BEOC, respectively ( Table 3. 3). The biochar - DOC concentrations generally increased in the order of AEOC (0.2 to 23 mg - C/g - biochar) < WEOC (0.5 to 40 mg - C/g - bio char) < BEOC (2.3 to 139 mg - C/g - biochar). In addition, the biochars from fast pyrolysis (FP) and slow pyrolysis (SP) at lower temperatures of 300 400 °C (SP300 400) generally had higher DOC concentrations than the biochars from slow pyrolysis at higher tem peratures of 450 600 °C (SP450 600), except for DDM500 ( Figure 3. 1a and Table 3. 3). For most biochars from FP and SP300 400, the AEOC solutions had clear to light - yellow colors, the WEOC solutions had light - yellow to light - brown colors, and the BEOC soluti ons had brown to dark - brown colors ( Figure 3. 1b). However, for most biochars from SP450 600, the AEOC and WEOC solutions were generally colorless, and only the BEOC solutions had light - yellow colors. The visual appearances of the extracted DOC solutions ge nerally agreed with the DOC measurements. The BEOC solutions had higher DOC concentrations and darker colors than those of AEOC and WEOC, presumably because more light - absorbing organic compounds were extracted under strong alkaline conditions due to the d issociation of surface functional groups (e.g., carboxyl and phenyl groups) or the cleavage of ester bonds, which promotes the solubility of larger molecules. 106, 111 Conversely, strong acidic conditions would inhi bit the extraction of DOC because most surface functional groups in the biochars would remain non - ionized, 111 resulting in lower AEOC concentrations. While most WEOC samples had deeper color than that of AEOC, for some biochars the WEOC concentrations were similar or even lo wer than the AEOC concentrations, especially for the biochars slowly - pyrolyzed at 300 °C ( Figure 3. 1a and Table 3. 3). 55 This inconsistency was presumably due to acidic hydrolysis of the labile C fraction in the biochars (i.e., pyrolysis intermediates and par tly pyrolyzed biomass residues) into weak light - absorbing small organic compounds (e.g., monosaccharides). 128 - 130 These results implied that the amount and chemical composition of AEOC, WEOC, and BEOC were different, which were further corroborated by the DOC fractionation and UV - vis analysis below. Figure 3.1. Dissolved organic carbon (DOC) concentrati ons (a) and illustrative solution colors (b) of acid - extrac table DOC (AEOC), water - extractable DOC (WEOC), and base - extractable DOC (BEOC) from 46 tested biochars (FP: fast pyrolysis; SP: slow pyrolysis; n/a: not available). 56 Table 3.3 Extrac table DOC con centration of biochar samples. Biochar ID Extrac table DOC concentration in solution (mg - C/L) Extrac table DOC, total mass based (mg - C/g - Biochar) Extrac table DOC, total carbon based (g - C/g - Biochar - C, %) AEOC WEOC BEOC AEOC WEOC BEOC AEOC WEOC BEOC SB500 252.6 419.2 1501.9 23.4 40.0 138.9 3.9 6.6 23.0 SG500 95.7 210.8 841.8 8.6 19.3 76.0 2.0 4.4 17.2 HW500 52.1 48.9 617.7 5.1 4.4 60.8 0.7 0.6 8.3 SW500 23.4 20.4 173.1 2.2 1.9 16.5 0.3 0.2 2.0 SG(2)500 38.4 44.7 147.8 3.8 4.1 14.6 0.5 0.6 2.1 PW(2)500 22.3 24.8 127.8 2.1 2.3 11.8 0.6 0.7 3.7 CS300 137.3 123.7 1253.8 12.9 11.6 118.4 2.2 1.9 19.8 CS400 60.4 89.0 523.5 5.8 8.3 50.6 0.9 1.3 7.8 CS600 5.8 30.1 50.7 0.6 2.8 4.8 0.1 0.4 0.7 YL500 21.3 24.7 166.5 2.0 2.3 15.7 0.3 0.4 2.6 BM300 138.0 142.8 1087.5 13.3 14.2 104.7 2.2 2.3 17.3 BM400 50.8 77.5 357.8 4.8 7.1 33.8 0.7 1.0 4.9 BM500 10.8 37.2 97.4 1.0 3.5 9.2 0.1 0.5 1.2 BM600 2.6 7.2 24.7 0.3 0.7 2.4 0.0 0.1 0.3 DM300 113.0 96.9 889.4 10.7 8.9 84.8 1.7 1.4 13.8 DM400 35.3 40.0 249.9 3.4 3.8 24.3 0.5 0.6 3.6 DM600 2.1 9.3 31.2 0.2 0.9 2.9 0.0 0.1 0.4 PM300 186.9 112.2 727.1 18.0 10.4 70.1 5.7 3.3 22.0 PM400 39.4 48.0 183.1 3.8 4.5 17.6 1.2 1.4 5.5 PM500 6.4 17.6 53.6 0.6 1.6 5.0 0.2 0.6 1.8 PM600 5.5 6.6 24.3 0.5 0.6 2.3 0.2 0.2 0.8 RDM5 00 4.1 17.9 39.1 0.4 1.7 3.7 0.1 0.3 0.7 DDM500 82.6 84.4 668.9 8.0 8.0 64.9 1.3 1.3 10.9 DDM600 4.8 24.5 112.6 0.5 2.2 10.6 0.1 0.3 1.7 CDM500 7.8 29.8 158.3 0.7 2.9 15.0 0.2 0.8 4.0 CDMW500 1.9 12.5 46.7 0.2 1.1 4.4 0.0 0.2 0.6 OW300 27.0 36.5 654.2 2.6 3.5 62.7 0.4 0.5 9.8 OW400 10.5 12.0 123.4 0.9 1.1 11.1 0.1 0.1 1.4 OW600 3.3 13.1 99.2 0.3 1.2 9.3 0.0 0.1 1.1 PW300 39.3 44.9 662.0 3.7 4.2 63.0 0.6 0.6 9.4 PW400 12.9 16.7 111.7 1.2 1.5 10.8 0.2 0.2 1.4 PW600 4.2 10.2 76.2 0.4 0.9 6.8 0.0 0.1 0.7 WC500 3.4 5.7 48.9 0.3 0.5 4.8 0.0 0.1 0.6 FW500 35.2 34.0 95.7 3.3 3.2 9.0 0.8 0.8 2.1 FW600 8.9 10.2 33.9 0.8 0.9 3.2 0.3 0.3 1.0 PMW500 11.0 12.4 63.8 1.1 1.1 6.3 0.6 0.6 3.3 PMW600 27.1 7.2 39.3 2.6 0.7 3.8 1.4 0.4 2.0 BP300 130.8 50.1 451.5 11.9 4.7 40.9 2.0 0.8 6.9 BP450 43.6 10.5 138.6 4.0 1.0 12.8 0.5 0.1 1.7 BP600 14.1 9.7 38.4 1.3 0.9 3.6 0.2 0.1 0.5 BG300 25.0 23.2 299.3 2.5 2.3 30.2 0.4 0.3 4.3 BG450 16.1 11.5 43.9 1.5 1.1 4.2 0.2 0.1 0.5 BG600 13.9 8.0 35.0 1.3 0.8 3.3 0.2 0.1 0. 4 SM450 4.4 27.1 113.1 0.4 2.6 10.7 0.1 0.5 1.9 CS(2)600 30.4 37.6 245.5 2.8 3.7 22.3 0.9 1.3 7.7 CB500 21.3 23.3 345.7 1.9 2.2 31.6 0.3 0.3 5.0 57 The acidification of the initially dark - colored BEOC samples from 27 tested biochars resulted in light - yellow colored AS fraction (34.3 79.5%) and dark - brown colored AP fraction (20.5 65.7%) ( Figure 3. 2 ). The AP fraction in the light - colored BEOC samples of the other 19 biochars, if any, was too low to form precipitates, which was verified by the UV - vis spectra before and after the acidification. Thus, the AP fraction of these biochars was operationally assumed as 0%. Of the WEOCs, only SB500 and SG500 had observable AP fractions (14.5% and 45.4%, respectively), whereas the AP frac tion in the WEOC of other biochars was again too low to be detected and operationally defined as 0%. Clearly, biochar - DOC could be considered as a mixture of the AS and AP fractions that varied with the extraction methods, pyrolysis conditions, and feedsto cks, as shown in Figure 3. 2 and 3. 3 . More AP components could be extracted by 0.1 M NaOH than by DI water or 0.1 M HCl ( Figure 3. 3 a), likely due to enhanced ionization of oxygenic functional groups in the biochars at higher pH, which in turn increased the solubility and extraction of the AP fraction. The AP fraction generally decreased with increasing pyrolysis temperature and residence time ( Figure 3. 3 b). As the pyrolysis temperature and residence time increased, more biopolymers and pyrolysis intermediate s were transformed into the condensed aromatic structures or cracked into low M w compounds and syngas. Therefore, less AP fraction characterized by larger M w (see next section) could be extracted from the high - temperature biochars. Finally, the DOC from he rbaceous and manure biochars generally contained more AP fractions than that from woody biochars ( Figure 3. 3 c), presumably due to greater abundance of more pyrolyzable cellulose and hemicellulose in their feedstocks. 58 Figure 3.2. Fractionation of WEOC a nd BEOC extracted from biochars . 59 Figure 3.3. Effects of the extraction methods (a), pyrolysis conditions (b), and feedstocks(c) on the acid - soluble (AS) and acid - precipitated (AP) fraction ratio of biochar - DOC. (AEOC: acid - extractable DOC; WEOC: water - extractable DOC; BEOC: base - extractable DOC; FP: fast pyrolysis at 500 °C; SP300 - 400: slow pyrolysis at 300 to 400 °C; SP450 - 600: slow pyrolysis at 450 to 600 °C). 60 The UV - vis absorption spectra of biochar - DOC sa mples were generally broad and featureless ( Figure 3. 4 ), presumably due to the overlapping absorption bands of the multiple chromophores. 54, 131, 132 The mean E 2 / E 3 ratios were 11.3 ± 1.9, 6.55 ± 1.91, 4.92 ± 2.00, 7.47 ± 1.02, and 2.48 ± 0.25, and the mean S 275 295 values were 0.0305 ± 0.0106, 0.0203 ± 0.0079, 0.0143 ± 0.0045, 0.0182 ± 0.0025, and 0.0078 ± 0.0011 for the AEOC, WEOC, BEOC, AS fraction of BEOC (BEOC - AS), and AP fraction of BEOC (BEOC - AP), respectivel y ( Figure 3. 5 and Table 3. 4). It is known that the E 2 / E 3 ratio is inversely proportional to the aromaticity and M w of DOC, and the S 275 295 values has an inverse relationship with M w of DOC. 120, 132, 133 Therefore, the aromaticity and M w decreased in the order of BEOC > WEOC > AEOC. The WEOC and BEOC of the biochars from FP and SP300 400 generally had lower E 2 / E 3 ratios and S 275 295 values (or higher aromaticity and M w ) than the biochars from SP450 600. The AEOC had very low aromaticity and M w , regardless of the biochar types. The lower E 2 / E 3 ratios and S 275 295 values of BEOC - AP indicated higher aromaticity and M w than those of BEOC - AS ( Figure 3.5 ). Therefore, the DOCs with greater AP fractions tended to have higher aromaticity and mean M w , e.g., the BEOC extracted from the biochars produced by FP and SP300 400. Although all AEOC, nearly all of the WEOC (44 of 46 b iochars), and the BEOC - AS were composed of 100% AS fraction ( Figure 3.5 ), the E 2 / E 3 ratios and S 275 295 values of the AEOC were significantly larger than those of WEOC and BEOC - AS ( p < 0.05, one - way ANOVA with post - hoc Tukey test), presumably again because of hydrolysis under acidic conditions (thus generation of smaller molecules). Interestingly, the relatively small variation in the E 2 / E 3 ratios and S 275 295 values of the BEOC - AS and BEOC - AP suggested that aromaticity and M w could be similar for the AS or AP fraction from diverse biochars. It is expected that the AS fraction with relatively higher water solubility, and 61 lower aromaticity and M w may be more susceptible to loss through abiotic and biotic degradation, and off - site transport than the AP fractio n, suggesting their differential contribution to the biochar stability. Figure 3.4. UV - vis spectra of DOC solutions (bull manure biochar as examples): (a) AEOC, (b) WEOC, (c) BEOC, and (d) the As and AP fractions of BEOC (BM300). 62 Figure 3.5. Box plo ts of UV - vis spectroscopic analyses of DOC in biochars: (a) E 2 : E 3 ratio and (b) S 275 295 . The box plots showed the first quartile, median, mean, and third quartile of the samples, and the whiskers showed the range of minimum and maximum. The symbols on the left side of box plots showed the distribution of sample values. Detailed data are provided in Table 3.4. (FP: fast pyrolysis; SP: slow pyrolysis; n/a: not available) 63 Table 3.4. UV - vis spectral parameters of AEOC, WEOC, BEOC, BEOC - AS, and BEOC - AP. Biocha r ID AEOC WEOC BEOC BEOC - AS BEOC - AP E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 SB500 10.3 0.0181 3.90 0.0130 3.15 0.0104 7.93 0.0184 2.45 0.0085 SG500 12.4 0.0244 3.35 0.0108 2.97 0.0096 7.99 0.0185 2.33 0.0075 HW500 ud a ud 3.60 0.0112 2.52 0.0092 5.43 0.0146 2.16 0.0065 SW500 10.2 0.0289 5.47 0.0212 3.26 0.0103 7.89 0.0186 2.32 0.0070 SG(2)500 8.18 0.0221 5.43 0.0142 3.39 0.0102 8.45 0.0203 2.31 0.0070 PW(2)500 8.36 0.0231 6.05 0.0155 2.98 0.0097 7.70 0.0191 2.04 0.0 066 CS300 10.2 0.0243 4.75 0.0146 3.33 0.0125 8.13 0.0162 2.73 0.0091 CS400 9.79 0.0239 5.09 0.0155 3.68 0.0120 8.11 0.0194 2.74 0.0090 CS600 ud ud 8.05 0.0211 7.17 0.0190 7.17 0.0190 n/a c n/a YL500 8.06 0.0221 6.92 0.0199 3.29 0.0107 6.76 0.0180 2.20 0.0069 BM300 11.3 0.0238 4.29 0.0138 3.37 0.0132 7.39 0.0173 2.78 0.0098 BM400 11.2 0.0251 4.64 0.0147 3.53 0.0108 7.36 0.0197 2.64 0.0085 BM500 bd b bd 4.62 0.0159 6.15 0.0173 6.15 0.0173 n/a n/a BM600 bd bd 8.61 0.0278 8.31 0.0226 8.31 0.0226 n/a n/a DM300 13.7 0.0278 5.17 0.0150 3.35 0.0112 7.70 0.0182 2.79 0.0096 DM400 13.7 0.0319 4.90 0.0153 3.96 0.0116 7.56 0.0198 2.88 0.0089 DM600 bd bd 10.2 0.0240 8.26 0.0205 8.26 0.0205 n/a n/a PM300 ud ud 5.43 0.0132 3.76 0.0117 7.32 0.0172 2.58 0.0082 PM4 00 ud ud 4.78 0.0122 5.13 0.0133 6.48 0.0160 2.84 0.0090 PM500 bd bd 8.55 0.0216 8.00 0.0185 8.00 0.0185 n/a n/a PM600 bd bd 9.81 0.0317 8.44 0.0218 8.44 0.0218 n/a n/a RDM500 ud ud 8.48 0.0203 6.83 0.0167 6.83 0.0167 n/a n/a DDM500 12.4 0.0271 4.55 0. 0130 3.25 0.0106 7.18 0.0173 2.58 0.0084 DDM600 ud ud 7.21 0.0187 4.79 0.0147 6.95 0.0184 2.59 0.0082 CDM500 ud ud 6.61 0.0148 3.21 0.0098 6.20 0.0154 2.31 0.0070 CDMW500 ud ud 8.92 0.0272 6.14 0.0146 6.14 0.0146 n/a n/a OW300 10.4 0.0301 4.70 0.0091 3 .19 0.0147 6.86 0.0151 2.39 0.0077 OW400 10.1 0.0499 9.03 0.0094 4.05 0.0134 8.49 0.0206 2.14 0.0062 OW600 bd bd 8.35 0.0309 8.76 0.0260 8.76 0.0260 n/a n/a PW300 13.9 0.0437 6.05 0.0240 3.44 0.0092 9.03 0.0182 2.66 0.0058 PW400 10.9 0.0561 9.66 0.0274 5.42 0.0146 5.42 0.0146 n/a n/a PW600 bd bd 8.43 0.0432 8.21 0.0216 8.21 0.0216 n/a n/a WC500 ud ud 8.07 0.0314 6.30 0.0171 6.30 0.0171 n/a n/a FW500 12.2 0.0196 4.82 0.0147 6.20 0.0161 6.20 0.0161 n/a n/a FW600 ud ud 7.61 0.0270 8.64 0.0228 8.64 0.02 28 n/a n/a PMW500 bd bd 7.25 0.0317 6.41 0.0204 6.41 0.0204 n/a n/a PMW600 bd bd 9.53 0.0376 6.84 0.0204 6.84 0.0204 n/a n/a 64 Table 3.4. Biochar ID AEOC WEOC BEOC BEOC - AS BEOC - AP E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 E 2 : E 3 S 275 295 BP300 14.7 0.0359 5.78 0.0198 3.65 0.0122 7.81 0.0182 2.58 0.0085 BP450 12.6 0.0499 6.82 0.0260 4.45 0.0141 8.76 0.0213 2.41 0.0079 BP600 bd bd 8.27 0.0291 8.00 0.0231 8.00 0.0231 n/a n/a BG300 10.4 0.0347 7.00 0.0201 3.76 0.0117 8.42 0.0191 2.77 0.0088 BG450 10.3 0.0425 7.54 0.0236 6.47 0.0143 6.47 0.0143 n/a n/a BG600 bd bd 8.77 0.0291 8.95 0.0230 8.95 0.0230 n/a n/a SM450 ud ud 4.56 0.0141 2.78 0.0090 7.24 0.0173 2.06 0.0062 CS(2)600 13.7 0.0219 4.78 0.0132 3.12 0.0096 7.96 0.0159 2.43 0.0076 CB500 13.2 0.0242 4.96 0.0145 2.97 0.0088 7.15 0.0150 2.39 0.0072 a ud: unable to determine due to matrix interference; b bd: a 365 below the detection limit; c n/a: not available. 65 Figure 3.6 presents the multiCP/MAS and multiCP/MAS/DD spectra and Table 3. 5 summarizes the quantitative composition of functional groups for the biochar and DOC samples. Several recognizable peaks could be observed in the 13 C NMR spectra of biochar and DOC samples ( Figure 3. 6 ). The peaks a t 15, 18, 23, and 25 ppm were assigned to methyl group ( CH 3 ), the peaks at 30 ppm to poly(methylene) group ( CH 2 ), and the peaks at 35 and 42 ppm to nitrogen - bonded methylene C (N CH 2 ) and/or quaternary C (Cq) groups. These peaks reflected the contributio ns of various short - and long - chain alkyl groups in biochar and DOC samples. The peak at 56 ppm was associated with both the OCH 3 group in lignin residues and the NCH group in peptides residues. The peak at 74 ppm (OCH) and the shoulder peaks at 62 ppm (OC H 2 ), 83 ppm (OCH), and 105 ppm (anomeric C, OCO) were attributed to the presence of cellulose residues or pyrolytic sugar. The strong peak at 129 ppm indicated the dominant presence of aromatic C in both biochar and DOC samples. The shoulder peak of aroma the phenolic groups in lignin residues or pyrolytic lignin. The peaks at 172, 174, 177, and 181 ppm were assigned to carboxyl group (COO) bonded to alky C or aromatic C as well as partially associated with amide group 190 220 ppm were relatively weak and small, suggesting a low abundance of ketone/aldehyde in both biochar and DOC samples. The BM300 - biochar - Raw sample showed the typical NMR characteristi cs of a biochar with a low degree of carbonization. 124, 134 The BM300 biochar - Raw sample exhibited great abundance of alky C, O/N - alkyl C, O - alkyl C, and aromatic C, as well as the clear features of incompletely py rolyzed biopolymers (i.e., cellulose at 74 and 105 ppm, lignin at 56, 129, and 146 ppm, and peptide at 56 and 174 ppm) ( Figure 3. 6 a). Compared to BM300 - biochar - Raw, DDM500 - 66 , SB500 - , and SG500 - biochar - Raw showed further enrichment of aromatic C, but decreas ed alky C, O/N - alkyl C, and O - alkyl C ( Figure 3. 6 b, c and d), indicating a higher degree of carbonization. The characteristic peaks of cellulose and lignin were still recognizable in the spectra of DDM500, indicating that some cellulose and lignin residues were still preserved in DDM500. Conversely, the characteristic peaks of cellulose and lignin were almost non - recognizable in the spectra of SB500 and SG500, suggesting most O/N - alkyl C and O - alkyl C in the fast - pyrolysis biochars were attributed to pyroly tic sugar. The NMR spectrum of BM600 - biochar - Raw showed a single well - defined aromatic C signal at 129 ppm with complete depletion of the biopolymer features ( Figure 3. 6 e), indicating the highest degree of carbonization among these five biochars. On the ot her hand, the quantitative NMR spectra indicated that the major components in DOC samples were aromatic C, followed by alkyl C and carboxyl/amide C ( Figure 3. 6 m to q). The DOC samples exhibited more abundance of alkyl C and carboxyl/amide C than the biocha r samples. These results indicated that the biochars with higher extractable DOC content generally also contained considerable amounts of alkyl C and carboxyl/amide C. In addition, the observation of biopolymer residues, especially for cellulose, in DDM500 was rare for this high degree of pyrolysis temperature. Typically, the most oxygen - containing functional groups and cellulose features should be eliminated at pyrolysis temperature of 500 °C, 124, 135, 136 and the NMR spectra would be quite similar to BM600 with one dominant aromatic C peak only. The abundance of functional groups and preservation of biopolymer residues in DDM500 indicated that the thermal conversion of DDM biomass was somehow limited during the pyr olysis. While the exact cause was not clear, the NMR spectra of DDM500 corroborated with its high DOC concentrations. 67 The relative abundance of functional groups in the biochars was altered by the extraction treatment ( Figure 3. 6 and Table 3. 5). Because hi gher DOC amounts were extracted with 0.1 M NaOH, the changes were more substantial for biochar - NaOH than for biochar - DI. After DOC extraction, the DDM500 ( Figure 3. 6 d and k), SB500 ( Figure 3. 6 a, f and h), and SG500 ( Figure 3. 6 b and i) each showed decreased Table 3. 5). Specifically, because fused aromatic rings increase in average cluster size wit h higher F aN / F a ratio and vice versa, 122, 124, 127 increased F aN / F a ratio of the biochars (i.e., from 0.67, 0.53, and 0.53 to 0.72, 0.68, and 0.60 for DDM500, SB500, and SG500 biochars, respectively) after the alka line extraction suggests increased average cluster size of fused aromatic rings in the residual bulk biochar. Because further aromatic condensation was unlikely to occur during the extraction, the increase of average aromatic cluster size may be attributed to the enrichment of highly condensed aromatic C in the biochars by the DOC release. Conversely, for BM300 ( Figure 3. 6 c, g, and j), the relative proportions of alkyl C, aromatic C, and carboxyl/amide C slightly decreased, and the proportion of O - alkyl C s lightly increased after DOC extraction. The characteristic peaks of lignin in BM300 were reduced in intensity at 56 and 146 ppm, together with a decrease of aromatic C signal at 129 ppm. Interestingly, in contrast to the decrease of lignin signals, the cha racteristic peaks of cellulose were markedly enhanced in intensity at 62, 74, 83, and 105 ppm. This observation was presumably because cellulose residues in the biochars have relatively lower solubility in DI water and 0.1 M NaOH compared with lignin, 130, 137 and thus these non - extrac t able cellulose residues would be more enriched after the DOC extraction. Furthermore, the enrichment of nonprotonated aromatic C in the DI - and NaOH - extracted biochar was not observed for BM300, presumably because both biochar and DOC in BM300 were composed of 68 smaller fused aromatic rings due to the insufficient pyrolysis. Finally, the NMR spectra of BM600 ( Figure 3. 6 e and l) acquired before and after the DOC extraction appeared almost identical due to the low DOC concentration. For DOC samples, the SB500 - BEOC exhibited prominent sharp alkyl C, aromatic C, and carboxyl/amide C ( Figure 3. 6 m). Specifically, the majority of aromatic C in SB500 - BEOC was protonated, suggesting that the avera ge cluster size of fused aromatic ring structures of SB500 - BEOC is very small ( F aN / F a ratio = 0.30). 122, 124, 127 Compared with SB500 - BEOC, the SB500 - dBEOC ( Figure 3. 6 n) showed a substantial decrease of alkyl C and carboxyl/amide C, but further enrichment of its aromatic C, especially for the nonprotonated aromatic C ( F aN / F a ratio = 0.56), suggesting that dissolved organic compounds with relatively large aromatic clusters were concentrated in SB500 - dBEOC after the r emoval of the low - M w compounds (< 500 Da) via dialysis. In fact, this observation was in line with the UV - vis data in that the biochar - DOC could be separated into the AS fraction with lower aromaticity and M w and the AP fraction with higher aromaticity an d M w . Furthermore, the freeze - dried BEOC samples were generally sticky tar - like substances, in contrast to the powder - like dBEOC samples, implying the sticky texture was due to the low - M w compounds that were removed during dialysis. Indeed, the markedly re duced spectral 181 ppm could be attributed to the removal of low - M w compounds ( Figure 3. 6 m and n). Based on these observations, the low - M w compounds were presumably bio - oil like compounds, such as organic acids (e.g., acetic and formic acids), small - ring polycyclic aromatic hydrocarbons (PAHs), and fatty acids or fatty acid esters. 55, 105, 138 Similar with SB500 - dBEOC, BM300 - , DDM500 - , and SG500 - dBEOC also contained greater abundance of alkyl C, aromatic C, and carboxyl/amide C ( Figure 3. 6 n q). Moreover, clear characteristic peaks of cellulose, lignin, and peptides were 69 present in BM300 - and DDM500 - dBEOC samples, but not in SB 500 - and SG500 - dBEOC samples, indicating the biopolymer residues were one of the major DOC sources in the slow - pyrolysis biochars. Figure 3.6. Solid - state 13 C multiCP/MAS NMR spectra (block black line) and multiCP/MAS after dipolar dephasing (thin red l ine) of biochar - Raw ((a) to (e)), biochar - DI ((f) and (g)), biochar - NaOH ((h) to (l)), BEOC (m) and dBEOC ((n) to (q)) samples. 70 Table 3.5. Functional groups of the biochars and DOC estimated by quantitative 13 C multiCP/MAS spectra. a Biochar ID ppm Structural parameters C=O COO/N - C=O Arom. C - O Arom. C - C Arom. C - H O - alkyl OCH 3 NCH 3 CH 2 /CH CH 3 F a (%) F aN / F a SB500 Biochar - Raw 3.7 6.7 7.0 26.8 30.0 4.1 0.3 2.6 12.9 5.9 63.7 0.53 Bioch ar - DI 3.7 5.1 7.4 31.7 28.3 3.4 0.5 2.7 10.7 6.5 67.4 0.58 Biochar - NaOH 1.7 4.7 7.5 42.0 23.3 3.4 0.1 2.2 6.6 8.4 72.8 0.68 BEOC 3.0 15.2 5.0 6.0 25.8 5.8 0.9 4.6 20.1 13.7 36.8 0.30 dBEOC 3.5 8.5 7.7 21.3 23.1 6.1 0.8 3.7 18.3 7.0 52.1 0.56 SG500 B iochar - Raw 2.6 5.6 6.5 29.1 31.6 4.1 0.6 2.3 10.6 7.0 67.3 0.53 Biochar - NaOH 1.4 4.5 5.6 38.0 29.6 4.9 0.2 2.0 7.6 6.0 73.2 0.60 dBEOC 3.2 8.5 9.3 24.5 24.7 5.4 0.7 2.7 13.7 7.3 58.5 0.58 BM300 Biochar - Raw 2.0 3.0 8.1 14.7 21.9 13.6 2.5 7.1 21.7 5.3 4 4.7 0.51 Biochar - DI 1.4 2.5 7.2 14.9 22.2 15.2 2.9 7.2 21.4 5.1 44.3 0.50 Biochar - NaOH 1.4 2.6 6.7 14.8 21.4 16.6 2.9 7.5 20.9 5.3 42.9 0.50 dBEOC 3.5 10.6 9.1 18.4 13.4 9.4 2.8 5.0 18.1 9.7 40.8 0.67 DDM500 Biochar - Raw 2.2 4.5 7.4 32.6 19.4 6.8 1.2 3.3 13.5 9.1 59.4 0.67 Biochar - NaOH 1.7 4.8 7.7 36.5 17.6 7.1 0.4 3.6 13.2 7.5 61.8 0.72 dBEOC 3.9 11.5 10.3 22.7 14.1 7.8 1.9 4.1 15.1 8.6 47.1 0.70 BM600 Biochar - Raw 1.3 3.4 4.8 60.6 24.4 2.5 0.4 0.4 1.7 0.6 89.8 0.73 Biochar - NaOH 1.2 3.4 4.6 62. 6 23.0 2.2 0.1 0.7 1.5 0.8 90.1 0.75 a c C F a : total aromatic C (165 ); F aN / F a : ratio of total nonprotonated aromatic C to total aromatic C, F aN / F a F a 71 Because the WEOC of biochars is considered more environmentally - meaningful, 108 we further compared the WEOC concentrations across a range of pyrolysis conditions and feedstocks. Clearly, the WEOC concentrations in the slow - pyrolysis biochars decreased exponentially with increasing pyrolysis temperature from 300 to 600 °C ( Figure 3. 7 a), likely due to increased degree of carbonization at higher temperature, in agreement with previous studies. 52, 55 At pyrolysis temperature of 500 and 600 °C, the biochar - DOC concentrations decreased substantially as the pyrolysis residence time increased from 0.11 s to 120 min ( Figure 3. 7 b). During fast pyrolysis, the high heating rate and short residence time facilitate the production of condensable vapors, 139 which could be easily condensed into biochar pore structure during cyclonic separation, thus forming bio - oil - like substances 138 that can later be released as DOC. In contrast, during slow pyrolysis, the condensable vapors would have enough time to escape as gases, or the trapped condensable vapors could be further decomposed into syngas or re - polymerized into the biochar structure by the secondary reaction. 103 Therefore, the fast - pyrolysis biochars had higher DOC concentrations than the slow - pyrolysis biochars at t he same pyrolysis temperature. Additionally, woody biochars produced lower DOC concentrations than herbaceous and manure biochars ( Figure 3. 7 c). Compared with the herbaceous and manure feedstocks, woody feedstocks generally have more lignin that is more th ermally s t able than hemicellulose and cellulose. 140 Thus, they are more favorable for forming biochars instead of bio - oils, resulting in lower DOC concentrations from woody biochars. Following Zhao et al., 141 standard deviation (SD) and coefficient of variation (CV) of WEOC for t he slow - pyrolysis biochars produced in the same facility were calculated ( Table 3. 6). The temperature - dependent CV of the WEOC (T - CV = 0.59 to 1.0) were generally greater than 72 the feedstock - dependent CV (F - CV = 0.48 to 0.68) ( Table 3. 6). Thus, pyrolysis te mperature was generally a more important determinant of the DOC concentrations than feedstocks. Additionally, the temperature - dependent SD of WEOC in the herbaceous and manure biochars (T - SD = 4.0 to 5.8 mg - C g 1 ) were greater than that in the woody biochar (T - SD = 1.3 to 1.8 mg - C g 1 ), presumably again because of their higher hemicellulose and cellulose content as described above. Furthermore, the SD of the WEOC in the biochars produced from various feedstocks decreased from 4.2 to 0.8 mg - C g 1 when pyrolysis temperature increased from 300 to 600 °C, indicating that the effect of feedstocks diminished at higher temperatures (500 and 600 °C). Table 3.6. Variation across pyrolysis temperature and feedstock of the WEOC of 20 tested biochars. a Pyrolysis temperature ( o C) Feedstock 300 400 500 600 T - SD T - CV WEOC (mg - C/g - Biochar) CS 11.6 8.27 - 2.76 4.49 0.59 BM 14.2 7.08 3.50 0.69 5.83 0.92 DM 8.89 3.84 - 0.90 4.04 0.89 PM 10.4 4.53 1.61 0.60 4.40 1.03 OW 3.47 1.11 - 1.23 1.33 0.69 PW 4.20 1.46 - 0.89 1.77 0.81 F - SD 4.22 2.89 1.34 0.80 F - CV 0.48 0.66 0.52 0.68 a T - SD: temperature - dependent standard deviation; T - CV: temperature - dependent coefficient of variation; F - SD: feedstock - dependent standard de viation; F - CV: feedstock - dependent coefficient of variation. Finally, the WEOC concentrations had significantly ( p < 0.05) positive correlations with oxygen (O) content ( r = 0.39), hydrogen (H) content ( r = 0.48), and H/C atomic ratio ( r = 0.67) ( Table 3. 7). Thus, it seems that DOC resulted mainly from the biochar labile fraction enriched with oxygenic functional groups. As a higher H/C atomic ratio of biochars indicates a lower degree 73 of carbonization, 36 the biochars with higher H/C atomic ratios tend to produce larger DOC concentrations. The International Biochar Initiative proposed to predict the biochar stabilit y based on the H to organic C (C org ) molar ratio, 142, 143 and the biochars with the H/C org value of less 0.4 or 0.4 t able t able bio char - DOC is more labile and thus more susceptible to loss through abiotic and biotic decomposition and/or transport. Consequently, the inclusion of DOC in calculating the H/C org atomic ratio may overestimate the biochar stability. Therefore, the biochar - DO C may need to be subtracted from C org when calculating the H/C org atomic ratio. On the contrary, the inclusion of DOC mineralization in calculating the overall biochar mineralization may underestimate the stability of bulk biochars. Table 3.7. The correlat ion coefficient (r) between WEOC and biochar properties (* and ns denote significant at p < 0.05 and not significant, respectively). Biochar properties WEOC r n Volatile Matter 0.30 ns, a 38 Ash - 0.11 ns 38 Fixed Carbon - 0.02 ns 38 C - 0.09 ns 46 O 0.39* 29 H 0.48* 29 N 0.15 ns 46 H/C 0.67* 29 O/C 0.05 ns 29 (O+N)/C 0.08 ns 29 a High WEOC content of fast pyrolysis biochar (SB500 and SG500) skewed the correlation, and the r can reach 0.48 ( p <0.05) if excludes SB500 and SG500. 74 Figure 3.7. Box - whisk er plot of WEOC concentrations vs pyrolysis temperature (a), pyrolysis type (b) and feedstocks (c). The box plots showed the first quartile, median, mean, and third quartile of the samples, and the whiskers showed the 1.5 times interquartile range. The col umn charts by the right side of the box plots showed the sample sets for box plots. 75 Predictive models for the biochar - DOC concentrations based on feedstocks and pyrolysis conditions have yet to be deve loped. Direct extraction and measurement of biochar - DOC are often needed. The most common method to measure the extracted DOC from biochars is to use a TOC analyzer, but this method is often time - consuming, requires a relatively larger sample volume, and c annot reveal any chemical characteristics of DOC. Alternatively, using UV - vis absorption spectroscopy to estimate biochar - DOC concentrations could be a quicker method that can overcome the above limitations. However, there are no sui t able chemicals that ca n be used as standards for biochar - DOC due to its highly complex composition. Therefore, establishing an appropriate relationship between the UV - vis absorbance and biochar - DOC concentrations would be critical to developing a quick, easy, and robust UV - vis spectrometric method for determining biochar - DOC concentrations. We first developed the UV - vis spectrometric method for estimating the biochar - DOC concentrations based on the linear regressions between a 254 and measured TOC concentrations of AEOC, WEOC, an d BEOC in 46 tested biochar samples ( Figure 3. 8 ). The generated linear regression equation of AEOC, WEOC, and BEOC were shown as follow: (3.1) (3.2) (3.3) where DOC (mg - C L 1 ) is the concentration measured by the TOC analyzer and a 254 (cm 1 ) is the decadic absorption coefficient at 254 nm measured by the UV - vis spectroscopy. In line with the DOC fractionation and UV - vis char acterization, the varying linear correlation slopes of AEOC, WEOC and BEOC suggested their different molecular composition (i.e., different AS and AP 76 fractions). In practice, the DOC concentration can be simply estimated by measuring a 254 and then substitu ted it in to Eq. 3. 1, 3. 2, or 3. 3 according to the extraction agent used (i.e., 0.1 M HCl, DI water, or 0.1 M NaOH). Considering the extracted DOC components (i.e., the AS and AP substances) would vary substantially with the extraction agent ( Figure 3.1), these equations are only recommended for determining the concentrations of DOC extracted with the same extraction agents described above (i.e., 0.1 M HCl, DI water, or 0.1 M NaOH). A more universal method independent of the extraction procedure is desirabl e. For this purpose, we further developed a method that allows for estimating the proportion of the AS fraction based on the E 2 / E 3 ratio and then more accurately determining the DOC concentrations from the AS fraction and a 254 . We consider the whole DOC c oncentration (DOC t ) as the sum of the DOC concentrations of the AS fraction (DOC AS ) and the AP fraction (DOC AP ). Assuming the proportion of the AS fraction in the DOC as f f f can be represented as: (3.4) Hence, DOC AS and DOC AP can be written as: (3.5) (3.6) The experimental UV - vis spectra of whole DOC, the AS fraction, and the AP fraction were showed in Figure 3.3 d, using BM300 as an exam ple, and Figure 3. 9 a. When the spectra of the AS and AP fractions were added to produce a new spectrum denoted as AS+AP, the spectrum of AP+AS almost overlapped with the spectra of whole DOC in the wavelength of 250 to 450 nm ( Figure 3. 9 a). Therefore, we c an assume that the a of whole DOC equals to the sum of the a of the AS and AP fractions. Thus, the a at 254 nm ( a 254 ) and a at 365 nm ( a 365 ) for the whole DOC can be represented as: 77 ( 3. 7) ( 3. 8) where a 254,t , a 254,AS , and a 254,AP are the a value at 254 nm for the whole DOC, the AS fraction, and the AP fraction, respectively, and a 365,t , a 365,AS , and a 365, AP are the a value at 365 nm for the whole DOC, the AS fraction, and the AP fraction, respectively. Therefore, the E 2 / E 3 ratio of the whole DOC, denoted as r , can be expressed as: ( 3. 9) According to the Beer - Lambert law ( ), a can be expressed as: ( 3. 10) where A is the absorbance, l is the light path length (cm), is the extinction coefficient (L mg 1 cm 1 ), and C is the concen tration (mg L 1 ). Therefore, the a 254,AS , a 254,AP , a 365,AS , and a 365,AP can be written as follows: ( 3. 11) ( 3. 12) ( 3. 13) ( 3. 14) where 254,AS , and 254,AP are the at 254 nm, and 365,AS , and 365,AP are the at 365 nm for the AS and AP, respectively. Assuming that the E 2 / E 3 ratio of the AS fraction is r AS and the E 2 / E 3 ratio of the AP fraction is r AP , r AS and r AP can then be expressed as: ( 3. 15) ( 3. 16) Rearran ging Eqs. 3. 15 and 3. 16 to obtain: 78 ( 3. 17) ( 3. 18) Substituting Eqs. 3. 5, 3. 6, 3. 17 and 3. 18 into Eqs. 3. 11 3. 14 to obtain: ( 3. 19) ( 3. 20) ( 3. 21) ( 3. 22) Substituting Eqs. 3. 19 S22 into Eq. 3. 9, and simplifying with the intent of eliminating DOC t , we can obtain: ( 3. 23) Eq. 3. 23 is the governing equation relating f and the E 2 / E 3 ratio ( r ) of the whole DOC. To further estimate DOC t based on a 254,t and f , we c an substitute Eq. 3. 19 and 3. 20 into Eq. 3. 7 and rearrange to obtain: ( 3. 24) Eq. 3. 24 is the governing equation for estimating the whole DOC concentration. However, there are no analytical solu tions to Eq. 3. 23 and 3. 24, and they were solved numerically based on the experimental data of BEOC - AS and BEOC - AP of 27 biochars, as follows. The linear regression between a 254 and the DOC concentrations of the AS and AP fractions are showed in Figure 3. 8 b. The generated linear regression equations of the AS and AP fractions and the final equation to estimate total DOC are shown as follows: ( 3. 25) 79 ( 3. 26) From the linear regression of DOC concentrations and a 254 for the AS and AP fractions, it is known that: ( 3. 27 ) ( 3. 28) Thus, we will have: ( 3. 29) ( 3. 30) In addition, the E 2 / E 3 ratios of the AS and AP fractions can be taken from the average of these 27 fractionable samples of BEOC - AS and BEOC - AP as r AS = 7.56 and r AP = 2.48, respectively ( Figure 3.9 b). Substituting the above numbers into Eq. 3. 23 to have: ( 3. 31) Since , we can set f from 0 to 1 in Eq. 3. 26 with a step of 0.005 and calculate its corresponding E 2t / E 3t ratio ( r ). Based on this set of data, we can draw a curve in f vs the E 2t / E 3t ratio ( r ) as shown in Figure 3.9 c. Fitting this curve with the rational function model by using MATLAB R2016a, we can obtain: ( 3. 32) Finally, substituting and into Eq. 3. 24 to derive: ( 3. 33) 80 T hus, Eqs. 3. 32 and 3. 33 are the final equations we can use to estimate the f and DOC t from the UV - vis absorbance measurements at 254 and 365 nm. In practice, the f value and biochar - DOC concentrations can be estimated simply by the E 2 / E 3 ratio and a 254 tha t can be easily determined from the UV - vis spectra. In addition, the E 2 / E 3 ratio could be used as a proxy of aromaticity and M w of biochar - DOC, as previously discussed. It is noted that Eq. 3. 3 2 estimates the DOC concentrations in the extracted solution (i n the unit of mg L 1 ) , from which the DOC concentration per unit of biochar mass can be further calculated. To validate the model, we substituted experimental UV - vis data of a 254 and a 365 of AEOC ( n = 35), WEOC ( n = 46), and BEOC ( n = 46) into Eq. 3. 32 and 3. 33 to calculate the modeled biochar DOC concentrations, and then compared with experimental biochar DOC concentrations. Performance of this model was further evaluated by the coefficient of determination ( R 2 ) and root - mean - square error (RMSE) between me asured and modeled data ( Figure 3. 10 and Figure 3.1 1 ). The modeled DOC was generally in good agreement with measured WEOC ( R 2 = 0.96, RMSE = 2.4 mg L 1 ) and BEOC ( R 2 = 0.97, RMSE = 1.9 mg L 1 ). Additionally, two data points deviated from the measured versu s modeled 1:1 relationship line at high WEOC concentrations were contributed by SB500 and SG500 ( Figure 3. 10 ), presumably due to their distinct composition from that of other 44 samples. For the AEOC ( R 2 = 0.85, RMSE = 3.6 mg L 1 ), the modeled concentratio ns were substantially lower than the measured concentrations, likely due to increased DOC concentrations from acidic hydrolysis unaccounted for by the predictive equations developed from the BEOC data. It is noted that the WEOC dataset can be considered in dependent from the BEOC dataset used to develop Eqs. 3. 1 and 3. 2 due to their distinct difference in quantity and properties. Thus, the good agreement between the modeled and measured WEOC concentrations demonstrated the validity of this method. More impor tantly, these results suggest that this model 81 may be universally applied for quantifying DOC concentrations in biochars produced from diverse feedstocks and pyrolysis conditions. The model can potentially be further improved by including more biochars foll owing the approach described here. As UV - vis spectrophotometers are routinely available in many laboratories, this method has the potential to provide a quick, easy and robust way of measuring DOC concentrations in biochars. 82 Figure 3.8. Linear regress ions between decadic absorption coefficient at 254 nm and biochar DOC concentrations in solution for (a) AEOC, WEOC, and BEOC, and (b) BEOC - AS and BEOC - AP. The dilution factor for AEOC and WEOC was 10 and for BEOC, BEOC - AS, and BEOC - AP was 50. For AEOC, 11 samples with serve matrix interference were excluded. For WEOC, SB500 and SG500 skewed the correlation because of the distinct compositional difference with other 44 samples (Figure 3.2), and thus were excluded. For BEOC - AS and BEOC - AP, only 27 fractionab le BEOC samples were included. 83 Figure 3.9. (a) Experimental data for BM300 as example, (b) boxplot of the E 2 / E 3 ratios of 27 fractionable BEOC samples, and (c) Fitting E 2 / E 3 vs f data with the rational function model. 84 Figure 3. 10 . Measured versus m odeled water - extractable DOC (WEOC) by E 2 / E 3 ratio and a 254 . Dashed line represents the 1:1 relationship. Dilution was made by 10 - folds for the WEOC samples. 85 Figure 3.1 1 . Measured versus modeled DOC for (a) AEOC and (b) BEOC by E 2 / E 3 ratio and a 254 . Das hed line represents the 1:1 relationship. Dilution was made by 10 - and 50 - folds for the AEOC and BEOC samples, respectively. 86 Our results may have several important implications to the production and application of biochars for agronomic and e nvironmental uses. Biochar - DOC was shown to be an important fraction of biochars, and its quantity and properties were dependent on feedstocks, pyrolysis conditions (i.e., pyrolysis temperature, and residence time), and the extraction procedure. Thus, bioc hars may be engineered so that the quantity and characteristics of their DOC can be properly controlled for their intended use. When used for soil C sequestration, the biochars with minimal labile DOC and maximal recalcitrant C content may be desired. If o ther benefits such as improving soil aggregation, water retention, and microbial health, the release of certain labile DOC may be beneficial. The drastic difference in the amount and chemical composition of BEOC and WEOC suggests that the alkaline extracti on cannot be used to produce the environmentally - meaningful DOC measurements, and the water extraction is thus preferred. Accurate measurement of the biochar - DOC is important because the amount of biochar - DOC could significantly influence the biochar stabi lity in soils and the appropriate methods to assess it. Therefore, the developed quick and easy UV - vis method for determining the biochar - DOC concentrations can be a useful tool for biochar production and application. 87 CHAPTER IV LONG - TERM SORPTION OF LI NCOMYCIN TO BIOCHARS: THE INTERTWINED ROLES OF PORE DIFFUSION AND DISSOLVED ORGANIC CARBON 88 Sequestration of anthropogenic antibiotics by biochars in soils may be a promising strategy to minimize environmental and human health risks of antibiotic resistance. This study investigated the long - term sequestration of lincomycin by 17 slow - pyrolysis biochars using batch sorption experiments during 365 days. Sorption kinetics were well fitted with the Weber - Morris intraparticle diffusion model for all tes ted biochars with the intraparticle diffusion rate constant ( K id ) ranging between 25.3 166 µg g 1 day 0.5 , suggesting that the sorption kinetics were mainly controlled by pore diffusion. The quasi - equilibrium sorption isotherms became more nonlinear with i ncreasing equilibration time at 1, 7, 30, and 365 days, likely due to increasing abundance of heterogeneous sorption sites in biochars over time. Intriguingly, low - temperature (300°C) biochars had higher sorption capacity and faster sorption kinetics than higher - temperature (400 600°C) biochars. The continuous release of dissolved organic carbon (DOC) from the low - temperature biochars may enhance the lincomycin sorption by decreasing biochar particle size and/or increasing the accessibility of sorption site s and pores initially blocked by DOC. Additionally, a large fraction (> 75%) of sorbed lincomycin after 240 - day equilibration could not be desorbed by the acetonitrile/methanol extractant from the tested biochars. This observed strong sorption/desorption h ysteresis illustrates that there is great potential of biochars as soil amendments to create long - term sequestration of antibiotics in - situ. 89 Antibiotics are used extensively in livestock industry for therapeutic, preventative, and growth prom otion purposes. 1 - 3 The use of antibiotics in animal feeding operations was 14,622 tons in the United States in 2012 and 84,240 tons in China in 2013 (i.e., the two largest users of antibiotics). 144 Globally, the total consumption of antibiotics in livestock industry was about 131,109 tons in 2013 and was projected to increase to 200,235 tons in 2030. 145 Because the administered antib iotics are often poorly absorbed within animals, a large portion of antibiotics are excreted into manure as parent compounds and metabolites, and released into agricultural soils and waters through manure land applications. 4, 12, 146 The widespread and repeated manure application has increased environmental concentrations of anthropogenic antibiotics, thus raising serious concerns about the proliferation of antibiotic resistant bacteria and associated food safety an d human health impacts. 1, 7, 147, 148 Mitigation strategies to reduce the release, transport, and bioavailability of manure - borne antibiotics in soils are urgently needed to minimize their environmental risks. Enha ncing sequestration of antibiotics in soils by biochar amendment may be a promising strategy for this purpose. Biochars are carbonaceous porous materials produced from the pyrolysis of biomass under oxygen - limited conditions at a typical temperature range of 300 700 o C. 149 Biochars have been promoted as soil amendments for their agronomical and environmental benefits such as increasing soil carbon storage, improving soil structure and quality, and immobilizing environmental contaminants. 33, 93, 149 Sorption plays an important role in controlling the fate, transport, and bioavailability of contaminants in soils, and the porous nature and heterogeneous surfaces of biochars lead to an excellent sorption ability for many inorganic and organic contaminants 29, 33, 35 (including antibiotics 40, 150, 151 ). The interactions between antibiotics and biochars may be 90 controlled by hydrophobic partitioning, van der Waals forces, hydrogen (H) bonding, charge - assisted H bonding (CAHB), electron donor acceptor ( EDA) interaction, electrostati c interaction, and pore filling . 40, 150, 151 The relative contribution of each sorption mechanism is collectively determined by physicochemical properties of antibiotics (e.g., hydrophobicity, polarity, ionization, and molecular structure) and biochars (e.g., surface area, surface charge, surface functionalization, and pore structure) as well as environmental factors (e.g., pH, ionic strength, and co - solutes). 40, 151 Thus, t he studies on contaminant sorption to biochars have recently focused on clarifying the complexity in sorption processes and controlling factors. Pyrolysis temperature is one of the key factors determining the physicochemical and sorption properties of bio chars. 29, 33, 35, 39 With increasing pyrolysis temperature, surface area and pore volume of biochars increase, but surface functionalization decreases with a concomitant increase in aromaticity. 38, 39, 136 As a result, higher - temperature biochars often had stronger sorption affinity to antibiotics (e.g., ciprofloxacin, 152 norfloxacin, 153 tetr acycline, 154, 155 and sulfamethoxazole 45, 156, 157 ) than lower - temperature biochars, which was attributed to greater surface area and porosity of those biochars. However, a number of studies reported the absence or opposite of such trend with regard to pyrolysis temperature for the sorption of ofloxacin, 45 norfloxacin, 45 and sulfamethoxazole 158 to biochars. Clearly, the effect of pyrolysis temperature on the sorption of antibiotics to biochars has yet to be settled. Additionally, considering the heterogeneous nature of biochar pore structure, the sorption o f antibiotics may need longer time to reach the true equilibrium. Kasozi et al. reported that the sorption kinetics of catechol on biochars reached equilibrium after 14 days. 75 Chen et al. found that the sorption o f naphthalene to biochars could take up to 36 days to reach equilibrium, depending on the pyrolysis temperature of biochars. 38 Our previous study showed that the 91 lincomycin sorption to bioch ars quickly reached a quasi - equilibrium in about 2 days, but did not reach true equilibrium after 180 days. 92 For most antibiotics that have been studied, the reported sorption equilibration time with biochars was generally several hours or days. 45, 152 - 158 Thus, some of those sorption experiments may have only reached quasi - equilibrium during such sho rt equilibration time. Consequently, the contribution of pore diffusion to the overall sorption may be underestimated due to short equilibration time. Furthermore, biochars could release a substantial amount of dissolved organic carbon (DOC, including trul y dissolved and colloidal DOC) upon exposure to water, 51, 54, 55, 76, 159 which may change the biochar surface and pore structure. For example, these water - soluble organic compounds (i.e., DOC) may initially fill u p the biochar pores during pyrolysis, or adsorb on the biochar surface, thus blocking the sorptive sites for antibiotics. The release of DOC from biochars may enhance the sorption of antibiotics to biochars. 96 Howe ver, the effects of long - term DOC release from biochars on their sorption capacity for antibiotics have not been well studied. Therefore, t his study aimed to examine: (1) the long - term sequestration of antibiotics by biochars and (2) the effect of the long - term DOC release on the sorption of antibiotics to biochars. Lincomycin was selected as a model antibiotic compound because it is one of the antibiotics widely administered to food animals, and is also medically important in human therapy. The long - term s orption kinetics and isotherms of lincomycin by 17 slow - pyrolysis biochars prepared from 7 manure feedstocks at 300 600 °C and one wood feedstock at 500 °C were evaluated to elucidate the underlying sorption mechanisms. For comparison, a commercial graphit e powder was selected to represent nonporous carbonaceous sorbents. 92 3 from Sigma - Aldrich, and sodium chloride (NaCl), sodium bicarbonate (NaHCO 3 ), sodium carbonate (NaCO 3 ) and sodium hydroxide (NaOH) from J.T. Baker. Selected physicochemical properties of lincomycin are listed in the Table 4. 1. All chemical reagents used were of analytical grade. Deionized (DI) water from a Milli - Q water system (Mill ipore, USA) was used for preparing all aqueous solutions. Table 4.1. Physicochemical properties of lincomycin . Chemical name Lincomycin Molecular structure a Molecular formula b C 18 H 34 N 2 O 6 S Molecular weight b 406.537 g mol 1 Water solubility b 927 mg L 1 at 25 °C Log octanol - water partition coefficient (log K ow ) b 0.20 Dissociation constant (p K a ) b 7.6 a Data from ChemSpider ( http://www.chemspider.com/ ); b Data from TOXNET ( http://www.toxnet.nlm.nih.gov/ ) Sixteen manure - based and one wood - based biochars were produced by the Best Energies Inc. (Daisy Reactor, Cashton, WI). The feedstocks and production conditions of these bioc hars have been described in detail elsewhere. 28, 71 Briefly, the feedstocks were bull manure with sawdust bedding (BM), dairy manure with rice hull bedding (DM), poultry manure with sawdust bedding (PM), raw dairy manure (RDM), digested dairy manure (DDM), composted digested dairy manure (CDM), composted digested dairy manure mixed with woodchip waste in a 1:1 ratio (CDMW), 93 and woodchip waste (WW). The same source of dairy manure was used to produce RDM, DDM, CDM, a nd CDMW with different pretreatments before pyrolysis in a Daisy Reactor at BEST Energies Inc. The feedstocks were slowly pyrolyzed in a N 2 atmosphere at 300, 400, 500 or 600 1 and a retention time of 15 20 min. The produced biochars were ground and sieved to obtain particles in the 75 vials prior to use. These biochars were hereafter labeled using feedstock abbreviation and pyrolysis temperature, e.g., BM300 for bull manure with sawdust bedding pyrolyzed at 300 °C. Nonporous graphite powder (< 150 µm, 99.9% C) was purchased from Sigma - Aldrich and used as receiv ed. The proximate (volatile matter, fixed carbon, and ash) and ultimate (C, H, O, and N) analyses of the biochars have been characterized and reported previously. 28, 71 Specific surface a rea (SSA) and micropore volume ( V mic ) of the biochars were measured by CO 2 adsorption on a Micromeritics Tristar 3020 analyzer (Micromeritics, USA) at Pacific Surface Science Inc. (Oxnard, CA). Zeta potential of the biochar particles was determined by a Ze tasizer Nano - ZS (Malvern Instruments, UK) . To generate a biochar suspension, 8 mg each biochar was mixed with 8 mL 0.02 M background electrolyte (6.7 mM NaCl, 2.5 mM Na 2 CO 3 , 2.5 mM NaHCO 3 , and 200 mg L - 1 NaN 3 .) in amber glass vials and then shaken end - over - end for 1 day. Afterwards, the vials were allowed standing for 30 min and then the top 1 mL of the suspension was withdrawn and measured for the zeta potential by the Zetasizer Nano - ZS. The remained suspensions were used to determine solution pH of the su spension (10.0 ± 0.1 for all tested biochars). Additionally, BM300 and BM600 were selected as model biochars (representing poorly - and highly - carbonized biochars, respectively) for further studying the characteristics of biochar particles after water expos ure. The shape and surface morphology of BM300 particles before and after 1 - d and 365 - d 94 kinetic sorption experiments (described later) and 1 - d exposure to 0.1 M NaOH solution were investigated with a scanning electron microscope (SEM) (JEOL JSM - 7500F, Japa n). To measure the biochar colloid size after the DOC release, biochars were suspended in 0.01M NaCl or 0.01M NaOH solution (1:1 solid/water ratio) and shaken end - over - end for 1 day. After shaking, the vials were allowed standing for 30 min and then the to p 1 mL of the biochar suspension was withdrawn and measured for particle size distribution by dynamic light scattering method using the Zetasizer. Batch sorption experiments were conducted in amber borosilicate glass vials with polytet rafluoroethylene (PTFE) lined screw - caps. All vials were covered with aluminum foils to prevent the potential photodegradation of lincomycin. The lincomycin solutions were freshly prepared in DI water with ionic strength of 0.02 M and pH of 10 using backgr ound electrolytes of 6.7 mM NaCl, 2.5 mM Na 2 CO 3 , and 2.5 mM NaHCO 3. NaN 3 of 200 mg L 1 was included as a biocide to prevent any biodegradation of lincomycin during the long - term sorption experiments. All sorption experiments were performed in duplicate at room temperature (23 ± 1 °C) and a sorbent - water ratio of 1 g L 1 . The above experimental condition and setup for the batch sorption studies were followed unless noted otherwise. For the kinetic sorption experiments, 8 mg of each sorbent were mixed with 8 mL of 1000 µg L 1 lincomycin in 8 mL vails and then agitated on an end - over - end shaker (Glas - Col, USA) at 30 rpm in dark for the duration of 1 365 days. At pre - determined time intervals, two vials for each sorbent were retrieved from the shaker. The vials were centrifuged at 2430 × g for 20 min, and the top 2 mL of supernatants were collected and filtered through a 0.45 - µm mixed cellulose esters syringe filter (Millipore, USA). The first 1 - mL filtrate was discarded, and the following 1 - mL filtrate was colle cted to minimize the potential loss of lincomycin sorbed by the filter. The 95 concentrations of lincomycin in the filtrate was determined by a Shimadzu Prominence high - performance liquid chromatograph coupled to an Applied Biosystems Sciex 3200 triple quadru pole mass spectrometer (LC - MS/MS). Since the sorbent - free control experiments showed a negligible loss of lincomycin during the experiments ( Figure 4. 1), the difference between the initial and final solution concentrations was used to calculate the sorbed lincomycin concentration in the sorbents. In addition, the DOC in the filtrate is operationally defined as biochar - derived DOC in this study. Because the filtrate volume was small, and if diluted, the DOC concentration could be below the detection limit of total organic carbon analyzer, the concentration of DOC in the filtrate was determined by ultraviolet (UV) absorption at 254 and 365 nm on a Varian Cary 50 Bio UV - visible spectrophotometer (Varian, USA), using our recently developed method. 160 Details of the LC - MS/MS and UV analytical protocols are provided in the Analytical Methods section . To conduct the quasi - equilibrium sorption isotherms, 8 mg of e ach sorbent were mixed with 8 mL lincomycin solutions with a series of initial concentrations ranging from 100 to 1000 g L 1 . The suspensions were shaken end - over - end at 30 rpm in dark. At 1, 7, 30, and 365 days, the vials were retrieved, centrifuged, filtered, and determined for the lincomycin concentration by the LC - MS/MS as described previously. 96 Figure 4.1. Lincom ycin concentrations in solution over time in the kinetic sorption experiments for the 17 tested biochars. Control was the biochar - free lincomycin solution. 97 To further elucidate the role of DOC on the sorption of linc omycin to biochars, three additional experiments were performed as detailed below . First, the freely dissolved lincomycin and DOC - bound lincomycin in solutions were determined using the solid - phase extraction method. 87 Briefly, 7.2 mL of each DI - water - extracted DOC solution as described above (40 - d extrac tion) was mixed with 0.8 mL of lincomycin solution (lincomycin concentration of 10,000 µg L 1 and ionic strength of 0.2 M background electrolytes) in vials to acquire the lincomycin/DOC mixture solution with the initial lincomycin concentration of 1000 µg L 1 , ionic strength of 0.02 M, and DOC concentration of 186, 93.8, 97.4, and 89.6 mg - C L 1 for BM300 - , DM300 - , PM300 - , and DDM500 - DOC, respectively. The vials were then end - over - end shaken at 30 rpm in dark for 1 day. Afterwards, the lincomycin/DOC mixture solution was passed through an Oasis hydrophilic lipophilic balance (HLB) cartridge (Water s Corporation, USA), which was preconditioned with 3.0 mL of methanol and 3.0 mL of DI water. At this step, the DOC - bound lincomycin in solution could pass through the HLB cartridge and the freely dissolved lincomycin in solution would be retained by the H LB cartridge. The retained freely - dissolved lincomycin was further eluted from the HLB cartridge with 5.0 mL of methanol, and then determined the concentration by LC - MS/MS. Finally, the DOC - bound lincomycin concentration was calculated by the difference be tween initial applied lincomycin concentration and freely dissolved lincomycin concentration in solutions. Its results could allow us to determine if the enhanced lincomycin sorption over time was due to the binding of lincomycin with DOC. Second, the lin comycin sorption to a wood biochar (WW500) was measured in the absence and the presence of DOC at 17.2, 7.94, 11.1, and 10.9 mg - C L 1 extracted from BM300, DM300, PM300, and DDM500, respectively. To extract the DOC from the biochars, 500 mg of each 98 selecte d biochar were mixed with 50 mL of DI water in 50 mL polypropylene (PP) centrifuge tubes, and then shaken end - over - end at 30 rpm in dark for 7 days. Afterwards the tubes were centrifuged at 8,000 × g for 20 min, and the supernatants were then vacuum - filter ed through a 0.45 - µm membrane (mixed cellulose esters). The final filtrates were collected as the DOC stock solutions, and the DOC concentrations were determined by a Shimadzu TOC - V CPN TOC analyzer (Shimadzu, Japan). Aliquots of each DOC stock solutions we re further diluted 10 - fold with a lincomycin solution (lincomycin concentration of 1111 µg L 1 and ionic strength of 0.022 M background electrolytes) to achieve the initial lincomycin concentration of 1000 µg L 1 , ionic strength of 0.02 M, and DOC concentr ation of 17.2, 7.94, 11.1, and 10.9 mg - C L 1 for BM300 - , DM300 - , PM300 - , and DDM500 - DOC, respectively. For comparison, a lincomycin solution without DOC was prepared using the same protocol but replacing the DOC stock solution with DI water. The prepared l incomycin solutions with and without DOC were denoted as lincomycin/DOC and lincomycin/DI, respectively. Thereafter, the lincomycin sorption kinetics in the presence of DOC were carried out using WW500 biochar, which was selected because of its low DOC con tent. Briefly, 8 mL of each lincomycin/DOC and lincomycin/DI solutions were mixed with 8 mg WW500 biochar in vials, and then the vials were shaken end - over - end at 30 rpm in dark for the duration of 1 day to 60 days. The other procedures were same as descri bed in the sorption kinetics section. In addition, the control experiments of lincomycin/DOC solutions without WW500 biochars were also performed using the same protocol, and the lincomycin concentrations in solution had no significant difference regardles s of the presence of DOC during 60 days (data not shown). This experiment allowed us to evaluate the effect of free DOC in solution on lincomycin sorption to biochars. 99 Finally, to evaluate the change in the lincomycin sorption to biochars after the DOC re lease, BM300, BM600, DM300, PM300, and DDM500 were washed with 0.1 M NaOH (only for BM300, BM600, and DM300) or DI water, respectively. To wash out the DOC, 500 mg of each selected biochar (BM300, BM600, DM300, PM300, and DDM500) were mixed with 50 mL of 0 .1 M NaOH (only for BM300, BM600, and DM300) or DI water in vials and then end - over - end shaken at 30 rpm in dark for 1 day or 40 days, respectively. The suspensions were then centrifuged at 8,000 × g for 20 min, and the supernatant was collected. The super natant was vacuum - filtered through a 0.45 - TOC analyzer after appropriate sample dilution. The treated biochar pellets were re - dispersed with 50 mL DI water and re - centrifuged for five times to rem ove remaining salt and DOC, and then freeze - dried to obtain the DOC - washed biochars. The sorption kinetics of lincomycin on the washed biochars were conducted as previously describe. Briefly, 8 mg of each washed biochar were suspended in 8 mL of 1000 µg L 1 lincomycin solution, and then end - over - end shaken at 30 rpm in dark for the duration of 1 to 30 days. The rest sampling and analysis procedures were identical as previously described. Single - point batch extr action experiments were performed to test the desorption hysteresis of lincomycin on the biochars. Following the sorption kinetics after 240 days, two vials of each biochar in the kinetic sorption experimental set were retrieved. The suspensions in vials w ere stirred with a PTFE - coated micro stir bar, and 2 mL of each suspension was uniformly withdrawn, filtered, and determined for the lincomycin concentration in filtrates by the LC - MS/MS. In addition, another 1 mL of each suspension was placed into a vial containing 4 mL of acetonitrile/methanol (8/2 in v/v) extraction solvent. The vials were end - over - end shaken at 30 100 rpm in dark for 7 days and then placed into an ultrasonic bath to sonicate for 60 min at 50 °C. The suspensions were then centrifuged, filter ed, and determined for the lincomycin concentration by the LC - MS/MS as described previously. The extraction recovery of lincomycin from biochars were calculated by mass balance. The concentration of lincomycin in solutions were determin ed by a Shimadzu Prominence high - performance liquid chromatograph coupled to an Applied Biosystems Sciex 3200 triple quadrupole mass spectrometer (LC - MS/MS). The analytical column was an Agilent ZORBAX Eclipse Plus C18 column with 50 mm length × 2.1 mm dia meter and 5µm particle size. The mobile phase A consisted of DI water and 0.3% formic acid. The mobile phase B consisted of 1:1 (v/v) acetonitrile - methanol mixture and 0.3% formic acid. Data were acquired using a gradient condition of 0 40 % B in 0 1 min, 40 70% B in 1 2 min, 70 80 % B in 2 3 min, 80 100 % B in 3 3.5 min, and 100% B for 0.5 min. The flow rate was set to 0.35 mL min 1 and the injection volume was set qua drupole MS. Lincomycin was detected and quantified using a multiple reaction monitoring mode with a precursor/product transition of 407.2/126.2. The retention time was 2.37 min and the instrument detection limit of lincomycin was 0.2 pg. The concentration of DOC released from the biochars were determined by our recently developed UV absorption method 160 with a Varian Cary 50 Bio UV - visible spectrophotomet er (Varian, USA). We considered the biochar DOC was a mixture of the acid - soluble (AS) and acid - precipi table (AP) fractions and the fraction of AS can be calculated via: (S4.1) 101 where f AS is the proportion of the AS frac f AS e is the E 2 / E 3 ratio. T he E 2 / E 3 ratio was calculated as the ratio of decadic absorption coefficient ( a , c m 1 ) at 254 nm ( a 254 ) to 365 nm ( a 365 ), where the a was calculated by UV - vis absorbance (unitless) divided by path length (cm). If calculated f AS value is < 0 or > 1, it will be assumed to be 0 or 1, respectively. Then, the biochar DOC concentration in solution (in the unit of mg - C L 1 ) can be calculated via: (S4.2) The DOC determi ned by the UV absorption method was generally in good agreement with the DOC measured by a total organic carbon (TOC) analyzer. T he experimental sorption kinetics were fitted to the intraparticle diffusion model (Eq. 4 .1) or pseudo - se cond - order kinetic model (Eq. 4.2) : 73, 74, 161 ( 4. 1) (4. 2 ) where q t ( g g 1 ) is the sorbed lincomycin concentration in the solid phase at time t , K id ( g g 1 day 0.5 ) is the intraparticle diffusion rate constant, t (day ) is the reaction time, C id ( g g 1 ) is the intercept constant that reflects the contribution from the rapid initial sorption , q e ( g g 1 ) is the sorbed lincomycin concentration at equilibrium, and k 2 (g g 1 day 1 ) is the pseudo - second - order rate constan t. According to Wu et al., 73 the relative importance of intraparticle diffusion and initial sorption could be further analyzed based on following equations: ( 4. 3 ) ( 4. 4 ) 102 where t ref (day) is the longest time used when fitting the intraparticle diffusion model, q ref ( g g 1 ) is the sorbed lincomycin concentration in the solid phase at time t ref , and R id is the intrapartic le diffusion factor that represents the relative contribution of the intraparticle diffusion to the total sorption. The quasi - equilibrium sorption isotherms were fitted to the Freundlich model: 162 (4 . 5 ) where q t ( g g 1 ) is the sorbed lincomycin concentration in the solid phase at time t , C t ( g L 1 ) is the lincomycin concentration in the solution at time t , K F ( g 1 N g 1 L N ) is the Freundlich sorption coefficient, and N (dimensionless) is the Freundlich nonlinearity factor. The selected physicochemical properties of 17 tested slow - pyrolysis biochars are shown in Table 4 . 2. The volatile matter content (25.7 55.5% ) decreased, whereas the fixed carbon content (0 62.1% ) and the ash content (7.7 58.5% ) increased with increasing pyrolysis temperature, due to increased carbonization of biomass at higher pyrolysis temperature. 103, 136 The volatile matter and fixed carbon contents could approximate the labile and recalcitrant fractions of biochars, respectively. 136 In addition, the biochars produced from PM, CDM, and CDMW had a greater ash content ( 32.0 55.8%) than that from BM, DM, DDM, and WW (7.70 18.8%), which was attributed to the high ash content in their feedstock. 163 For biochars from the same feedstocks, the total C content (27.8 85.9% ) increased, while total O (11.6 26.6% ), H (0.4 4.9% ), and N (0.4 2.6% ) contents decreased with increasing pyrolysis temperatu re. Accordingly, the value of atomic ratios of H/C (0.17 0.97) and (O+N)/C (0.13 0.52 ) decreased at higher pyrolysis 103 temperature, suggesting that the high - temperature biochars had more condensed aromatic structures and less polar functional groups. 36, 49, 136 The SSA and V mic of the tested biochars ranged from 42.8 243 m 2 g 1 and 0.02 0.12 cm 3 g 1 , respectively, and generally increased with increasing pyrolysis temperature. The SSA of the biochars was positively co rrelated with their fixed carbon ( r = 0.90) and total carbon contents ( r = 0.92), but negatively correlated with their volatile matter ( r = 0.62) and ash contents ( r ( Figure 4. 2). In agreement with Sun et al., 30 this observation suggests that the SSA of the biochars was mainly contributed by the carbonized fraction in the biochar matrix, other than the uncarbonized or ash fractions. The SEM images of BM300 and BM600 revealed that the biochar pores were irr egular in shape, and heterogeneous in pore size distribution from nanometers to micrometers ( Figure 4. 3 ). The majority of macroporous structures originated from the feedstock pore structure remained relatively similar for BM300 and BM600. But the abundance of finer nanopores and smoother external surface was greater for BM600 ( Figure 4. 3 ), which was in line with the increase of SSA and V mic . Furthermore, the coarse amorphous substance accumulated on the surface of BM300 was presumably formed by the labile c arbon compounds (i.e. volatile compounds or DOC) due to the incomplete pyrolysis that is absent at higher pyrolysis temperature. ionic strength of 0.02 M ( Tab le 4. 2), indicating that the biochars carried net negative surface charge under the experimental conditions. 104 Table 4.2. Selected properties of biochar and graphite samples. Samples Proximate analysis a Ultimate analysis a Atomic ratio VM b Ash FC c C O H N H/C (O+N)/C SSA d V mic e ZP f % % % % % % % m 2 g 1 cm 3 g 1 mV BM300 55.5 7.7 36.8 60.6 26.6 4.9 1.3 0.97 0.35 125 0.08 - 54 BM400 37.0 9.4 53.7 68.5 17.4 3.5 1.2 0.61 0.21 160 0.09 - 50 BM500 30.5 10.4 59.2 74.1 17.4 2.6 1.1 0.42 0.19 196 0.10 - 58 BM600 30.0 10.6 59.4 76.0 14.3 1.8 0.8 0.28 0.15 237 0 .12 - 57 DM300 45.4 10.1 44.5 61.5 22.6 4.5 1.6 0.88 0.30 112 0.07 - 61 DM400 39.1 11.5 49.5 67.1 16.8 3.3 1.4 0.59 0.21 148 0.08 - 58 DM600 30.7 12.6 56.6 75.2 11.6 2.0 1.3 0.32 0.13 221 0.11 - 63 PM300 46.8 46.7 6.5 31.9 16.9 2.2 2.3 0.83 0.46 46.8 0.03 - 45 PM400 43.8 51.7 4.5 32.1 14.3 0.7 1.2 0.26 0.37 42.8 0.03 - 48 PM500 43.2 52.6 4.2 27.8 17.9 0.5 1.1 0.22 0.52 53.1 0.03 - 43 PM600 44.2 55.8 0.0 28.7 14.3 0.4 0.9 0.17 0.40 47.0 0.02 - 43 RDM500 33.0 32.0 35.0 51.2 n/a g n/a 2.1 n/a n/a 112 0.06 - 52 DDM500 42.7 14.7 42.6 59.4 n/a n/a 2.6 n/a n/a 110 0.06 - 60 DDM600 39.4 18.8 41.7 62.8 n/a n/a 2.2 n/a n/a 183 0.09 - 58 CDM500 33.0 50.1 16.9 37.8 n/a n/a 2.0 n/a n/a 88.9 0.05 - 50 CDMW500 25.7 58.5 15.8 74.0 n/a n/a 0.6 n/a n/a 129 0.06 - 56 WW500 26.9 10.9 62.1 85.9 n/a n/a 0.4 n/a n/a 243 0.12 - 64 Graphite n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a - 60 a D ata adapted from Enders et al.,2012 and Rajkovich et al., 2012. 28, 71 ; b VM: volatile matter; c FC: fix ed carbon; d SSA: specific surface area, measured by the BET - CO 2 method; e V mic : micropore volume, calculated using Dubinin - Astakhov method; f ZP: zeta potential, sorbent suspension were measured at pH 10 in 0.02 M ionic strength of background solution (6 .7 mM NaCl, 2.5 mM Na 2 CO 3 , 2.5 mM NaHCO 3 , and 200 mg L - 1 NaN 3 ); g n/a: not available. 105 Figure 4.2. The relationship of (a) total carbon, (b) fixed carbon, (c) volatile matter, and (d) ash contents versus CO 2 - BET specific surface area for biochars. 106 Fi gure 4. 3 . Scanning electron microscopy images of raw biochars: (a) BM300 (bull manure biochar produced at 300 °C) and (b) BM600 (bull manure biochar produced at 600 °C). 107 As shown in Figure 4. 4 , the lincomycin sorption onto the bioc hars occurred rapidly in the initial sorption phase (within the first day), followed by a slower sorption that gradually increased removed by the biochars after 1 PM400) of that was removed by 365 days. The lincomycin sorption kinetics could approach an PM500, a nd CDM500 that did not reach equilibrium by the end of the experiments (i.e., 365 days). Considering the porous nature of biochars, the fast initial sorption was primarily attributed to the instantaneous or very rapid sorption on the external surface of bi ochars that provides readily accessible sorption sites for lincomycin. The subsequent long - term slow sorption was mainly caused by the relatively slower intraparticle diffusion into the internal biochar pore structures that provide abundant sorption sites, but require longer time for lincomycin to access. 32 As a comparison, the sorption of lincomycin onto the nonporous graphite reached a sorption equilibrium within 1 day and remained unchanged for 30 days due to the lack of pore structures ( Figure 4. 5 ). The significant difference in the sorption behaviors between the porous biochars and the nonporous graphite further supported that the sorption of lincomycin to the biochars was controlled by fast surface sorption in the short term and slow intraparticle diffusion in the long term. The tested biochars had different sorption kinetics, presumably due to the heterogeneity in their pore structures and surface chemistries. Overall, the sorption kinetics decreased in the or der: Figure 4. 4 Figure 4. 4 b), and PM600 > PM300 > PM500 > PM400 ( Figure 4. 4 WW500 > CDMW500 > CDM500 ( Figure 4. 4 d). Specifically, although the biochars produced at 108 hi gher temperature (i.e. 400 600 °C) generally had faster sorption kinetics in the initial sorption phase, lower - temperature (300 °C) biochars generally exhibited faster sorption kinetics and reached the apparent equilibrium more quickly in the following lon g - term sorption phase. The sorption kinetics prior to the apparent sorption equilibrium were well fitted by the Weber - Morris intraparticle diffusion model for all tested biochars ( R 2 = 0.940 0.998 ) ( Table 4. 3). The K id and C id values were in the range of 2 5.3 166 day and 39.0 339 , respectively. Table 4.3. Fitted parameters of the intraparticle diffusion model for the long - term sorption kinetics of lincomycin by the biochars . a Samples t ref K id C id R id R 2 day day BM 300 30 166 90.6 0.903 0.940 BM400 180 61.7 137 0.852 0.989 BM500 365 43.2 115 0.876 0.998 BM600 180 55.3 180 0.801 0.996 DM300 90 109 53.5 0.946 0.944 DM400 300 50.5 145 0.847 0.975 DM600 90 88.6 205 0.789 0.972 PM300 240 54.1 68.6 0.924 0.984 PM40 0 365 25.3 39.0 0.928 0.975 PM500 365 35.1 162 0.807 0.993 PM600 180 49.4 262 0.719 0.994 RDM500 180 62.1 162 0.829 0.983 DDM500 180 62.9 209 0.789 0.982 DDM600 180 44.8 339 0.625 0.977 CDM500 365 42.4 124 0.864 0.994 CDMW500 300 47.5 162 0.824 0.98 7 WW500 240 48.4 211 0.768 0.989 a t ref : the longest time used when fitting the intraparticle diffusion model; K id : the intraparticle diffusion rate constant; C id : the intercept constant; and R id : the intraparticle diffusion factor. Interestingly, the C id values showed a positive linear relationship ( Figure 4. 6 a), while the K id values exhibited a U - shaped relationship with increasing pyrolysis temperature from 300 to 600 °C ( Figure 4. 6 b). For example, the average C id values increased monotonically from 70.9 ± 18.7 , 107 ± 59 and 164 ± 37 to 247 ± 71 , whereas the K id values followed the order of 300 °C (110 ± 56 day ) > 600 °C (59.5 ± 19.8 day ) > 500 109 °C (48.8 ± 10.3 day g day ) for the biochars produced at 300, 400, 500, 600 °C, respectively. As the C id values represent the initial surface sorption, this positive linear trend was expected because of the greater external surface area of higher - temperature biochars t han that of lower - temperature biochars. Furthermore, the observed U - shaped relationship between K id and pyrolysis temperature was unique, which cannot be explained by any measured physicochemical properties of biochars. The greater K id of the higher - temper ature biochars might result from more open and less blocked micropores ( Figure 4. 3 and Table 4. 2). However, the greater K id for the lower - temperature (300°C) biochars may be controlled by different mechanisms as elucidated later. The R id values could refl ect the relative contribution of initial sorption and intraparticle diffusion to the total sorption. The R id values closer to one indicate a dominant contribution from the intraparticle diffusion, whereas the R id values closer to zero imply a primary contr ibution of initial sorption. According to Wu et al., 73 the lincomycin sorption kinetics of BM300, DM300, PM300, and PM400 could be classified as a weak initial sorption and strong intraparticle diffusion (1.0 > R id > 0.9). For the rest of the biochars produced at 400, 500, and 600 °C, the lincomycin sorption kinetics could be classified as intermediate initial sorption and intraparticle diffusion (0.9 > R id > 0.5). The R id of all tested biochars ranged from 0.625 to 0.946, showing a negative correlation with pyrolysis temperature ( Figure 4. 6 c). Thus, the relative contribution of initial sorption was more pronounced for the high - temperature biochars, presumably due to their greater SSA. As lincomycin exists as neutral species (~100%, pKa = 7.6) in aqueous solution under - electron donor or acceptor moieties ( Table 4. 1), lincomycin sorption to biochars was unlikely due to hydrophobic partition, electrostatic and - EDA interactions. 92 Therefore, H - bonding, van der Waals forces, and pore diffusion could 110 reasonably be considered as possible mechanisms con tributing to lincomycin sorption on biochars. 92 Because lower - temperature biochars contained more oxygenic functional groups and lower SSA a nd micropore volume than higher - temperature biochars, the contribution of H - bonding may be more important for lincomycin sorption to the low - temperature biochars, whereas the van der Waals interaction may be more important for the high - temperature biochars . However, the different relative contribution of H - bonding and van der Waals interactions in lincomycin sorption still cannot explain why the greater K id values were observed for the low - temperature biochars than for the intermediate - temperature biochars. To further examine possible mechanisms for this observation, we hypothesized that the release of DOC from biochars may play an important role in lincomycin sorption by biochars. As shown in Figure 4. 7 , the leachable DOC concentrations generally increased with decreasing pyrolysis temperature due to the higher labile carbon fraction. The biochars produced at 300 400 °C generally had greater leachable DOC content than the biochars produced at 500 600 °C with the exception of biochar from DDM feedstock. Thus , the continual and significant release of DOC from lower - temperature biochars probably enhanced their lincomycin sorption during the long - term sorption period by increasing the accessibility of internal pores that were initially blocked by DOC. To further investigate the observed enhancement of lincomycin sorption to the biochars of higher DOC concentration, more experiments were performed as discussed later. 111 Figure 4.4. Long - term kinetics of lincomycin sorption by biochars. The sorption data were fitt ed by the intraparticle diffusion model (solid line), and the hollow data were excluded from the fitting because of reaching sorption saturation. 112 Figure 4.5. Sorption kinetics (a) and isotherms (b) of lincomycin to graphite. The solid lines were fitte d by the pseudo - second - order model and the Freundlich model, respectively. 113 Figure 4.6. The relationship of (a) intraparticle diffusion rate constant ( k id ), (b) initial sorption ( C id ), and (c) interparticle diffusion factor ( R id ) versus pyrolysis tempera ture for 17 biochars. 114 Figure 4.7. Long - term release of dissolved organic carbon from biochars. 115 The quasi - equilibrium isotherms of lincomycin to the 17 biochars with contact time of 1, 7, 30, and 365 days were all nonlinear and exhibited a concave - downward shape ( Figure 4. 8 and 4.9 ). All quasi - equilibrium isotherm data could be fitted reasonably well to the Freundlich model ( Table 4. 4). As expected, for all biochars the K f values increased, but the N values decreased with inc reasing equilibration time. For example, the N values decreased from 0.727 at 1 day to 0.424 at 30 days for BM300 and from 0.510 at 1 day to 0.325 at 365 days for BM600 ( Figure 4. 8 a and 4.8 d). The lower N values (i.e., more nonlinear) observed at the longe r equilibration time indicates a more heterogeneous distribution of the sorption sites in the biochars, which could be explained by the greater contribution of intraparticle pore diffusion allowing lincomycin molecules to interact with more heterogeneous p ore space and sorptive sites. As a comparison, the sorption isotherms of lincomycin for the nonporous graphite at 1 day and 30 days were almost identical with similar K f and N values due to the absence of intraparticle diffusion ( Figure 4. 5 ). This result f urther confirmed that the observed time - dependent lincomycin sorption isotherms were caused by increasing contribution of intraparticle diffusion. Similar to the kinetic sorption data, there was an equilibration - time - dependent relationship between K f or N values and pyrolysis temperature ( Table 4. 4 and Figure 4. 10 ). The K f values exhibited a positive linear relationship with pyrolysis temperature increasing from 300 to 600 °C for the equilibration time of 1 day, but gradually became the U - shaped relationshi p as the equilibration time increased to 7 and 30 days ( Figure 4. 10 a). The N values exhibited a negative linear relationship with increasing pyrolysis temperature from 300 to 600 °C for the equilibration time of 1 day, but again gradually became an inverte d U - shaped relationship as the equilibration time increased to 7 and 30 days ( Figure 4. 10 b). The positive and negative linear relationship for 116 K f and N with pyrolysis temperature at 1 day suggests that the lincomycin sorption to biochars became greater and more nonlinear at higher pyrolysis temperature, presumably due to greater SSA and more heterogeneous surface sorption sites. 39 More interestingly, at the longer equilibration time, the lower - temperature (i.e., 300 °C) biochar had greater sorption affinity and non linearity, likely resulted from enhanced intraparticle pore diffusion facilitated by the increasing release of DOC. Table 4.4. Fitted parameters of the Freundlich model for quasi - equilibrium sorption isotherms of lincomycin on the biochars at 1, 7, 30, an d 365 days . a Samples 1 - d 7 - d 30 - d 365 - d K F N R 2 K F N R 2 K F N R 2 K F N R 2 BM300 1.49 0.727 0.945 30.3 0.554 0.974 237 0.424 0.955 n/a n/a n/a BM400 1.64 0.691 0.942 5.54 0.626 0.943 10.4 0.572 0.893 454 0.290 0.920 BM500 4.54 0.556 0.874 7.21 0.524 0.97 6 12.2 0.514 0.952 73.0 0.483 0.958 BM600 7.57 0.510 0.961 16.4 0.480 0.962 26.9 0.460 0.971 282 0.325 0.924 DM300 0.827 0.690 0.873 22.0 0.513 0.951 65.9 0.459 0.887 n/a n/a n/a DM400 2.51 0.609 0.854 4.10 0.590 0.957 13.6 0.537 0.969 146 0.480 0.957 DM600 10.3 0.483 0.895 38.0 0.397 0.915 104 0.369 0.966 n/a n/a n/a PM300 1.39 0.688 0.922 4.68 0.599 0.946 8.37 0.552 0.959 215 0.407 0.957 PM400 1.21 0.559 0.858 3.22 0.531 0.889 6.44 0.531 0.968 20.5 0.524 0.978 PM500 4.86 0.541 0.939 11.2 0.490 0.95 2 19.5 0.476 0.966 89.7 0.402 0.929 PM600 12.5 0.493 0.907 18.9 0.479 0.971 45.6 0.414 0.931 312 0.348 0.914 RDM500 6.05 0.519 0.876 14.3 0.479 0.919 29.4 0.456 0.946 359 0.367 0.912 DDM500 6.76 0.554 0.905 12.9 0.513 0.973 38.2 0.413 0.922 n/a n/a n/a DDM600 15.4 0.482 0.917 22.7 0.479 0.957 46.4 0.435 0.970 302 0.340 0.915 CDM500 3.25 0.543 0.791 8.30 0.523 0.954 14.2 0.516 0.962 77.1 0.478 0.915 CDMW500 4.10 0.540 0.834 9.38 0.511 0.947 19.4 0.498 0.935 127 0.434 0.930 WW500 5.66 0.525 0.860 19.8 0.438 0.926 40.2 0.415 0.927 187 0.403 0.915 a K F : Freundlich sorption coefficient ( g 1 N g 1 L N ); N : Freundlich heterogeneity factor; and n/a: fitted parameters were not available because the concentrations of lincomycin in solution were below detection limit. 117 Figure 4.8. Quasi - equilibrium sorption isotherms of lincomycin by bull ma nure - based biochars produced at different temperature: (a)BM300, (b) BM400, (c) BM500, and (d) BM600. K F ( g 1 N g 1 L N ) is the Freundlich sorption coefficient, and N (dimensionless) is the Freundlich nonlinearity factor. 118 Figure 4.9. Quasi - equilibrium so rption isotherms of lincomycin to biochars: (a) DM300, (b) DM400, (c) DM600, (d) PM300, (e) PM400, (f) PM500, (g) PM600, (h) RDM500, (i) DDM500, (j) DDM600, (k) CDM500, (l) CDMW500, and (m) WW500. The solid lines were fitted with the Freundlich isotherm mo del. 119 Figure 4.10. The relationship of Freundlich sorption coefficient ( K F ) and Freundlich nonlinearity factor ( N ) versus pyrolysis temperature for biochars. 120 We first hypothesized that lincomycin might bind with the DOC in so lution. If so, the lincomycin sorption to biochars could be overestimated when the DOC - bound lincomycin was included into the lincomycin sorption to biochars. At the initial lincomycin concentration of 1000 µg/L, 15, 6.0, 5.8, and 3.0 % of initially applie d lincomycin was bound to DOC - BM300, DOC - DM300, DOC - PM300, and DOC - DDM500 of 186, 93.8, 97.4, and 89.6 mg - C L 1 , respectively. The distribution coefficients of lincomycin to DOC - BM300, DOC - DM300, DOC - PM300, and DOC - DDM500 were 955, 686, 631, and 348 L kg - C 1 , respectively. Based on the DOC release kinetics ( Figure 4. 7 ), the DOC concentrations from 1 day to 365 da ys in the kinetic sorption experiments were 10.5 84.1, 6.35 51.9, 17.2 41.6, and 10.0 54.9 mg - C L 1 for BM300, DM300, PM300, and DDM500, respectively. Even assuming all released DOC could bind with lincomycin in solution, the fraction of the DOC - bound linc omycin was only 0.9 6.8%, 0.4 3.3%, 1.0 2.5%, and 0.3 1.9% of the initially applied amount for DOC - BM300, DOC - DM300, DOC - PM300, and DOC - DDM500, respectively. Therefore, the contribution of lincomycin sorption to DOC in solution could not explain the enhanc ed lincomycin sorption to biochars over time. Secondly, we hypothesized that the DOC as co - solute in solution might facilitate the lincomycin sorption to biochars. However, the presence of DOC as co - solute actually inhibited the lincomycin sorption onto WW 500 ( Figure 4. 11 ). Comparing with lincomycin sorption kinetics without DOC, the fitted K id 1 day 0.5 and the fitted C id 1 in the presence of DOC ( Table 4. 5). The extent of sorption suppression followed the order of DOC - - PM300 > DOC - DM300 > DOC - DDM500, which generally (but not completely) agreed with the DOC concentration trend (DOC - BM300 > DOC - DM300 > DOC - DDM500 > DOC - PM300). Thus, the inhibitory effect of 121 DOC in solution depends on not only the concentration, but also the chemical composition of DOC. The observed slower diffusion rate and lower initial sorption confirmed that the DOC could not enhance the lincomycin sorption by itself. In contrary, the DOC in solution strongly suppressed the lincomycin sorption by blocking the pore entrances (i.e., decreased K id ) and/or by competing for the external surface sorption sites (i.e., decreased C id ) in biochars. Table 4.5. Fitted parameters of the intraparticle diff usion model for the sorption kinetics of lincomycin by woodchip waste biochar. a Samples t ref K id C id R id R 2 day day WW500+DI 60 55.2 178 0.705 0.997 WW500+DOC(BM300) 60 13.3 80.3 0.535 0.678 WW500+DOC(DM300) 60 29.1 70.5 0.767 0.9 51 WW500+DOC(PM300) 60 15.0 71.1 0.598 0.743 WW500+DOC(DDM500) 60 23.1 85.6 0.648 0.931 a t ref : the longest time used when fitting the intraparticle diffusion model; K id : the intraparticle diffusion rate constant; C id : the intercept constant; and R id : t he intraparticle diffusion factor. We finally tested the hypothesis in that the long - term release of DOC might gradually increase the accessibility of sorption sites on the external surface and in the biochar pore structure, thus enhancing their sorption ability for lincomycin. Therefore, the sorption kinetics of lincomycin by raw, 40 - day - DI - washed, and 1 - day - NaOH - washed biochars (selected BM300, DM300, PM300, DDM500, BM600) were analyzed ( Figure 4. 12 , Figure 4. 13 and Table 4. 6). Apparently, the removal of DOC from the biochars (BM300, DM300, PM300, and DDM500) substantially enhanced the lincomycin sorption kinetics ( Figure 4. 12 ), and the DOC removal with NaOH solution was more effective than that with DI water for the enhancement of sorption kinetics ( Figu re 4. 12 ). In addition, the fitted K id and C id values both increased after the DOC removal for these tested biochars ( Table 4. 6). For example, the K id 1 day 0.5 and the C id 1 for BM300 - Ra w, BM300 - DI, and BM300 - NaOH biochars, respectively. The enhancement of lincomycin sorption kinetics by the DOC removal was 122 very limited for BM600 ( Figure 4. 12 c). Considering that BM600 was highly carbonized, and had a relatively low DOC content and rigid p ore structure, the DOC removal would not substantially alter the surface sorption sites and pore structure of BM600, resulting in minimal enhancement of the sorption kinetics. Furthermore, a close examination of SEM images revealed that the biochar particl es of low - temperature biochars (e.g., BM300) were disintegrated, and the biochar particle size appeared to decrease after aging in 0.02 M background solution for 365 - d and in 0.1 M NaOH solution for 1 - d, presumably because of the DOC release from the bioch ars ( Figure 4. 14 ). We further compared the size of biochar colloids by aging BM300 and BM600 biochars in either 0.1 M NaOH or 0.1 M NaCl solution ( Figure 4. 1 5 ). The size of biochar colloids was much smaller in 0.1 M NaOH than in 0.1 M NaCl for BM300, where as no obvious difference was observed for BM600. In summary, these results supported that the release of DOC from biochars could enhance the lincomycin sorption on biochars because of increased accessibility of sorption sites initially blocked by DOC on th e external surface and in pore structure as well as decreased biochar particle sizes. Table 4.6. Fitted parameters of the intraparticle diffusion model for the sorption kinetics of lincomycin by raw - , DI - water - washed, and 0.01M - NaOH - washed biochars. a Sampl es t ref K id C id R id R 2 day day BM300 - Raw 30 160 87.9 0.904 0.968 BM300 - DI 15 166 285 0.694 1.000 BM300 - NaOH 7 176 527 0.460 0.985 DM300 - Raw 60 113 49.8 0.945 0.984 DM300 - DI 30 148 99.1 0.894 0.990 DM300 - NaOH 10 172 381 0.587 1. 000 PM300 - Raw 60 51.3 83.1 0.831 0.995 PM300 - DI 60 68.1 131 0.811 0.976 DDM500 - Raw 60 74.1 164 0.781 0.994 DDM500 - DI 60 98.5 191 0.800 0.999 BM600 - Raw 60 53.8 174 0.710 0.993 BM600 - DI 60 52.2 175 0.705 0.983 BM600 - NaOH 60 55.9 203 0.685 0.996 a t re f : the longest time used when fitting the intraparticle diffusion model; K id : the intraparticle diffusion rate constant; C id : the intercept constant; and R id : the intraparticle diffusion factor. 123 Figure 4.11. The effect of DOC as co - solutes on sorption k inetics of lincomycin by WW500 biochar (WW500+DI was the control of absence DOC). 124 Figure 4.12. Long - term kinetics of lincomycin sorption by raw and DOC - washed biochars. The sorption data were fitted by intraparticle diffusion model (solid line). 125 Figu re 4.13. Long - term kinetics of lincomycin sorption by raw and DOC - washed biochars. The sorption data were fitted by the intraparticle diffusion model (solid line) and the hollow data were excluded because of approaching sorption saturation. 126 Figure 4.14. Scanning electron microscopy images of bull manure biochar pyrolyzed at 300°C (BM300): (a) raw BM300 without treatment, (b) BM300 after 1 - d background solution exposure, (c) BM300 after 365 - d background solution exposure, and (d) BM300 after 1 - d 0.1M NaOH solution exposure. Background solution contained 1000 g L 1 lincomycin, 6.7 mM NaCl, 2.5 mM Na 2 CO 3 , 2.5 mM NaHCO 3 , and 200 mg L - 1 NaN 3 . 127 Figure 4.15. Particles size distribution of (a) bull manure biochar pyrolyzed at 300°C (BM300) and (b) bull manure biochar pyrolyzed at 600°C (BM600) suspended in 0.1 M N aCl (upper panel) or in 0.1 M NaOH (lower panel) after one - day exposure. 128 As shown in Figure 4. 1 6 a, the extraction recoveries of lincomycin for all tested biochars were generally low. The degree of desorption hysteresis varied among t he biochars, with the extraction recoveries ranging from the lowest of 0.02% for BM300 to the highest of 24.7% for PM500. Thus, the long - term sorbed lincomycin on the biochars was highly resistant to desorption. In addition, the extraction recoveries exhib ited a negative logarithmic correlation with the K id ( R 2 = 0.721) ( Figure 4. 1 6 b), implying that faster pore diffusion would cause stronger desorption hysteresis. This observation was presumably because lincomycin could diffuse deeper into the biochar pores and become trapped in the narrower pores, resulting in lower extraction efficiency. From the standpoint of soil biochar amendment for contaminant immobilization, the observed strong sorption/desorption hysteresis for lincomycin may be desirable because th e sorbed lincomycin would tend to remain within the biochars over the long term, thus reducing the mobility and bioavailability of lincomycin in soils. 129 Figure 4.16. (a) Extraction efficiency of 240 d - sorbed lincomycin in the biochars and (b) the relati onship of intraparticle diffusion rate constant ( K id ) versus lincomycin extraction efficiency for biochars. 130 We have previously proposed that sequestering manure - borne antibiotics in soils by biochars produced from animal manure may be a novel mitigation strategy for managing animal manures and manure - borne antibiotics. 92 On one hand, using manure as feedstock to produce biochars could destroy any microbial pathogen and antibiotics via pyrolysis (i.e. 300 to 600 °C). On the other hand, the produced biochars could be applied in soils to reduce the mobility and bioavailability of anthropogenic antibiotics. Under the same tested conce g L 1 ), the observed K f g 1 N g 1 L N g 1 N g 1 L N ) were greater than the previously reported K f g 1 N g 1 L N ) 85 . The release of DOC from biochars via aging could even enhance the sorption of antibiotics. Coupled with the strong irreversible sorption, biochars could be promising soil amendments for enhancing both short - and lo ng - term sequestration of antibiotics and reducing the mobility and bioavailability of antibiotics in soils. 131 CHAPTER V BLACK CARBON NANOPARTICLES FACILITATED TRANSPORT OF ANTIBIOTICS IN SATURATED SAND 132 Black carbon (BC) nanoparticles are ubiquito us in nature. However, the impact of BC nanoparticles on the transport of environmental contaminants has not been well studied. This study investigated the possible facilitated transport of three antibiotics (lincomycin, oxytetracycline, and sulfamethoxazo le) by BC nanoparticles in saturated sand columns at solution pH of 7, and ionic strength of 0.1, 1, and 10 mM. The transport of BC nanoparticles de creased with increasing ionic strength, in agreement with the XDLVO energy calculations. In the absence of B C nanoparticles, lincomycin transport increased with increasing ionic strength, whereas there was no effect of ionic strength on the transport of sulfamethoxazole and oxytetracycline. Under all tested ionic strength levels, all of the injected sulfamethoxa zole was conservatively transported through the column, while all of the injected oxytetracycline was retained. In the presence of BC nanoparticles, the BC nanoparticles facilitated the transport of oxytetracycline with the effluent mass recovery of 1.9 76 .7% of the injected mass, but decreased the transport of sulfamethoxazole (4.6 89.6% effluent mass recovery) under all ionic strengths. The lincomycin transport was enhanced at 0.1 mM ionic strength, but decreased at 1 mM and 10 mM ionic strengths, with mu ch earlier breakthroughs under all ionic strengths. The BC - facilitated transport of antibiotics decreased with increasing ionic strength due to enhanced deposition of BC nanoparticles at greater ionic strength s . O verall, o ur results suggest that the facili tated transport of antibiotics by BC nanoparticles is likely and would occur under rainfall or irrigation with low - salinity water. 133 Black carbon (BC) is a group of pyrogenic carbonaceous materials produced from thermal decomposition of biomas s, organic wastes, and fossil fuel under oxygen - free or - limited conditions, ranging from slightly charred biomass to highly condensed aromatic and elemental carbon. It includes a variety of materials such as biochar, charcoal, carbon black, activated carb on, soot, etc. The common sources of BC are wildfires, vehicle emissions, burning of crop residues, and bioenergy pyrolysis. 164 accounting for 3.8 7.7% of global soil organic carbon (SOC) pool (54 109 Pg), 5 15% of the SOC flux in terrestrial sediments (29 87 Tg yr 1 ), as well as 19 80 Tg yr 1 of particulate BC and 24.7 28.3 Tg yr 1 of dissolved BC in the global riverine fluxes to oceans , 17 where dissolved BC is often operationally defined as a size fraction less than 0.45 or 0.70 µm. 17 A large portion of dissolved BC may be actually prese nt in the form of nanoparticles with at least one dimension less than 100 nm. For example , carbon black (typically ranging 10 500 nm) is a BC material widely used as filler in rubber, plastic film, and ink pigment, with an annual global production of over 10 million tons (i.e., 9.7 Tg yr 1 ). 165 - 167 After the product with the BC is disposed of or degraded , the engineered BC nanoparticles are eventually be released into the environment. It has been was reported that the BC in urban runoff contribute d significantly to the BC flux to streams and lakes. For example, in Lake Tahoe, this BC flux typically ranged between 1 for highway stormwater runoff samples, which likely resulted from vehicle emission and tire wear. 168, 169 In addition to engineered BC nanoparticles, it is well known that many BCs are not completely inert, but consist of a range of materials that can be transformed, degraded, and mineralized to varying degrees. 17, 170, 171 This BC can originally contain fine particles, or physically disintegrate and decrease in size to produce nano - and colloidal - particles 134 over time. 62, 102, 172, 173 For example, after ultrasonication the mass percentage of micron - sized biochars (0.1 2 µm) was about 4.3 6.5%, and that of nano - sized biochars was about 1.6 2.6%, respectively. 62 Spokas et al. 102 also reported that the percentage of micron - or submicron - sized biochars ranged from 1.0% to 47% for a variety of biochars, whereas Qu et al. 172 found that the percentage of 0.45 1 µm biochars was about 1.1 1.2% for the rice and bamboo biochars. Due to the prevalence of BC colloids and nanoparticles in nature, a number of recent studies have fo cused on the aggregation and transport of BC colloids and nanoparticles in soil and water systems. 63, 173, 174 The BC nanoparticles tend to aggregate to various degrees in aqueous suspension, depending on BC surfac e property and solution chemistry. 175 - 180 The BC nanoparticles with more oxygenic and hydrophilic surface functional groups are more s table in suspension than pristine BC nanoparticles. 181 Aggregation of BC nanoparticles is enhanced at higher ionic strength, lower solution pH and in the presence of multivalent cations (such as Ca 2+ ) due to reduced electrostatic repulsion. 179, 180 Whereas, n atural organic matter and anionic surfactants in solution often inhibit the aggregation of BC nanoparticles. 176, 177, 181 Aggregation of BC nanoparticles can s ubstantially influence their transport in aquatic systems and their transport in the subsurface such as soils, sediments, and groundwater aquifers. 175, 182 The subsurface transport of BC nanoparticles is also depen dent on properties of BC nanoparticles and porous media, and solution chemistry. R ecent work found that the transport of BC colloids through quartz sand decreased with increasing pyrolysis temperature, BC particle size, and iron oxide coating of sand surfa ce, but increased with concentrations of natural organic matter and surfactants. 62, 63, 173, 177 Higher ionic strength and lower solution pH often increase the retention of BC nanoparticles in porous media, 183, 184 due to enhanced aggregation of BC nanoparticles as well as increased attraction between the BC 135 nanoparticles and grain surfaces. Overall, the BC nanoparticles are more mobile in the subsurface than micron - sized an d bulk BC particles. As the BC particles interact with many other contaminants in the environment, it becomes important to examine the association of BC nanoparticles with other contaminants and how BC nanoparticles can facilitate contaminant transport. A m endment s of BC to soils (e.g., biochar) is being proposed for many agronomic and environmental benefits, including improved soil characteristics (e.g., improved soil structure, reduced bulk density, and enhanced water and nutrient retention), decreased gre enhouse gas emission, and in - situ immobilization of contaminants such as excess nutrients, organic pollutants, and trace metals. 25, 29, 93, 185, 186 However, the possibility of and quantification of contaminant tra nsport that may be facilitated by BC nanoparticles is needed as it is important to determining the overall effectiveness of the BC - based remediation strategy. Hence, i n this study, we focused on the interaction of BC nanoparticles with anthropogenic antibi otics transport in porous media . A nthropogenic a ntibiotics are extensively used in human health care and animal agriculture, resulting in the prevalent presence of antibiotics in soil and water environment. 15, 187 - 1 89 Antibiotics are now considered as emerging contaminants. They vary substantially in their physicochemical properties such as molecular size, pH - dependent charge speciation and hydrophobicity, and consequently their sorption behaviors in the environment . 9, 188 - 190 For example, tetracyclines are highly sorptive, but sulfonamides are very mobile in soils and sediments. 9, 190 Recent studies have revealed that BC has strong s orption affinity to antibiotics. 40 Considering the high mobility of BC nanoparticles, they could potentially function as a carrier to facilitate the transport of antibiotics in the soil and water systems. Therefore , it is essential to understand how BC nanoparticles may influence the transport of antibiotics in the subsurface , which has not been fully studied . 136 This study aimed to elucidate the transport of three representative antibiotics, i.e., lincomycin (LCM), ox ytetracycline (OTC) and sulfamethoxazole (SMX) in saturated sand at ionic strength of 0.1, 1, or 10 mM KCl and solution pH of 7.0, as influenced by the presence of BC nanoparticles. Sorption of LCM, OTC, and SMX to BC nanoparticles and sand was characteriz ed using batch sorption experiments. Their transport through saturated sand columns with and without BC nanoparticles was measured by solute transport experiments in combination with numerical modeling. These column experiments and model results could give some of the first insights into understanding the transport of common antibiotics facilitated by BC nanoparticles in soils . sulfamethoxazole (analytical standard grade) were purchased from Sigma - Aldrich (St. Louis, MO, USA). The molecular structures and selected physicochemical properties of LCM, OTC, an d SMX are listed in Table 5. 1. The three antibiotics vary in their molecular weight and pKa, thus their pH - dependent charge speciation and representing mostly cations (LCM, 80%), zwitterion (OTC, 74%), and anion (SMX, 95%) at experimental solution pH of 7. 0 ( Table 5.1) . These antibiotics - Aldrich) to prepare the stock solutions of 100 mg L 1 . The stock solutions were stored in darkness in a refrigerator prior to use. Deionized (DI) water from a Milli - Q water system (Millipore, Billerica, MA, USA) was used to prepare all J.T. Baker) was applied as a conservative tracer in column experiments to quantify hydrologic 137 transport conditions of each experiment . Dilute hydrochloric acid (HCl, Merck) and potassium hydroxide (KOH, J.T. Baker) solutions were used to adjust solution pH. Table 5.1. Physicochemical properties of lincomycin, oxytetracycline, and sulfamethoxazole . Antibiotics Chemical Structure a Molecular weight b (g/mol) Solubility b (mg/L) p K a b Speciation (at pH 7.0) Lincomycin 406.54 927 7.6 Cation (80%) Neutral (20%) Oxytetracycl ine 460.43 313 3.2; 7.5; 8.9 Zwitterion (74%) Anion (26%) Sulfamethoxazole 253.28 610 1.6; 5.7 Neutral (5%) anion (95%) a Data from ChemSpider ( http://www.chemspider.com/ ); b Data from TOXNET ( http://www.toxnet.nlm.nih.gov/ ) Porous carbon nanoparticles were obtained from US Research Nanomaterials Inc. (> 95% carbon, US1075, Houston, Texas, USA), and used as the model BC nanoparticles in this s tudy. These nanoparticles were produced from perennial mountain bamboo and holly trees, and the 727 ± 24 m 2 g 1 determined by the N 2 adsorption at 77K on a Micromeritics ASAP 2020 analyzer (Micromeritics, Norcross, GA, USA). The stock suspension of BC nan oparticles at 2 0 mg L 1 was prepared by mixing 4 0 mg of the BC nanoparticle powder with 2 L of DI water in a glass bottle, followed by ultrasonication in a water bath sonicator (FS140, Fisher Scientific, Pittsburgh, PA, USA) for 8 h. The prepared stock sus pension was ultrasonicated daily for 20 min to maintain the 138 dispersion of BC nanoparticles. Scanning electron microscopy (SEM, JEOL, JSM - 7500F, Tokyo, Japan) images of the BC nanoparticles showed irregular - shaped aggregates formed by primary nanoparticles ( Figure 5. 1). The hydrodynamic diameter ( D h ), zeta potential, and electrophoretic mobility (EPM) of BC nanoparticles suspensions in identical background solution chemistry to that in column transport experiments (i.e., initial antibiotic concentration of 0 or 100 µ g L 1 , BC concentration of 10 mg L 1 , ionic strength of 0.1, 1, or 10 mM KCl, and pH of 7.0 ± 0.2) were determined using a Zetasizer Nano - ZS (Malvern Instrument, Westborough, MA, USA). The BC suspension were sonicated for 20 min prior to the D h , z eta potential, and EPM measurements. Aggregation kinetics of BC nanoparticles at ionic strength of 0.1, 1, or 10 mM and pH of 7.0 was determined by measuring D h over the first 120 min with time step of 10 s after 20 min sonication. Figure 5.1. Scanning electron microscopy images of BC nanoparticles prepared from stock suspensions. 139 Ottawa sand (99.69% silica, Granusil 4020, Unimin Corporation, Le Seueur, MN, USA) used in this study . It was first sequentially with 20 mM KCl solution and DI water to remove fine particles. This washing step was repeated until turbidity was no longer visually observed in the DI water. The cleaned sand was further rinsed with DI water several times, and then oven - dried and stored in a bottle prior to use. To characterize surface potential of sand surface, sand colloid suspension was generated, following the previously established method , 191 which is b riefly summarized here. First , 20 g of sand grains were ultrasonicated in 20 mL DI water for 30 min to generate sand colloids. Th is sand colloidal suspension was t hen passed through a 0.45 - µm filter and the filtrates were mixed with KCl solution at ionic strength to 0.1, 1, or 10 mM and solution pH of 7.0. The prepared sand colloidal suspensions were then used to determine the zeta potentials of the sand colloids si milar to the sand surface potentials. 192 The sorption kinetic s and isotherms of LCM, OTC, and SMX on the BC nanoparticles and the Ottawa sand were measured in glass vials with polytetrafluoroethylene (PTFE) lined screw - caps and aluminum foil covered. All batch sorption experiments were performed in duplicate at room temperature (23 ± 1 °C) in the dark . The working solutions of the three antibiotics were freshly prepared by diluting the stock solutions with DI water and KCl solutions to desired antibiotic concentrations (100 to 1000 µg L 1 ) and ionic strengths (0.2, 2 , and 20 mM). After 20 min ultrasonication, aliquots of the stock suspensions were withdrawn as the working suspensions of BC nanoparticles. The sand and water mixtures were prepared by mixing 20 g sand in 10 mL 140 DI water. All antibiotic solutions, BC nanop article suspensions, and the mixture of sand and water were adjusted to pH of 7.0. Kinetic sorption experiments were conducted following the similar procedure as sorption isotherm experiments detailed below, except for different initial antibiotic concentr ation (i.e. 100 µg L 1 ) and different contact time s (from 10 min to 8 h). The sorption of all three antibiotics on both the BC nanoparticles and the Ottawa sand occurred rapidly and reached equilibrium within 10 min for the BC nanoparticles and about 60 mi n for the sand ( Figure 5. 2). Therefore, the contact time of 2 h was determined for the following sorption isotherm experiments to ensure complete reactions. For sorption isotherm experiments, 10 mL of BC nanoparticle working suspensions (20 mg L 1 ) or sand - water mixtures (2 kg L 1 ) was mixed with 10 mL of LCM, OTC, or SMX working solution to reach initial antibiotic concentrations of 50 to 500 µg L 1 , ionic strength of 0.1, 1, or 10 mM, pH of 7.0 ± 0.2, and sorbent - water ratio of 10 mg L 1 for BC nanopartic les and 1 kg L 1 for sand, respectively. These mixtures were horizontally shaken at 200 rpm in an incubator shaker (C24, New Brunswick Scientific NJ, USA) for 2 h. After equilibration, 2 mL of suspensions was pipetted into 2 mL microcentrifuge tubes. The t ubes were centrifuged at 13793 × g for 10 min, and then the top 1 - mL of supernatants were carefully collected. The concentrations of LCM, OTC, or SMX in the supernatants were determined by a Shimadzu Prominence high - performance liquid chromatograph coupled with an Applied Biosystems Sciex 4500 QTrap mass spectrometer (LC - MS/MS) as described in the Analytical Methods section . Since the control experiments free of BC nanoparticles or sand showed a negligible loss of antibiotics during the sorption experiments (data not shown), the difference between the initial and final antibiotic concentrations in solutions was assumed to be sorbed by the BC nanoparticles or the sand. 141 Figure 5.2. Sorption kinetics of LCM (a and d), OTC (b and e), SMX (c and f) on BC nano particles and sands under ionic strength (IS) of 0.1, 1 or 10 mM and solution pH of 7.0. Packed column experiments were conducted to investigate the transport of each tested antibiotic (LCM, OTC, or SMX) accompanied with and w ithout BC nanoparticles at three different ionic strength (0.1, 1, and 10 mM) under saturated condition. All column experiments were performed in duplicate. The Ottawa sand (61.4 g) was wet - packed into an Omnifit glass column of 2.5 - cm inner diameter and 7 .3 - cm length (Diba Industries, Danbury, CT, USA) and had a porosity of 0.35. The packed sands were supported by stainless steel filter membrane (104 - µm mesh opening, Spectra/Mesh, Spectrum laboratories, Houston, TX, USA) and sealed by O - rings and PTFE tubi ng connectors on both ends of the column. A MasterFlex L/S peristaltic pump (Cole - Parmer Instrument , Vernon Hills, IL, USA) was connected to the inlet at the top of the column to 142 supply a steady - state downward flow at a flow rate of 1.0 mL min 1 and a pore water velocity of 0.58 cm min 1 . During the transport experiments, each column was first flushed with 20 mM KCl solution for 25 min, followed by flushing with DI water for 25 min. After flushing, the background solution free of either antibiotics, BC nan oparticles, or Br 1 tracer at ionic strength of 0.1, 1, or 10 mM and pH of 7.0 was injected for at least 120 min to condition the column. Meanwhile, the input solutions and suspensions were freshly prepared following the similar procedure as described abov e in the batch sorption experiments. Briefly, the antibiotic - only solutions were prepared by mixing 25 mL of LCM, OTC, or SMX working solutions (initial antibiotic concentrations of 200 µg L 1 and ionic strength of 0.2, 2, or 20 mM) with 25 mL of DI water. The BC nanoparticle suspensions were prepared by mixing 25 mL of BC nanoparticle working suspensions (20 mg L 1 in DI water) with 25 mL of KCl solution (initial concentration of 0.2, 2, or 20 mM). Finally, the mixed suspensions of BC nanoparticles with LC M, OTC, or SMX as co - solute were prepared by mixing 25 mL of LCM, OTC, or SMX working solutions with 25 mL of BC nanoparticle working suspension. All input solutions and suspensions (with initial antibiotic concentrations of 0 or 100 µg L 1 , initial BC nan oparticle concentrations of 0 or 10 mg L 1 , ionic strength of 0.1, 1, or 10 mM, and pH of 7.0 ± 0.2) were shaken for 120 min to reach equilibrium, followed by 20 - min sonication just before injection. The transport experiment was then commenced by instantan eous switching from the background solution to the input solution or suspension as described above . The injection of input solution or suspension continued for 25 min, i.e., about 2 pore volumes (PVs). Afterwards the influent was switched back to the backg round solution for another 75 min (about 6 PVs) to observe flushing and breakthrough curve tailing behavior in the BC and antibiotics . The effluent samples 143 were collected from the column outlet with 2 mL intervals by a Retriever 500 fraction collector (Tel edyne ISCO, Lincoln, NE, USA). To determine dissolved antibiotic concentrations, 1 mL of each influent and effluent samples were pipetted into 1.5 mL microcentrifuge tubes and centrifuged at 13793 × g for 10 min. The top 0.75 mL of the supernatants was th en carefully collected to be analyzed with the LC - MS/MS. To determine the BC nanoparticles concentrations, 1 mL of each influent and effluent samples were measured for the absorbance at wavelength of 550 nm (the calibration curve showed in Figure 5. 3) usin g a Cary 50 Bio UV - Visible Spectrophotometer (Varian Inc., Palo Alto, CA). For the concentrations of antibiotics associated with BC nanoparticles, the preliminary ultrasonic - assisted solvent extraction of sorbed antibiotics was conducted by sonicating the BC nanoparticles in the mixture of 1 - mL 150 mg L 1 ethylenediaminetetraacetic acid solution and 5 - mL acetonitrile/methanol mixture (65/35 by volume) for 30 min. However, the extraction recoveries of antibiotics sorbed on the BC nanoparticles were generally low, i.e., 38.8 ± 0.3, 4.4 ± 0.0, and 32.7 ± 0. 1% for LCM, OTC, and SMX, respectively. Therefore, the BC - associated antibiotic concentrations were calculated by the sorption amounts of antibiotics onto BC nanoparticles and the breakthrough curves (BTCs) of BC nanoparticles in the co - transport experimen ts. Detailed calculation method is provided in the Analytical Method s section . The bromide tracer experiment followed the same protocols with 50 mg L 1 KBr solution as input solution and DI water as background water. The bromide concentrations of effluent samples were determined by the UV absorbance at wavelength of 212 nm. The baseline of effluent background concentrations was subtracted from the effl uent sample concentrations. Finally, the BTCs were plotted as normalized effluent concentrations ( C / C 0 , where C 0 is initial solute concentration) as a function of PVs. 144 Effluent mass recoveries ( M R ) were calculated from the measured BTCs by dividing the rec overed mass in the effluents by the total applied mass. Figure 5.3. Linear regressions between UV - vis absorbance at 550 nm and BC nanoparticle concentrations in suspension . The concentrations of freely dissolved lincomycin (LCM), ox ytetracycline (OTC), or sulfamethoxazole (SMX) in solutions were determined by a Shimadzu Prominence high - performance liquid chromatograph coupled with an Applied Biosystems Sciex 4500 QTrap mass spectrometer (LC - MS/MS). The analytical column was a ZORBAX Eclipse Plus C18 column with 50 mm length × 2.1 mm diameter and 5 µm particle size (Agilent, Santa Clara, CA, USA). The 145 mobile phase A consisted of DI water and 0.3% formic acid. The mobile phase B consisted of 65:35 (v/v) acetonitrile/methanol mixture and 0.3% formic acid. The separation was achieved using a gradient condition of 0 40% B in 0 1.0 min, 40 70% B in 1.0 2.0 min, 70 80% B in 2.0 3.0 min, 80 100% B in 3.0 3.5 min, and then 100% B for 7.2 min. The flow rate was 0.35 mL min 1 and the injection vo ionization mode were used in the tandem quadrupole MS. Antibiotics were detected and quantified using a multiple reaction monitoring mode with a precursor/product transition of 407.2/126.2 for LCM, 426.1/283.1 for OTC, and 254.0/108.1 for SMX. The retention time was 2.6, 2.8, and 3.7 min for LCM, OTC, and SMX, respectively. The concentrations of antibiotics associated with BC nanoparticles were alternatively calculated by the sorption amounts of antibiotics onto the BC nanoparticles and the BTCs of the BC nanoparticles from co - transport experiments. Before the co - transport column experiments, the mixed suspensions of antibiotic and BC nanoparticles were prepared by mixing 25 mL of antibiotic work ing solutions (antibiotic concentrations of 200 µg L 1 and ionic strength of 0.2, 2, or 20 mM KCl) with 25 mL of BC nanoparticle working suspensions (BC concentrations of 20 mg L 1 in DI water) to reach initial antibiotic concentrations ( C 0, anti ) of 100 µ g L 1 , initial BC nanoparticles concentrations ( C 0, BC ) of 10 mg L 1 , ionic strength of 0.1, 1, or 10 mM KCl, and pH of 7.0 ± 0.2. The mixed suspensions were shaken for 120 min to reach equilibrium. Aliquots of suspensions were withdrawn, centrifuged, and measured for the equilibrium concentration of antibiotics ( C e, anti ). The antibiotic sorption amount ( q e ) on the BC nanoparticles were calculate by the difference between C 0 and C e and then divided by C BC . After the co - transport experiments, the BC nanopar ticle concentrations in each collected effluent sample ( C e, BC ) were determined by the UV - Vis spectrometer at 550 nm. Simply assuming that constant q e values (there was no further 146 sorption/desorption) and homogeneous sorption of antibiotics to the BC nanop articles, the mass of sorbed antibiotic concentration ( M BC - anti ) in each effluent could be calculated by sampled effluent volume (0.002 L in this study) times C e, BC (converted unit form mg L 1 to µg L 1 ), and then times q e (µg g 1 ). To calculate the relat ive concentration ( C / C 0 ) for plotting BTCs, the calculated M BC - anti were divided by sampled effluent volume (0.002 L) and then divided by C 0, anti (µg L 1 ). Finally, the mass recoveries of total antibiotic (including dissolved and BC - associated fraction) w ere calculated by integrating M BC - anti from each effluent samples and then division by the total applied mass. The sorption isotherms from the batch experiments were fitted to the Freundlich model: 162 ( 5. 1) where q e ( g g 1 ) is the sorbed antibiotic concentration in the solid phase, C e ( g L 1 ) is the antibiotic concentration in solution, K F ( g 1 N g 1 L N ) is the Freundlich sorption coefficient, and N (dimensionless) is the Fre undlich nonlinearity factor. The BTCs were fitted using the CXTFIT 2.0 code in the STANMOD (version 2.08.1130) to simulate one - dimensional transport and co - transport of BC nanoparticles, LCM, OTC, or SMX. 193, 194 The deterministic equilibrium or nonequilibrium convection - dispersion equation (CDE) was used to fit the experimental BTCs with a zero initial concentration, a pulse - input boundary condition and a zero - concentration - gradient boundary condition at the outlet under the steady flow condition , using the Levenberg - Marquardt optimization algorit hm. The transport of the BC nanoparticles or the bromide tracer was described by an equilibrium CDE with a first - order kinetic deposition term as follows : ( 5. 2) 147 where C B is the effluent concentration of BC nanoparticles or bromide (mg L 1 ), t is the elapsed time (min), D is the hydrodynamic dispersion coefficient (cm 2 min 1 ), x is the travel distance (cm) in the direction of flow , v is the pore water velocity (cm min 1 ), and k d is the first - order deposition rate coefficient (min 1 ). The hydrodynamic propert ies of the columns was first characterized by the conservative bromide BTC ( Figure 5. 4 ) . The k d of the bromide tracer was equal to zero because bromide is nonreactive to the sand, and the fitted D value was 0.025 cm 2 min 1 ( R 2 = 1.00). We then assumed the same D value for all tested column conditions, the k d values were then estimated by fit ting the BTCs of the BC nanoparticles. 195 The transport of LCM, OTC, or SMX and their co - transport with BC nanoparticles were described by a two - site chemical nonequilibrium CDE model. This model assumes that total sorption sites can be divided into equilibrium sorption sites and kinetic sorption sites. Retention on the equilibrium and kinetic sorption sites is assumed to be instantaneous and time - dependent, respectively. The model can be described in the dimensionl ess forms below: ( 5. 3) ( 5. 4) 148 where is the partitioning coefficient for the equilibrium and kinetic sorption sites, R is the retardation factor, C 1 and C 2 are the normalized effluent concentrations associated with the equilibrium and k inetic sorption sites, respectively, T is the dimensionless elapsed time , P is the Peclet number, Z is the dimensionless travel distance , is the dimensionless mass transfer coefficient, is the volumetric water content, f is the fraction of equilibrium sorption sites in total sorption sites, K d is the distribution coefficient for linear sorption isotherms (cm 3 g 1 ), is the first - order kinetic rate coefficient ( min 1 ), b is the bulk density (g cm 3 ) of the sand column, and L is the column length (cm). To fit the BTCs of total LCM, OTC, or SMX (including both the dissolved and BC - associated fraction in the effluents) , the same D value ( 0.025 cm 2 min 1 ) was applied, and the parameters of R , , and were then estimated. Figure 5.4. Measured and fitted breakthrough curve of the bromide tracer through saturated sand column. Symbols are experimental data and lines are fitted result. 149 The extended Derjaguin - Landau - Verwey - Overbeek (XDLVO) interaction energies were calculated as the sum of Lifshitz - van der Waals (LW), Lewis acid - base (AB), electrical double layer (EL), and Born repulsion (BR) interactions for the BC nanoparticles interacting with sand XDLVO ) as a function of separation distance ( x ) was calculated via: (5. 11 ) The LW interaction energy per unit area ( ) for a surface (1) interacting with another surface (2) through a medium (3) can be determined as: 196 (5. 12 ) where is the apolar component of LW interaction of surface 1 (e.g., BC), and is the LW component of surface 2 (e.g., quartz sand), and is the LW component of water. The Hamaker constant ( ) was then calculated as: 197, 198 (5. 13 ) where x 0 (0.158 nm) is the minimum equilibrium distance at which two condensed - phase surfaces are in contact. The calculated A 13 2 for the BC nanoparticles interacting the sand surface through water was 5.2 × 10 21 J. The non - retarded LW interaction energy for the BC nanoparticles interacting with the sand surface was then determined as: 199 (5. 14 ) where a p is the particle radius. The AB interaction energy per unit area at contact ( ) was calculated as: 196 150 (5. 15 ) + are electron - acceptor and electron - donor components of each surface. The AB interaction energy was calculated as: 197, 198 (5. 16 ) where w is the decay length for AB interactions in water (0.6 nm). 198 An improved equation using linear superposition approximation for the EL interaction of nanoparticles with a planar surface was used: 200 (5. 17 ) where r is the dielectric constant of the water (80.1 at 293.15 K), 0 is the vacuum permittivity (8.854 × 10 12 C 2 N 1 m - 2 ), k is the Boltzmann constant (1.381 × 10 23 J K 1 ), T is temperature in Kelvin, e is the elementary charge (1.602 × 10 19 C), z is the charge number of the electrolyte, 1 and 2 are the surface potential of the BC n anoparticles and sand surface, and is the reciprocal electrical double layer thickness ( 1 ). The measured zeta potentials were used in place of the surface potentials. 196 The Born repulsion was calculated via: 201 (5. 18 ) where (0.5 nm) is the collision. The XDLVO energy calculations were conducted at ionic strength of 0.1 mM, 1 mM or 10 mM for BC nanoparticles interacting with sand surface in the absence of antibiotics. It was 151 believed that the presence of antibiotics would not change the XDLVO energies. Surface energy parameters used in the calculations are provided in Table 5.2. Table 5.2. Surface energy components and Hamaker con stants used in XDLVO calculations. LW (mJ/m 2 ) + (mJ/m 2 ) (mJ/m 2 ) A 132 (J) m Refs. BC 45.0 5.67 0 .0 202 Water 21.8 25.5 25.5 202 Quartz (SiO 2 ) 36.3 1.1 57.0 4.3 × 10 21 203 In colloidal filtration theory, attac hment efficiency ( ) determines whether particle collision with collector surfaces can result in attachment. Theoretical attachment efficiency ( theory ) was calculated from a Maxwell model that includes colloid deposition in both the primary and secondary minima. 204, 205 (5.1 9 ) where E 2 is the kinetic energy of particle normalized by kT max 2min . Experimental exp can be estimated from the column experiments via: 206, 207 (5. 20 ) where k d is the deposition rate coefficient, d c is the volumetric water cont ent, v is the pore water velocity, and 0 is the single - collector contact efficiency calculated via the Tufenkji and Elimelech equation. 206 As shown in Table 5. 3 , both BC nanoparticles and sand surface were negatively charged under all experimental conditions. With increasing ionic strength from 0.1 mM to 10 mM, zeta to 50.3 mV for the sand, respectively ( Table 5. 3 ), due to charge screening at higher ionic 152 strength. 180, 208, 209 Thus, at higher ionic strength, electrostatic repulsion among BC nanoparticles could decrease, resultin g in large size of aggregate s ( Table 5. 3 ). 175, 179, 180 Additionally, the presence of 100 µg L 1 of LCM, OTC, or SMX in the BC nanoparticle suspensions had no effect on the size and zeta potential of the BC aggrega tes ( Table 5. 3 ), presumably because the antibiotic concentrations were too low to exert any effect. . As shown by Figure 5. 5 , BC nanoparticles became more aggregated when ionic strength increased from 0.1 and 1 mM to 10 mM. Further, even the aggregate size of BC nanoparticles at 10 mM ionic strength increased with time from 453 ± 29 nm to 589 ± 47 nm at the end of 120 min. During the first 40 min there was no significant difference in the aggregate sizes at three ionic strength levels ( p < 0.05, one - way ANOV A with Tukey HSD test to compare the hydrodynamic diameters for 10 min intervals). Therefore, it was reasonable to assume that the BC nanoparticle suspension was s table during the equilibration phase in the batch sorption experiments and the injection phas e in the transport columns. However, over 2 hours, the BC nanoparticles could have form ed larger aggregates at 10 mM KCl, which may have influence d the sorption and transport of antibiotics. Table 5.3. Properties for BC nanoparticles and sand colloids. a IS pH D h PDI EPM Zeta potential (mM) (nm) (µm cm V s ) (mV) BC nanoparticles 0.1 7.1 410 ± 20 0.35 1 7.0 437 ± 6 0.34 10 7.0 461 ± 9 0.31 BC nanoparticles + LCM 0.1 7. 1 402 ± 8 0.36 1 7.0 444 ± 20 0.41 10 7.0 454 ± 15 0.48 BC nanoparticles + OTC 0.1 7.1 396 ± 7 0.38 1 7.0 444 ± 31 0.44 10 7.0 468 ± 21 0.50 BC nanoparticles + SMX 0.1 7.1 424 ± 13 0.39 1 7.0 433 ± 11 0.41 10 7.0 473 ± 37 0.43 Sand 0.1 7.0 nd nd 1 7.0 nd nd 10 7.0 nd nd a D h : hydrodynamic diameter ; PDI: p olydispersion index ; and EPM : electrophoretic mobility 153 Figure 5.5. Aggregation kinetics of BC nanoparticles dispersed in the KCl solution wi th ionic strength (IS) of 0.1, 1, or 10 mM at pH 7.0. The sorption isotherms of LCM, OTC, and SMX to the BC nanoparticles were all nonlinear with a concave - downward shape at ionic strength of 0.1, 1, and 10 mM and pH 7.0 ( Figure 5. 6 a - c ). For the Ottawa sand, t he LCM sorption isotherms exhibited a nonlinear concave - upward shape, the OTC sorption isotherms were nearly linear, and no sorption was observed for SMX ( Figure 5. 6 d - f). All sorption isotherms (expect for the SMX sorption onto the sand) could be fitted well with the Freundlich model ( Table 5.4 ). The distribution coefficients ( K d , with unit of L Kg 1 , calculated from the fitted Freundlich model at C e = 100 µg L 1 ) decreased in the order from OTC/BC - nanoparticles, SMX/BC - nanoparticle s, LCM/BC - nanoparticles, OTC/sand, LCM/sand, 154 and finally SMX / sand (assumed to be 0) ( Table 5.4 ) . The K d values of LCM, OTC, and SMX were in the order of 10 6 10 7 L Kg 1 for BC nanoparticles and 10 2 10 1 L Kg 1 for sand, indicating much stronger sorption aff inity of the three antibiotics to BC nanoparticles than to sand. This observation could be attributed to the greater specific surface area and more sorption sites on the BC nanoparticles. For the sand, the sorption of antibiotics is mainly controlled by el ectrostatic and van der Waals interactions. Therefore, the negatively charged sand surface could electrostatically attract positive LCM and zwitterionic OTC, but repel negative SMX (thus no observed SMX sorption). On the other hand, BC nanoparticles can in teract with antibiotics not only through electrostatic and van der Waals interactions, but also through other more specific sorption + bonding, and pore diffusion, which would greatly enhance the sorption of antibiotics to BC nanoparticles. 39, 40 Intriguingly, with increasing ionic strength the amount of sorption was decreased for LCM sorption to the BC nanoparticles and the sand, and for OTC sorption to the sand ( Figure 5. 6 ) . This sorption response is likely due to competition from other cations with the charged antibiotic molecules. Thus, electrostatic interaction seems to play an important role in the sorption of LCM and OTC to s orbents. A small decrease was observed for SMX sorption to the BC nanoparticles with increased ionic strength. Since no electrostatic attraction between SMX and the BC nanoparticles was expected, and thus no competitions from anions in solution, this decre ase was presumably due to the reduced accessibility of the sorption sites elicited by aggregation at higher ionic strength. Overall, the BC nanoparticles showed much stronger sorption affinity to LCM, OTC, and SMX than sand . Together these sorption results indicate that the presence of BC nanoparticles can substantially affect the transport of antibiotics through sand s . 155 Figure 5.6 Sorption isotherm of LCM (a and d), OTC (b and e), SMX (c and f) on black carbon (BC) nanoparticles and sands under ionic st rength (IS) of 0.1, 1 or 10 mM and pH of 7.0. Table 5.4 . Fitted parameters of the Freundlich model for sorption isotherms of LCM, OTC, or SMX on BC nanoparticles and sand under ionic strength (IS) of 0.1, 1, or 10 mM and pH of 7.0 . a IS BC nanoparticles S and K F N R 2 K d K F N R 2 K d LCM 0.1 2.48 ×10 3 0.66 0.97 5.10×10 5 8.80 ×10 5 1.2 0.95 0.26 1 2.47 ×10 3 0.62 0.97 4.38×10 5 1.53 ×10 5 1.4 0.87 0.12 10 2.22 ×10 3 0.61 0.97 3.69×10 5 4.60 ×10 6 1.6 0.87 0.06 OTC 0.1 2.53 ×10 4 0.76 0.97 8.24×10 6 9.75 ×10 3 1.1 0. 94 18. 1 2.53 ×10 4 0.78 0.98 8.98×10 6 8.30 ×10 3 1.1 0.96 15 10 2.53 ×10 4 0.78 0.99 9.14×10 6 8.20 ×10 3 1.0 0.94 9.1 SMX 0.1 1.07 ×10 4 0.54 0.98 1.29×10 6 nd nd nd nd 1 9.99 ×10 3 0.49 0.99 9.76×10 5 nd nd nd nd 10 9.03 ×10 3 0.50 0.99 8.89×10 5 nd nd nd nd a IS: ionic strength (mM); K F : Freundlich sorption coefficient ( g 1 N g 1 L N ); N : Freundlich nonlinearity factor; K d : distribution coefficients (L Kg 1 ), calculated from the fitting parameters of Freundlich isotherm at equilibrium concentration ( C e ) = 100 g g 1 , and nd: parameters were not determined. 156 The transport of BC nanoparticles through saturated sand followed classic colloid transport behaviors that had no retardation , which was similar to a conservative tracer ( Figure 5. 4 ) , and was controlled by the first - order kinetic deposition ( Figure 5. 7 ). 183 In agreement with the zeta potential and aggregate size measurements, there was no difference in the transport of BC nanoparticles with and without antibiotics through saturated sand column ( Figure 5. 7 and Table 5. 3 ). With increasing ionic strength, the retention of BC nanoparticles was significantly enhanced ( Figure 5. 7 ), in agreement with the XDLVO calculations ( Figure 5. 8 ). The XDLVO energy profiles showed unfavorable conditions for the deposition of BC nanoparticles, characterized by the formidab le energy barriers and shallow secondary minima ( Figure 5. 8 ). The energy barrier decreased, and the secondary minimum increased with increasing ionic strength ( Figure 5. 8 b). Also, the estimated theory value was 0.001, 0.046, and 0.516 for the BC nanoparticles at 0.1, 1, and 10 mM, respectively, suggesting greater deposition of BC nanoparticles at higher ionic strength. Nonetheless, the theory values were much smaller than the experimental exp values ( Table 5.5 ). This discrepancy was not surprising because the XDLVO theory neglected the roughness of sand surfaces that could decrease the energy barrier, and increase the depth of secondary minimum. 210, 211 Thus, the theory values estimated from the XDLVO energy calculations may underestimate the actual exp values. The retention of the BC nanoparticles at the secondary minima may be enhanced by low velocity zones located in the valley, crevices, and pits on rough san d surfaces. 210, 211 Furthermore, hydrodynamic traps at regions of flow stagnation, low flow vortices, and backward flow in pore space of the sand column may also contribute to the retention of BC nanoparticles, 208, 210 - 213 which may actually play a more important role under less favorable conditions. Indeed, the exp value was about 22 and 5 times of the theory value at ionic strength of 0.1 and 1 mM, but only 157 about 1.4 times of the theory value at ionic strength of 10 mM. Therefore, the surface attachment of the BC nanoparticles at the secondary minima became m ore important at higher ionic strength ( 10 mM ) , resulting in more favorable attachment condition. Figure 5.7. Measured and fitted breakthrough curves of black carbon nanoparticles (BCN) without (a) and with (b, c and d) of lincomycin (LCM), oxytetracycl ine (OTC) or sulfamethoxazole (SMX) in saturated sand columns at solution pH of 7 and ionic strength (IS) of 0.1, 1, or 10 mM KCl. 158 Figure 5.8. XDLVO surface energy profiles for black carbon (BC) nanoparticles interacting with sand surfaces with the ene rgy barrier (a) and the secondary minima (b). Table 5.5 . Fitted transport parameters for breakthrough curves of BC nanoparticles with and without LCM, OTC or SMX in saturated sand column. a IS (mM) k (min ) R 2 exp BC nanoparticles 0.1 0.013 0.998 0.022 1 0.130 0.986 0.235 10 0.376 0.962 0.702 BC nanoparticles + LCM 0.1 0.019 0.992 0.032 1 0.141 0.988 0.256 10 0.319 0.935 0.589 BC nanoparticles + OTC 0.1 0.022 0.998 0.037 1 0.147 0.991 0.268 10 0.324 0.975 0.611 BC nanoparticles + SMX 0.1 0.016 0.996 0.028 1 0.133 0.988 0.238 10 0.331 0.971 0.627 a k : d eposition rate coefficient (k) and exp : e xperimental attachment efficiency 159 Considering the strong sorption of LCM, OTC, or SMX to the BC nanoparticles and the transport behaviors of the BC nanoparticles as discussed above, it was hypothesized that the co - presence of BC nanoparticles and antibiotics could dramatically change the transport of antibiotics in porous media. To elucidate these complex interactions, we first examined the transport of LCM, OTC, or SMX through the sand column without the BC nanoparticles. A s shown in Figure 5. 9 a, the LCM retention decreased with increasing ionic strength, and the effluent mass recovery increased from 49.4 ± 2.4% to 97.3 ± 4.4% when ionic strength increased from 0.1 mM to 10 mM ( Table 5.6 ). This observation was likely due to the competition between K + cations and positively charged LCM cations ( Table 5. 1) for the sorption sites on the sand surface, which was also supported by the LCM sorption isotherms to the sand ( Figure 5. 6 d). The fitted retardation factor of LCM decreased f rom 26.6 to 1.61 with increasing ionic strength from 0.1 to 10 mM ( Table 5. 7 ), suggesting that LCM was more mobile at higher ionic strength. Due to stronger sorption of OTC to the sand, no OTC was transported out of the columns under all experimental condi tions ( Figure 5. 9 b and Table 5.6 ). Conversely, due to minimal sorption of SMX to the sand ( Figure 5. 6 e), about 100% of the initial SMX mass was flushed out of the column ( Figure 5. 9 c and Table 5.6 ). As a result, the fitted retardation factor was between 0. 85 1.05, suggesting a minimal SMX retention. Furthermore, the transport of OTC and SMX was not influenced by ionic strength, in contrast to that of LCM. Next we examined the transport of LCM, OTC, or SMX in the presence of BC nanoparticles. As shown in Fig ure 5. 9 d, the BTCs of LCM (including both the sorbed and dissolved LCM in the effluents) were drastically different from those in the absence of the BC nanoparticles. The LCM BTCs were similar to the BTCs of the BC nanoparticles with no 160 retardation, and th e LCM transport decreased with increasing ionic strength from 0.1 to 10 mM KCl ( Figure 5. 9 d) with the LCM mass recovery decreased from 78.7 ± 3.3% to 17.8 ± 2% ( Table 5.6 ). Indeed, the fitted results showed the small value of (0.0145 0.0957), suggesting the minimal contribution of equilibrium sorption and the predominant contribution of kinetic sorption to the LCM retention. Intriguingly, after the end of the injection phase, the dissolved LCM concentrations in the effluents continued to increase ( Figure 5. 10 a), likely resulted from the desorption of LCM from the retained BC nanoparticles due to replacement of sorbed LCM cations by K + . In the presence of the BC nanoparticles, the transport of OTC was substantial (up to 76.7 ± 2% at 0.1 mM), and decreased to 1.9 ± 0.2% when increasing ionic strength to 10 mM ( Figure 5. 9 e and Table 5.6 ). The transported OTC were exclusively associated with the BC nanoparticles ( Table 5.6 ), and the BTCs of OTC resembled those of the BC nanoparticl es. Similarly, the OTC transport had very large retardation factors and minimal values ( Table 5. 7 ), further supporting the dominant contribution from the kinetic sorption of the BC - associated OTC due to the deposition of BC nanoparticles. Clearly, the BC nanoparticles could facilitate the transport of a large portion of OTC. Finally, the transport of SMX was reduced by the presence of BC nanoparticles ( Figure 5. 9 f), and the mass recovery ranged between 4.56 89.6% which were much lower than 100% of the mas s recovery in the absence of BC nanoparticles ( Table 5.6 ). The transport of SMX decreased with increasing ionic strength, likely again reflecting the contribution from the deposition of the BC nanoparticles. The fitted transport parameters were characteriz ed by the intermediate retardation factors, and lower values at higher ionic strength. The sizable value (0.383) at 0.1 mM KCl suggests that SMX equilibrium sorption to the sand and BC nanoparticles still contributed a significant portion of the SMX re tention. However, this contribution diminished 161 at 1 and 10 mM KCl, indicating that the kinetic sorption of BC - associated SMX was the dominant contributor to the SMX retention. Figure 5.9. Measured and fitted breakthrough curves of lincomycin (LCM), oxyt etracyline (OTC) and sulfamethoxazole (SMX) without black carbon nanoparticles (BCN) (a, b and c) and the BCN - associated LCM, OTC and SMX (d, e and f) in saturated sand columns at solution pH of 7 and ionic strengths of 0.1, 1, or 10 mM KCl 162 Table 5.6 . E f fluent mass recovery calculations of breakthrough curves for LCM, OTC, and SMX in the antibiotic - only and co - transport experiments . IS Mass recovery ( M R ) Dissolved antibiotics BC - associated antibiotics Total transported antibiotics Total retained antib iotics mM % % % % Antibiotics - only transport experiments LCM 0.1 49.4 ± 2.4 n/a 49.4 ± 2.4 50.6 ± 2.4 1 86.6 ± 10.8 n/a 86.6 ± 10.8 13.4 ± 10.8 10 97.3 ± 4.4 n/a 97.3 ± 4.4 2.7 ± 4.4 OTC 0.1 0 ± 0 n/a 0 ± 0 100 ± 0 1 0 ± 0 n/a 0 ± 0 100 ± 0 10 0 ± 0 n/a 0 ± 0 100 ± 0 SMX 0.1 100.3 ± 4.7 n/a 100 ± 4.7 - 0.26 ± 4.7 1 99.9 ± 7.6 n/a 99.9 ± 7.6 0.08 ± 7.6 10 100.4 ± 5.3 n/a 100 ± 5.3 - 0.43 ± 5.3 Antibiotics and BC nanoparticles co - transport experiments LCM 0.1 3.3 ± 0.93 75.4 ± 2.4 78.7 ± 3.3 21.3 ± 3.3 1 7.55 ± 0.88 16.9 ± 2.2 24.4 ± 3.1 75.6 ± 3.1 10 15.8 ± 1.3 2.01 ± 0.67 17.8 ± 2 82.2 ± 2 OTC 0.1 0 ± 0 76.7 ± 2 76.7 ± 2 23.3 ± 2 1 0 ± 0 16.4 ± 2.1 16.4 ± 2.1 83.6 ± 2.1 10 0 ± 0 1.9 ± 0.24 1.9 ± 0.2 98.1 ± 0.2 SMX 0.1 9.90 ± 0.76 79.7 ± 2.6 89.6 ± 3.3 10.4 ± 3.3 1 3.91 ± 0.22 18.8 ± 3.9 22.8 ± 4.1 77.2 ± 4.1 10 2.84 ± 0.09 1.71 ± 0.44 4.6 ± 0.5 95.4 ± 0.5 Table 5.7. Fitted transport parameters of breakthrough curves for LCM, OTC, and SMX in the antibiotic - only and co - transpor t experiments . a IS (mM) R R 2 Antibiotics - only transport experiments LCM 0.1 26.6 0.095 0.811 0.978 1 3.66 0.580 0.422 0.984 10 1.61 0.855 0.311 0.997 OTC 0.1 NF NF NF NF 1 NF NF NF NF 10 NF NF NF NF SMX 0.1 1.05 1.00 8496 0.999 1 0.85 1.00 8007 0.999 10 1.01 1.0 0 7947 0.997 Antibiotics and BCN co - transport experiments b Total LCM 0.1 10.5 0.0957 0.300 0.991 1 69.0 0.0145 1.63 0.985 10 21.8 0.0460 3.25 0.839 Total OTC 0.1 34.3 0.029 0 0.28 0.998 1 1005 0.000995 1.85 0.990 10 9272 0.000108 4.08 0.975 Tota l SMX 0.1 2.62 0.383 0.22 0.997 1 141 0.007 1.59 0.985 10 141 0.007 3.61 0.934 a R : the retardation factor; : the partitioning coefficient of equilibrium sorption and kinetic deposition sites; is the mass transfer coefficient, and NF: not fitted. b Total LCM, total OTC, and total SMX included both dissolved fraction and BC - associated fraction. 163 Figure 5.10. Breakthrough curves of LCM (a), OTC (b), and SMX (c) in the presence of black carbon (BC) nanoparticles in saturated sand columns at solution pH of 7 and ionic strengths of 0.1, 1, or 10 mM KCl. The inserts (d, e, and f) showed the x - axis range of 0.0 to 0 .1 to better view the released antibiotics in solution. 164 This study was limited to only one solution pH level of 7.0 in a model porous media. Future study should be extended to slightly acidic and alkaline pH range in diverse soil types. Overa ll, the co - presence of BC nanoparticles and antibiotics substantially changed the transport of LCM, OTC or SMX in saturated sand. At all ionic strength levels, the BC nanoparticles facilitated the transport of OTC, but decreased the transport of SMX. It is intriguing that at low ionic strength of 0.1 mM, the BC nanoparticles increased the transport of LCM, but decreased its transport at higher ionic strength of 1 mM and 10 mM. Therefore, the risks for facilitated transport of antibiotics could be much highe r for low - salinity pore water , such as when rainfall or irrigation occurs on soils . Still, a s soil solution in typical soils range between 1 180 mM, 86 the transport of antibiotics in most soils would likely experience a net decrease with the addition of BC nanoparticles. However, this is a steady - state perspective. In natural settings, soil moisture aand transport in pore water is a dynamic process, so durin g transient flow conditions such as infiltration and percolation of rainwater and irrigation water water of low salinity , the facilitated transport of antibiotics sorbed on the BC nanoparticles could be substantially higher, especially when the BC nanopart icles are released and mobilized. 214 - 216 165 CHAPTER V I CONCLUSIONS AND FUTURE WORK 166 In this dissertation, the sorption and transport of antibiotics associated with black carbon (BC) in soil and water syste ms were investigated using batch and column approaches with combination of various spectroscopic analysis and mathematical modeling. This dissertation research demonstrated BC (i.e. biochars) could provide a rapid immobilization of antibiotics by surface a dsorption and a lasting sequestration of antibiotics via pore diffusion, and therefore land application of BC as a soil amendment may be used as an effective in - situ sequestration strategy to reduce the mobility and bioavailability of antibiotics in soil. The Dissolved organic carbon (DOC) released from BC could be characterized as a mixture of acid - precipitated (AP) fraction with higher molecular weight and aromaticity and an acid - soluble (AS) fraction with lower molecular weight and aromaticity. A quick, easy and robust UV - vis spectrometric method was developed to measure the DOC concentrations in BC produced from diverse feedstocks and pyrolysis conditions. The continuous release of DOC from BC enhanced the lincomycin sorption by decreasing particle size of BC and/or increasing the accessibility of sorption sites initially blocked by DOC. Finally, the facilitated transport of antibiotics by BC nanoparticles in soils was investigated and the results showed that the total transport of antibiotics was enhance d in the presence of BC nanoparticles in low - salinity water, but decreased at high - salinity water, implying that the facilitated transport of antibiotics would occur under rainfall or irrigation. For the directions of future works, the field st udy in investigating the application of BC as a soil amendment will be needed for understanding its antibiotics sequestration ability of BC in the real world. The proposed antibiotic sorption mechanisms onto BC (i.e. electrostatic interactions, hydrogen bo nding, van der Waals forces, and pore - filling process ) need to be validated by direct 167 evidences in future studies. The role of released DOC from B C plays a critical role in carbon dynamics and contaminant transport in soils and further understand of the ch emical compositions of DOC will be important to assess their potential physical, chemical, and biological effects in the environment. Finally, transport and co - transport of antibiotics study should be extended to different antibiotics, BC, solution chemist ry in the diverse soil column in the future. 168 APPENDICES 169 Figure 2.8 C t Q t Ct Qt µg L µg g µg L µg g AVG SD AVG SD AVG SD AVG SD BM600 pH 6.0 BM600 pH9.9 7.9 1.0 69.9 1.0 33.4 3.8 64.4 3.8 48.5 0.9 192.7 0.9 109.7 9.3 138.7 9.3 155.5 4.2 358.3 4.2 304.3 13.9 212.7 13.9 346.9 13.9 441.7 13.9 528.5 2 0.8 230.7 20.8 518.7 11.6 492.4 11.6 765.6 18.1 261.1 19.7 DM600 pH 6.5 DM600 pH10.0 7.4 0.3 70.4 0.3 32.6 1.4 65.1 1.4 36.1 1.2 205.1 1.2 100.0 9.0 148.4 9.0 136.8 3.2 376.9 3.2 304.3 13.9 212.7 13.9 322.3 16.2 466.3 16.2 502 .3 25.5 256.9 25.5 466.3 20.8 544.8 20.8 710.5 22.5 316.2 25.4 PM600 pH 7.3 PM600 pH10.4 34.1 2.7 43.7 2.7 41.9 1.2 55.8 1.2 100.0 8.6 141.2 8.6 117.4 3.9 131.0 3.9 283.1 16.2 230.7 16.2 314.2 18.5 202.9 18.5 453.2 30.1 335.4 30.1 503.9 23.1 255.2 23.1 651.2 27.8 359.9 27.8 711.7 16.5 315.0 19.8 AM600 pH 6.9 AM600 pH10.0 14.3 1.0 63.5 1.0 36.3 3.1 61.5 3.1 60.0 3.1 181.2 3.1 93.6 4.2 154.8 4.2 170.5 3.7 343.2 3.7 288.0 18.5 229.0 18.5 328.9 6.9 459 .7 6.9 479.4 11.6 279.8 11.6 481.0 9.3 530.1 9.3 678.5 18.1 348.2 17.5 Figure 4.8 and 4.9 C t Q t C t Q t C t Q t C t Q t µg L µg g µg L µg g µg L µg g µg L µg g 1d 7d 30d 365d BM300 76.3 29.2 12.8 94.3 0.6 107.1 0.0 102.1 73.2 33.4 11.8 92.9 0.8 108.2 0.0 102.0 157.3 52.7 27.7 174.8 0.9 210.8 0.0 207.6 149.7 60.0 30.6 172.9 1.1 2 05.4 0.0 200.9 321.5 83.4 71.1 323.1 3.2 401.5 0.0 396.3 307.3 99.5 74.7 323.1 1.8 399.3 0.0 398.3 434.8 143.5 126.2 470.2 8.4 584.0 0.0 590.0 455.5 122.4 123.3 473.7 6.0 573.5 0.0 599.6 649.9 155.8 202.1 586.6 17.2 795.3 0.0 790.1 622.0 185.9 196.6 611.7 13.9 779.0 0.0 802.0 824.5 175.9 290.8 719.3 33.9 971.4 0.0 1011.4 801.9 200.5 327.7 674.3 26.9 988.4 0.0 985.3 BM400 72.4 33.1 45.8 60.3 38.8 69.6 0.0 102.8 83.3 22.6 42.9 64.2 33.3 76.4 0.0 101.6 163.1 46.4 110.4 92.0 74.8 132.8 0.1 201.8 156.0 52.6 113.6 90.7 68.3 137.4 0.1 203.9 310.1 95.3 233.0 162.3 183.3 215.9 1.0 399.3 321.5 84.6 233.0 166.0 194.4 205.8 1.2 408.7 170 470.4 110.3 372.0 225.4 314.2 277.7 1.2 591.7 452.5 1 28.4 365.6 234.3 344.8 245.4 3.2 596.5 643.7 160.4 502.5 296.4 429.3 371.1 3.7 804.3 668.7 136.1 509.4 290.9 521.0 279.4 10.6 796.4 850.5 151.6 654.7 353.1 578.8 418.7 12.0 975.9 821.3 179.1 719.6 283.3 555.4 440.1 14.4 980.8 BM500 73.4 32.7 56.9 48.5 47.4 62.9 1.0 103.5 71.8 34.4 58.6 47.7 39.3 70.8 1.0 103.3 144.6 64.3 114.2 88.6 90.1 117.6 8.6 195.9 138.0 71.4 115.2 88.2 83.8 124.6 8.6 196.1 301.6 105.7 260.6 135.8 216.6 183.1 23.3 385.8 287.4 120.1 266.6 131.7 202.5 197.3 44.2 355.9 443.7 136.0 413.0 186.0 329.4 258.3 66.9 524.8 428.9 150.8 421.8 178.3 314.2 277.7 55.7 540.0 653.1 154.4 589.2 206.5 532.4 272.8 113.2 677.3 612.8 193.6 582.0 213.4 498.3 310.9 98.5 694.4 801.9 1 98.7 773.3 228.1 653.3 351.8 132.5 879.9 847.2 152.7 781.1 220.4 674.7 331.9 168.1 827.2 BM600 53.3 53.3 29.5 76.4 10.9 98.1 0.0 101.7 51.5 53.8 31.3 74.9 16.6 92.0 0.0 101.2 126.7 83.4 81.8 122.8 52.1 157.1 0.6 205.2 120.2 90 .4 80.2 125.5 55.1 151.3 0.6 205.7 264.8 139.4 196.4 205.3 145.3 255.8 1.5 402.3 284.6 120.1 200.2 198.3 139.1 260.1 3.0 394.9 405.4 171.8 321.5 274.5 254.8 328.7 8.1 585.6 417.2 162.6 307.1 292.0 216.6 375.2 16.9 569.6 582.1 220.9 457.2 337.4 413.1 398.9 20.9 783.9 606.6 196.1 470.7 323.2 383.9 421.2 26.6 765.6 779.4 226.6 672.0 334.3 538.1 470.0 28.5 963.2 795.5 209.0 642.4 358.3 512.5 496.6 43.5 944.8 PM300 81.4 24.7 61.3 44.9 52.7 57.9 0.8 100.2 87. 0 19.0 57.9 48.6 47.8 62.1 0.7 102.5 162.3 47.3 133.9 69.3 109.2 99.2 0.8 201.6 165.3 44.6 133.0 71.0 99.5 110.0 0.9 203.5 335.9 70.9 264.6 133.4 214.2 186.7 2.6 393.3 330.1 74.2 256.6 142.2 210.5 188.8 3.0 394.9 479.3 100.8 406.5 194.7 368.1 216.7 10.9 573.5 467.4 110.2 415.2 183.3 394.4 193.9 12.4 574.8 681.2 123.8 567.8 231.6 526.7 273.8 27.5 759.1 671.8 133.5 577.2 223.7 538.1 269.8 18.8 786.0 844.0 158.5 773.3 228.4 680.8 318.8 34.5 970.5 883.1 118.7 77 0.8 233.3 705.6 299.1 43.1 946.4 PM400 92.1 14.0 81.3 24.4 65.4 44.6 19.6 82.4 95.5 10.3 80.4 25.6 62.3 46.8 19.4 84.7 185.8 23.5 166.8 36.8 128.1 78.9 51.3 154.7 189.7 19.7 158.5 46.3 125.2 83.3 46.8 159.2 370.5 34.9 323.6 73 .4 262.1 135.2 140.0 260.0 376.3 29.4 327.7 70.8 271.9 126.2 149.3 250.8 536.4 43.0 493.4 106.7 418.5 167.9 213.9 385.5 530.3 49.1 495.7 101.7 410.4 175.6 216.3 374.0 747.5 58.4 686.9 108.9 605.3 200.5 352.2 449.6 171 757.0 48.6 694.4 102.1 605.3 197.3 353.2 444.7 959.1 43.8 903.3 100.7 791.0 210.1 482.0 523.8 945.8 56.5 889.8 113.8 787.8 210.2 507.5 503.3 PM500 64.7 41.8 48.6 57.8 29.7 80.4 4.8 97.4 67.9 38.6 49.2 56.1 32.5 78.0 4.8 99.1 134.8 73.5 102.6 1 02.8 68.5 138.0 13.9 187.5 143.2 67.0 98.6 107.3 72.7 135.9 10.6 195.8 284.6 119.7 231.0 168.2 158.1 238.1 21.2 380.6 298.7 106.4 238.9 158.1 166.0 227.7 33.8 362.1 461.4 115.5 369.8 227.2 294.1 297.3 63.3 533.0 431.9 145.5 378.4 2 20.9 276.8 306.3 66.4 526.6 656.2 149.9 541.9 253.9 451.1 355.2 136.3 670.2 637.5 170.2 537.2 258.2 423.9 384.5 113.6 694.0 805.1 196.3 750.2 253.1 623.2 382.7 264.2 745.8 831.0 171.0 729.7 274.5 605.3 397.3 216.8 772.2 PM600 49.1 57.7 29.8 76.3 12.1 97.9 0.0 103.4 42.5 63.8 31.5 73.4 14.6 95.1 0.0 101.1 84.9 123.1 68.0 137.5 31.1 176.9 0.2 205.0 95.0 115.8 66.1 140.3 27.9 177.9 0.2 204.7 231.5 176.2 177.5 217.6 105.5 297.3 1.9 404.4 221.7 187.2 165.0 2 29.7 69.2 333.5 5.5 401.8 361.8 217.7 286.7 309.0 208.4 386.5 6.1 583.2 341.6 237.4 288.7 315.5 201.1 392.8 8.2 581.1 533.4 275.9 448.3 348.0 274.3 534.9 8.8 787.2 494.2 309.7 432.8 365.8 274.3 530.2 10.1 801.9 665.5 334.2 603.6 39 5.4 448.4 547.1 26.8 973.3 741.1 263.5 622.9 382.9 462.1 531.5 28.4 984.0 DM300 89.4 16.7 25.5 81.5 8.7 101.5 0.0 103.7 93.4 12.8 25.0 81.7 10.3 98.0 0.0 102.4 176.5 32.6 56.6 145.1 15.7 192.1 0.0 204.2 177.8 31.2 56.8 146.3 1 1.7 197.3 0.0 206.8 361.8 43.3 123.7 275.5 31.9 364.8 0.0 409.4 364.7 40.8 123.7 271.1 36.9 356.8 0.0 406.3 509.3 68.5 216.3 388.3 77.9 505.1 0.0 589.2 518.3 61.6 207.6 385.3 71.0 515.8 0.0 600.4 715.8 89.7 335.0 458.3 179.0 633.4 0.0 800.0 725.3 81.4 327.1 463.3 132.1 664.1 0.0 812.2 932.6 68.9 502.5 502.3 159.0 849.0 0.0 991.4 899.6 101.5 511.7 494.3 262.1 732.2 0.0 1019.1 DM400 79.3 26.7 60.8 45.3 26.5 82.8 0.0 104.3 78.2 28.0 63.0 43.6 32.5 76.8 0.0 101.5 148.6 60.0 130.1 75.2 69.8 139.6 1.1 202.3 164.2 45.8 135.6 67.2 74.8 131.8 1.2 203.8 301.6 105.2 292.8 105.6 180.4 220.0 7.8 392.0 330.1 76.2 278.6 118.0 173.7 223.9 7.9 394.8 470.4 109.6 448.3 153.3 294.4 293.7 21.9 566.7 491.3 86.2 435.0 164.0 308.1 282.4 22.5 568.3 643.7 163.2 622.9 173.4 437.4 361.7 26.5 783.3 662.4 141.7 608.4 190.8 452.5 348.6 35.9 777.7 866.8 133.8 773.3 225.9 611.3 387.0 48.7 964.7 857.0 147.7 812.5 188.8 552.5 454.8 45.5 965 .5 172 DM600 48.6 57.5 16.3 89.5 3.3 105.6 0.0 104.2 56.2 50.5 19.8 87.5 3.3 104.6 0.0 101.4 102.8 105.9 51.2 151.9 8.0 202.1 0.0 208.1 105.2 104.9 49.7 157.1 8.9 200.1 0.0 203.9 245.2 163.1 122.0 275.4 26.1 375.8 0.0 405.8 2 67.6 137.5 132.5 267.3 22.3 380.1 0.0 405.8 408.4 168.7 211.7 392.5 62.3 535.8 0.0 588.5 390.8 189.3 238.9 353.7 71.0 526.2 0.0 604.2 554.6 249.9 363.5 434.4 132.3 666.5 2.1 798.8 572.9 236.4 378.4 422.6 165.8 630.1 2.4 791.6 731.6 268.7 586.8 414.1 233.2 755.2 2.3 996.5 789.0 210.4 560.7 443.9 238.0 770.4 2.8 1007.3 RDM500 60.2 45.8 39.1 66.4 19.1 91.7 0.0 101.2 67.3 39.3 38.3 68.8 19.1 90.3 0.0 101.1 124.8 83.3 93.7 110.8 45.2 165.5 0.5 201.7 129.4 79 .1 90.9 113.9 45.2 162.8 0.6 203.9 287.4 119.1 200.2 197.6 143.3 255.3 1.4 401.9 281.7 125.4 225.2 170.4 117.2 284.0 1.6 406.7 431.9 149.0 331.9 265.5 200.2 385.9 1.7 584.7 476.3 101.9 334.0 262.5 235.6 357.0 4.5 593.6 628.2 178.5 511.7 288.6 386.5 422.8 6.2 791.8 606.6 198.5 495.7 304.9 368.1 435.4 10.3 777.0 801.9 200.5 719.6 278.4 464.9 540.8 12.4 976.7 821.3 180.5 669.5 330.5 535.3 460.0 18.9 997.4 DDM500 61.5 44.4 34.8 71.8 9.4 99.5 0.0 104.2 61.8 43.7 34.6 70.8 9.4 100.0 0.0 101.7 124.3 86.9 92.1 113.6 37.5 168.2 0.0 203.7 105.7 104.9 89.5 115.6 37.5 169.2 0.0 202.4 256.4 151.3 185.0 212.0 111.8 284.4 0.0 405.3 248.0 159.7 209.8 189.5 123.9 278.9 0.0 395.8 399.6 182.6 338.2 262.9 259.7 330.0 0.0 600.4 373.4 206.9 327.7 275.8 238.0 348.4 0.0 595.9 594.3 207.7 484.3 312.4 362.9 434.1 0.0 794.0 566.8 235.7 473.0 319.8 362.9 436.7 0.0 801.0 709.5 292.1 662.1 342.6 538.1 455.5 0.9 992.9 769.8 229.4 657.1 340.2 429.3 575.9 0.6 1015.9 DDM600 40.2 65.1 24.5 83.0 10.7 98.9 0.4 104.2 43.8 61.7 25.7 80.9 9.2 99.2 0.4 101.5 78.5 130.6 59.6 144.9 19.0 187.6 0.4 203.3 86.5 122.0 56.9 147.6 30.3 175.1 0.4 205.8 204.3 205.0 139.8 258.0 8 8.0 308.8 3.1 398.6 197.7 208.0 150.2 245.4 88.0 313.1 3.1 398.6 310.1 274.0 240.8 363.8 153.8 433.7 2.3 586.9 321.5 256.8 268.6 332.2 132.9 451.2 5.2 597.4 482.3 317.3 372.0 427.4 245.2 550.5 15.8 778.3 470.4 331.9 395.6 396.7 281 .7 524.1 10.4 778.9 709.5 297.6 541.9 453.7 413.1 597.5 32.6 961.5 637.5 359.7 577.2 430.0 391.8 615.2 35.4 958.8 CDM500 75.0 30.6 51.2 55.4 32.1 76.8 3.5 100.6 69.4 36.6 54.9 51.6 33.9 75.7 3.7 100.6 173 166.3 43.0 116.0 86.6 81. 5 125.8 5.6 201.1 165.0 44.4 109.5 93.0 74.4 133.6 5.6 197.3 333.0 73.4 246.7 150.9 181.7 216.5 21.1 375.5 327.3 78.4 236.9 161.9 189.8 210.0 51.3 347.1 473.3 107.0 397.8 201.7 294.1 293.2 61.1 527.3 479.3 98.6 384.8 212.1 304.1 28 1.1 66.0 525.0 681.2 122.7 558.3 236.4 498.3 307.0 70.9 724.4 703.2 100.6 579.6 219.6 459.4 348.2 79.9 706.7 906.1 94.8 765.6 239.7 587.6 416.1 140.0 865.8 840.7 159.9 729.7 270.8 635.2 371.1 176.6 840.6 CDMW500 73.4 32.3 47.8 57.3 24.5 85.7 0.7 103.9 65.7 39.6 47.8 58.6 20.9 87.4 0.5 103.4 151.1 57.7 108.8 94.2 69.0 137.8 3.1 197.8 143.5 65.7 109.5 94.0 62.3 146.0 3.1 199.3 304.4 99.3 246.7 150.3 143.3 254.0 14.7 391.0 324.4 81.6 236.9 160.9 144.2 257. 9 9.4 390.0 476.3 103.1 397.8 203.5 289.2 293.8 30.3 566.9 452.5 124.4 374.1 222.4 271.9 315.0 52.6 542.4 653.1 150.6 558.3 238.7 405.1 398.0 52.6 737.2 678.0 127.6 537.2 257.6 445.6 365.8 67.3 726.2 814.8 188.5 765.6 241.5 492.7 5 00.8 65.5 944.1 879.9 122.9 729.7 273.2 575.8 419.0 93.1 907.2 WW500 61.8 44.0 35.3 71.0 15.0 94.4 0.0 103.8 57.0 48.2 33.8 71.9 17.6 90.8 0.0 102.6 142.1 67.8 83.4 122.2 30.3 176.0 2.5 205.0 145.6 63.4 80.2 124.7 44.3 162.4 2 .5 204.0 293.1 112.9 183.1 216.0 96.5 299.2 5.0 398.3 273.3 133.3 205.9 190.0 104.0 297.3 11.1 390.2 440.7 139.1 317.4 284.9 202.5 391.4 16.4 577.3 461.4 119.8 317.4 281.0 216.6 369.6 10.4 588.4 615.9 189.3 482.0 311.2 357.7 445.7 34.8 752.9 625.1 178.9 488.8 306.0 337.1 469.8 23.3 789.5 792.3 210.1 672.0 326.9 432.0 569.6 56.2 940.5 847.2 153.1 696.9 304.1 543.9 464.7 60.6 933.7 Figure 4.8 and 4.9 C t Q t C t Q t C t Q t C t Q t C t Q t C t Q t µg L µg g µg L µg g µg L µg g µg L µg g µg L µg g µg L µg g BC Sand IS = 0.1 mM IS = 1 mM IS = 10 mM IS = 0.1 mM IS = 1 mM IS = 10 mM LCM 2.9 3866 3.1 3843 3.5 3809 35.4 0.0 36.0 0.0 43.4 0.0 3.0 3859 3.1 3850 3.6 3796 38.5 0.0 41.0 0.0 40.0 0.0 4.9 9425 5.3 9385 7.4 9178 76.8 0.0 95.9 0.0 95.3 0.0 5.1 9408 5.5 9365 7.7 9142 75.2 0.0 93.5 0.0 96.5 0.0 13.1 14405 14.9 14230 16.7 14052 118.1 0.0 146.0 0.0 141.7 0.0 12.0 14520 14.7 14242 17.4 13975 127.6 0.0 13 6.8 0.0 139.8 0.0 20.9 18242 23.3 18006 24.6 17873 157.7 0.0 180.0 0.0 188.6 0.0 21.2 18214 24.3 17904 27.7 17566 159.5 0.0 179.7 0.0 181.5 0.0 32.7 22861 32.4 22887 40.1 22119 189.4 0.1 217.3 0.0 231.2 0.0 31.2 23012 34.8 22650 46.4 21487 172.3 0.1 20 4.9 0.0 222.7 0.0 39.7 26567 47.1 25832 51.2 25420 220.0 0.1 254.4 0.0 264.7 0.0 39.8 26563 47.1 25834 58.5 24687 236.8 0.1 256.0 0.0 258.6 0.0 48.8 31698 61.8 30403 68.9 29691 258.3 0.1 282.3 0.1 315.7 0.0 174 52.1 31373 61.5 30426 78.4 28742 274.4 0.1 29 3.2 0.1 320.4 0.0 58.0 34604 71.0 33304 81.9 32211 296.0 0.1 318.1 0.1 360.6 0.0 52.9 35119 64.1 33994 93.1 31096 290.9 0.1 319.6 0.1 347.9 0.0 65.9 40458 79.5 39092 102.1 36833 325.9 0.1 361.6 0.1 397.5 0.1 72.5 39790 78.6 39183 93.7 37668 333.1 0.1 3 72.5 0.1 395.6 0.1 74.2 43462 93.6 41527 114.8 39405 349.2 0.1 396.6 0.1 415.6 0.1 78.5 43040 92.4 41640 118.3 39048 363.5 0.1 379.8 0.1 428.7 0.1 OTC 0.1 4805 0.1 4801 0.1 4800 4.5 0.0 4.6 0.0 6.3 0.0 0.2 4794 0.2 4799 0.1 4801 4.7 0.0 4.6 0.0 6.1 0.0 0.3 10134 0.3 10130 0.3 10129 6.8 0.1 8.9 0.1 9.5 0.1 0.3 10127 0.3 10129 0.3 10134 7.2 0.1 8.7 0.1 9.1 0.1 0.5 15156 0.4 15165 0.4 15160 8.9 0.1 10.8 0.1 13.3 0.1 0.5 15149 0.4 15162 0.6 15147 9.1 0.1 10.5 0.1 12.6 0.1 0.8 19967 0.8 1997 0 0.8 19964 11.0 0.2 12.3 0.2 17.1 0.2 0.7 19971 0.8 19965 0.8 19970 10.9 0.2 12.4 0.2 17.6 0.2 0.9 25237 1.0 25217 1.0 25223 14.5 0.2 17.0 0.2 22.1 0.2 1.0 25226 0.9 25236 0.9 25233 13.9 0.2 16.0 0.2 21.4 0.2 1.2 29729 1.1 29731 1.2 29724 18.0 0.3 19. 8 0.3 28.4 0.3 1.1 29739 1.2 29727 1.1 29733 16.9 0.3 20.5 0.3 27.3 0.3 1.5 34250 1.4 34254 1.5 34253 22.6 0.3 24.3 0.3 36.0 0.3 1.4 34258 1.5 34247 1.5 34245 21.9 0.3 23.1 0.3 35.0 0.3 1.8 41003 1.8 41003 1.8 41004 26.6 0.4 27.3 0.4 43.6 0.4 1.7 4101 2 1.7 41006 1.8 41003 26.9 0.4 28.3 0.4 42.8 0.4 2.1 44151 2.3 44136 2.3 44137 28.8 0.4 33.7 0.4 49.8 0.4 2.4 44126 2.1 44152 2.1 44156 30.0 0.4 32.6 0.4 47.4 0.4 2.6 49991 2.7 49976 2.4 50010 33.7 0.5 40.2 0.5 55.9 0.4 2.8 49965 2.7 49980 2.7 49975 32 .2 0.5 38.3 0.5 52.1 0.4 SMX 0.3 5155 0.3 5153 0.3 5149 56.3 0.0 56.3 0.0 55.9 0.0 0.4 5145 0.3 5149 0.4 5145 56.3 0.0 56.3 0.0 55.9 0.0 0.9 9780 0.8 9788 1.3 9746 107.9 0.0 111.4 0.0 106.1 0.0 1.0 9774 0.9 9783 1.3 9744 108.6 0.0 106.7 0.0 106.2 0.0 1.5 14715 2.2 14647 2.4 14625 157.6 0.0 156.4 0.0 154.6 0.0 1.6 14701 2.1 14652 2.3 14630 157.6 0.0 156.4 0.0 154.6 0.0 2.4 19714 3.3 19617 3.8 19567 205.3 0.0 205.6 0.0 200.1 0.0 2.5 19698 3.4 19609 3.9 19556 203.5 0.0 200.3 0.0 201.1 0.0 3.7 24784 5.7 24580 6.6 24491 247.3 0.0 245.8 0.0 243.4 0.0 4.0 24756 5.8 24575 6.9 24459 247.3 0.0 245.8 0.0 243.4 0.0 5.3 29514 7.8 29261 10.5 28990 295.1 0.0 298.6 0.0 294.4 0.0 5.6 29483 8.1 29237 10.8 28966 299.7 0.0 293.2 0.0 294.4 0.0 9.0 34213 10.5 34057 13.7 33736 354.1 0.0 353.1 0.0 349.3 0.0 9.3 34175 11.6 33946 14.2 33688 354.1 0.0 353.1 0.0 349.3 0.0 11.0 39090 16.0 38587 20.4 38145 404.6 0.0 408.8 0.0 399.0 0.0 11.5 39039 16.5 38536 20.9 38099 408.2 0.0 403.3 0.0 400.2 0.0 16.9 43588 2 1.9 43092 24.6 42820 452.0 0.0 453.4 0.0 450.3 0.0 14.9 43785 22.4 43035 25.0 42773 452.0 0.0 453.4 0.0 450.3 0.0 18.8 47892 24.6 47311 28.4 46928 492.4 0.0 500.1 0.0 497.6 0.0 18.4 47925 25.6 47210 27.1 47062 496.2 0.0 494.9 0.0 495.1 0.0 175 Figure 2.1 Time C t C t C t C t C t day µg L µg L µg L µg L µg L AVG SD AVG SD AVG SD AVG SD AVG SD Control BM600 DM600 PM600 AM600 0.04 822.2 14.7 820.7 0.0 773.2 12.6 840.0 14.7 0.13 810.3 2.1 804.3 2.1 753.9 2.1 816.2 10.5 0.21 1001.8 4.2 802.9 4.2 798.4 2.1 743.5 4.2 791.0 16.8 1 1000.4 2.1 788.0 8.4 740.5 8.4 733.1 10.5 706.3 10.5 2 1000.4 2.1 758.3 12.6 707.8 12.6 707.8 0.0 666.2 8.4 3 1006.3 14.7 750.9 6.3 669.2 8.4 700.4 1 0.5 645.5 4.2 5 1012.2 10.5 734.5 12.6 638.0 18.9 679.6 2.1 617.2 10.5 7 1006.0 4.2 712.2 6.1 615.9 43.2 674.4 14.7 591.4 19.6 15 1005.7 1.9 682.3 43.1 499.0 54.4 611.3 24.9 503.0 14.9 30 999.1 2.8 521.3 20.4 331.0 13.2 569.3 36.8 451.3 32.9 60 1002.7 21.3 467.5 28.7 219.3 60.9 471.9 26.4 394.0 19.8 90 998.4 6.3 420.0 33.0 123.5 51.1 381.8 54.2 285.8 11.3 180 1006.2 23.9 71.8 2.2 10.9 1.9 81.8 34.4 44.5 8.1 Figure 2.5 Time Q t Q t Q t Q t day µg g µg g µg g µg g AVG SD AVG SD AVG SD AVG SD BM600 DM600 PM600 AM600 0.04 182.1 14.7 183.5 0.0 231.1 12.6 164.2 14.7 0.13 193.9 2.1 199.9 2.1 250.4 2.1 188.0 10.5 0.21 201.4 4.2 205.8 2.1 260.8 4.2 213.2 16.8 1 216.2 8.4 263.7 8.4 271.1 1 0.5 297.9 10.5 2 245.9 12.6 296.4 12.6 296.4 0.0 338.0 8.4 3 253.3 6.3 335.0 8.4 303.8 10.5 358.8 4.2 5 269.7 12.6 366.2 18.9 324.6 2.1 387.0 10.5 7 290.2 6.1 386.5 43.2 327.9 14.7 411.0 19.6 15 320.1 43.1 503.4 54.4 391.1 24.9 499 .3 14.9 30 481.0 20.4 671.4 13.2 433.1 36.8 551.0 32.9 60 534.9 28.7 783.0 60.9 530.5 26.4 608.4 19.8 90 582.3 33.0 878.9 51.1 620.6 54.2 716.5 11.3 180 930.6 2.2 991.5 1.9 920.6 34.4 957.9 8.1 Figure 4.1 Time C t C t C t C t C t day µg L µg L µg L µg L µg L AVG SD AVG SD AVG SD AVG SD AVG SD Control BM300 BM400 BM500 BM600 0 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1 1008.3 10.3 807.0 19.9 821.1 28.5 847.5 31.6 777.1 5.6 2 1004.8 19.3 691.1 3 8.2 801.0 22.6 831.2 25.7 733.7 11.1 3 1010.2 13.6 622.3 0.0 789.1 33.8 811.1 25.6 737.6 0.0 5 1010.8 9.1 588.7 26.3 737.7 22.2 797.3 27.9 722.0 22.1 7 1005.4 5.7 340.1 18.3 696.7 2.4 780.9 5.3 666.4 21.3 14 1009.7 15.8 240.1 5.5 624.9 9.3 720. 6 12.1 611.8 18.5 21 1010.4 20.5 157.2 6.3 542.5 11.2 688.3 23.9 569.6 13.6 30 1000.5 12.9 70.3 14.9 518.5 1.6 658.8 17.6 519.8 22.9 60 999.5 14.6 1.2 0.8 359.1 1.7 551.8 5.3 390.7 19.0 176 90 1004.5 6.8 1.2 0.1 265.2 5.1 466.4 1.0 275.7 3.7 180 1007.6 21.1 0.5 0.0 79.4 1.7 316.5 9.3 103.8 2.8 240 997.2 22.2 0.0 0.0 43.4 1.9 189.9 12.1 75.6 2.7 300 994.7 22.8 0.0 0.0 14.8 0.3 157.1 1.3 41.8 0.1 365 975.2 8.5 0.0 0.0 2.9 0.0 80.7 3.2 14.2 0.1 DM300 DM400 DM600 PM300 PM400 0 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1 884.2 14.5 840.5 14.8 741.6 27.8 848.0 16.8 928.6 4.9 2 833.2 17.2 822.6 6.3 700.6 8.2 827.7 2.4 918.2 9.8 3 815.0 2.8 797.4 16.7 652.6 5.4 821.0 2.4 909.6 17.1 5 801.0 11.3 791.5 8.3 620.4 2.7 814.2 2.4 902.7 22.0 7 539.3 11.2 766.5 10.3 569.6 0.0 778.1 6.4 890.6 14.6 14 467.8 36.8 624.3 6.9 437.2 10.7 766.6 8.6 879.3 17.4 21 413.2 2.1 574.9 18.5 347.2 16.3 741.1 12.8 845.3 0.0 30 287.6 14.1 534.7 30.7 237.8 12.2 665.9 6.8 810.2 7.1 60 84.9 22.5 416.3 6.9 104.8 18.6 565.6 3.6 820.5 20.6 90 14.3 5.2 341.3 40.3 33.8 8.3 402.0 24.1 741.4 36.2 180 0.7 0.0 153.9 18.5 7.7 1.3 165.0 9.6 678.1 16.7 240 0.0 0.0 100.1 11.5 3.6 0.6 100.5 6.4 566.6 13.4 300 0.0 0.0 52.0 4.7 4.8 3.0 42.2 2.5 488.7 30.2 365 0.0 0.0 18.5 3.1 5.7 0.1 6.2 1.3 465.2 5.9 PM500 PM600 RDM500 DDM500 DDM600 0 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1002.8 9.5 1 800.9 21.2 702.8 6.1 802.0 16.5 729.9 20.1 658.4 9.8 2 787.6 21.1 657.3 18.0 777 .2 14.3 722.8 22.1 618.7 7.7 3 772.7 23.4 646.1 29.8 768.5 6.1 707.2 12.0 599.8 11.4 5 772.7 28.0 634.8 5.9 724.2 4.0 676.5 23.6 577.1 1.9 7 743.0 9.3 619.4 19.7 679.2 3.9 647.4 1.9 551.9 0.0 14 716.7 10.8 571.0 9.7 578.4 0.0 533.7 29.6 456.2 1 8.9 21 697.6 12.5 487.7 21.2 508.2 13.0 500.2 4.8 422.0 1.5 30 624.2 11.3 474.7 36.7 476.1 8.6 438.2 10.7 396.3 10.5 60 597.3 27.0 387.0 0.0 345.8 13.7 264.5 20.1 302.6 20.3 90 539.4 28.2 274.0 10.1 230.9 10.4 145.8 10.6 240.1 2.0 180 335.7 26.5 74.9 4.5 63.0 0.5 17.5 2.0 102.7 3.3 240 292.5 24.4 48.5 1.3 36.9 3.2 4.7 0.1 59.6 0.8 300 246.7 13.8 33.9 1.2 16.3 0.0 1.3 0.1 31.0 0.1 365 170.9 17.4 9.4 3.8 4.1 2.0 0.0 0.0 13.1 2.7 CDM500 CDMW500 WW500 0 1002.8 9.5 1002.8 9.5 1 002.8 9.5 1 837.3 22.9 817.1 5.7 769.1 0.0 2 827.1 14.3 795.0 8.5 753.3 5.6 3 819.1 2.8 785.0 5.6 716.1 2.8 5 809.0 17.0 747.4 2.8 685.2 2.7 7 763.7 14.8 725.7 24.2 668.1 9.5 14 737.7 2.4 661.5 33.1 613.5 20.8 21 676.5 2.4 608.6 27.7 556.9 22.6 30 595.2 13.6 537.1 14.8 492.3 29.0 60 536.7 8.9 450.8 3.5 390.7 22.4 90 499.7 0.0 361.1 0.0 305.9 35.0 180 291.6 5.8 164.5 13.3 138.0 17.7 240 211.2 22.9 120.9 3.0 94.5 13.4 3 00 152.8 3.2 81.5 5.9 63.7 0.3 365 93.5 1.3 36.5 6.3 23.9 0.2 Figure 4.4 Time Q t Q t Q t Q t Q t 177 day µg g µg g µg g µg g µg g AVG SD AVG SD AVG SD AVG SD AVG SD BM300 BM400 BM500 BM600 DM300 1 196.4 19.8 183. 7 28.6 156.3 31.3 227.6 5.4 119.5 14.3 2 311.7 37.5 202.9 21.9 172.2 25.2 270.1 12.7 171.3 17.1 3 380.5 1.0 214.9 32.5 193.1 26.4 267.2 1.2 189.4 3.2 5 414.5 25.9 266.0 22.2 206.6 27.5 281.2 21.0 202.9 10.2 7 665.1 17.7 307.1 3.2 223.3 6.7 336. 4 20.4 463.8 10.8 14 763.4 2.2 379.5 9.3 282.7 12.1 392.5 21.6 534.2 36.7 21 846.3 7.1 460.3 10.4 317.0 23.1 434.9 12.9 594.2 1.6 30 936.0 19.9 485.1 1.4 346.0 16.4 482.1 22.4 716.8 10.9 60 1002.7 0.8 644.1 2.8 452.2 6.1 614.0 17.9 923.1 23.4 90 1006.6 3.7 738.8 3.8 537.6 2.8 727.4 7.6 989.7 3.5 180 1006.0 3.5 921.1 1.7 687.9 11.1 902.4 1.2 1002.1 3.5 240 1006.5 3.6 980.8 4.6 812.6 11.3 974.1 7.4 1001.5 3.5 300 1004.0 7.1 989.8 0.6 848.5 2.0 982.4 4.6 1006.5 3.6 365 1003.3 4.4 999 .2 4.4 929.1 3.2 991.6 0.8 1000.2 0.0 DM400 DM600 PM300 PM400 PM500 1 163.1 14.8 262.8 27.6 155.5 17.1 75.1 4.8 203.9 21.2 2 181.4 6.0 303.8 10.4 176.3 3.6 85.9 10.0 216.0 20.9 3 206.6 17.4 352.7 5.4 183.2 1.4 94.5 17.7 232.3 24.1 5 213.1 7 .4 384.0 3.3 190.1 1.5 101.2 22.0 231.0 26.6 7 237.3 11.4 432.2 0.0 226.9 5.8 113.5 14.6 261.8 10.0 14 380.9 7.3 565.8 13.2 237.7 8.2 124.9 18.2 287.5 13.1 21 428.8 19.6 658.3 12.8 263.4 14.4 158.6 0.8 307.5 12.6 30 470.1 27.9 767.6 8.8 340.2 6 .9 194.2 8.1 380.0 11.6 60 589.5 9.6 900.8 19.4 437.5 5.5 183.6 20.0 408.7 27.8 90 665.6 41.1 974.4 10.9 599.4 23.5 263.7 36.1 463.7 30.1 180 852.2 15.5 994.4 5.7 839.5 14.8 325.2 15.8 667.8 28.3 240 903.9 17.8 1005.4 0.6 904.0 4.0 437.3 11.1 7 12.9 26.4 300 950.8 9.7 1000.4 3.0 984.5 0.1 516.3 32.5 756.4 17.8 365 984.9 3.0 998.9 1.0 995.9 3.9 541.8 6.5 837.3 19.0 PM600 RDM500 DDM500 DDM600 CDM500 1 302.3 6.1 202.7 16.2 274.9 19.9 345.1 8.5 167.6 22.9 2 346.5 19.5 226.3 13.3 280.5 23.0 387.2 8.4 176.3 14.4 3 359.1 30.9 235.9 7.6 297.9 12.5 404.9 13.9 185.8 2.5 5 368.7 5.3 279.8 3.5 327.5 22.4 427.2 0.8 195.2 18.1 7 385.2 18.7 326.0 4.0 355.5 2.2 451.8 2.0 240.4 15.0 14 431.9 8.1 426.9 1.9 469.6 29.6 545.7 19.8 265.9 2.9 21 518.2 20.4 498.9 13.1 502.2 6.2 584.2 1.5 326.9 2.1 30 528.2 35.2 528.1 5.4 566.1 14.2 605.8 11.0 409.1 16.9 60 618.9 0.5 658.6 17.7 737.2 22.0 704.9 20.4 468.2 6.0 90 734.6 10.2 772.6 7.0 859.9 15.9 764.3 5.4 504.3 3.6 180 933.2 3.7 945 .1 0.3 987.1 8.1 905.2 0.9 711.9 2.7 240 977.5 0.5 983.1 2.0 1004.3 1.7 981.8 7.2 795.3 26.5 300 986.1 4.7 990.8 4.4 1005.2 3.4 989.1 5.2 847.0 3.2 365 994.0 6.4 998.0 0.6 1005.9 4.5 1002.8 7.1 914.4 1.1 CDMW500 WW500 1 186.6 5.5 233. 9 0.4 2 208.9 7.4 251.9 5.2 3 220.0 6.1 287.3 3.5 5 255.7 2.1 319.0 0.2 7 278.5 26.5 337.8 9.2 14 341.8 32.7 392.0 20.2 21 394.8 26.3 447.7 25.0 178 30 468.9 13.7 511.3 26.7 60 552.2 5.9 6 12.4 19.1 90 642.4 0.6 698.6 38.1 180 842.6 16.4 868.7 15.4 240 886.3 1.5 912.3 12.7 300 922.4 4.2 972.5 3.0 365 991.7 3.8 1003.2 1.1 Figure 4.11 Time Q t Q t Q t Q t Q t day µg g µg g µg g µg g µg g AVG SD AVG SD AVG SD AVG SD AVG SD WW500+DI WW500+DO C(BM300) WW500+DO C(DM300) WW500+DO C(PM300) WW500+DO C(DDM500) 1 228.3 22.3 117.5 36.8 121.2 56.9 81.4 55.4 94.2 34.3 3 271.5 18.8 64.6 22.4 100.5 36.8 98. 2 28.6 121.4 51.2 5 303.7 26.5 99.3 19.0 122.2 6.1 73.1 41.9 136.7 26.7 7 317.1 20.7 111.5 34.1 143.9 24.1 112.5 24.5 146.4 47.1 14 388.9 24.8 157.9 30.9 194.9 55.1 163.3 46.5 181.1 22.3 21 444.8 35.7 154.3 16.6 212.9 37.9 150.7 25.7 218.3 46.5 41 523.5 26.8 165.0 16.9 241.2 10.8 176.8 25.5 239.2 30.8 60 602.1 18.3 172.7 38.3 303.0 18.4 164.9 40.3 242.9 36.1 Figure 4.12 and 4.13 Time Q t Q t Q t Q t Q t day µg g µg g µg g µg g µg g AVG SD AVG SD AVG SD AVG SD AVG SD BM300Raw BM300DI BM300NaOH DM300Raw DM300DI 1 243.8 27.5 451.8 7.1 692.7 2.5 141.3 30.1 284.4 2.1 3 328.5 17.4 576.4 32.8 843.0 17.7 226.9 5.7 332.7 30.5 5 434.6 26.8 654.5 32.1 934.2 0.7 275.2 12.7 423.7 24.5 7 518.8 4.7 720.0 26.4 975.9 7.6 330.0 7.9 482.2 26.4 10 620.1 0.6 813.5 20.0 380.0 0.5 559.9 26.9 15 786.2 25.2 930.5 13.7 499.4 18.8 653.2 37.7 30 912.2 0.8 714.8 7.5 931.2 9.7 60 91 1.5 5.8 DM300NaOH BM600Raw BM600DI BM600NaOH PM300Raw 1 550.7 39.4 231.8 17.9 228.1 3.6 259.2 2.7 135.6 17.7 3 680.6 13.7 285.9 6.9 288.4 11.4 293.2 11.8 184.0 1.8 5 770.2 3.3 289.2 20.0 300.4 14.2 336.2 26.9 200.4 23.6 7 835.8 15.1 312.8 23.3 309.0 16.7 360.8 3.4 217.0 15.1 10 923.0 35.2 330.9 16.7 324.9 11.7 376.4 20.4 237.5 9.9 15 379.4 20.2 355.0 26.8 415.5 21.1 276.2 14.4 30 462.7 17.8 455.0 25.4 497.3 22.0 353.8 32.3 60 600.9 16.4 594.3 15.0 643.5 31.0 491.6 24.1 PM300DI DDM500Raw DDM500DI 1 199.0 16.9 236.5 27.5 286.3 34.3 3 265.0 17.9 292.0 8.4 369.1 30.3 5 298.0 17.5 327.5 14.2 419.3 29.9 7 320.5 17.2 365.6 16.1 459.2 17.9 10 333.9 13.1 394.3 11.9 488.3 1.8 15 372.4 2. 7 466.4 11.5 563.7 41.6 30 464.0 22.8 542.6 10.4 734.8 1.3 60 691.0 3.3 748.2 2.8 956.8 5.9 Figure 5.2 179 Time C t C t C t C t C t C t h µg L µg L µg L µg L µg L µg L BC Sand IS = 0.1 mM IS = 1 mM IS = 10 mM IS = 0.1 mM IS = 1 mM IS = 10 mM AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD LCM 0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 0.2 1.7 0.4 3.3 0.0 3.1 0.1 76.1 0.1 88. 2 0.0 95.4 0.5 0.5 2.4 0.8 3.3 0.4 3.2 0.2 75.4 0.1 86.8 1.0 93.9 0.7 1 1.3 0.2 2.9 1.1 2.9 0.3 69.6 0.1 82.2 0.1 90.0 0.0 2 1.7 0.7 1.9 0.5 2.1 0.2 69.8 0.4 82.2 0.3 90.5 0.3 4 1.1 0.2 2.6 1.3 2.4 0.3 69.3 0.6 80.8 0.8 88.7 0.2 8 0.8 0.0 2.1 0.8 2.8 0.3 69.5 0.3 81.8 0.4 89.7 0.2 OTC 0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 0. 2 0.5 0.2 0.4 0.1 0.3 0.0 18.3 0.7 17.2 2.0 15.9 1.5 0.5 0.1 0.2 0.9 0.5 0.2 0.0 14.7 1.5 14.2 2.2 11.3 1.6 1 0.6 0.8 1.2 1.1 0.3 0.1 9.8 0. 4 8.2 0.2 9.4 0.2 2 0.1 0.1 0.8 0.9 0.1 0.0 8.7 0.4 8.4 0.5 9.0 0.7 4 0.2 0.3 0.9 0.8 0.1 0.0 8.3 0.7 8.8 0.1 9.1 0.1 8 0.3 0.5 0.4 0.6 0.0 0.0 8.9 0.5 8.5 0.3 9.1 0.2 SMX 0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 100.0 0.0 0.2 1.4 0.1 2.0 0.3 1.7 0.1 100.6 1.5 101.3 1.0 100.5 1.5 0.5 1.4 0.0 2.6 1.0 2.1 0.3 100.0 1.6 100.5 2.4 100.5 0.8 1 3.2 2.5 3.3 2.5 2.0 0.4 100.1 1.7 100.6 0.6 100.9 1.0 2 1.7 1.1 2.1 1.2 1.5 0.2 100.3 1.8 100.2 1.6 100.1 1.4 4 1.6 0.3 3.0 2.4 1.7 0.4 99 .2 1.8 100.5 1.3 100.4 0.9 8 1.5 0.4 2.7 2.0 1.6 0.4 99.9 1.8 100.4 0.8 100.5 1.1 180 Figure 5.4 Tracer experiments PV C / C 0 PV C / C 0 PV C / C 0 AVG SD AVG SD AVG SD 0.15 0.00 0.0 0 2.83 0.91 0.01 5.52 0.00 0.00 0.31 0.00 0.00 2.99 0.43 0.03 5.67 0.00 0.00 0.46 0.00 0.00 3.15 0.06 0.02 5.83 0.00 0.00 0.62 0.00 0.00 3.31 0.00 0.00 5.99 0.00 0.00 0.78 0.01 0.00 3.46 0.00 0.00 6.15 0.00 0.00 0.94 0.30 0.01 3.62 0.00 0.00 6.31 0.00 0.00 1.09 0.82 0.04 3.78 0.00 0.00 6.46 0.00 0.00 1.25 0.99 0.01 3.94 0.00 0.00 6.62 0.00 0.00 1.41 1.00 0.01 4.10 0.00 0.00 6.78 0.00 0.00 1.57 1.00 0.00 4.25 0.00 0.00 6.94 0.00 0.00 1.73 1.00 0.01 4.41 0.00 0.00 7.10 0.00 0.00 1.88 1.01 0.01 4.57 0.00 0.00 7.25 0.00 0.00 2.04 0.99 0.00 4.73 0.00 0.00 7.41 0.00 0.00 2.20 0.99 0.00 4.89 0.00 0.00 2.36 1.00 0.00 5.04 0.00 0.00 2.52 1.00 0.01 5.20 0.00 0.00 2.67 0.99 0.00 5. 36 0.00 0.00 Figure 5.7 BC only experiments LCM - BC co - transport experiments IS=0.1 mM IS=1 mM IS=10 mM IS=0.1 mM IS=1 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.02 0.01 0. 01 0.00 0.00 0.00 0.07 0.00 0.02 0.01 0.00 0.00 0.94 0.25 0.01 0.07 0.01 0.01 0.00 0.38 0.06 0.08 0.03 0.02 0.01 1.09 0.64 0.05 0.15 0.01 0.01 0.00 0.69 0.06 0.15 0.03 0.02 0.01 1.25 0.82 0.01 0.20 0.01 0.01 0.00 0.77 0.02 0.16 0.02 0.02 0.01 1.41 0.85 0.01 0.21 0.02 0.01 0.00 0.79 0.00 0.17 0.02 0.02 0.01 1.57 0.85 0.01 0.21 0.03 0.01 0.00 0.80 0.00 0.17 0.02 0.02 0.00 1.73 0.86 0.01 0.21 0.03 0.01 0.00 0.80 0.00 0.17 0.02 0.02 0.01 1.88 0.86 0.01 0.21 0.03 0.01 0.00 0.80 0.01 0.18 0.02 0.02 0.01 2 .04 0.85 0.00 0.21 0.04 0.01 0.00 0.80 0.01 0.18 0.03 0.02 0.01 2.20 0.85 0.00 0.20 0.03 0.01 0.00 0.79 0.01 0.19 0.02 0.02 0.01 2.36 0.85 0.01 0.20 0.03 0.01 0.00 0.79 0.00 0.19 0.03 0.02 0.01 2.52 0.85 0.01 0.20 0.03 0.01 0.00 0.77 0.00 0.18 0.02 0.02 0.01 2.67 0.86 0.02 0.18 0.04 0.01 0.00 0.78 0.01 0.17 0.01 0.02 0.00 2.83 0.79 0.05 0.13 0.06 0.01 0.00 0.63 0.00 0.13 0.00 0.01 0.00 2.99 0.42 0.11 0.06 0.06 0.00 0.00 0.28 0.05 0.07 0.01 0.00 0.00 3.15 0.11 0.05 0.03 0.03 0.00 0.00 0.08 0.04 0.03 0 .00 0.00 0.01 3.31 0.02 0.02 0.01 0.02 0.00 0.00 0.03 0.02 0.01 0.00 0.00 0.00 3.46 0.00 0.00 0.01 0.01 0.00 0.00 0.01 0.01 0.01 0.01 0.00 0.00 3.62 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 3.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0 0.00 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 181 4.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.04 0.00 0.00 0.00 0.00 0. 00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.83 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.31 0.00 0 .00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.9 4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 .00 OTC - BC co - transport experiments SMX - BC co - transport experiments IS=0.1 mM IS=1 mM IS=10 mM IS=0.1 mM IS=1 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0. 00 0.00 0.01 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.78 0.04 0.00 0.02 0.01 0.00 0.00 0.02 0.02 0.03 0.03 0.00 0.00 0.94 0.29 0.02 0.08 0.01 0.01 0.00 0.26 0.07 0.11 0.06 0.01 0.00 1.09 0.60 0.02 0.13 0.02 0.02 0.00 0.59 0.05 0.16 0.04 0.02 0.00 1.25 0.72 0.02 0.15 0.02 0.02 0.00 0.74 0.03 0.18 0.03 0.02 0.00 1.41 0.75 0.01 0.16 0.02 0 .02 0.00 0.78 0.01 0.19 0.02 0.02 0.00 1.57 0.76 0.02 0.16 0.02 0.02 0.00 0.81 0.01 0.19 0.02 0.02 0.00 1.73 0.76 0.02 0.16 0.02 0.02 0.00 0.82 0.02 0.19 0.03 0.02 0.00 1.88 0.77 0.02 0.17 0.02 0.02 0.00 0.84 0.01 0.19 0.02 0.02 0.00 2.04 0.77 0.02 0.1 7 0.02 0.02 0.00 0.84 0.01 0.20 0.02 0.02 0.00 2.20 0.77 0.02 0.17 0.01 0.02 0.00 0.84 0.00 0.20 0.02 0.02 0.00 2.36 0.77 0.02 0.17 0.02 0.02 0.00 0.85 0.01 0.20 0.02 0.02 0.00 2.52 0.77 0.02 0.17 0.02 0.02 0.00 0.86 0.00 0.20 0.02 0.02 0.00 2.67 0.77 0.01 0.16 0.02 0.02 0.00 0.86 0.01 0.20 0.02 0.02 0.00 2.83 0.66 0.00 0.11 0.00 0.01 0.00 0.74 0.01 0.14 0.01 0.01 0.01 2.99 0.32 0.01 0.05 0.01 0.00 0.00 0.37 0.01 0.05 0.02 0.00 0.00 3.15 0.09 0.01 0.02 0.01 0.00 0.00 0.11 0.00 0.01 0.00 0.00 0.00 3. 31 0.02 0.00 0.01 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 3.46 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 3.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 3.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 4.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0. 01 0.00 0.00 4.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 4.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 4.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 5.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 182 5.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 5.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 5.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 5.67 0.00 0.00 0.00 0.00 0.00 0.00 0 .00 0.00 0.00 0.01 0.00 0.00 5.83 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 5.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 6.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 6.31 0.00 0.00 0.00 0.00 0.0 0 0.00 0.00 0.00 0.00 0.01 0.00 0.00 6.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 6.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 6.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 7.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 Figure 5.9 LCM only experiments LCM - BC co - transport experiments IS=0.1 mM IS=1 mM IS=10 mM IS=0.1 mM IS=1 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0. 00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.02 0.02 0.00 0.00 0.94 0.00 0.00 0.00 0.00 0.00 0.00 0.37 0.05 0.12 0.04 0.02 0.01 1.09 0.00 0.00 0.00 0.00 0.03 0.02 0.66 0.06 0.19 0.03 0.05 0.01 1.25 0.00 0.00 0.00 0.00 0.17 0.06 0.73 0.04 0.20 0.02 0.06 0.01 1.41 0.00 0.00 0.00 0.00 0.43 0.05 0.76 0 .01 0.20 0.02 0.07 0.01 1.57 0.00 0.00 0.01 0.01 0.67 0.03 0.77 0.02 0.21 0.03 0.07 0.01 1.73 0.00 0.00 0.06 0.02 0.78 0.02 0.76 0.01 0.21 0.02 0.07 0.01 1.88 0.00 0.00 0.15 0.03 0.85 0.01 0.76 0.01 0.21 0.03 0.07 0.01 2.04 0.01 0.00 0.28 0.04 0.87 0.0 2 0.75 0.01 0.21 0.03 0.07 0.01 2.20 0.05 0.01 0.42 0.04 0.90 0.01 0.75 0.01 0.21 0.03 0.07 0.01 2.36 0.12 0.02 0.52 0.04 0.92 0.02 0.75 0.01 0.22 0.03 0.06 0.01 2.52 0.21 0.02 0.61 0.04 0.91 0.02 0.73 0.01 0.21 0.02 0.07 0.01 2.67 0.29 0.03 0.66 0.05 0.92 0.01 0.73 0.01 0.20 0.01 0.06 0.00 2.83 0.36 0.02 0.71 0.06 0.94 0.02 0.60 0.00 0.16 0.00 0.05 0.01 2.99 0.42 0.01 0.75 0.06 0.93 0.00 0.28 0.05 0.10 0.01 0.04 0.00 3.15 0.46 0.01 0.77 0.05 0.84 0.05 0.09 0.04 0.04 0.01 0.04 0.01 3.31 0.49 0.01 0. 79 0.06 0.62 0.06 0.03 0.02 0.02 0.00 0.04 0.01 3.46 0.51 0.02 0.77 0.05 0.37 0.04 0.02 0.01 0.02 0.01 0.04 0.01 3.62 0.52 0.01 0.74 0.06 0.22 0.02 0.01 0.00 0.01 0.00 0.04 0.00 3.78 0.52 0.01 0.65 0.05 0.14 0.01 0.01 0.00 0.01 0.00 0.05 0.00 3.94 0.46 0.01 0.52 0.06 0.09 0.01 0.01 0.00 0.01 0.00 0.05 0.00 4.10 0.39 0.01 0.40 0.04 0.07 0.01 0.01 0.00 0.01 0.00 0.05 0.00 4.25 0.30 0.01 0.31 0.04 0.05 0.01 0.01 0.00 0.01 0.00 0.05 0.00 4.41 0.23 0.02 0.23 0.04 0.04 0.01 0.01 0.00 0.01 0.00 0.05 0.00 4 .57 0.17 0.02 0.18 0.04 0.04 0.01 0.01 0.00 0.01 0.00 0.05 0.00 4.73 0.12 0.01 0.14 0.03 0.03 0.00 0.01 0.00 0.01 0.00 0.05 0.00 4.89 0.10 0.01 0.12 0.03 0.03 0.01 0.01 0.00 0.01 0.00 0.05 0.00 5.04 0.07 0.01 0.10 0.03 0.02 0.00 0.01 0.01 0.01 0.00 0.05 0.00 5.20 0.05 0.01 0.08 0.03 0.02 0.00 0.01 0.00 0.01 0.00 0.05 0.01 5.36 0.04 0.01 0.07 0.02 0.02 0.00 0.01 0.00 0.01 0.00 0.05 0.01 5.52 0.03 0.00 0.06 0.02 0.02 0.00 0.01 0.01 0.01 0.00 0.05 0.00 5.67 0.03 0.00 0.06 0.02 0.02 0.00 0.01 0.00 0.01 0 .00 0.05 0.00 183 5.83 0.02 0.00 0.05 0.02 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.00 5.99 0.02 0.00 0.04 0.02 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.00 6.15 0.02 0.00 0.04 0.02 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.00 6.31 0.01 0.00 0.04 0.02 0.01 0.00 0.01 0.0 0 0.01 0.00 0.05 0.01 6.46 0.01 0.00 0.03 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 6.62 0.01 0.00 0.03 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 6.78 0.01 0.00 0.03 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 6.94 0.01 0.00 0.03 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 7.10 0.01 0.00 0.02 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 7.25 0.01 0.00 0.02 0.01 0.01 0.00 0.01 0.00 0.02 0.00 0.05 0.01 7.41 0.01 0.00 0.02 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.05 0.01 OTC only experiments OTC - BC co - transport experiments IS=0.1 mM IS=1 mM IS=10 mM IS=0.1 mM IS=1 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.02 0.01 0.00 0.00 0.94 0.00 0 .00 0.00 0.00 0.00 0.00 0.29 0.02 0.08 0.01 0.01 0.00 1.09 0.00 0.00 0.00 0.00 0.00 0.00 0.60 0.02 0.13 0.02 0.02 0.00 1.25 0.00 0.00 0.00 0.00 0.00 0.00 0.72 0.02 0.15 0.02 0.02 0.00 1.41 0.00 0.00 0.00 0.00 0.00 0.00 0.75 0.01 0.16 0.02 0.02 0.00 1.5 7 0.00 0.00 0.00 0.00 0.00 0.00 0.76 0.02 0.16 0.02 0.02 0.00 1.73 0.00 0.00 0.00 0.00 0.00 0.00 0.76 0.02 0.16 0.02 0.02 0.00 1.88 0.00 0.00 0.00 0.00 0.00 0.00 0.77 0.02 0.16 0.02 0.02 0.00 2.04 0.00 0.00 0.00 0.00 0.00 0.00 0.77 0.02 0.17 0.02 0.02 0 .00 2.20 0.00 0.00 0.00 0.00 0.00 0.00 0.76 0.02 0.17 0.01 0.02 0.00 2.36 0.00 0.00 0.00 0.00 0.00 0.00 0.77 0.02 0.17 0.02 0.02 0.00 2.52 0.00 0.00 0.00 0.00 0.00 0.00 0.76 0.02 0.17 0.02 0.02 0.00 2.67 0.00 0.00 0.00 0.00 0.00 0.00 0.77 0.01 0.16 0.0 2 0.02 0.00 2.83 0.00 0.00 0.00 0.00 0.00 0.00 0.65 0.00 0.11 0.00 0.01 0.00 2.99 0.00 0.00 0.00 0.00 0.00 0.00 0.32 0.01 0.05 0.01 0.00 0.00 3.15 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.01 0.02 0.01 0.00 0.00 3.31 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.01 0.00 0.00 0.00 3.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.00 0.00 0.00 0. 00 0.00 0.00 0.00 0.00 0.00 4.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.20 0.00 0.00 0.00 0 .00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.83 0.00 0.0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 184 6.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0 7.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SMX only experiments SMX - BC co - transport experiments IS=0.1 mM IS=1 mM IS=10 mM IS=0.1 mM IS=1 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.31 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.78 0.00 0.00 0.01 0.03 0.01 0.01 0.04 0.02 0.03 0.03 0.01 0.00 0.94 0.10 0.08 0.35 0.15 0.29 0.00 0.28 0 .06 0.12 0.06 0.02 0.00 1.09 0.72 0.15 0.83 0.12 0.77 0.00 0.60 0.05 0.18 0.04 0.03 0.00 1.25 0.95 0.02 0.96 0.06 0.91 0.05 0.74 0.03 0.20 0.03 0.03 0.00 1.41 1.00 0.01 1.00 0.02 1.01 0.02 0.79 0.01 0.21 0.02 0.03 0.01 1.57 1.01 0.02 1.00 0.01 1.03 0.0 1 0.81 0.01 0.21 0.02 0.03 0.00 1.73 1.01 0.06 1.00 0.03 1.03 0.03 0.82 0.02 0.21 0.03 0.03 0.00 1.88 0.99 0.01 1.00 0.00 1.00 0.02 0.84 0.01 0.21 0.02 0.03 0.00 2.04 1.01 0.03 1.00 0.02 0.99 0.09 0.85 0.01 0.21 0.02 0.03 0.00 2.20 0.99 0.03 0.99 0.01 0.99 0.08 0.84 0.01 0.22 0.02 0.03 0.00 2.36 1.02 0.02 1.01 0.00 0.98 0.08 0.86 0.01 0.22 0.02 0.03 0.00 2.52 0.98 0.03 0.99 0.01 1.06 0.01 0.86 0.00 0.22 0.02 0.03 0.00 2.67 1.00 0.01 1.00 0.00 0.94 0.12 0.87 0.01 0.22 0.02 0.03 0.00 2.83 0.95 0.04 0. 88 0.08 0.97 0.07 0.74 0.02 0.15 0.01 0.02 0.01 2.99 0.63 0.06 0.39 0.14 0.43 0.02 0.39 0.01 0.06 0.02 0.01 0.00 3.15 0.16 0.03 0.07 0.06 0.13 0.04 0.14 0.01 0.02 0.00 0.00 0.00 3.31 0.02 0.00 0.00 0.01 0.03 0.02 0.05 0.00 0.01 0.00 0.00 0.00 3.46 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.01 0.01 0.00 0.00 0.00 3.62 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.01 0.01 0.01 0.00 0.00 3.78 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.00 0.00 0.00 4 .10 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.00 0.00 0.00 4.25 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.00 0.00 4.41 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.01 0.01 0.00 4.57 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 4.73 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.01 0.01 0.00 4.89 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 5.04 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 5.20 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0 .01 0.01 0.00 5.36 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.00 0.01 0.00 5.52 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 5.67 0.00 0.00 0.00 0.01 0.00 0.00 0.02 0.00 0.01 0.01 0.01 0.00 5.83 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.0 0 0.01 0.01 0.01 0.00 5.99 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 6.15 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 6.31 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 6.46 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.01 0.01 0.00 6.62 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 6.78 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 6.94 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 7.10 0.00 0.00 0.00 0.01 0. 00 0.00 0.03 0.00 0.01 0.01 0.01 0.00 7.25 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.01 0.01 0.00 185 7.41 0.00 0.00 0.00 0.01 0.00 0.00 0.03 0.01 0.01 0.01 0.01 0.00 LCM - BC co - transport experiments Dissolved LCM BC - associated LCM Dissolved LCM BC - associated LCM Dissolved LCM BC - associated LCM IS=0.1 mM IS=0.1 mM IS=1 mM IS=1 mM IS=10 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0. 31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.01 0.00 0.06 0.00 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.94 0.02 0.00 0.36 0.05 0.04 0.01 0.08 0.03 0.01 0.01 0.01 0.01 1.09 0.01 0.00 0.65 0.06 0.05 0.00 0.13 0.03 0.03 0.00 0.02 0.01 1.25 0.02 0.01 0.72 0.02 0.05 0.01 0.15 0.02 0.04 0.00 0.02 0.01 1.41 0.01 0.01 0.74 0.00 0.05 0.01 0.15 0.02 0.05 0. 00 0.02 0.01 1.57 0.02 0.02 0.75 0.00 0.05 0.01 0.16 0.02 0.05 0.01 0.02 0.00 1.73 0.01 0.01 0.75 0.00 0.05 0.00 0.16 0.02 0.05 0.00 0.02 0.01 1.88 0.01 0.00 0.75 0.01 0.04 0.01 0.16 0.02 0.05 0.01 0.02 0.01 2.04 0.01 0.00 0.74 0.01 0.05 0.00 0.17 0.02 0.05 0.01 0.02 0.01 2.20 0.01 0.00 0.74 0.01 0.04 0.01 0.17 0.02 0.05 0.01 0.02 0.01 2.36 0.01 0.00 0.74 0.00 0.04 0.01 0.17 0.02 0.05 0.00 0.02 0.01 2.52 0.01 0.00 0.72 0.00 0.04 0.00 0.17 0.02 0.05 0.01 0.02 0.01 2.67 0.01 0.00 0.72 0.01 0.04 0.00 0 .16 0.01 0.05 0.00 0.02 0.00 2.83 0.01 0.00 0.59 0.00 0.04 0.00 0.12 0.00 0.04 0.00 0.01 0.00 2.99 0.02 0.00 0.26 0.05 0.03 0.01 0.07 0.01 0.04 0.00 0.00 0.00 3.15 0.01 0.01 0.08 0.04 0.02 0.00 0.03 0.00 0.04 0.00 0.00 0.01 3.31 0.01 0.00 0.03 0.01 0.0 1 0.00 0.01 0.00 0.04 0.01 0.00 0.00 3.46 0.00 0.00 0.01 0.01 0.01 0.00 0.01 0.01 0.04 0.01 0.00 0.00 3.62 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.04 0.00 0.00 0.00 3.78 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.10 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.25 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.41 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.57 0.01 0. 00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.73 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 4.89 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.04 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.20 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.36 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.52 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.67 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0. 00 5.83 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 5.99 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 6.15 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 6.31 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 6.46 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 6.62 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 6.78 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 6.94 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0 .05 0.01 0.00 0.00 7.10 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 7.25 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 7.41 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.05 0.01 0.00 0.00 OTC - BC co - transport experiments 186 D issolved OTC BC - associated OTC Dissolved OTC BC - associated OTC Dissolved OTC BC - associated OTC IS=0.1 mM IS=0.1 mM IS=1 mM IS=1 mM IS=10 mM IS=10 mM PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AVG SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.00 0. 00 0.04 0.00 0.00 0.00 0.02 0.01 0.00 0.00 0.00 0.00 0.94 0.00 0.00 0.29 0.02 0.00 0.00 0.08 0.01 0.00 0.00 0.01 0.00 1.09 0.00 0.00 0.60 0.02 0.00 0.00 0.13 0.02 0.00 0.00 0.02 0.00 1.25 0.00 0.00 0.72 0.02 0.00 0.00 0.15 0.02 0.00 0.00 0.02 0.00 1.41 0.00 0.00 0.75 0.01 0.00 0.00 0.16 0.02 0.00 0.00 0.02 0.00 1.57 0.00 0.00 0.76 0.02 0.00 0.00 0.16 0.02 0.00 0.00 0.02 0.00 1.73 0.00 0.00 0.76 0.02 0.00 0.00 0.16 0.02 0.00 0.00 0.02 0.00 1.88 0.00 0.00 0.77 0.02 0.00 0.00 0.16 0.02 0.00 0.00 0.02 0. 00 2.04 0.00 0.00 0.77 0.02 0.00 0.00 0.17 0.02 0.00 0.00 0.02 0.00 2.20 0.00 0.00 0.76 0.02 0.00 0.00 0.17 0.01 0.00 0.00 0.02 0.00 2.36 0.00 0.00 0.77 0.02 0.00 0.00 0.17 0.02 0.00 0.00 0.02 0.00 2.52 0.00 0.00 0.76 0.02 0.00 0.00 0.17 0.02 0.00 0.00 0.02 0.00 2.67 0.00 0.00 0.77 0.01 0.00 0.00 0.16 0.02 0.00 0.00 0.02 0.00 2.83 0.00 0.00 0.65 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.01 0.00 2.99 0.00 0.00 0.32 0.01 0.00 0.00 0.05 0.01 0.00 0.00 0.00 0.00 3.15 0.00 0.00 0.09 0.01 0.00 0.00 0.02 0.01 0 .00 0.00 0.00 0.00 3.31 0.00 0.00 0.02 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 3.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.78 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0 0.00 0.00 0.00 0.00 0.00 3.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.04 0.00 0.00 0.00 0. 00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.83 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.31 0 .00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.78 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 .00 0.00 SMX - BC co - transport experiments Dissolved SMX BC - associated SMX Dissolved SMX BC - associated SMX Dissolved SMX BC - associated SMX IS=0.1 mM IS=0.1 mM IS=1 mM IS=1 mM IS=10 mM IS=10 mM 187 PV C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 C / C 0 AVG SD AVG SD AV G SD AVG SD AVG SD AVG SD 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.31 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.46 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.01 0.00 0 .00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 0.01 0.00 0.02 0.02 0.00 0.00 0.03 0.03 0.00 0.00 0.00 0.00 0.94 0.03 0.00 0.25 0.06 0.02 0.00 0.10 0.05 0.01 0.00 0.01 0.00 1.09 0.03 0.00 0.57 0.05 0.02 0.00 0.16 0.04 0.02 0.00 0.02 0.00 1.25 0.03 0.01 0.71 0.0 3 0.02 0.00 0.18 0.02 0.02 0.00 0.02 0.00 1.41 0.04 0.00 0.76 0.01 0.02 0.00 0.18 0.02 0.02 0.00 0.02 0.00 1.57 0.04 0.00 0.78 0.01 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 1.73 0.04 0.00 0.78 0.02 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 1.88 0.04 0.00 0.81 0.01 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 2.04 0.04 0.00 0.81 0.01 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 2.20 0.04 0.00 0.81 0.00 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 2.36 0.04 0.00 0.82 0.01 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 2.52 0. 04 0.00 0.82 0.00 0.03 0.00 0.20 0.02 0.02 0.00 0.02 0.00 2.67 0.04 0.00 0.83 0.01 0.02 0.00 0.19 0.02 0.02 0.00 0.02 0.00 2.83 0.04 0.01 0.71 0.01 0.02 0.00 0.13 0.01 0.01 0.00 0.01 0.01 2.99 0.04 0.00 0.36 0.01 0.01 0.00 0.05 0.02 0.01 0.00 0.00 0.00 3.15 0.03 0.00 0.10 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 3.31 0.03 0.00 0.02 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.46 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.62 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.00 0.00 0. 00 0.00 3.78 0.02 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.94 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.10 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.25 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 4.41 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 4.57 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 4.73 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 4.89 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0 .01 0.01 0.00 0.00 0.00 5.04 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 5.20 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 5.36 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.00 5.52 0.03 0.00 0.00 0.00 0.01 0.0 0 0.00 0.01 0.01 0.00 0.00 0.00 5.67 0.02 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 5.83 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 5.99 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00 6.15 0.03 0.00 0.00 0.00 0.01 0.00 0.00 0.01 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