ENZYME PRETREATMENT OF FATS, OIL AND GREASE FROM RESTAURANT WASTE TO PROLONG DRAIN FIELD EFFECTIVENESS By Younsuk Dong A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Biosystems Engineering - Master of Science 2015 ABSTRACT ENZYME PRETREATMENT OF FATS, OIL AND GREASE FROM RESTAURANT WASTE TO PROLONG DRAIN FIELD EFFECTIVENESS By Younsuk Dong When a fast - food restaurant wastewater containing high strength of FOG is discharge d int o sewer s , it builds up over time and clogs the sewer pipe s . Similarly , when a fast - food restaurant wastewater flow s into a drain field, it adheres to the surface of inlet pipes, gravel and soil , which will restrict the flow and eventually clog the drain field either physically or biologically . In this study, the A dvanced G rease I nterceptor S ystem (AGIS) was used for enzym atic pretreatment o f wastewater from a fast - food restaurant. Th is system uses aeration equipment, baffles , and a one - time inoculum with an in - situ condition in order to microbiologically breakdown FOG. The effect of the decomposed FOG in a drain field has not been previously studied , the focus of this research . The objectives of this study were to examine the impact of enzyme treatment on changes of the characteristic of triglyceride, design a bench - scale drain field and assess performance , and determine the impact of wastewater with/without enzyme pretreatment on clogging. LC/MS results showed that enzyme treatment impacted the characteri stics of the triglycerides by breaking down the long chain fatty acid and reducing the number of double bonds . Bench - scale trenches with embedded soil moisture sensors for monitoring clogging proved to be a unique, an d effective method to investigate the i mpact of diverse feedstocks . All b ench - scale trenches removed a significant amount of COD, BOD 5 and FOG, regardless of their initial concentrations. The results from the laboratory trenches show ed that pretreatment of restaurant wastewater using an in - situ enzyme producing bacteria will delay clogging and premature drain field aging. Copyright by YOUNSUK DONG 2015 iv ACKNOWLEDGMENTS I would like to thank everyone for their support and I would not be able to start and complete this study withou t their help. I am truly thankful to my advisor, Dr. Steven Safferman who gave me the best guidance through the study. He is the best professor, I have ever met and gave me the support not only academically but also emotionally. He is not only a great men tor, but also a good friend. I t has been a huge honor to work with him. Thanks also to my committee, Dr. Timothy Harrigan and Dr. Yan (Susie) Liu. They have kindly given their time and expertise to help me to complete this research. In addition, I also th ank to Dr. Daniel Jones at Mass spectrometry facility in MSU, who trained and helped me to use Liquid Chromatography/Mass Spectrometry . I would like to thank to my research team, Lauren Costantini, Beth Swanberg and Alex Vincent. Thanks to my family for t heir endless love and support, my parents, Illwon Dong and JeongJa Choi and my sister , Jiyeon Dong , and my fiancé Yeoreum Lee . Last, thanks to my church members who have prayed for me, especially Pastor, Sungjong Cho, and his wife Yooja Chang , Deacon, S angh yu p Jeong. v TABLE OF CONTENTS LIST OF TABLES ................................ ................................ ................................ ........................ vii LIST OF FIGURES ................................ ................................ ................................ ..................... viii KEY TO ABBREVIATIONS ................................ ................................ ................................ ....... xii Chapter 1: Introduction ................................ ................................ ................................ ................... 1 1.1. Problem statement ................................ ................................ ................................ ............ 4 1.2. Objective ................................ ................................ ................................ .......................... 5 Chapter 2: Literature review ................................ ................................ ................................ ........... 6 2.1. Composition of FOG ................................ ................................ ................................ ........ 6 2.2. FOG treatment technologies ................................ ................................ ............................. 6 2.2.1. Grease t rap ................................ ................................ ................................ ................ 7 2.2.2. Enzyme treatment ................................ ................................ ................................ ..... 7 2.2.2.1. Direct enzyme hydrolysis ................................ ................................ ...................... 8 2.2.2.2. In - situ enzyme production ................................ ................................ ..................... 8 2.2.2.3. Enzyme activ ity ................................ ................................ ................................ ... 11 2.3. Commercial system ................................ ................................ ................................ ........ 11 2.4. Operation of drain field ................................ ................................ ................................ .. 13 C hapter 3: Methods ................................ ................................ ................................ ....................... 16 3.1. Enzyme impact on the characteristics of triglycerides ................................ ................... 16 3.1.1. Enzyme pretreatment system ................................ ................................ .................. 16 3.1.2. Sample collection and storage ................................ ................................ ................ 17 3.1.3. Sample preparation ................................ ................................ ................................ . 17 3.1.4 . An alysis ................................ ................................ ................................ ................... 19 3.1.5. Data i nterpretation ................................ ................................ ................................ .. 20 3.2. Bench - scale drain field design and performance ................................ ........................... 20 3.2.1. Trench design ................................ ................................ ................................ .......... 20 3.2.2. Instrumentation ................................ ................................ ................................ ....... 25 3.2.3. Analytical ................................ ................................ ................................ ................ 27 3.2.4. Data interpretation ................................ ................................ ................................ .. 27 3.3. Impact of wastewaters with/without enzyme pretreatment on clogging ........................ 28 3.3.1 . Sample c ollection and storage ................................ ................................ ................. 31 3.3.2 . Operation ................................ ................................ ................................ ................. 32 3.3.3 . Analysis ................................ ................................ ................................ ................... 34 3.3.4. Data interpretation ................................ ................................ ................................ .. 36 Chapter 4: Result and Discussion ................................ ................................ ................................ . 37 4.1. Enzyme impact the characteris tics of triglycerides ................................ ........................ 37 4.2. Bench - scale drain field design and performance ................................ ........................... 39 4.2.1. Phase 1 ................................ ................................ ................................ .................... 39 vi 4.2.2. Phase 2 ................................ ................................ ................................ .................... 40 4.2.3. Phase 3 ................................ ................................ ................................ .................... 46 4.2.4. Phase 4 ................................ ................................ ................................ .................... 53 4.3. Impact of wastewater with/without enzyme pretreatment on clogging ......................... 61 4.3.1. Moisture Content s in trenches ................................ ................................ ................ 61 4.3.2. Volatile solids ................................ ................................ ................................ ......... 69 4.3.3. Visual Observation ................................ ................................ ................................ .. 74 Chapter 5: Conclusion and recommendations ................................ ................................ .............. 80 5.1. Summary ................................ ................................ ................................ ........................ 80 5.2 . Recommendation ................................ ................................ ................................ ............ 83 APPENDICES ................................ ................................ ................................ .............................. 88 APPENDIX A: Construction pictures ................................ ................................ ...................... 89 A PPENDIX B: Analytical result ................................ ................................ .............................. 91 A PPENDIX C: QAQC ................................ ................................ ................................ ............. 94 REFERENCES ................................ ................................ ................................ ............................. 95 vii LIST OF TABLES Table 1. FOG hydrolysis studies using enzymes ................................ ................................ ............ 9 Table 2. In - situ enzyme production for FOG hy drolysis ................................ .............................. 10 Table 3. Wastewater analytical parameters ................................ ................................ .................. 27 Table 4. Feedstock constituents for K itchen wastewater ................................ .............................. 30 Table 5. Total kitchen and sanitary wastewater disc harges per day ................................ ............. 31 Table 6. Mixture for feedstock in 18.9L ( 5 gal ) carboy ................................ ................................ 31 Table 7. Operations by phases ................................ ................................ ................................ ...... 33 Table 8. Parameter analysis of influent concentration of each trench in Phase 1 ......................... 40 Table 9. Microbial Community in a drain field (Atoyan et al. 2013) ................................ ........... 86 Table 10. Literature reviews of enzyme activity on biogas production ................................ ........ 87 Table 11 . Phase 2 performance result ................................ ................................ ........................... 91 Table 12 . Phase 3 performance result ................................ ................................ ........................... 92 Table 13 . Phase 4 performance result ................................ ................................ ........................... 93 Table 14 . Relative percentage difference bet ween standards ................................ ....................... 94 Table 15 . Relative percentage difference between replicates ................................ ....................... 94 viii LIST OF FIGURES Figure 1. FOG build up in a sewer (Town of Tyngsborough, 2015) ................................ .............. 2 Figure 2 . AGIS installed in the septic tank (Sustainable Environmental Technologies 2012) .... 12 Figure 3 . Pipe interior before AGIS treatment and 17 months after implementation (Sustainable Environmental Technologies 2009) ................................ ................................ . 13 Figure 4. Soil phases from dry to saturation ................................ ................................ ................. 14 Figure 5. Xenosep Solid - Phase Extraction system setup ................................ .............................. 18 Figure 6. FOG extraction of kitchen wastewater treated with AGIS ................................ ............ 18 Figure 7. Solid FOG extracted from samples ................................ ................................ ............... 19 Figure 8. Xevo G2 - S TOF, Mass Spectrometry Facility, Michigan State University .................. 19 Figure 9. Schematic of trench ................................ ................................ ................................ ....... 21 Figure 10. Dimensions of trench ................................ ................................ ................................ ... 21 Figure 11. Front view of trench ................................ ................................ ................................ .... 22 Figure 12. Profile view of trench ................................ ................................ ................................ .. 23 Figure 13. Top view of trench ................................ ................................ ................................ ....... 24 Figure 14. Overview of trench construction ................................ ................................ ................. 25 Figure 15. CS 616 Water Content Reflectometer ................................ ................................ ......... 25 Figure 16. Ins tallation of 30 of CS 616 Water content reflectometer connected with AM 16/32 multiplexer and CR 1000 datalogger ................................ ................................ .................... 26 Figure 17. Type K thermocouple with PVC - insulated probe and epoxy - coated tip ..................... 26 Figure 18. Flow diagram of brown grease at a fast - food restaurant ................................ ............. 29 Figure 19. Detail view of influent pipe ................................ ................................ ......................... 32 Figure 20. Diagram of soil sampling locations for 1 st VS analysis, brown boxes indicate soil sample collection locations. ................................ ................................ ................................ .. 34 ix Figure 21. Diagram o f soil sampling locations for 2 nd VS analysis , b rown boxes indicate soil sample collection locations. ................................ ................................ ................................ .. 35 Figure 22 . Relative proportion of double bonds in triglycerides of Kitchen wastewater. The values are the total number of double bonds that were found in the triglycerides. ....... 37 Figure 23 . Relative proportion of double bonds in triglycerides of Treated kitchen wastewat er , The value are the total number of double bonds that were found in the triglycerides. ......... 38 Figure 24 . Average influent and effluent concentrations of COD in Phase 2 .............................. 41 Figure 25. Average influent and effluent concentrations of FOG in Phase 2 ............................... 42 Figure 26. Average influent and effluent concentrations of TP in Phase 2 ................................ .. 43 Figure 27. Average influent and effluent concentrations of TN in Phase 2 ................................ . 44 Figure 28. Average influent and effluent concentrations of nitrate in Phase 2 ............................. 45 Figure 29. Average influent and effluent concentrations of COD in Phase 3 .............................. 47 Figure 30. Average of influ ent and effluent concentration of BOD 5 in Phase 3 .......................... 48 Figure 31. Average influent and effluent concentrations of FOG in Phase 3 ............................... 49 Figure 32. Average influent and effluent concentrations of TP in Phase 3 ................................ .. 50 Figure 33. Average influent and effluent concentrations of TN in Phase 3 ................................ . 51 Figure 34. Average influent and effluent concentrations of ammonia in Phase 3 ........................ 52 Figure 35. Average influent and effluent concentrations of nitrate in Phase 3 ............................. 53 Figure 36. Average influent and effluent concentrations of COD in Phase 4 .............................. 54 Figure 37. Average influent and effluent concentrations of BOD 5 in Phase 4 ............................. 55 Figure 38. Average of influent and effluent concentrations of FOG in Phase 4 .......................... 56 Figure 39. Average influent and ef fluent concentrations of TP in Phase 4 ................................ .. 57 Figure 40. Average of influent and effluent concentrations of TN in Phase 4 ............................. 58 Figure 41 . Average influent and effluent concentrations of ammonia in Phase 4 ........................ 59 Figure 42. Average influent and effluent concentrations of nitrate in Phase 4 ............................. 60 x Figure 43 . Schematic diagram of moisture sensor locations on a trench. Each circle represents a moisture sensor (not to scale). ................................ ................................ .............................. 61 Figure 44 . Daily moisture levels in the trench receiving Sanitary wastewater ............................. 62 Figure 45 . Daily moisture levels in trenches receiving Sanitary/kitchen wastewater (top) and Sanitary/treated kitchen wastewater (bottom) ................................ ................................ ...... 63 Figure 46 . Daily moisture level of the trench receiving Kitchen wastewater ............................... 64 Figure 47 . Daily moisture levels in the trench receiving Treate d kitchen wastewater ................. 65 Figure 48 . Moisture content of trench receiving Sanitary wastewater (10 minutes segments) .... 66 Figure 49 . Mo isture levels of trenches receiving Sanitary/kitchen (top) and Sanitary/treated kitchen (bottom) (10 minutes segments) ................................ ................................ ............... 67 Figure 50 . Moisture levels of trenches receiving Kitchen (top) and Trea ted kitchen (bottom) (10 minutes segments) ................................ ................................ ................................ .......... 68 Figure 51 . VS at 35.6 cm (14 inch) depth for columns 1 and 2 ................................ .................... 69 Figure 52. VS at 50.8 cm (20 inch) depth for columns 1 and 2 ................................ .................... 69 Figure 53 . VS of Sanitary trench at depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of the sandy loam ................................ ................................ ................................ ............ 71 Figure 54 . VS of Sanitary/kitchen trench at a depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam ................................ ................................ ................................ ... 71 Figure 55. VS of Sanitary/treat ed kitchen trench a t depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam ................................ ................................ .......................... 72 Figure 56. VS of Kitchen trench at depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam ................................ ................................ ................................ ........................ 72 Figure 57. VS Treated kitchen trench at depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam ................................ ................................ ................................ ............ 73 Figure 58 . Top view of Sanitary trench ................................ ................................ ........................ 74 Figure 59. Top view of Treated kitchen trench ................................ ................................ ............. 75 Figure 60 . Biomat was found i n the Treated kitchen trench ................................ ......................... 75 Figure 61 . Inlet pipe condition in the Sanitary trench after 505 days of operation ...................... 76 Figure 62 . I nlet pipe condition in the Sanitary/kitchen trench after 505 days of operation ......... 77 xi Figure 63 . Inlet pipe condition in the Sanitary/treated kitchen trench after 505 days of operation ................................ ................................ ................................ ................................ ............... 77 Figure 64 . Inlet pipe condition in the Kitchen trench after 337 days of operation ....................... 78 Figure 65. Inlet pipe from the Treated kitchen trench after 505 days of operation ...................... 79 Figure 66 . Effluent pipes ................................ ................................ ................................ ............... 89 Figure 67 . Trench construction ................................ ................................ ................................ ..... 89 Figure 68 . Three effluent outlets ................................ ................................ ................................ ... 90 Figure 69 . Moisture sensors locations ................................ ................................ .......................... 90 Figure 70 . Inside of inle t distribution pipe ................................ ................................ .................... 90 xii KEY TO ABBREVIATIONS Abbreviation Full Word FOG Fats, Oil and Grease AGIS Advanced Grease Interceptor System 1 Chapter 1: Introduction Fats, oil and grease (FOG) come f rom animal meat, cooking oil and dairy products. The chemical structure of FOG is a triglyceride. Each triglyceride is composed of 3 fatty acids connected with glycerol, which is an alcohol with three carbons, each bearing a hydroxyl group. A fatty acid ha s a long structure with usually 16 or 18 carbon atoms and potentially several double bonds . FOG containing fatty acids with a greater number of double bonds are less biodegradable and more cohesive (sticky). Cohesiveness of FOG results in producing non - bio degradable grease balls. Restaurants use animal meats, cooking oil and dairy products and produce FOG in their wastewater. Annual grease produced from a single restaurant ranges from 363 to 7,711 kg ( 800 to 17,000 lbs) (U.S. Environmental Protection Agency 2007) . In the United States, the total amount of restaurant grease generated and collected and recycled by renderers in 2010 w ere 2 , 061 b illion kg and 1 , 092 kg ( 4,543 billion lbs and 2,408 billion lbs), respectively . Consequently, only 53 % of greases was recycled (U.S. Environmental Protection Agency 2014) . There are two types of FOG. Yellow grease originates from fryer oil and other such concentrated sources. This FOG is not contaminated with water, wastewater a nd solid waste and is usually recycled for animal feed and biofuels . Brown grease results from rinsing and washing dishes, sanitizing, mopping floors and washing rags. Unlike yellow grease, brown grease is contaminated and is typically discharged into the wastewater sys tem, which results in sewer blockages as it builds up over time. When sewer pipes are clogged ( Figure 1 ) , raw sewage overflow s into homes, streets, rivers and parks and people who are exposed to wastewater have a h igher chance of contracting diseases. 2 Figure 1 . FOG build up in a sewer (Town of Tyngsborough, 2015) FOG plays a major r ole in sewer clogging and is expensive to remove. In 2004, the U.S. EPA reported that there were 20,000 sanitary sewer overflows in the United States. Of these, 49 % were related to FOG clogging coming from restaurants, homes and industrial sources (U.S. Environmental Protection Agency 2004) . The United States spends $25 billion of tax dollars annu ally to manage FOG build up in sewers (Washtenaw County 2014) . The New York Times stated that 62 % of the 15,000 sewer backup complaints in New Your City were related to FOG accumulation (Gregory 2014) . FOG issues in sewers cost $3.5 million and $4.65 million, in San Francisco and New York City, respectively (San Francisco Water Power Sewer 2012; Gregory 2014) . In London, 10 tons of congealed fat and house hold waste blocked and broke a sewer and cost approximately $450,000 US dollars to repair (Ratcliffe 2015) . From these cases, it is clear that the FOG in a sewer is great concern all over the world and proper and sufficient management is needed. A drain field associated with on - site wastewater disposal is a complete treatment system using microbial, physical and chemical mechanisms. When fast food restaurant discharge wastewater containing FOG into a drain field, FOG adheres to the surface of inlet pipes, gravels 3 and soil, restricts the flow an d eventually clogs the drain field. FOG will not coagulat when the temperature is below 60°C (140 °F) and typical temperature of drain field, at 61 cm (2 ft) below from the ground, is from 3°C (37°F) to 20°C (68°F) (Naylor & Gustin 2015) . Therefore, FOG in a drain field will be coagulated and clog the porosity of pipe, gravel , and/or soil. In general, the average of typical life of a drain field is 25 30 years (Mckenzie 2010) . However, the high strength of FOG in fast - food restaurant wastewater will premature the life of drain field. Wod alski (2012) reported that drain field in a large and quick - serve restaurant was replaced three times in first five years of business, because of FOG (Wodalski 2012) . In order to prevent sewer and drain field clogging, FOG collection and/or treatment systems are required so that the discharge limit of 100 mg/L should not be exceeded (U.S. Environmental Protection Agency 2007) . These systems can use physical or biological treatment techniques. The common physical treatment technology is a grease trap. A grease trap intercepts most of the FOG and solids by using baffles in a tank to trap floating FOG and separates it from the wastewater. A grease trap must be pumped when 25 % of it is full (Leverenz et al. 2002) otherwise the grease trap loses efficiency. The efficient grease trap decreases during peak wastewater discharges. An alternative to the grease trap is to pretreat wastewater containing FOG with enzymes . Enzymes, excreted from certain microbial populations, cleave long chain fatty acids and double bonds. The greater the number of double bonds in a triglyceride, the more difficult it is to biodegrade (de Waard et al. 1993) . Once FOG is broken down, it will not be restored back to its original form and it is not cohesive. The use of enzyme treatment at restaurants minimizes the cost of pumping, hauling and disposing of FOG. 4 1.1. Proble m statement Enzyme treatment of FOG prevents clogging in sewer pipes by converting triglycerides into fragment that do not adhere and cause wastewater constituents to conglomerate (Gajeski 2010) . Pretreatment of brown FOG using enzymes in a drain field has not been widely studied. The hypothesis of this research is that enzyme treatment breaks down long fatty acid chains, associated with the triglycerides, reducing clogging potential and extending the life of a drain field. Drain field clogging from fast - food restaurant wastewater can result from several scenarios, as listed below. - Kitchen wastewater containing a high concentration of FOG will clog the inlet pipe, even before the wastewater flows into the drain field. - Kitchen wastewater containing a high concentration of FOG flows into a drain fie ld , but the FOG adheres to the soil surface and clogs the drain field. - Kitchen wastewater pretreated with enzyme still clogs the drain field because of the high biodegradable organic loading consisting of FOG with low molecular weight s and fewer double bo nds. 5 1.2. Objective The above problem statement and hypothesis lead to the project objectives entailing assessing the effectiveness of enzymatic wastewater pretreatment in preventing the pr emature aging of a drain field. Sub - objectives follow. 1. Measure change s in the characteristics of triglycerides , resulting from enzymatic pretreatment. 2. Design a bench - scale drain field that represents a field - scale system. Observe the performance of drain field from different characteristics of wastewater. 3. Operate bench - scal e drain fields using different wastewater types, with and without enzymatic pretreatment. Assess the differences in performance to estimate if enzymatic pretreatment can potentially prevent premature aging of a drain field. Include soil water moisture sens ors to enable in situ clogging monitoring. 6 Chapter 2: Literature review This chapter discusses the composition of FOG, FOG treatment technologies, including the grease trap and enzymatic treatment, commercially available enzyme systems and the general op eration of a drain field. 2.1. Composition of FOG FOG is composed of a triglyceride which consists of three fatty acids and a glycerol. Typically, there are five long chain fatty acids that produce FOG, including M yristic acid (C14:0, C 14 H 28 O 2 ), P almitic acid (C16:0, C 16 H 32 O 2 ), S tearic acid (C16:0, C 18 H 36 O 2 ) , O leic acid (C18:1, C 18 H 34 O 2 ) and L inoletic acid (C18:2, C 18 H 32 O 2 ). The proportion of the five fatty acids that classified as saturated ( Myristic acid, Palmitic acid, Stearic acid) , monounsaturated ( Oleic a cid) and polyunsaturated ( Linoletic acid) determines the effectivene ss of hydrolysis. Monounsaturated and polyunsaturated fatty acids , which consist of double bonds, are more difficult to be degraded than saturated fatty acids (de Waard et al. 1993) . 2.2. FOG treatment technologies Several technologies have been used to treat a FOG. The following reviews each technology in detail. 7 2.2.1. Grease t rap To prevent sewer blockages, a gr ease trap is commonly used at restaurants. A typical grease trap collects FOG by cooling and flotation (Metcalf & Eddy 2003) . The trap requires maintenance including cleaning every 3 6 months (Leverenz et al. 2002) . The efficiency o f grease traps is relatively low resulting in a typical a FOG effluent concentration of 100 mg/L (Chan 2010; Chu & Ng 2000) . Aziz et al. (2011) show s that c hanging the shape and form of conventional grease abatement devices can improve the FOG capture efficiency. This study found that the 3 most important factors for efficient operation is the inlet configuration , baffle wall arrangement and the HRT . The study was conducted with bench - scale equipment and a computational fluid dynamics model (Aziz et al. 2011) . 2.2.2. Enzyme treatment Many bacteria are able to produce extracellular enzyme, including lipase. Lipase is one of the enzymes that break down FOG, also known as triacylglycerol ester hydr olases. Tang et al. (2012) found that enzyme treatment converts unsaturated fats (containing double bond) to saturated fats (containing single bond), resulting in increased biodegradability. Many researchers (Cavaleiro et al. 2013; Cammarota & Freire 2006; Jeganathan et al. 2006; Kunst et al. 1997; Daverey & Pakshirajan 2015; Wakelin & Forster 1997; Roheim 2003; Tang et al. 2012; Brooksbank et al. 2007; Mazlin 2012; Markossian et al. 2000; Tano - Debrah et al. 1999; Leal et al. 2006; Valladão et al. 2007; Moon & Song 2011) have investigated the effectiveness of enzyme treatment on FOG. These studies showed mixed results due to different enzymes and v ariables used in the studies, including the type of bacteria, temperature, retention time and dose. 8 Some processes hydrolyzed FOG by adding enzymes directly. Others hydrolyzed FOG by adding bacteria that excreted the enzymes (in situ enzyme production). 2.2.2.1. D irect enzyme hydrolysis Previous studies show that optimal temperature, hydraulic retention time (HRT) and dose are the major factors for maximizing efficiency of hydrolysis. Table 1 shows results from studies on the effectiveness of FOG hydrolysis by enzy me. 2.2.2.2. In - situ enzyme production Previous studies showed that the addition of some microorganisms will excrete enzymes. Table 2 shows the effectiveness of several that were documented in the literature. 9 Table 1 . FOG hydrolysis studies using enzymes Name Temperature HRT Dose Results Reference Candida rugosa 37°C 24 hours 0.02% (w/w) Hydrolysis : 52 54 % of FOG (Cavaleiro et al. 2013) Candida rugosa 35°C 3 days 0.5 and 1.5 g of bead/L (0.4 g - lipase/ g - b ead) Hydrolysis : 45 54% of FOG (Jeganathan et al. 2006) Candida rugosa 35°C 5 hours 0.25 - 1.00% Hydrolysis : 88% of soybean oil (Ting et al. 2006) Candida rugosa 40°C 3 hours 1.5% (w/v) Hydrolysis : 97% on used frying oil (Rashid et al. 2014) Penicillium restrictum 35°C 14 hours 0.1% (w/v) Hydrolysis : 70% of FOG (initial FOG : 1000 mg/L) (Leal et al. 2006) Penicillium restrictum 35°C 22 hours 0.1, 0.5, 1.0 % (w/v) Hydrolysis : 35% of FOG (Valladão et al. 2007) Penicillium restrictum 35°C 12 hours 0.1, 0.2 , 0.5 % (w/v) FOG removal : 79 90% (Cammarota et al. 2001) Pancreatic lipase 250 (PL - 250) 25°C 4 hours 25 - 1500 mg/L Hydrolysis : 35% of neutral fat (Masse et al. 2001) 10 Table 2 . In - situ enzyme production for FOG hydrol ysis Name Temperature HRT Dose Results Reference Acinetobacter sp. 30 35 °C 24 hours 5% (v/v) FOG removal : 60 65% (Wakelin & Forster 1997) Bio - Amp (Commercia l product) Combination of Pseudomonas fluorescens, Pseudomonas putida, Bacillus subtilis, Bacillus licheniformis, Bacillus thuringiensis 22 ± 2°C 24 hours 32 g of Bio - Amp Pellets FOG removal : 40% (Tang et al. 2012) Unidentified consortium of Gram negative bacteria which was isolated from grease trap, Activated sludge 30 35°C 4 days 10% (v/v) FOG removal : 84 96% (Wakelin & Forster 1998) F69 (Commercial Product) Various microbes 30°C 21 - 28 days 0.6% (v/v) FOG removal : 37 62% (Brooksbank et al. 2007) Bacteria cultured from used cooking oil 30 35°C 7 days 10% (v/v) FOG removal : 88% (Mazlin 2012) Bacillus thermoleovorans IHI - 91 65°C 7 hours 5 10% (v/v) 93 % of triolein (olive oil) was degraded (Markossian et al. 2000) JAT (Commerical Product) 15 types of bacteria that isolated from various fatty wastewater samples 20 25°C 4 weeks 2% (v/v) FOG removal : 79 % (Tano - Debrah et al. 1999) Candida bombicola 30 35°C 72 hours 5% (v/v) FOG removal : over 90% (Daverey & Pakshirajan 2015) Pseudomonas aeruginosa LP 602 55 °C 24 hours 2% (v/v) Lipid removal : 70% (Dharmsthiti & Kuhasuntisuk 1998) 11 2.2.2.3. Enzyme activity Enzyme activity is quantity of active enzyme present under a defined condition . Enzyme activity is impacted by ty pe of enzyme and its concentration , temperature, HRT , pH and substrate concentration (Scopes 2002) . Evalution of optimal condition for enzyme activity is critical in order to increase the efficiency. There are several methods to observe enzyme activity such as titrimetric determination, colorimetric assay, spectrophotometric determination , fluorometry , and chromatography (S toytcheva et al. 2015) . The most common method is the titrimetric determination which quantifies a yield of fatty acids produced by hydrolysis of enzyme activity. 2.3. Commercial system Previous studies showed the feasibility of enzyme hydrolysis on FOG. In this section, full - scale systems using an enzyme for pretreatment before discharge into a sewer or drain field are discussed. Bio - amp system is developed by NCH Waste Water (West Midlands, United Kingdoms ), is used as a pretreatment bef ore a grease trap. E ach day, 32 grams of tablets are added into the growth vessel. The vessel is then filled with water and spun for 24 hours at room temperature to excrete the enzymes. Thereafter, the entire content of the vessel is discharged into the sewer system. The syst em has been used to pretreatment before a grease trap at restaurants (NCH Waste Water 2011) . The FOG concentr ation of grease trap effluent was 281 mg/L . W ith Bio - amp , the grease trap effluent decreased to 168 mg/L (40 % reduction). The chemical o xygen 12 d emand, total nitrogen, and total phosphorus were reduced by 39 %, 33 % and 56 %, respectively (Tang et al. 2012) . The Advanced Grease Interceptor System (AGIS) was developed by Sustainable Environmental Technologies (Mt. Morris, Michigan). The system is a reactor to generate enzymes and is installed in a 5,678 L ( 1,500 gal) underground modified septic tank (Figure 2) adjacent to the restaurant and uses a low energy aeration system, baffles and a one - time inoculum of a bacteria population that excretes enzymes to microbiologically breakdown FOG (Sustainable Environmental Technologies 2012) . The microbial culture, BIO - FLO, is commercially produced by Bio - Systems International, in Beloit, WI. B IO - FLO is a liquid and contains multiple bacterial cultures and is commonly used for liquid odor control, in a grease trap, drain and for septic tank maintenance (Bio - systems International n.d.) . The m icrobial population excretes extra cellular lipases that cleave long chain fatty acids . Figure 2 . AGIS installed in the septic tank (Sustainable Environmental Technologies 2012) Figure 3 shows the interior of a pipe before AGIS was installed and 17 months after installation. The u se of AGIS at restaurant helps to reduce the cost of pumping, hauling and disposing of FOG . 13 Figure 3 . Pipe interior before AGIS treatment and 17 months after implementation (Sustainable Environmental Technologies 2009) Aerobic Bacterial Generators (ABG) was developed by SludgeHa mmer ( Petoskey, Michigan). The system is installed in an aerobic treatment tanks and uses 0.07 - k W blowers with diffuser a 130.9 m 2 fixed film media and a bacterial pack. ABG stimulates the growth of bacteria and removes COD, FOG, TP and TKN by 70 %, 89 %, 28 % and 30 %, respectively (Heger et al. 2010) . Application of ABG was not only used for sewer but also for drain field (Sludgehammar 2015) . 2.4. Operation of drain field A typical drain field can fail due to either physical or biological cloggin g. Suspended solids, sludge and FOG plays a major role on physical clogging (Matejcek et al. 2000) whereas biomat plays a role in biological clogging. Physical clogging occurs when the solids and FOG adhere to the inlet pipe, distribution gravel and/or soil. Biological clogging occurs form excessive mi croorganism growth in the drain field due to large organic, biodegradable loading. 14 The l ife of a typical drain field is between 25 and 30 years (Mckenzie 2010) . A typical type of soil in a drain field is sandy loam and the total available water capacity is between 20 35 % (Peacock & Christensen 2000; Northeast Region Certified Crop Advisor 2010) . Once the soil reaches saturation, the porosity in the soil becomes fully filled with water ( Figure 4 ) . Figure 4 . Soil phases from dry to saturation Biomat formation in the soil, caused by anaerobic microorganisms, restricts the hydraulic flow and will eventually cause the soil to become saturated and the influent to over - flow the drain field (NESC 2 005) . A typical thickness of biomat ranges from 0.7 to 2.5 cm in the soil and gravel below the perforated inlet pipe (May 1996) . The biomat decreases filt ration rates, reducing the removal of pathogens. High strength organic, biodegradable wastewater loading (Heger 2013) . Typically, d rain fields are placed 61 122 cm (2 4 ft) under the surface. The most ab undant bacteria in the soi l down to a depth of 120 cm ( 47 inch), including within the drain 15 field (Pettersson & Erland 2003) , are Archaea, Acidobacteria, Actinobacteria, Alphaproteobacteria, Bacteroidetes, Verruc om icrobia, Alphaproteobacteria, E taproteobacteira,Gammaproteobactiera, Deltaproteobacteria and Gemmatimonadetes (Eilers et al. 2012) . Lauber st. al (2013) conducted a study for 7 months and found that the community of bacteria remained same in the temperature range of - 5 °C to 28 °C, although the qua ntity of bacteria may increase or decrease with higher and lower temperatures, respectively. 16 Chapter 3: Methods In this chapter, methods to achieve each objective are provided. Included is assessing the impact of an enzymatic fast food restaurant wastew ater pretreatment on the type of FOG, the design of a bench - scale drain field and the impact of enzymatic pretreatment on the drain field. 3.1. Enzyme impact on the characteristics of triglycerides Liquid Chromatography/Mass Spectrometry (LC/MS) combines phys ical separation and mass analysis and was conducted in order to observe changes in the characteristics of triglycerides impacted by enzymatic pretreatment. Observation of the changes in the quantity of double bond in a triglyceride determines the impact o f the enzyme. The greater number of double bonds, the more cohesive the FOG, resulting in greater negative impacts on the treatment system and less biodegradability. 3.1.1. Enzyme pretreatment system Fast - food restaurant wastewater containing a high level of FOG , treated with a commercially available bacteria pretreatment system was used for this study. Specifically, the AGIS , which is a reactor to generate enzymes that was installed at fast - food restaurant in Grand Blanc, Michigan was selected for this study, be cause the system ha s been demonstrated for over 12 years and was requested to be used by sponsor of the research. 17 3.1.2. Sample collection and storage Fast - food restaurant wastewaters with/without AGIS treatment were collected from the restaurant in Grand Bla nc, Michigan. Samples were stored in clean glass bottles. If the analysis was delayed more than 4 hours, the sample s were adjusted to a pH below 2 with 1:1 hydrochloric acid (HCl) (HACH 2015b) . The sample was stored at 0 4 °C and analyzed within 28 da ys of collection. 3.1.3. Sample preparation FOG was first extracted from the wastewater. To begin the extraction, a 1 L sample of wastewater at room temperature was required. The Xenosep Solid - Phase Extraction method was used, which is EPA approved (1664A). All aluminum dishes were washed three times with approximately 3 mL of H exane (>=95 %), A cetone (>=99.5 %) and M ethanol (>=99 %) , in sequence , and pre - heated in 103° C oven. Following multiple Xenosep Solid - Phase Extraction system procedures, the FOG became so lid and was separated from the liquid fraction. Figure 5 - 7 show Xenosep Solid - Phase Extraction system setups and residues. 18 Figure 5 . Xenosep Solid - Phase Extraction system setup Figu re 6 . FOG extraction of kitchen wastewater treated with AGIS 19 Figure 7 . Solid FOG extracted from samples 3.1.4. Analysis The extracted FOG was dissolved with isobutyl alcohol (>=99.9%) and diluted for the analys is using LC/MS. LC/MS was conducted at the M ichigan S tate U niversity Mass Spectrometry Facility using the Xevo G2 - S QTof machine ( Figure 8 ) with an Acquity UPLC - 2.1 x 50 mm column. MassLynx V4.1 s oftware was used to set up a method and to analyze the samples. The method was developed with Dr. Daniel Jones from the Department of Chemistry at Michigan State University. Xevo G 2 - S QTof has autosampler that automatically injected the samples. Figure 8 . Xevo G2 - S TOF, Mass Spectrometry Facility, Michigan State University 20 3.1.5. Data i nterpretation Results from the LC/MS were processed using a MarkerLynx XS . S tatistical analysis was conducted using an o ne - way ANOVA in SAS 9.4 with significance level of 0.05 . The ANOVA test assumptions were that the samples are independent, normally distributed and the variances are homogenous. The assumption s w ere tested by nor mal probability plot and side - by - side box plot. The analysis allowed comparing interaction between treatment s using the difference of least squares means. 3.2. Bench - scale drain field design and performance In order to observe the impact of enzyme pretreated fast - food restaurant wastewater on a drain field, bench - scale drain fields (trenches), including soil moisture sensors embedded within the soil, were designed. 3.2.1. Trench design All dimensions of the trenches were based on the Michigan criteria for subsurfa ce sewage disposal (Michigan Department of Public Health 1994) . Figure 9 shows the schematic of the tr ench. The feedstock flowed by gravity into the trench. At the bottom of the trench, the treated water exit ed through a water trap that did not allow air flow into the trench. A typical drain field has multiple inlet pipes, and the maximum width of each is 91 cm ( 36 inch ). Figure 10 shows the dimension of the trenches used for this research. 21 Figure 9 . Schematic of trench Figure 10 . Dimensions of trench The desi gn of typical drain field is based on hydraulic loading. Equation 1 shows the total surface area required using the typical application rate for sandy loam of 10.2 L/day/ m 2 ( 0.25 gal/day/ ft 2 ) . The hydraulic loading of the bench - scale trench used for this r esearch with a 0.74 m 2 22 ( 8 ft 2 ) surface area was 7.57 L/day ( 2 gal/day ) . The e mpty bed contact time (EBCT) of each trench was 60 days . This indicates that a complete exchange of water would take approximately 40 minutes due to the soil porosity. Consequentl y, the trenches were operated many times this EBCT indicating that equilibrium conditions existed. ( Equation 1 ) The walls of each trench were made of plexiglass and cor ners were primed and glued. Each trench was supported with wooden frames constructed from 38 x 89 mm (1.5 x 3.5 inch) and 19 x 140 mm (0.75 x 5.5 inch) lumber. All seams were caulked and the i nside of the trenches was lined with heavy - duty plastic sheeting by Blue Hawk Inc. (Mooresville, North Carolina) . Figure 11 shows the cross sectional area . The bottom was sloped to allow treated water to exit through the outlet. At the outlet, a 5. 08 cm (2 inch) diameter bulkh ead were mounted and connected to a water tra p. Figure 11 . Front view of trench 23 Figure 12 barriers with a height , width, and length of 5.1 cm, 10.1 cm and 61 cm (2 x 4 x 24 inch), respectively were mounted on the bottom of the trench in order to capture the exiting water along the distance from the inlet. The depth of the sandy loam that served as the treatment medi a was 60.9 cm (2 ft). On the top of sandy loam, 15.2 cm ( 6 in ch) depth of gravel was placed then installed inlet pipe with covering 7.6 cm ( 3 inch ) depth of gravel. The top of the trench was covered with 22.9 cm (9 inch) depth of top soil, before wastewate r entered, simulating a typical drain field. Sandy loams, top soils, gravels and 6A stones were ordered from Carl Schlegel, Inc. in Lansing, Michigan. Figure 12 . Profile view of trench 24 Six CS616 soil moisture sensors manufactur ed by Campbell Scientific were placed at two depths at 3 locations along the length of the trench . All soil moisture sensor wires exited through a 2.5 cm ( 1 inch ) PVC pipe were inserted at the top of the trench and were connected to a CR1000 data logger, m anufactured by Campbell Scientific . Three temperature sensors were placed in each between two different depths of sensors. The data was download ed to a dedicated computer. Figure 13 shows the top view of the soil t rench including the CS616 soil moisture sensors, barriers and water traps. Figure 13 . Top view of trench Figure 14 show the pictures of constructing a bench - scale drain field (trenches) . Additional pictures of constructed bench - scale trenches are presented in Appendix A. 25 Figure 14 . Overview of trench construction 3.2.2. Instrumentation In order to monitor in situ clogging, a CR 1000, AM 16/32 and CS 616 Water Conte nt Reflectometer s , manufactured by Campbell Scientific, were used. The CS 616 water content reflectometer ( Figure 15 ) me asures the volumetric water content from 0 % to saturation in a soil using two 30 cm stainles s steel rods . The variability between probes is ± 0.5 % volumetric moisture content in dry soil and ± 1.5 % volumetric moisture content in typical saturated soil (Campbell Scientific 2014 ) . Figure 15 . CS 616 Water Content Reflectometer 26 Because m ore than 8 of CS 616 sensors were required , a AM 16/32 multiplexer was needed in order to connect CS 616 sensors to datalogger. Figure 16 shows installation of 30 of CS 616 sensors connected to AM 16/32 multiplexer and CR 1000 datalogger. Figure 16 . Installation of 30 of CS 616 Water content reflectometer connected with AM 16/32 multiplexer and CR 1000 d atalogger The Temperatures of trenches were monitored using type K thermocouples with PVC - insulated probes and epoxy coated tip by Digi - Sense ( Figure 17 ). The type K thermocouples measure from - 250 °F to 221 °F wi th accuracy of ± 3. 0 °F (Cole - Parmer 2015) . Figure 17 . Type K thermocouple with PVC - insulated probe and epoxy - coated tip 27 3.2.3. Analytical The analysis of trench influent and effluent wastewater parameters (Table 3) shows the validity of simulation and the impact of different characteristics of wastewaters on the drain field. All analyses were conducted wi th HACH analytical method and following proper Quality Assurance Quality Control (QA / QC) protocols, which is presented in Appendix C . Table 3 . Wastewater analytical parameters Parameter HACH Method U.S. EPA Method Reference Chem ical oxygen demand (COD) 8000 40 CFR 136.3. (HACH 2015a) Biological oxygen demand ( BOD 5 ) 8043 SM 5210 B Fats, Oil and Grease (FOG) 10300 EPA 1664A Total phosphate (TP) 8 190 EPA 365.1, 365.3 Total nitrogen (TN) 10208 N/A Ammonia 10205 EPA 350.1, 351.1, 351.2 Nitrate 10206 40 FR 141 3.2.4. Data interpretation Nutrient removal caused by the bench - scale trench was compared to the performance of a typical drain field using one - way ANOVA in SAS 9.4 with significance level of 0.05 . Assumptions of the statistical analysis are samples are independent, normally distributed and variances are homogeneous. The assumption was tested by normal probability plot and side - by - side box plot. This demonstrated that the trenches represented a field - scale installation. Direct comparisons of each parameter between two trenches were also compared to determine if enzyme pretreatment was impact ing results . The comparison was conducted between Sanitar y 28 trench and rest trenches, Sanitary/kitchen and Sanitary/treated kitchen and Kitchen and Treated kitchen. 3.3. Impact of wastewaters with/without enzyme pretreatment on clogging F eedstocks were prepared to simulate different condition s , as listed below . Each trench received only one of the following feedstocks. Sanitary wastewater (Sanitary) Served as a control that does not cause premature aging of the drain field. Sanitary wastewater mixed with kitchen wastewater without AGIS pretreatment (Sanitary /kitchen) Simulates condition for a typical restaurant. Assumed to clog a drain field causing premature of aging. Sanitary wastewater mixed with kitchen wastewater treated with AGIS pretreatment (Sanitary/treated kitchen) Test condition. Kitchen wastewa ter without AGIS pretreatment (Kitchen) Extreme condition that is expected to rapidly, physically clog the drain field. Kitchen wastewater treated with AGIS pretreatment (Treated kitchen) Extreme condition that is expected to rapidly, biologically clog th e drain field. 29 The sanitary wastewater collection was from a small cluster wastewater treatment system serving 25 homes in Dimondale, Michigan. Kitchen wastewater treated with AGIS pretreatment was collected fr o m a restaurant in Grand Blanc, Michigan with an AGIS that has been operating for over 12 years and discharging to a municipal sewer. To collect kitchen wastewater without AGIS pretreatment, the wastewater had to be mixed from the same restaurant as where the AGIS pretreated kitchen wastewater was col lected. This was necessary because there was no direct sample location plus a representative sample over a 24 hour period would have been difficult to obtain. Figure 18 shows the flow diagram from kitchen to AGIS a t the sampling site. Figure 18 . Flow diagram of brown grease at a fast - food restaurant 30 Table 4 shows the composition of the Kitchen wastewater. Table 4 . Feedstock constituents for K itchen wastewater Samples Discharge Frequency Total discharge Washing dishes 37.9 L /discharge ( 10 gal/discharge) 10 (discharge/day) 378.5 L /discharge ( 10 0 gal/discharge) Rinsing 37.9 L /discharge ( 10 gal/discharge) 10 (discharge /day) 378.5 L /discharge ( 10 0 gal/discharge) Sanitizing 37.9 L /discharge ( 10 gal/discharge) 10 (discharge/day) 378.5 L /discharge ( 10 0 gal/discharge) Mopping floor 22.7 L /discharge ( 10 gal/discharge) 3 (discharge/day) 68.1 L /discharge ( 1 8 gal/discharge) G rill grease 37.9 L /discharge ( 10 gal/discharge) 1 (discharge/day) 37.9 L /discharge ( 10 gal/discharge) Washing rags 151.4 L /discharge (40 gal/discharge) 1 (discharge/day) 151.4 L /discharge (40 gal/discharge) Total 1,393.0 L /discharge (368 gal/discharg e) The discharge was calculated by measuring the volume of the sinks or tub of units at the restaurant. The frequency of discharge per day was based on a conversation with the manager at 31 the restaurant. By multiplying these two values, the total amount o f discharge was calculated. Table 5 shows the total wastewater from kitchen and sanitary discharges per day at the restaurant. Table 5 . Total kitchen and sanitary wastewater discharges per d ay Sample s Total discharge per day Comment K itchen wastewater 1393 L /day (368 gal/day) Refer to Table 4 Sanitary wastewater 5564 L /day (1470 ga l /day) 35 gpd/seat* 42 seats = 1470 gpd (Metcalf & Eddy 2003) Table 6 shows the mixture for feedstock in 18.9L ( 5 gal ) carboy. Table 6 . Mixture for feedstock in 18.9L ( 5 gal ) carboy Samples Sanitary Kitchen Sanitary 18.9 L (5 gal) 0 L (0 gal) Sanitary/kitchen 3.78 L (1 gal) 15.1 L (4 gal) Sanitary/tr e ated kitchen 3.78 L (1 gal) 15.1 L (4 gal) Kitchen 0 L (0 ga l ) 18.9 L (5 gal) Treated kitchen 0 L (0 g al) 18.9 L (5 gal) 3.3.1 . S ample c ollection and storage To save time and cost, enough restaurant samples were collected to operate trenches for two weeks. Treated kitchen wastewater was collected from the AGIS tank using a sump pump. Kitchen wastewater was required the collect ion of samples from each source in the kitchen as shown in Figure 18 . Sanitary wastewater was collected from the centralized septic tank where 32 the wastewaters from all of the homes were combined before being pumped to th e advanced treatment unit. Because this wastewater was biologically active, it was stored at 0 4 °C. Before each trip to the restaurant and sanitary system, all carboys were rinsed with water. 3.3.2 . Operation Influent was fed three times every day at approximately 9:30 AM, 1:30 PM, and 8:30 PM to simulate the cleaning schedule at a typical fast - food restaurant. Figure 19 shows the details of the influent line. Note that the holes were opened downward as is in a typical drain field . F eedstock s were pumped into the inlet pipe using a Masterflex pump. Temperature was measured three times a day. Figure 19 . Detail view of influent pipe The length of the operation was 505 days for all t renches except Kitchen (362 days). The trench receiving Kitchen operation was less, because of a change in experimental plan, due to taking one modified AGIS system offline. The research operated with 4 different phases, as described in Table 7 . 33 Table 7 . Operations by phases Phase Operation Log Phase 1 11/03/13 - 11/19/13 (17 days) Mixture ratio for Sanitary/kitchen and Sanitary/treated kitchen : - Sanitary: 1.5 L /day (0.4 gal/day) - K itchen: 6.1 L /day (1.6 gal/day) Influent and effluent parameters tested weekly: COD, FOG, TP and Nitrate Phase 2 11/20/13 02/17/14 (90 days) Mixture ratio for Sanitary/kitchen and Sanitary/treated kitchen ( based on Matcalf and eddy ): - Sanitary: 6. 1 L /day (1.6 gal/day) - Kitchen: 1.5 L /day (0.4 gal/day ) Operation stopped due to heavy ice storm, holidays and maintenanc e. - 12/20/14 - 12/27/14 - 01/26/14 - 01/29/14 - 03/29/14 - 03/30/14 Influent and effluent parameters tested weekly: COD, FOG, TP and Nitrate Influent and effluent parameters were tested once: TN Phase 3 02/18/14 06/22/14 (125 day) Mixture ratio for Sanitary/kitchen and Sanitary/treated kitchen ( based on COD result in phase 2): - Sanitize : 227.1 L /day (60 gal/day) - Washing Machine : 302.8 L /day (80 gal/day) The trench receiving Kitchen wastewater began on 03/25/14. Influent and effluent parameters tested weekly: COD, FOG, TP, TN, Ammonia and Nitrate Influent and effluent parameters were tested once: BOD 5 Phase 4 06/23/14 03/22/15 (273 days) Mixture ratio for Sanitary/kitchen and Sanitary/treated kitchen ( based on COD result in phase 3): - Mop Water: 147.6 L /day ( 39 gal/day) - Washing Machine : 283.9 L /day ( 75 gal/day) Influent and effluent parameters tested bi - w eekly: COD, BOD 5 , TP, TN, Ammonia and Nitrate Influent and effluent parameters were tested discontinued on 07/14/14: FOG 34 3.3.3. Analysis To provide an indication if clogging was occurring, readings from the soil, moisture sensors were monitored. Observation of moisture content in each trench was conducted with CR 1000 datalogger, AM16/32 and CS 616 sensors. Measurements were recorded automatically by CR 1000 datalogger. Downloading data from CR 1000 datalogger w as required monthly because the datalogger has a li mit of memory. Soil analysis was conducted on two different days of operation. First soil samplings were collected on the 207 th day of operation by using a 1.9 cm (3/4 inch) diameter soil sampler ( Figure 18). This small diameter soil sampler was used to m inimize disruption to the system because the operation was still on - going. Figure 20 . Diagram of soil sampling locations for 1 st VS analysis, brown boxes indicate soil sample collection locations. 35 Collected soil samples were tran sported in plastic sealed bottles with proper label. Volatile Solids (VS) analysis was conducted following EPA 1684 method. Samples were stored at 4 °C to minimize microbiological decomposition of solids and were not to be held for more than 24 hours. Befo re the analysis, soil was set at room temperature. VS analysis is an economical method to compare the microorganism population s between different soil treatments . Figure 21 . Diagram of soil sampling locations for 2 nd VS analysis , b rown boxes indicate soil sample collection locations. The second soil sampling was conducted on the day after the last day of operation. Soil sampling locations were as shown in Figure 19. Soil sampling was completed by scooping soils out of trench and stored in sealed zip - lock bags with proper label and the VS was measured. 36 3.3.4. Data interpretation T he CR1000 datalogger automatically downloaded readings from the moisture sensors as a comma separated variable file. T his data was transferred to a spreadsheet bi - weekly, due to the memory limits in the datalogger and to prevent loss of data in case of a malfunction. The file was opened in Microsoft Excel and plotted using a scatter graph in order to com par e different locations of sensors for each trench. A stati stical analysis of this data was not possible because there were not replicate trenches for each condition because of budget constraints. A statistical analysis of the VS level in the soil result was conducted using an one - way ANOVA in SAS 9.4 with signifi cance level of 0.05 . Assumptions of the statistical analysis are samples are independent, normally distributed and variances are homogeneous. The assumption was tested by normal probability plot and side - by - side box plot. Difference of least squares means allowed comparing the interactions. The comparison was conducted between the Sanitary trench and rest trenches, Sanitary/kitchen and Sanitary/treated kitchen and Kitchen and Treated kitchen. 37 Chapter 4: Result and Discussion Result and discussion for eac h objective are presented in this chapter. Included are sections on the enzyme impact on the characteristics of triglycerides, bench - scale drain field design and the impact of wastewaters with and without enzyme pretreatment on potential clogging. 4.1. Enzy me impact the characteristics of triglycerides The LC/MS analysis was compared between Kitchen wastewater and Treated kitchen wastewater in order to observe the impact on the triglyceride. Three replications were conducted for each sample. Figure 22 and Figure 23 show the relative proportions of double bonds in triglycerides of Kitchen wastewater and Treated kitchen wastewater. Figure 22 . Relative p roportion of double bonds in triglycerides of Kitchen wastewater . The values are the total number of double bonds that were found in the triglycerides . 15% 11% 14% 9% 21% 3% 15% 12% 0 1 2 3 4 6 7 8 # of double bond 38 Figure 23 . Relative proportion of double bonds in triglycerides of Treated kitchen wastewater , The value are the total number of double bonds that were found in the triglycerides . Results show that the relative proportion of single bond and one double bond in triglycerides of Treated kitchen wastewater were significa ntly increased from 15 to 38 % and from 11 to 40 %, respectively ( ANOVA, P - ). Result displayed that greater than four double bonds in triglycerides of Kitchen wastewater were significantly reduced from 60 % to 8 % by the enzyme treatment ( ANOVA, P - ). Therefore, result show that enz yme treatment impacted on characteristics of triglyceride in fast - food restaurant wastewater. 38% 40% 14% 5% 1% 1% 1% 0 1 2 3 4 6 7 8 # of double bond 39 4.2. Bench - scale drain field design and performance Bench - scale trenches were operated for 505 days and influent and effluent concentrations of COD, BOD 5 , FOG, TP, TN, ammonia and nitrate were monitored. Removal of these constituents in the trench receiving Sanitary wastewater was compared to a typical field drain field (Hossain 2010) . Additionally, removals of these constituents for the other feedstocks are also presented in this Chapter to gauge the effectiveness of the trenches for the variety of wastewaters. Results are discussed in sequential phases as each had different conditions, as described in Chapter 3. 4.2.1. Phase 1 In P hase 1, influent concentrations of COD, TP, FOG and nitrate for each trench were analyzed ( Table 8). Effluent concentration of the parameters were not tested as this phase was designed simply to determine if the sanitary wastewater matched the characteristics reported in the literature and to compare the non - treated and treated kitchen wastewater. Also during this Phase, there was not a trench being oper ating with Kitchen waste only (kitchen waste not treated with AGIS). This resulted because resources only allowed for the construction of 5 trenches and one was being used for a variation of the AGIS process, as requested by the sponsor that prov ed to be i neffective (data not presented). Consequently, a comparison with the Treated k itchen wastewater was not possible . 40 Table 8 . Parameter analysis of influent concentration of each trench in Phase 1 The i nfluent concentration s of COD from Sanitary/kitchen and Sanitary/treated kitchen were approximately 7 and 10 times higher than Sanitary, respectively. The i nfluent concentration of COD in the Treated kitchen trench was approximately 31 times higher than Sanitary. The influent conce ntration of TP and nitrates for all trenches were consistent. The COD, TP, FOG and n itrate influent concentrations of Sanitary wastewater were found to be similar to the drain field influent for a typical s anitary wastewater . These concentrations are 120 150 mg/L, 15 mg/L, 10 30 mg/L, and < 1 mg/L for COD, FOG, TP and n itrate, respectively (Metcalf & Eddy 2003; Hammerlund & Glotfelty 2008; Cui et al. 2003) . 4.2.2. Phase 2 Based on Phase 1 results, the formulations of the feedstocks with kitchen wastewater were changed to better match field conditions. These changes included altering the mixture ratio for Sanitary/kitchen and Sanitary/treated kitchen to 6.1 L /day (1.6 gal/day) of s anitary 41 wastewater and 1.5 L /day (0.4 gal/day) of kitchen wastewater, based on Metcalf and Eddy (Metcalf & Eddy 2003) . Figures 24 28 show the influent and effluent values of COD, FOG, TP, TN and n itrate for each trench during this Phase. As in Phase 1, t here was not a trench being operating with Kitchen waste only. The error bars represent the standard deviation. Figure 24 shows the average of influent and effluent concentration of COD for each trench in Phase 2. Figure 24 . Average influent and efflu ent concentrations of COD in Phase 2 Even though there was a wide range of influent COD concentration , from 100 to 3,000 mg/L, all bench - scale trenches removed significant amounts of COD . More than 80 % of the mass was removed by the trenches, even though the effluent levels for the each feedstock 42 containing kitchen wastewater were found to be statistically different. The COD Influent concentration of the trench receiving Sanitary wastewater wa s 118 mg/L, which is close to typical drain field COD influent concentration of 120 150 mg/L (Cui et al. 2003) . H owever , data on the t ypical COD in the effluent was not found in the literature . Figure 25 shows the average of influent and effluent concentration of FOG for each trench in Phase 2. Figure 25 . Average influent and effluent concentrations of FOG in Phase 2 Similar to COD result, even though there was a wide range of influent FOG concentration s, from 10 to 471 mg/L, bench - scale trenches reduced FOG concentration significantly. The FOG influent concentration of the t rench receiving Sanitary wastewater is 10.9 43 mg /L, which is close to typical drain field FOG influent concentration of 15 mg/L (Hammerlund & Glotfelty 2008) . Removal rate of the trench receiving Sanitary/treated kitchen wastewater statistical ly higher than the trench receiving Sanitary/kitchen (ANOVA, P - value=0. 0007 0.05). This is hypothesized based on Sanitary/treated kitchen wastewater becoming more biodegradable after enzyme treatment, resulting in better FOG removal by a drain field. Figure 26 shows average of influen t and effluent concentrations of TP for each trench in Phase 2. Figure 26 . Average influent and effluent concentrations of TP in Phase 2 Unlike COD and FOG results, all TP influent concentrations were statistically consistent ( ANOVA, P - ) and all bench - scale trenches reduced TP concentration significantly. However, the Treated kitchen trench did not remove the phosphorus down to the 44 same levels as the others ( ANOVA, P - ) for unknown reasons. The TP influent and effluent concentration of the trench receiving Sanitary wastewater are 22.9 mg/L and 4.6 mg /L, which is close to typical drain field TP influent and effluent concentration of 10 30 mg/L and 4.9 mg/L, respectively (Hossain 2010; Metcalf & Eddy 2003) . Figure 27 shows in fluent and effluent concentrations of TN for each trench in Phase 2. Figure 27 . Average influent and effluent concentrations of TN in Phase 2 Result shows all TN concentration of influent were consistent, except treated kitchen . All trenches except Treated kitchen did not removed TN significantly. Statistical analysis including average and standard deviation could not be calculated because TN analysis was conducted only once at the end of Phase 2. The TN influent and effluent co ncentration of the trench receiving 45 Sanitary wastewater were 43 mg/L and 42 mg /L, respectively, which is close to typical drain field TN influent and effluent concentration s of 25 - 60 mg/L and 48 mg/L, respectively (Hossain 2010; Metcalf & Eddy 2003) . Figure 28 shows average of influen t and effluent concentration of nitrate for each trench in Phase 2. Figure 28 . Average influent and effluent concentrations of n itrate in Phase 2 Result shows that all nitrate concentrations increased after treated with the benc h - scale trenches. Combined with the relatively consistent influent and effluent TN values for each trench, this indicates that denitrification did not occur. The Nitrate influent and effluent concentration s of the trench receiving Sanitary wastewater were 9.1 mg/L and 39.1 mg /L, 46 respectively, which is close to typical drain field influent and effluent concentration s of < 1 mg/L and 42 mg/L, respectively (Hossain 2010; Metcalf & Eddy 2003) . 4.2.3. Phase 3 In Phase 3, the composition of the non - AGIS treated kitchen wastewater was changed so that it better correspond to AGIS treated kitc hen wastewater . As a result, 227.1 L /day (60 gal/day) for Sanitary and 302.8 L /day (80 gal/day) for w ashing m achine wastewater , based on COD result in P hase 2. Also, the previously discussed fifth trench that was receiving feedstock form the modified AG IS system was switched to a feedstock consisting of only not - treated kitchen wastewater (Kitchen) . This was hypothesized to serve as the most extreme condition that would likely quickly physically clog the trench. The error bars represent the standard deviati on. Figures 29 35 show influent and effluent concentrations of COD, BOD 5 , FOG, TP, TN, a mmonia and n itrate for each trench in P hase 3. Figure 29 shows average of influent and effluent concentration of COD for ea ch trench in Phase 3. 47 Figure 29 . Average influent and effluent concentrations of COD in Phase 3 The influent COD for the Sanitary/kitchen and the Sanitary/treated kitchen were statistically the same with the new formulation (A NOVA, P - S imilar to P hase 2, all bench - scale trenches removed significant amount s of COD . The Sanitary trench continued to perform as expected. Figure 30 shows average of influent and effluen t concentration of BOD 5 for each trench in Phase 3. 48 Figure 30 . Average of influent and effluent concentration of BOD 5 in Phase 3 Even though there was a wide range of influent BOD 5 concentration s from 100 to 700 mg/L, all bench - scale trenches removed significant amount of as was also found for the COD. Statistical analysis , including average and standard deviation , could not be calculated because the BOD 5 analysis was conducted only once at the end of Phase 3. The BOD 5 influent a nd effluent concentration of the trench receiving Sanitary wastewater were 119 mg/L and 28 mg /L, respectively, which is fairly close to typical drain field BOD 5 influent and effluent concentration of 140 200 mg/L and 1.2 mg/L, respectively (Hossain 2010; Metcalf & Eddy 2003) . Figure 31 shows average of influent and effluent concentr ation of FOG for each trench in Phase 3 . 49 Figure 31 . Average influent and effluent concentrations of FOG in Phase 3 S imilar result s to that in P hase 2 were found in that all bench - scale trenches reduced FOG concentration significantly. The Sanitary trench continued to perform as expected. The removal rate of the trench receiving Sanitary/treated kitchen wastewater was statistically lower than the trench receiving Sanitary/kitchen w astewater ( ANOVA, P - value < 0. 0001 . Figure 32 shows average of influent and effluent concentrations of TP for each trench in Phase 3 . 50 Figure 32 . Average influent and effluent concentrations of TP in Phase 3 S imilar result to that found in Phase 2 was found in that all bench - scale trenches reduced TP concentration significantly. The Sanitary trench continued to perform as expected. Figure 33 shows average of influent a nd effluent concentrations of TN for each trench in Phase 3 . 51 Figure 33 . Average influent and effluent concentrations of TN in Phase 3 Similar results to that in Phase 2 were found in that TN in all trenches except Treated kitche n did not removed TN significantly. The Sanitary trench continued to perform as expected. Sanitary/kitchen ha d better removal of TN than Sanitary/treated kitchen ( ANOVA , P - ) . T he t rench receiving Treated kitchen ha d a higher removal rat e of TN than the trench with AGIS (ANOVA , P - ) . This indicates that the soil in these trenches was saturated and consequently, anaerobic conditions persisted , enhancing the denitrification process. There may have also been a high er leve l of carbon throughout the soil because of the very high organic loading. This is also essential for denitrification. Figure 34 shows average of influent and effluent concentrations of a mmonia for each trench in Ph ase 3 . 52 Figure 34 . Average influent and effluent concentrations of a mmonia in Phase 3 Result show that all bench - scale trenches removed most of the ammonia . Low concentrations of ammonia in effluent indicate that the nitrogen in influent was nitrified to nitrate, resulting in increased nitrate concentration in effluent. The a mmonia influent and effluent concentration of the trench receiving Sanitary wastewater are 27.3 mg/L and 0.1 mg /L, respectively, which is close to typical inf luent and effluent to an actual 20 - 60 mg/L and 0.03 mg/L, respectively (H ossain 2010; Metcalf & Eddy 2003) . Figure 35 shows average of influent and effluent concentrations of n itrate for each trench in Phase 3 . 53 Figure 35 . Average influent and effluent concent rations of n itrate in Phase 3 Similar results to that in Phase 2 were observed as the effluent nitrate concentrations in all trenches except Treated kitchen increased after treated with the bench - scale trenche s, as expected from ammonia result. The efflue nt level of nitrate for Sanitary/kitchen w as statistically lower ( ANOVA, P - ) t han Sanitary/treated kitchen wastewater . As mentioned in Phase 3, the soil in the trenches receiving Treated kitchen and Sanitary/kitchen wastewater were saturated and , consequently, anaerobic conditioned enhanc ed the denitr ification process. T he Sanitary trench continued to perform as expected. 4.2.4. Phase 4 In Phase 4 , the composition of the non - AGIS treated kitchen wastewater was changed in order to more closely correlate with AGIS treated kitchen wastewater . This resulted in using 54 147.6 L /day ( 39 gal/day) o f m op w ater and 283.9 L /day ( 75 gal/day) o f w ashing m achine wastewater , based on COD result s in P hase 3 . Figures 36 42 show influent and effluent concentrations of COD, BOD 5 , FOG, TP, TN, ammonia and nitrate for each tr ench in Phase 4. The error bars represent the standard deviation. Figure 36 shows the average influent and effluent concentrations of COD for each trench in Phase 4. Figure 36 . Average influent and effluent concentrations of COD in Phase 4 The influent COD for the Sanitary/kitchen and the Sanitary/treated kitchen were statistically the same with the new formulation (ANOVA, P - Similar result to that in Phase 2 were found as all bench - scale trenches removed significant a mount s of COD . The Sanitary trench continued to perform as expected. 55 Figure 37 shows the average influent and effluent concentrations of BOD 5 for each trench in Phase 4. Figure 37 . Aver age influent and effluent concentrations of BOD 5 in Phase 4 Similar result s to that in Phase 3 were found as all bench - scale trenches removed significant amount of BOD 5 . The Sanitary trench continued to perform as expected. Figure 38 shows the average influent and effluent concentrations of FOG for each trench in Phase 4. 56 Figure 38 . Average of influent and effluent concentrations of FOG in Phase 4 Similar result s to that in Phase 2 were found as all bench - scale trenches reduced FOG concentration significantly. The Sanitary trench continued to perform as expected. . The removal rate of the trench receiving Sanitary/treated kitchen was statistically lower (ANOVA, P - value < 0. 0001 than the trench receiving Sanitary/kitchen wastewater , as expected. Figure 39 shows average influent and effluent concentrations of TP for each trench in Phase 4. 57 Figure 39 . Average influent and effluent concentrations of TP in Phase 4 Similar result s to that in Phase 2 were found as all bench - scale trenches reduced TP concentration significantly as expected . The Sanitary trench continued to perform as expected. Figure 40 shows average influent and effluent concentrations of TN for each trench in Phase 4. 58 Figure 40 . Average of influent and effluent concentrations of TN in Phase 4 Similar resul t s to that in Phase 2 were found as all trenches except the Treated kitchen trench did not removed TN significantly. The Sanitary trench continued to perform as expected. Sanitary/kitchen ha d a statistical ( ANOVA , P - ) better removal rat e than Sanitary/treated kitchen . Figure 41 shows the average influent and effluent concentrations of ammonia for each trench in Phase 4. 59 Figure 41 . Average influent and effluent concent rations of a mmonia in Phase 4 Similar results to that in Phase 2 were found as all bench - scale trenches removed most of ammonia significantly. The Sanitary trench continued to perform as expected. Figure 42 shows the average influent and effluent concentrations of n itrate for each trench in Phase 4 . 60 Figure 42 . Average influent and effluent concentrations of n itrate in Phase 4 Similar result s to that in Phase 2 were found as the nitrate i n all trenches increased after treatment except in the Treated kitchen trench . The effluent level of nitrate for Sanitary/kitchen w as statically lower ( ANOVA, P - ) than Sanitary/treated kitchen wastewater, as previously discussed. Overall, result show that the performance of the bench - scale trench receiving Sanitary wastewater was similar to a n actual drain field receiving sanitary wast ewater. All trenches achieved significant removal s of COD, BOD 5 , FOG and TP. E nzyme pretreatment did not reduce the influent COD and FOG. However, t he FOG removal rate in the trench with Sanitary/kitchen and Kitchen w ere substantially lower than the trench es with Sanitary/treated kitchen and Treated kitchen wastewater . A fter enzym atic treatment , the FOG apparently became more biodegradable because of the lower molecular weight of the triglycerides. All bench - scale trenches nitrified most of the ammonia to nitrate The trench receiving Kitchen and Sanitary/kitchen wastewater 61 reduced TN concentration s , indicat ing that the soil in these trenches was saturated, and consequently, anaerobic, enhancing the denitrification process. 4.3. Impact of wastewater with/withou t enzyme pretreatment on clogging In order to study this objective, observation of soil moisture content, soil volatile solid s and visual conditions of the inlet pipes were conducted. 4.3.1. Moisture Content s in trenches All trenches had 6 moisture sensors embe dded in the soil at different locations ( Figure 43 ) . Figure 43 . Schematic diagram of moisture sensor locations on a trench. Each circle represents a moisture sensor (not to sc ale). Each of the six moisture content sensors was labeled by location as shown in Figure 41. 62 Figure 44 - 47 show the average daily moisture content for each sensor. The averaged was calculated from measurements m ade every 10 minutes. Figure 44 shows d aily moisture levels in the trench that received Sanitary wastewater. Figure 44 . Daily moisture levels in the trench receiving Sanitary wastewater Results show consistent moisture contents throughout the 505 days of operation. There is no to very low increasing slopes at all l ocations . T he highest moisture content was found at 1 st Top location and the lowest was at the 3 rd Bottom location. T his ind icates very little water flowed across the length of the trench. Figure 45 shows daily moisture levels in trenches that received Sanitary/kitchen ( t op) and Sanitary/treated kitchen ( b ottom). 63 Figure 45 . Daily moisture levels in trenches receiving Sanitary/kitchen wastewater (top) and Sanitary/treated kitchen wastewater (bottom) Results show that the moisture levels in the Sanitary/kitchen trench was not constant. Moisture levels at the 1 st bottom and 2 nd bottom locations almost reached the saturation (20 35%), indicating premature aging of the rain field by clogging of soil porosity. Moisture levels of the Sanitary/treated kitchen trench (bottom graph in Figure 45 ) were relatively constant during the 505 days of operation, except at the 1 st bottom location. Both graphs showed a higher moisture levels than the Sanitary wastewater trench , however , the trench receiving Sanitary wastewat er ( Figure 44 ) was substantially lower . 64 Figure 46 shows the d aily moisture levels for the trench that received Kitchen wastewater. Figure 46 . Dai ly moisture level of the trench receiving Kitchen wastewater Result show that moisture levels did not changed significantly during the 362 days of operation. Note that this condition was not operated for as long as the others as the trench originally rece ived a feedstock from a modification to the AGIS system consisting of an effluent filter that was proven to be detrimental. The relatively low, constant moisture levels seem unusual but results from the inspection of the soil and inlet lines demonstrated c logging that only allowed water to very slowly flow into the soil. This was also directly demonstrated after 178 days of operation when the feedstock started backing up in the inlet pipe , making it difficult to add the wastewater to the trench . Figure 47 shows the daily moisture levels of the trench that received Treated kitchen wastewater. 65 Figure 47 . Daily moisture levels in the trench receiving Treated kitchen wastewater The trench re ceiving Treated kitchen wastewater had the highest moisture level of all the conditions. This trench also had the highest biodegradable organic loading, and consequently was demonstrated to have the highest level of microorganisms (discussed in VS section ). The graph showed a higher moisture levels than the Sanitary wastewater trench . To gain a better perspective on the change in moisture content, monthly plots of the 10 minute moisture contents values were produced over a 24 hour period beginning on 254 th day of operation and 88 th day for the Kitchen trench. These plots could not be routinely produced due to memory limitations of the CR 1000 datalogger. Figure 48 - 50 show the moisture level for the 10 minutes segm ent. The peaks in the figures represent a hydraulic flow of feedstock. Figure 48 shows the moisture level of the trench that received Sanitary wastewater. 66 Figure 48 . Moisture content o f trench receiving Sanitary wastewater (10 minutes segment s ) Only the 1 st bottom location was impacted during 505 days of operation. The other locations show ed consistent moisture contents. Figure 49 shows the 10 minute moisture level of the trenches that received Sanitary/kitchen and Sanitary/treated kitchen trenches. 67 Figure 49 . Moisture levels of trenches receiving Sanitary/kitchen (top) and Sanitary/treated kitchen (bottom) (10 minut es segment s ) The soil moisture levels were greater for the Sanitary/kitchen trench , although both received close to the sa me COD and FOG concentrations. More impacted locations and higher peaks of moisture levels are hypothesized to cause the premature of aging of the drain field. Both graph s showed higher moisture levels than the Sanitary wastewater trench . Figure 50 shows the moisture levels of the trenches that received K itchen (top) and Treated kitchen (bottom) . 68 Figure 50 . Moisture levels of trenches receiving Kitchen (top) and Treated kitchen (bottom) (10 minutes segment s ) Result shows a clear difference between the trenches. Water started to surface in the Treated kitchen trenc h on day 242 of operation. This was at first surprising but data from the soil VS and visual examination of the inlet pipe and soil after the systems were shut down, discussed in the next subsections, and provides the explanation. The t rench receiving kitc hen wastewater showed a higher moisture levels than the Sanitary wastewater trench . 69 4.3.2. Volatile solids The VS concentration is an indicator of the microorganism population within the soil (Ellis 2004) . Figure 51 and 52 show the VS (mg/g) concentration collected on the 207 th day of operation for each trenc h at depths of 35.6 cm (14 inch) and 50.8 cm (20 inch) and each soil column within the trench . The diagram of the soil sampling location s is shown in Figure 20 . Figure 51 . VS at 35.6 cm ( 14 inch) depth for columns 1 and 2 Figure 52 . VS at 50.8 cm (20 inch) depth for columns 1 and 2 70 The values of column 1 ( Kitchen ) at 35.6 cm (14 inch) depth and column 2 ( Treated kitchen ) at 50.8 cm (20 inch) are not available be cause of laboratory errors. Only one sample was analyzed for this VS analysis without any replications because the operation was on - going and collecting more samples would have increased the risk of disrupting the system. The results show that Sanitary/tr eated kitchen of column 1 at 35.6 cm (14 inch) and 50.8 cm (20 inch) depths had slightly higher VS levels than the Sanitary/kitchen trench soil. I n the column 2 at 50.8 cm (20 inch) depth , high er VS level was found in the Sanitary/treated kitchen than Sani tary, Sanitary/kitchen and Kitchen . This indicates that enzyme pretreatment increased the biodegradable organic matter (microorganism population) in the soil because the wastewater that was treated with enzyme became more biodegradable . The second soil ana lysis was conducted on the day after operation . T hree replica tes for each column at 20.3 cm (8 inch) and 45.7 cm (18 inch) depth from the top of sandy loam were collected ( Figure 21 ). Figure 53 - 57 show the VS concentrations of each trench, in each column and at depths of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam layer. The error bars represent the standard deviation. 71 Figure 53 . VS of Sanitary trench at depth s of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of the sandy loam Figure 54 . VS of Sanitary/kitchen trench at a depth s of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sand y loam 72 Figure 55 . VS of Sanitary/treated kitchen trench a t depth s of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam Figure 56 . VS of K itchen trench at depth s of 20.3 cm (8 inch) and 4 5.7 cm (18 inch) from the top of sandy loam 73 Figure 57 . VS Treated kitchen trench at depth s of 20.3 cm (8 inch) and 45.7 cm (18 inch) from the top of sandy loam The VS in the trench that received Treated kitchen is statistically higher than the trench receiving Kitchen wastewater (ANOVA, P - the trench receiving Sanitary/treated kitchen wastewater is statistically higher than Sanitary and Sanitary/kitchen wastewater (ANOVA, P - levels for the trenches that received Sanitary wastewater and Sanitary/kitchen were not statistically different except C1 at a depth of 20.3 cm (8 inch). Results indicate that there is a greater microorganism population in enzyme pretreated wastewater. 74 4.3.3. Visual Observation Visual observation of gravel in the trenches, influent pipes and treatment soils are an indication were made when the system was dissassembled . A typical drain field failes due to physical pipe, gravel and/or soil blockage s or extens ive biomat growth (NESC 2005; Bio - Safe One 2011; Owens & E. Moye Rutledge 2011; Mckenzie 2010; Matejcek et al. 2000) and is often realized by water surfacing . Figure 58 shows the top view of the Sanitary trench. The soil is dry as water from the inlet pipe always progressed downward and across the trench. Figure 58 . Top view of Sanitary trench The trenches that receive d Sanitary/kitchen, Sanitary/treated kitchen and Kitchen feedstocks had similar appearances. Figure 59 shows the Treated kitchen trench . Water started surfacing on the 242 th days of operation, indicating that the underlying soil was becoming clogged. This wa s confirmed from the moisture sensor data. 75 Figure 59 . Top view of Treated kitchen trench The clogging was found to be caused by the extensive growth of biomat (Figure 59). The biomat restricts the flow and eventually clogged the trench. Figure 60 . Biomat was found in the Treated kitchen trench The COD concentration s of both Kitchen and Treated kitchen wastewater were approximately 30 times higher than sanit ary wastewater. However, AGIS treatment transformed the FOG so that it was biodegradable, causin g the extensive biomat growth. To manage this large 76 biodegradable , organic load the sizing of the drain field should be designed based on organic loading, not t he standardly used hydraulic loading. Figure 61 shows the clean condition of the inlet pipe from the Sanitary trench after 505 days of operation . Figure 61 . Inlet p ipe condition in the Sa nitary trench after 505 days of operation Since sanitary wastewater contain s relatively low concentration s of FOG, when compared to fast - food restaurant wastewater, it did not cause physical clogging. Figure 62 sh ows the condition of the inlet pipe in the Sanitary/kitchen trench after 505 days of o peration. 77 Figure 62 . Inlet p ipe condition in the Sanitary/kitchen trench after 505 days of operation Some FOG residues were adhered on both the inner and outer side s of the pipe after 505 days of operation. This solids accumulation has the potential to ultimately clog the pipe. Figure 63 shows the clean inlet pipe from the Sanitary/treated kitchen trenc h . Figure 63 . Inlet p ipe condition in the Sanitary/treated kitchen trench after 505 days of operation 78 There is no evidence of FOG accumulation on both the inner and outer sides of the pipe. Result shows that enzyme treatment de graded the cohesiveness of the triglycerides so that FOG in will not physically clog the pipe. Figure 64 shows the condition of the inlet pipe in the Kitchen trench . Figure 64 . Inlet p ip e condition in the Kitchen trench after 337 days of operation The pipe is plugged with FOG result ing in wastewater back - up within the pipe and in the soil. The feedstock was only able to slowly trickle down into the soil, hence the reason for the low soil moisture levels previously discussed ( Figure 46 and Figure 50 ) . Figure 65 shows the inlet pipe from the Treated kitchen wastewate r trench . 79 Figure 65 . Inlet p ipe from the Treated kitchen trench after 505 days of operation Approximate l y half of the effluent holes were clogged with a layer of biomat. 80 Chapter 5: Conclusion and recommendations Three object ives were formulated and studied. The r esults are first summarized. Thereafter, recommendations are provided. 5.1. Summary The o bjectives of th is research were to o bserv e changes in the characteristic of triglycerides resulting from enzyme treatment , the de velopment of a bench - scale drain field that simulated actual installations and its performance for various feedstocks and the evaluation of drain field clogging by feedstocks with/without enzyme pretreatment . A summary of the results follow s . LC/MS analys i s showed that enzyme treatment impacted the characteristics of the triglycerides composing the FOG . Specifically, the number of double bonds and the molecular weight of the individual components of the FOG were reduced. Bench - scale trenches with embedd ed soil moisture sensors for monitoring clogging proved to be a unique, effective method to research the impact of diverse feedstocks. Their performance with typical sanitary feedstocks closely correlated to that found in the literature. B ench - scale trench es designed based on hydraulic loading effective ly remov ed a significant amount of COD, BOD 5 and FOG , regardless of their initial concentrations. Daily graphs of readings from the moisture sensors were not sensitive enough to detect water flow in a drain f ield . Ten minute segment g raphs show ed substantial changes in moisture level , including a n increase at each feeding and then a slow decrease thereafter. 81 Moisture levels in the t rench es receiving s anitary wastewater (serving as a control) and the sanitary w astewater mixed with kitchen wastewater that was enzymatically pretreated did not have substantially elevated moisture levels. The t rench receiving the s anitary wastewater and untreated kitchen wastewater showed sign s of premature aging based o n the elevat ed moisture levels and increasing slopes . The t rench receiving only untreated k itchen wastewater had a consistent level of moisture due to the clogged inlet pipe. However, the t rench receiving only enzymatic t reated kitchen wastewater had the highest level of moisture due to the formation of a biomat . VS level s in the trench receiving S anitary wastewater were consistently low . The trench receiving S anitary/treated kitchen wastewater showed higher VS level s th an the trench receiving S anitary/kitchen wastewat er. The VS levels of trench receiving K itchen wastewater showed no significant difference in different trench location, whereas significant VS level s in different trench location were found in the trench rec eiving T reated kitchen wastewater. These r es ults indicate that there is a greater microorganism population in enzyme pretreated wastewater. Inlet pipe s from the trenches receiving S anitary wastewater and S anitary/treated kitchen wastewater w ere found to be relatively clean . The inlet pipe receiving the S anitary/kitchen showed signs of clogging because of FOG accumulation. The inlet pipe receiving K itchen wastewater was clogged . However, the i nlet pipe receiving T reated kitchen wastewater was also partially clogged but this was caused by the extensive biom at growth. Since the bench - scale drain field meet Michigan Department of Public Healt h criteria, scaling up will likely perform as the bench - scale drain field. Scaling up may result in a 82 different quantity of bacteria because of the lower temperature in an actual system , however , the the bacteria community would not be different . Further, FOG does not coagulate at higher temperatures but the ambient temperature in which the trench was operated is not high enough to significantly impact the FOG. However, t he bench - scale trench has walls with a width of 61 cm (24 inch), therefore, the spreading of influent water and oxygen may be different with field demonstration drain field which has no wall s . Overall, results from the laboratory trenches show pretreatment of restaurant wastewater using an in - situ enzyme producing bacteria (enzyme generator) will delay clogging and, consequently, premature drain field aging. Th is research verified that the mechanism was that enzyme treatment helps t he FOG to become more bio degradable which reduce s the risk of physical clogging. The resulting increase in the biodegradable organic load may increase the growth of the biomat but i f the drain field is clogged by a biomat, it can be rested and will recover after several months. H owever, if it is clogged by the accumulation of FOG, protions of the drain field must be replaced. Designing the drain field based on organic loading, instead of the standard hydraulic loading, is recommended when pretreating with enzymes. Alternatively, c onstructing two separated drain fields; one for operation and another one at rest , is also an option . The c ost for installing AGIS is approximately $10,000 and annual operation (aeration) is approximately $ 204 (300 W, 24 hours per day, always on) (Duke Energy 2015) . Th is cost is substantially less than replacing a commercial drain field which will cost tens or hundreds of thousand s dol lar. 83 5.2 . Recommendation Bench - scale trenches demonstrated the effectiven ess of enzymatic pretreatment. Further research is justified to examine additional variables. Th is study used sandy loam for the soil type, which resulted in the significant removal of COD, BOD 5 , TP and FOG. The Michigan C riteria for S ubsurface S ewage D isposal provide s multiple options for soil type, such as coarse sand, medium sand, sandy loam and loamy sand. Depending on the soil type, the hydraulic loading of a drain field can be d etermined. Repeating this research using these different soil types is suggested. Precipitation and snow can impact the performance of a drain field because the efficiency of drain field decreases when there is an increase in the hydraulic loading. Simula tion of precipitation is suggested. Bench - scale drain field performed identical ly to a typical drain field during the operation period (505 days) . A field demonstration for a longer period of operation is recommended. Field demonstration s are more realisti c as seasonal and precipita tion influences are included. Installation of moisture content sensors in the field demonstration is recommended. B iomat is formed by an excessive anaerobic microorganism , resulting from high o rganic loading s . A treatment system using enzymatic pretreatment and then an advanced treatment unit may prevent any premature aging due to the increase formation of a biomat which is caused by highe r biodegradable organic load. Demonstrating a combination of both systems is recommended. 84 F or future research, the following changes to the experimental design are recommended . Formulating kitchen wastewater from its components (rinsing sink, washing dish, mop water, sanitization, washing machine and grill grease) was challeng ing . In future studies, a septic tank for kitchen wastewater prior to enzyme treatment is suggested so that typical and consistent samples can be obtained. Constructing bench - scale trenches was a challenge, because there were no previous studies or instructions. Plexig lass sheets were used for the walls of the bench - scale trenches and rounded wood frames to support the weight of the soil. To avoid leakages, plastic sheeting was embedded in the trench . A major reason for custom building the trenches was that the required container size of 61 x 122 x 122 cm (24 x 48 x 48 inch) was not available. In future studies, a 330 gal i ntermediate b ulk c ontainer (IBC) with welded galvanized tubular steel frame is recommended because it is more economical, less time consuming to build and has a lower risk of leaking. The typical size of an IBC container is 122 x 102 x 135 cm (48 x 40 x 53 inch) which is not a correct for the trench. However, a partition wall inside the container can be constructed. As moisture content sensors showed t he potential clogging of a trench, however, installing oxygen sensors in addition to moisture content sensors is suggested in order to show the potential clogging by a biomat. Since biomat grow occurs in an anaerobic condition, oxygen sensor can display po tential biomat formation by determining whether the soil environment is aerobic or anaerobic. A verage of moisture content s were shown as daily values. T h is measurement was not sensitive enough to detect water flow. Representing values as average of 10 min ute 85 segments was sensitive enough to detect water flow, however 10 minute segments will overload the datalogger memory without frewuent data downloading. Investigating the optimal segment for measuring moisture content is suggested so that the datalogger memory is not overloaded but also to be sensitive enough for water flow detection. Cost and performance comparison s of commercial enzyme applications are suggested , including capital cost, operation cost, enzyme activity, FOG removal and nutrient removal . Evaluation of enzyme activity is suggested. In order to measure enzyme activity, there are titrimetric determination, colorimetric assay, spectrophotometric determination , fluorometry and chromatography (Stoytcheva et al. 2015) . Enzyme activity shows the effectiveness of the enzyme pretreatment and the influence on performance and/ or premature of aging the drain field. Microbial community analysis is suggested in ord er to understand the impact of different characteristics of wastewater with/without enzyme pretreatment on the microbial community in a drain field. Bacteria play a significant role in treatment, because each bacterium has a potential function for treatmen t. Table 9 shows the common phylum, genus and species of microorganisms in a typical drain field soil and species that have a potential function of oil degradation. These are the target genus groups and species tha t are suggested to be identified and compared during the analysis. 86 Table 9 . Microbial Community in a drain field (Atoyan et al. 2013) Phylum Genus and Species Potential function Phylum Genus and Species Potential function Acidobacteria Terriglobus roseus Extracellular polysaccharide production - Proteobacteria Methylocystis sp. CH 4 oxidation Actinobacteria Leucobacter komagatae Biosurfactant production Labrys sp. Unknown Mycobacterium arupense Pathogen Erythrobacter sp. Aerobic phototrophic bacteria Mycobacterium sp. Pathogen; PAH degrada tion Sphingobium sp. Degradation of phenolic compounds Rhodococcus coprophilus Phenol degradation Sphingopyxis sp. Degradation of polyvinyl alcohols Acinetobacter Oil degrader Arthrobacter Oil degrader - Proteobacteria Acidovorax defluvii Denitr ification Nocardia Oil degrader Acidovorax facilis Degradation of polyhydroxyalkanoates Bacteroidetes Flavobacterium succinicans Cellulose & polysaccharide degradation Thiobacillus sp. Fe, S & S 2 oxidation Flavobacterium Oil degrader Dechloromonas sp. Perchlorate reduction Firmicutes Bacillus sp. Pathogen; various Rhodocyclus tenuis Purple, non - S photosynthetic bacteria; Oil degrader Clostridium sp. Pathogen; various methanol & formate oxidation Nitrospirae Nitrospira sp. NO 2 - oxidatio n Zoogloea ramigera Extracellular polysaccharide production - Proteobacteria Caulobacter sp. Unknown - Proteobacteria Desulfovibrio desulfuricans SO 4 2 & NO 3 reduction Phenylobacterium sp. Degradation of chlorinated N - heterocyclics - Proteobacteria Legionella pneumophila Pathogen & linear alkylbenzenesulfonat es Methylosarcina sp. Methane oxidation Beijerinckia sp. Non - symbiotic N fixation; Pseudomonas stutzeri Pathogen; denitrification; degradation of CCl 4 degradation of aromatic compound Pseudomonas umsongensis Various Afipia sp. Pathogen Pseudomo nas sp. Various Bradyrhizobium elkanii Symbiotic N fixation Luteibacter rhizovicinus Chitin degradation Nitrobacter vulgaris NO 2 - oxidation Lysobacter sp. Glucan & chitin degradation Methylocystis parvus CH 4 oxidation Thermomonas sp. Fe 2+ oxidati on; NO 3 reduction Proteobacteria Achromobacter Oil degrader Alcaligenes Oil degrader Pseudomonas spp. Oil degrader 8 7 Transforming FOG to become more biodegradable is not only beneficial to sewer clogging but also increasing biogas productio n in anaerobic digestion as shown in Table 10 . Further studies to investigate the cost benefit are warranted. Table 10 . Literature reviews of enzyme activity on biogas production Sludge E nzymes Results Reference Biological Sludge Mixture of lipase, glycosidic enzymes Improved solubilisation of organic matter (20 - 40 %) Reduced vitality Increased methane production(60 %) (Wawrzynczyk et al. 2003) Primary & waste activated sludge mixture(WWTP) Mixtures of enzymes Increased methane yield(60 %) (Davidsson & Jansen 2006) Mixed waste water sludge Two glycosidic enzymes Increase methane production (20%) Improved dewatering properties (Wawrzynczyk et al. 2008) Anaerobically digested sludge Protease, lipase, & other Improved dewatering properties (Ayol et al. 2008) Primary sewage sludge (WWTP) Mixture of enzymes Reduction of total solids (80 %) (Roman et al. 2006) Effluents form slaughterhouse Lipase ( Penicillium restrictum) High COD rem oval (85 %) Increased bio gas production (37 ml to 175 ml ) (Valladão et al. 2007) Nile perch processing waste water Lipase ( Penicill ium restrictum) Methane yield increment (76 %) (Gumisiriza et al. 2009) Synthetic waste water (COD 10.000 - 12,000 & BOD 5 7,000 - 9000 mg/L and oil & grease 200 - 1200 mg/L) Lipase ( Penicillium restrictum) High COD removal (91 %) Oil & grease removal (82 %) Similar Biogas production (before and after) Cost effectiveness (1 % w/v) for oil & grease 700 - 800 mg/L (Cammarota et al. 2001) Synthetic waste water (powder milk and fat) Lipase ( Penicillium restrictum) High COD removal (90%) Same methane percentage in bio gas (~65%) (Leal et al. 2006) Food waste (vegetable: grain: meat =49:31:17(W/W)) Mixture of enzymes (Carbohydras :protease :Lipase) (Not e: Lipase from Candida rugose) At 1:2:1 of C:P:L, Achieved High COD removal ( >95 %), VSS reduction (61 %), and Methane content(67 - 75 %) (Moon & Song 2011) P et food waste water Lipase (Candida rugosa) Achieved 90% of Overall COD and oil&grease removal Methane to COD yield of 80 % (Jeganathan et al. 2006) Meat - processing waste Lipase (Candida rugosa) Achi eved high COD removal (60 %) Fat hydrolysis (28 %) Methane production was same (Cavaleiro et al. 2013) 88 APPENDICES 89 APPENDIX A: Construction pictures Figure 66 . Effluent pipes Figure 67 . Trench construct ion 90 Figure 68 . Three effluent outlets Figure 69 . Moisture sensors locations Figure 70 . Inside of inlet distribution pipe 91 APPENDIX B: Analytical result Table 11 . Phase 2 performance result Sanitary Sanitary/kitchen Sanitary/treated kitchen Treated kitchen Influent Effluent Influent Effluent Influent Effluent Influent Effluent COD (mg/L) n 12 12 12 12 12 12 12 12 Av g . 118.3 28.1 554.4 137.4 772.8 105.9 2907.8 213.5 Std. 25.3 4.7 178.0 54.4 58.8 41.6 523.1 68.2 FOG (mg/L) n 12 6 12 6 12 6 12 6 Av g . 10.9 5.4 132.5 25.7 114.3 8.8 471.3 27.3 Std. 2.6 1.7 24.8 3.8 27.0 4.2 104.7 13.5 TP (mg/L) n 12 12 12 12 12 12 12 12 Av g . 22.9 4.6 20.7 5.4 20.8 3.5 19.6 7.4 Std. 1.9 2.2 2.9 3.3 3.3 1.0 4.9 2.5 TN (mg/L) n 1 1 1 1 1 1 1 1 Av g . 43.0 42.0 41.0 31.0 42.0 29.0 60.0 28.0 Std. N/A N/A N/A N/A N/A N/A N/A N/A Nitrate (mg/L) n 12 12 12 12 12 12 12 12 Av g . 9.1 39.1 4.0 35.2 2.5 31.7 1.8 22.1 Std. 5.5 4.1 1.6 2.9 1.3 8.7 0.6 6.4 92 Table 12 . Phase 3 performance result Sanitary Sanitary/kitchen Sanitary/treated kitchen Kitchen Treated kitchen Influent Effluen t Influent Effluen t Influent Efflue nt Influent Effluen t Influent Effluen t COD (mg/L) n 12 12 12 12 12 12 12 12 12 12 Av g . 101.8 30.3 576.4 52.9 683.3 46.8 2533.6 145.5 2740.0 179.8 Std. 11.8 6.3 156.8 21.3 165.0 11.2 432.0 26.4 291.7 72.7 BOD (mg/L) n 1 1 1 1 1 1 1 1 1 1 Av g . 119.0 28.0 318.8 143.9 321.4 164.9 707.8 128.4 698.8 150.4 Std. N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A FOG (mg/L) n 12 3 12 3 12 3 12 3 12 3 Av g . 14.6 6.5 150.3 25.0 147.4 11.1 560.5 42.7 587.8 29.2 Std. 8.0 2.7 44.3 3.7 25.5 7.4 231.5 13.5 152.8 10.9 T P (mg/L) n 12 12 12 12 12 12 12 12 12 12 Av g . 22.8 6.6 20.4 6.4 20.9 5.2 16.9 1.8 22.5 2.8 Std. 4.0 2.7 3.5 2.3 3.5 2.0 3.1 0.7 8.2 1.8 TN (mg/L) n 12 12 12 12 12 12 12 12 12 12 Av g . 36.1 37.1 40.4 24.0 40.1 30.8 51.3 33.4 57.3 20.3 Std. 3.4 4.0 6 .0 4.2 6.7 5.2 11.2 7.2 12.7 7.6 Ammonia (mg/L) n 12 12 12 12 12 12 12 12 12 12 Av g . 27.3 0.1 39.8 1.5 28.6 0.8 20.5 0.2 44.5 3.8 Std. 6.8 0.2 7.2 1.1 3.5 0.6 7.1 0.3 10.6 2.3 Nitrate (mg/L) n 12 12 12 12 12 12 12 12 12 12 Av g . 5.3 38.7 2.0 22.4 2. 1 30.7 1.1 30.8 1.7 3.5 Std. 4.0 3.2 2.6 3.1 4.1 5.5 0.4 8.0 0.7 4.9 93 Table 13 . Phase 4 performance result Sanitary Sanitary/kitchen Sanitary/treated kitchen Kitchen Treated kitchen Influent Effluent Influent Effluent Influent Effluent Influent Effluent Influent Effluent COD (mg/L) n 20 20 20 20 20 20 20 20 20 20 Avg. 119.8 29.3 703.9 59.9 740.6 47.5 2615.4 152.9 2903.8 133.4 Std. 22.4 7.0 110.7 19.0 132.3 19.5 268.2 40.9 256.3 35.6 BOD (mg/L) n 19 15 18 18 18 19 18 18 19 17 Avg. 102.6 31.4 327.9 72.4 406.6 63.3 1120.3 118.5 1267.9 84.3 Std. 24.8 9.9 50.1 24.9 95.6 16.7 325.4 43.0 359.1 25.1 FOG (mg/L) n 3 3 3 3 3 3 3 3 3 3 Avg. 12.8 2.6 180.3 32.0 184.3 6.5 588.7 48.7 605.0 27.3 Std. 3.0 3.3 19.2 4.6 29.3 3.5 19.6 9.5 31.6 6.5 TP (mg/L) n 20 20 20 20 20 20 20 20 20 20 Avg. 21.0 8.2 23.8 7.8 23.8 7.9 21.7 6.7 23.5 3.0 Std. 1.3 2.1 2.7 2.8 2.4 2.0 7.6 4.3 3.6 1.3 TN (mg/L) n 20 20 20 20 20 20 20 20 20 20 Avg. 37.9 37.3 46.1 28.8 42.7 38.8 45 .4 39.0 54.7 14.6 Std. 5.5 5.7 6.0 5.1 6.5 5.0 10.8 10.5 11.4 2.1 Ammonia (mg/L) n 20 20 20 20 20 20 20 20 20 20 Avg. 32.5 0.3 36.9 0.4 32.1 0.5 35.7 0.3 42.4 6.9 Std. 6.1 0.4 6.0 0.6 5.8 0.7 7.7 0.4 8.9 2.9 Nitrate (mg/L) n 20 20 20 20 20 20 20 20 20 20 Avg. 1.9 37.4 2.4 22.7 3.1 29.2 1.9 38.4 2.6 9.4 Std. 4.7 4.1 2.6 3.8 1.9 3.3 1.3 10.3 1.4 4.0 94 APPENDIX C: QAQC Table 14 . Relative percentage difference between standards Phase 1 Phase 2 Phase 3 Phase 4 Average CO D (%) 9.6 8.4 10.2 12.1 10.1 BOD (%) N/A N/A 15.4 11.4 13.4 FOG (%) 12.1 10.4 11.2 8.9 10.7 TP (%) 6.9 7.2 12.1 4.5 7.7 TN (%) N/A 4.2 5.2 4.9 4.8 Ammonia (%) N/A N/A 3.1 3.6 3.4 Nitrate (%) 5.6 3.4 4.2 2.4 3.9 Average 8.6 6.7 8.8 6.8 7.7 Table 15 . Relative percentage difference between replicates Phase 1 Phase 2 Phase 3 Phase 4 Average COD (%) 9.1 6.8 7.7 9.4 8.3 BOD (%) N/A N/A 13.2 10.1 11.7 FOG (%) 5.9 4.6 6.4 5.8 5.7 TP (%) 3.5 4.4 3.1 4.9 4.0 TN (%) N/A 4.5 5.8 6.2 5.5 Ammonia (%) N/A N/A 11.5 10.4 11.0 Nitrate (%) 4.2 4.9 5.8 6.1 5.3 Average 5.7 5.0 7.6 7.6 7.3 95 REFERENCES 96 REFERENCES Atoyan, J. et al., 2013. Microbial Community Structure of a Leachfie ld Soil: Response to Intermittent Aeration and Tetracycline Addition. Water , 5(2), pp.505 524. Available at: http://www.mdpi.com/2073 - 4441/5/2/505/ [Accessed December 2, 2014]. Ayol, A. et al., 2008. Aerobic and anaerobic bioprocessing of activated sludge: floc disintegration by enzymes. Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering , 43(13), pp.1528 1535. Aziz, T.N. et al., 2011. Performance of Grease Abatement Devices for Removal of Fat, Oil, an d Grease. Journal of Environmental Engineering , 137(1), pp.84 92. Bio - Safe One, 2011. The truth about drain field replacement. , p.1. Available at: http://www.biosafeone.com/bio112.html [Accessed August 12, 2013]. Bio - systems International, BIO - FLO. Bio - sy stems International M.S.D.S . Available at: http://www.biobugs.com/Products.html. Brooksbank, a. M., Latchford, J.W. & Mudge, S.M., 2007. Degradation and modification of fats, oils and grease by commercial microbial supplements. World Journal of Microbiolog y and Biotechnology , 23(7), pp.977 985. Cammarota, M.C. & Freire, D.M.G., 2006. A review on hydrolytic enzymes in the treatment of wastewater with high oil and grease content. Bioresource Technology , 97(17), pp.2195 2210. Cammarota, M.C., Teixeira, G. a. & Freire, D.M.G., 2001. Enzymatic pre - hydrolysis and anaerobic degradation of wastewaters with high fat contents. Biotechnology Letters , 23(19), pp.1591 1595. Campbell Scientific, 2014. CS616 - L Water Content Reflectometer. Available at: https://www.campbell sci.com/cs616 - l. Cavaleiro, a. J. et al., 2013. Biochemical methane potential of raw and pre - treated meat - processing wastes. Bioresource Technology , 129, pp.519 525. Available at: http://dx.doi.org/10.1016/j.biortech.2012.11.083. Chan, H., 2010. Removal an d recycling of pollutants from Hong Kong restaurant wastewaters. Bioresource Technology , 101(17), pp.6859 6867. Available at: http://dx.doi.org/10.1016/j.biortech.2010.03.104. Chu, W. & Ng, F. - L., 2000. Upgrading the conventional grease trap using a tube s ettler. Environment International , 26(1), pp.17 22. 97 Cole - Parmer, 2015. Digi - Sense Type - K PVC - Ins Probe. Available at: http://www.coleparmer.com/Product/Digi_Sense_Type_K_PVC_Ins_Probe_Epoxy_Coated _Tip_Mini_Con_Undgrd_10Ft_20_Gauge/EW - 08466 - 04#Specs. Cui, L . - H. et al., 2003. TREATMENT AND UTILIZATION OF SEPTIC TANK EFFLUENT USING VERTICAL FLOW CONSTRUCTED WETLANDS AND HYDROPONIC CULTIVATION OF VEGETABLES. Journal of environmental sciences (China) , 15(1), pp.75 82. Daverey, A. & Pakshirajan, K., 2015. Treatme nt of dairy wastewater containing high amount of fats and oils using a yeast - bioreactor system under batch, fed - batch and continuous operation. Desalination and Water Treatment , (June), pp.1 7. Available at: http://www.tandfonline.com/doi/abs/10.1080/19443 994.2014.1003609. Davidsson, A. & Jansen, 2006. Pre - treatment of wastewater sludge before anaerobic digestion Hygienisation, Ultrasonic treatment and Enzyme dosing. Vatten , 64(4), pp.335 340. Dharmsthiti, S. & Kuhasuntisuk, B., 1998. Lipase from Pseudomo nas aeruginosa LP602: biochemical properties and application for wastewater treatment. Journal of Industrial Microbiology and Biotechnology , 21(1 - 2), pp.75 80. Duke Energy, 2015. Electric Appliance Operating Cost List. Duke Energy , p.8. Available at: http: //www.duke - energy.com/pdfs/Appliance_OpCost_List_Duke_v8.06.pdf. Eilers, K.G. et al., 2012. Digging deeper to find unique microbial communities: The strong effect of depth on the structure of bacterial and archaeal communities in soil. Soil Biology and Bio chemistry , 50, pp.58 65. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0038071712001137 [Accessed October 25, 2014]. Ellis, T., 2004. Chemistry of wastewater. Eolss Publishers , p.1. Available at: http://www.eolss.net/eolsssamplechapters/c06/e6 - 13 - 04 - 05/e6 - 13 - 04 - 05 - txt - 03.aspx [Accessed January 1, 2015]. Gajeski, G., 2010. Enzymes help cut through fats, oils and greases in septic tank, drain line and sewer applications. Lenzyme , p.1. Available at: http://www.lenzyme.com/Grease_Education_Clearing _the_F.html [Accessed January 7, 2015]. Gregory, K., 2014. New York Tries to Rid Its Sewers of FOG (Fat, Oil and Grease). The New Yrok Times . Available at: http://www.nytimes.com/2014/02/15/nyregion/new - york - tries - to - clear - its - sewers - of - fog - fat - oil - and - gre ase.html?_r=0. 98 Gumisiriza, R. et al., 2009. Enhancement of anaerobic digestion of Nile perch fish processing wastewater. African Journal of Biotechnology , 8(2), pp.328 333. Available at: http://www.ajol.info/index.php/ajb/article/view/59806. HACH, 2015a. E PA Compliant Methods. HACH Company . Available at: http://www.hach.com/epa [Accessed January 1, 2015]. HACH, 2015b. Oil and Grease. , Edition 9(Method 10300). Hammerlund, D. & Glotfelty, B., 2008. Onsite Sewage Disposal Of High Strength Wastewater High Stre ngth Waste. Source Water Assessment Program , p.1. Heger, S., 2013. Loading rates How much can the soil take? , Heger, S.F., Schmidt, D.R. & Janni, K.A., 2010. AEROBIC AND MEDIA FILTER TREATMENT SYSTEMS FOR MILK HOUSE WASTEWATER ON SMALL DAIRY OPERATIONS. Am erican Society of Agricultural and Biological Engineers , 26(2), pp.319 328. Hossain, F., 2010. Comparison of Traditional Standard Drainfield with Innovative B&G Treatment Bed for Nutrient Removal from Septic Tank Wastewater . University of Central Florida. Available at: http://etd.fcla.edu/CF/CFE0003271/Hossain_Fahim_201008_Ph.D.pdf. Jeganathan, J., Bassi, A. & Nakhla, G., 2006. Pre - treatment of high oil and grease pet food industrial wastewaters using immobilized lipase hydrolyzation. Journal of Hazardous M aterials , 137(1), pp.121 128. Kunst, F. et al., 1997. The complete genome sequence of the gram - positive bacterium Bacillus subtilis. Nature , 390(6657), pp.249 256. Leal, M.C.M.R. et al., 2006. Effect of enzymatic hydrolysis on anaerobic treatment of dairy wastewater. Process Biochemistry , 41(5), pp.1173 1178. Leverenz, H., Tchobanoglous, G. & Darby, J., 2002. REVIEW OF TECHNOLOGIES FOR THE ONSITE TREATMENT OF WASTEWATER IN CALIFORNIA , California. Markossian, S. et al., 2000. Isolation and characterization of lipid - degrading Bacillus thermoleovorans IHI - 91 from an icelandic hot spring. conditions , 4(6), pp.365 371. Masse, L., Kennedy, K.J. & Chou, S., 2001. Testing of alkaline and enzymatic hydrolysis pretreatments for fat particles in slaughterhouse wastewater. Bioresource Technology , 77(2), pp.145 155. 99 Matejcek, B.C., Erlsten, S. & Bloomquist, D., 2000. Determination of Properties and the Long Term Acceptance Rate of Effluents from Food Service Establishments that Employ Onsite Sewage Treatment , Gainesville, Florida. May, R., 1996. Problems Associated with the Use of Gravel in Septic Tank Leachfield Systems. Journal of Environmental Health1 , 59(2). Mazlin, M.A., 20 12. BIODEGRADATION OF USED COOKING OIL BY INDIGENOUS BACTERIA . UNIVERSITI TEKNOLOGI MALAYSIA. Mckenzie, C., 2010. How to Maintain your Drainfield. AquaKlear Engineering . Available at: http://www.aquaklear.com/blog/sewage - treatment - systems/how - to - maintain - y our - drainfield/. Metcalf & Eddy, 2003. Wastewater Engineering Treatment, Disposal, and Reuse Third Edit., McGraw - Hill. Michigan Department of Public Health, 1994. Michigan Criteria for Subsurface Sewage Disposal. Moon, H.C. & Song, I.S., 2011. Enzymatic Hy drolysis of FoodWaste and Methane Production Using UASB Bioreactor. International Journal of Green Energy , 8(3), pp.361 371. Naylor, S. & Gustin, A., 2015. Geothermal Ground Source Heat Pumps and Geology in Indiana. Indiana Geological Survey . Available at: http://igs.indiana.edu/Geothermal/HeatPumps.cfm. NCH Waste Water, 2011. Overview of BioAmp system. NCH Europe , p.1. Available at: http://www.bioamp.co.uk/overview [Accessed January 1, 2015]. NESC, 2005. Drainfield Rehabilitation. , 16(1), pp.1 8. Northeas t Region Certified Crop Advisor, 2010. Competency Area 2: Soil hydrology AEM. Cornell University . Available at: http://nrcca.cals.cornell.edu/soil/CA2/CA0212.1 - 3.php [Accessed January 1, 2015]. Owens, P.R. & E. Moye Rutledge, 2011. Septic Drain Field Desig n and Maintenance. Phosphorus Best Management Practices . Peacock, W. & Christensen, L., 2000. Interpretation of soil and water analysis , Oakland, Calibronia: UCANR. Available at: http://books.google.com/books?hl=en&lr=&id=rMoAET18u9YC&oi=fnd&pg=PA115&dq =In terpretation+of+Soil+and+Water+Analysis&ots=0gLv7wMDO2&sig=ySYQik0IYLyD gQPt - 100 4P8NWdeVT0 \ nhttp://books.google.com/books?hl=en&lr=&id=rMoAET18u9YC&oi=fnd &pg=PA115&dq=Interpretation+. Pettersson, M. & Erland, B., 2003. Temperature - dependent changes in the soil bacteiral community in limed adn unlimed soil. FEMS Microbiology Ecology , 45(1). Rashid, R., Zaharudin, N.A. & Idris, A., 2014. Enzymatic hydrolysis of used - frying oil using Candida rugosa lipase. Jurnal Teknologi (Sciences and Engineering) , 67(3), pp.101 107. Ratcliffe, R., 2015. 10 - tonne fatberg removed from west London sewer. theguardian . Available at: http://www.theguardian.com/uk - news/2015/apr/21/huge - 10 - ton - fatberg - removed - chelsea - sewer - london. Roheim, J., 2003. Low cost automated on site system for growing and dispensing vegetative bacteria. Proceedings of the Water Environment Federation, Industrial Wastes , pp.634 647. Roman, H.J., Burgess, J.E. & Pletschke, B.I., 2006. Enzyme treatment to decrease solids and improve digestion of primary sewage slud ge. African Journal of Biotechnology , 5(May), pp.963 967. San Francisco Water Power Sewer, 2012. Commercial Fats, oil and grease(FOG) control. Available at: http://sfwater.org/index.aspx?page=480. Scopes, R.K., 2002. Enzyme Activity and Assays. Encyclopedi a of Life Sciences , pp.1 6. Available at: http://www.life.illinois.edu/biochem/455/Lab exercises/B - gal/enzymology.pdf. Sludgehammar, 2015. HOW IT WORKS. Sludgehammar , p.1. Available at: http://www.sludgehammer.net/. Stoytcheva, M. et al., 2015. Analytical Sustainable Environmental Technologies, 2012. AGIS Technology. Available at: http://set - agis.com/agis - technology/. Sustainable Environmental Technologies, 2009. Sagebrush Cantina Fenton Township , Tang, H.L., Xie, Y.F. & Chen, Y.C., 2012. Use of Bio - Amp, a commercial bio - additive for the treatment of grease trap wastewater containing fat, oil, and grease. Bioresource Technology , 1 24, pp.52 58. Available at: http://dx.doi.org/10.1016/j.biortech.2012.08.012. Tano - Debrah, K. et al., 1999. An inoculum for the aerobic treatment of wastewaters with high concentrations of fats and oils. Bioresource Technology , 69(2), pp.133 139. 101 Ting, W.J . et al., 2006. Application of binary immobilized Candida rugosa lipase for hydrolysis of soybean oil. Journal of Molecular Catalysis B: Enzymatic , 42(1 - 2), pp.32 38. Town of Tyngsborough, 2015. Fats, Oils And Grease (FOG) , Massachusetts. Available at: htt p://www.tyngsboroughma.gov/government/departments/sewer/what - not - to - flush - online - guide/. U.S. Environmental Protection Agency, 2014. Food Waste Scoping Analysis , U.S. Environmental Protection Agency, 2007. National Pretreatment Program. , 30 CFR 403. U.S. Environmental Protection Agency, 2004. Report to Congress on Impacts and Control of Combined Sewer Overflows and Sanitary Sewer Overflows. Available at: http://water.epa.gov/polwaste/npdes/cso/2004 - Report - to - Congress.cfm. Valladão, A.B.G., Freire, D.M.G. & Cammarota, M.C., 2007. Enzymatic pre - hydrolysis applied to the anaerobic treatment of effluents from poultry slaughterhouses. International Biodeterioration and Biodegradation , 60, pp.219 225. De Waard, P. et al., 1993. Heteronuclear NMR analysis of unsat urated fatty acids in poly(3 - hydroxyalkanoates). Study of beta - oxidation in Pseudomonas putida. The Journal of biological chemistry , 268(1), pp.315 319. Wakelin, N.G. & Forster, C.F., 1997. An investigation into microbial removal of fats, oils and greases. Bioresource Technology , 59(1), pp.37 43. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0960852496001344. Wakelin, N.G. & Forster, F., 1998. THE AEROBIC TREATMENT OF GREASE - CONTAINING FAST FOOD RESTAURANT WASTEWATERS. Trans IChemE , 76(February ). Washtenaw County, 2014. FOG - Fats, Oil and Grease. Available at: http://www.ewashtenaw.org/government/departments/environmental_health/food_safety/eh _fatsoilsgrease.html. Wawrzynczyk, J. et al., 2003. Alternative method for sludge reduction using commerc ial enzymes. In Aqua Enviro TechnologyTransfer: Eighth CLWEM/Aqua Enviro European Biosolids and Organic Residuals Conference . Wakefield West Yorkshire, UK, pp. 1 5. Wawrzynczyk, J. et al., 2008. The function of cation - binding agents in the enzymatic treatment of municipal sludge. Water Research , 42(6 - 7), pp.1555 1562. Wodalski, E., 2012. Up To the Challenge. Pumper , p.1. Available at: http://www.pumper.com/editorial/2 012/03/up_to_the_challenge.