EVALUATION OF ANAEROBIC BIODEGRADABILITY OF ZOOLOGICAL ORGANIC
WASTE TO ENHANCE SUSTAINABLE WASTE MANAGEMENT AT ZOOS
By
Gina Marie Masell Haylett

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Biosystems Engineering – Master of Science
2018

ABSTRACT
EVALUATION OF ANAEROBIC BIODEGRADABILITY OF ZOOLOGICAL ORGANIC
WASTE TO ENHANCE SUSTAINABLE WASTE MANAGEMENT AT ZOOS
By
Gina Marie Masell Haylett
Zoos across the country are pushing for sustainable solutions to mitigate their highenergy consumption and provide organic waste management. Anaerobic digestion provides an
alternative to traditional waste management solutions such as landfilling, incineration, and
composting. The Detroit Zoological Society (DZS) was selected as the zoo for this study. This
study analyzed seven waste samples and mixtures from the DZS. A biochemical methane
potential (BMP) test was performed on these wastes and their mixtures to determine the energy
content. The results show that all samples are anaerobically biodegradable with samples yielding
501, 622, 269, 117, 232, 653, and 302 L biogas per kg initial VS for carnivore, primate,
hoofstock mix, bird mix, zoo mix, food waste, and ZMF, respectively. The energy balance and
carbon footprint analyses on BMP data further conclude that anaerobic digestion can efficiently
handle zoo wastes, generate renewable energy to compensate 1.4% of the zoo’s energy demand
for their animal operations, as well as reduce carbon dioxide emission by 16%. In addition, the
zoo mix and ZMF samples were tested in small-scale pilot digesters. Results show that the zoo
mix sample yielded the highest cumulative gas production while the ZMF sample indicated
inhibition due to low operating pH. The zoo mix and ZMF samples were fit to the Modified
Gompertz Equation model to determine performance parameters for scale-up considerations.

ACKNOWLEDGEMENTS

I would like to thank, wholeheartedly, my advisors, Dr. Dana Kirk and Dr. Wei Liao, for
their guidance and assistance throughout both my undergraduate and graduate experiences. It is
largely due to their support that I have been able to complete this project and develop a passion
for bioenergy. I extend a special thank you to Dr. Kirk, to whom I am thankful for the
tremendous experience working at the Anaerobic Digestion Research and Education Center
(ADREC), and the mentorship he has shown me in my professional development, for which I
would not be the person I am today without. Thank you for always challenging me and giving
me that extra push when it was needed. I would also like to acknowledge Ilsoon Lee for his
support as a member on my committee.
I would like to thank the many laboratory technicians of the ADREC for their copious
help, effort, and enthusiasm on this project. Without their dedication and passion for the work,
this work may not have been completed. I am also grateful to fellow graduate students, Juan
Pablo Rojas and Sebastian Hernandez, for their knowledge, guidance, and kindness throughout
my time in the graduate program. I am also thankful to the Detroit Zoological Society for
supporting this project and providing unique and fun research questions. Their passion for
sustainability, conservation, and education is truly inspiring, and I hope to promote this sort of
enthusiasm in my future endeavors.
Finally, I would like to thank the Biosystems and Agricultural Engineering Department
for the truly wonderful 6 years of learning, experience, and personal and professional
development. It truly has been an honor to be a part of such a great engineering program and
graduate with both Bachelor’s and Master’s degrees from Michigan State University.

iii

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................................... vi
LIST OF FIGURES ................................................................................................................ viii
KEY TO SYMBOLS ................................................................................................................ ix
1. INTRODUCTION...................................................................................................................1
1.1 Problem statement..............................................................................................................1
1.2 Goal and objectives ............................................................................................................3
2. LITERATURE REVIEW ........................................................................................................5
2.1 Anaerobic digestion ...........................................................................................................5
2.1.1 Factors influencing anaerobic digestion .......................................................................5
2.1.2 Evaluation of substrates for anaerobic digestion ..........................................................7
2.1.3 Anaerobic digestion outputs ........................................................................................9
2.1.4 Environmental impact of anaerobic digestion ............................................................ 10
2.1.5 Locations and types of anaerobic digesters ................................................................ 11
2.1.6 Models for anaerobic digestion .................................................................................. 13
2.2 Anaerobic digestion for zoos ............................................................................................ 14
2.2.1 Organic waste management at zoos ........................................................................... 14
2.2.2 Zoo animal waste characterization ............................................................................. 15
2.2.3 Zoo energy consumption ........................................................................................... 15
2.3 Anaerobic digester safety ................................................................................................. 16
3. MATERIALS AND METHODS ........................................................................................... 18
3.1 Organic waste collection and handling ............................................................................. 18
3.1.1 Zoo organic waste ..................................................................................................... 18
3.1.2 Food waste ................................................................................................................ 18
3.1.3 Filtrate....................................................................................................................... 18
3.2 Waste quantification ........................................................................................................ 19
3.3 Preparation of sample mixtures ........................................................................................ 20
3.4 Waste characterization ..................................................................................................... 23
3.5 Biochemical methane potential Test (BMP) ..................................................................... 23
3.5.1 Set-up........................................................................................................................ 23
3.5.2 Operation and Monitoring ......................................................................................... 24
3.5.3 BMP Calculations ..................................................................................................... 25
3.6 Mass and Energy Balance ................................................................................................ 27
3.7 Carbon Footprint .............................................................................................................. 29
3.8 Pilot systems design and operation and analysis ............................................................... 32
3.8.1 Pilot monitoring ........................................................................................................ 36
3.8.2 Feeding ..................................................................................................................... 36
3.8.3 Leachate collection .................................................................................................... 37
3.8.4 Gas ............................................................................................................................ 37
3.8.5 Digestate ................................................................................................................... 38

iv

3.8.6 Model Fitting ............................................................................................................ 38
4. CHARACTERIZATION AND BIOCHEMICAL METHANE POTENTIAL ........................ 41
4.1 Characteristics of animal wastes ....................................................................................... 41
4.2 BMP Test......................................................................................................................... 45
4.2.1 Pre and post-digestion characterization ...................................................................... 45
4.3 Theoretical Mass and Energy Balance and Carbon Footprint ............................................ 51
5. PILOT TESTING AND FITTING A MODEL TO DATA FOR DETERMINATION OF
DIGESTER PERFORMANCE PARAMETERS ....................................................................... 54
5.1 Purpose ............................................................................................................................ 54
5.2 Results and discussion ..................................................................................................... 54
5.2.1 Characterization ........................................................................................................ 54
5.2.2 Gas Production .......................................................................................................... 56
5.2.3 Gas chromatography analysis .................................................................................... 60
5.3 Fitting the pilot data to a simplified anaerobic digestion model ........................................ 61
5.4 Scale-up and future considerations ................................................................................... 68
6. OVERALL CONCLUSIONS AND RECOMMENDATIONS .............................................. 70
6.1 Waste characterization and biochemical methane potential testing ................................... 70
6.2 Pilot data and model fitting .............................................................................................. 71
6.2.1 Physical results .......................................................................................................... 71
6.2.2 Modeling ................................................................................................................... 72
6.3 Future work ..................................................................................................................... 73
APPENDICES .......................................................................................................................... 75
Appendix A: Visual description of zoo samples ..................................................................... 76
Appendix B: Additional BMP data ........................................................................................ 77
Appendix C: Additional data from small-scale pilot testing.................................................... 84
Appendix D: MATLAB code for fitting model to the small-scale pilot digester data .............. 98
REFERENCES ....................................................................................................................... 106

v

LIST OF TABLES

Table 1: Type and quantity of animal wastes at the Detroit Zoo ................................................. 20
Table 2: Comparison of design conditions for Detroit Zoo digester and pilot digesters .............. 33
Table 3: List of materials used for construction of small-scale pilot digesters ............................ 33
Table 4: Pilot feeding schedule .................................................................................................. 36
Table 5: Individual animal waste characterization ..................................................................... 42
Table 6: Characteristics of animal wastes by category a ............................................................. 44
Table 7: Pre and post-digestion TS content in BMP bottles ....................................................... 46
Table 8: Pre and post-digestion VS content in BMP bottles ....................................................... 46
Table 9: Pre and post-digestion chemical oxygen demand in BMP bottles ................................. 47
Table 10: Pre and post-digestion ammonia-nitrogen in BMP bottles .......................................... 47
Table 11: Pre and post-digestion pH in BMP bottles.................................................................. 48
Table 12: Total average cumulative biogas production from 30-day BMP test ........................... 49
Table 13: Biochemical methane potential of zoo wastes a, b ....................................................... 50
Table 14: Theoretical mass and energy balance of anaerobic digestion of zoo wastes ................ 52
Table 15: Pre and post-digestion total solids content in pilot digesters ....................................... 55
Table 16: Pre and post-digestion volatile solids in pilot digesters .............................................. 55
Table 17: Pre and post-digestion carbon-nitrogen ratio .............................................................. 55
Table 18: Pilot digester leachate volume and pH ....................................................................... 56
Table 19: Biogas production at day 30 and day 50 of pilot test .................................................. 60
Table 20: Parameter estimation and result of statistical analysis ................................................ 66
Table 21: Visual description of zoo samples .............................................................................. 76
Table 22: BMP round 1 raw characterization ............................................................................. 77

vi

Table 23: Round 1 BMP pre-digestion data ............................................................................... 78
Table 24: Round 1 BMP post-digestion data.............................................................................. 79
Table 25: Round 1 BMP gas composition from weekly gas chromatography analysis ............... 79
Table 26: BMP round 2 raw characterization ............................................................................. 80
Table 27: Round 2 BMP pre-digestion data ............................................................................... 80
Table 28: Round 2 BMP post-digestion data.............................................................................. 81
Table 29: BMP Round 2 gas composition from weekly gas chromatography analysis ............... 81
Table 30: BMP round 3 raw characterization ............................................................................. 82
Table 31: Round 3 BMP pre-digestion data ............................................................................... 82
Table 32: Round 3 BMP post-digestion data.............................................................................. 83
Table 33: BMP Round 3 gas composition from weekly gas chromatography analysis ............... 83
Table 34: Biogas production data for each collection point for zoo mix 1 pilot .......................... 84
Table 35: Gas composition measured weekly for zoo mix 1 pilot .............................................. 87
Table 36: Leachate volume and pH measured as needed from the zoo mix 1 pilot ..................... 87
Table 37: Biogas production data for each collection point for zoo mix 2 pilot .......................... 87
Table 38: Gas composition measured weekly for zoo mix 2 pilot .............................................. 90
Table 39: Leachate volume and pH measured as needed from the Zoo Mix 2 pilot .................... 90
Table 40: Biogas production data for each collection point for ZMF 1 pilot............................... 91
Table 41: Gas composition measured weekly for ZMF 1 pilot ................................................... 93
Table 42: Leachate volume and pH measured as needed from the ZMF 1 pilot .......................... 94
Table 43: Biogas production data for each collection point for ZMF 2 pilot............................... 94
Table 44: Gas composition measured weekly for ZMF 2 pilot ................................................... 97
Table 45: Leachate volume and pH measured as needed from the ZMF 2 pilot .......................... 97

vii

LIST OF FIGURES

Figure 1: Weight distribution of different waste blends ............................................................. 22
Figure 2: Diagram of a small-scale pilot dry anaerobic digester system ..................................... 34
Figure 3: Tip meter connected to pilot digesters ........................................................................ 35
Figure 4: Pilot set-up in temperature-controlled room................................................................ 35
Figure 5: Gas sampling port connected to the gas outlet tubing from the small-scale pilot
digesters prior to the gas entering the tip meter .......................................................................... 38
Figure 6: Reduction of TS, VS, COD, and increase NH3-N during the BMP testing .................. 48
Figure 7: Average cumulative biogas production from BMP testing .......................................... 49
Figure 8: Carbon footprint of zoo with different waste treatment processes ............................... 53
Figure 9: Cumulative biogas production from each pilot digester .............................................. 57
Figure 10: Leachate pH as collected in 60 day period ................................................................ 58
Figure 11: Rate of gas production during pilot testing ............................................................... 59
Figure 12: Pilot methane content from gas chromatography analysis ......................................... 60
Figure 13: Scaled sensitivity coefficients ................................................................................... 62
Figure 14: Normalized sequential parameter.............................................................................. 64
Figure 15: Model plotted with confidence and prediction bands ................................................ 68

viii

KEY TO SYMBOLS

AD

anaerobic digestion

ADREC

Anaerobic Digestion Research and Education Center

AZA

Association of Zoos and Aquariums

BMP

biochemical methane potential (L biogas per kg VS)

BMPm

biochemical methane potential (L CH4 per kg VS)

CH4

methane

CN

carbon nitrogen

CO

carbon monoxide

CO2

carbon dioxide

COD

chemical oxygen demand

CSTR

continuous stirred tank reactor

DZS

Detroit Zoological Society

GWP

global warming potential

H2S

hydrogen sulfide

MSU

Michigan State University

MSUSCAD Michigan State University South Campus Anaerobic Digester
N2

nitrogen

NH3

ammonia gas

NH3-N

ammonia-nitrogen

OSHA

Occupational Health and Safety Administration

O2

oxygen

ix

RMSE

root mean square error

SSC

scaled sensitivity coefficient

TS

total solids

VS

volatile solids

ZMF

zoo mix & 10 % food waste

x

1. INTRODUCTION
1.1 Problem statement
Sustainability is becoming increasingly important for zoos and aquariums across the country.
The Association of Zoos and Aquariums (AZA), with over 230 accredited zoos and aquariums in
the United States, supports the conservation of animals, and providing resources for sustainable
practices through green initiatives ("Association of Zoos and Aquariums," 2016). In 2008, the
“Communicating Climate Change and the Oceans Summit” was held in Monterey, California
(Kelsey, 2010). The results of the summit were a mobilization of representatives to make an
effort to fight climate change through visitor education in aquariums (Kelsey, 2010). The same
summit, held in Baltimore, Maryland in 2012, followed up on the 2008 conclusions and
furthered the discussion on increasing climate change awareness through a variety of initiatives
(2012 Summit Aquariums Communicating Climate Change, 2011). A public opinion survey
conducted by The Ocean Project (2009) that found that zoos and aquariums are trusted public
outlets for environmental action and campaigns for climate change, so that people expect
information and leadership on climate change from these venues ("America, the Ocean, and
Climate Change: New Research Insights for Conservation, Awareness, and Action," 2009; Kerr,
2010).
The Detroit Zoological Society (DZS) in Royal Oak, Michigan, began operations in 1928
with just 14 permanently housed animals, and is now home to over 2,400 animals ("Detroit Zoo,"
2016). The AZA accredited zoo abides by the vision of AZA to promote green practices and
holds paramount a commitment to environmental leadership and conservation ("Detroit Zoo,"
2016; "Greenprint," 2016). As part of this commitment, the zoo developed an initiative,

1

Greenprint, as a “green roadmap” to improve zoo policies and practices to decrease the zoo’s
environmental footprint ("Greenprint," 2016). In addition to Greenprint, the zoo also has an
initiative entitled “The Zoo that Could”, that promotes on-site energy production and the use of
100% renewable energy in the zoo ("The Zoo that Could,"). At the forefront of sustainability
issues for the Detroit Zoo and other zoos across the world are organic waste management and
high energy consumption (Klasson & Nghiem, 2003; Kusch, 2012).
The Detroit Zoological Society generates over 450 metric tons of animal manure each year.
A majority of this waste is collected in a 20-yard garbage truck and hauled offsite to be
composted (Handbury, 2016). Along with animal manure, each year the zoo has 45 metric tons
of organic food waste generated from on-site cafeteria style food venues (Handbury, 2016).
In addition to the need for sustainable waste management, there is also a large energy
consumption at zoos across the United States, with one study estimating 0.52-26.32 kWh per
square meter per year (Kusch, 2012). Using this estimate, at nearly 506,000 square meters, the
energy consumed by the Detroit Zoo is between 263,000 and 13,318,000 kWh per year. This
wide range is attributed to the recreation of animal habitats with differences in energy
requirements such as heating, cooling, and lighting (Kusch, 2012). Animal care management
guidelines from AZA provide standards for animal habitats including temperature ranges,
lighting, and water and air quality, thus setting baseline values for energy consumption
("Association of Zoos and Aquariums," 2016).
Anaerobic digestion (AD) is a technology that converts organic waste materials into value
added products. AD provides appropriate waste treatment in an energy-efficient manner, while
mitigating the adverse environmental impact of organic waste disposal. The outputs of anaerobic
digestion are a nutrient rich digestate and biogas containing 55 to 75% methane (Tambone et al.,

2

2010). Methane (CH4), the same constituent in natural gas, can be converted to generate
electricity or directly combusted for fuel. Digestate can be further treated with composting or
other value added treatments, or land applied as an organic fertilizer.
There is limited information regarding characterization, biogas potential, and anaerobic
digestion of zoo animal wastes (Kusch, 2012). Waste management practices at zoos across the
United States include composting, landfilling, and incineration, all of which deny the potential to
maximize value from the waste produced. In addition, landfilling and incineration of wastes can
produce CH4 and carbon dioxide (CO2), noxious greenhouse gasses released directly into the
environment contributing to global climate change. With an in depth understanding of organic
waste produced at zoos, anaerobic digestion systems can be applied to alleviate adverse
environmental impacts.
In addition, optimization, safety, education, and operations must also be considered to
achieve maximum benefits of an anaerobic digestion system. Proper education on management
is important in ensuring long term success of the system (Bracmort, Burns, Beddoes, & Lazarus,
2008).
1.2 Goal and objectives
In order to determine the treatment capacity of on-site organic waste including animal
manure and food waste from the Detroit Zoo, this study performed a comprehensive analysis of
zoo animal waste. The analysis was conducted to allow zoos to make educated decisions in
design, implementation, and optimization of an anaerobic digester for on-site waste management.
The specific objectives of this study were to:

3

(1) quantify and characterize organic waste substrates from the Detroit Zoo for application in
anaerobic digestion,

(2) determine the potential biogas production from manure and food waste, generated from
the zoo, and

(3) establish and improve the digester operating parameters such as feedstock for
codigestion, retention time, and leachate recirculation schedule through small-scale pilot
testing and model development.

4

2. LITERATURE REVIEW
2.1 Anaerobic digestion
Anaerobic digestion (AD) is a waste treatment technology that biologically converts organic
waste into value added products that thrive in the absence of oxygen (Olsen & Caruana, 2011).
There are four primary reactions in AD including (1) hydrolysis, (2) acidogenesis, (3)
acetogenesis, and (4) methanogenesis (Crook & Gould, 2009; Khalid, Arshad, Anjum,
Mahmood, & Dawson, 2011; Mani, Sundaram, & Das, 2016; Q. Zhang, Hu, & Lee, 2016).
During the process complex organic compounds in the substrate are converted into methane-rich
biogas (Brule, Oechsner, & Jungbluth, 2014; Crook & Gould, 2009). In addition to biogas, solid
and liquid effluent, or digestate, are produced.
2.1.1 Factors influencing anaerobic digestion
Several important factors that are used to measure the quality of waste treatment and methane
production in anaerobic digestion including pH, temperature, total solids (TS), volatile solids
(VS), chemical oxygen demand (COD), carbon nitrogen (CN) ratio, and ammonia-nitrogen
(NH3-N).
VS and COD content are both parameters that can be used to analytically predict the biogas
output of a substrate in anaerobic digestion, therefore determining the suitability of a substrate
for digestion (Crook & Gould, 2009). During fermentation volatile solids are turned into acids
and then used by methanogens to produce biogas (Brule et al., 2014; Crook & Gould, 2009).
High volatile solids content is desirable for increasing gas production (Crook & Gould, 2009).
In addition to substrates with high volatile solids content, wastewaters with COD greater than
250 mg/L are applicable for digestion given that there is a sufficient amount of organic material
that is able to be used for digestion (Mes, Stams, Reith, & Zeeman, 2003; Olsen & Caruana,

5

2011). Under ideal temperature, microbial, and degradability conditions, each kg of COD
converted can produce 331 L methane (Crook & Gould, 2009).
Temperature and pH are both parameters that need to be considered for the optimal methane
production and stability of the microbial community in the digester. The pH of a digester is
important to maintain viability of the anaerobic microbes in the material (Liu, Yuan, Zeng, Li, &
Li, 2008). The pH effects the enzymatic activity in the digester given that certain enzymes are
active in a narrow band of pH values (Lay, Li, & Noike, 1997). Low pH can prevent the
production of methane and produce a buildup of hydrogen (H 2) which reduces pH further and
inhibits production (Crook & Gould, 2009). One study developed a model for determining pH
for optimum methane production at varying temperatures that can be useful in digester operation
and optimization (Liu et al., 2008).
Carbon, a food for anaerobic microbes, is used up 25 to 30 times faster by microbes than
nitrogen during anaerobic digestion the CN ratio should be in the 25:1 to 30:1 range for efficient
digestion (Yadvika, Santosh, Sreekrishnan, Kohli, & Rana, 2004). In a study that observed
differences in temperature ranges and CN ratio on anaerobic digestion of dairy (cow) manure,
poultry manure, and rice straw, found a CN ratios of 25:1 and 30:1 at temperatures of 35°C and
55°C, respectively, yielded maximum methane production (Wang, Lu, Li, & Yang, 2014). The
same study found that lower CN ratios of 15 and 20 at 35°C and 55°C reduced methane potential
and increased ammonia inhibition (Wang et al., 2014). Ammonia-nitrogen can be used as a
measure of the viability of the gas production in the digestion process. Ammonia toxicity can
occur at ammonia concentrations above 3,000 mg/L and can cause digester failure (Crook &
Gould, 2009).

6

Anaerobic digestion can occur in three different temperature ranges: psychrophilic (below
20°C), mesophilic (25 to 40°C), and thermophilic (52 to 58°C) (Crook & Gould, 2009; DonosoBravo, Bandara, Satoh, & Ruiz-Filippi, 2013). The mesophilic range, usually around 38°C, is
considered to be the preferred temperature for stability of microorganisms (Crook & Gould,
2009). Donoso-Bravo, Bandara, Satoh, and Ruiz-Filippi (2013) compared two models on the
effect of temperature on anaerobic digestion wherein the temperature was allowed to fluctuate
with seasonal changes from 5-30°C (Donoso-Bravo et al., 2013). The study determined that a
cardinal temperature model could accurately describe the trend in both CH4 and CO2 production,
wherein temperature fluctuations directly impacted gas production (Donoso-Bravo et al., 2013).
2.1.2 Evaluation of substrates for anaerobic digestion
To determine the feasibility and economic viability of using a certain substrate for
anaerobic digestion, there are several methods and method adaptations for estimating biogas
potential of organic waste materials including: a Biochemical Methane Potential (BMP) test and
an Automatic Methane Potential Test System (ASMPTS), among other methods (Badshah, Lam,
Liu, & Mattiasson, 2012; El Achkar et al., 2016). BMP results are typically reported as L biogas
per kg of volatile solid in the raw feed. Using the conversion method described by Maclellan,
Chen, Kraemer, Zhong, and Liao (2013), the biogas potential value can be converted to
estimated electrical output (Maclellan et al., 2013). For the purpose of evaluating zoo organic
waste materials, this study will employ the BMP test method described by Faivor and Kirk
(2011), and derived from Chynoweth and others (1993) (Chynoweth, Turick, Owens, Jerger, &
Peck, 1993; Faivor & Kirk, 2011). This BMP method uses a 2:1 sample VS to filtrate VS ratio
for test set up. The test is run under temperature controlled mesophilic conditions. The results
of the BMP test are the biogas potential (BMP), or methane potential (BMP m).

7

There is a variety of organic feedstocks applicable to AD including manure and food
waste, among other organic materials. Currently, there is significant research surrounding
anaerobic digestion of ruminant hoofstock animal manure such as cattle, sheep, and goat. In
addition, there is also prevalent research on other livestock animal wastes like horse, swine, and
poultry litter. In a BMP study performed on five different livestock animal manures including:
dairy (cow), swine, goat, and horse gas production was 295, 495, 242 and 222 L biogas per kg
VS, respectively (Kafle & Chen, 2016). The Association for Technology and Structures reported
BMP values for cattle, swine, poultry, as 420, 817, and 584 L biogas per kg VS, respectively
("Cost-Effectiveness Biogas Calculator," 2016). Another study reported BMPm for cattle, swine,
and poultry manure as 323, 558, and 290 L CH4 per kg VS respectively (Hidalgo & MartĂ­nMarroquĂ­n, 2015). It is expected that the BMP and characterization of animal waste at the
Detroit Zoo, which contains 95% hoofstock animals, would be in the range of other hoofstock
animals waste.
Codigestion is when two or more substrates are blended together to improve biogas
production, digestion of the material, and economic feasibility. Prior to excretion, animal manure
goes through the digestive tract of the animal, therefore utilizing much of the energy potential,
whereas food waste has not previously undergone digestion and therefore has higher energy
content (LĂłpez, Passeggi, & Borzacconi, 2015). Food waste could be codigested with the zoo
waste to improve gas production. However, food waste as a mono-substrate is not favorable for
anaerobic digestion due to its rapid biodegradability, production of long chain fatty acids, and
drop in pH throughout the course of the test (Ebner, Labatut, Lodge, Williamson, & Trabold,
2016; C. Zhang, Xiao, Peng, Su, & Tan, 2013).

8

At the DZS, food waste can be codigested along with the herbivore animal waste to
capitalize on synergistic properties of microbial communities in different waste streams. In a
study performed by Zhang, Xiao, Peng, Su, and Tan (2013) the addition of food waste to cattle
manure in comparison to manure digestion, in both batch and continuous tests, increased
methane production (C. Zhang et al., 2013). Ebner, Labatut, Lodge, Williamson, and Trabold
(2016) reported BMPm values for manure and food waste ranging from 165 L CH4 per kg VS for
a blend of preparation waste (kitchen waste with low biodegradability) to 496 L CH 4 per kg VS
for a food service blend (food preparation post-consumer waste, and uneaten food) (Ebner et al.,
2016). The same study reported an increase in biogas potential in blends of raw manure and
food waste, validating the benefits of codigestion with food waste (Ebner et al., 2016). Another
report estimated BMP for food waste to be 879 L biogas per kg volatile solids ("CostEffectiveness Biogas Calculator," 2016).
2.1.3 Anaerobic digestion outputs
The products of anaerobic digestion are biogas and solid and liquid effluent
(Wedwitschka, Jenson, & Liebetrau, 2016). Biogas containing CH4, CO2 and trace amounts of
other gasses (ammonia (NH3), hydrogen sulfide (H2S), oxygen (O2), nitrogen (N2), and carbon
monoxide (CO)) is produced as a result of anaerobic digestion (Khalid et al., 2011; Sun et al.,
2015; Q. Zhang et al., 2016). Biogas with a composition of 55 to 75% methane has an energy
content of 6.0 to 6.5 kWh per m3 of biogas and can be combusted (Deublein & Steinhauser,
2008)
Biomethane is another term that is used to describe the methane portion of the biogas. In
large scale anaerobic digestion systems biogas can be collected and upgraded to run a generator,
but also can be sent to the natural gas grid or used in boilers and stoves (Sun et al., 2015).

9

Depending on the end use of the biomethane, it is usually necessary to improve the quality of the
biogas to remove moisture, H2S, and CO2 (Sun et al., 2015). There are a variety of methods for
upgrading biogas including water scrubbing, physical and chemical absorption, and membrane
technology, among others (Sun et al., 2015).
As suggested by Appels and others (2011), the digestate, or slurry produced from
anaerobic digestion can separated and land applied as a fertilizer or turned into other value added
products such as biochar or bioalcohol (Appels et al., 2011; Kondaveeti & Min, 2015; Tambone
et al., 2010). Digestate from anaerobic digestion is high in mineralized nutrients, or nutrients that
are readily used by crops, therefore posing a positive economic reuse of waste material (Crook &
Gould, 2009; "Local energy production from biowaste," 2014). In batch anaerobic digestion,
liquid digestate can be recycled to inoculate the new material (Wedwitschka et al., 2016).
2.1.4 Environmental impact of anaerobic digestion
If released into the environment directly, as in a landfill, methane gas can have adverse
environmental impacts and increase the global warming potential (GWP). GWP refers to how
much energy one ton of gas will absorb compared to one ton of CO2 over time ("Understanding
Global Warming Potentials," 2016). As reported by the Environmental Protection Agency
(EPA), CH4, the primary component of biogas, has a GWP of 28-36 tons of CO2 over a 100-year
span ("Understanding Global Warming Potentials," 2016). CH4, when combusted in a generator,
produces CO2 that is carbon-neutral, with less net impact on greenhouse emissions than direct
release of biomethane (Khalid et al., 2011; Ward, Hobbs, Holliman, & Jones, 2008).
While digestate from AD can function as a well-mineralized fertilizer for crop
application, it can also adversely impact the environment if it is not utilized properly. Digestate
can be applied in excess of what crops can uptake and can leach into local waterways causing

10

eutrophication (Yilmazel & Demirer, 2013). One study suggested that removal of the nitrogen
and phosphorus content in the digestate is necessary to avoid eutrophication (Yilmazel &
Demirer, 2013). The appropriate level of nitrogen and phosphorus needs to be reduced during
digestion or post-digestion to avoid adverse environmental impact from over applying the
material. With a nutrient loading calculation of the targeted land, digestate can be appropriately
land applied as an organic fertilizer to reduce the use of chemical based fertilizers.
2.1.5 Locations and types of anaerobic digesters
Anaerobic digesters have applications in many different parts of society and the world. In
small scale application, digesters can function to improve energy reliability and deal with waste
treatment roadblocks, such as those in rural India (Appels et al., 2011). Agriculture and industry
are also important applications for anaerobic digestion as many digesters in the United States are
located on dairy farms, wastewater treatment plants, and food processing facilities (EPA, 2016;
Water, 2016).
There are several different designs of digesters that consider varying design constraints
such as manure handling on-site, TS content of material, material consistency, and local climate
(Roos, Martin Jr., & Moser, 2004). Covered lagoon and fixed film reactors require a solids
content of less than 3% and are suitable in warm and temperate climates and is generally applied
in dairy and swine applications (Crook & Gould, 2009; Roos et al., 2004). A continuous Stirred
Tank Reactor (CSTR), also known as a complete mix digester, is common in dairy and swine
operations with a total solids concentration of manure less than 11% (Conservation Practice
Standard Anaerobic Digester Code 366, 2009; Crook & Gould, 2009; Roos et al., 2004).
Organic waste produced from the zoo is high in solids content due to the manure being
mixed with bedding, leaves, animal feed, and other organic materials. Studies report high solids

11

digesters are applicable when feedstocks have a total solids content greater than 25-30% (w/w)
(Mes et al., 2003; Wedwitschka et al., 2016) . Given the high solids content of zoo organic
waste, high solids batch anaerobic digestion is the best suited technology (Kusch, 2012;
Wedwitschka et al., 2016). In a high-solids batch reactor the substrate is placed into a chamber
where it remains, typically without mixing, for 20 to 30, or more days (Wedwitschka et al.,
2016). Batch digestion relies on recirculation of liquid digestate, or leachate, from the previously
digested material to provide a microbial inoculum to each new batch (Wedwitschka et al., 2016).
The leachate percolates through the material, is collected in a holding tank, and pumped back
into the chamber. Solid digestate is removed after the required retention time and can be further
composted or land applied.
High-solids digestion generally does not need water added to the process, and is simple to
construct and relatively inexpensive to operate (Wedwitschka et al., 2016). High-solids digesters
are favorable for integration with a composting process, as the effluent does not have to pass
through a solid liquid separator. Given that the digestate does not have to be separated, and that
the material is not mixed regularly as in a CSTR, there is less energy consumption from these
types of digesters. Despite less energy consumption, there is typically less energy produced, as
the system is generally not as efficient as CSTR systems likely due to less uniformity in the
process (Wedwitschka et al., 2016). As high solids-digesters require recycle of solid digestate to
ramp up production and stabilize the new system, often the capacity must be large to
accommodate the material needed, which can increase construction costs.
High solids batch digestion systems are dependent on operational parameters being
optimal for digestion efficiency. Retention time, leachate recirculation, and feedstock
codigestion are all parameters that can be adjusted to improve digester performance and biogas

12

production. Small-scale pilot systems can be employed to study the digestion performance and
develop models for methane production to predict scale-up performance parameters.
2.1.6 Models for anaerobic digestion
Modeling allows for an improved understanding of anaerobic digestion, increased
knowledge of design constraints, and a method for prediction of waste treatment capacity and
methane production (Garcia-Ochoa, Santos, Naval, Guardiola, & Lopez, 1999) . There are
several models for batch anaerobic digestion of livestock manures and other organic materials.
One study was able to successfully model the production of acetogenic and methanogenic
bacterial biomass (Garcia-Ochoa et al., 1999). By simplifying the steps of anaerobic digestion
into acid formation (hydrolysis and acidogensis), and methane formation (acetogensis and
methanogensis), Brule and others (2014) developed a model for the prediction of methane
production from a BMP test (Brule et al., 2014). Another study was able to optimize the design
time of leachate recirculation by determining a relationship between the sprinkling rate of
leachate and the solids retention time to maximize methane production (Thamsiriroj, Nizami, &
Murphy, 2012). One study comparatively analyzed the following models: the Logistic function,
Modified Gompertz equation (Equation 20), and reaction curve-type model by fitting data from
anaerobic digestion of sewage sludge (Donoso-Bravo, PĂŠrez-Elvira, & Fdz-Polanco, 2010). The
study found that each of the models were able to estimate the performance parameters. Another
study used the same model to assess the performance conditions under influences of pH and
moisture content in high solids sludge digestion (Lay et al., 1997). Appels et. al. (2011)
concludes that more development of models is necessary to improve the understanding of the
system for optimization (Appels et al., 2011).

13

2.2 Anaerobic digestion for zoos
As part of the Greenprint initiative, the DZS committed to “lessening their environmental
impact” by developing a plan to “refine and improve daily practices, develop new policies and
programs, and improve green literacy” ("Greenprint," 2016). As part of this initiative, the zoo
looked to anaerobic digestion to provide a value added waste management solution to their onsite organic waste production.
2.2.1 Organic waste management at zoos
There is a need for sustainable waste management of organic material produced on-site at
zoos. The Detroit Zoo produces over 450 metric tons of animal manure each year that is hauled
offsite each week with a standard garbage truck to be composted. In addition, the zoo landfills
45 metric tons of organic food waste yearly. Anaerobic digestion is a viable solution to address
organic waste management, while providing the economic incentive of waste reutilization. In
order to determine the feasibility of an anaerobic digestion system at the Detroit Zoo, a
comprehensive understanding of the organic waste is necessary.
Currently, composting is an option for management of the bird and hoofstock animal
waste on site. Other animal manures in the primate, carnivore, and omnivore categories are
landfilled due to concern of the end compost retaining human transmittable pathogens.
According to Martins and others (2013), composting zoo animal waste is a good method to break
down the waste (Martins et al., 2013). Although composting is an appropriate method for
treatment, it does not allow biogas to be collected, which can improve the economic impact of
organic waste management.
Anaerobic digestion is used for waste management for few zoos in the world, including
the Hellabrun Zoo in Munich, Germany, and since 2017, the DZS. At the Munich Zoo, a batch

14

anaerobic digester with 3 digestion chambers was constructed and operates on herbivore manure,
bedding, and green wastes (Kusch, 2012). Each chamber has a loading capacity of 100 m3 and
average 410 m3 per day of biogas under mesophilic conditions (Kusch, 2012). Biogas from the
digester is ran through a combined heat and power generator to provide electricity and heat on
site (Kusch, 2012). Although the Hellabrun Zoo has different animals than the Detroit Zoo, it
validates that anaerobic digestion is feasible at zoos across the world.
2.2.2 Zoo animal waste characterization
There is minimal information available to describe the waste characteristics of zoo animal
manure (Kusch, 2012). In a study performed by Oak Ridge National Laboratory, elephant and
rhinoceros manure were determined to have a biogas potential of 26 L biogas per kg waste and
33 L biogas per kg waste, respectively. The study determined that an anaerobic digester that
treats 20 metric tons of material per week would produce enough energy to run two standard
garden grills. Due to limited characterization data, additional characterization of zoo animal
wastes was necessary to determine the biogas potential and feasibility of a batch digester at the
DZS.
2.2.3 Zoo energy consumption
In a study performed on German, Swiss, and Austrian zoos, and reported by Kusch, zoos
consume 0.52 to 26 kWh per m2 per year (also estimated to be 26 to 1,978 kWh per animal per
year) (Kusch, 2012; Simon). There is a large variation in habitat energy consumption due to the
different conditions that zoos must replicate for the animals to thrive in and the zoos use of
interactive and visual displays (Kusch, 2012). The Detroit Zoo specifically, has 506,000 m2 of
‘naturalistic habitats’, which converts to 263,000 to 13,300,000 kWh per m2 land surface area per
year ("Detroit Zoo," 2016; Kusch, 2012).

15

2.3 Anaerobic digester safety
To manage an anaerobic digester at a zoo, it is important to understand the safety aspects.
The Occupational Safety and Health Administration (OSHA) regulations applicable to anaerobic
digesters need to be implemented to maintain the safety of persons in contact with the digester.
Both influent and effluent from anaerobic digestion should be handled properly to avoid
adverse impacts. Feedstock and digestate should be handled carefully and extra attention should
be given when loading and unloading digester cells (Agstar, 2011). Material should be contained
to the loading area and spills outside the area should be contained. Additionally, leachate is
produced in the batch anaerobic digestion process and generally stored in a holding tank.
Confined space training is required by OSHA for small spaces where workers must enter to
perform tasks, such as fixing sump levels or clogged pipes that can occur in batch digestion
(Agstar, 2011). Persons entering a confined space must test the atmosphere prior to entry using a
handheld device, and O2 should be above 19.5 percent volume by air, CH4 below 5 percent
volume by air, and H2S level below 20 ppm (Agstar, 2011).
Given that anaerobic digestion produces a flammable gas, there are safety concerns that
need to be addressed in operation. One primary concern is the anaerobic conditions within the
digester. If air is mixed in large quantities, it may produce an explosive mixture of gas (Crook &
Gould, 2009). The gas produced also has potential to leak to the environment causing a fire
hazard, explosion potential, and an increase in GHG emissions (Crook & Gould, 2009). In a dry
digestion system, there is risk when opening the chamber to refill it and being exposed to CH 4,
CO2, and H2S. These gases produced with storage of organic material and during anaerobic
digestion are asphyxiants and should be monitored closely (Agstar, 2011). Given this, it is

16

important that operators always have a wearable safety monitor on-person and follow appropriate
loading and unloading procedures.
The generator used for anaerobic digestion is a source of noise in anaerobic digestion.
Proper noise canceling equipment should be employed to protect individuals from excessive
noise. OSHA requires that the managing facility provide hearing protection to maintain a safe
maximum allowable decibel level(Agstar, 2011). There are hazards associated with production
of electrical generation. Licensed electricians should provide maintenance and repairs (Agstar,
2011). Electrical equipment should be regularly inspected and problems should be noted and
fixed by licensed personnel (Agstar, 2011). Signage should be posted for electrical generation
hazards present (Agstar, 2011).
An emergency action plan should be implemented in the AD facility that should include
the events needed in case of an emergency at the facility (Agstar, 2011). Contact personnel, state
and local health requirements, and equipment manuals should also be included. Emergency and
safety equipment should be readily available on-site for operators to employ.

17

3. MATERIALS AND METHODS
3.1 Organic waste collection and handling
Organic waste samples were collected and analyzed by the MSU Anaerobic Digestion
Research and Education Center (ADREC).
3.1.1 Zoo organic waste
Zoo manures were picked up triweekly from the DZS and subsamples were taken
between April 2016 and September 2017. In addition to raw animal manure, the samples
contained bedding, hay, leaves, twigs, and animal feed, among other organic materials. Samples
were transported to MSU in coolers with ice. All zoo wastes were refrigerated at 4°C prior to
analysis.
3.1.2 Food waste
Pre-consumer food waste used was collected from Brody Cafeteria at MSU and was
assumed similar in nature to the cafeteria-style pre-consumer food waste generated at DZS. The
waste was collected from a pulper containing all food prep wastes from the cafeteria. Due to the
rapid degradability of food waste, samples were stored in a freezer at -18°C prior to analysis.
3.1.3 Filtrate
Filtrate was collected from the MSU South Campus Anaerobic Digester (MSUSCAD).
The MSUSCAD utilized a mix of approximately 50% dairy manure and 50% food waste and
food processing residuals as feedstock. The filtrate is the liquid portion of the effluent after the
material passed through a screw press solid-liquid separator with a 500-micron main screen and
750-micron press screen. New filtrate was collected prior to each round of BMP samples (n=3)
and weekly for pilot testing. Filtrate for characterization and BMP analyses was stored in a

18

refrigerator at 4°C. Filtrate used in pilot testing was stored at room temperature, 20-22°C,
opposed the refrigerator in order to mimic zoo conditions.
3.2 Waste quantification
The waste was quantified based on estimates provided from the DZS landscape and
sustainability managers. Total waste production was calculated based on an estimated amount of
cans picked up per animal habitat per pickup and the assumed density of the wastes. Given the
large quantity of bedding used and the nature of the samples, the density of the hoofstock mix
was assumed to be similar to sawdust, 272 kg/m3, and bird mix was assumed to be the same as
loose straw, 40 kg/m3 (Glover, 1995; Lorimor, Powers, & Sutton, 2004). Waste production and
percentages from the respective animal habitats can be found in Table 1. In addition to animal
wastes, the DZS estimates 10 % of their total annual waste is food waste from their cafeterias
and animal feed prep.

19

Table 1: Type and quantity of animal wastes at the Detroit Zoo
Animal
Animal type
Waste production
Weight percentage
category
of the total waste
(kg per year)
(%)
Aardvark
13,752
2.57
Barnyard a
85,950
16.06
Bison
34,380
6.42
Camel, Deer
85,950
16.06
Eland
27,504
5.14
Hoofstock
Giraffe
41,256
7.71
Guanaco, Rhea, Deer
27,504
5.14
Kangaroo
20,628
3.85
Rhino
68,760
12.85
b
Veldt
103,140
19.27
Bird Mix 1 c
5,056
0.94
d
Bird
Bird Mix 2
5,056
0.94
e
West Pampas
1,011
0.19
Carnivore
Lion
9,412
1.76
Primate
Great Ape
5,772
1.08
Total
535,131
100
a.
Barnyard includes cow, horse, swine, and goat.
b.
Veldt includes warthog and zebra.
c.
Bird mix 1 includes flamingo, vulture, golden crown, spoonbill, and stork.
d.
Bird mix 2 includes flamingo, goose, and vulture.
e.
West pampas includes emu and flightless birds.
3.3 Preparation of sample mixtures
Animal wastes were grouped into four categories including: carnivore, primate, hoofstock
mix, and bird mix. The carnivore and primate samples contained the lion and great ape habitats,
respectively. Hoofstock and bird mixtures were prepared according to the estimated waste
production from the respective category (Figures 1a and 1b). A zoo mix was prepared by mixing
the carnivore, primate, hoofstock mix, and bird mix based on the estimated proportion of waste
produced each year (Figure 1c). Additionally, Based on food waste estimates from the DZS, the
zoo mix was combined with food waste in a 90:10 ratio of zoo mix to food waste (ZMF) (Figure
1d). For pilot testing and NREL characterization, carnivore and primate wastes were excluded

20

due to the likelihood of them not being included in the commercial-scale system at the Detroit
Zoo. All other testing included carnivore and primate wastes.

Giraffe
Eland 8%
5%

Aardvark
3%

Kangaroos
4%
Rhinos
14%

Veldt
20%

a. Hoofstock Mix

Barnyard
17%
Bison
7%

Camels,
Deer
17%

Guanaco,
Rhea, Deer
5%

West Pampas
9%

b. Bird Mix

Bird Mix 1
45%

Bird Mix 2
46%

Figure 1: Weight distribution of different waste blends

21

Figure 1 (cont’d)
Bird Mix
2%

Primate
Carnivore
1%
2%

c. Zoo Mix

Hoofstock
Mix
95%

d. ZMF

Food Waste
10%

Zoo Mix
90%

22

3.4 Waste characterization
The raw samples were characterized for TS and VS using EPA accepted Hach methods
8271 and 8276, respectively. For TS, the oven holding time was increased from six to 24 hours
to ensure complete drying. The VS holding time was increased from one to 6 hours to guarantee
complete sample combustion.
Pre and post BMP digestion analyses performed were TS, VS, NH3-N, CN ratio, COD,
and pH. NH3-N was performed using accepted Environmental Protection Agency (EPA) Hach
standard 10205. COD was performed using EPA accepted Hach method 8000. The BMP pH and
EC was tested using an Accumet Excel XL60 meter by Fisher Scientific.
Pre and post pilot digestion testing included TS, VS, CN ratio, and structural
carbohydrates and lignin. CN ratio was performed by two outside laboratories including
Michigan State University (MSU) Plant and Soil Science Lab and A&L Great Lakes
Laboratories using elemental analyses. Samples sent to an outside lab for CN ratio analysis were
stored in containers with ice during transport and were shipped overnight. The pilot leachate pH
testing was done using a Thermo Scientific Orion Star A215 Benchtop meter.
3.5 Biochemical methane potential Test (BMP)
Three rounds of BMP testing were performed. Each round, new zoo, food waste, and
filtrate samples were collected. Samples were collected in June, July, and October of 2016. The
samples tested were carnivore, primate, hoofstock mix, bird mix, zoo mix, food waste, and ZMF.
3.5.1 Set-up
The BMP samples were set up using the method described by Faivor and Kirk (2011), and
derived from Chynoweth and others (Chynoweth et al., 1993; Faivor & Kirk, 2011). After the

23

initial raw sample characterization was completed, sample blends were calculated for the BMP
analysis based on a 2:1 filtrate to sample ratio, with the volume of the filtrate not to exceed 20%
of the bottle volume. Blends were set up to contain 60 mL of filtrate, a calculated amount of
sample to achieve a 2:1 filtrate to sample VS ratio, and the remaining amount up to 300 mL of
deionized water. Due to the heterogeneity of the DZS samples, they were macerated using a
Nutri-Ninja Professional BL450 900 Watt blender without the addition of water to increase
uniformity (Hansen et al., 2004). BMPs for each sample were set up in triplicate to account for
varying quality of filtrate and heterogeneity of the material (Hansen et al., 2004). Triplicate
controls were also set up containing 60 mL of filtrate and 240 mL of deionized water. The
blends were mixed on a stir plate for 10 minutes and 150 mL of the blend was placed into a 200
mL Kimble Chase serum bottle. The remaining 150 mL of the blends were retained for predigestion analyses. The bottles were sealed with a butyl rubber septa from Geo-Microbial
Technologies, INC. and a crimped aluminum cap. The bottles were flushed with nitrogen at a
flowrate of 750 mL per minute for 10 minutes and placed into a mesophilic temperature room at
35°C on a Thermolyne Bigger Bill Oscillator laboratory mixer. After two hours, gas was
released from the bottles and the time was recorded as the starting time. The BMP testing
continued for 30 days.
3.5.2 Operation and Monitoring
Gas production was measured daily using a 10, 30, 50 or 100 mL wetted glass syringe.
Syringe volume selection was based on the prior day’s gas production. Gas composition
including CH4, CO2, and H2S was measured weekly using a HayeSep D column in a SRI 8610
Gas Chromatograph with a flame ionization detector (FID) and thermal conductivity detector
(TCD). The sample was taken from the bottle headspace after gas production was measured.

24

The bottles were taken apart after 30 days and post-digestion analyses were performed on the
effluent.
3.5.3 BMP Calculations
Raw gas is measured in a lab maintained at 22°C and is assumed saturated. Gas is
normalized for standard temperature (0°C) and pressure (1 atm) (STP) using the Equation 1.

𝐺𝑆𝑇𝑃 = 𝐺𝑅 × 0.897

(1)

GSTP

gas normalized for standard temperature and pressure, mL

GR

raw gas production, mL

0.897

STP conversion factor for conditions in East Lansing, MI

Each bottle’s biogas production is normalized to the control bottles that contain only
filtrate and DI water using Equation 2.

𝐺𝑁 = 𝐺𝑆𝑇𝑃 −

𝐶𝑜𝑛𝑡𝑟𝑜𝑙1 + 𝐶𝑜𝑛𝑡𝑟𝑜𝑙2 + 𝐶𝑜𝑛𝑡𝑟𝑜𝑙3
3

GN

normalized gas production, mL

Control1

biogas production from control 1, mL

Control2

biogas production from control 2, mL

Control3

biogas production from control 3, mL

25

(2)

The VS content is calculated for the bottles based on the VS of the raw sample using
Equation 3.
𝑉𝑆𝑁 = 𝑉𝑆𝑅 × 𝑆 ×

1
1000

VSN

volatile solids content in the bottle, mg

VSR

volatile solids content of the raw sample, mg/kg

S

mass of sample in the bottle, g

1/1000

conversion factor, kg/g

(3)

The biogas content of the respective bottles (BMP i) was found by using Equation 4.
𝐵𝑀𝑃𝑖 =

i

𝐺𝑁
𝑉𝑆𝑁

(4)

bottle number

The triplicate bottles are then averaged using Equation 5.
𝐵𝑀𝑃 =

𝐵𝑀𝑃1 + 𝐵𝑀𝑃2 + 𝐵𝑀𝑃3
1
×
× 106
3
1000

BMP

biochemical methane potential, L biogas/kg initial VS

1/1000

conversion factor, L/mL

106

conversion factor, mg/kg

26

(5)

3.6 Mass and Energy Balance
Mass and energy balance analysis were carried out based on the experimental data and
local environmental conditions in Detroit, MI. The analysis was conducted based on 1 kg dry
raw feed. The BMP test data were used to carry out the analysis. The CH 4 production was
calculated using Equation 6.

𝑀=

𝐵𝑀𝑃𝑚 × 𝐺 × 16
0.082 × 𝑇

(6)

M

CH4 production, g methane/kg dry feed

BMPm

biochemical methane potential, L methane/kg initial VS

G

ratio of initial VS to TS in the raw feed

T

biogas temperature, K

16

molecular weight of methane, g/mol

0.082

gas constant, L atm/K/mol

The energy balance was analyzed based on high heat value (HHV) of methane, local
temperature, and thermal efficiencies of combined heat and power (CHP) unit. Energy inputs and
outputs were assigned as negative and positive, respectively. The biogas was assumed to be used
by a combined heat and power (CHP) unit to generate heat and electricity. The energy outputs as
heat (Eheat) and electricity (Eelectricity) were calculated using Equations 7 and 8, respectively.

27

𝐸ℎ𝑒𝑎𝑡 = 𝑀 × 55 × 0.6 × 0.0002778
𝐸𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 = 𝑀 × 55 × 0.3 ×

(7)

1
3600

(8)

Eheat

energy output as heat, kWh-e/kg dry raw feed

Eelectricity

energy output as electricity, kWh-e/kg dry raw feed

55

HHV of methane, kJ/g

0.6

thermal efficiency of a typical CHP (Kurchania, Panwar, & D. Pagar, 2011)

0.3

electrical efficiency of a gas engine

1/3600

conversion factor, kWh/kJ

The energy inputs for the digestion operation include heat to maintain the digestion
temperature as well as electricity to power pumps, mixers, and other accessary equipment. The
heat and electricity energy inputs were calculated using Equations 9 and 10, respectively.

𝑊ℎ𝑒𝑎𝑡 =

1
× 𝐶𝑝 × (308.16 − 283.16) × (1 + 10%) × 0.0002778
𝑇𝑆𝐹𝑒𝑒𝑑

𝑊𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 = 𝐸𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 × 9%

(9)
(10)

Wheat

heat input, kWh-e/kg dry raw feed

Welectricity

electricity input, kWh-e/kg dry raw feed

TSFeed

TS content of the feed, %

Cp

specific heat capacity of the wet feed, 3.95 kJ/kg/K (Zhong et al., 2015)

308.16

digestion temperature, K

28

283.16

average atmosphere (feed) temperature in Detroit, MI, K

10%

percentage of the parasitic heat to maintain digester temperature aside from heat
required by the feed

9%

percentage of the electricity required to power digester related equipment (SlizSzkliniarz & Vogt, 2012)

3.7 Carbon Footprint
The carbon footprint analysis focused on three main sources of carbon dioxide emission:
electricity usage, natural gas usage, and waste handling. Carbon dioxide equivalent emissions
from electricity and natural gas usages (EPA, 2017) were calculated using the EPA methods in
Equations 11 and 12, respectively.

𝐶𝑂2𝑒−𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 = 𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑎𝑛𝑛𝑢𝑎𝑙 × 0.6997

(11)

𝐶𝑂2𝑒−𝑔𝑎𝑠 = 𝐻𝑒𝑎𝑡𝑎𝑛𝑛𝑢𝑎𝑙 × 3600 × 50.25 × 1/106

(12)

CO2e-electricity

CO2 equivalent emissions from electricity (kg/year)

CO2e-gas

CO2 equivalent emissions from natural gas (kg/year)

Electricityannual

annual electricity consumption at the zoo (kWh-e/year)

0.6997

CO2 equivalent emission per kWh electricity usage (kg/kWh) (EPA, 2014)

Heatannual

thermal energy from natural gas consumption at the zoo (kWh-e/year)

3,600

conversion factor, kJ/kWh

50.25

CO2 equivalent emission per kJ thermal energy use, mg/kJ (EPA, 2017)

29

1/106

conversion factor, kg/mg
Two waste handling processes of composting and landfill are applied in these analyses to

study the impact of them on carbon footprint of the zoo. The EPA and IPCC methods (EPA,
2010b) were modified and applied to estimate CO2 equivalent emissions. The CO2 equivalent
emission of the landfill was determined using Equation 13.

𝐶𝑂2𝑒−𝑙𝑎𝑛𝑑𝑓𝑖𝑙𝑙 = 21 × 𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 𝑉𝑆𝑤𝑎𝑠𝑡𝑒𝑠 × 𝐵𝑀𝑃𝑚 × 0.60 ×

1
× 0.67 +
1000

(13)

1 × 𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 𝑉𝑆𝑤𝑎𝑠𝑡𝑒𝑠 × (𝐵𝑀𝑃 − 𝐵𝑀𝑃𝑚 × 0.60) × 1/1000 × 1.77

CO2e-landfill

CO2 equivalent landfill admission, kg/year

21

CH4 GWP

1

CO2 GWP

Fwastes

annual zoo waste generation (zoo mix and food waste), kg wet wastes/year

VSwastes

VS of wastes, kg VS/kg wet wastes

0.60

landfill gas collection efficiency (EPA, 2010a)

1/1000

conversion factor, kg/g

1.77

conversion factor of m3 to kg for CO2

0.67

conversion factor of m3 to kg CH4

The CO2 equivalent emission of the in-vessel composting was calculated using Equation
14.

30

𝐶𝑂2𝑒−𝑐𝑜𝑚𝑝𝑜𝑠𝑡𝑖𝑛𝑔 = 21 × 𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 𝑉𝑆𝑤𝑎𝑠𝑡𝑒𝑠 × 𝐵𝑀𝑃𝑚 × 0.005 ×

1
× 0.67 +
1000

1
𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 𝑉𝑆𝑤𝑎𝑠𝑡𝑒𝑠 × (𝐵𝑀𝑃 − 𝐵𝑀𝑃𝑚 × 0.005) ×
× 1.77 + 𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 0.1 × 0.6997
1000

(14)

0.005

CH4 conversion factor for in-vessel composting (EPA, 2010b)

0.1

electricity consumption rate of composting operation (kWh/kg wet wastes) (H.
Zhang & Matsuto, 2011)

The implementation of anaerobic digestion with biogas power generation converts the
CH4 in the biogas into CO2. The CO2 emissions from anaerobic digestion were calculated using
Equation 15.

𝐶𝑂2𝑒−𝑎𝑑 = 𝐹𝑤𝑎𝑠𝑡𝑒𝑠 × 𝑉𝑆𝑤𝑎𝑠𝑡𝑒𝑠 × 𝐵𝑀𝑃 × 1/1000 × 1.77

CO2e-ad

(15)

CO2 emissions from anaerobic digestion, kg/year

The total CO2 equivalent emission of the zoo with landfill treatment of zoo wastes was
calculated using Equation 16.

𝐶𝑂2𝑒−𝑧𝑜𝑜,𝑙𝑎𝑛𝑑𝑓𝑖𝑙𝑙 = 𝐶𝑂2𝑒−𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 + 𝐶𝑂2𝑒−𝑔𝑎𝑠 + 𝐶𝑂2𝑒−𝑙𝑎𝑛𝑑𝑓𝑖𝑙𝑙

CO2e-zoo,landfill

CO2 equivalent zoo emissions with landfill treatment, kg/year

The total CO2 equivalent emission of the zoo with composting treatment of zoo wastes was
calculated using Equation 17.

31

(16)

𝐶𝑂2𝑒−𝑧𝑜𝑜,𝑐𝑜𝑚𝑝𝑜𝑠𝑡𝑖𝑛𝑔 = 𝐶𝑂2𝑒−𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 + 𝐶𝑂2𝑒−𝑔𝑎𝑠 + 𝐶𝑂2𝑒−𝑐𝑜𝑚𝑝𝑜𝑠𝑡𝑖𝑛𝑔

(17)

CO2e-zoo, composting CO2 equivalent zoo emissions with composting treatment, kg/year

The total CO2 equivalent emission of the zoo with anaerobic digestion of zoo wastes was
calculated using Equation 18.

𝐶𝑂2𝑒−𝑧𝑜𝑜,𝑎𝑑 = 𝐶𝑂2𝑒−𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 + 𝐶𝑂2𝑒−𝑔𝑎𝑠 + 𝐶𝑂2𝑒−𝑎𝑑

CO2e-zoo,ad

(18)

CO2 equivalent zoo emissions with AD treatment, kg/year

3.8 Pilot systems design and operation and analysis
Pilot systems were designed to test operational parameters of batch AD for organic waste
from the DZS. High solids batch AD pilots were built based on the design parameters of the dry
anaerobic digester constructed at the Detroit Zoo. The design conditions for both the DZS
digester and the pilot scale digester are found in Table 2. A diagram of the pilot digester design
in shown in Figure 2. A list of materials used for the construction of the small-scale pilot
digesters is included in Table 3.

32

Table 2: Comparison of design conditions for Detroit Zoo digester and pilot digesters
Detroit Zoo Digester
Small-scale Pilot Digester
Construction Material Concrete
Construction Material PVC
Height (m)
3.0
Height (m)
0.3
Length (m)
4.3
Radius (m)
0.08
Width (m)
3.0
Batch (kg)
9,100
Batch (kg)
1.27
Table 3: List of materials used for construction of small-scale pilot digesters
Component
Quantity
Material
Part Number
a
Flange socket end
1
PVC
4881K221
Flange capa
1
PVC
4881K972
a
End cap
1
PVC
4880K141
a
Oil-resistant Buna-N Gasket
1
Buna-N rubber
8516T243
Schedule 40 PVC pipea
1
PVC
48925K25
Barbed hose fittinga
4
brass
5346K19
Ball valvea
3
PVC
45975K28
Thick wall 0.95 cm tee fittinga
1
PVC
4596K322
a
Pressure gauge
1
Brass
4026K17
Hex nipplea
3
Brass
5485K23
a
Tubing
2m
vinyl
5233K63
Wet tip gas meterb
1
a.
("McMaster-Carr," 2018)
b.
(wettipgasmeter.com, 2018)
Unlike the DZS digester, the pilot systems were cylindrical in shape due to the ease and
cost-effectiveness of sourcing polyvinyl chloride (PVC) piping. The body of the digester was a
0.30 m long schedule 40 PVC pipe. A PVC flange socket end was affixed on top of the digester
body. An oil-resistant compressible Buna-N gasket was placed on the flange socket and a flange
cap was bolted down using eight 19.05 mm bolts. A standard-wall PVC pipe fitting was affixed
to the bottom of the digester.

33

(d) Tip meter

(c) Filtrate wetting port port

(a) Pressure gauge

(b) Gas out

(e)Leachate out

Figure 2: Diagram of a small-scale pilot dry anaerobic digester system
Three ports were drilled into the top flange to input a feeding port with a pressure gauge
(Figure 2a), gas output line (Figure 2b), and filtrate wetting port (Figure 2c). The gas output line
was connected to an accumulative gas flow meter (Wet Tip Gas Meter) filled with water and
affixed with a counter (Figure 2d, Figure 3). Each tip corresponded to a volume of gas produced
determined by calibrating the equipment. Tip meters were placed outside of the temperaturecontrolled room to minimize changes in calibration due to evaporation of water. A ball valve
with an attached barb fitting was installed on the flange cap on the bottom of the digester for

34

leachate output (Figure 2e). One meter of tubing was connected to the barb fitting on the bottom
and the other end was connected to a barb fitting with attached ball valve. The pilots were placed
in a temperature-controlled room (temperature measured daily 37°C¹1) (Figure 4).

Figure 3: Tip meter connected to pilot digesters

Figure 4: Pilot set-up in temperature-controlled room

35

3.8.1 Pilot monitoring
Pilots were monitored each day during feedings. The time, number of tips, amount filtrate fed,
air temperature and pressure was read and recorded. Leachate production was also monitored
and emptied as necessary.
3.8.2 Feeding
Filtrate from the MSUSCAD was used to feed the pilots. Each pilot system was run on a 60-day
feeding schedule that was tapered down every two weeks with the most leachate being fed
during the two weeks. Manual feedings were scheduled 4 times per day at 8 am, 10 am, 2 pm,
and 4 pm. If a scheduled feeding time was missed, the digester was fed at the next scheduled
feeding with both the missed amount and the new feed amount required. On average, the pilots
were scheduled to be wetted 12.5 mL per day (Table 4).

Table 4: Pilot feeding schedule
Volume
Week
(mL/day)
1
20
2
20
3
16
4
16
5
10
6
10
7
4
8
4
Average
12.5

To feed the system, the required amount was drawn into a 60 mL syringe that was
subsequently inserted into the barb fitting on the feed port. The ball valve to the feed port
(Figure 2) was opened and the contents of the syringe were ejected into the digester. The ball
valve was then closed and the syringe removed.

36

3.8.3 Leachate collection
During the course of the test, the ball valve attached to the digester was left open while
the ball valve on the opposite end remained closed to allow the tubing to fill with leachate.
Leachate was collected each time the outlet tubing was full by closing the ball valve connected to
the outlet and opening the other. The volume of leachate out was recorded by pouring the
leachate into a 50 mL graduated cylinder. The leachate pH was also measured and recorded.
3.8.4 Gas
Cumulative gas production was calculated using Equation 19.
𝐺𝐶 = 𝑇 ∗ 𝐶

(19)

GC

cumulative gas production, mL

T

number of tips

C

calibration of tip meter, mL
Gas analysis was performed weekly to record CH4, CO2, and H2S. To collect a sample for

GC analysis a 5 mL SGE Analytical Science syringe was used. The syringe was connected to
the gas sampling port on the gas output line before the tip meter (Figure 5). Once connected, the
syringe was flushed by pulling and plunging slowly three times. Three mL of sample was then
drawn into the syringe and the syringe was connected to the gas chromatograph.

37

Figure 5: Gas sampling port connected to the gas outlet tubing from the small-scale pilot
digesters prior to the gas entering the tip meter
3.8.5 Digestate
The solid digestate was collected after the pilot systems were taken apart. TS, VS, and
NREL tests were performed on the material. A sample was also sent to A&L Great Lakes
Laboratories for CN testing.

3.8.6 Model Fitting
A simplified model was used to describe biogas production per kg initial VS over the
course of the test. The Modified Gompertz equation (Equation 20), described by Donoso-Bravo
and others (2010) and Lay, Li, & Noike (1997), was fit to the pilot data for both the zoo mix and
ZMF samples to estimate the performance parameters (P, Rm, and 𝞴). Duplicate data sets were
used for the fitting to determine the performance parameters.

38

M = P ∗ exp(− exp (

𝑅𝑚 ∗ e
∗ (λ − t) + 1))
P

(20)

P

maximum biogas production, L biogas/kg initial VS

Rm

maximum biogas production rate, L biogas/kg initial VS/day

𝞴

lag phase time, day

e

Euler’s number

t

time, day

In order to determine if the parameters could be identified the scaled sensitivity
coefficients (SSCs) were calculated with the method described by Beck & Arnold (1977), using
initial parameter estimates based on the data. The SSCs are representative of the sensitivity of the
model to the parameters. To calculate the SSCs for a model Ρ(x, t, β), where x and t are
independent variables and β is the parameter vector, the ith sensitivity coefficient was first
calculated using Equation 21 and a forward difference approximation of the first derivative.
𝑋𝑖 =

𝜕η
𝜕β𝑖

(21)

It is desirable to have the SSCs be large relative to Ρ, the dependent variable, and
uncorrelated with each other. To compare the sensitivity coefficients, the sensitivity coefficients
were scaled to find the SSC using Equation 22.
𝑋𝑖′ = β

𝜕η
𝜕β𝑖

(22)

The parameters were then estimated using nlinfit, a MATLAB nonlinear regression
algorithm using ordinary least squares. From the MATLAB analysis, the root mean square error

39

(RMSE), standard error, relative error, residuals, and confidence intervals were determined. The
RMSE determined the goodness-of-fit of the data to the model and should be low relative to the
scale of the model. The most accurate parameters will have the lowest relative error and largest
SSC. The 95% confidence intervals were determined for each parameter. The confidence bands
were plotted along with the bootstrapping confidence and prediction bands. Bootstrapping was
done with the Monte Carlo method of bootstrapping the residuals. Appendix D shows the
MATLAB code used to fit the data to the model and perform the statistical analysis.

40

4. CHARACTERIZATION AND BIOCHEMICAL METHANE POTENTIAL
4.1 Characteristics of animal wastes
Waste samples from 28 different animals and enclosures were collected in June of 2016
for solids content characterization; results are summarized in Table 5. Results show high
variability in samples, due to variation in animal types, sizes, bedding requirements, and sample
content, among others. TS content of the wastes ranged from 172,354 to 915,028 mg per kg for
red panda and bird mix, respectively, while VS content ranged from 146,359 to 858,617 mg per
kg for veldt and bird holding, respectively. Notably, the bird samples were higher in TS and VS
than other waste samples overall due to the high amount of bedding, with the bird mix having the
highest TS at 915,028 mg per kg.

41

Table 5: Individual animal waste characterization
Sample
TS
VS
TS:VS Moisture Content
(mg/kg) (mg/kg)
(%)
Aardvark
383,486
300,287
78%
61.7
a
Asian Horse
411,719
303,860
74%
58.8
Barnyard
327,595
280,214
86%
67.2
Bird Breeding Penb
749,369
726,463
97%
25.1
Bear
476,297
306,339
64%
52.4
c
Bird Holding
880,300
858,617
98%
12.0
d
Bird Mix
915,028
660,713
72%
8.5
Bison
232,897
166,506
71%
76.7
Bush Dog
417,496
200,557
48%
58.3
Camel
273,715
240,858
88%
72.6
Eland
414,745
260,038
63%
58.5
Free Flight Aviarye
647,869
632,836
98%
35.2
Giraffe
604,873
491,643
81%
39.5
Guanaco, Rhea, Deer Mix
494,779
404,056
82%
50.5
Great Ape
262,481
226,224
86%
73.8
Kangaroo
367,322
267,121
73%
63.3
Lion
438,353
321,817
73%
56.2
f
Amphibian Conservatory
330,206
305,872
93%
67.0
Ostrich
465,576
307,053
66%
53.4
Red Panda
172,354
150,744
87%
82.8
Rhino
214,342
194,642
91%
78.6
Stork, Crane
850,055
801,961
94%
15.0
Tree Kangaroo
482,850
419,043
87%
51.7
g
Veldt
339,276
146,359
43%
66.1
h
Warthog
215,260
176,658
82%
78.5
Watering Holei
459,696
303,850
66%
54.0
j
West Pampas
413,363
373,634
90%
58.7
k
Zebra
296,495
245,100
83%
70.4
a.
Asian horse habitat contains Asian horse, vulture, camel, and deer.
b.
Bird breeding pen types of bird vary during the year.
c.
Bird holding types of birds vary during the year.
d.
Bird mix includes flamingo, vulture, golden crown, spoonbill, and stork.
e.
Free flight aviary contains a large variety of bird types.
f.
Amphibian conservatory contains a large variety of amphibian types.
g.
Veldt includes warthog and zebra and was collected along with bedding.
h.
Warthog collected without bedding.
i.
Watering hole contains flamingo, pelican, eland, and ostrich, among other bird types.
j.
West pampas includes emu and flightless birds.
k.
Zebra collected without bedding.

42

The total waste generation from animals at the Detroit Zoo is estimated to be 535,131 kg
per year. Among these, the hoofstock animals produced approximately 508,824 kg wastes per
year. The hoofstock mix was the largest portion and accounted for 95% (w/w) of the zoo animal
wastes (Table 1, Figure 1a). Given this proportion, it was assumed that the hoofstock mix TS and
VS content would be similar to the zoo mix. Table 6 gives the characteristics of animal wastes by
category. TS and VS of the hoofstock mix (395,635 and 296,872 mg per kg) and zoo mix
(397,555 and 295,159 mg per kg) were within the same range as each other. Animals wastes
included in the hoofstock blend ranged from 214,342 to 604,873 mg per kg and 146,359 to
491,643 mg per kg for TS and VS, respectively. Variations in TS content were relative to the
amount of bedding used, size of animal, number of animals in the habitat, and time of year the
samples were collected. For example, the giraffe habitat had high TS at 604,873 mg per kg and a
visual observation of the sample showed it was mostly bedding materials, while the rhino waste
had relatively low TS at 214,342 mg per kg and appeared to contain very little hay and no
bedding material. Visual appearance sample descriptions (i.e. primarily bedding, only manure,
etc.) can be found in Appendix A.
The other 5% (w/w) of the waste include the bird mix at 11,123 kg per year (2.1% w/w),
carnivore at 9,412 kg per year (1.8% w/w), and primate at 5,772 kg per year (1.1%) (Table 1,
Figure 1b). Characterization of the wastes indicates that among zoo wastes, the bird mix has the
highest TS and VS (693,219 and 650,055 mg per kg, respectively), followed by carnivore
(431,385 and 296,196 mg per kg) and hoofstock mix (397,635 and 296,872 mg per kg); primate
waste has the least TS and VS (255,789 and 215,909 mg per kg) (Table 6). Carnivore had much
higher NH3-N and COD concentrations than the other samples.

43

Table 6: Characteristics of animal wastes by category
Sample
TSa
VSa
(mg/kg)
(mg/kg)

a

Carnivore
431,385Âą39,989
296,196Âą31,729
Primate
255,789Âą7,298
215,909Âą12,749
Hoofstock Mix
397,635Âą22,029
296,872Âą10,289
Bird Mix
693,219Âą158,271 650,055Âą116,185
Zoo Mix
397,555Âą22,786
295,159Âą19,696
Food Waste
327,084Âą72,973
274,839Âą27,144
ZMF
362,493Âą17,811
275,729Âą13,693
a.
Data are average with standard deviation.
b.
Data are average with standard error.

C:Nb

pH

12Âą0
14Âą1
30Âą4
27Âą6
26Âą9
14Âą5
26Âą3

8.14
8.23
8.81
6.96
8.64
4.17
8.41

NH3-N
(mg/kg)

COD
(mg/kg)

2,773
332
414
265
401
540
550

426,250
274,875
151,500
152,500
262,000
343,000
264,500

Elemental analysis was conducted to evaluate the CN ratio, NH3, and COD. Data
summarized in Table 6 present that bird and hoofstock mixtures have much higher CN ratios
(27:1 and 30:1, respectively) than carnivore and primate (12:1 and 14:1, respectively). This
indicates that carnivore and primate waste would likely need to be codigested with a high carbon
source to increase the efficiency of digestion and reduce risk of ammonia inhibition (Yadvika et
al., 2004). Additionally, the carnivore waste was very high in NH3-N at 2,773 mg per kg
indicating that if used as a mono-substrate, there could be a chance for ammonia toxicity (Crook
& Gould, 2009).
Hoofstock and bird mixtures with high C:N ratio mixed with low CN ratio carnivore and
primate wastes resulted in the CN ratio of zoo mix (26:1) being in the optimal CN ratio range (of
20:1 to 30:1) for anaerobic digestion (Crook & Gould, 2009). Considering available food waste,
the zoo mix and food waste at a ratio of 90:10 was considered as another feed combination for
anaerobic digestion (Figure 1d). The ZMF has slightly less TS and VS (362,493 and 275,729 mg
per kg), and similar CN ratio (26:1) compared to the zoo mix (Table 6).

44

pH of the zoo samples was in the 8.00-9.00 range with the exception of the bird mix
(6.96) (Table 6). Food waste had the lowest pH at 4.17. This indicates that food waste would
not do well as a mono substrate for the stability of the system given that a low pH can hinder
stability in the system and inhibit the production of methane.
4.2 BMP Test
Seven samples (carnivore, primate, hoofstock mix, bird mix, zoo mix, food waste, and
ZMF) were tested along with the inoculum control in three separate BMP trials, with the
exception of just two BMP trials run for primate. Each BMP sample was tested in triplicate with
the exception of lost data points from laboratory error (breaking a serum bottle). The number of
bottles (n) were averaged together to obtain results. Additional BMP data is located in Appendix
B.
4.2.1 Pre and post-digestion characterization
Pre and post-digestion characterization was carried out to determine the anaerobic
biodegradability of the samples. Table 7 contains the pre and post-digestion TS content, the TS
reduction, and the percent reduction. Initial TS for all runs was approximately 10,000 mg per kg,
except the control run of the seed at approximately 8,000 mg per kg. Each of the samples had a
higher TS percent reduction than the seed. This was due to the higher amount of total solids, and
that there were more easily degradable compounds in fresh feedstocks, opposed to previously
digested material. The food waste sample achieved the highest percentage reduction (33%)
followed by the zoo mix and ZMF samples (27% and 26%, respectively).

45

Table 7: Pre and post-digestion TS content in BMP bottles
Sample
Pre-digestion
Post-digestion
Reduction Reduction
Average Âą Std. Dev. Average Âą Std. Dev.
(mg/L)
(mg/L)
(mg/L)
(%)
Seed
Carnivore
Primate
Hoofstock Mix
Bird Mix
Zoo Mix
Food Waste
ZMF

7,927Âą738
10,716Âą1,741
10,786Âą1,694
9,916Âą579
9,485Âą762
9,838Âą967
10,067Âą1,458
10,489Âą1,206

6,258Âą561
8,122Âą944
8,094Âą937
7,567Âą463
7,115Âą496
7,141Âą564
6,758Âą738
7,807Âą666

1,669
2,593
2,691
2,349
2,370
2,698
3,310
2,682

21%
24%
25%
24%
25%
27%
33%
26%

n

9
9
5
8
9
9
9
8

Table 8 contains the pre and post-digestion VS content, the mass of VS reduced, and the
percent reduction. Similar to TS reduction, food waste had the highest VS reduction percent
(43%), while the hoofstock mix was the lowest.

Table 8: Pre and post-digestion VS content in BMP bottles
Sample
Pre-digestion
Post-digestion
Reduction Reduction
Average Âą Std. Dev. Average Âą Std. Dev.
(mg/L)
(mg/L)
(mg/L)
(%)
Seed
Carnivore
Primate
Hoofstock Mix
Bird Mix
Zoo Mix
Food Waste
ZMF

5,599Âą542
7,717Âą437
8,042Âą1,190
7,154Âą972
7,044Âą824
7,200Âą695
7,594Âą411
7,669Âą543

4,019Âą274
5,037Âą250
5,279Âą609
4,943Âą765
4,761Âą368
4,713Âą464
4,315Âą733
5,112Âą596

1,581
2,680
2,763
2,211
2,283
2,487
3,279
2,557

28%
35%
34%
31%
32%
35%
43%
33%

n

9
9
5
8
9
9
9
8

Table 9 summarizes the pre and post-digestion COD characteristics and the percent
reduction. Again, food waste had the greatest percent reduction indicating it is the most readily
biodegradable.

46

Table 9: Pre and post-digestion chemical oxygen demand in BMP bottles
Sample
Pre-digestion
Post-digestion
Reduction Reduction
Average Âą Std. Dev. Average Âą Std. Dev.
(mg/L)
(mg/L)
(mg/L)
(%)
Seed
Carnivore
Primate
Hoofstock Mix
Bird Mix
Zoo Mix
Food Waste
ZMF

10,122Âą1,780
13,500Âą1,963
13,500Âą1,671
12,688Âą1,339
10,789Âą1,673
11,383Âą1,698
13,256Âą1,830
10,900Âą1,359

7,033Âą472
8,067Âą990
8,580Âą428
7,444Âą916
6,806Âą476
7,350Âą775
7,106Âą848
8,450Âą1,269

3,089
5,433
4,920
5,244
3,983
4,033
6,150
2,450

31%
40%
36%
41%
37%
35%
46%
22%

n

9
9
5
8
9
9
9
8

Table 10 contains the pre and post-digestion ammonia-nitrogen in the BMP test and the
percentage increase. The hoofstock mix had the highest increase in NH 3-N at 61%. Given that all
of the post-digestion pH levels are above 7.00 and the pre and post-digestion values are below
the level of ammonia toxicity (3,000 mg per L), the digestion process will not be inhibited due to
ammonia concentration (Crook & Gould, 2009).
Table 10: Pre and post-digestion ammonia-nitrogen in BMP bottles
Sample
Pre-digestion Post-digestion
Accumulated
Average Âą Std. Average Âą Std.
Dev.
Dev.
(mg/L)
(mg/L)
(mg/L)
Seed
464Âą247
675Âą168
210
Carnivore
493Âą305
772Âą175
278
Primate
651Âą134
709Âą180
58
Hoofstock Mix
473Âą231
759Âą246
286
Bird Mix
475Âą300
609Âą153
134
Zoo Mix
460Âą265
692Âą325
232
Food Waste
504Âą272
638Âą230
134
ZMF
505Âą275
768Âą238
263

Increase

(%)
45%
56%
9%
61%
28%
50%
27%
52%

Figure 6 summarizes the percent reduction of TS, VS, and COD, and increase in NH 3-N.

47

n

9
9
5
8
9
9
9
8

80

Reduction (%)

60

TS

VS

COD

NH3-N

40
20
0

-20
-40
-60

Seed

Carnivore Primate Hoofstock Bird Mix Zoo Mix
Mix

Food
Waste

ZMF

Figure 6: Reduction of TS, VS, COD, and increase NH3-N during the BMP testing
Table 11 contains the pre and post-digestion pH characteristics and difference after
digestion. All post-digestion samples pH were in the optimal range for anaerobic digestion
indicating a stable environment during the BMP test (Liu et al., 2008).
Table 11: Pre and post-digestion pH in BMP bottles
Pre-digestion Post-digestion Difference
Sample
Seed
8.13
7.46
-0.66
Carnivore
7.99
7.32
-0.67
Primate
8.03
7.45
-0.57
Hoofstock Mix
8.02
7.32
-0.70
Bird Mix
8.04
7.46
-0.58
Zoo Mix
8.08
7.32
-0.76
Food Waste
7.79
7.33
-0.46
ZMF
8.17
7.28
-0.89

n
9
9
5
8
9
9
9
8

Average cumulative biogas production data from the BMP test show that during the 30
days test, carnivore, primate, hoofstock mix, bird mix, zoo mix, food waste, and ZMF generated
339, 438, 272, 275, 318, 472, and 343 mL biogas, respectively (Figure 7, Table 12). Food waste
and primate had the highest cumulative biogas production (472 and 438 mL biogas) among all
samples. As for reduction of TS, VS, COD, and NH3-N, food waste had significantly higher TS,

48

VS, COD reduction (33%, 43%, and 46%, respectively) than other samples, while hoofstock mix
had highest NH3-N accumulation (61%) among all samples (Figure 6).

Average Cumulative Biogas Production (mL)

500

Seed
Carnivore
Primate
Hoofstock Mix
Bird Mix
Zoo Mix
Food
Zoo Mix & Food Waste

450

400
350
300
250
200

150
100
50
0

0

5

10

15

20

25

30

Time (day)
Figure 7: Average cumulative biogas production from BMP testing
Table 12: Total average cumulative biogas production from 30-day BMP test
Sample
Average Cumulative
Gas Production
(mL biogas)
Seed
236Âą79
Carnivore
339Âą14
Primate
438Âą63
Hoofstock Mix
272Âą25
Bird Mix
275Âą81
Zoo Mix
318Âą69
Food
472Âą25
ZMF
343Âą60

Biogas production and VS reduction were used to evaluate the digestion performance of
individual samples and mixes. Primate and food waste again had highest BMP of 622 and 653 L

49

biogas per kg initial VS, respectively, among all samples (Table 13). Even though carnivore and
primate samples yielded the highest biogas production, their available quantities only make up
3% of the overall zoo mix. The hoofstock mix as the largest waste of the overall zoo mix had a
BMP of 269 L biogas per kg initial VS. The BMP of the hoofstock mix is in the same range with
other hoofstock animal BMP results (Kafle & Chen, 2016). Since hoofstock mix is the major
composition of the zoo mix, BMP of the zoo mix (232 L biogas per kg initial VS) was not
significantly different from the hoofstock mix (269 L biogas per kg initial VS) (Table 13).
Table 13: Biochemical methane potential of zoo wastes a, b
Sample
BMP
Average Maximum
BMPm
(n)
(L biogas/
methane
methane
(L methane/
kg initial
(%)
(%)
kg initial VS)
VS)
Carnivore
501Âą22
56
68
280Âą41
9
Primate
622Âą42
60
70
374Âą3
5
Hoofstock Mix
269Âą44
61
71
164Âą36
8
Bird Mix
117Âą75
58
71
69Âą46
9
Zoo Mix
232Âą43
59
71
137Âą27
9
Food Waste
653Âą138
63
73
411Âą109
9
ZMF
302Âą40
60
71
183Âą33
8
a.
All data are average with standard deviation.
b. The BMP values were corrected for the methane produced by the seed in the mixture.
In addition, the results of cumulative biogas and BMP clearly demonstrate that food
waste addition improved digestion performance and increased biogas production. The mixture of
90% (w/w) zoo mix and 10% (w/w) food waste had a BMP of 302 L biogas per kg initial VS,
which is 30% more than zoo mix alone (232 L biogas per kg initial VS). The samples all yielded
similar average CH4 percentages. Considering both BMP and available quantities of above tested
samples, zoo mix and ZMF were selected to run mass and energy balance in the following
section.

50

4.3 Theoretical Mass and Energy Balance and Carbon Footprint
The mass and energy balance was conducted to compare the digestion performance with
zoo mix and ZMF (Table 14). Although the zoo digester is a high-solids dry digestion system, a
completely stirred tank reactor (CSTR) was assumed as the digester for theoretical analysis given
that the BMP data are representative of wet digestion systems. TS Feed and retention time were set
at 15% and 30 days, respectively. Using data from BMP (Table 13), the CH4 production of zoo
mix and ZMF were calculated to be 22 and 29 g per kg dry feed, respectively. Based on the
amount of CH4 generated and local environmental condition, the energy balance analysis
concluded that with implementation of a CHP unit, net electricity outputs of zoo mix and ZMF
were 0.09 and 0.12 kWh-e per kg dry feed, respectively, and corresponding net heat outputs were
0.01 and 0.07 kWh-e per kg dry feed. Due to the relatively low annual average temperature in
Detroit (10°C), thermal energy requirements to heat the feed and maintain the digester
temperature were considerably high. The energy generation efficiencies (net energy output per
CH4 energy × 100) were 29% and 42% for zoo mix and ZMF, respectively. Even though the
energy generation efficiencies were relatively low, both feeds showed the positive efficiencies.
Particularly, the addition of food waste is able to increase the gas production and improve the
energy generation efficiency.
Based on the mass and energy balance data (Table 14), anaerobic digestion of 535,131
wet kg per year animal waste from DZS can produce 4,847 kg CH4 per year, and corresponding
net heat and electricity outputs are 1,034 kWh-e and 20,219 kWh-e, respectively. With addition
of food wastes (ZMF ratio of 90:10), the CH4 production, net heat, and electricity outputs were
increased to 6,835 kg, 15,344 kWh-e, and 28,510 kWh-e per year, respectively. It has been

51

reported that average electricity and heat demands of zoo are 553 kWh-e and 1,012 kWh-e per
animal per year, respectively (Kusch, 2012). DZS has approximately 2,000 animals, and
correspondingly requires 1,106,000 and 2,024,000 kWh-e per year of electricity and heat,
respectively for the animal operations. The energy produced from anaerobic digestion of ZMF
can contribute 1.4% of the total energy demand of the zoo animal operations.
Table 14: Theoretical mass and energy balance of anaerobic digestion of zoo wastes
Zoo mix
ZMF
Mass balance
Methane production (M, g/kg dry feed) a

22.47

29.06

Heat input (Wheat, kWh-e/kg dry feed) c

-0.20

-0.20

Electricity input (Welectricity, kWh-e/kg dry feed) d

-0.01

-0.01

Energy output as heat (Eheat, kWh-e/kg dry feed) e

0.21

0.27

Energy output as electricity (Eelectricity, kWh-e/kg dry feed) f

0.10

0.13

Net heat output (kWh-e/kg dry feed) g

0.01

0.07

Net electricity output (kWh-e/kg dry feed) h

0.09

0.12

Energy balance b

Net energy output

a.
b.
c.
d.
e.
f.
g.
h.

Eq. 1 was used to calculate the methane production.
Negative numbers mean energy inputs, and positive numbers mean energy outputs.
Eq. 4 was used to calculate the heat input.
Eq. 5 was used to calculate the electricity input.
Eq. 2 was used to calculate the energy output as heat.
Eq. 3 was used to calculate the energy output as electricity.
The net heat output = Eheat - Wheat
The net electricity output = Eelectricity - Welectricity

Even though the energy generation from anaerobic digestion only contributes a small
portion to the total zoo energy demand, containing zoo wastes has a significant impact on
reducing carbon footprint of the zoo (Figure 8). The total CO2 emission of the zoo with landfill

52

as the waste treatment was 1,450,000 kg CO2-e per year with 53%, 25%, and 21% of the
emission from electricity use, heat use, and waste treatment. With implementation of anaerobic
digestion, the total CO2 emission of the zoo was reduced to 1,210,000 kg CO2-e per year with
only 7% of the emission from the waste treatment, which are 16% lower than the emission with
landfill (1,450,000 kg CO2-e per year with 21% of the emission from the waste treatment), as
well as lower than the emission with composting (1,270,000 CO 2-e per year with 10% of the
emission from the waste treatment).

Figure 8: Carbon footprint of zoo with different waste treatment processes

53

5. PILOT TESTING AND FITTING A MODEL TO DATA FOR DETERMINATION OF
DIGESTER PERFORMANCE PARAMETERS
5.1 Purpose
Given the limited information on anaerobic digestion of zoo organic wastes and dry
digestion systems, it was necessary to test the anaerobic biodegradability. BMP testing,
discussed in Chapter 4, is a standard parameter for which to compare different feedstocks with
one another and is done in a batch, wet anaerobic digestion condition. Dry, batch, anaerobic
digesters were constructed to allow for analysis of zoo organic wastes in dry anaerobic digestion
conditions. By fitting a model to the pilot data, performance parameters can be determined and
decisions can be made to improve operations to increase digestion and gas production in the
commercial-scale system.
5.2 Results and discussion
The zoo mix and ZMF mixture, collected in October 2017, were tested in duplicate in
batch anaerobic digesters. Neither mixture included carnivore nor primate wastes because they
are not being utilized for the commercial-scale system. This is due to concerns with parasites in
the effluent, and their relatively small contribution (less than 3% of total, Table 1) to the overall
waste generation.
5.2.1 Characterization
Pre and post-digestion characteristics were analyzed to determine the biodegradability of
the material in the pilot digester. Table 15 shows the pre and post digestion TS characterization
mass reduced, and the percent reduction of TS. The zoo mix samples had a higher total solids
content (569,776 mg per kg) than the ZMF (420,690 mg per kg), and a higher average percent

54

reduction (48% and 41% for zoo mix and ZMF, respectively) in TS over all, which corresponds
to the higher gas production seen in those samples.
Table 15: Pre and post-digestion total solids content in pilot digesters
Sample
Pre-digestion Post-digestion
Reduction
Reduction
(mg/kg)
(mg/kg)
(mg/kg)
(%)
Zoo Mix (1)
569,776
320,128
276,648
44
Zoo Mix (2)
569,776
273,399
323,377
52
ZMF (1)
420,690
222,629
198,061
47
ZMF (2)
420,690
278,240
142,450
34

Table 16 shows the pre and post-digestion VS characteristics for the pilot digesters. Like
the TS, the zoo mix pilots saw the greatest reduction in volatile solids with zoo mix ranging from
50 to 55% and ZMF ranging from 32 to 48%. As volatile solids are converted into volatile fatty
acids and then used by methanogens to produce gas, the higher VS percent reduction
corresponds with a higher level of gas production and enhanced digestion.
Table 16: Pre and post-digestion volatile solids in pilot digesters
Sample
Pre-digestion Post-digestion
Reduction
(mg/kg)
(mg/kg)
(mg/kg)
Zoo Mix (1)
295,864
147,847
148,017
Zoo Mix (2)
295,864
133,749
162,115
ZMF (1)
260,865
136,686
124,179
ZMF (2)
260,865
177,869
82,996

Reduction
(%)
50
55
48
32

Table 17 shows the CN ratios for pre and post-digestion. The ZMF sample had a lower
CN ratio than the zoo mix, but both samples are in or close to the optimal range for digestion.
Table 17: Pre and post-digestion carbon-nitrogen ratio
Sample
Pre-digestion
Zoo Mix (1)
31.2
Zoo Mix (2)
31.2
ZMF (1)
27.1
ZMF (2)
27.1

55

5.2.2 Gas Production
The leachate began discharge from the pilot much earlier in the ZMF pilots with leachate
production beginning around day 15, as opposed to day 20 for the zoo mix samples. Table 18
shows the cumulative volume of leachate collected from each of the pilots with 158.3, 99.6,
235.6, and 260.1 mL of leachate produced during the test for the zoo mix (1), zoo mix (2), ZMF
(1), and ZMF (2), respectively. On average, the ZMF pilots leached nearly 119 mL more than the
zoo mix sample over the course of the test.
Table 18: Pilot digester leachate volume and pH
Sample
Cumulative
Volume
(mL)
Zoo Mix (1)
158.3
Zoo Mix (2)
99.6
Average Zoo Mix
129.0
ZMF (1)
235.6
ZMF (2)
260.1
Average ZMF
247.9
Figure 9 shows the cumulative biogas production from each of the pilot digesters. The
zoo mix samples showed a higher cumulative gas production than the food waste, and the
duplicate points were much closer to each other. Given the trend found in the BMP results
where the food waste increased production, it is clear that there was an inhibitory effect of the
food waste in the pilot digesters, which was not seen in the BMP results. A t-test of the total
cumulative gas production showed that the zoo mix and ZMF results were significantly different.

56

Figure 9: Cumulative biogas production from each pilot digester

The conditions of the digesters were measured by analyzing the leachate production pH
over the course of the test and determining the volume leaching from the cells. Figure 10 shows
the pH content over time for each sample collected. The data indicates that the ZMF digesters
have a clearly lower pH than the zoo mix digesters. By day 25, the pH reached above 7.00, but it
is clear there was an inhibitory effect of the pH on the gas production, and the microbes did not
recover. One study performed on the influence of pH and moisture content in high-solids
digestion found that in a digester with a pH lower than 6.1 or higher than 8.3, failure can occur
(Lay et al., 1997). For the ZMF samples, both digesters were at or near (6.04 and 6.38 for ZMF
1 and 2, respectively) this critical threshold, and do not reach above 8.00 until between days 30
and 40. While this shows there may be some recovery of the stability, the inhibitory effect of the
low beginning pH still produced a lower gas production overall.

57

Figure 10: Leachate pH as collected in 60 day period

This indicates that the added filtrate may not have the buffering capacity to maintain the
pH in the system with the addition of low pH food waste. More leachate will need to be
recirculated in the beginning of the test or a buffer will need to be added in order to increase the
pH and maintain the system stability. A study that looked at the effect of pH on high solids
anaerobic digestion of food waste set up four samples (untreated, pH 7, pH 8, and pH 9)
concluded that pH 8 reached the maximum methane yield, 7.57 times higher than the untreated
sample (Yang et al., 2015). Figure 10 shows that after day 30, where there was an increase in the
pH for ZMF (1), there is also an increase in the rate of gas production (Figure 11). ZMF (2) did
not reach above 8.00 until day 40, and the rate of production remained relatively constant until
the end of the test. This can also be seen in the cumulative gas production (Figure 9), where the
difference in cumulative production for each sample diverges more drastically after that point
and gas production does not recover in ZMF 2.

58

Figure 11: Rate of gas production during pilot testing
Table 19 summarizes the total biogas per initial VS produced on day 30, and on day 50.
The results show that on day 30, there was 192, 209, 131, and 80 L biogas per kg VS produced
for zoo mix 1, zoo mix 2, ZMF 1, and ZMF 2, respectively. In all pilots, aside from zoo mix and
food waste 1, the majority of gas production occurs in the first 30 days. Due to the pH and rate of
gas production, ZMF 1 produces the majority of its gas after day 30. Given that on average, the
majority of gas production occurs in the first 30 days of the test, in scale-up to a commercial
system it may not be worth running the batches for longer than 30 days, but this operational
parameter would also be dependent on the goals of the project.

59

Table 19: Biogas production at day 30 and day 50 of pilot test
Sample
Day 30 Biogas
Day 50 Biogas
Production
Production
(L biogas/
(L biogas/
kg initial VS)
kg initial VS)
Zoo Mix (1)
192
226
Zoo Mix (2)
209
260
Average
201
243
ZMF (1)
131
210
ZMF (2)
80
96
Average
106
153

Increase
(%)
18
24
21
60
20
40

5.2.3 Gas chromatography analysis
Gas chromatography was performed on the samples typically once per week from each of
the digesters. The maximum and average CH4 values are given in Figure 12. In both the zoo mix
and the ZMF pilots, the digesters reached around 50% methane around day 13 and remained
relatively constant (45-55%) until the end of the test.

Figure 12: Pilot methane content from gas chromatography analysis

60

5.3 Fitting the pilot data to a simplified anaerobic digestion model
A simplified practical model was fit to the in order to determine performance parameters
from the zoo mix and ZMF pilot data. Using the Modified Gompertz equation (Equation 20),
described by Donoso-Bravo and others (2010) and Lay, Li, & Noike (1997), the model was fitted
to determine the following parameters: maximum biogas production (P, L biogas/kg initial VS),
maximum rate of biogas production (Rm, L/kg initial VS*day), and the lag phase time (𝞴, day)
(Donoso-Bravo et al., 2010; Lay et al., 1997).
To determine if the parameters could be adequately identified, the scaled sensitivity
coefficients (SSC) were calculated using initial parameter estimates and the averaged pilot data
for the zoo mix and ZMF samples. A large (>10% of the total scale) and uncorrelated SSC will
provide the most accurate estimate results. Figures 13a and 13b show the SSCs for the zoo mix
and ZMF models, respectively. Since the SSCs were large, and uncorrelated, the parameters
could be individually identified. The zoo mix SSCs show that parameter P is the largest relative
to the scale and will have the lowest relative error. It is also clear that it takes a longer
experimental time to estimate P, likely more than 30 days, whereas R m and 𝞴 can be estimated
after a shorter time. The ZMF SSCs show that parameter Rm is the largest and will have the
lowest relative error. Parameter P (Figure 13b) is small until after day 40, so the experiment
needs at least 40 days to accurately estimate P.

61

(a) Zoo Mix

(b) ZMF
Figure 13: Scaled sensitivity coefficients
Sequential analysis determines the parameter response as more data are introduced over
time. Sequential estimation is important to determine the amount of time the experiment needs
to run for accurate determination of the parameters. Figures 14a and 14b show the sequential
analysis of the zoo mix and ZMF models, respectively. It is clear from the sequential plots that

62

the parameters are more accurately estimated for the zoo mix and variation is decreased as new
data are introduced over time. The zoo mix sequential parameters converge around day 20, so
future experiments will need at least 20 days for accurate parameter estimation, and more than 35
days will yield the most accurate results. This validates the preliminary analysis of the SSC
plots. The ZMF SSCs take longer to converge. While some convergence can be seen after day
50, the ZMF samples may need additional time to more accurately estimate the parameters. This
is likely due to the divergence of the two sets of data and will be more accurately estimated with
additional data points.

63

(a) Zoo Mix

(b) ZMF
Figure 14: Normalized sequential parameter

Table 20 provides the parameter estimation and results of the statistical analysis. In
comparing the model fitting, the zoo mix data has a better fit than the ZMF data. This is due to
the higher variance in the ZMF data. The relative errors of the parameters for the zoo mix, 0.56,
0.75, 1.68% for parameters P, Rm, and 𝞴, respectively, were much lower than those for the ZMF,

64

11.4, 3.8, and 12.6, for P, Rm, and 𝞴, respectively. It is expected, given the trend of the ZMF
data, that the lag time would be most accurately estimated, given that the variance increases as
the time increases, and the lag time concerns only the beginning of the digestion time. The zoo
mix has a low RMSE (<5% of total scale), indicating a good fit of the model to the data. The
ZMF also has a low RMSE relative to the scale (<10% of total scale).
The parameter estimates show a higher maximum gas production (P) and maximum gas
production rate (Rm) in the zoo mix, which was also indicated in the cumulative biogas results.
The lag phase for both systems was similar at 7.1 and 7.5 days for zoo mix and ZMF,
respectively.

65

Table 20: Parameter estimation and result of statistical analysis
Sample Parameter Estimate Relative
95%
Mean of
Error
Confidence
Residuals
(%)
Intervals
339.6
0.56
(335.8,
343.3)
P
Zoo Mix Rm
9.0
0.75
(8.9, 9.1)
-0.03
7.1
1.68
(6.9,7.4)
𝞴
291.8
11.4
(226.1,357.5)
P
ZMF
4.8
3.8
(4.4, 5.1)
0.14
Rm
7.5
12.6
(5.7, 9.4)
𝞴

66

RMSE

Maximum
Correlation
Coefficient

5.61

0.84

25.09

0.79

Further analysis of the residuals shows a signature or serial correlation in the results. This
non-random pattern can indicate that there may be some variable missing from the model or
there is a missing interaction between terms already in the model. Another possibility is that it is
necessary to use different analysis technique that accounts for the serial correlation in the
residuals.
Figures 20a and 20b show the observed data and model with the asymptotic confidence
and prediction bands, and the bootstrapping confidence and prediction bands. The bootstrapping
bands provide a slightly narrower range than the asymptotic bands. The zoo mix shows very
narrow banding, with much of the data fitting within the bootstrapping and asymptotic
confidence bands, indicating a good fit. The ZMF show much wider prediction bands, with only
some of the data fitting within the confidence bands, indicating a worse fit.

67

(a) Zoo Mix

(b) ZMF
Figure 15: Model plotted with confidence and prediction bands
5.4 Scale-up and future considerations
Using this model in scale-up for a commercial system could improve design parameters
and operational conditions. It is necessary to further the research under several operating
conditions to develop more robust parameter estimates. The operating conditions that can be

68

varied include leachate recirculation rate, temperature, in addition to varying the feedstocks used.
Varying the leachate recirculation cycle will likely result in different parameter estimates for the
zoo blend & food waste samples as it will influence the pH of the system. Additionally, future
work may consider a more complex model that accounts for more of the variables in the system.
In considering the design of a high-solids anaerobic digester at a zoo, this model could
help to determine key design aspects. The maximum biogas production could help in
determining the generator size and amount of material needed for desired gas production. The
maximum biogas production rate could help in sizing the gas storage or gas bladder and help in
estimating maximum generator runtime.

69

6. OVERALL CONCLUSIONS AND RECOMMENDATIONS
6.1 Waste characterization and biochemical methane potential testing
The TS and VS content of the individual wastes and waste mixes were variable, with the
bird samples having the highest TS content. Animal habitat bedding appears to be the primary
driver in differences in solids and moisture content, with habitats using more bedding have
higher solids content and lower moisture levels. Given that the zoo uses more bedding in the
winter months and with new animal births, these results will likely vary throughout the year and
additional data points will likely show this variance.
The BMP test of zoo wastes and waste mixes showed that all zoo wastes are
anaerobically biodegradable. The BMP results for the hoofstock mixture (269Âą44 L biogas per
kg initial VS), and the zoo mixture (232Âą43 L biogas per kg initial VS), were similar, given that
the zoo mixture contained 95% hoofstock mixture. Published data for domestic livestock showed
biogas production were in the range of 222 to 584 L biogas per kg VS. Carnivore and primate
wastes had a much higher BMP, however they account for less than 3% of the total waste
production from the zoo. This is likely because the samples contained more readily digestible
material with higher energy content than samples containing lower energy content such as
bedding and hay.
Mixing 10% of food waste with the zoo mix led to 30% increase on biogas production.
Food waste achieved the highest TS, VS, and COD reduction, indicating that it is the most
anaerobically biodegradable sample. Given solely the results of the BMP test, food waste will
improve biogas production and increase the capacity for renewable energy generation and
greenhouse gas reduction.

70

Mass and energy balances indicate that biogas from the anaerobic digestion of zoo wastes
at the Detroit Zoo only replaces a small amount of fossil-based energy, though, the carbon
footprint analysis indicated that 16% reduction of CO2 emission was achieved. The results
concluded that anaerobic digestion is an appropriate solution to manage zoo wastes, significantly
reduce carbon footprint of the zoo, and generate renewable energy.
6.2 Pilot data and model fitting
6.2.1 Physical results
Pilot testing was able to achieve cumulative biogas production, on average, of 244 and
153 L biogas per kg initial VS for zoo mix and ZMF samples, on day 50. The zoo mix samples
showed the highest TS and VS percent reduction. However, the results contradicted the BMP
results, as the zoo mix yielded 90 L biogas per kg VS more than the ZMF in the pilot testing at
day 50.
The inhibition of gas production in the ZMF pilots was shown in the low pH of the
system, with the pH remaining between 6.00 and 7.78 in the ZMF pilots during the first 30 days,
while the zoo mix pH was between 8.08 and 8.37 in the zoo mix. This indicates that it is
necessary to increase the buffering capacity of the system in the beginning of the digestion
process to maintain the pH in the acceptable range for optimal digestion. This could be done by
increasing the amount of leachate sprayed onto the system or controlling the leachate pH by
adding a buffering solution. Another possibility is to add a system to anaerobically digest the
leachate in order to stabilize the pH through a microbial process. The effect of the pH was not
seen in the BMP results due to the amount of filtrate in the system (20% filtrate in the bottle) that
provided the buffering capacity to accommodate the low pH of the food waste.

71

Zoo mix (1) and zoo mix (2) rate of gas production decreased after days 35 and 36,
respectively, indicating that a commercial-scale retention time of over 35 days will reach the
maximum gas production. The ZMF samples saw their rates of production later in the time with
ZMF (1) and zoo mix and food waste (2) reaching their maximum production rates after 43 and
49 days, respectively. The lag in achieving the maximum biogas production rate was the length
of time it took for the pH to stabilize.
6.2.2 Modeling
The model developed from the Modified Gompertz equation (Equation 20) was able to
predict performance parameters in a commercial scale digester, given the fit of the pilot data.
The zoo mix fit the model better than the ZMF data. The SSCs of the parameters were
determined to be large an uncorrelated, which indicated that the parameters could be estimated
with low relative error. These results were confirmed by the low relative errors of the parameters
(Table 20), which indicates a good parameter estimation. Results of sequential analysis indicates
that the parameters could be estimated after day 20 for zoo mix and after day 50 for zoo mix and
food waste. Future testing could shorten the length of the test and still accurately estimate model
parameters. Statistical analysis shows that there is a signature in the residuals, which does not
meet the standard statistical assumptions required to run ordinary least squares. This means
either that a parameter apparent in the biology of the digestion is not being accounted for in the
model or that a different residual analysis may be necessary to account for the serial correlation.
The model can be applied to commercial-scale design and operations. Given a known
amount of zoological organic waste and using the characterization provided in this study, biogas
production per kg initial VS can be estimated at a given time. This can aid in digester design to
determine sizing for both the generator and chamber. The lag phase time can be used to assess

72

system performance and determine when gas production will ramp up. The maximum gas
production rate can be used to determine design parameters for the gas storage tank or bladder, in
addition to generator size and runtime. Additionally, given the BMP finding that the zoo mix will
behave similarly to other hoofstock animals, the model could be broadly applied to zoos with a
similar percentage of hoofstock animals, regardless of the specific animal species percentage, to
aid in digester design.
6.3 Future work
Given the limited data available on anaerobic digestion of zoological organic waste,
many future design considerations could improve the knowledge gap that currently exists. BMP
testing could be performed on individual animal wastes to provide data that are more robust and
more accurately define the biogas potential ranges at zoos. Individual animal waste feedstocks
could also be analyzed for other parameters such as pH, COD, NH3-N, and CN ratio to continue
to improve the research. There is currently a concern that primate and carnivore wastes may
continue to harbor transmittable pathogens post-digestion and composting. Given the high BMP
results from both of these substrates, future data should look at pathogen reduction in both
anaerobic digestion and composting. This could be especially useful in zoos that have a high
percentage of primate and carnivore animals.
Given the simplicity of the model, there are many improvements that could be made, and
future work should look at comparing other models in addition to the Modified Gompertz
Equation, such as those described by Donoso-Bravo and others (2010), or other more complex
models. Additional research on pilot digestion could enhance the robustness of the model.
Potential improvements could be to test additional zoo feedstocks (primate, carnivore, hoofstock,
bird, varying food waste percentages, etc.) to provide a range of parameter values for zoos to

73

more accurately apply the model to various zoo conditions. The leachate recirculation schedules
can also be tested to optimize operations and improve digestion of the ZMF sample.
Additionally, pilot data and the simplified model should be used for comparison against
commercial-scale data to determine validity of the model.

74

APPENDICES

75

Appendix A: Visual description of zoo samples
This appendix gives information on the visual description of collected zoo samples.
Table 21: Visual description of zoo samples
Animal Type
Description
Aardvark
Mix of leaves, bedding, manure
Stork, Crane
Primarily bedding, hay, pellets
Kangaroo
Mix of bedding, hay, manure
Tree Kangaroo
Primarily bedding, leaves, twigs
Bison
Only manure
Rhino
Primarily manure, some hay
Camel
Primarily manure, some hay
Amphibian Conservatory Primarily leaves, tree, dirt
Red Panda
Small amount of bedding
Great Ape
Only manure
Zebra
Only manure
Giraffe 2
Lots of bedding, leaves
Asian Horse
Mix of hay, variety of manure
Watering Hole
Primarily sticks, bedding, leaves
Veldt
Mix of hay, variety of manure
Lion
Only manure
Bush Dog
Only manure
Barnyard 2
Mix of hay, variety of manure
Eland
Primarily manure, some sticks, leaves
Guanaco, Rhea, Deer Mix Mix of manure, sticks, hay, bedding
Free Flight Aviary
Primarily bedding
West Pampas
Primarily bedding
Bird Breeding Pen
Primarily bedding, hay, pellets
Ostrich
Primarily hay
Bird Holding
Primarily bedding, hay
Bird Mix 1
Primarily bedding, hay
Bird Mix 2
Primarily bedding, leaves, hay
Bear
Only manure
Warthog
Only manure

76

Appendix B: Additional BMP data
This appendix provides additional BMP data (raw, pre, and post-digestion analyses) for
individual triplicate samples.
A1. Round 1 BMP
Table 22: BMP round 1 raw characterization
Sample
TS
VS
(mg/kg)
(mg/kg)
Filtrate
35,025
24,278
Carnivore
459,786
288,187
Primate
250,628
206,894
Hoofstock Mix
413,212
302,812
Bird Mix
805,134
717,134
Zoo Mix
421,279
317,902
Food Waste
275,485
259,168
ZMF
375,088
283,635

77

TS
(%)
3.5
46.0
25.1
41.3
80.5
42.1
27.5
37.5

VS TS:VS
(%)
2.4
69%
28.8
63%
20.7
83%
30.3
73%
71.7
89%
31.8
75%
25.9
94%
28.4
76%

Table 23: Round 1 BMP pre-digestion data
Sample
pH
TS
VS
(mg/L)
(mg/L)
Seed 1
8.22
7,132
5,020
Seed 2
8.29
7,263
5,122
Seed 3
8.32
6,582
4,685
Carnivore 1
8.19
10,352
7,362
Carnivore 2
8.23
9,937
7,188
Carnivore 3
8.22
10,130
7,265
Primate 1
Primate 2
8.2
10,170
7,520
Primate 3
7.99
9,657
7,432
Hoofstock Mix 1 8.21
9,817
7,083
Hoofstock Mix 2 8.23
9,678
6,965
Hoofstock Mix 3
Bird Mix 1
8.25
9,325
7,058
Bird Mix 2
8.15
8,645
6,488
Bird Mix 3
8.3
8,165
5,907
Zoo Mix 1
8.19
9,625
7,110
Zoo Mix 2
8.24
9,657
6,947
Zoo Mix 3
8.21
9,452
6,882
Food Waste 1
7.9
9,435
7,213
Food Waste 2
7.91
9,167
6,935
Food Waste 3
8.05
9,552
7,223
ZMF 1
8.27
10,002
7,313
ZMF 2
8.29
10,178
7,445
ZMF 3
8.28
9,697
7,080

78

COD
Ammonia
(mg/L)
(mg/L)
10,850
675
7,750
685
6,900
666
11,800
735
12,700
753
11,500
801
11,650
11,800
11,000
11,550

818
768
680
686

8,900
8,500
9,200
9,750
9,000
9,500
11,050
10,250
12,000
9,850
10,050
8,850

683
673
692
690
681
669
738
787
758
708
688
691

Table 24: Round 1 BMP post-digestion data
Sample
pH
TS
VS
(mg/L)
(mg/L)
Seed 1
7.58
6,082
4,140
Seed 2
7.59
5,945
3,915
Seed 3
7.62
6,055
3,988
Carnivore 1
7.33
8,153
5,065
Carnivore 2
7.40
7,952
4,972
Carnivore 3
7.40
8,178
5,025
Primate 1
Primate 2
7.34
7,112
4,492
Primate 3
7.28
7,560
4,780
Hoofstock Mix 1 7.25
7,765
5,347
Hoofstock Mix 2 7.33
6,918
4,625
Hoofstock Mix 3
Bird Mix 1
7.45
7,442
5,222
Bird Mix 2
7.43
6,963
4,810
Bird Mix 3
7.40
7,000
4,700
Zoo Mix 1
7.25
7,147
4,828
Zoo Mix 2
7.28
7,105
4,887
Zoo Mix 3
7.29
6,302
4,138
Food Waste 1
7.29
5,678
3,583
Food Waste 2
7.32
5,962
3,783
Food Waste 3
7.31
8,680
6,060
ZMF 1
7.21
8,680
6,060
ZMF 2
7.27
7,840
5,192
ZMF 3
7.32
7,822
5,315

COD
Ammonia
(mg/L)
(mg/L)
6,800
584
6,600
560
6,950
520
8,900
591
9,100
614
9,300
587
8,900
8,450
7,900
7,700

573
461
553
552

7,000
7,300
6,350
7,800
8,500
7,450
8,700
6,500
7,050
8,650
7,950
9,500

552
542
535
533
550
535
561
553
573
556
545
561

Table 25: Round 1 BMP gas composition from weekly gas chromatography analysis
Sample
Average
Max
Average
Max
Average
Max
Methane Methane
CO2
CO2
H2 S
H2 S
(%)
(%)
(%)
(%)
(%)
(%)
Carnivore
48
58
20
23
644
792
Primate
61
68
23
26
466
690
Hoofstock Mix
64
69
17
25
162
231
Bird Mix
58
68
14
17
160
199
Zoo Mix
60
67
15
20
163
248
Food Waste
67
71
23
24
455
729
ZMF
63
68
20
24
214
254

79

A2. Round 2 BMP
Table 26: BMP round 2 raw characterization
TS
VS
(mg/kg)
(mg/kg)
Sample
Filtrate
41,709
28,204
Carnivore
448,715
331,162
Primate
260,949
224,924
Hoofstock Mix
413,212
302,812
Bird Mix
805,134
717,134
Zoo Mix
395,546
283,832
Food Waste
275,485
259,168
ZMF
375,088
283,635
Table 27: Round 2 BMP pre-digestion data
pH
TS
VS
(mg/L)
(mg/L)
Sample
Seed 1
8.05
8,430
5,741
Seed 2
8.13
8,289
5,651
Seed 3
8.07
8,346
5,727
Carnivore 1
7.80
11,739
8,430
Carnivore 2
7.96
11,059
7,554
Carnivore 3
7.90
11,180
7,693
Primate 1
7.83
12,173
9,095
Primate 2
7.79
9,405
6,685
Primate 3
8.33
12,525
9,480
Hoofstock Mix 1 8.15
11,350
8,325
Hoofstock Mix 2 8.07
10,908
8,105
Hoofstock Mix 3 7.93
11,315
8,287
Bird Mix 1
8.08
10,308
7,630
Bird Mix 2
7.92
9,627
7,078
Bird Mix 3
7.83
8,845
6,613
Zoo Mix 1
8.19
11,108
7,982
Zoo Mix 2
8.00
11,830
8,470
Zoo Mix 3
8.14
10,343
7,575
Food Waste 1
7.70
10,660
7,717
Food Waste 2
7.58
10,783
8,033
Food Waste 3
7.51
10,758
8,083
ZMF 1
8.02
11,198
8,362
ZMF 2
8.27
11,060
8,035
ZMF 3
8.07
11,728
8,488

80

TS
(%)
4.2
44.9
26.1
41.3
80.5
39.6
27.5
37.5

VS TS:VS
(%)
2.8
68%
33.1
74%
22.5
86%
30.3
73%
71.7
89%
28.4
72%
25.9
94%
28.4
76%

COD
Ammonia
(mg/L)
(mg/L)
10,650
571
10,100
575
10,050
585
16,000
626
14,100
613
14,450
606
14,100
545
14,700
521
15,250
606
13,600
610
12,200
588
12,400
625
11,750
687
11,850
620
11,150
687
12,800
599
12,550
598
12,900
568
14,500
606
13,650
590
14,750
592
11,800
614
12,400
602
12,250
607

Table 28: Round 2 BMP post-digestion data
pH
TS
(mg/L)
Sample
Seed 1
7.78
6,815
Seed 2
7.74
6,790
Seed 3
7.69
7,063
Carnivore 1
7.56
8,427
Carnivore 2
7.48
8,788
Carnivore 3
7.45
8,680
Primate 1
7.54
8,510
Primate 2
7.61
8,370
Primate 3
7.50
8,920
Hoofstock Mix 1
7.48
8,567
Hoofstock Mix 2
7.52
8,788
Hoofstock Mix 3
7.61
8,790
Bird Mix 1
7.73
7,857
Bird Mix 2
7.76
7,740
Bird Mix 3
7.73
7,585
Zoo Mix 1
7.61
8,285
Zoo Mix 2
7.61
7,650
Zoo Mix 3
7.56
8,063
Food Waste 1
7.41
7,320
Food Waste 2
7.55
7,265
Food Waste 3
7.56
6,965
ZMF 1
7.43
7,935
ZMF 2
7.36
8110
ZMF 3
7.37
8217.5

VS
(mg/L)
4,250
4,337
4,392
5,340
5,295
5,258
5,708
5,530
5,885
5,450
5,903
5,737
5,060
5,045
4,945
5,405
4,828
5,278
4,483
4,512
4,168
5,178
5375
5222.5

COD
Ammonia
(mg/L)
(mg/L)
6700
751
7650
768
6750
785
8900
862
7750
853
7650
885
8950
817
7900
859
8700
836
8200
808
8500
796
7750
798
6850
813
7100
803
7350
747
7100
780
7450
789
8350
766
7400
986
7900
914
7000
860
8150
802
7800
799
8250
796

Table 29: BMP Round 2 gas composition from weekly gas chromatography analysis
Sample
Average
Max
Average
Max
Average
Max
Methane Methane
CO2
CO2
H2 S
H2 S
(%)
(%)
(%)
(%)
(%)
(%)
Carnivore
58
71
17
25
382
719
Primate
59
71
21
29
471
682
Hoofstock Mix
57
70
16
26
156
223
Bird Mix
54
70
12
18
111
174
Zoo Mix
58
71
15
24
159
263
Food Waste
57
71
20
26
15
45
ZMF
57
70
18
26
160
243

81

A3. Round 3 BMP
Table 30: BMP round 3 raw characterization
TS
VS
(mg/kg)
(mg/kg)
Sample
Filtrate
27,700
20,007
Carnivore
385,655
269,239
Primate
227,454
193,773
Hoofstock Mix
382,058
284,991
Bird Mix
581,304
515,897
Zoo Mix
375,840
283,744
Food Waste
378,684
306,183
ZMF
349,899
259,917
Table 31: Round 3 BMP pre-digestion data
pH
TS
VS
(mg/L)
(mg/L)
Sample
Seed 1
7.98
8,705
6,155
Seed 2
8.05
8,427
6,145
Seed 3
8.02
8,170
6,147
Carnivore 1
7.65
11,040
8,230
Carnivore 2
8.00
10,605
7,678
Carnivore 3
7.95
10,400
8,055
Primate 1
Primate 2
Primate 3
Hoofstock Mix 1
8.00
9,202
6,290
Hoofstock Mix 2
7.96
8,757
6,082
Hoofstock Mix 3
7.62
8,302
6,097
Bird Mix 1
7.79
9,877
7,282
Bird Mix 2
8.05
11,550
8,777
Bird Mix 3
7.98
9,023
6,562
Zoo Mix 1
7.67
9,002
6,622
Zoo Mix 2
8.10
8,415
6,230
Zoo Mix 3
7.96
9,115
6,983
Food Waste 1
7.93
9,890
7,418
Food Waste 2
7.84
10,005
7,775
Food Waste 3
7.73
10,358
7,950
ZMF 1
ZMF 2
8.04
10,250
7,282
ZMF 3
8.11
9,797
7,343

82

TS
(%)
2.8
38.6
22.7
38.2
58.1
37.6
37.9
35.0

VS TS:VS
(%)
2.0
0.72
26.9
0.7
19.4
0.85
28.5
0.75
51.6
0.89
28.4
0.75
30.6
0.81
26.0
0.74

COD
Ammonia
(mg/L)
(mg/L)
10,450
191
12,200
105
12,150
128
16,650
59
11,100
219
13,200
30

15,050
11,950
13,750
11,400
13,700
10,650
11,200
11,050
13,700
12,850
14,800
15,450

233
179
181
150
12
75
149
101
87
206
137
127

10,000
12,000

63
67

Table 32: Round 3 BMP post-digestion data
pH
TS
VS
(mg/L)
(mg/L)
Sample
Seed 1
6.95
5,215
3,680
Seed 2
7.06
6,113
3,765
Seed 3
7.17
6,245
3,700
Carnivore 1
7.13
7,620
4,868
Carnivore 2
7.13
7,388
4,530
Carnivore 3
7.02
7,915
4,980
Primate 1
Primate 2
Primate 3
Hoofstock Mix 1 7.24
7,422
4,505
Hoofstock Mix 2 7.08
6,580
4,065
Hoofstock Mix 3 7.08
5,704
3,912
Bird Mix 1
7.24
6,213
4,103
Bird Mix 2
7.22
6,464
4,290
Bird Mix 3
7.16
6,770
4,678
Zoo Mix 1
7.07
6,213
4,040
Zoo Mix 2
7.08
6,717
4,525
Zoo Mix 3
7.12
6,783
4,488
Food Waste 1
7.29
6,100
3,895
Food Waste 2
7.11
6,785
4,427
Food Waste 3
7.17
6,063
3,925
ZMF 1
ZMF 2
7.13
7,007
4,440
ZMF 3
7.16
6,845
4,112

COD
Ammonia
(mg/L)
(mg/L)
6,900
639
8,000
465
6,950
1,003
7,000
680
7,300
1,115
6,700
759

6,600
5,700
7,200
6,650
6,800
5,850
6,450
6,400
6,650
6,900
6,800
5,700

660
598
1,305
525
623
347
449
369
1,460
388
332
580

6,500
10,800

819
1,270

Table 33: BMP Round 3 gas composition from weekly gas chromatography analysis
Sample
Average
Max
Average
Max
Average
Max
a
a
Methane Methane
CO2
CO2
H2 S
H2 S
(%)
(%)
(%)
(%)
(%)
(%)
Carnivore
62
75
19
21
454
1027
Primate
Hoofstock Mix
61
75
17
21
62
182
Bird Mix
61
75
16
17
227
376
Zoo Mix
58
75
15
19
64
164
Food Waste
64
76
18
19
515
860
ZMF
60
75
16
18
112
196
a. The first week’s data point for the CO2 reading was not measured and is not included in
the max or average results.

83

Appendix C: Additional data from small-scale pilot testing
This appendix provides additional data from the small-scale pilot testing.
C1. Zoo Mix 1
Table 34: Biogas production data for each collection point for zoo mix 1 pilot
Lapsed Lapsed Cumulative
Biogas
Biogas
Pressure
time
Time
Biogas
Production
Production Rate
(hr)
(day)
(L)
(L biogas/kg
(L biogas/kg
(Pascal)
initial VS)
initial VS*day)
0
0.0
0.0
0.0
0.0
0
18
0.8
2.5
6.7
8.9
1219
22
0.9
2.8
7.5
8.1
1244
24
1.0
2.9
7.7
7.7
1244
73
3.0
4.7
12.5
4.1
1294
88
3.7
4.8
12.8
3.5
100
91
3.8
4.8
12.8
3.4
0
94
3.9
4.8
12.8
3.3
0
96
4.0
4.8
12.8
3.2
0
113
4.7
4.8
12.8
2.7
0
114
4.8
4.8
12.8
2.7
0
119
4.9
4.8
12.8
2.6
0
120
5.0
4.8
12.8
2.6
1244
136
5.7
5.6
14.9
2.6
796
138
5.8
5.7
15.2
2.6
1244
142
5.9
5.9
15.7
2.7
1244
169
7.0
7.2
19.2
2.7
1095
166
6.9
7.5
20.0
2.9
1269
168
7.0
7.6
20.2
2.9
1269
186
7.8
9.0
24.0
3.1
1269
190
7.9
9.4
25.0
3.2
1269
212
8.8
11.3
30.1
3.4
1269
256
10.7
15.9
42.3
4.0
1269
258
10.8
16.1
42.8
4.0
1269
262
10.9
16.5
43.9
4.0
1244
264
11.0
16.6
44.2
4.0
1244
280
11.7
18.5
49.2
4.2
1244
286
11.9
19.1
50.8
4.3
1244
289
12.0
19.4
51.6
4.3
1294
304
12.7
21.1
56.2
4.4
1244
306
12.8
21.4
57.0
4.5
1244
311
12.9
21.8
58.0
4.5
1294
312
13.0
22.0
58.5
4.5
1244
331
13.8
24.2
64.4
4.7
1418
334
13.9
24.5
65.2
4.7
1394

84

Table 34 (cont’d)
336
14.0
353
14.7
355
14.8
358
14.9
360
15.0
405
16.9
425
17.7
426
17.8
430
17.9
432
18.0
449
18.7
450
18.8
454
18.9
456
19.0
472
19.7
478
19.9
480
20.0
521
21.7
526
21.9
528
22.0
554
23.1
593
24.7
594
24.8
598
24.9
600
25.0
617
25.7
618
25.8
622
25.9
624
26.0
640
26.7
646
26.9
648
27.0
670
27.9
691
28.8
744
31.0
761
31.7
762
31.8
766
31.9
784
32.7
786
32.8
790
32.9
792
33.0
808
33.7
810
33.8

24.7
26.7
26.9
27.4
27.6
33.2
35.8
36.1
36.6
36.9
39.1
39.2
39.7
40.0
42.0
42.7
42.9
48.8
49.3
49.6
52.7
57.6
57.7
58.2
58.4
60.4
60.8
61.0
61.2
63.2
63.8
64.1
66.6
68.9
74.8
76.4
76.4
76.9
78.7
78.9
79.3
79.5
81.3
81.5

65.7
71.1
71.6
72.9
73.5
88.4
95.3
96.1
97.4
98.2
104.1
104.3
105.7
106.5
111.8
113.6
114.2
129.9
131.2
132.0
140.3
153.3
153.6
154.9
155.4
160.7
161.8
162.3
162.9
168.2
169.8
170.6
177.2
183.4
199.1
203.3
203.3
204.7
209.4
210.0
211.0
211.6
216.4
216.9

85

4.7
4.8
4.8
4.9
4.9
5.2
5.4
5.4
5.4
5.5
5.6
5.6
5.6
5.6
5.7
5.7
5.7
6.0
6.0
6.0
6.1
6.2
6.2
6.2
6.2
6.3
6.3
6.3
6.3
6.3
6.3
6.3
6.3
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4

1344
1443
1443
1418
1394
1244
1244
1344
1319
1244
1244
1344
1244
1344
1294
1145
1244
1344
1244
1269
1244
1244
1244
1269
1244
1194
1394
1269
1394
1244
1244
1244
1244
1244
1319
1244
1244
1244
1244
1244
1244
1244
1344
1344

Table 34 (cont’d)
814
33.9
834
34.8
838
34.9
858
35.8
862
35.9
864
36.0
909
37.9
931
38.8
935
38.9
936
39.0
952
39.7
954
39.8
958
39.9
960
40.0
977
40.7
982
40.9
984
41.0
1,004
41.8
1,026
42.8
1,032
43.0
1,077
44.9
1,097
45.7
1,099
45.8
1,102
45.9
1,104
46.0
1,122
46.8
1,126
46.9
1,128
47.0
1,144
47.7
1,146
47.8
1,266
52.8
1,290
53.8
1,294
53.9
1,312
54.7
1,314
54.8
1,318
54.9
1,339
55.8
1,362
56.8
1,366
56.9
1,368
57.0
1,386
57.8

81.9
84.1
84.4
86.4
86.7
86.9
91.0
93.0
93.3
93.4
94.9
95.0
95.4
95.6
97.0
97.4
97.6
99.0
100.7
101.2
104.4
105.8
105.9
106.1
106.3
107.4
107.6
107.7
108.6
108.8
115.5
116.6
116.7
117.5
117.6
117.7
118.7
119.6
119.6
119.7
120.4

218.0
223.8
224.6
229.9
230.7
231.3
242.2
247.5
248.3
248.6
252.6
252.8
253.9
254.4
258.2
259.2
259.7
263.5
268.0
269.3
277.8
281.6
281.8
282.4
282.9
285.8
286.4
286.6
289.0
289.6
307.4
310.3
310.6
312.7
313.0
313.2
315.9
318.3
318.3
318.6
320.4

86

6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.4
6.3
6.3
6.3
6.3
6.3
6.3
6.2
6.2
6.2
6.1
6.2
6.1
6.1
6.1
6.1
6.1
5.8
5.8
5.8
5.7
5.7
5.7
5.7
5.6
5.6
5.6
5.5

1219
1145
1244
1244
1194
1244
1219
1244
1244
1244
1194
1194
1219
1194
1194
1294
1244
1194
1095
1194
1145
1145
1194
1194
1194
1194
1120
1145
1244
1194
1145
0
1070
1194
796
1145
1145
1145
1145
1145
1194

Table 35: Gas composition measured weekly for zoo mix 1 pilot
Day
Methane Carbon Dioxide
(%)
(%)
5
3
6
12
52
35
19
55
35
27
46
31
47
50
37
55
46
32
59
46
33
Table 36: Leachate volume and pH measured as needed from the zoo mix 1 pilot
Day
pH
Volume
(mL)
20
8.08
25
23
8.34
22
30
8.37
32
35
8.39
33
48
8.36
46
55
8.67
17
58
8.50
42
59
8.27
16
C2. Zoo Mix 2
Table 37: Biogas production data for each collection point for zoo mix 2 pilot
Lapsed Lapsed Cumulative
Biogas
Biogas
Pressure
time
Time
Biogas
Production
Production Rate
(hr)
(day)
(L)
(L biogas/kg
(L biogas/kg
(Pascal)
initial VS)
initial VS*day)
0
0.0
0.0
0.0
0.0
0
18
0.8
2.4
6.4
8.6
1170
22
0.9
2.6
7.0
7.7
1244
24
1.0
2.9
7.6
7.6
1194
73
3.0
4.5
12.0
3.9
1344
88
3.7
4.6
12.3
3.3
100
91
3.8
4.6
12.3
3.3
100
94
3.9
4.6
12.3
3.1
100
96
4.0
4.6
12.3
3.1
50
113
4.7
4.6
12.3
2.6
75
114
4.8
4.6
12.3
2.6
50
119
4.9
4.6
12.3
2.5
0
120
5.0
4.6
12.3
2.5
1145
136
5.7
5.4
14.3
2.5
50

87

Table 37 (cont’d)
138
5.8
142
5.9
169
7.0
166
6.9
168
7.0
186
7.8
190
7.9
212
8.8
256
10.7
258
10.8
262
10.9
264
11.0
280
11.7
286
11.9
289
12.0
304
12.7
306
12.8
311
12.9
312
13.0
331
13.8
334
13.9
336
14.0
353
14.7
355
14.8
358
14.9
360
15.0
405
16.9
425
17.7
426
17.8
430
17.9
432
18.0
449
18.7
450
18.8
454
18.9
456
19.0
472
19.7
478
19.9
480
20.0
521
21.7
526
21.9
528
22.0
554
23.1
593
24.7
594
24.8

5.5
5.6
6.8
7.2
7.2
8.5
8.8
10.6
15.1
15.2
15.5
15.6
17.6
18.2
18.5
20.2
20.6
21.0
21.1
23.4
23.8
24.0
26.2
26.4
27.0
27.2
33.3
36.1
36.4
37.1
37.4
39.9
40.0
40.6
40.9
43.2
44.1
44.3
50.5
51.2
51.4
55.1
60.9
61.1

14.6
14.9
18.2
19.0
19.0
22.5
23.4
28.1
40.1
40.4
41.3
41.6
46.8
48.3
49.2
53.9
54.7
55.9
56.2
62.4
63.2
63.8
69.7
70.3
71.7
72.3
88.7
96.0
96.9
98.7
99.5
106.3
106.6
108.0
108.9
115.1
117.4
118.0
134.4
136.1
136.7
146.7
162.2
162.5

88

2.5
2.5
2.6
2.7
2.7
2.9
3.0
3.2
3.8
3.8
3.8
3.8
4.0
4.1
4.1
4.3
4.3
4.3
4.3
4.5
4.5
4.6
4.7
4.8
4.8
4.8
5.3
5.4
5.5
5.5
5.5
5.7
5.7
5.7
5.7
5.9
5.9
5.9
6.2
6.2
6.2
6.4
6.6
6.6

1219
1244
1095
1194
1991
1219
1194
1194
1244
1219
1194
1194
1194
1219
1145
1194
1244
1194
1194
1170
1244
1145
1194
1194
1194
1244
1045
1170
1145
1045
1145
1194
1244
1194
1219
1244
1095
1194
1194
1145
1194
1145
1145
1194

Table 37 (cont’d)
598
24.9
600
25.0
617
25.7
618
25.8
622
25.9
624
26.0
640
26.7
646
26.9
648
27.0
670
27.9
691
28.8
744
31.0
761
31.7
762
31.8
766
31.9
784
32.7
786
32.8
790
32.9
792
33.0
808
33.7
810
33.8
814
33.9
834
34.8
838
34.9
858
35.8
862
35.9
864
36.0
909
37.9
931
38.8
935
38.9
936
39.0
952
39.7
954
39.8
958
39.9
960
40.0
977
40.7
982
40.9
984
41.0
1,004
41.8
1,026
42.8
1,032
43.0
1,077
44.9
1,097
45.7
1,099
45.8

61.6
61.9
64.2
64.5
65.0
65.2
67.7
68.4
68.8
71.7
74.5
81.7
83.7
83.8
84.4
86.7
86.9
87.5
87.7
90.0
90.3
90.9
93.1
93.4
95.0
95.3
95.4
98.8
100.2
100.4
100.5
101.6
101.6
102.0
102.1
103.1
103.4
103.5
104.4
105.6
105.9
107.8
108.6
108.6

163.9
164.8
171.0
171.6
173.0
173.6
180.0
182.1
183.0
190.9
198.2
217.5
222.8
223.1
224.5
230.7
231.3
232.7
233.3
239.5
240.3
241.8
247.7
248.5
252.9
253.5
253.8
262.9
266.7
267.3
267.6
270.5
270.5
271.4
271.7
274.3
275.2
275.5
277.8
281.0
281.9
286.9
288.9
288.9

89

6.6
6.6
6.7
6.7
6.7
6.7
6.8
6.8
6.8
6.8
6.9
7.0
7.0
7.0
7.0
7.1
7.1
7.1
7.1
7.1
7.1
7.1
7.1
7.1
7.1
7.1
7.1
6.9
6.9
6.9
6.9
6.8
6.8
6.8
6.8
6.7
6.7
6.7
6.6
6.6
6.6
6.4
6.3
6.3

1170
1219
1145
1194
1170
1145
1145
1244
1170
1194
1170
1219
1145
1194
1194
1145
1095
1145
1194
1145
1194
1145
1045
1145
1070
1244
1194
1170
1170
1194
1194
1145
1219
1170
1170
1170
1145
995
1194
946
1095
995
995
1045

Table 37 (cont’d)
1,102
45.9
1,104
46.0
1,122
46.8
1,126
46.9
1,128
47.0
1,144
47.7
1,146
47.8
1,266
52.8
1,290
53.8
1,294
53.9
1,312
54.7
1,314
54.8
1,318
54.9
1,339
55.8
1,362
56.8
1,366
56.9
1,368
57.0
1,386
57.8

108.7
108.8
109.3
109.5
109.6
110.7
110.9
114.5
115.1
115.2
116.2
116.2
116.4
117.8
118.9
119.0
119.1
119.7

289.2
289.5
291.0
291.3
291.6
294.5
295.1
304.8
306.2
306.5
309.1
309.1
309.7
313.5
316.5
316.8
317.0
318.5

6.3
6.3
6.2
6.2
6.2
6.2
6.2
5.8
5.7
5.7
5.7
5.6
5.6
5.6
5.6
5.6
5.6
5.5

946
1045
896
1269
1219
1194
1145
1070
0
995
1170
697
1045
1045
1095
1941
1244
1294

Table 38: Gas composition measured weekly for zoo mix 2 pilot
Day
Methane Carbon Dioxide
(%)
(%)
5
10
27
12
47
37
19
54
33
27
50
34
47
50
38
55
35
24
59
49
35
Table 39: Leachate volume and pH measured as needed from the Zoo Mix 2 pilot
Day
pH
Volume
(mL)
30
8.32
20
35
8.48
33
48
8.27
47
55
8.75
15
58
8.61
26
59
8.25
24

90

C3. ZMF 1
Table 40: Biogas production data for each collection point for ZMF 1 pilot
Lapsed Lapsed Cumulative
Biogas
Biogas
Pressure
time
Time
Biogas
Production
Production Rate
(hr)
(day)
(L)
(L biogas/kg
(L biogas/kg
(Pascal)
initial VS)
initial VS*day)
0
0.0
0.0
0.0
0.0
0
16
0.7
1.0
3.0
4.5
1344
32
1.3
1.0
3.0
2.2
348
34
1.4
1.1
3.3
2.3
1344
38
1.6
1.4
4.3
2.7
1319
58
2.4
2.5
7.6
3.2
1145
62
2.6
2.9
8.6
3.3
1319
64
2.7
2.9
8.6
3.2
1319
82
3.4
3.6
11.0
3.2
1294
86
3.6
3.9
11.6
3.2
1319
108
4.5
4.6
13.9
3.1
1194
152
6.3
6.2
18.6
2.9
1269
154
6.4
6.2
18.6
2.9
1219
158
6.6
6.2
18.6
2.8
1344
160
6.7
6.3
18.9
2.8
1344
176
7.3
6.8
20.6
2.8
1294
182
7.6
6.9
20.9
2.8
1369
185
7.7
7.0
21.2
2.8
1394
200
8.3
7.6
22.9
2.7
1344
202
8.4
7.6
22.9
2.7
1294
207
8.6
7.7
23.2
2.7
1244
208
8.7
7.7
23.2
2.7
1344
227
9.5
8.4
25.2
2.7
1170
230
9.6
8.5
25.6
2.7
1344
232
9.7
8.5
25.6
2.6
1145
249
10.4
9.1
27.6
2.7
1194
251
10.4
9.2
27.9
2.7
1344
254
10.6
9.4
28.2
2.7
1344
256
10.7
9.5
28.6
2.7
1294
301
12.5
11.3
34.2
2.7
1095
321
13.4
12.3
37.2
2.8
1344
322
13.4
12.4
37.5
2.8
1344
326
13.6
12.7
38.2
2.8
1194
328
13.7
12.8
38.5
2.8
1294
345
14.4
13.8
41.5
2.9
1344
346
14.4
13.8
41.5
2.9
1344
350
14.6
13.9
41.8
2.9
1344
352
14.7
14.0
42.2
2.9
1294

91

Table 40 (cont’d)
368
15.3
374
15.6
376
15.7
417
17.4
422
17.6
424
17.7
450
18.7
489
20.4
490
20.4
494
20.6
496
20.7
513
21.4
514
21.4
518
21.6
520
21.6
536
22.3
542
22.6
544
22.7
566
23.6
587
24.4
640
26.7
657
27.4
658
27.4
662
27.6
680
28.3
682
28.4
686
28.6
688
28.7
704
29.3
706
29.4
710
29.6
730
30.4
734
30.6
754
31.4
758
31.6
760
31.7
805
33.5
827
34.4
831
34.6
832
34.7
848
35.3
850
35.4
854
35.6
856
35.7

14.9
15.2
15.3
17.8
18.0
18.3
19.8
22.9
23.0
23.2
23.4
24.8
24.8
25.1
25.2
26.5
27.0
27.2
28.9
30.7
35.6
37.2
37.2
37.6
39.4
39.6
40.0
40.2
41.9
42.1
42.5
44.7
45.0
47.1
47.4
47.5
51.8
53.8
54.1
54.3
55.9
56.0
56.4
56.5

44.8
45.8
46.2
53.8
54.5
55.1
59.8
69.1
69.4
70.1
70.7
74.7
74.7
75.7
76.0
80.0
81.3
82.0
87.3
92.6
107.6
112.2
112.2
113.6
118.9
119.5
120.9
121.2
126.5
127.2
128.2
134.8
135.8
142.1
143.1
143.4
156.4
162.4
163.4
164.0
168.7
169.0
170.3
170.7

92

2.9
2.9
2.9
3.1
3.1
3.1
3.2
3.4
3.4
3.4
3.4
3.5
3.5
3.5
3.5
3.6
3.6
3.6
3.7
3.8
4.0
4.1
4.1
4.1
4.2
4.2
4.2
4.2
4.3
4.3
4.3
4.4
4.4
4.5
4.5
4.5
4.7
4.7
4.7
4.7
4.8
4.8
4.8
4.8

1344
1194
1344
1344
1344
1344
1344
1294
1294
1369
1344
1344
1294
1319
1319
1294
1319
1319
1294
1319
1294
1294
1294
1244
1244
1194
1244
1219
1244
1244
1244
1194
1244
1244
1219
1244
1244
1244
1244
1244
1244
1244
1244
1344

Table 40 (cont’d)
873
36.4
878
36.6
880
36.7
900
37.5
902
37.6
922
38.4
928
38.7
973
40.5
993
41.4
995
41.4
998
41.6
1001
41.7
1018
42.4
1022
42.6
1024
42.7
1040
43.3
1042
43.4
1162
48.4
1186
49.4
1190
49.6
1208
50.3
1210
50.4
1214
50.6
1235
51.5
1258
52.4
1262
52.6
1264
52.7
1282
53.4

58.1
58.5
58.6
60.2
60.4
62.0
62.2
65.3
66.7
66.9
67.1
67.3
68.4
68.8
68.9
69.9
70.0
76.8
78.0
78.2
78.5
78.5
78.7
79.4
79.4
79.5
79.5
80.6

175.3
176.6
177.0
181.6
182.3
187.3
187.6
197.2
201.2
201.9
202.5
203.2
206.5
207.5
207.8
210.8
211.2
231.8
235.4
236.1
237.1
237.1
237.4
239.7
239.7
240.1
240.1
243.4

Table 41: Gas composition measured weekly for ZMF 1 pilot
Day
Methane Carbon Dioxide
(%)
(%)
7
21
49
14
47
41
22
55
34
32
56
33
39
54
42
56
34
50
51
30
54
55
24

93

4.8
4.8
4.8
4.8
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.9
4.8
4.8
4.8
4.7
4.7
4.7
4.7
4.6
4.6
4.6
4.6

1369
1344
1319
1394
1344
1194
1294
1194
1294
1344
1344
1344
1344
1369
1319
1344
1344
1294
1443
0
149
199
1170
149
224
1120
1194
1145

Table 42: Leachate volume and pH measured as needed from the ZMF 1 pilot
Day
pH
Volume
(mL)
15
6.04
32
18
6.52
32
22
7.29
35
25
7.78
29
30
8.18
30
35
8.50
38
42
8.40
40
50
8.59
43
53
8.04
54
8.40
13
C4. ZMF 2
Table 43: Biogas production data for each collection point for ZMF 2 pilot
Lapsed Lapsed Cumulative
Biogas
Biogas
Pressure
time
Time
Biogas
Production
Production Rate
(hr)
(day)
(L)
(L biogas/kg
(L biogas/kg
(Pascal)
initial VS)
initial VS*day)
0
0.0
0.0
0.0
0.0
0
16
0.7
1.2
3.7
5.5
1344
32
1.3
3.1
9.3
7.0
1344
34
1.4
3.2
9.6
6.8
1294
38
1.6
3.5
10.6
6.7
1294
58
2.4
4.5
13.6
5.6
1145
62
2.6
4.7
14.3
5.5
1319
64
2.7
4.7
14.3
5.4
1617
82
3.4
5.5
16.6
4.9
1369
86
3.6
5.7
17.3
4.8
1344
108
4.5
6.4
19.3
4.3
1294
152
6.3
7.6
22.9
3.6
1294
154
6.4
7.7
23.2
3.6
1219
158
6.6
7.7
23.2
3.5
1244
160
6.7
7.7
23.2
3.5
1269
176
7.3
8.1
24.6
3.4
1244
182
7.6
8.3
24.9
3.3
1194
185
7.7
8.3
24.9
3.2
1294
200
8.3
8.6
25.9
3.1
1294
202
8.4
8.7
26.2
3.1
1194
207
8.6
8.8
26.6
3.1
1194
208
8.7
8.8
26.6
3.1
1244
227
9.5
9.1
27.6
2.9
1045

94

Table 43 (cont’d)
230
9.6
232
9.7
249
10.4
251
10.4
254
10.6
256
10.7
301
12.5
321
13.4
322
13.4
326
13.6
328
13.7
345
14.4
346
14.4
350
14.6
352
14.7
368
15.3
374
15.6
376
15.7
417
17.4
422
17.6
424
17.7
450
18.7
489
20.4
490
20.4
494
20.6
496
20.7
513
21.4
514
21.4
518
21.6
520
21.6
536
22.3
542
22.6
544
22.7
566
23.6
587
24.4
640
26.7
657
27.4
658
27.4
662
27.6
680
28.3
682
28.4
686
28.6
688
28.7
704
29.3

9.2
9.2
9.6
9.7
9.8
9.8
10.9
11.6
11.6
11.7
11.8
12.3
12.3
12.4
12.5
13.0
13.1
13.2
14.4
14.5
14.6
15.4
16.9
16.9
17.1
17.2
17.7
17.7
17.8
17.9
18.5
18.7
18.8
19.6
20.4
22.7
23.3
23.3
23.5
24.3
24.4
24.6
24.8
25.6

27.9
27.9
28.9
29.2
29.6
29.6
32.9
34.9
34.9
35.2
35.5
37.2
37.2
37.5
37.9
39.2
39.5
39.8
43.5
43.8
44.2
46.5
51.1
51.1
51.5
51.8
53.5
53.5
53.8
54.1
55.8
56.4
56.8
59.1
61.4
68.4
70.4
70.4
71.1
73.4
73.7
74.4
74.7
77.4

95

2.9
2.9
2.8
2.8
2.8
2.8
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.5
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6

1219
1045
1095
1294
1294
1194
1045
1145
1294
1095
1194
1244
1244
1194
1145
1244
1070
1244
1244
1294
1294
1244
1244
1244
1244
1244
1244
796
1269
1294
1244
1244
1294
1244
1269
1244
1244
1294
1244
1244
1244
1244
1244
1244

Table 43 (cont’d)
706
29.4
710
29.6
730
30.4
734
30.6
754
31.4
758
31.6
760
31.7
805
33.5
827
34.4
831
34.6
832
34.7
848
35.3
850
35.4
854
35.6
856
35.7
873
36.4
878
36.6
880
36.7
900
37.5
902
37.6
922
38.4
928
38.7
973
40.5
993
41.4
995
41.4
998
41.6
1001
41.7
1018
42.4
1022
42.6
1024
42.7
1040
43.3
1042
43.4
1162
48.4
1186
49.4
1190
49.6
1208
50.3
1210
50.4
1214
50.6
1235
51.5
1258
52.4
1262
52.6
1264
52.7
1282
53.4

25.7
26.0
27.1
27.3
28.4
28.5
28.6
30.7
31.8
32.0
32.2
33.0
33.1
33.3
33.4
34.3
34.7
34.8
35.6
35.8
36.9
37.2
39.5
40.5
40.6
40.8
41.0
41.8
41.9
42.0
42.5
42.8
48.0
49.0
49.1
49.7
49.8
49.9
50.2
50.4
50.4
50.4
50.4

77.7
78.4
81.7
82.3
85.7
86.0
86.3
92.6
96.0
96.6
97.3
99.6
99.9
100.6
100.9
103.6
104.6
104.9
107.6
107.9
111.2
112.2
119.2
122.2
122.5
123.2
123.8
126.2
126.5
126.8
128.2
129.2
144.8
147.8
148.1
150.1
150.4
150.7
151.4
152.1
152.1
152.1
152.1

96

2.6
2.6
2.7
2.7
2.7
2.7
2.7
2.8
2.8
2.8
2.8
2.8
2.8
2.8
2.8
2.8
2.9
2.9
2.9
2.9
2.9
2.9
2.9
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
2.9
2.9
2.9
2.9
2.8

1244
1244
1244
1194
1269
1244
1244
1244
1244
1269
1269
1294
1244
1244
1244
1369
1219
1244
1244
1244
1145
1294
1194
1244
1244
1244
1244
1244
1394
1344
1344
1319
1319
597
771
1344
1095
1344
1244
1344
1145
747
846

Table 44: Gas composition measured weekly for ZMF 2 pilot
Day
Methane Carbon Dioxide
(%)
(%)
7
19
52
14
40
46
22
53
39
32
57
37
39
52
42
57
34
50
29
18
54
60
25
Table 45: Leachate volume and pH measured as needed from the ZMF 2 pilot
Day
pH
Volume
(mL)
15
6.38
34
18
6.58
40
22
6.60
28
25
7.05
38
30
7.52
36
42
8.18
42
43
8.08
42
50
8.53
30
54
8.44
16

97

Appendix D: MATLAB code for fitting model to the small-scale pilot digester data
This appendix provides the code used for fitting the the Modified Gompertz equation model to
the data from the small-scale pilot digesters.
%% Housekeeping
close all
clear
clc
format long
%% Read in data
data=xlsread('zoo model data');
%% Experimental Data
tobs=data(:,1);
nobs=length(tobs);
yobs=data(:,2);
figure
plot(tobs, yobs,'o')
xlabel 'Time (d)'
ylabel 'Cumulative Biogas Production (L/kg initial VS)'
%% Explicit Function
fnameFOR=@Gompertz_FOR;
type Gompertz_FOR.m
%% Initial Guesses
P= 300;
Rm= 9;
lambda= 8;
beta0(1)=P;
beta0(2)=Rm;
beta0(3)=lambda;
p=length(beta0);
%% Call and plot the function
Y=Gompertz_FOR(beta0,tobs);
plot(tobs,Y)
%% nlinfit returns parameters, residuals, Jacobian (sensitivity coefficient matrix),
fnameINV=@Gompertz_FOR;
[beta,resids,J,COVB,mse] = nlinfit(tobs, yobs,fnameINV, beta0);
beta
rmse=sqrt(mse)

98

condX=cond(J)
detXTX=det(J'*J)
[R,sigma]=corrcov(COVB);
R
sigma
relerr=sigma'./beta
ci=nlparci(beta,resids,J)
meanr=mean(resids)
%% Plot of Observed Data and Predicted Model
ypred=fnameINV(beta,tobs);
figure
plot(tobs,ypred)
hold on
plot(tobs,yobs,'o')
ylabel 'Biogas (L per kg initial VS)'
xlabel 'Time (d)'
legend ('Predicted', 'Observed', 'location', 'best')
%% X' = scaled sensitivity coefficients using forward-difference for estimated parameters
ts=linspace(0,max(tobs),1000)';
ypred=fnameINV(beta,ts);
Xp=SSC_V3(beta,ts,fnameFOR);
ns=length(ts);
cmap = ['r' 'g' 'b' 'c' 'y' 'm' 'k' ]';
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
h2(1)=plot(ts,ypred,'-','color',cmap(1,:),'LineWidth',2);
for i=1:p
h2(i+1) = plot(ts,Xp(:,i),'-','color',cmap(i+1,:),'LineWidth',2);
end
legend('Predicted','P','R_m','\lambda', 'location', 'best')
xlabel('Time (d)'); ylabel('Scaled Sensitivity Coefficient or L biogas/kg initial VS');
grid on
%% Confidence and prediction intervals for the dependent variable
[ypred, delta] = nlpredci(fnameINV,tobs,beta,resids,J,0.05,'on','curve');
[ypred, deltaob] =nlpredci(fnameINV,tobs,beta,resids,J,0.05,'on','observation');
CBu=ypred+delta;
CBl=ypred-delta;
PBu=ypred+deltaob;
PBl=ypred-deltaob;
figure
hold on

99

plot(tobs,ypred,'-b');
plot(tobs,yobs,'sb','MarkerFaceColor','b');
plot(tobs,CBu,'--r','LineWidth',1);
plot(tobs,CBl,'--r','LineWidth',1);
plot(tobs,PBu,'-.m','LineWidth',1);
plot(tobs,PBl,'-.m','LineWidth',1);
legend('ypred','yobs','CB','','PB','','location','best')
xlabel 'Time (d)'
ylabel 'Cumulative Biogas Production (L biogas/kg initial VS)'
%% residual scatter plot
figure
hold on
n=length(tobs);
plot(tobs(:,1), resids(1:n), 'sb','Markerfacecolor', 'b')
YLine = [0 0];
XLine = [0 60];
plot (XLine, YLine,'R');
ylabel('Observed M - Predicted M','fontsize',14,'fontweight','bold')
xlabel('Time (d)','fontsize',14,'fontweight','bold')
legend('Residuals','location','best')
%% residual histogram
figure
normhist(resids);
[n1, xout] = hist(resids,10);
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
bar(xout, n1)
xlabel('Observed y/\sigma - Predicted y/\sigma','fontsize',16,'fontweight','bold')
ylabel('Frequency','fontsize',16,'fontweight','bold')
%% prior information
b_old=beta0';
p=length(b_old);
sig=25;
sig=sig*ones(n,1);
tol=5e-4;
ratio = 1;
d=0.001;
count=1;
%% start sequential estimation
while ratio>tol
b= b_old;

100

ypred=Gompertz_FOR(b,tobs);
e=yobs-ypred;
for i=1:length(b)
bin=b;
bin(i)=b(i)*(1+d);
yhat{i}=Gompertz_FOR(bin,tobs);
XX{i}=(yhat{i}-ypred)/(b(i)*d);
if i==1
X=XX{i};
else
X=[X XX{:,i}];
end
end

P=10*[b_old(1)^2 0 0; 0 b_old(2)^2 0; 0 0 b_old(3)^2];
B=b_old';
for ii=1:n;
A=P*X(ii,:)';
Delta=sig(ii)^2+X(ii,:)*A;
K=A/Delta;
b=b+K*(e(ii)-X(ii,:)*(b-b_old));
P=P-K*A';
B=[B;b'];
if ii==1
PP=[P(1,1) P(1,2) P(2,2)];
else
PP=[PP; P(1,1) P(1,2) P(2,2)];
end
end
b_new=b;
ratio=max(abs((b_new-b_old)./b_old));
b_old=b_new;
count=count+1;
end
BB=B(2:end,:);
%% Compute final sensitivity matrix
b= b_old;
ypred=Gompertz_FOR(b,tobs);
e=yobs-ypred;
for i=1:length(b)
bin=b;
bin(i)=b(i)*(1+d);

101

yhat{i}=Gompertz_FOR(bin,tobs);
XX{i}=(yhat{i}-ypred)/(b(i)*d);
if i==1
X=XX{i};
else
X=[X XX{:,i}];
end
end
%% results
b_new
sigma=sqrt(diag(P))
relerr=sigma./b_new
mse=e'*e/(n-p);
rmse=sqrt(mse)
%% sequential plots
figure
hold on
plot(tobs,BB(:,1),'sg','markerfacecolor','b')
plot(tobs,BB(:,2),'ob','markerfacecolor','r')
plot(tobs,BB(:,3),'oc','markerfacecolor','g')
xlabel('Cumulative Biogas Production (L biogas/kg initial VS)')
ylabel('Parameter')
grid on
%% sequential normalized plots
BBn=BB(:,1)./BB(end,1);
BBn(:,2)=BB(:,2)./BB(end,2);
BBn(:,3)=BB(:,3)./BB(end,3);
figure
plot(tobs,BBn(:,1),'-g', 'linewidth',1.8)
hold on
plot(tobs,BBn(:,2),'-b','linewidth',1.8)
plot(tobs,BBn(:,3),'-c','linewidth',1.8)
xlabel('Time (d)')
ylabel('Normalized Parameter')
legend('P','R_m','\lambda', 'location', 'best')
grid on
%% Bootstrapping
%% nlinfit returns beta, residuals, Jacobian (sensitivity coefficient matrix),
%covariance matrix, and mean square error
t=tobs;
[beta,resids,J,COVB,mse] = nlinfit(t,yobs,@Gompertz_FOR,beta0);
rmse=sqrt(mse);

102

%% R is the correlation matrix for the betaeters, sigma is the standard deviation vector
[R,sigma]=corrcov(COVB);
%% asymptotic confidence intervals for beta
ci95=nlparci(beta,resids,J);
ci90=nlparci(beta,resids,J, 0.1);
%% nonlinear regression confidence intervals-- 'on' means simultaneous
[ypred, delta] = nlpredci('Gompertz_FOR',t,beta,resids,J,0.05,'on','curve');
[ypred, deltaob] =nlpredci('Gompertz_FOR',t,beta,resids,J,0.05,'on','observation');
%% simultaneous confidence bands for regression line
CBu=ypred+delta;
CBl=ypred-delta;
%% simultaneous prediction bands for regression line
PBu=ypred+deltaob;
PBl=ypred-deltaob;
%% bootstrap CI for beta
nboot=1000;
betab(1,:)=beta;
ypredb(1,:)=ypred;
mm=2;
for j=2:nboot
r=round(1 + (n-1).*rand(n,1));
for i=1:n
if mm==1
tt(i)=t(r(i));
yboot(i)=yobs(r(i));
end
if mm==2
tt=t;
yboot(i)=ypred(i)+resids(r(i));
if i==n
yboot=yboot';
end
end
end
[betab(j,:),rr(j,:),J2,COVB2,mse2]= nlinfit(tt,yboot,'Gompertz_FOR',beta0);
ypredb(j,:)=Gompertz_FOR(betab(j,:),t);
clear yboot
end
r2=rr(1,:)';

103

for j=2:nboot
r2=[r2; rr(j,:)'];
end
bsort=sort(betab,1); ysort=sort(ypredb,1);
L=round(0.025*nboot);
if L==0; L=1; end
U=round(0.975*nboot);
cib(1,1)=bsort(L,1); cib(1,2)=bsort(U,1);
cib(2,1)=bsort(L,2); cib(2,2)=bsort(U,2);
for i=1:n
ybci(i,1)=ysort(L,i); ybci(i,2)=ysort(U,i);
end
%% compute bootstrap prediction bands
D=rmse*tinv(.975,n-p);
CIwb(:,1)=ybci(:,1)-ypred; CIwb(:,2)=ypred-ybci(:,2);
PIwb(:,1)=sqrt(CIwb(:,1).^2+D^2); PIwb(:,2)=sqrt(CIwb(:,2).^2+D^2);
PIb(:,1)=ypred+PIwb(:,1); PIb(:,2)=ypred-PIwb(:,2);
%% residual histogram for bootstrap residuals
[n1, xout] = hist(r2,6);
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
bar(xout, n1)
xlabel('Observed M-Predicted M','fontsize',16,'fontweight','bold')
ylabel('Frequency','fontsize',16,'fontweight','bold')
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
L4 = ['Time (d)'];
xlabel(L4,'fontsize',16,'fontweight','bold');
ylabel('Cumulative Biogas Production (L/kg initial VS)','fontsize',16,'fontweight','bold');
h1(1)=plot(t,yobs,'square', 'Markerfacecolor', 'b');
h1(2) = plot(t,ypred,'-','LineWidth',1);
h1(3) = plot(t,CBu,'--r','LineWidth',1);
plot(t,CBl,'--r','LineWidth',1);
%% plot prediction band for regression line
h1(4) = plot(t,PBu,'-.m','LineWidth',1);
plot(t,PBl,'-.m','LineWidth',1);
%% plot bootstrap bands
h1(5) = plot(t,ybci(:,1),'--k','LineWidth',1);
plot(t,ybci(:,2),'--k','LineWidth',1);
h1(6) = plot(t,PIb(:,1),'-g','LineWidth',1);

104

plot(t,PIb(:,2),'-g','LineWidth',1);
legend(h1,'Biogasobs','Biogaspred','asyCB','asyPB','bootCB','bootPB','location','best')
meanres=mean(resids);
%% residual scatter plot
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
plot(t, resids, 'square', 'Markerfacecolor', 'b')
plot([0,max(t)],[0,0], 'R')
ylabel('Observed M-Predicted M','fontsize',16,'fontweight','bold')
xlabel('Time (d)','fontsize',16,'fontweight','bold')
%% residual histogram
[n1, xout] = hist(resids,6);
figure
hold on
set(gca, 'fontsize',14,'fontweight','bold');
bar(xout, n1)
xlabel('Observed M-Predicted M','fontsize',16,'fontweight','bold')
ylabel('Frequency','fontsize',16,'fontweight','bold')

105

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