vvEPA
United States
Environmental Protection
Agency
EPA/600/R-17/207 | June 2017 | www.epa.gov/research
Environmental Life Cycle Assessment
and Cost Analysis of Bath, NY
Wastewater Treatment Plant:
Potential Upgrade Implications
Office of Research and Development
Washington, D.C.
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SEPA
United States
Environmental Protection
Agency
Environmental Life Cycle Assessment
and Cost Analysis of Bath, NY
Wastewater Treatment Plant:
Potential Upgrade Implications
Ben Morelli and Sarah Cashman
Eastern Research Group, Inc.
110 Hartwell Ave
Lexington, MA 02421
Prepared for:
Cissy Ma, Jay Garland, Diana Bless, Jennifer Cashdollar
U.S. Environmental Protection Agency
National Exposure Research Laboratory
National Risk Management Research Laboratory
Office of Research and Development
26 W. Martin Luther King Drive
Cincinnati, OH 45268
June 21, 2017
EPA Contract No. EP-C-12-021
Work Assignment 3-41
and
EPA Contract No. EP-C-16-0015
Task Order 0003
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This U.S. Environmental Protection Agency (U.S. EPA) report was developed under Contract
Nos. EP-C-12-021 and EP-C-16-015 awarded by the U.S. EPA. This document has been
reviewed in accordance with U.S. EPA policy and approved for publication. Any mention of
trade names or commercial products does not constitute endorsement or recommendation for use.
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ACKNOWLEDGEMENTS
This research was part of the U.S. Environmental Protection Agency (U.S. EPA) Office
of Research and Development's Safe and Sustainable Water Resources (SSWR) Program. The
research was supported by U.S. EPA contracts EP-C-12-021 and EP-C-16-0015. Kim Miller and
Guy Hallgren provided primary data on the Bath, NY wastewater treatment plant operations and
infrastructure for both the legacy and upgraded systems investigated. Engineering design of
treatment plant upgrades was performed by personnel from Conestoga-Rovers & Associates,
now a division of GHD Inc. Lauren Fillmore and Lori Stone of Water Environment & Reuse
Foundation (WE&RF) as well as Pradeep Jangbari of New York State Department of
Environmental Conservation provided technical review comments. Jason Turgeon and Michael
Nye of U.S. EPA helped develop the initial project scope. Janet Mosely and Jessica Gray of
Eastern Research Group provided technical input and review of the life cycle inventory and cost
analysis.
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Abstract
ABSTRACT
Many municipalities are facing the call to increase nutrient removal performance of their
wastewater treatment plants to limit the impacts of eutrophication on waterbodies receiving the
treated effluent. The associated upgrades often demand investment in new technologies and
increases in energy and chemical use, which create the potential for environmental trade-offs.
The main goal of this study is to quantify these trade-offs for a case study community from an
environmental and cost perspective by performing a life cycle assessment and cost analysis. The
impacts of a conventional activated sludge treatment process are compared against an upgraded
system incorporating chemically enhanced primary settling, Modified Ludzack-Ettinger
secondary treatment, and anaerobic digestion (AD). The sensitivity analysis explores the effect
of composting emission assumptions, AD operational performance, and the use of excess AD
capacity for the processing of high strength organic waste on environmental impact and cost per
cubic meter of wastewater treated.
Results show that eutrophication potential impacts decrease by approximately 40 percent
following treatment plant upgrades, and that this reduction remains relatively consistent within
the sensitivity analysis. Most other impact categories register an increase in impact results of
between 5 and 31 percent with the plant upgrades under base case scenario assumptions. The
water use category shows an environmental benefit of switching to the upgraded system in all
study scenarios, and receives environmental credits in this category from wastewater reuse and
avoided fertilizer production from land application of biosolids. Impact results in the remaining
categories such as global warming potential and cumulative energy demand are strongly affected
by AD and composting emission scenarios. High operational performance of the AD in
combination with acceptance of high strength organic waste produces reductions in
environmental impact relative to the legacy wastewater treatment system and even net
environment benefits. These environmental benefits are attributable to the avoided burdens of
grid electricity and natural gas production from recovered AD biogas. Additional benefits are
realized as a result of avoided fertilizer production, attributable to land application of composted
biosolids. Achievement of net environmental benefits by the upgraded treatment plant are
possible for 7 of 8 assessed impact categories. Eutrophication potential is the sole exception
where impact results remain positive, although eutrophication potential is still reduced in respect
to the legacy system. For global warming potential, the realization of benefits is dependent on
the performance of the composting system. In a worst-case scenario, the acceptance of additional
feedstock for AD can lead to a near 200 percent increase in global warming potential impact if
paired with a poorly managed windrow composting system, emphasizing the importance of
selecting the appropriate composting system with proper system maintenance.
Life cycle costs were calculated for the upgraded system, which was found to have a net
present value of 37.1 million dollars under the base cost scenario. Several cost scenarios were
explored in this study, with assumptions regarding discount rate having a significant effect on
project net present value. Whether the AD unit process additions could generate annual revenue,
and thus a reasonable payback period, was found to depend on AD performance and the
feedstock scenario. Holding cost and AD performance assumptions constant, the AD is shown to
reduce project net present value by approximately 13 percent relative to the base case when the
full capacity of the AD unit is made available for the processing of high strength waste.
l
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Abstract
The results show that improvements in environmental performance are available to
communities that undertake a similar approach to treatment plant upgrades. Improved
environmental performance is largely due to the inclusion of AD, and the avoided electricity and
heat production that is a result of energy recovery from biogas. This study revealed that plant
level impact results are sensitive to AD operational performance and greenhouse gas emissions
associated with composting, indicating the importance of sound management of these unit
processes if improvements are to be realized across environmental impact categories.
11
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List of Acronyms
LIST OF ACRONYMS
A
Current, amps
AD
Anaerobic digester
ASP
Aerated Static Pile
BEAM
Biosolids Emissions Assessment Model
BEGWS
Bath Electric, Gas & Water Systems
BFP
Belt filter press
BNR
Biological nutrient removal
BOD
Biological oxygen demand
CAS
Conventional activated sludge
cBOD
Carbonaceous biological oxygen demand
CHP
Combined heat and power
C:N
Carbon to nitrogen ratio
COD
Chemical oxygen demand
EOL
End-of-life
EPA
Environmental Protection Agency (U.S.)
ERG
Eastern Research Group, Inc.
GBT
Gravity belt thickener
GHG
Greenhouse gas
GPD
Gallons per day
HP
Horsepower
IPCC
Intergovernmental Panel on Climate Change
ISO
International Standardization Organization
LCA
Life cycle assessment
LCCA
Life cycle cost analysis
LCI
Life cycle inventory
LCIA
Life cycle impact assessment
MCF
Methane correction factor
MGD
Million gallons per day
MLE
Modified Ludzack-Ettinger
N
Nitrogen
NMVOC
Non-methane volatile organic compounds
NPV
Net present value
NYDEC
New York Department of Environmental Conservation
P
Phosphorus
PAC
Polyaluminum chloride
QAPP
Quality Assurance Project Plan
RAS
Return activated sludge
RDT
Rotary drum thickener
SCP
Screen compaction press
SPDES
State pollution discharge elimination system
TKN
Total Kjeldahl nitrogen
TN
Total nitrogen
TP
Total phosphorus
TRACI
Tool for the Reduction and Assessment of Chemical and Environmental Impacts
TSS
Total suspended solids
111
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US LCI
V
VFA
VS
WAS
WWT
WWTP
List of Acronyms
United States Life Cycle Inventory Database
Voltage
Volatile fatty acids
Volatile solids
Waste activated sludge
Wastewater treatment
Wastewater treatment plant
IV
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Table of Content
TABLE OF CONTENTS
Page
1. Introduction and Study Goal 1-1
2. Study Scope 2-1
2.1 Functional Unit 2-1
2.2 System Definition and Boundaries 2-1
2.3 Study Site Description 2-3
2.3.1 Legacy WWTP: Conventional Activated Sludge 2-5
2.3.2 Upgraded WWTP: Chemically Enhanced Primary
Clarification with MLE 2-7
2.4 Background LCI Databases 2-10
2.5 Metrics and Life Cycle Impact Assessment (LCIA) Scope 2-10
3. LCA Methodology 3-1
3.1 Water Quality and Organic Feedstock Characteristics 3-1
3.2 Legacy WWTP 3-5
3.2.1 Screening and Grit Removal 3-6
3.2.2 Primary Clarifier 3-6
3.2.3 Aeration Tanks and Secondary Clarification 3-7
3.2.4 Sludge Thickening 3-7
3.2.5 Aerobic Digestion 3-8
3.2.6 Belt Filter Press 3-8
3.2.7 Sludge Landfilling 3-9
3.2.8 Effluent Release 3-11
3.3 Upgraded WWTP 3-11
3.3.1 Sludge Receiving and Holding 3-12
3.3.2 Chemically Enhanced Primary Clarification 3-13
3.3.3 Primary Effluent Wet Well 3-13
3.3.4 Anoxic and Swing Tank 3-14
3.3.5 Aeration and Secondary Clarification 3-14
3.3.6 Belt Filter Press 3-15
3.3.7 Gravity Belt Thickening 3-16
3.3.8 Blend Tank 3-16
3.3.9 Anaerobic Digestion 3-17
3.3.10 Composting 3-22
3.3.11 Land Application of Composted Biosolids 3-25
3.3.12 Effluent Release 3-27
3.4 LCI Limitations & Data Quality 3-27
4. LCCA Methodology 4-1
4.1 LCCA Data Sources 4-1
4.2 Unit Process Costs 4-1
4.2.1 Collection System 4-1
4.2.2 Chemically Enhanced Primary Clarification 4-1
v
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Table of Contents
TABLE OF CONTENTS (Continued)
Page
4.2.3 Anoxic-Swing Tank 4-1
4.2.4 Aeration Basins 4-2
4.2.5 Sludge Receiving and Holding 4-2
4.2.6 Gravity Belt Thickening 4-2
4.2.7 Blend Tank 4-2
4.2.8 Belt Filter Press 4-2
4.2.9 Anaerobic Digestion 4-2
4.2.10 Combined Heat and Power 4-3
4.2.11 Composting 4-3
4.3 LCCA Methods 4-3
4.3.1 Total Capital Costs 4-3
4.3.2 Purchased Equipment Costs 4-4
4.3.3 Direct Costs 4-4
4.3.4 Indirect Costs 4-5
4.3.5 Total Annual Costs 4-6
4.3.6 Net Present Value 4-7
4.3.7 LCCA Cost Assumption Scenarios 4-8
5. LCA and LCCA Results by Treatment Stage 5-1
5.1 Guide to Results Interpretation 5-1
5.2 Eutrophication Potential 5-3
5.3 Cumulative Energy Demand 5-4
5.4 Global Warming Potential 5-6
5.5 Acidification Potential 5-7
5.6 Fossil Depletion Potential 5-8
5.7 Smog Formation Potential 5-9
5.8 Particulate Matter Formation Potential 5-10
5.9 Water Use 5-11
5.10 LCCA 5-12
6. Scenario Sensitivity Analysis 6-1
6.1 Landfill and Compost Emission Scenarios 6-1
6.2 Feedstock, AD, and End-of-Life Scenario Sensitivity 6-4
6.3 Bulking Material Amendment Sensitivity 6-12
6.4 Narrative Impact Scenario 6-13
6.5 LCCA Cost Scenarios 6-16
7. Conclusions 7-1
8. References 8-1
Appendix A: Detailed LCI Calculations and Background Information
VI
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List of Tables
LIST OF TABLES
Page
Table 2-1. Bath Electrical Grid Mix 2-2
Table 2-2. Bath NY Permitted Effluent Quality Standards 2-5
Table 2-3. Typical Biogas Composition for Residential Waste 2-8
Table 2-4. Environmental Impact and Cost Metrics 2-10
Table 2-5. Description of LCA Impact Categories 2-11
Table 2-6. Assignment of Unit Processes to Treatment Stage for Results Presentation 2-12
Table 2-7. Process Categories for Results Presentation 2-13
Table 3-1. Average Influent Composition of Bath, NY Wastewater Treatment Plant 3-1
Table 3-2. Effluent Composition of Two Bath, NY Wastewater Treatment Configurations 3-3
Table 3-3. Waste Characteristics of AD Feedstock 3-4
Table 3-4. Screening and Grit Removal - Annual Equipment Electricity Use 3-6
Table 3-5. Clarifier - Annual Equipment Electricity Use 3-6
Table 3-6. Aeration Tanks - Annual Equipment Electricity Use 3-7
Table 3-7. Sludge Thickening - Annual Equipment Electricity Use 3-7
Table 3-8. Aerobic Digester - Annual Equipment Electricity Use 3-8
Table 3-9. Belt Filter Press - Annual Equipment Electricity Use 3-8
Table 3-10. Methane Emission Calculation Parameters for the Low, Base, and High
Emission Scenarios 3-9
Table 3-11. Methane Capture Performance of Bath and National Average Landfills 3-10
Table 3-12. N2O Emission Rates During Active Landfilling 3-11
Table 3-13. Landfill N2O Emission Factors per Cubic Meter of Wastewater 3-11
Table 3-14. Sludge Receiving and Holding - Annual Equipment Electricity Use 3-12
Table 3-15. Transport Calculations for Incoming High Strength Organic Waste and
Septage 3-12
Table 3-16. Enhanced Primary Clarification - Annual Equipment Electricity Use 3-13
Table 3-17. Primary Effluent Wet Well - Annual Equipment Electricity Use 3-13
Table 3-18. Anoxic and Swing Tank - Annual Equipment Electricity Use 3-14
Table 3-19. Aeration and Secondary Clarification - Annual Equipment Electricity Use 3-14
vii
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List of Tables
LIST OF TABLES (Continued)
Page
Table 3-20. Belt Filter Press - Annual Equipment Electricity Use 3-15
Table 3-21. Polymer Additions forthe BFP by Feedstock and AD Scenario 3-16
Table 3-22. Gravity Belt Thickener - Annual Equipment Electricity Use 3-16
Table 3-23. Blend Tank - Annual Equipment Electricity Use 3-17
Table 3-24. Anaerobic Digestion - Annual Equipment Electricity Use 3-17
Table 3-25. Feedstock Scenarios for AD Sensitivity Scenarios (prior to dewatering) 3-17
Table 3-26. Operational Parameters for AD Sensitivity 3-19
Table 3-27. Biogas Yield for AD Sensitivity (ft3 biogas/ lb VS destroyed) 3-20
Table 3-28. Biogas Production by Feedstock and AD Scenario 3-20
Table 3-29. Electricity Production from Biogas by Feedstock and AD Scenario 3-21
Table 3-30. Potential Heat Production from Biogas by Feedstock and AD Scenario 3-21
Table 3-31. Modeled Avoided Heat from Natural Gas by Feedstock and AD Scenario 3-21
Table 3-32. Required Heat from Natural Gas by Feedstock and AD Scenario 3-21
Table 3-33. Methane Losses from Digester by Feedstock and AD Scenario 3-22
Table 3-34. Methane Losses from CHP by Feedstock and AD Scenario 3-22
Table 3-35. Composting Supplemental Feedstock Characteristics 3-22
Table 3-36. Organic Compost Additions by Feedstock-AD Scenario (Metric Tons/Year) 3-23
Table 3-37. Low, Medium, and High Estimates of Potential Composting Emissions for
the Base Feedstock-Base AD Scenario 3-24
Table 3-38. Compost Emission Study Description 3-25
Table 3-39. Physical Characteristics of Finished Compost, Base Feedstock-Base AD
Scenario 3-25
Table 3-40. Emission Rates at National Average Application Rate 3-26
Table 3-41. Effluent Release - Annual Equipment Electricity Use 3-27
Table 4-1. Direct Cost Factors 4-5
Table 4-2. Indirect Cost Factors 4-6
Table 4-3. Parameter Values Varied in the Low, Base, and High Cost Scenarios 4-9
Table 6-1. Percent Change in Impacts between the Upgraded and Legacy WWTPs1 6-10
Vlll
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List of Tables
LIST OF TABLES (Continued)
Page
Table 6-2. Annual LCIA Results by Feedstock, AD, and Emissions' Scenarios 6-11
Table 6-3. Summary Table of Calculated Payback Period for Anaerobic Digester and
Composting Facilities (in years) 6-16
IX
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List of Figures
LIST OF FIGURES
Page
Figure 2-1. General system diagram for both legacy and proposed upgraded systems 2-3
Figure 2-2. Regional map of Bath, NY and discharge location 2-4
Figure 2-3. Legacy, CAS treatment system diagram 2-6
Figure 2-4. Upgraded WWTP, enhanced primary clarification, MLE and AD system
diagram 2-9
Figure 5-1. Eutrophication potential results by treatment stage 5-3
Figure 5-2. Eutrophication potential results by process category 5-4
Figure 5-3. Cumulative energy demand results by treatment stage 5-5
Figure 5-4. Cumulative energy demand results by process category 5-5
Figure 5-5. Global warming potential results by treatment stage 5-6
Figure 5-6. Global warming potential results by process category 5-7
Figure 5-7. Acidification potential results by treatment stage 5-8
Figure 5-8. Fossil depletion potential results by treatment stage 5-9
Figure 5-9. Smog formation potential results by treatment stage 5-10
Figure 5-10. Particulate matter formation potential results by treatment stage 5-11
Figure 5-11. Water use results by treatment stage 5-12
Figure 5-12. Base life cycle costs by cost category for upgraded WWTP 5-13
Figure 6-1. Life cycle global warming potential end-of-life emission scenario results 6-3
Figure 6-2. Effect of feedstock and anaerobic digestion sensitivity scenarios on
eutrophication potential results 6-5
Figure 6-3. Effect of feedstock and anaerobic digestion sensitivity scenarios on
cumulative energy demand results 6-6
Figure 6-4. Effect of feedstock and anaerobic digestion sensitivity scenarios on global
warming potential results 6-7
Figure 6-5. Effect of feedstock and anaerobic digestion sensitivity scenarios on
particulate matter formation potential results 6-8
Figure 6-6. Effect of feedstock and anaerobic digestion sensitivity scenarios on water use
results 6-9
Figure 6-7. Effect of compost amendment on life cycle global warming potential results
for Low, Base, and High end-of-life emissions scenarios 6-13
x
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List of Figures
LIST OF FIGURES (Continued)
Page
Figure 6-8. Narrative environmental impacts of an upgraded wastewater treatment plant 6-15
Figure 6-9. Life cycle cost assessment summary showing results for each Feedstock-AD
Scenario by cost scenario 6-17
XI
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1—Introduction and Study Goal
1. Introduction and Study Goal
The impacts of eutrophication and pollutants on waterbodies in the United States has
been a driving factor in the movement towards enhanced effluent quality standards leading to
more stringent permitting of municipal wastewater treatment systems. At the same time,
municipalities are faced with pressure to minimize the increases in capital and operational
expenditures associated with wastewater treatment. As understandings of the environmental and
financial resources at stake in this process have been increased, the U.S. Environmental
Protection Agency (U.S. EPA) is looked to by municipalities for guidance on how best to meet a
set of goals that often seem at odds. Communities and experts have rightly pointed out the
potential trade-offs in environmental impact associated with increased standards for nutrient
removal as nutrient load reductions are achieved often at the expense of increases in energy use,
chemical inputs, and system costs.
The objective of this project is to help the community of Bath New York (hereafter
referred to as "Bath") work through these considerations by quantifying the system-wide
environmental impacts and monetary costs associated between the legacy and upgraded
wastewater treatment plants (WWTP). This work will serve as a case study to provide guidance
to other communities as they approach similar questions regarding process upgrades and system
analyses.
Bath Electric, Gas, & Water Systems (BEGWS), uniquely having electricity, gas and
water services under one utility entity, has implemented a system upgrade for enhanced nutrient
removal by way of a Modified Ludzack-Ettinger (MLE) biological treatment step to reach a
summer time permit limit of 3.6 mg/L ammonia nitrogen. BEGWS staff is considering the
installation of a chemically enhanced primary clarification unit. Both completed and planned
improvements are made in part through the construction of new units as well as through the
repurposing of existing infrastructure. This approach to upgrades is common among
municipalities looking to improve and retrofit their existing municipal wastewater process.
BEGWS staff is also considering the implementation of anaerobic digestion (AD) and biosolids
composting to improve solids handling, while creating an opportunity for resource recovery. This
system will be referred to collectively throughout the report as the "upgraded WWTP" or
"upgraded system." This system replaces the conventional activated sludge (CAS) treatment
process that was in place prior to 2016, and includes upgrades such as the recently installed MLE
treatment process and the treatment steps of AD and composting.
System upgrades look not only to improve plant operations, expand services available to
the region for hauled-in waste, and potentially reduce environmental impact, but also eventually
to transform the WWTP into a resource recovery hub for the community. AD produces useful
biogas for energy recovery, and in combination with composting helps to stabilize biosolids,
providing a beneficial amendment for agricultural fields to reduce chemical fertilizer production
and use.
Pursuit of the upgrades outlined above involve economic, environmental, and social costs
and benefits, which aim to address issues at the center of the sustainability debate. The balance
of economic and environmental costs and benefits can be assessed using holistic approaches such
as life cycle assessment (LCA) and life cycle cost analysis (LCCA). LCAs is a widely-accepted
technique to assess the environmental aspects and potential impacts associated with products,
1-1
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1—Introduction and Study Goal
processes, or services. It provides a "cradle-to-grave" analysis of environmental impacts and
benefits that can better inform and assist in selecting the most environmentally preferable choice
among various options. The steps for conducting an LCA include (1) identifying goal and scope,
(2) compiling a life cycle inventory (LCI) of relevant energy and material inputs and
environmental releases, (3) evaluating the potential environmental impacts associated with
identified inputs and releases, and (4) interpreting the results to help make a more informed
decision.
LCCA is a complementary process to LCA for evaluating the total economic costs of an
asset by analyzing initial costs and discounted future expenditures over the life cycle of an asset
(Varnier 2004). It is used to evaluate differences in cost and the timing of costs between
alternative projects.
This study prepares a cost estimate for the upgraded treatment plant and compares
environmental impacts associated with Bath's legacy CAS system and the upgraded treatment
plant. Bath's CAS system is referred to as the "legacy WWTP" or "legacy system" throughout
this report. Applying holistic approaches such as LCA and LCCA to decision making provides
the opportunity to optimize environmental and cost benefits without unknowingly shifting
burdens between categories of impact. This approach does not eliminate the existence of trade-
offs, but it does facilitate a rational, informed decision-making process. Specifically, the study
addresses the following objectives:
• Calculate the environmental benefits and burdens of CAS wastewater treatment for a
typical small community;
• Quantify the comparative environment benefits and burdens associated with enhanced
nutrient removal for a small community wastewater treatment facility, processing 1
million gallons per day (MGD) of wastewater;
• Determine the energy recovery potential of AD, and evaluate the environmental and
cost benefits of offsetting external electricity and heat generation;
• Evaluate the co-digestion of industrial food wastes for enhanced energy recovery; and
• Determine the life cycle costs associated with the upgraded treatment plant over a 30-
year timespan.
The metrics planned for use in this assessment are cost and a suite of LCA-related impact
categories in addition to the traditional suite of wastewater quality parameters. The life cycle
impact assessment (LCIA) categories cover global warming potential, eutrophication potential,
particulate matter formation potential, smog formation potential, acidification potential, and
fossil depletion potential. Water use and cumulative energy demand are incorporated LCI
categories. The specific impact categories and associated methods considered are introduced in
more detail in Section 2.5.
1-2
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2—Study Scope
2. Study Scope
This study design follows the guidelines for LCA provided by ISO 14044 (ISO 2006).
The following subsections describe the scope of the study based on the treatment system
configurations selected and the functional unit used for comparison, as well as the system
boundaries, LCIA methods, and datasets used in this study.
2.1 Functional Unit
A functional unit provides the basis for comparing results in a LCA. The key
consideration in selecting a functional unit is to ensure the treatment system configurations are
compared on a fair and transparent basis and provide an equivalent end service to the
community. The functional unit for this study is the treatment of one cubic meter of municipal
wastewater with the influent wastewater characteristics shown in Table 3-1. Impact results are
normalized per cubic meter of the 1 MGD permitted flowrate (approximately 1.4 million cubic
meters per year). The quantity of waste treated by the facility varies slightly depending upon the
investigated scenario. The legacy system accepts trucked in septage waste, while the upgraded
treatment plant accepts both septage and industrial high strength organic wastes. The quantities
of accepted septage plus industrial high strength organic waste vary between 8,000 and 24,000
gallons per day (GPD, 0.8 and 2.4 percent of 1 MGD flowrate) depending upon the scenario
considered. The basis of normalization for the functional unit is not varied to account for this,
and instead the additional burdens of treating septage and high strength organic waste are
allocated equally to the permitted 1 MGD flowrate of the facility. Composting amendment is
also processed by the upgraded facility and is treated in the same manner as trucked in organic
wastes. The main results section presents results per cubic meter of wastewater. LCIA results are
also presented on an annual basis for all sensitivity scenarios in Section 6.2.
It is important to note that the composition of effluent resulting from the treatment system
configurations is not part of the definition of the functional unit. Rather the level of performance
in terms of nitrogen and phosphorus effluent concentration is a key differentiator of the two
systems. Differences in effluent composition are captured in the estimation of impacts associated
with effluent discharge for each system. Effluent quality values for the two treatment systems are
presented in Table 3-2.
The AD sensitivity analysis explores the effect of accepting increased quantities of high
strength organic waste to boost volatile solids (VS) available for biogas generation. Composting
of yard waste is included in the AD scenarios, as it is necessary to achieve appropriate moisture
and nutrient balances for the composting process. As such, the quantity of waste treated by the
upgraded system is greater than the legacy system, and it is recommended that the avoided
burdens of alternative pathways for treating this waste be examined in future phases of this
project to achieve the fairest possible comparison.
2.2 System Definition and Boundaries
The boundary for each wastewater treatment system configuration includes all on-site
wastewater and sludge treatment processes necessary to treat the maximum daily flowrate of 1
MGD of municipal wastewater, starting from receiving wastewater influent to the WWTP,
operation of the treatment train, and ending in final discharge of the treated effluent and disposal
2-1
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2—-Study Scope
of sludge in a landfill or through land application after conversion to compost. A general system
diagram for both systems is presented in Figure 2-1.
WWTPs include electricity and chemical use as well as select infrastructure elements.
Concrete, rebar, inter-unit piping, excavation, and sub-grade coarse aggregate are included to
represent plant infrastructure. All included infrastructure components are expected to have a
useful lifespan that extends beyond the 40-year study timeframe, which eliminates the need to
consider material replacement of infrastructure in the environmental analysis. Pumps,
electronics, other in-unit mechanical equipment, engineering services, and end-of life (EOL)
disposal of plant infrastructure are excluded from the system boundary. Other studies have
shown that for activated sludge systems infrastructure and EOL demolition contributions to life
cycle energy demand are low as compared to the operational phase (Emmerson et al. 1995),
which provides justification for the simplified treatment of infrastructure elements. The electrical
grid mix for the Bath region is used in the analysis and is depicted in Table 2-1. Process
greenhouse gas (GHG) emissions resulting from biological treatment, fugitive methane releases
from AD and landfill disposal and agricultural emissions are estimated and included in the
calculation of impacts.
Table 2-1. Bath Electrical Grid Mix
Fuel Source
Electrical Grid Mix
(o/o)1'2
Biomass
3.1%
Wind
1.9%
Solar
0.4%
Hydro
29%
Nuclear
29%
Gas
31%
Coal
5.5%
Total
100%
References:
^.S. EPA 2016
2ISO-NE 2016
Avoided electricity and heat production associated with methane capture and avoided
fertilizer production associated with bio so lids land application are considered, and lead to the
generation of environmental credits, thereby decreasing the environmental impact of treatment
units for which this is applicable. Figure 2-1 shows that production of the constituents that make
up the wastewater such as treated drinking water and human and industrial sources of organic
material are excluded from the system boundary. The environmental impact of generating these
materials is not attributable to wastewater treatment.
2-2
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2—Study Scope
Industrial
Organic
BFP Supernatant
Processing
Electrical and
Mechanical Equipment
EOL Disposal of
Plant Infrastructure
Sewage System
Eneinecnng
Waste
Services
Maintenance
Raw Material
1 -atraction and
Processing
Avoided
Electricity &
Heat
Production
Electricity and
Natural Gas
Generation
Distribution
Avoided
Select
Chemical
Manufacturing
Fertilizer
Infrastructure
Manufacturing
Production
Primary
Biological
Sludge
Anaerobic
Composting1
Land
Treatment
Treatment
Processing
Digestion1
T
T
Application1
Avoided
Drinking
Water
Treatment1
n
Effluent Reuse1 Effluent Release
Landfill-
Upgraded WWTP only 2 Legacy WWTP only
KEY
LCA System
Boundary
Excluded Unit
Process
Wastewater
Treatment Plant
Foreground Unit
Processes
Background
Unit Processes
~ Emissions to Nature
T - Transport
Figure 2-1. General system diagram for both legacy and proposed upgraded systems.
2.3 Study Site Description
This section provides a basic description of the study site, treatment systems considered,
and main unit process options. This description is meant to convey what is included in the
analysis and to provide an overview of the systems analyzed.
The Village of Bath is in the Finger Lakes district of southwestern New York, and has a
population of 5,600. The wastewater treatment facility, operated by BEGWS was originally
constructed in 1935, and underwent significant upgrades in both 1972 and 1993.The WWTP
currently has the capacity to treat 1 MGD of wastewater and this permitted volume remains
consistent for the upgraded system. Analysis of the legacy, CAS system is based on the treatment
process that had been in place since the 1993 upgrades. In 2016, the plant finished renovating the
CAS system into a MLE biological treatment process. The plant discharges effluent into the
nearby Cohocton River, which is part of the Susquehanna River basin that ultimately discharges
into the Chesapeake Bay. A map of the region showing Bath and the discharge location is
included in Figure 2-2.
Bath's position within the Chesapeake Bay watershed is a contributing factor in their
motivation to minimize nutrient loads in their effluent due to the Chesapeake Bay Cleanup
Initiative. A new State Pollutant Discharge Elimination System (SPDES) permit from New York
2-3
-------
2—Study Scope
Department of Environmental Conservation (NYDEC) was issued in 2014 to reflect the
regulatory effort. The Chesapeake is an important ecological, cultural, and economic feature that
has suffered over the years from the effects of upstream development and industry. It is home to
renowned shell fishing beds and provides a point of entry to spawning grounds for several
migratory fish species such as the American Shad (CBF 2016a/b). More stringent requirements
necessary to protect this resource are expected in the future.
Rochester
W YORK
Bath NY
Philadelphia
York
MARYLAN
A ® V
Discharge Point:
Chesapeake Bay
Rockville
Washington
Figure 2-2. Regional map of Bath, NY and discharge location.
BEGWS is exploring the option of chemically enhanced primary settling in combination
with the existing MLE biological treatment system as a means of consistently achieving effluent
quality standards that limit summertime ammonia concentrations to 3.6 mg/L. A list of permitted
effluent quality standards is included in Table 2-2.
2-4
-------
2—-Study Scope
Table 2-2. Bath NY Permitted Effluent Quality Standards
Wastewater
Characteristic1
Value
Units
Flow
1
MGD
cBOD
25
mg/L monthly average
TSS
30
mg/L monthly average
Ammonia N (as NH3)
3.6
mg/L summer
Ammonia N (as NH3)
8.4
mg/L winter
Total Nitrogen
61,000
lb/year2
Phosphorus
1,960
lb/year2
Notes & References:
1 SPDES permit #NY0021431, effective 9/1/2014-8/31/2019
2 No concentration requirement (i.e. mg/L)
The plant is designed primarily to process residential wastewater and hauled-in septage.
The plant has also historically serviced several commercial and industrial customers, and the
acceptance of this waste is reflected in the reported influent quality values. BEGWS is exploring
the option of expanding its receipt of residential septage and high strength organic waste for
processing in the proposed AD, and this option is considered within the sensitivity analysis for
this study.
Detailed descriptions of each treatment system along with separate descriptions of the
AD, composting, and land application unit processes are included in the following sections.
2.3.1 Legacy WWTP: Conventional Activated Sludge
The legacy treatment system is a standard example of CAS treatment as deployed by
many communities around the country. Preliminary treatment consists of a mechanical bar
screen, comminutors, and a grit well. These elements are arrayed around a Parshall Flume, which
is used to monitor the influent flow rate. Wastewater then moves into a two-chambered primary
settling tank for the removal of settleable solids. Solids move on to a gravity thickener, while
wastewater flows to a primary wet well for polyaluminum chloride (PAC) addition prior to being
pumped into a bank of three aeration basins. Aeration and secondary clarification are carried out
in concentric regions of circular tank units with clarification occurring in the interior region. A
return activated sludge (RAS) flow is utilized to seed the aeration basins with the appropriate
microbial biomass. Following clarification, wastewater is discharged to the Cohocton River. No
disinfection step is required at this time. Waste activated sludge (WAS) is separately pumped to
the thickener wet well, where it is combined with primary sludge prior to entering the gravity
thickener. Thickened sludge is sent to a series of four concrete basins for aerobic digestion of
solids. Digested sludge is sent to a belt filter press (BFP) with polymer addition for further
dewatering before it is trucked to a local landfill for disposal (CRA 2015). A simplified depiction
of this treatment process, showing relevant material and energy flows, is included in Figure 2-3.
2-5
-------
2—Study Scope
>4
Wastew aer
influent
Septage
Hauling
imp
Electricity
h:
W
Infrastructure
Primay
Screening S. Grit Clarification
Ran oval
Q *¦ 'to
Grt
KEY:
L
Gra/ity Sludge
Thickener
Beit Fitter Press Filtrate
^ Prvitp
On-site wastewater
treatment plant
processes
Upstream energy
and material inputs
Process Air
Emissions
Figure 2-3. Legacy, CAS treatment system diagram.
Nitrous Oxide
Emissions from
Receiving Stream
Primary Effluent
Wet Well
Aerobe Begins &
Ss: ondarv C la "# iers
tffiuent
Discharge in
R'wer
WAS
Polymer
Transportation
Emissions and Process
iet - :er
Hauiirig aid
Landfilfcng
2-6
-------
2—Study Scope
2.3.2 Upgraded WWTP: Chemically Enhanced Primary Clarification with MLE
The proposed treatment system upgrade is an example of enhanced primary clarification
in combination with a MLE biological treatment process for nitrogen removal, as described later
in this Section (depicted in Figure 2-4). Ferric chloride is added to the wastewater at the influent
pump station prior to entering the chemically enhanced primary clarification tank. Following
primary clarification, a screen compaction press (SCP) is used to remove grit from the primary
sludge before it moves on to a gravity belt thickener (GBT) where solids concentration is
increased to 6 percent. Wastewater flows from primary clarification to a wet well for the addition
of PAC before being pumped to the MLE unit. A pre-anoxic tank is the first stage in the MLE
process and provides for the removal of nitrogen as N2 gas via denazification. A swing tank,
which can be operated either as an aerobic or anaerobic unit can be adjusted to provide either
nitrification or denitrification as dictated by influent wastewater quality and weather related
demands on treatment. The anoxic and swing tank repurpose cells of the existing aerobic digester
with the addition of new mixing units. Water exiting these tanks is pumped into the existing bank
of three aeration basins. Aeration and secondary clarification are carried out in concentric
regions of circular units with clarification occurring in the interior region as in Legacy system.
Separate RAS and nitrate recycle flows are utilized to seed the MLE process with the appropriate
microbes and boost nitrogen removal rates, respectively. Treated effluent is either discharged to
the Cohocton River or is pumped to a local golf course for reuse as irrigation water. The
upgraded plant includes a receiving station for acceptance of high strength organic waste, which
is to be processed in the AD. The remaining cells of the aerobic digester are to be used as a
holding tank for the high strength organic waste. No thickening step is required for the organic
waste feedstocks included in this analysis. The high strength organic waste is combined with
primary and waste activated sludge in a blend tank prior to entering the AD. Digested sludge is
pumped to the BFP, which is used as a final dewatering step with polymer addition prior to
composting. Compost is land applied for use as an agricultural amendment.
2.3.2.1 Anaerobic Digestion
AD is to be used as the main sludge processing step within the upgraded treatment plant,
and is set to replace the aerobic digestion system currently in use. AD uses a methanogenic
process to break down volatile suspended solids contained within the sludge. Biogas is produced
as a result of this degradation process. The biogas is comprised mostly of methane and carbon
dioxide gas. An example of a typical biogas composition is shown in Table 2-3. Feedstocks for
AD include primary solids, WAS, residential septage, and industrial organic wastes such as
animal renderings, cheese whey, and winery waste.
The AD system is an example of conventional two-stage mesophilic digestion, and is
accomplished in cylindrical primary and secondary vessels operated in series. Both units have a
maximum capacity of approximately 300,000 gallons solids/sludge with a diameter of 45 feet
and a 23.5-foot side water depth. The primary vessel runs at a constant temperature of 95°F. The
secondary vessel is unheated and unmixed (CRA 2015). Sludge influent to the ADs is heated to
match the reactor temperature prior to introduction into the primary vessel. Dual membrane
covers are used for gas storage, and a combined heat and power (CHP) system is used to convert
biogas into electricity and heat energy. Heat energy is used to provide process heat for AD and
the on-site control buildings, thereby off-setting natural gas usage. It is assumed that any
2-7
-------
2—Study Scope
additional heat energy is wasted as there are no current plans for the distribution system which
would be required to utilize this energy. Additional on-site uses of excess heat energy such as to
heat wastewater in the colder months or for thermal processing of compost are possibilities,
however no benefits to this effect are quantified in the analysis.
Table 2-3. Typical Biogas Composition for Residential Waste
Bio^is Component
Kxpcclcd Riingc1
Methane (CH4) - dry basis, by volume
60-70%
Carbon Dioxide (CO2) - dry basis, by volume
30-45%
Nitrogen (N2) - dry basis, by volume
0.2-2.5%
Hydrogen (H2) - dry basis, by volume
0-0.5%
Hydrogen Sulfide (H2S) - ppm
200-3500
Water Vapor (H2O) - wet basis, by volume
5.9-15.3%
Notes & References:
1 Reproduced from Wiser et al. 2010
2.3.2.2 Composting
Thickened solids exiting the AD are trucked 0.8 km to a composting facility located
adjacent to the Bath WWTP. An active windrow system is modeled as the composting method in
the baseline scenario, which utilizes locally available sources of yard waste organic material as
bulking agent and to achieve the desired carbon to nitrogen (C:N) ratio. The composting process
is designed to achieve a target moisture content of between 55 and 60 percent. Digested solids
are trucked to the composting site and unloaded into windrows. Additional organic material is
placed next to the digested solids. Material mixing and the necessary water addition are
accomplished using a self-propelled compost windrow turner. A minimum of five turnings are
assumed during the active composting phase with up to two during compost curing. The turnings
should be timed to maintain an average windrow temperature of 55°C for a period of 15 days for
vector control and pathogen reduction (U.S. EPA 1994). Finished compost is screened prior to
the curing stage, and is loaded into transport vehicles via a front-end loader for hauling to the site
of land application. A sensitivity analysis is included that examines the effect on environmental
impacts when an aerated static pile composting system is used in place of the windrow facility.
2.3.2.3 Land Application
Finished compost is assumed to be applied to local agricultural fields as both a soil
amendment and source of essential plant nutrients. A transport distance of 25 km is assumed.
Compost is spread on agricultural fields at typical agronomic rates (U.S. EPA 2013). Avoided
fertilizer production is calculated based on compost application at the specified rates.
2-8
-------
2—Study Scope
WAS
AD arxl BFP supernatant
Polymer
GBT
Filtrate
Fugitive Emissions
Gravity Belt GBT Solids
Composing
Beit Filter Press
Belt Filter PressFiltrate
Hauling aid Land Applicaion
Influent
Pump
Collection
Pumps .
Primay Effluent
Wet Weil
ArioxtTank
WAS
Electricity
Infrastructure
Wcstewaer
Co Sect (on
RAS/Nitrate Recycle
High Strength
Organic Waste
Process GHG Pl;mP
Emissions
influent Pump
Staion ChemicaBy
Enhanced
Primay
Clarification
Process GHG
Emissions
!*—[
1
Receiving
Stalon
Holding
Tank
Aerobe Basins &
Sazondary Cfaifiers
^ flrviranotsivpi
On-site wastewater
treatment plant
processes
Supplemental
Organic Materials
Piocess GHG
Emissions
Transportation
Emissions
Biend
Tank
Tric*=ocf
Upstream energy
and material inputs
Fertilizer
Diesel
Water Reuse
Nitrous Oxide
Emissions from
Receiving Stream
t
Effluent ReCase
Figure 2-4. Upgraded WWTP, enhanced primary clarification, MLE and AD system diagram.
2-9
-------
2—Study Scope
2.4 Background LCI Databases
In addition to the primary data sources described in the preceding sections, several
background LCI databases have been used to provide information on upstream processes such as
electricity inputs, transportation and manufacturing of chemical and material inputs. Ecoinvent
2.2 serves as the basis for most of the upstream infrastructure inputs and chemical and avoided
fertilizer manufacturing (Frischknecht et al. 2005). The U.S. Life Cycle Inventory (U.S. LCI)
database is used to represent the manufacture of some chemical and energy inputs in cases where
applicable U.S. specific processes are available in the database (U.S. LCI 2012). A U.S. EPA
LCI database is also used for electricity and transportation processes, and a number of
infrastructure elements (U.S. EPA 2015a).
2.5 Metrics and Life Cycle Impact Assessment (LCIA) Scope
Table 2-4 summarizes the metrics calculated for each treatment system option, together
with the method and units used to characterize each. The cost of the upgraded system
configuration is estimated using standard approaches for LCCA, with more detail on the costing
methodology provided in Section 4. Most of the LCIA metrics are estimated using the Tool for
the Reduction and Assessment of Chemical and Environmental Impacts (TRACI), version 2.1
(Bare et al. 2003, Bare 2011). TRACI is an LCIA method developed by the U.S. EPA. It
includes a compilation of methods representing current best practice for estimating human health
and ecosystem impacts based on U.S. conditions and emissions information provided by LCI
models. Global warming potential is estimated using the 100-year characterization factors
provided by the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report,
which are the global warming potentials currently used for international reporting (Myhre et al.
2013). In addition to TRACI, the ReCiPe LCIA method is used to characterize water use and
fossil depletion potential (Goedkoop et al. 2009), impacts which are not included in the current
version of TRACI. To provide another perspective on energy, cumulative energy demand
including the energy content of all non-renewable and renewable energy resources extracted
throughout the supply chains associated with each configuration is estimated using a method
adapted from one provided by the Ecoinvent Centre (Ecoinvent Centre 2010). Table 2-5 includes
a description of each impact category.
Table 2-4. Environmental Impact and Cost Metrics
Metric
Method
Unit
Cost
LCCA
USD 2014
Global Warming Potential
TRACI 2.1
kg C02-eq.
Eutrophication Potential
TRACI 2.1
kg N-eq.
Particulate Matter Formation Potential
TRACI 2.1
kg PM25-eq.
Smog Formation Potential
TRACI 2.1
kg 03-eq.
Acidification Potential
TRACI 2.1
kg S02-eq.
Water Use
ReCiPe
m3
Fossil Depletion Potential
ReCiPe
kg oil-eq.
Cumulative Energy Demand
Ecoinvent
MJ-eq.
2-10
-------
2—Study Scope
Table 2-5. Description of LCA Impact Categories
Impact/Inventory
Category
Description
I i nit
Eutrophication
Potential
Eutrophication assesses the potential impacts from excessive
loading of macro-nutrients to the environment and eventual
deposition in waterbodies. Excessive macrophyte growth resulting
from increased nutrient availability can directly affect species
composition or lead to reductions in oxygen availability that harm
aquatic ecosystems. Pollutants covered in this category are
phosphorus and nitrogen based chemical species. The method used
is from TRACI 2.1, which is a general eutrophication method that
characterizes limiting nutrients in both freshwater and marine
environments, phosphorus and nitrogen respectively, and reports a
combined impact result.
kg N eq
Global Warming
Potential
The global warming potential impact category represents the heat
trapping capacity of GHGs over a 100-year time horizon. All
GHGs are characterized as kg CO2 equivalents using the TRACI
2.1 impact assessment method. TRACI GHG characterization
factors align with the IPCC 4th Assessment Report for a 100-year
time horizon.
kg C02 eq
Cumulative Energy
Demand
The cumulative energy demand indicator accounts for the total
usage of non-renewable fuels (natural gas, petroleum, coal, and
nuclear) and renewable fuels (such as biomass and hydro). Energy
is tracked based on the heating value of the fuel utilized from point
of extraction, with all energy values summed together and reported
on a MJ basis.
MJ
Water Use
Water use results are based on the volume of fresh water inputs to
the life cycle of products within the WWTP supply-chain. Water
use is an inventory category, and does not characterize the relative
water stress related to water withdrawals. This category has been
adapted from the water depletion category in the ReCiPe impact
assessment method.
m3
Particulate Matter
Formation Potential
Particulate matter formation results in health impacts such as
effects on breathing and respiratory systems, damage to lung tissue,
cancer, and premature death. Primary pollutants (including PM2.5)
and secondary pollutants (e.g., SOx and NOx) leading to
particulate matter formation are characterized here as kg PM2.5 eq
based on the TRACI 2.1 impact assessment method.
kg PM2.5
eq
2-11
-------
2—Study Scope
Table 2-5. Description of LCA Impact Categories
Impact/Inventory
Category
Description
I i nit
Acidification
Potential
Acidification potential quantifies the acidifying effect of
substances on their environment. Acidification can damage or shift
sensitive plant and animal populations and lead to damaging effects
on human infrastructure (i.e. acid rain) (Norris 2003). Important
emissions leading to terrestrial acidification include SO2, NOx, and
NH3. Results are characterized as kg SO2 eq according to the
TRACI 2.1 impact assessment method.
kg S02 eq
Smog Formation
Potential
Smog formation potential results determine the formation of
reactive substances that cause harm to human respiratory health
and can lead to reduced photosynthesis and vegetative growth
(Norris 2003). Results are characterized here to kg of ozone (O3) eq
according to the TRACI 2.1 impact assessment method. Some key
emissions leading to smog formation potential include CO,
methane (CH4), NOx, non-methane volatile organic compounds
(NMVOCs), and SOx.
kg 03 eq
Fossil Fuel
Depletion
Fossil fuel depletion captures the consumption of fossil fuels,
primarily coal, natural gas, and crude oil. All fuels are normalized
to kg oil eq based on the heating value of the fossil fuel and
according to the ReCiPe impact assessment method.
kg oil eq
LCIA results are grouped according to treatment stage for results presentation in all
LCIA impact categories. Table 2-6 shows the assignment of unit processes to treatment stage
categories for both the legacy and upgraded system. The 'X' indicates that a unit process is
included in the referenced system.
Table 2-6. Assignment of Unit Processes to Treatment Stage for Results Presentation
Treatment Stage
Unit Process Name
Legacy
Svstem
Upgraded
Svstem
Preliminary/Primary
Wastewater collection; operation and
infrastructure
X
X
Preliminary/Primary
Influent pump station
X
Preliminary/Primary
Screening and grit removal
X
Preliminary/Primary
Chemically enhanced primary clarification
X
Preliminary/Primary
Primary clarifier
X
Sludge Handling and Treatment
Screen compaction press
X
Preliminary/Primary
Wet well and sump station
X1
X
Biological Treatment
Pre-anoxic & swing tank
X
Biological Treatment
Aeration tanks
X
X
Sludge Handling and Treatment
Waste receiving and holding
X
Sludge Handling and Treatment
Gravity belt thickener
X
2-12
-------
2—Study Scope
Table 2-6. Assignment of Unit Processes to Treatment Stage for Results Presentation
Treatment Stage
Unit Process Name
Legacy
Svstem
Upgraded
Svstem
Sludge Handling and Treatment
Gravity thickener
X
Sludge Handling and Treatment
Blend tank
X
Sludge Handling and Treatment
Anaerobic digestion
X
Sludge Handling and Treatment
Combined heat and power
X
Sludge Handling and Treatment
Aerobic digester
X
Sludge Handling and Treatment
Belt filter press
X
X
Sludge Handling and Treatment
Biosolids composting
X
Sludge Disposal
Land application of compost
X
Sludge Disposal
Sludge disposal in landfill
X
Effluent Release
Effluent release; to surface water
X
X
Facilities
Control building
X
X
1 Impact results grouped with the primary clarifier for the legacy system
Results are also presented according to process categories for eutrophication potential,
global warming potential, and cumulative energy demand. All unit processes in the LCA model
are assigned to the process categories listed in Table 2-7.
Table 2-7. Process Categories for Results Presentation
Process Categories
Electricity
Natural Gas
Chemicals
Unit Process Emissions
Effluent Release
Transport
Landfill
Composting
Land Application
Avoided Products
Infrastructure
Diesel
2-13
-------
3—LCA Methodology
3. LCA Methodology
This chapter covers the data sources, assumptions, and parameters used to establish the
LCI values used in this study.
3.1 Water Quality and Organic Feedstock Characteristics
The characteristics associated with the influent municipal wastewater are the same for
both the legacy and the upgraded treatment systems (Table 3-1). Wastewater influent to the Bath
treatment facility is mixture of residential sewage and local industrial wastewater generators
including a hospital, leachate treatment facility, and an airport (CRA 2015). Suspended solids
concentrations are higher than those observed for typical domestic wastewater, while biological
oxygen demand (BOD), nitrogen, and phosphorus values all fall within the expected range
(Tchobanoglous et al. 2014). The temperature of influent and effluent wastewater varies between
8 and 20 degrees Centigrade depending upon the season. Influent wastewater characteristics for
this study are set equal to the average observed influent values over the period from October
2011 to November 2015 (BEGWS 2016). Records of influent and effluent wastewater quality
during this period are reported in the Appendix. The reported influent values include loadings
from the permitted commercial and industrial sources which discharge to the Bath sewer system.
Table 3-1. Average Influent Composition of Bath, NY Wastewater Treatment Plant
Clia r iicter istic
Value
Unit
R(.Tcrcncc(s)
Suspended Solids
437
mg/L
BEGWS 2016
Volatile Solids
51
%
calculated
Carbonaceous Biological Oxygen Demand (cBOD)1
279
mg/L
BEGWS 2016
Biological Oxygen Demand
323
mg/L
calculated, Brake
2007
Total Kieldahl Nitrogen (TKN)
56
mg/L N
BEGWS 2016
Ammonia
32
mg/L N
BEGWS 2016
Total Phosphorus (TP)
8
mg/L P
Miller 2016
Nitrite
<1
mg/L N
Cunningham
2016
Nitrate
<1
mg/L N
Cunningham
2016
Organic Nitrogen
29
mg/L N
Miller 2016
Temperature
8-23
°C, seasonal
BEGWS 2016
Notes & References:
1 Assum es BOD/cBOD ratio of 1.16 (Brake 2007)
Effluent characteristics for the two systems are a key differentiating factor in this study.
Effluent values used in this study are reported in Table 3-2 and are presented next to the effluent
criteria values from the SPDES permit for the Bath WWTP. The effluent standards, which
became effective in September 2014, require a treatment system upgrade to be met consistently.
Effluent values for the legacy system are the average of recorded effluent test values over the
period from October 2011 to November 2014 (BEGWS 2016). Expected effluent values for the
3-1
-------
3—LCA Methodology
upgraded treatment system are taken from engineering documents associated with the upgraded
treatment system (CRA 2015).
3-2
-------
3—LCA Methodology
Table 3-2. Effluent Composition of Two Bath, NY Wastewater Treatment Configurations
Cluiriict eristic
Legncy
lipgrsided1
SPDKS
Permit
Shind iii(l?
Unit
Reference (Legacy; Upgraded)
Suspended Solids
7.9
5.0
30
mg/L
BEGWS 2016; CRA2015, fig. 5.4
Biological Oxygen Demand2
8.5
2.3
255
mg/L
BEGWS 2016; CRA2015, fig. 5.4
Total Kjeldahl Nitrogen
16
4.4
n.a.4
mg/L N
BEGWS 2016; CRA2015, fig. 5.4
Ammonia
6.7
3.6
3.6
mg/L NH3
BEGWS 2016; CRA2015, fig. 5.4
Total Phosphorus
0.7
0.6
1,960
lb/yr P
BEGWS 2016; CRA2015, fig. 5.4
Nitrite
2.8
0.8
n.a.4
mg/L N
BEGWS 2016; calculated
Nitrate
13
14
n.a.4
mg/L N
BEGWS 2016; Cunningham 2016
Organic Nitrogen
9
0.8
n.a.4
mg/L N
calculated
Total Nitrogen
31
20
61,000
lb/yr N
BEGWS 2016; CRA2015, fig. 5.4
Notes & References:
1 Upgraded system accepts a quantity of septage and organic waste not covered under current permit
2 Assum es BOD/cBOD ratio of 1.16 (Brake 2007)
3 SPDES 2014
4 n.a. - not applicable
5 Permit is specific to cBODs
3-3
-------
3—LCA Methodology
Characteristics of waste destined for treatment via AD affect both plant operation and
biogas production. Table 3-3 lists basic feedstock characteristics that describe waste as it is
received by the Bath treatment facility, or in the case of primary and WAS, as it exists prior to
thickening or blending. Both residential septic tank and portable toilet waste are treated within
the WWTP alongside municipal sewage waste, which is to say that they are subject to both
primary and secondary treatment. Septic tank and portable toilet waste are referred to
collectively as septage throughout this report. Primary and WAS are collected via primary and
secondary clarification, respectively, and will include solids derived from both forms of septage
waste. The quantity of septage waste is limited to 8,000 GPD in the legacy treatment system. The
quantity of accepted septage waste is limited to 16,000 GPD in the upgraded treatment plant as is
specified in the engineering planning documents (CRA 2015). The loadings associated with
septage waste are considered in both the legacy and upgraded effluent values. Septage is
distinguished from high strength organic waste for the purposes of this study.
The high strength organic wastes considered in this study include slaughterhouse, winery,
and cheese waste. High strength organic wastes skip primary and secondary treatment and are
introduced directly into the AD following blending with thickened primary and waste activated
sludge. The high solids content of these wastes allows them to bypass gravity belt thickening.
This serves several purposes, including maximization of loading to the ADs, which in turn
increases the potential for methane generation. This decision also eliminates a source of
increased pollutant loading to primary and secondary treatment, which would result from the
need to process supernatant from the avoided thickening step. The high strength organic waste
feedstock scenarios analyzed in the sensitivity analysis are presented in Section 1.1 and the
supplemental organic amendments for composting are listed in Section 3.3.
Table 3-3. Waste Characteristics of AD Feedstock
Solids
Volatile
Total N
Total P
Content
Solids (%
(nig
Wiisle Type
(% w/w)
Source
ol I S)
Source
N/L)
Source
P/L)
Source
Waste Activated Sludge
0.5%
1
31%
7
190
2
120
2
Primary Sludge
1.8%
1
68%
7
453
2
127
2
Septic Tank Waste
0.1%
3
57%
3
103
3
14.0
3
Portable Toilet Waste
0.3%
3
43%
3
937
3
67.7
3
Slaughterhouse Waste
13%
4
92%
4
1.50E+3
9
NA
8
Winery Waste
3.7%
5
60%
5
105
5
NA
8
Cheese Waste
7.8%
6
62%
6
1.02E+3
6
300
6
Notes & References:
1 GHD Engineering Service 2015
2 calculated based on T chobanoglous et al. 2014
3 ALS 2015
4 Luste and Luostarinen 2010
5 Bustamante et al. 2005
6 Gelegenis et al. 2007
7 CRA 2015
8 NA - not available
9 Between values reported in Palatsi et al. 2011 and Sindt 2006, nitrate/nitrite assumed negligible (De Guardia et al.
2009)
3-4
-------
3—LCA Methodology
3.2 Legacy WWTP
Data regarding the construction and operation of the legacy system was provided by
BEGWS staff. The system as modeled has been in operation since 1993, leaving a detailed
record of treatment performance over many years. The secondary treatment system was
upgraded to an MLE unit in 2016, replacing the legacy CAS system.
Utility records were provided by BEGWS for electricity, natural gas, and water usage for
the years 2014 and 2015. Electricity usage for units is calculated on the basis of mechanical
equipment horsepower (HP) or recorded voltage (V) and current (A) readings for each piece of
equipment according to Equation 1 and Equation 2. Equation 2, which relies on facility records
of equipment V and A draw, is preferred over Equation 1 when this information is available.
Natural gas is used for building space conditioning, and is not expected to increase as a result of
increasing the flow rate from the current average of 0.67 MGD to the maximum flowrate of 1
MGD, which is used as the basis of this analysis. The energy requirement of treating 8,000 GPD
of septage is included in the numbers prior to scaling and the quantity is expected to remain
constant, meaning that no further adjustments are required. The quantities of chemical inputs
were provided by BEGWS staff, and these values were increased in the LCA model to account
for the increased flow rate of the study system as compared to the current average flow rate.
Values in electricity use tables throughout this section have been rounded to three significant
figures.
Electricity Use (kWh/year) = Unit HP x (0.746 kw/HP) x annual operation (hr/yr)
Equation 1
Electricity Use (kWh/year) = (Amps x Volts)/1000 x annual operation (hr/yr)
Equation 2
System dimensions from construction drawings for the 1968 and 1993 plant upgrades
were used to estimate the included infrastructure components of each unit. Concrete volume,
rebar weight, aggregate weight, piping quantity, and excavation volume comprise the majority of
infrastructure included. Example infrastructure calculations are included in Appendix A. Smaller
infrastructure components such as pumps, valves, pipe elbows, and internal unit piping are
excluded from the analysis. The following units are included in the infrastructure estimate: (1)
parshall flume, (2) primary settling tank, (3) wet well, (4) aeration basins, (5) aerobic digester,
(6) sludge thickener, (7) inter-unit piping, (8) control buildings, and (9) collection system piping.
Process based GHG emissions and those emanating from receiving waters were
calculated based on the methods introduced in the following unit descriptions, and described in
detail in the Appendix A. The following subsections provide the detailed operational LCI
developed for the legacy WWTP by unit process on an annual basis. Annual inputs and outputs
are allocated to the functional unit by dividing annual input and output quantities by the number
of cubic meters of wastewater treated at the plant per year.
3-5
-------
3—LCA Methodology
3.2.1 Screening and Grit Removal
This unit includes the drive motor for the mechanical bar screen and the equipment
involved in grit removal as well as flow sensor and transmitter equipment associated with the
operation of the Parshall flume (Table 3-4). No chemical use is associated with this unit.
Table 3-4. Screening and Grit Removal — Annual Equipment Electricity Use
Equipment
IIP
A
V
Run Time (hr/vr)
Electricity I ise (kWh/yr)
Drive Motor
1.50
2.60
460
8,740
10,400
Grit Feed Pump Motor
5.00
8.10
460
2,900
10,900
Screw Drive Motor
1.00
1.60
460
8,740
6,430
Vacuum Pump
0.50
0.90
115
728
75.3
Air Compressor
0.50
0.90
115
728
75.3
Flow Sensor
0.50
0.90
24.0
8,740
189
Flow Transmitter
0.50
0.90
115
8,740
904
3.2.2 Primary Clarifier
As shown in Table 3-5, the primary clarifier unit process includes the mechanical
equipment required to collect primary sludge. Electricity use for the primary effluent pump and
PAC feed pump are also included in this unit in the LCA results. The primary effluent pump
moves wastewater from the primary clarifier to the aeration basins.
Table 3-5. Clarifier — Annual Equipment Electricity Use
Eq uipment
IIP
A
V
Run lime
(hr/vr)
Electricity Use
(kWh/vr)
Longitudinal Collector 1
0.50
0.90
460
8,740
3,620
Longitudinal Collector 2
0.50
0.90
460
8,740
3,620
Cross Collector Drive
0.50
0.90
460
8,740
3,620
Scum Pump
5.00
8.10
460
728
2,710
Wet Well Level Sensor
0.50
0.90
24.0
8,740
189
Primary Effluent Pump No. 1
20.0
27.5
460
8,740
111,000
Primary Effluent Pump No. 21
20.0
27.5
460
-
-
PAC Feed Pump
1.00
1.60
110
8,740
1,540
Note:
1 Auxiliary pump
It was reported that 114,000 gallons of PAC are used annually. The calculation in
Equation 3 determines the resulting LCI quantity:
PAC (kg/m3) = 114,000 gal/year + 264 gal/m3 x (1.18 (specific gravity) x 1000 kg/m3) +
(1,381,676 m3/yr x 0.67 MGD) | = 0.55 kg/m3
Equation 3
3-6
-------
3—LCA Methodology
3.2.3 Aeration Tanks and Secondary Clarification
A bank of three aeration tanks forms the secondary treatment system, which includes
integrated secondary clarification, and the blowers and mechanical equipment required to run
these units. Electricity use calculations for these aeration tanks and integrated secondary
clarification are provided in Table 3-6. PAC, which aids flocculation in this unit, is added in the
primary effluent wet well, and its impacts are included with the primary clarifier.
Table 3-6. Aeration Tanks — Annual Equipment Electricity Use
Kq uipmenl
IIP
A
V
Run rime
(hr/yr)
Klectricitv Use
(kWh/yr)
Multi-Stage Centrifugal Blower
No. 1
50.0
61.0
460
8,740
245,000
Multi-Stage Centrifugal Blower
No. 2
50.0
61.0
460
8,740
245,000
Multi-Stage Centrifugal Blower
No. 31
50.0
61.0
460
-
-
Clarifier Drive No. 1
0.50
1.00
460
8,740
4,020
Clarifier Drive No. 2
0.50
1.00
460
8,740
4,020
Clarifier Drive No. 3
0.50
1.00
460
8,740
4,020
WAS System
0.50
0.90
110
2,910
288
Note:
1 Auxiliary blower
GHG emissions from the aerobic tanks are calculated based on influent TKN and BOD
concentrations. For a CAS system, it is assumed that 0.035 percent of influent nitrogen is
released as nitrous oxide (Czepiel 1995). Methane emissions from the aeration tanks are
calculated using a theoretical maximum methane generation rate of 0.6 kg CH^kg influent BOD,
which is adjusted downwards using a methane correction factor of 0.005 (Czepiel 1993) as
demonstrated in the Appendix.
3.2.4 Sludge Thickening
The sludge thickening unit process includes electricity requirements for pumping from
the sludge well to the thickener unit and the thickener drive motor (Table 3-7). No chemicals are
used for gravity sludge thickening.
Table 3-7. Sludge Thickening — Annual Equipment Electricity Use
JOq uipment
HP
A
V
Run l ime (hr/yr)
Kledricilv Use (kWh/yr)
Thickener Feed Pump No. 1
7.50
9.50
460
364
1,590
Thickener Feed Pump No.
21
7.50
9.50
460
-
-
Thickener Drive Motor
1.00
1.60
110
8,740
1,540
Note:
1 Auxiliary pump
3-7
-------
3—LCA Methodology
3.2.5 Aerobic Digestion
Aerobic digestion includes electricity use for the operation of two digester feed pumps
and four positive displacement blowers for aeration of the thickened sludge (Table 3-8).
Table 3-8. Aerobic Digester — Annual Equipment Electricity Use
Kq uipment
IIP
A
V
Run rime (lir/vr)
Klectricitv Use
(kWh/yr)
Digester Feed Pump No. 1
3.00
4.40
460
364
737
Digester Feed Pump No. 21
3.00
4.40
460
—
—
Positive Displacement Blower
No. 1
25.0
32.0
460
8,740
129,000
Positive Displacement Blower
No. 2
25.0
32.0
460
8,740
129,000
Positive Displacement Blower
No. 3
25.0
32.0
460
8,740
129,000
Positive Displacement Blower
No. 4
25.0
32.0
460
8,740
129,000
Positive Displacement Blower
No. 51
25.0
32.0
460
__
__
Note:
1 Auxiliary pump and blower
GHG emissions from the aerobic digester are calculated based on influent TKN and BOD
concentrations. It is assumed that 0.035 percent of influent nitrogen is released as nitrous oxide
(Czepiel 1995). Methane emissions from the tanks are calculated using a theoretical maximum
methane generation rate of 0.6 kg CH^kg influent BOD, which is adjusted downwards using a
methane correction factor of 0.005 (Czepiel 1993) as demonstrated in the Appendix.
3.2.6 Belt Filter Press
The BFP includes all equipment required for sludge dewatering. Associated electricity
use calculations for the BFP are presented in Table 3-9.
Table 3-9. Belt Filter Press — Annual Equipment Electricity Use
Run rime
lOlect ricitv Use
Kq uipment
HP
A
V
(hr/yr)
(kWli/vr)
BFP Feed Pump No. 1
5.00
6.60
460
2,080
6,310
BFP Feed Pump No. 2
5.00
6.60
460
-
-
Drum Drive
1.00
1.60
460
2,080
1,530
Belt Drive
1.50
2.80
460
2,080
2,680
Spray Pump
7.50
9.40
460
2,080
8,990
Screw Conveyor Drive
1.00
1.60
460
2,080
1,530
Belt Conveyor Drive
1.00
1.60
460
2,080
1,530
Polymer Feed Pump
1.00
1.60
110
8,740
1,540
3-8
-------
3—LCA Methodology
It is reported that 23,000 gallons of polymer solution are used annually. The following
calculation in Equation 4 was performed to determine the resulting LCI quantity:
polymer (kg/m3) = 23,000 gal/year + 264 gal/m3 x (1.14 (specific gravity) x 1000 kg/m3)
polymer quantity = 0.1 lkg/m3*(0.5/100)
= 5.36E-4 kg/m3
water quantity = 0.11 - 5.36E-4
= 0.107 kg/m3
Equation 4
3.2.7 Sludge LandfiUing
Landfilling of biosolids following aerobic digestion is the EOL approach for the legacy
plant. This can be compared to composting and land application, which is the EOL reuse option
applied to the upgraded system. Preliminary screening of results indicated the importance of
EOL disposal routes, particularly composting, to GHG impacts per cubic meter of wastewater.
Three methane emission scenarios were developed for the landfill emissions sensitivity
analysis using parameters listed in Table 3-10. The method first calculates the fraction of
degradable carbon. A first-order decay equation is used to calculate the portion of degradable
carbon that degrades each year over a 100-year timespan. Fifty percent of carbon that degrades is
assumed to produce methane, with the remainder producing biogenic CO2. Emissions occurring
within the first 3 years are assumed to be released to the atmosphere as it takes time to put a
methane capture system in place. Carbon sequestration is estimated as the fraction of non-
degradable carbon plus the fraction of degradable carbon that does not degrade over the 100-year
time horizon.
Table 3-10. Methane Emission Calculation Parameters for the Low, Base, and High Emission
Scenarios
Parameter
Low Kmission
l&ase Kmission
1 ligli Kmission
Value
Source
Value
Source
Value
Source
Wet Weight of Solids Landfilled Annually
2,636
1
2,636
1
2,636
1
Moisture Content of Biosolids
20
2
20
2
20
2
Dry Weight of Solids
527
calculated
527
calculated
527
calculated
Carbon Content of Dry Solids
39%
3
48%
average
57%
4
Incoming C, Annual (metric tons)
206
calculated
253
calculated
300
calculated
Carbon, % of wet mass
8%
calculated
10%
calculated
11%
calculated
Non-degradable Carbon, % of wet mass
3%
calculated
5%
calculated
6%
calculated
Degradable Organic Carbon, % of wet mass
5%
5
5%
5
5%
5
Fraction of Degradable Carbon Decomposed
50%
3
65%
average
80%
3
Fraction of Degraded Carbon Turning to CH4
50%
3,5
50%
3,5
50%
3,5
Fraction of Methane Oxidized to CO2 in
landfill cover
25%
3
10%
3
3%
3
MCF (methane conversion factor)
1
3,5
1
3,5
1
3,5
K
0.1
3,5
0.175
3,5
0.225
3
Notes & References:
1 Bath Sludge Report to EPA
2 Hydromantis 2014
3 SYLVIS 2011
4 Maulini-Duran 2013
5 RTI 2010
3-9
-------
3—LCA Methodology
Two scenarios were evaluated to determine the impact of methane fate on life cycle
impacts: (1) bath landfill and (2) national average landfill. Table 3-11 shows the methane capture
performance of the landfill scenarios. The Steuben County landfill that services the Town of
Bath was retrofitted with a modern gas capture system in 2010 that is designed to capture 95
percent of methane produced in the facility. Ten percent of the methane released without
treatment is assumed to oxidize to CO2 as it moves upwards through the landfill prior to
emission. Of methane produced in the national average landfill, 28.8 percent is assumed to be
lost to the atmosphere, 3.8 percent is oxidized to CO2 within the landfill, 10.6 percent is flared,
and 56.8 percent is recovered and used for energy production (U.S. EPA 2015b).
Table 3-11. Methane Capture Performance of Bath and National
Average Landfills
Parameter
Bath NY
Land llll
(baseline)
iNiitioiinl
Average
Land llll
Percentage of landfilled C that produces methane
50%
50%
Percentage of methane released w/o treatment
4.5%
29%
Percentage of methane captured for energy recovery
95%
57%
Percentage of methane flared
0%
11%
Percentage of methane oxidized to CO2
0.5%
3.8%
The potential range of nitrous oxide (N2O) emissions that could be expected from
landfilling of sludge was determined through a review of published emission factors. All
estimates of landfill nitrous oxide emissions are in the form of mass N2O emitted per m2 of
landfill area per hour during active landfilling. Only one study was found that deals specifically
with nitrous oxide emissions of landfilled sludge, and this is in the context of daily cover for the
landfill (Borjesson and Svensson 1997).
Low, medium, and high estimates of potential landfill N2O emissions were taken from
the literature (Rinne et al. 2005, Barton and Atwater 2002, Borjesson and Svensson 1997). Table
3-12 shows reasonable, low, medium, and high estimates of N2O emission rates during active
landfilling. The ratio of landfilled waste to landfill area from Rinne et al. 2005 was used to
transform N2O emission rates (mg/m2/hr) into kg N2O emitted per kg of waste landfilled. These
values are used to calculate the N2O emission factors used in the LCI and displayed in Table
3-13. The work of Barton and Atwater indicates that N2O emissions after landfill closure will be
negligible in comparison to the values found for the active phase of the landfill's lifetime. The
base N2O emission factor is equivalent to a 1.65 percent loss of nitrogen content as N2O (Barton
and Atwater 2002), which is like estimates for land application.
Transport requirements were calculated by multiplying the weight of dewatered sludge
by an estimated average transport distance to the landfill of 24 km (15 miles), one way.
3-10
-------
3—LCA Methodology
Table 3-12. N2O Emission Rates During Active Landfilling
Parameter
Value
Unit
Source
Low N2O emission factor during active
landfilling
1.70
mg N20/m2/hr
Borjesson and Svensson
1997
Medium N2O emission factor during active
landfilling
4.20
mg N20/m2/hr
Rinne et al. 2005
High N2O emissions during active landfilling
56.1
mg N20/m2/hr
Borjesson and Svensson
1997
Table 3-13. Landfill N2O Emission Factors per Cubic Meter of Wastewater
Parameter
Value
Units
N2O emission factor, low
4.01E-05
kg N20/m3
N2O emission factor, base
6.14E-04
kg N20/m3
N2O emission factor, high
1.34E-03
kg N20/m3
3.2.8 Effluent Release
Nitrous oxide emissions from receiving streams are calculated based on the IPCC
guideline that 0.005 kg of N2O-N are emitted per kg of nitrogen discharged to the aquatic
environment. Details of that calculation are presented in the Appendix.
3.3 Upgraded WWTP
Data concerning the upgraded wastewater treatment facility was also provided by
BEGWS staff. Most of the original values the study is based upon were generated by GHD
Engineering as part of the facility design process (CRA 2015).
Estimates of unit electricity use are based on the assumed daily flowrate of 1 MGD.
Electricity usage for units is calculated based on mechanical equipment horsepower or recorded
voltage and current readings for each piece of equipment according to Equation 1 and Equation
2, respectively. Equation 2, which relies on facility records of equipment V and A draw, is
preferred over Equation 1 when this information is available. Electricity use of appropriate units
is scaled for the medium and high feedstock scenarios to account for additional solids
processing. Values in electricity use tables throughout this section have been rounded to three
significant figures. Annual estimates of chemical usage for each unit were determined by GHD
Engineering based on the assumed influent wastewater characteristics presented in Table 3-1.
When necessary, chemical use was adjusted upwards to account for the difference between
GHD's assumed average annual flow rate of 0.67 MGD to the maximum daily flowrate of 1
MGD.
The following units are included in the infrastructure estimate for the upgraded system:
(1) chemically enhanced primary clarification, (2) wet well, (3) anoxic and swing tanks, (4)
aeration basins, (5) waste holding and receiving tanks, (6) blend tank, (7) primary and secondary
AD, (8) inter-unit piping, and (9) collection system piping. The chemically enhanced primary
clarification unit, receiving station, and ADs all require new infrastructure. Other units are re-
purposed. Basic dimensions for the enhanced primary settling tank and the waste receiving
3-11
-------
3—LCA Methodology
station were provided by BEGWS staff assuming the same basic construction methods as
employed by all other units for tank walls, slab, rebar, excavation, and foundation gravel.
Infrastructure estimates for the primary and secondary digesters were calculated using
CAPDETWorks™ engineering design and costing software (Hydromantis 2014).
Process based GHG emissions and those emanating from receiving waters were
calculated based on the methods introduced in the following unit descriptions, and described in
detail in the Appendix. The following subsections provide the detailed operational LCI
developed for the upgraded WWTP by unit process on an annual basis. Annual inputs and
outputs are allocated to the functional unit by dividing annual input and output quantities by the
number of cubic meters of wastewater treated per year. Environmental benefits and burdens,
including those generated due to treatment of additional high strength organic waste, are
normalized to the maximum facility flow capacity of 1 MGD.
3.3.1 Sludge Receiving and Holding
Electricity use for the sludge receiving and holding unit process includes the operation of
sludge pumps (2) and (3) and an estimate of aeration energy required for odor control during
sludge holding before blending and introduction into the ADs (Table 3-14). Electricity usage is
scaled up for the medium and high feedstock scenarios to account for additional pumping and
aeration energy requirements based on the additional volume of organic waste accepted at the
receiving station. No chemical use is required for this unit process.
Table 3-14. Sludge Receiving and Holding — Annual Equipment Electricity Use
Kq uipmenl
MP
A
V
Run Time
(hr/vr)
Annual Klectricitv
Use(kWh)
Sludge Pump (2)
7.50
-
-
2,190
12,300
Sludge Pump (3)
7.50
-
-
2,080
11,600
Coarse Bubble Diffused Aeration
25.0
32.0
460
2,920
43,000
Truck transport energy of incoming high strength organic waste is also included in the
analysis and is calculated for each feedstock scenario (Table 3-15). An incoming transport
distance of 25 km is assumed.
Table 3-15. Transport Calculations for Incoming High Strength Organic Waste and
Septage
Feedstock Scenario
Waste Volume (gal)
W aste Mass (metric
ton/yr)
transit (t-km)1
tkm/m*
Base
16,000
22,120
553,000
0.40
Medium
20,000
27,820
695,000
0.50
High
24,000
33,590
840,000
0.61
Note:
1 t-km = metric ton*kilometer
3-12
-------
3—LCA Methodology
3.3.2 Chemically Enhanced Primary Clarification
As illustrated in Table 3-16, electricity use for enhanced primary clarification in the LCA
results included operation of the influent pump, SCP and grit equipment, and the ferric chloride
feed equipment. Electricity requirements for primary clarification remain constant across the
scenarios due to a minimal, less than 0.5 percent, increase in flow rate at the headworks due to
supernatant recycling from the AD and BFP.
Table 3-16. Enhanced Primary Clarification — Annual Equipment Electricity Use
Kquipmcnl
Unit
Qunntilv
Units On
IIP
Run rime
(lir/vr)
Ann Uiil
Klcctricilv I isc
(kWh)
Influent Pumps
2
1
40.0
2,340
69,700
Lift Drives
8
2
5.00
8,760
65,300
Air Scour Blowers
8
3
1.20
8,760
23,500
Backwash Booster
Pump
1
1
5.00
8,760
32,700
Actuator Valves
41
20
0.25
730
2,720
SCP Pumps
2
1
15.0
4,380
49,000
SCP
2
1
3.00
4,380
9,800
Grit Pumps
2
1
15.0
1,460
16,300
Chemical Feed -
FeCl3
2
1
0.10
8,760
653
The reported ferric chloride addition was 30 mg/L of influent wastewater. The following
calculation in Equation 5 was performed to determine the ferric chloride addition used in the
LCI:
FeCl3 addition = 30 mg/L x (1,381,676 m3/yr x 1000 L/m3) 1E6 mg/kg 1,381,676 m3/yr =
41,450 kg/yr 1,381,676 m3/yr |= 0.03 kg FeCh/m3 Wastewater
Equation 5
3.3.3 Primary Effluent Wet Well
As shown in Table 3-17, the primary effluent wet well includes pumping energy required
to move wastewater from primary to secondary treatment in addition to the energy required for
PAC addition.
Table 3-17. Primary Effluent Wet Well — Annual Equipment Electricity Use
lCq uipment
HP
A
V
Run rime
(hr/vr)
Annuul Klcctricitv
Use(kWh)
Primary Effluent Pump No. 1
20.0
27.5
460
8,740
130,000
Primary Effluent Pump No. 2
0.0
27.5
460
-
-
Primary Effluent Wet Well Level
Sensor
0.50
0.90
24.0
8,760
189
CHEMFEED-PAC
1.00
1.60
110
8,760
1,540
3-13
-------
3—LCA Methodology
It is reported that 27 pounds of PAC is used per day at a flow rate of 0.67 MGD. The
following calculation in Equation 6 is used to determine the PAC addition used in the LCI:
PAC addition = 27 lb/day - 0.67 MGD 2.2 lb/kg x 365 days/yr -
1,381,676 m3/yr wastewater = 0.0048 kg/m3 wastewater
Equation 6
3.3.4 Anoxic and Swing Tank
Electricity consumption includes tank mixers, aeration for the swing tank, and pump
energy required to move wastewater to the aeration basins (Table 3-18). Electricity use of the
swing tank aerators is increased for the medium and high feedstock scenarios based on the
percent increase in BOD and total nitrogen (TN) attributable to supernatant return flows. No
chemical use is required for the anoxic or swing tanks. The use of a carbon source to aid
denitrification is possible, but is not anticipated to be necessary. GHG emissions from this unit
are included with the aeration and secondary clarification unit process.
Table 3-18. Anoxic and Swing Tank — Annual Equipment Electricity Use
Units
Run Time
lOlectricitv Use
lCc] uipnienl
On
IIP
(hr/diiv)
(kWli/vr)
Pre-Anox and Swing Tank
Submersible Mixers
1
8.30
3.60
8,140
Swing Tank, Aeration
1
25.0
4.00
27,200
Pump, to Aeration Tank
1
20.0
24.0
131,000
3.3.5 Aeration and Secondary Clarification
Electricity consumption for this unit includes aeration and clarifier drive energy, nitrate
and RAS pumping, and movement of WAS to the sludge well (Table 3-19). Electricity use is not
scaled for aeration and secondary clarification due to the minimal effect of supernatant return
flows on flowrate and the assumption that unit equipment is operating at a fixed capacity. The
PAC addition which aids flocculation in this unit is added in the primary effluent wet well.
Table 3-19. Aeration and Secondary Clarification — Annual Equipment Electricity Use
Kq uipment
HP
A
V
Run l ime
(hr/yr)
lOlectricitv Use
(kWli/vr)
RAS Pumps
3.00
-
-
8,760
19,600
RAS Pumps
3.00
-
-
8,760
19,600
RAS Pumps
3.00
-
-
8,760
19,600
WAS Pumps1
0.50
0.90
110
2,910
1,090
Nitrate Recycle Pumps
5.00
-
-
8,760
32,700
Nitrate Recycle Pumps
5.00
-
-
8,760
32,700
Nitrate Recycle Pumps
5.00
-
-
8,760
32,700
Multi-Stage Centrifugal Blower
No. 1
50.0
61.0
460
8,740
245,000
Multi-Stage Centrifugal Blower
No. 2
50.0
61.0
460
8,740
245,000
3-14
-------
3—LCA Methodology
Table 3-19. Aeration and Secondary Clarification — Annual Equipment Electricity Use
Kq uipment
HP
A
V
Run Time
(lir/vr)
Electricity Use
(kWli/vr)
Clarifier Drive No. 1
0.50
1.00
460
8,740
4,020
Clarifier Drive No. 2
0.50
1.00
460
8,740
4,020
Clarifier Drive No. 3
0.50
1.00
460
8,740
4,020
Note:
1 Equation 1 was used to calculate electricity use of the WAS pump, which yields a higher estimate of electricity
consumption than Equation 2. While this approach is inconsistent with the preference for use of Equation 2 when
electrical load information is available, the effect is negligible at a process unit and treatment system level.
GHG emissions from the aerobic tanks are calculated based on influent TKN and BOD
concentrations. For a MLE system with zones for both nitrification and denitrification it is
assumed that 0.16 percent of influent nitrogen is lost as nitrous oxide (Chandran 2012). Methane
emissions from the upgraded secondary treatment system are calculated using a theoretical
maximum methane generation rate of 0.6 kg CFU/kg influent BOD, which is adjusted
downwards using a methane correction factor of 0.05 (Daelman et al. 2013) as demonstrated in
Appendix A.
3.3.6 Belt Filter Press
Electricity use includes the operation of pumps and drive motors for the BFP and energy
required for chemical additions (Table 3-20). Baseline electricity requirements for all BFP
equipment are scaled based on the increase in waste processed for each Feedstock-AD scenario
relative to the baseline. Scaling factors are recorded in the Appendix.
Table 3-20. Belt Filter Press — Annual Equipment Electricity Use
Eq uipment
IIP
A
V
Run lime
(lir/vr)
Annuiil Electricity
Use (kWli)
Chemical Feed - Polymer BFP
1.00
-
-
4,380
3,270
BFP Feed Pump No. 1
5.00
6.60
460
2,080
6,320
Drum Drive
1.00
1.60
460
2,080
1,530
Belt Drive
1.50
2.80
460
2,080
2,680
Spray Pump
7.50
9.40
460
2,080
8,990
Screw Conveyor Drive
1.00
1.60
460
2,080
1,530
Belt Conveyor Drive
1.00
1.60
460
2,080
1,530
A dosage of 8 lb active polymer ingredient is required per dry ton of solids processed by
the BFP to aid dewatering (GHD 2016, pg. 32), which is determined according to the Feedstock-
AD scenarios introduced in Section 3.3.9. It is assumed that a similar dosage is required for the
gravity belt thickener. The following calculation in Equation 7 is performed to determine the
3-15
-------
3—LCA Methodology
polymer LCI addition for each scenario (Table 3-21), using values from the Base Feedstock-Base
AD scenario as an example:
Polymer Addition (kg/m3) = 8 lb/ short ton x 2.3 short ton/day 2.2 lb/kg x 365 day/yr -5-
1,381,676 m3/yr | = 0.0022 kg/n?
Equation 7
Table 3-21. Polymer Additions for the BFP by Feedstock and AD Scenario
Feedstock Scenario
Polvmer Addition (kg/m*)
Al) Low
Al) Base
AD High
Base
0.0023
0.0021
0.0020
Medium
0.0032
0.0028
0.0027
High
0.0045
0.0039
0.0037
3.3.7 Gravity Belt Thickening
Electricity use for the GBT includes pumping energy from the sludge well, and operation
of drive motors, pumps, and compressors as well as energy required for polymer addition (Table
3-22).
Table 3-22. Gravity Belt Thickener — Annual Equipment Electricity Use
Kq uipmcnl
HP
A
V
Run lime
(lir/yr)
Annual Electricity
Use(kWh)
Sludge Pump (1)
7.50
-
-
2,080
11,600
GBT Air compressor
1.00
-
-
1,460
1,090
Gravity Belt Thickener
1.00
-
-
2,080
1,550
GBT Booster Pump
5.00
-
-
2,080
7,760
Chemical Feed- Polymer GBT
1.00
-
-
4,380
3,270
The GBT processes the same quantity of dry solids each day regardless of feedstock
scenario as the high strength organic waste is assumed to bypass this unit, leading to a constant
polymer addition of 0.003 kg/m3 as shown in Equation 8.
Polymer Addition (kg/m3) = 8 lb/ short ton x 3.09 short ton/day 2.2 lb/kg x 365 day/yr -5-
1,381,676 m3/yr | = 0.003 kg/iif
Equation 8
3.3.8 Blend Tank
Blend tank operation and pumping energy to the primary digester comprise equipment
energy use for the blend tank (Table 3-23). Baseline electricity requirements for the blend tank
3-16
-------
3—LCA Methodology
are scaled based on the increase in waste processed for each Feedstock-AD scenario relative to
the baseline. Scaling factors are recorded in Appendix A. No chemical additions are required for
the blend tank.
Table 3-23. Blend Tank — Annual Equipment Electricity Use
Kq uipmenl
HP
A
V
Run rime
(hr/yr)
Annual Kleclricitv
Use(kWh)
Raw Sludge Transfer Pump
7.50
-
-
2,080
11,600
Blend Tank Mixer
8.30
-
-
1,310
8,140
3.3.9 Anaerobic Digestion
AD electricity consumption includes unit mixing, sludge transfer, and biogas cleaning
energy (Table 3-24). Baseline electricity requirements for the digested sludge transfer pump are
scaled based on the increase in waste processed for each Feedstock-AD scenario relative to the
baseline. Scaling factors are recorded in the Appendix. The gas cleaning system runs 24 hours a
day regardless of gas production, with the assumption that electricity consumption remains
constant. No chemical additions are required for this unit.
Table 3-24. Anaerobic Digestion — Annual Equipment Electricity Use
Kq uipmcnl
HP
Run rime
(lir/vr)
Annual Klectricity
Use (kwh)
Digester Mixing Pump
25.0
8,760
163,000
Digested Sludge Transfer Pump
7.50
2,080
11,600
Gas Cleaning System Booster Pump
30.0
8,760
196,000
AD operational parameters were calculated using the approach developed for
implementation in the CAPDETWorks™ WWTP design and costing software (Hydromantis
2014). The base scenario incorporates sludge quantities associated with operating the treatment
plant at its full capacity of 1 MGD, plus the acceptance of an additional 16,000 GPD of septic
and portable toilet waste (GHD 2016). The medium and high feedstock scenarios have been
developed assuming additional acceptance of high strength organic wastes as reflected in Table
3-25, leading to a maximum acceptance of 24,000 GPD of trucked in waste in the High feedstock
scenario. Quantities of accepted waste were determined by the size of the ADs and a reasonable
range of targeted loading rates of between 130 and 205 lb VS/1000 fi3/day at a retention time of
15 days (Tchobanoglous et al. 2014). The quantities included in Table 3-25 are prior to
dewatering in the GBT. Actual daily flow to the AD is just below 20,100 gal/day in the high
feedstock scenario, which is below the maximum flow capacity of 21,000 gal/day (CRA 2015).
The characteristics of each feedstock are included in Table 3-3.
Table 3-25. Feedstock Scenarios for AD Sensitivity Scenarios (prior to dewatering)
Waste Type1
.Base (gal/day)
Medium (gal/day)
High (gal/day)
Primary Sludge
17,654
17,654
17,654
3-17
-------
3—LCA Methodology
Table 3-25. Feedstock Scenarios for AD Sensitivity Scenarios (prior to dewatering)
Waste Type1
Biisc (£
-------
3—LCA Methodology
Table 3-26. Operational Parameters for AD Sensitivity
Al) Low
Al) Base
Al) High
Parameter Nsi me
Value
Reference
Viilue
Reference
Value
Reference
Units
Percent Volatile Solids Reduction
45
1
60
1
65
1
%
ft3/lb VS
Base5
12.0
calculated
15.0
calculated
34.7
calculated
destroyed
Biogas Yield
Medium5
12.8
calculated
16.7
calculated
30.0
calculated
ft3/lb VS
destroyed
ft3/lb VS
High5
14.2
calculated
19.2
calculated
29.1
calculated
destroyed
Methane Content of Biogas
60
2
65
2
75
2
% v/v
Biogas Heat Content
0.55
2
0.59
2
0.61
2
MJ/tf
Electrical Efficiency
30
2
36
3
42
2
%
Thermal Efficiency
41
2
51
3
43
2
%
Northern
Northern
Northern
Reactor Heat Loss
US
4
US
4
US
4
Notes & References:
1 Appleton and Rauch Williams 2017
2 Wiser et al. 2010
3 GHD 2016
4 Hydromantis 2014
5 Refers to the feedstock scenario
3-19
-------
3—LCA Methodology
Table 3-27. Biogas Yield for AD Sensitivity (ft3 biogas/ lb VS destroyed)
Feedstock
Al) Low
Al) Base
A
)IIii>h
Value
Reference
Viilue
Reference
Viilue
Reference
Primary Sludge
12.0
3,1
15.0
1
43.5
2
Waste Activated Sludge
12.0
3,1
15.0
1
18.0
8,1
Septic Tank Waste
12.0
3,1
15.0
1
18.0
8,1
Slaughterhouse Waste
17.0
3,4,5
23.9
3,4,5
29.4
3,4,5
Cheese Waste
11.1
3,7
14.9
3,7
15.9
3,7
Winery Waste, Vinasse
10.0
6
14.0
6
17.3
6
Portable Toilet Waste
12.0
3,1
15.0
1
18.0
8,1
Notes & References:
1 Hydromantis 2014
2 GHD 2016,
3 20% reduction in biogas yield due to ammonia inhibition (IEA 2009)
4 Braun and Wellinger 2003
5 Luste and Luostarinen 2010
6 Belhadj et al. 2013
7 Rico et al. 2014
8 20% increase, represents general improvement in AD performance. Value is within the range of other referenced
increases in biogas yield.
The quantity of biogas generated varies across both feedstock scenarios and AD
operational scenarios. As shown in Table 3-28, biogas production varies by a factor of ten
between the Base Feedstock-Low AD scenario and the High Feedstock-High AD scenarios.
Table 3-28. Biogas Production by Feedstock and AD Scenario
Feedstock Scenario
Al) Seen
Al) Low
ario (m* biotas/in* tre
Al) Base
jted water)
Al) High
Base
0.13
0.21
0.53
Medium
0.22
0.38
0.74
High
0.40
0.71
1.17
Electricity production varies by a factor of 14 across the scenarios because electrical
efficiency of CHP technology increases from the low to high AD scenarios on top of the
differences in biogas production (Table 3-29). One hundred percent of electricity produced
avoids electrical production via the local grid. Electricity produced by the CHP system is feed
into the grid to satisfy local demand. Three perspectives on production and use of heat energy
associated with the AD unit are presented in Table 3-30 through Table 3-32. Table 3-30 shows
total potential heat production available when the full quantity of biogas is used in CHP. Only
the portion of heat required for preheating sludge, AD unit heat, and building heat offsets natural
gas production (Table 3-31) in the absence of further technology used to upgrade and distribute
the heat product. The difference between heat values reflected in Table 3-30 and Table 3-31 is
heat production that is currently not utilized, and therefore does not generate a credit for avoiding
natural gas use. Seasonality of heat demand for both the AD and the facility itself are considered
3-20
-------
3—LCA Methodology
within the AD heat loss equation and utility records. Table 3-32 shows the quantity of natural gas
that is required for AD operation and building heat on top of the heat provided via biogas
combustion. The inclusion of AD at the WWTP is able to satisfy the heat energy requirement of
the facility for the High Feedstock-Base AD scenario and all feedstock scenarios under the best-
case (High AD) scenario for AD operational performance.
Table 3-29. Electricity Production from Biogas by Feedstock and AD Scenario
Feedstock Scenario
Al) Scenario (kwh/m* treatci
water)
AD Low
AI) Bust'
Al) High
Base
0.21
0.45
1.34
Medium
0.35
0.80
1.87
High
0.64
1.50
2.95
Table 3-30. Potential Heat Production from Biogas by Feedstock and AD Scenario
Feedstock Scenario
Al) Scenario (MJ/m* treated water)
Al) Low
Al) Base
AD High
Base
1.01
2.24
4.92
Medium
1.74
4.05
C\
CO
\6
High
3.14
7.56
10.9
Table 3-31. Modeled Avoided Heat from Natural Gas by Feedstock and AD Scenario
Feedstock Scenario
Al) Scenario (iVM/m* treated water)
AD Low
Al) Base
Al) High
Base
1.01
2.24
3.01
Medium
1.74
4.05
3.30
High
3.14
4.45
3.59
Table 3-32. Required Heat from Natural Gas by Feedstock and AD Scenario
Feedstock Scenario
AD Scenario (iVM/m* treated water)
AD Low
AD Base
AD High
Base
2.87
1.63
-
Medium
2.42
0.114
-
High
1.31
-
-
As shown in Table 3-33 and Table 3-34, methane emissions associated with the anaerobic
digesters and CHP also increase from the Base Feedstock-Low AD to High Feedstock-High AD
3-21
-------
3—LCA Methodology
scenarios as it is assumed that 1 percent of biogas methane content is lost during each subsequent
step.
Table 3-33. Methane Losses from Digester by Feedstock and AD Scenario
Feedstock Scenario
AD Scenario (kg (.'H4/m* treated water)
AD Low
AD Base
AD High
Base
5.00E-4
9.03E-4
2.43E-3
Medium
8.61E-4
1.63E-3
3.40E-3
High
1.56E-3
3.04E-3
5.38E-3
Table 3-34. Methane Losses from CHP by Feedstock and AD Scenario
Feedstock Scenario
AD Scenario (kg (TI4/m* treated water)
AD Low
AD Base
AD High
Base
4.95E-4
8.94E-4
2.41E-3
Medium
8.52E-4
1.61E-3
3.37E-3
High
1.54E-3
3.01E-3
5.32E-3
3.3.10 Composting
Both the feedstock scenarios and AD operational parameters affect the quantity of sludge
that is influent to the composting system. High operational performance of AD leads to less dry
solids production as more of the feedstock is converted to biogas. The composting process is
designed to hit a moisture content of approximately 55 percent and a C:N ratio of approximately
30:1. A standard C:N ratio of 12.7:1 is assumed for the digested biosolids (Maulini-Duran et al.
2013). Supplemental organic materials expected to be readily available have been used to adjust
the C:N ratio and moisture content of biosolids to match these targets for the feedstock and AD
operational scenarios. Loose dry leaves and newsprint serve as the feedstocks of choice in all the
analyzed scenarios. Table 3-35 provides feedstock characteristics for a range of materials that are
likely to be available in Bath, NY.
Table 3-35. Composting Supplemental Feedstock Characteristics
Feedstock
Moist lire
(% w/w)1
Carhon
(% w/w)1
Nitrogen
(% w/w)1
Ci.V
Densitv
(kg/m3)2'3
Leaves Loose, Dry
15%
49%
0.9%
54
388
Grass, Loose
82%
58%
3.4%
17
716
Newsprint
6%
63%
0.1%
625
425
Leaves, Fresh
38%
49%
0.9%
54
590
Food Waste
87%
39%
3.3%
12
866
Chipped Wood
40%
58%
0.1%
641
897
Notes & References:
1 Richard 2014
2 CWMI 1990
3 Harris and Phillips 1986
3-22
-------
3—LCA Methodology
Digested biosolids are transported by truck a short distance (0.8 km) from the wastewater
treatment plant to the composting site. The baseline scenario uses a basic windrow composting
system where the piles are turned regularly using a self-propelled compost turner. To be
classified as Class A biosolids it is necessary to maintain compost pile temperatures at 55°C for a
minimum period of 15 days with 5 turnings during this time (U.S. EPA 1994). Elevated
temperatures within the compost pile are due solely to microbial activity and decomposition. No
external source of heat is provided to the compost pile. It is assumed that compost is left on site
for a total period of 14 to 16 weeks for curing with an additional two turnings during this time
(ROU 2006). Windrows are modeled to be 10 feet wide by 4.5 feet tall (Hao et al. 2001). In
addition to regular pile turning, the use of bulking agents is employed to help provide adequate
aeration (Malinska et al. 2013). Table 3-36 lists the supplemental organic feedstock mixtures
used in the sensitivity analysis. Small quantities of water are required to adjust the initial
moisture content of the compost pile, amounting to less than 150 m3 per year (less than 0.1
percent of treated wastewater). Compost is assumed to be screened prior to being sold as an
agricultural soil amendment. Electricity and diesel consumption factors of 0.13 kWh and 5.02
liters/ton of incoming material are used to account for grinding, windrow turning, and screening
energy consumption (ROU 2006).
Table 3-36. Organic Compost Additions by Feedstock-AD Scenario (Metric Tons/Year)
I'l'cdstock
Itasc-
Low
Ifcise-
liilSO
Base-
lligh
Medium-
Low
Medium-
Base
M odium -
High
High-
Low
lligh-
Ifcise
1 ligh-
lligh
Leaves Loose,
Dry
2,500
2,250
2,100
3,400
3,100
3,000
4,700
4,300
4,000
Newsprint
15
15
10
25
25
20
35
35
25
Opinions on the emission of methane and nitrous oxide during the composting process
range widely within the published literature. Some authors indicate that no methane is released
(ROU 2006), while other authors indicated that up to 2.5% of incoming carbon content in the
composting feedstock can be liberated as methane during the composting process (SYLVIS
2011). The 2006 IPCC Guidelines for National GHG Inventories suggest a range of less than one
percent to a few percent of incoming carbon content can be released as methane. The range is
even wider for nitrous oxide with a potential emission range of 0.5 to 5 percent of initial nitrogen
content being released as N2O-N (IPCC 2006).
A range of GHG emissions from composting are available within the literature and given
the many parameters that can vary within a study there is a large uncertainty as to which values
most closely apply to our proposed management system. The above management practices are
expected to minimize GHG production, but even a well-managed composting system can be
expected to produce some emissions of methane and nitrous oxide. Given these considerations,
three sets of emission factors are applied during the sensitivity analysis to test their effect on
system level environmental impacts. Ammonia, non-methane volatile organic compounds
(NMVOC), and carbon monoxide emissions are also included in the inventory. The emission of
CO2 is not included in the analysis as it is biogenic in origin, and therefore carbon neutral. Table
3-37 shows emission factors for the Base Feedstock-Base AD scenario used in the sensitivity
analysis. A table detailing compost emission factors for all scenarios is included in Appendix A.
3-23
-------
3—LCA Methodology
Emission factors vary across scenarios due to the variable quantity of carbon and nitrogen
present in the compost mixtures as specified.
A sensitivity analysis is also employed to quantify the potential benefits and burdens
associated with the use of an aerated static pile (ASP) composting system in place of the
windrow system. The Biosolids Emissions Assessment Model (BEAM) composting emissions
suggest that ASP systems can eliminate methane emissions if paired with an effective biofilter
(SYLVIS 2011). The ASP biofilter reduces NH3 and NMVOC emissions by 95% relative to a
non-filtered system (Williams 2009). CO and N2O emissions are the same as those from the
windrowing system. Fuel and electricity use for the ASP is set at 2.5 L/wet metric ton and 90
kWh/dry metric ton (Brown et al. 2008).
Table 3-37. Low, Medium, and High Estimates of Potential Composting Emissions for
the Base Feedstock-Base AD Scenario
Emission
Species
Low Ksliimile
Medium Ksliimile
High Ksliimile
Vulue
Unit
Ref.
Vulue
Unit
Note
Vulue
Unit
Ref.
Methane (CH4)
0.0016
kg
CFU/m3
1
0.0070
kg
CHVm3
Average
0.0246
kg
CHVm3
2
Nitrous Oxide
(N20)
0.0002
kg
NaO/m3
1
0.0017
kg
NiO/m3
Average
0.0029
kg
NiO/m3
3
Ammonia
fNH3)
0.0006
kg
NFb/m3
4
0.0033
kg
NFb/m3
Average
0.0062
kg
NFb/m3
3
Carbon
Monoxide
0.0010
kg
CO/m3
1
0.0010
kg
CO/m3
Average
0.0010
kg
CO/m3
1
NMVOC
0.0002
kg
NMVOC
/m3
4
0.0002
kg
NMVO
C/m3
Average
0.0002
kg
NMVO
C/m3
4
Notes & References:
1 Hellmann 1997
2 Hellebrand 1998
3 Fukumoto et al. 2003
4 Maulini-Duran et al. 2013
To best interpret the compost emission values, a description of each study considered is
included in Table 3-38. Several variables emerge as being crucial to ultimate emissions from
composting: (1) moisture content, (2) carbon and nitrogen content of incoming material, (3) C:N
ratio, and (4) composting method. Moisture contents above 60 percent are expected to contribute
to the formation of anaerobic zones, and therefore increased methane production (Fukumoto et
al. 2003). Low C:N ratio is reported to increase the emission of volatile nitrogen compounds
(Brown et al. 2009). Some authors have also reported that methane emissions tend to peak after
pile turnings (Hao et al. 2001), however given the requirements for Class A biosolids, the
number of pile turnings cannot be reduced without movement to a forced aeration system.
3-24
-------
3—LCA Methodology
Table 3-38. Compost Emission Study Description
C'iliilion
Sluilv Description
Hellmann 1997
This study is conducted on a full-scale windrow composting system,
which utilizes the organic fraction of municipal solid waste and yard waste
as feedstocks. The initial moisture content is 60%, with an initial C:N ratio
is 26.1:1
Hellebrand 1998
This study is conducted on a full-scale, trapezoidal compost heap, utilizing
grass cuttings, soil, and manure as feedstocks. The initial moisture content
is not reported, but was 70 percent for a concurrent lab-scale experiment
that was run by the authors. Initial C:N ratio was 27:1.
Fukumoto et al. 2003
This study is conducted on a full-scale compost heap using forced
aeration. Results from both small and large piles were developed. The
feedstock for this study was pig manure amended with sawdust. Initial
moisture content of both piles was 68 percent, and while the authors do not
report their C:N ratio they note that the value tends to be low for livestock
manure.
Maulini-Duran et al. 2013
This is a pilot-scale study testing emissions on forced aerated anaerobic
digester sludge. Initial moisture content was 58 percent with an initial C:N
ratio of 12.7:1.
The chemical composition of finished compost is used to determine environmental
benefits and burdens of land application. Table 3-39 shows typical physical characteristics for
finished compost that is produced from a mixture of biosolids and organic plant residues, such as
those assumed in this study.
Table 3-39. Physical Characteristics of Finished Compost, Base Feedstock-Base AD
Scenario
Parameter
Value
Unit
Moisture Content
45
% w/w
Organic Matter
55-75
% dry matter
Total N
2.9
% dry matter
Total P
0.5
% dry matter
Total K
0.2
% dry matter
Reference:
ROU 2006
3.3.11 Land Application of Composted Biosolids
Composted biosolids are assumed to be transported an average of 25 km to farm fields
for application as a fertilizer and soil amendment. Compost is hauled in an 18-ton dump truck,
which is assumed to be empty during the back-haul. Compost is loaded into a manure spreader
and is surface applied to agricultural fields at the average U.S. application rate. It is assumed that
1.02 liters of diesel fuel are required per ton of compost (ROU 2006). In 2011, an average of 138
pounds of nutrient was applied per acre of agricultural land in the U.S. Nutrient content is
calculated in terms of N, P2O5, and K2O, which comprise 59, 20, and 21 percent of total nutrient
3-25
-------
3—LCA Methodology
additions respectively (U.S. EPA 2013). The ratio of elemental nitrogen, phosphorus, and
potassium in finished compost is not the same as the typical agricultural application rate. Due to
the greater relative presence of phosphorus in finished compost it is assumed that composted
biosolids are applied at a rate necessary to achieve the average per acre phosphorus addition of
27.4 lbs P205/acre/year. If application rates were based on nitrogen or potassium content the
corresponding additions of phosphorus would be greater than what is required.
Estimates of avoided fertilizer costs are based on N, P2O5, and K2O in the form of urea,
triple phosphate, and potassium sulfate. Inorganic fertilizers tend to have greater plant
availability than do organic fertilizers with equivalent nutrient contents. A fertilizer replacement
value of 73 percent is assumed for this study when calculating the avoided quantity of mineral
fertilizer to produce a conservative estimate of environmental benefit. This value was
demonstrated for digested manure over the course of four years (Smith 2007). This study applies
the same replacement value for both phosphorus and potassium.
Typical agricultural emissions such as nitrous oxide, ammonia, nitrate, soluble
phosphorus, and sediment bound phosphorus have been calculated based on a conservative
estimate of the potential net change in agricultural emissions that could occur by replacing
inorganic fertilizers with organic alternatives. As with composting emissions, field emissions of
nutrients can vary over a wide range depending upon application method and timing, soil type,
and a variety of climatic factors. The methods used to estimate field emissions are based on
nutrient application rates, and assuming equivalent emissions between organic and inorganic
fertilizer types per unit mass of nutrient land applied, this could lead to an increase in field
emission of nutrients due to the higher application rate of organic nutrients implied by the 73
percent fertilizer replacement value cited above. A summary of agricultural emission rates, given
the assumed application rates are presented in Table 3-40. Impacts based on values calculated in
this report should be viewed as a reasonable estimate, however significant variability in these
values is expected in practice.
Table 3-40. Emission Rates at National Average Application
Rate
Kmission Species
Com part me lit
Kmission1
Units
Ammonia
air
16.5%
of applied N
Nitrous Oxide
air
1.17%
of applied N
Nitrate
water
10.5%
of applied N
P, sediment
water
10.1%
of applied P
P, soluble
water
3.20%
of applied P
P, soluble
groundwater
0.32%
of applied P
P, sediment
air
2.40%
of applied P
Note:
1 Emissions are calculated as a function of application rate for nitrate and ammonia.
3-26
-------
3—LCA Methodology
3.3.12 Effluent Release
One of the goals of the upgraded wastewater treatment system is to produce wastewater
that can be put to a variety of reuse applications such as for landscape irrigation. A local golf
course has expressed interest in reusing up to 13 million gallons of treated effluent annually for
irrigation. It is assumed that this reuse application avoids the need to treat an equivalent quantity
of water to fill that need. An estimate of pumping energy to the golf course in addition to the
operation of an effluent sampler is included in the study (Table 3-41). No standard set of
guidelines specifying target effluent quality for specific reuse applications are available for New
York (CDM Smith 2012). However, water reuse projects have occurred within NY State and it is
assumed that they are approved on an individual basis.
Table 3-41. Effluent Release - Annual Equipment Electricity Use
lCc] uipmcnl
HP
A
V
Run rime
(hr/vr)
Annual Kleetrieitv
Use(kWh)
Sampler
0.50
0.90
115
1,250
129
Pump to Reuse Location
20.0
27.5
460
3,600
45,500
Nitrous oxide emissions from receiving streams are calculated based on the IPCC
guideline that 0.005 kg of N2O-N are emitted per kg of nitrogen discharged to the aquatic
environment. Details of that calculation are presented in the Appendix.
3.4 LCI Limitations & Data Quality
LCI information that falls outside of the system boundary is introduced and discussed in
Section 2.2. More general LCI limitations that readers should understand when interpreting the
data and findings are as follows:
• Transferability of Results. While this study is intended to inform decision-making
for WWTPs of similar size and design, the data presented here relates to a specific
U.S. WWTP in Bath, NY. Further work is recommended to understand the variability
of key parameters across different conditions, system sizes, and configurations.
• Representativeness of Background Data. Background processes are representative
of either U.S. average data (in the case of data from U.S. EPA LCI or U.S. LCI) or
European average (in the case of Ecoinvent) data. In some cases, European Ecoinvent
processes were used to represent U.S. inputs to the model (e.g., for chemical inputs)
due to lack of available representative U.S. processes for these inputs. The
background data, however, met the criteria listed in the project quality assurance
project plan (QAPP) for completeness, representativeness, accuracy, and reliability.
• Data Accuracy and Uncertainty. In a complex study with literally thousands of
numeric entries, the accuracy of the data and how it affects conclusions is truly a
difficult subject, and one that does not lend itself to standard error analysis
techniques. The reader should keep in mind the uncertainty associated with LCI
models when interpreting the results. Comparative conclusions should not be drawn
based on small differences in impact results.
3-27
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4—LCCA Methodology
4. LCCA Methodology
This section presents the methodology used to develop life cycle costs for the upgraded
WWTP. Forward looking life cycle cost estimates of the legacy system are not appropriate as
this system will be superseded in the future. Cost data has been collected and adjusted from
several sources as described in Section 4.1. Basic LCCA methods are described in Section 4.3.
LCCA results are presented according to three cost scenarios, which cover a reasonable range
regarding potential input parameters. Parameter values for the low cost, base, and high cost
scenarios are listed in Section 4.3.7.
4.1 LCCA Data Sources
Cost data were obtained from the following sources:
• Primary budget data for the legacy WWTP, budget year 2013-2014.
• GHD Engineering Life Cycle Cost Analysis of Preliminary and Primary Treatment
Processes (GHD 2016)
• CAPDETWorks Version 3.0 (Hydromantis 2014)
• RSMeans Building Construction Cost Data (RSMeans 2016)
• Personal communication with BEGWS personnel
4.2 Unit Process Costs
The following sections describes data sources and cost estimation assumptions for
individual unit processes.
4.2.1 Collection System
Only operational costs associated with electricity consumption are considered for the
collection system.
4.2.2 Chemically Enhanced Primary Clarification
GHD Engineering carried out a LCCA on the costs of installing chemically enhanced
primary clarification at the Bath wastewater treatment facility. Cost estimates from that study are
used in this analysis. The GHD LCCA was carried out for process upgrades taking place for the
preliminary and primary treatment processes (GHD 2016). The GHD analysis uses an average
annual flow rate of 0.67 MGD, which necessitates an update of annual operating costs associated
with chemical and electricity use. It is assumed that annual maintenance and periodic equipment
replacement costs remain the same regardless of flowrate. The equipment specified by GHD is
designed to handle the 1 MGD flow rate specified in this analysis.
4.2.3 Anoxic-Swing Tank
The anoxic and swing tank repurposes two cells of the existing aerobic digester. These
units require the installation of new aeration devices and mixing units. The direct and indirect
costs associated with unit renovation, as described in Section 4.3, are applied to this unit.
4-1
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4—LCCA Methodology
4.2.4 Aeration Basins
The three aeration basins will continue to function much as they have during the
operation of the legacy system, with the addition of nitrate recycle pumping. As the aeration
basins have been in use for a considerable period, it is assumed that all major equipment
including the clarifier drive and centrifugal blowers will require replacement during the initial
renovation as they are reaching the end of their useful lifespan. Equipment costs have been
approximated using estimates from BEGWS personnel or the RSMeans database. Direct and
indirect cost assumptions associated with unit renovation are applied as discussed in Sections
4.3.3 and 4.3.4.
4.2.5 Sludge Receiving and Holding
Sludge receiving and holding consists of a mixture of new construction and repurposed
units. Two of the existing aerobic digester cells are to be repurposed for temporary storage of
incoming high strength organic waste. A new sludge pumping system will be required, as well as
the replacement of the existing aeration system for use during temporary storage. The cost of
transporting septage and high strength organic waste to the wastewater treatment facility is borne
by the waste generator, and is excluded from the analysis. Direct and indirect cost assumptions
associated with unit renovation are applied as discussed in Section 4.3.
4.2.6 Gravity Belt Thickening
The GBT is a new unit. Cost estimates for a rotary drum thickener were included in the
GHD analysis, and in the absence of better information and remaining uncertainty regarding the
type of unit that will ultimately be implemented, these costs have been used to approximate the
thickening step. GHD's assumptions regarding direct and indirect costs are included for this unit.
4.2.7 Blend Tank
The existing gravity thickening tank is repurposed to serve as a blend tank for the mixture
of high strength organic waste, WAS, and primary sludge prior to AD. The addition of a mixing
unit and sludge pump are required. Direct and indirect cost assumptions associated with unit
renovation are applied.
4.2.8 Belt Filter Press
The BFP is an existing unit that is housed in the control building. Given the age of this
unit it is assumed that all main pieces of equipment are replaced or refurbished during the plants
initial renovation and construction period. Indirect costs associated with engineering design and
profit are excluded for this unit, which is considered a material replacement as opposed to a
renovation or new construction.
4.2.9 Anaerobic Digestion
The costs of unit construction, mechanical equipment, additional personnel, and all other
associated direct and indirect costs for AD have been calculated using CAPDETWorks™
engineering costing software. The full suite of direct and indirect costs as listed in Table 4-1 and
Table 4-2 are included. Revenue from waste tipping fees, electricity production, and avoided
4-2
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4—LCCA Methodology
natural gas purchasing are calculated based on LCI input values associated with each Feedstock-
AD scenario.
4.2.10 Combined Heat and Power
The costs of unit construction and maintenance were developed based on an EPA report
titled Evaluation of Combined Heat and Power Technologies for Wastewater Facilities (Wiser
2010). Cost of the engine itself accounts for 14 percent of total costs with gas cleaning,
engineering, facility, and installation costs contributing the remainder of the cost. No additional
direct and indirect costs apply.
4.2.11 Composting
The composting facility requires the purchase and maintenance of a material grinder,
self-propelled pile turner, front end loader, and material screen. Taxes, housing, insurance, and
an estimate of salvage value is included for each piece of equipment. Diesel and electricity
consumption costs are also included. It is assumed that one full personnel position is required to
manage the composting facility with an inclusive annual cost of $100,000. The effect of compost
sale price on life cycle costs is examined in the low, base, and high cost scenarios in the results
section. No further costs associated with land application are assumed. The facility has an area
adjacent to the treatment plant that can be used for the composting facility, which is assumed to
be sufficient. If additional land purchases are required these costs would need to be added to the
calculation of life cycle costs.
4.3 LCCA Methods
The LCCA, applied to the upgraded system, uses a net present value (NPV) method to
consider capital costs and annual or otherwise periodic costs associated with operation,
maintenance, and material replacement.
Upgrades to the legacy WWTP include the installation of new unit processes in the case
of both AD and chemically enhanced primary clarification. The installation of new units is
assumed to incur all costs typically associated with new construction. The upgraded MLE
secondary treatment process and other process upgrades such as the conversion of the existing
GBT to a sludge blending tank constitute upgrades to existing infrastructure, which eliminates
some costs while modifying others. This necessitates the application of different costing methods
on a unit-by-unit basis as described in Sections 4.2.1 through 4.2.11. General costing methods
used are described below.
4.3.1 Total Capital Costs
Total capital costs include purchased equipment, direct, and indirect costs. Direct costs
are costs incurred as a direct result of installing the WWTP. Direct costs include mobilization,
site preparation, site electrical, yard piping, instrumentation and control, and lab and
administration building. Indirect costs include land, miscellaneous items, legal costs, engineering
design fee, inspection costs, contingency, technical, interest during construction, and profit. Both
direct and indirect costs are determined using cost factors based on purchased equipment pricing.
Total capital costs are calculated using Equation 9.
4-3
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4—LCCA Methodology
Total Capital Costs = Purchased Equipment Costs + Direct Costs + Indirect Costs
Equation 9
where:
Total Capital Cost (2014 $) = Total capital costs
Purchased Equipment Costs (2014 $) = Costs to purchase the equipment for the WWTP
Direct Costs (2014 $) = Costs incurred as a direct result of installing the WWTP
Indirect Costs (2014 $) = All non-direct costs incurred as a result of installing the WWTP
4.3.2 Purchased Equipment Costs
It was necessary to seek outside sources of cost information for pieces of equipment
required in the secondary treatment plant upgrade as well as those pieces of equipment which
will require replacement within the 30-year horizon of the LCCA. Sources for this information
are described in Section 4.2.
A base escalation factor of 3 percent is applied to all purchased inputs. Escalation factor
describes an estimated increase in the price of purchased inputs beyond the rate of inflation.
Escalation factors are applied using Equation 10. Escalation factors for various facility costs are
varied within the LCCA scenarios as described in Section 4.3.7.
Costx= Costo (1+ESC)X
Equation 10
where:
Costx = Cost in future year x
Costo = cost in year zero, 2014
ESC = escalation rate, 3% in base cost scenario
x = number of years in the future
4.3.3 Direct Costs
Direct costs include mobilization, site preparation, site electrical, yard piping,
instrumentation and control, and lab and administration building construction.
Table 4-1 lists the direct cost factors used for this project. The full list of direct costs
applies to the newly constructed primary treatment process as well as AD. For retrofitted units,
such as the anoxic-swing tank, it is assumed that mobilization, instrumentation and control costs,
and one-half of the new construction direct costs for site electrical and yard piping apply. This
works out to a total direct cost factor of 27 percent of equipment purchase price. An additional
50 percent factor is applied for the estimated cost of labor for equipment installation.
4-4
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4—LCCA Methodology
When a piece of equipment is replaced it is assumed that direct cost factors for
mobilization and control and instrumentation apply, which yields a total direct cost factor for
material replacement of 13 percent of the purchased equipment price. It is assumed that labor
costs for material replacement are 40 percent of the equipment purchase price. Direct cost factors
for site preparation and lab and administration building are assumed not to apply for plant
renovations and equipment replacement. Equation 11 demonstrates the basic method used to
calculate direct costs from purchased equipment prices.
Level 1 Direct Cost
Direct Cost Factor = - - - :
Level 1 Purchased Equipment Cost
Equation 11
where:
Direct Cost Factor (%) = Direct cost factor for each direct cost element, see Table 4-1
below
Level 1 Purchased Equipment Cost (2014 $) = Equipment price paid by the WWTP
Level 1 Direct Cost (2014 $) = Direct cost in excess of purchased equipment price
Table 4-1. Direct Cost Factors
Direct (.lost Klcmcnls
Direct Cost Knctor (% ol'Purchiisctl
Kquipmcnt Cost)
Mobilization
5%
Site Preparation
7%
Site Electrical
15%
Yard Piping
10%
Instrumentation and Control
8%
Lab and Administration Building
12%
Reference:
CAPDETWorks™
4.3.4 Indirect Costs
Indirect costs typically include land costs, legal costs, engineering design fee, inspection,
contingency, technical costs, interest during construction, and profit. Table 4-2 lists indirect cost
factors as reported by CAPDETWorks™ engineering cost estimation software. Land costs and
interest during construction do not apply to this project and are excluded from the analysis. The
upgraded facility will be located completely within the boundaries of lands currently held by
BEGWS. The upgrades are set to be funded through a combination of grants and zero interest
loans made available by New York State. Total indirect costs are the sum of all individual
indirect costs as calculated in Equation 12. Indirect cost factors are applied to the sum of
purchase price and direct costs. Indirect costs are assumed to apply both to the construction of
4-5
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4—LCCA Methodology
new units and major renovation and upgrade projects. No indirect costs are assumed to be
associated with material replacement.
Remaining Indirect Costs = Indirect Cost Factorx(Purchased Equipment Cost+Direct Cost)
Equation 12
where:
Remaining Indirect Cost (2014 $) = Indirect costs associated with miscellaneous costs,
legal costs, engineering design fee, inspection costs, contingency, technical, and profit
Indirect Cost Factor (%) = Indirect cost factor for each indirect cost element, see Table
4-2 below
Purchased Equipment Cost = Total purchased equipment cost
Direct Cost (2014 $) = Total direct costs
Table 4-2. Indirect Cost Factors
Indirect Cost Elements
Indirect Cost Kuctor (% of
purchased equipment cost)
Miscellaneous Costs
5%
Legal Costs
2%
Engineering Design Fee
15%
Inspection Costs
2%
Contingency
10%
Technical
2%
Profit
15%
Reference:
CAPDETWorks™
4.3.5 Total Annual Costs
The total annual costs include the operation and maintenance labor, materials, chemicals,
and energy. Total annual costs are calculated using Equation 13.
Total Annual Costs = Operation Costs + Replacement Labor Costs +
Materials Costs + Chemical Costs + Energy Costs
Equation 13
where:
Total Annual Costs (2014 $/year) = Total annual operation and maintenance costs
Operation Costs (2014 $/year) = Labor costs for manual labor required to operate the
WWTP for a year, including operation, administrative, laboratory labor, and routine
equipment maintenance
4-6
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4—LCCA Methodology
Replacement Labor Costs (2014 $/year) = Contract labor costs required to replace
equipment over the WWTP lifespan
Materials Costs (2014 $/year) = Materials costs for operation and maintenance of the
WWTP for a year, including equipment replacement
Chemical Costs (2014 $/year) = Chemical costs for chemicals required for WWTP
operation (e.g., PAC, polymer) for a year
Energy Costs (2014 $/year) = Electricity costs to run the WWTP for a year
Operational labor cost associated with primary and secondary treatment remain the same
for the upgraded treatment plant with additional personnel requirements for both the AD and
composting unit. Regular plant maintenance is assumed to be carried out by BEGWS personnel,
and as such does not require additional labor costs beyond their annual salary and benefits. Labor
for equipment replacement is assumed to require contractor labor. Maintenance costs per unit, as
calculated by GHD, are the primary source of maintenance cost data used in this analysis.
GHD's original maintenance costs include labor. This analysis uses actual plant labor costs as
the source of maintenance labor costs, and therefore only 50 percent of the original GHD
maintenance costs are included to approximate the material portion of maintenance costs.
4.3.6 Net Present Value
NPV for the upgraded system is calculated using Equation 14.
Net Present Value=S(Costx/(l+i)x)
Equation 14
where:
NPV (2014 $) = Net present value of all costs and revenues necessary to construct and
operate the WWTP
Costx = Cost in future year x
i (%) = Real discount rate
x = number of years in the future
A real discount rate of 5 percent is used in the base cost scenario. The planning period of
the LCCA is 30 years.
A standard payback period is calculated using Equation 15 for both the composting
facility and the AD unit. In determining payback, the value of avoided energy production is
attributed to the AD. Compost value is attributed to the composting facility. A payback period
will only exist if unit annual revenue exceeds annual costs.
Payback Period = Costc0nst/Revenueannuai
Equation 15
4-7
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4—LCCA Methodology
4.3.7 LCCA Cost Assumption Scenarios
Many assumptions are required to perform an LCCA. These assumed parameter values
can have a significant effect on total life cycle costs or the cost performance of any particular
unit within the WWTP. Table 4-3 documents assumptions that comprise the low, base, and high
cost scenarios covered in the sensitivity analysis. The low cost scenario corresponds to parameter
values that will yield a lower system NPV than the base cost scenario, while the high cost
scenario corresponds to parameter values that lead to a high estimate of system NPV. The low,
base and high cost scenarios define an envelope of expected NPV estimates for the upgraded
treatment system.
The study period remains consistent across scenarios, while the real discount rate varies
between 3 and 6 percent between the high cost and low cost scenarios. A lower discount rate
indicates that a higher value is placed on money in the future, which increases the contribution of
future operational costs and material replacement to NPV. The interest rate is assumed to be zero
percent across all scenarios given the funding sources that are available for this project. The low
cost scenario explores the effect of increased electricity rate, increased disposal fee for high
strength organic waste, and a rise in the price of natural gas on plant NPV. The low cost scenario
also assumes that a market for all the potential biogas heat output can be found. The base and
high cost scenario assume that avoided electricity is valued at the current electricity rate paid by
BEGWS, $0,051. In the high cost scenario, dieselfuel costs are assumed to rise to $3.50 per
gallon. In both the base and high cost scenarios, only the portion of biogas heat that can be used
within the facility is considered to avoid natural gas production. The remainder of biogas heat is
wasted until a suitable market can be found, and generates no revenue or avoided value. The fee
generated per yard of finished compost increases from 0, to 5, to 10 dollars per cubic yard
between the high and low cost scenarios. More compost and biogas revenue are generated in the
low cost scenario. The lower section of Table 4-3 lists the assumed escalation factors for various
annual and periodic costs.
4-8
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4—LCCA Methodology
Table 4-3. Parameter Values Varied in the Low, Base, and High Cost Scenarios
Parameter Value
Low Cost
Scenario
Base Cost
Scenario
High Cost
Scenario
Planning Period (years)
30
30
30
Real Discount Rate (%)
6%
5%
3%
Interest Rate (%)*
0%
0%
0%
Electricity Cost (S/kWh)1
0.077
0.051
0.077
Electricity Revenue ($/kWh)
0.077
0.051
0.051
Diesel Cost ($/gal)
2.00
2.70
3.50
Natural Gas Cost (S/MCF)
4.50
3.84
3.84
Septage Disposal Fee ($/gallon)
0.010
7.00E-3
7.00E-3
High Strength Organic Waste ($/gallon)2
0.150
0.060
0.030
Compost Revenue ($/yd3)3
10.0
5.00
_
Landfill Tipping Fee ($/wet ton)1
50.8
50.8
50.8
Fraction of Biogas Heat Valued
Total Heat
Potential
Facility Use
Facility Use
Material and Maintenance Escalation
2%
3%
4%
Labor Escalation
1%
2%
3%
Taxes/Salvage Escalation
0%
0%
0%
Operations General Escalation
1%
2%
3%
Fee Escalation
1%
2%
2%
Energy Escalation
2%
2%
3%
References & Notes:
1 GHD2016
2 Appleton and Rauch-Williams 2017, fee received by WWTP
3 Williams 2009
4-9
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5—LCA and LCCA Results by Treatment Stage
5. LCA and LCCA Results by Treatment Stage
This section presents comparative LCA results for the legacy and upgraded wastewater
treatment systems by impact category.
5.1 Guide to Results Interpretation
Results for this project were calculated for all combinations of the following parameters.
Baseline results, presented in Section 5, represent a subset of these parameters, with the full
range of results being presented within the sensitivity and scenario analysis of Section 6. While
the full range of results is presented within the report, not all possible parameter results'
combinations are shown.
Model Parameters varied within the Analysis:
• Feedstock Scenarios - Results are available for the low, base and high feedstock
scenarios for the upgraded WWTP, which demonstrates the effect of accepting
additional high strength organic wastes on impact potential of the treatment system.
Feedstock quantities associated with the scenarios are presented in Table 3-25.
• Anaerobic Digestion - Results are calculated for a set of parameters defining low,
base, and high operational performance of the AD units, as presented in Table 3-26.
• Composting Method - Results are calculated assuming either a windrow or ASP
composting system. The windrow system is presented as the baseline scenario in
Section 5
• Landfill Methane Capture System - The performance of the methane capture system
at the landfill in the Bath region of NY is significantly higher than the national
average landfill methane capture system. Results have been calculated for both
systems and are presented in Section 6.1. The Bath landfill values are presented as
baseline results in Section 5.
• Compost Bulking Material - The sensitivity analysis explores the effect of including
or excluding compost bulking material from the calculation of cumulative potential
impacts. Calculation of results including the impact associated with bulking material
is presented as the baseline scenario.
The above model parameters are varied over the ranges defined in Section 3 to
accurately convey the potential variability in impact results that can be realized by wastewater
treatment systems of the types considered in this analysis. The trends observed and the key
variables that drive environmental impacts, as described in Sections 5 and 6, can be used by
facilities or during the design process to estimate potential impacts and areas for potential
improvement by choosing results associated with the parameter combinations that most closely
match those of their specific system of interest.
5-1
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5—LCA and LCCA Results by Treatment Stage
Throughout this section, results calculated at the unit process level have been aggregated
by treatment stage, as shown in Table 2-6. Eutrophication potential, global warming potential,
and cumulative energy demand also include impact results aggregated according to the process
categories listed in Table 2-7. Results presented in Section 5 refer to the base case scenario for
feedstock consumption, anaerobic digester operational performance, and composting and landfill
emissions. Sensitivity analyses for these scenarios are conducted in Section 6.
The relationship between gross and net impact is presented in Equation 16. Impact
contributions from individual treatment stages or processes are calculated relative to gross
environmental impact results. This method is preferred such that impact contributions do not
exceed 100 percent, and the percent reduction in impact attributable to avoided products is
calculated relative to the gross impact that avoided products serve to reduce. This generalized
calculation is presented in Equation 17, and an example calculation specific to avoided product
contribution for cumulative energy demand of the upgraded WWTP is presented in Equation 18.
Percent contributions calculated based on net impact yield higher values, which can exceed 100
percent when environmental credits (i.e., avoided products), are associated with the investigated
system. The two calculation methods yield identical values if no environmental credits are
associated with an impact category, which is typically not the case in this analysis.
Net Impact = Gross Impact + (—Avoided Product Credit)
process impact
Process Impact Contribution or Reduction =
gross impact
Equation 16
Upgraded WWTP CED Avoided Product Impact Reduction =
Equation 17
avoided product credit — 6.96 MJ
gross CED 16.5 MJ
= —42 Percent Reduction in Gross CED
Equation 18
Changes in impact between the legacy and upgraded system are calculated relative to the
legacy system using Equation 19.
Upgraded Impact — Legacy Impact
Relative Change =
Legacy Impact
Equation 19
Baseline results for both the legacy and upgraded WWTP include the environmental
burdens attributable to 1 MGD of municipal wastewater. The legacy and upgraded WWTPs
accept an additional 8,000 and 16,000 GPD of septic and portable toilet waste, respectively. The
additional burdens of treating this waste are allocated equally to the 1 MGD of municipal
wastewater. No high strength organic waste is associated with either system in the baseline
scenario.
5-2
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5—LCA andLCCA Results by Treatment Stage
5.2 Eutrophication Potential
Given the goal of improving nutrient removal performance, eutrophication is a critical
metric for measuring the comparative environmental performance of the legacy and upgraded
wastewater treatment systems. Figure 5-1 presents net eutrophication potential results grouped
by treatment stage, while Figure 5-2 presents impact results according to process category. Total
values in both figures refer to net impact results. Please refer to Table 2-6 for a reminder of
which treatment processes contribute to each treatment stage.
Eutrophication impacts are dominated by effluent release for both the legacy and the
upgraded system. Effluent release contributes 94 percent to eutrophication impact for the legacy
system, and 71 percent to the upgraded system. Nitrogen deposition resulting from fossil fuel
combustion for electricity production and emissions to water resulting from land application of
composted biosolids are the other main contributors to eutrophication impacts. Additional
nutrient removal accomplished with the introduction of the upgraded MLE secondary treatment
unit leads to a 37 percent reduction in net eutrophication potential impact per cubic meter of
wastewater treated. Avoided fertilizer production from land application of bio so lids and avoided
energy production from AD biogas recovery reduce gross eutrophication impact for the upgraded
treatment system by 2 and 3 percent, respectively. This study assumes no leaching of nutrients to
surface or groundwater from the composting facility.
TJ
S-H
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5—LCA andLCCA Results by Treatment Stage
TJ
-------
5—LCA andLCCA Results by Treatment Stage
TJ
S-H
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5—LCA andLCCA Results by Treatment Stage
5.4 Global Warming Potential
Figure 5-5 presents the global warming potential results grouped according to treatment
stage, while Figure 5-6 presents results according to process category. For the base scenario, the
upgraded WWTP demonstrates a net global warming potential that is approximately 25 percent
greater than that realized by the legacy system. This is despite a 21 percent reduction in gross
impact due to avoided electricity, natural gas, and fertilizer consumption from bio gas recovery
and agricultural reuse of compost. The environmental credit for these avoided products is fully
visible in Figure 5-6. The figure also shows the carbon credit that results from carbon storage in
soil due to land application of compost that reduces gross global warming potential by 24
percent. Approximately 42 percent of impact is due to composting emissions of methane and
nitrous oxide. In the base scenario, 1,500 and 54 metric tons of elemental carbon and nitrogen,
respectively, enter the composting facility each year either within the digested sludge or in the
supplemental organic materials. The base scenario emission factors assume that 0.82 and 2.7
percent of incoming carbon and nitrogen are lost as methane and nitrous oxide, respectively,
which is in the middle of the expected range as reported by the IPCC (2006). Emissions of
methane and nitrous oxide from the landfill contribute 17 percent of impact for the legacy
system. Due to uncertainty concerning the magnitude of these emissions, and their importance to
the overall environmental impact of the system, low and high emissions scenarios are analyzed
in the sensitivity analysis to explore the effect on environmental impacts per cubic meter of
wastewater.
Legacy Upgraded
¦ Preliminary/Primary ¦ Biological Treatment
¦ Facilities ¦ Sludge Handling and Treatment
¦ Sludge Disposal ¦ Effluent Release
• Total
Figure 5-5. Global warming potential results by treatment stage.
5-6
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5—LCA andLCCA Results by Treatment Stage
TJ
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5—LCA andLCCA Results by Treatment Stage
TJ
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5—LCA andLCCA Results by Treatment Stage
TJ
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5—LCA andLCCA Results by Treatment Stage
0.35
0.30
0.25
0.20
0.15
0.10
o"
0.05
0.00
-0.05
TJ
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5—LCA andLCCA Results by Treatment Stage
TJ
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5—LCA andLCCA Results by Treatment Stage
TJ
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5—LCA andLCCA Results by Treatment Stage
Material ($/yr)
6%
Replacement Labor
(S/yr)
1%
Chemical ($/yr)
Energy ($/yr)
3%
40,
Operation ($/yr)
Construction ($)
46%
Total NPV:
$37,145,000
Figure 5-12. Base life cycle costs by cost category for upgraded WWTP.
5-13
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6—Scenario Sensitivity Analysis
6. Scenario Sensitivity Analysis
The first section in the sensitivity analysis provides an isolated look at the effect of low,
medium (i.e., base), and high estimates of the emission factors for composting and landfilling
GHG emissions on global warming potential impact. The second sensitivity analysis is employed
to determine the impact of AD and compost feedstock scenarios on life cycle environmental
impacts and costs of operating a 1 MGD wastewater treatment system. The analysis highlights
the range in environmental impacts that can result from variations in AD feedstock inputs and
operational performance as outlined in Section 3.3.9. Figures in Section 1.1 also include the
effect of compost and landfill emissions scenarios. Section 6.3 isolates the effects of including or
excluding composting amendment material from the system boundaries and the effect that this
decision has on cumulative global warming potential impacts of the WWTP. Results of the
LCCA scenario assumptions on system costs over 30 years are presented in Section 6.5
6.1 Landfill and Compost Emission Scenarios
Figure 6-1 shows the effect of low, base, and high compost and landfill emission
scenarios on total global warming potential impact results for the legacy and upgraded WWTPs.
The figure also includes alternative scenarios, utilizing Base Feedstock-Base AD scenario
assumptions, that represent the use of national average landfill gas capture rates and an ASP
composting system in place of the windrow system and the Bath regional landfill values. The
figure shows the contribution of each life cycle stage to net global warming potential impact
results for the entire treatment system. For the upgraded treatment system, EOL processes
include both composting and land application, while for the legacy treatment plant EOL includes
only the landfilling process. The figure highlights the wide range of potential impacts associated
with composting emissions, the sensitivity of global warming potential impact to this parameter,
and the potential negative impact of a poorly managed composting system. Likewise, the figure
highlights the potential environmental benefit that is possible given a well-managed composting
operation.
Under the base EOL emissions scenario, the ASP composting system demonstrates the
lowest net EOL global warming potential impact given that the carbon credit associated with
land application nearly balances out the GHG emissions released during the composting process.
The biofilter that is part of the ASP system is assumed to effectively eliminate CH4 emissions,
however the system still produces N2O. The BEAM model, which can be used to estimate global
warming potential impacts associated with wastewater treatment, indicates that N2O emissions
can also be eliminated if the solids content of the composting pile is greater than 55 percent
(SYLVIS 2011). However, the recommended moisture content of a composting pile is between
50 and 60 percent, placing 55 percent solids content outside of the moisture range recommended
in practice (Pawlowski et al. 2013, Chardoul et al. 2011). CO2 emissions associated with all
systems are assumed to be of biogenic origin, and therefore do not contribute to global warming
potential. In the base emissions' scenario, the windrow composting system has impacts that fall
between those of the Bath regional landfill and national average landfill. Under the low
emissions scenario, the windrowing system demonstrates the lowest net EOL global warming
potential, followed closely by the ASP system. Within the low EOL emissions scenario, all EOL
options demonstrate a net negative impact on global warming potential due to the carbon
sequestration credit associated with all options. The high EOL emission scenario leads to notable
6-1
-------
6—Scenario Sensitivity Analysis
contributions of this life cycle stage to net global warming potential impacts. The windrow
composting system has the greatest potential contribution the GHG emissions, which indicates
the importance of sound management if this system is to be employed without negative
environmental effects. The biofilter emission control system of the ASP composting method
leads to lower variability between the emission scenarios and the lowest net EOL global
warming potential impacts under the high EOL emission scenario making it an attractive option
for communities. The impact of the ASP system is dependent on the composition of the local
electricity grid as it uses forced aeration to maintain aerobic conditions. The Bath regional
electricity grid relies on a relatively clean set of generating technologies, and it is possible that
the ASP system will demonstrate higher relative global warming potential impact in other
regions of the country.
6-2
-------
6—Scenario Sensitivity Analysis
2.5
TJ
-------
6—Scenario Sensitivity Analysis
6.2 Feedstock, AD, and End-of-Life Scenario Sensitivity
Three feedstock scenarios are analyzed in the sensitivity analysis, as outlined in Table
3-25. The base scenario assumes that the upgraded WWTP accepts 14,000 gallons of septic tank
waste and 2,000 gallons of portable toilet waste on top of the approximately 93,000 gallons of
combined primary and WAS that result from the daily treatment of 1 MGD of residential,
commercial, and industrial sewage. The high feedstock scenario assumes that the facility accepts
an additional 8,000 GPD of high strength organic waste, and while this is a relatively modest
quantity of additional waste, it provides a significant boost to available VS for biogas production.
Each feedstock scenario is analyzed assuming low, base, and high AD operational
performance parameters. In general, the high scenario corresponds to the greatest biogas and
energy recovery as a result of more optimistic assumptions regarding biogas production rates, VS
destruction, methane content of the resulting gas, and greater electrical efficiency of the CHP
system.
The figures in this section list the combined feedstock and AD scenario names. The
portion of the scenario name preceding the hyphen indicates the feedstock scenario listed in
Table 3-25. The latter portion of the name, following the hyphen, refers to the AD operational
assumptions listed in Table 3-26. Bar coloration is used to differentiate the landfill and compost
emissions scenario results for each Feedstock-AD scenario. Results are presented for
eutrophication potential, cumulative energy demand, global warming potential, particulate matter
formation potential, and water use. Negative impact results represent a net environmental benefit
attributable to the wastewater treatment system. The general trends exhibited by these five
impact categories are representative of results for the other LCIA categories, and a description of
these similarities is included in the discussion.
Figure 6-2 presents net eutrophication potential results for the legacy system, the 9
upgraded Feedstock-AD scenarios, and the landfill and compost emission scenarios. The
feedstock and AD scenarios demonstrate a limited impact on eutrophication results. The visible
effect is due largely to composting and land application. A portion of the ammonia that volatizes
from the compost pile will eventually find its way into the freshwater system as a result of
atmospheric deposition. Nitrogen and phosphorus emissions to both land and water result from
land application. The magnitude of this effect for any given Feedstock-AD scenario yields an
approximate 10 percent increase in the net impact result. From the figure, it appears that
increased operational performance of the AD also exerts a slight positive influence on
eutrophication potential impacts, however this is partially a consequence of modeling a static
C:N ratio for the incoming digested biosolids across all feedstock scenarios. Variable carbon and
nitrogen contents of high strength organic waste could lead to greater relative nitrogen content
depending upon the feedstocks accepted for co-digestion. Taking this into account would affect
eutrophication potential results.
6-4
-------
6—Scenario Sensitivity Analysis
100%
3 90%
& 80%
>> 70%
§> 60%
H-)
C4—I
o
S3
50%
40%
30%
20%
10%
0%
-¦I
V
/
^ ^ ^ ^ ^ >v?
s ~
&
Low Emissions Base Emissions High Emissions
Scenario Names: Feedstock-AD Scenario
Figure 6-2. Effect of feedstock and anaerobic digestion sensitivity scenarios on
eutrophication potential results.
Figure 6-3 presents net cumulative energy demand results for the legacy system, the 9
upgraded Feedstock-AD scenarios, and the landfill and compost emission scenarios. In the Base
Feedstock-Base AD scenario, net cumulative energy demand impacts for the upgraded system
exceed those of the legacy plant by between 3 and 7 percent depending upon the composting
emissions scenario. Net cumulative energy demand decreases as the upgraded WWTP accepts
more feedstock and generates greater quantities of avoided electricity and natural gas. The results
are more sensitive to the assumed changes in AD operational performance than they are to the
feedstock scenarios. The figure shows that through a combined approach of maximizing AD
operational performance and accepting additional high strength organic wastes for biogas
production it is possible to generate net negative impacts in the cumulative energy demand
impact category. The general pattern shown in the figure below is representative of fossil
depletion potential results. The reason for this is that impacts in both categories are strongly
linked to energy production and consumption.
6-5
-------
6—Scenario Sensitivity Analysis
200%
s
& 150%
& 100%
h L ¦ II
Ph O/o HI aaa
I / sP* J # ™
-------
6—Scenario Sensitivity Analysis
illustrate the importance of avoiding high composting emissions if it is desired not to increase the
global warming potential impacts attributable to the WWTP. All scenarios realize a relative
increase in global warming potential impact, relative to the legacy system, under the high EOL
emissions scenario. This relative increase is at a minimum of 25 percent for the Base Feedstock-
High AD scenario and increases to a maximum of 178 percent for the High Feedstock-Low AD
performance scenario. In general, the figure shows that increased operational performance of the
AD leads to a reduction in net global warming potential impacts, but that the realization of true
benefits is only possible when paired with a well-managed composting system.
o
(D
J
O
o
S-H
Ph
>
&
300%
250%
200%
150%
100%
50%
0%
-50%
-100%
-150%
V
<§>
A
y*
<$
&
&
~ ~
# #
-200%
Low Emissions Base Emissions High Emissions
Scenario Names: Feedstock-AD Scenario
Figure 6-4. Effect of feedstock and anaerobic digestion sensitivity scenarios on global
warming potential results.
Figure 6-5 presents net particulate matter formation potential results for the legacy
system, the 9 upgraded Feedstock-AD scenarios, and the landfill and compost emission
scenarios. Particulate matter impacts are dramatically affected by the Feedstock-AD scenarios.
For the base scenario, particulate matter formation potential results of the upgraded system
exceed the legacy plant's impact results by between 5 and 17 percent, depending upon the
emissions scenario. High operational performance of the AD for the base feedstock scenario
produces an almost net zero impact due to the benefits of avoided electricity and natural gas
production. Low operational performance of the AD leads to a significant dampening of avoided
energy production, and an associated increase in particulate matter formation potential as a result
of lower avoided energy credits. Three of the Feedstock-AD scenarios generate net negative
impact results, which indicates a reduction in environmental burdens as a result of wastewater
treatment with AD. Similar patterns of relative results to those described are exhibited for smog
6-7
-------
6—Scenario Sensitivity Analysis
formation potential and acidification potential, which like particulate matter formation potential,
are strongly linked to electricity use and generation.
+-»
&
o
o
-------
6—Scenario Sensitivity Analysis
150%
-2 100%
o
4)
J
O
-100%
V
&
$
^ NyP
~ ~ ~ ~
-150%
¦ Low Emissions ¦ Base Emissions
Scenario Names: Feedstock-AD Scenario
High Emissions
Figure 6-6. Effect of feedstock and anaerobic digestion sensitivity scenarios on water use
results.
Table 6-1 shows impact results for the upgraded system relative to legacy impact results
for all scenarios and impact categories. As an example of how to interpret the table, when
referencing the Base Feedstock-Base AD scenario, the upgraded system generates a net global
warming potential impact result that is 25 percent greater than that of the legacy system. Other
values can be read in a similar manner.
Table 6-2 presents total annual LCI A results for the legacy system and all sensitivity
scenarios analyzed for the upgraded treatment plant. Negative values in the table indicate a net
environmental benefit for the treatment system and Feedstock-AD scenario to which they apply.
For the legacy system, we can see that approximately 1 million kg of CO2 equivalent emissions
are released annually by the WWTP, which equates to approximately 191 kg of CO2 equivalent
emissions per resident in the Town of Bath. Potential GHG emissions for the upgraded treatment
plant range between -1 and 4.3 million kg of CO2 equivalents depending upon the specific
assumptions of the sensitivity scenario. The breadth of this range highlights the importance of
the decisions facing treatment plant personnel and community managers regarding technology
selection and WWTP management. To put these numbers into context, net GHG emissions in
2015 were approximately 6,500 million metric tons of CO2 equivalent emissions, which
translates into 20.5 tons per U.S. citizen (U.S. EPA 2017). This indicates that wastewater
treatment emissions can contribute between -1 and 4 percent of average per capita GHG
emissions for a resident in Bath, NY.
6-9
-------
6—Scenario Sensitivity Analysis
Table 6-1. Percent Change in Impacts between the Upgraded and Legacy WWTPs1
Impact Category
Global Warming Potential -
kg CO2 eq
Eutrophication Potential - kg N eq
Cumulative Energy Demand - MJ
Particulate Matter Formation
Potential - kg PM2.5 eq
Emissions Scenario2
Low
Base
High
Low
Base
High
Low
Base
High
Low
Base
High
Legacy
-
-
-
-
-
-
-
-
-
-
-
-
Upgraded, Base-Low
14%
57%
97%
-36%
-34%
-33%
55%
57%
59%
35%
42%
49%
Upgraded, Base
-27%
25%
68%
-38%
-37%
-36%
3%
5%
7%
5%
11%
17%
Upgraded, Base-High
-108%
-28%
25%
42%
41%
-40%
-98%
-97%
-97%
-100%
-96%
-92%
Upgraded, Medium-Low
-37%
61%
134%
-32%
-31%
-29%
36%
38%
40%
20%
28%
37%
Upgraded, Medium-Base
-120%
2%
83%
-36%
-35%
-33%
-60%
-59%
-58%
-35%
-29%
-22%
Upgraded, Medium-High
-166%
-32%
53%
41%
40%
-39%
-135%
-135%
-135%
-160%
-156%
-151%
Upgraded, High-Low
-128%
57%
178%
-28%
-26%
-24%
-11%
-9%
-7%
-11%
0%
10%
Upgraded, High-Base
-199%
0%
124%
-34%
-32%
-30%
-113%
-112%
-112%
-113%
-106%
-98%
Upgraded, High-High
-258%
-49%
78%
42%
40%
-38%
-214%
-215%
-216%
-283%
-280%
-276%
Impact Category
Smog Formation Potential - kg O3 eq
Acidification Potential - kg SO2 eq
Water Use - m3 H20
Fossil Depletion Potential - kg oil eq
Emissions Scenario2
Low
Base
High
Low
Base
High
Low
Base
High
Low
Base
High
Legacy
-
-
-
-
-
-
-
-
-
-
-
-
Upgraded, Base-Low
34%
37%
40%
44%
63%
82%
-111%
-111%
-110%
66%
68%
70%
Upgraded, Base
5%
7%
9%
14%
31%
48%
-104%
-103%
-103%
7%
9%
10%
Upgraded, Base-High
-101%
-101%
-101%
-90%
-77%
-61%
-108%
-108%
-107%
-99%
-98%
-98%
Upgraded, Medium-Low
19%
21%
24%
34%
58%
85%
-148%
-147%
-147%
46%
49%
51%
Upgraded, Medium-Base
-37%
-35%
-34%
-22%
-1%
23%
-139%
-138%
-137%
-64%
-63%
-62%
Upgraded, Medium-High
-161%
-163%
-164%
-144%
-127%
-107%
-142%
-142%
-142%
-132%
-132%
-132%
Upgraded, High-Low
-13%
-11%
-9%
11%
43%
79%
-201%
-200%
-200%
-5%
-3%
-1%
Upgraded, High-Base
-116%
-116%
-116%
-93%
-65%
-34%
-187%
-187%
-186%
-112%
-112%
-111%
Upgraded, High-High
-286%
-290%
-293%
-260%
-239%
-213%
-189%
-189%
-188%
-206%
-207%
-207%
1 Percent change is calculated relative to the legacy system ([ImpactuPgraded/InipactiegaCy]-1*100)
2 Upgraded treatment system names refer to the respective Feedstock-AD scenario.
6-10
-------
6—Scenario Sensitivity Analysis
Table 6-2. Annual LCIA Results by Feedstock, AD, and Emissions' Scenarios
Impact Category
Global Warming Potential - kg CO2
eq
Eutrophication Potential - kg N eq
Cumulative Energy Demand - MJ
Particulate Matter Formation
Potential - kg PM2.5 eq
Emissions Scenario1
Low
Base
High
Low
Base
High
Low
Base
High
Low
Base
High
Legacy
635,695
1,071,006
1,537,446
33,764
33,736
33,715
12,726,175
12,537,715
12,398,843
5,777
5,653
5,556
Upgraded, Base-Low
726,775
1,683,282
3,032,516
21,772
22,103
22,462
19,668,863
19,714,209
19,760,647
7,777
8,009
8,271
Upgraded, Base
462,406
1,342,547
2,578,981
21,036
21,333
21,664
13,157,618
13,198,460
13,240,297
6,065
6,275
6,511
Upgraded, Base-High
-50,486
769,442
1,921,179
19,493
19,769
20,087
302,891
341,785
381,647
20
221
444
Upgraded, Medium-Low
400,341
1,728,670
3,595,535
22,919
23,364
23,875
17,264,359
17,327,336
17,391,833
6,906
7,233
7,587
Upgraded, Medium-Base
-125,470
1,097,189
2,812,692
21,678
22,092
22,547
5,061,231
5,117,590
5,175,302
3,737
4,032
4,360
Upgraded, Medium-High
422,088
728,005
2,349,982
19,897
20,291
20,719
-4,452,492
-4,398,372
-4,342,939
-3,443
-3,156
-2,855
Upgraded, High-Low
-177,283
1,676,166
4,276,425
24,371
24,993
25,698
11,319,726
11,407,380
11,497,175
5,169
5,625
6,124
Upgraded, High-Base
-626,162
1,070,371
3,450,667
22,279
22,845
23,495
-1,605,024
-1,527,567
-1,448,245
-757
-345
115
Upgraded, High-High
-1,006,275
548,512
2,735,152
19,730
20,255
20,849
-14,544,060
-14,471,122
-14,396,387
-10,555
-10,175
-9,755
Impact Category
Smog Formation Potential- kg O3 eq
Acidification Potential - kg SO2 eq
Water Use - m3 H2O
Fossil Depletion Potential - kg oil eq
Emissions Scenario1
Low
Base
High
Low
Base
High
Low
Base
High
Low
Base
High
Legacy
408,286
399,388
392,852
43,505
42,551
41,860
1,725
1,722
1,720
240,362
236,977
234,476
Upgraded, Base-Low
548,442
548,802
549,437
62,742
69,222
76,366
-186
-186
-172
397,881
398,779
399,691
Upgraded, Base
427,670
428,002
428,568
49,547
55,544
62,148
-72
-58
-58
257,240
258,056
258,885
Upgraded, Base-High
-3,288
-2,998
-2,459
4,436
9,990
16,152
-136
-136
-122
3,565
4,338
5,126
Upgraded, Medium-Low
484,554
485,037
485,908
58,404
67,426
77,374
-821
-807
-807
350,752
351,996
353,281
Upgraded, Medium-Base
258,484
258,926
259,727
33,976
42,307
51,509
-669
-655
-641
87,419
88,538
89,671
Upgraded, Medium-High
-250,940
-250,512
-249,752
-19,343
-11,564
-2,970
-728
-728
-714
-77,664
-76,600
-75,495
Upgraded, High-Low
354,787
355,478
356,693
48,207
60,794
74,722
-1,740
-1,726
-1,712
228,446
230,187
231,956
Upgraded, High-Base
-65,270
-64,662
-63,571
3,151
14,702
27,468
-1,497
-1,497
-1,483
-29,292
-27,758
-26,183
Upgraded, High-High
-759,051
-758,485
-757,462
-69,691
-59,135
-47,474
-1,528
-1,528
-1,514
-253,911
-252,460
-250,981
1 Upgraded treatment system names refer to the respective Feedstock-AD scenario.
6-11
-------
6—Scenario Sensitivity Analysis
6.3 Bulking Material Amendment Sensitivity
The sensitivity of global warming potential impact results to EOL emissions warrants
consideration of the effect of assumptions regarding compost bulking materials contribution to
cumulative treatment impacts. Both windrow and ASP composting systems require
bulking/amendment material to hit target ranges for moisture, carbon, and nitrogen content
within the compost pile. Given this requirement, the bulking material can be considered a
necessary input to biosolids composting, which provides a rationale for attributing the associated
emissions to the wastewater treatment system. However, given that much of this bulking material
is municipal yard waste, which may have been composted regardless of the chosen biosolids
disposal method, there exists an alternate rationale for excluding emissions associated with the
bulking material from the environmental burdens attributable to the WWTP. Figure 6-7 shows
the effect of including and excluding compost bulking material on global warming potential
impact results across the low, base, and high compost emission scenarios for both composting
systems within the Base Feedstock-Base AD scenario.
The figure shows that for the windrow base EOL emissions scenario, the effect of
including or excluding compost amendment from the system has only a minor effect on
cumulative treatment impacts. Two separate forces are responsible for this. The additional
carbon associated with compost amendment material yields both emissions during the
composting process, and a carbon credit when the finished compost is land applied. These factors
balance one another leading to minimal net effect on global warming potential impact results for
the base EOL emission windrow and the high EOL emission ASP compost scenarios. Under the
low emission scenario, where only a small fraction of C and N incoming to composting is
assumed to be liberated as GHGs, the figure shows that global warming potential of the whole
system experiences a net benefit when including compost amendment within the system
boundaries because of the carbon credit that is associated with this material. The opposite is true
under the high EOL emissions scenario where GHG emissions during the composting phase
outweigh the benefit of the carbon credit accrued during land application. The ASP system is less
sensitive to the choice to include or exclude compost amendment from the system boundary, as
the potential range of emissions during the composting stage is narrower than that of the
windrow system.
The fate of bulking material in the absence of a biosolids composting operation is the
primary determinant of whether it is appropriate to attribute the environmental benefits and
burdens of composting amendment to the WWTP. The exclusion of amendment materials from
the system boundary only changes impact attributable to the WWTP, and not the larger
environment, as these emissions will occur regardless of the methodological choice.
6-12
-------
6—Scenario Sensitivity Analysis
2.00
•73 1.80
!
1 1.40
I 1.20
c3
* 1.00
£
& 0.80
c-J
8 0.60
3
ii j .i
Base
Base
Low
Low
High
High
Windrow
ASP
Windrow
ASP
Windrow
ASP
0.40
0.20
0.00
With Amendment ¦ Without Amendment
Figure 6-7. Effect of compost amendment on life cycle global warming potential results for
Low, Base, and High end-of-life emissions scenarios.
6.4 Narrative Impact Scenario
The options presented in the sensitivity section above are intended to inform
environmental managers, municipalities, and WWTP operators of the range of potential
environmental impacts that are possible as upgrades are undertaken to increase effluent quality.
The combination of options can be complex, and this section has been included to illustrate how
a theoretical WWTP could use the results of this analysis to work towards management practices
and system upgrades that realize environmental benefits. Figure 6-8 demonstrates a series of
management steps and equipment upgrades that are undertaken, and the affect that these choices
have on net eutrophication potential, global warming potential, and cumulative energy demand.
In Figure 6-8, legacy, or historical impacts prior to system upgrades, are set to 100
percent and are taken as the reference system. Legacy results in this figure assume national
average landfill performance of the methane capture system. Following the initial upgrades, the
plant realizes an immediate improvement in effluent quality and a corresponding reduction in
eutrophication potential impact. One can imagine that during this time-period, operators are
getting used to the management of both the AD and composting systems. Furthermore, the plant
is not yet utilizing the full capacity of the digesters. Therefore, the plant sees an increase in
global warming potential (High EOL emissions, Low AD scenario). The benefits of avoided
energy production limit the increase in cumulative energy demand to just 3 percent over the
impact of the legacy system. Over time, operators improve management of the composting
system, better balancing pile C:N ratios, hitting target moisture content, and ensuring that pile
temperatures remain elevated (base emissions scenario). After a time, the plant decides to invest
6-13
-------
6—Scenario Sensitivity Analysis
in an ASP composting system to reduce GHG emissions, limit odors, and conserve space. With
this step, the plant realizes an improvement in net global warming potential for the entire
wastewater facility, relative to their historic baseline. Installation of ASP increases relative
cumulative energy demand by 13 percent. Operators locate a steady source of high strength
organic waste, yielding additional biogas production and a reduction in both cumulative energy
demand and global warming potential. At this point the environmental impact of all three impact
categories is reduced relative to the legacy system, despite treatment of a greater quantity of
organic waste and achievement of improved effluent quality. Once operators become
comfortable with the management of co-digestion, they maximize the available capacity of their
digesters and realize a consistent improvement in digester performance (High Feedstock-High
AD). With this final step, the plant begins to produce more energy than they consume, and the
facility approaches climate neutrality.
6-14
-------
6—Scenario Sensitivity Analysis
250%
200%
"3 150%
I
o
CO
o
.B
!Z>
?3
PQ
O
00
Cij
100%
50%
0%
| -50%
Ph
Increase from
Legacy System
199%
100%
103%
102%
115%
I ^
104%
81%
64%
i
59%
64%
k
58%
— mJ
Decrease from
63%
63%
53%
Legacy System
2%
Net Zero Impact (i.e.
Impact Neutral)
-100%
-150%
Legacy System
Impacts
Install Upgraded Improve Compost
Treatment Plant with System Management
Limited Management
of Windrow
Composting System
Install ASP Increase Acceptance Improve AD
Composting of High Strength Management and
Organic Waste Accept the Maximm
Quantity of High
Strength Waste
Cumulative Energy Demand
Global Warming Potential
Eutrophication Potential
Figure 6-8. Narrative environmental impacts of an upgraded wastewater treatment plant.
6-15
-------
6—Scenario Sensitivity Analysis
6.5 LCCA Cost Scenarios
Figure 6-9 presents total NPV value for each Feedstock-AD-cost scenario broken down
by cost category. Parameter values that correspond to each cost scenario are defined in Section
4.3.7. Generally, the low cost scenario corresponds to parameter values that will yield a lower
system NPV than the base cost scenario, while the high cost scenario corresponds to parameter
values that define a high estimate of system NPV. The base case scenario (Base Feedstock-Base
AD-Base Cost) yields an NPV of just over 37 million dollars over a 30-year time horizon. Low
cost assumptions drop the NPV by approximately 12 percent to 32.6 million dollars. A payback
period is calculated separately for the AD and the composting facility, each of which produces a
revenue stream. The payback period calculation for the AD unit includes costs to install and
maintain the CHP system. No payback period is calculated for other elements of the upgraded
facility such as the chemically enhanced primary clarifier or the MLE biological treatment unit.
Neither the AD, nor the composting facility, can payback their initial capital cost under
base case assumptions, as shown in Table 6-3. Given the low value of finished compost there are
no scenarios for which the composting facility can pay for itself over 30 years. With base cost
assumptions, the Medium Feedstock-Base AD, Medium Feedstock-High AD, and all the High
feedstock scenarios can generate a positive payback period which ranges from 850 years for the
Medium Feedstock-Base AD scenario to 45 years for the High Feedstock-High AD scenario.
Assuming the high cost scenario, the Medium Feedstock-Base AD scenario no longer generates a
payback period, and the payback period for the High Feedstock-High AD increases to 70 years.
The high cost scenario raises the calculated NPV of the Base Feedstock-Base AD scenario to
48.7 million dollars. The minimum potential payback period for the AD unit is 16 years. Under
the low cost scenario assumptions, the three High Feedstock scenarios yield an AD payback
period of less than the assumed system lifespan of 30 years.
Table 6-3. Summary Table of Calculated Payback Period for Anaerobic Digester and
Composting Facilities (in years)
Scenario (feedstock
Scenario-Anaerobic
Digester Scenario)
Low Cost Scenario
IJase Cost Scenario
1 ligli Cost Scenario
Anaerobic
Digester
Compost
Facility
Anaerobic
Digester
Compost
Facility
Anaerobic
Digester
Compost
Facility
Base Feed-Low AD
No Payback
No Payback
No Payback
No Payback
No Payback
No Payback
Base Feed-Base AD
No Payback
No Payback
No Payback
No Payback
No Payback
No Payback
Base Feed-High AD
378
No Payback
No Payback
No Payback
No Payback
No Payback
Medium Feed-Low AD
79
No Payback
No Payback
No Payback
No Payback
No Payback
Medium Feed-Base AD
56
No Payback
847
No Payback
No Payback
No Payback
Medium Feed-High AD
34
No Payback
162
No Payback
No Payback
No Payback
High Feed-Low AD
27
No Payback
98
No Payback
No Payback
No Payback
High Feed-Base AD
21
No Payback
65
No Payback
243
No Payback
High Feed-High AD
16
No Payback
45
No Payback
70
No Payback
6-16
-------
6—Scenario Sensitivity Analysis
,000,000
50,000,000
49,500,000
I I
700,000
48,500,000
40,000,000
47,100,000 to,->w,wv/ 47 QQQ QQQ 47,300,000
45,700,000 A 45 500 000 43,600,000
i i
37,60(^)00 37,100
33,100,000 |
32,60( )00
Q
30,000,000
20,000,000
10,000,000
00
36,100
30,800^00
¦
00 35,50®00
I
34,600
28,800,000
27,80(M) 00
00 33,701
25,90
000
000
33,100,000
32,1 (
I
24,00
*
000
22,3(
r
,00(
000
30,900.
19,8(
,00(
j | | / // HI i i i || ^ | || i i i
i
Si Si Si
4? <3
/ t ii i i if f / { // / / / / / / / / / / /t
Low Base High Low Base High Low Base High Low Base High Low Base High Low Base High Low Base High Low Base High Low Base High
Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost Cost
¦ Construction ($) ¦ Operation ($/yr) ¦ Replacement Labor ($/yr) ¦ Material ($/yr) ¦ Chemical ($/yr) ¦ Energy ($/yr) • Total NPV
Figure 6-9. Life cycle cost assessment summary showing results for each Feedstock-AD Scenario by cost scenario.
6-17
-------
7—Conclusions
7. Conclusions
LCA results presented in this study serve to highlight the trade-offs in environmental
performance that can accompany efforts to reduce nutrient loading to receiving waters and
identify several key treatment options and management practices that can be used to effectively
reduce or eliminate trade-offs. As would be expected, the upgraded treatment system realizes a
consequential 25-40 percent reduction in net eutrophication impact dependent on the Feedstock-
AD scenario being considered. Eutrophication impacts are generally less sensitive to scenario
assumptions than are other impact categories more strongly linked to electricity use and process
air emissions. The eutrophication benefit comes at the expense of an approximate 25-30 percent
increase in global warming potential and acidification potential within the base case scenario.
Net smog formation potential, cumulative energy demand, fossil depletion potential, and
particulate matter formation potential results for the upgraded treatment system are between 5
and 11 percent greater than the legacy system in the base scenario, while water use in the base
scenario is reduced dramatically due to avoided fertilizer production and wastewater reuse.
The relative gap in global warming potential impact between the two systems narrows
considerably if low composting emissions are achieved, and widens if composting emissions at
the higher end of the spectrum are assumed. In general, the results demonstrate a strong
sensitivity to the use of composting and associated assumptions regarding EOL emission factors.
The results indicate that considerable effort is warranted to ensure that compost management
practices minimize GHG emissions. Further research determining best management practices
that can be used to ensure low composting emissions and/or alternative strategies for pest and
vector reduction warrant consideration. The ASP composting system demonstrated the potential
to avoid the highest GHG emission rates associated with the windrow system and provides a
good option for communities, particularly when paired with AD as a source of clean electrical
energy. Section 6.1 also demonstrates the environmental benefit of improved landfill methane
gas capture systems, such as the system installed at the Bath regional landfill, as compared to
national average gas capture performance.
The sensitivity analysis clearly demonstrates the benefit of avoided natural gas and
electricity production attributable to the addition of AD as part of the upgraded plant. Marked
reductions in environmental impact are demonstrated in scenarios exploring increased
acceptance of high strength organic waste and the pursuit of exceptional digester operational
performance, even as the plant accepts additional high strength waste relative to quantities
treated in the legacy scenario. Both strategies boost biogas production, and subsequently yield
environmental credits from avoided energy production. Net environmental benefits are
demonstrated to be possible for some of the Feedstock-AD scenarios in seven of eight
environmental impact categories included in this study, with eutrophication potential being the
sole exception where impact results remain positive although reduced in respect to the legacy
system.
The absolute magnitude of LCCA results show a strong dependence on basic parameters
employed within the analysis, specifically the discount rate, escalation rates, and revenue rates
for trucked organic waste and electricity sales. Setting this aside, the analysis demonstrates the
economic benefit on project NPV when high strength organic waste is processed in the AD unit,
particularly if high AD operational performance is achieved. Biogas yields for the high AD
7-1
-------
7—Conclusions
scenario are specifically related to the expected pairing of chemically enhanced primary
treatment with AD, and indicate a potential cost benefit of this combination if pilot scale results
concerning biogas yield can be achieved at full-scale. LCCA results show that achieving an AD
payback period which is shorter than the system lifetime is challenging at this scale. The results
suggest that future work should focus on determining the minimum quantity of high strength
organic waste processing that begins to demonstrate appreciable cost benefits for 1 MGD
facilities and the communities that they serve.
The environmental benefits of installing AD and biosolids reuse programs accrue more
quickly than do financial benefits to the utility and municipality. However, the analysis shows
that even modest quantities of high strength organic waste begin to show a potential cost
justification for the installation of AD, providing a quantitative justification for the concept of
the resource recovery hub, its environmental benefits, and the possibility of an economic
rationale if the capacity of infrastructure is maximized and markets are found for recovered
energy and material resources.
The following next steps are suggested by the results of this analysis:
• Exploration of the effect that increased acceptance of high strength organic waste for
a larger capacity AD would have on cumulative environmental impacts of the Bath
facility, the potential to generate revenue, and the WWTP's position as a resource
recovery hub within the community.
• Investigation of the additional system-wide benefits due to diversion of high strength
organic waste from current disposal methods to treatment at the Bath facility. For
example, industrial waste sources may currently be treated at the industrial facility.
The need for smaller industrial WWTPs and the associated environmental burdens
would be eliminated if the Bath WWTP were to treat this waste.
• Further research into composting emissions, particularly whether there exists
sufficient evidence to tie specific management practices to emission rates in the lower
end of the potential range.
• Analysis of alternative pathogen reduction and vector control strategies that can be
used to produce Class A biosolids.
7-2
-------
8—References
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APPENDIX A: DETAILED LCI CALCULATIONS
AND BACKGROUND INFORMATION
-------
Appendix A - Detailed LCI Calculations and Background Information
Appendix A
Detailed LCI Calculations and Background Information
GHG Calculations
Process based GHG emissions are calculated for biological treatment, aerobic and
anaerobic digestion unit processes, landfilling, composting, and effluent release. In each of these
processes, some portion of influent carbon and nitrogen in wastewater or sludge is released to the
atmosphere in the form of carbon dioxide (CO2), methane (CH4), or nitrous oxide (N2O). CO2
releases are assumed to be biogenic in origin, and therefore do not contribute to global warming
potential impacts. Calculation of CO2 process emissions are therefore not included in this study.
The following sections describe detailed calculation procedures used to estimate process based
GHG emissions in this analysis.
Nitrous Oxide Emissions from Biological Treatment
The methodology for calculating N2O emissions associated with wastewater treatment is
based on estimates of emissions reported in the literature. The guidance provided in the IPCC
Guidelines for national inventories does not provide a sufficient basis to distinguish N2O
emissions from varying types of wastewater treatment configurations, particularly related to
biological nutrient reduction. More recent research has highlighted the fact that emissions from
these systems can be highly variable based on operational conditions, specific treatment
configurations, and other factors (Chandran 2012).
Data collected from 12 WWTPs were reviewed to identify which wastewater treatment
configuration they may best represent (Chandran 2012). Using the emissions measured from
these systems, an average emission factor (EF) was calculated and applied to the modeled data.
The methodological equation is:
N20 PROCESS = TKN (mg/L) x Flow (MGD) x 3.785 L/gal x 365.25 days/yr x 1x10-6 kg/mg
x EF% x 44/14
where:
N2O PROCESS = N2O emissions from wastewater treatment process (kg N2O /yr)
TKN = Concentration of TKN entering biological treatment process (mg/L)
Flow = Wastewater treatment flow entering biological treatment process (MGD)
EF% = average measured % of TKN emitted as N2O, %
44/14 = molecular weight conversion of N to N2O
Annual emissions per system were translated to emissions per m3 of wastewater treated,
using the following calculation.
N2O Process Emissions (kg N2O /m3 wastewater) = N2O PROCESS +
[1 MGD x 365 days/yr x 0.00378541 m3/gal]
A-l
-------
Appendix A - Detailed LCI Calculations and Background Information
Methane Emissions from Biological Treatment
The methodology for calculating CH4 emissions associated with the wastewater treatment
configurations evaluated as part of this study is generally based on the guidance provided in the
IPCC Guidelines for national inventories. CH4 emissions are estimated based on the amount of
organic material (i.e., BOD) entering the unit operations that may exhibit anaerobic activity, an
estimate of the theoretical maximum amount of methane that can be generated from the organic
material (Bo), and a methane correction factor that reflects the ability of the treatment system to
achieve that theoretical maximum. In general, the IPCC does not estimate CH4 emissions from
well managed centralized aerobic treatment systems. However, there is acknowledgement that
some CH4 can be emitted from pockets of anaerobic activity, and more recent research suggests
that dissolved CH4 in the influent wastewater to the treatment system is emitted when the
wastewater is aerated.
For this analysis, some of the wastewater treatment configurations include anaerobic
zones within the treatment system. For these configurations, a methane correction factor (MCF)
was used. The methodological equation is:
CH4 PROCESS = BOD (mg/L) x Flow (MGD) x 3.785 L/gal
x 365.25 days/yr xlxlO-6 kg/mg x Bo x MCF
where:
CH4 PROCESS = CH4 emissions from wastewater treatment process (kg CH4 /yr)
BOD = Concentration of BOD entering biological treatment process (mg/L)
Flow = Wastewater treatment flow entering biological treatment process (MGD)
Bo = maximum CH4 producing capacity, kg CFL^/kg BOD
MCF = methane correction factor (fraction)
For this analysis, there was no relevant MCF provided in the IPCC guidance for
centralized aerobic treatment with the wastewater treatment configurations included in this study.
Instead, MCFs were developed based on GHG emission studies that were conducted at two U.S.
WWTPs. The first study (Czepiel, 1993) evaluated emissions associated with a conventional
activated sludge treatment plant, resulting in an MCF of 0.005, which was used for the legacy
system. The second study (Daelman et al., 2013) evaluated emissions associated with a
municipal treatment plant with biological nutrient removal (specifically nitrification and
denitrification), resulting in an MCF of 0.05, which was used for the upgraded WWTP.
Annual emissions per system were than translated to emissions per m3 of wastewater
treated, using the following calculation.
CH4 Process Emissions (kg CH4/m3 wastewater) = CH4 PROCESS
- [10 MGD x 365 days/yr x 0.00378541 m3/gal]
A-2
-------
Appendix A - Detailed LCI Calculations and Background Information
Nitrous Oxide Emissions from Effluent Release
The methodology for calculating nitrous oxide emissions associated with effluent
discharge is based on the guidance provided in the IPCC Guidelines for national inventories.
N2O emissions from domestic wastewater (wastewater treatment) were estimated based on the
amount of nitrogen discharged to aquatic environments from each of the system configurations,
which accounts for nitrogen removed with sewage sludge.
N20effluent = Neffluent x Flow x 3.785 L/gal x 365.25 days/yr
x 1x10-6 kg/mg x EF3 x 44/28
where:
N20effluent = N2O emissions from wastewater effluent discharged to aquatic
environments (kg N20/yr)
Neffluent = N in wastewater discharged to receiving stream, mg/L
Flow = Effluent flow, MGD
EF3 = Emission factor (0.005 kg N2O -N/kg sewage-N produced)
44/28 = Molecular weight ratio of N2O to N2
Annual emissions per system were translated to emissions per m3 of wastewater treated,
using the following calculation.
N2O Effluent Emissions (kg N20/m3 wastewater) = N2OEFFLUENT
- [1 MGD x 365 days/yr x 0.00378541 m3/gal]
Methane Emissions from Landfilling
The methodology for calculating CH4 emissions associated with landfill disposal are
based on a first-order decay model adapted from an RTI methodology developed for the U.S.
EPA (RTI 2010). The quantity of degradable carbon that breaks down over 100 years is
calculated, using the following equation. An initial fraction of the degradable carbon that
ultimately decomposes is applied to the total quantity of degradable carbon prior to the use of
this equation. Equation parameters corresponding to the low, base, and high EOL emissions
scenarios are listed in Table 3-10 of the main report.
Degradable Carbon Remaining (metric tons) = Ct= Co*e^"kn)
Ct = Degradable carbon remaining at time t
Co = Degradable carbon remaining at time 0
k = Degradation rate constant
t = time elapsed
Fifty percent of carbon is assumed to degrade to CH4 with the remainder degrading to
CO2. Under base case assumptions 41 percent of degradable carbon breaks down in the first 3
years. The method assumes that this methane is lost to the atmosphere, contributing to global
A-3
-------
Appendix A - Detailed LCI Calculations and Background Information
warming potential, because the gas capture system takes time to be installed following the
closure of a landfill cell. After the initial three years, the gas capture statistics associated with the
Bath regional landfill or the national average landfill are applied to determine the methane
emissions released from the landfill. Non-degradable carbon and the quantity of degradable
carbon that does not break down in 100 years generates a carbon sequestration credit.
GHG Emissions from Composting
The composting emissions scenario employs a range of emission factors for methane,
nitrous oxide, ammonia, and carbon monoxide as presented in Table A-l. The table also
calculates the fraction of incoming nitrogen or carbon that these emissions represent and
demonstrates that they conform to the range of expected composting emissions as stated by the
IPCC (2006).
A-4
-------
Appendix A - Detailed LCI Calculations and Background Information
Table A-l. Composting Emission Factors by Feedstock-AD Scenario
Kmission
Scenurio
Feedstock-
AI) Scenario
Kmission
Species
Klcmcnl
LCI
Kmission
Kiiclor
LCI Units
Loss of
Incoming
Klcmcnl to
CIICs
Units
Low
Base-Low
CH4
c
1.6E-03
kg CHym3 wastewater
0.11%
% of incoming C lost as CH4
Low
Medium-Low
CH4
c
2.1E-03
kg CHi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
High-Low
CH4
c
3.0E-03
kg CHi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
Base-Base
CH4
c
1.4E-03
kg CHi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
Medium-Base
CH4
c
2.0E-03
kg CHym3 wastewater
0.11%
% of incoming C lost as CH4
Low
High-Base
CH4
c
2.7E-03
kg CHi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
Base-High
CH4
c
1.3E-03
kg CHi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
Medium-High
CH4
c
1.9E-03
kg CLLi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
High-High
CH4
c
2.5E-03
kg CLLi/m3 wastewater
0.11%
% of incoming C lost as CH4
Low
Base-Low
N20
N
2.2E-04
kg NiO/m3 wastewater
0.35%
% of incoming N lost as N2O
Low
Medium-Low
N20
N
3.0E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
High-Low
n2o
N
4.2E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
Base-Base
n20
N
2.0E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
Medium-Base
n2o
N
2.8E-04
kg NaO/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
High-Base
n20
N
3.8E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
Base-High
n2o
N
1.9E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
Medium-High
n20
N
2.6E-04
kg N20/m3 wastewater
0.35%
% of incoming N lost as N2O
Low
High-High
n2o
N
3.5E-04
kg N20/m3 wastewater
0.34%
% of incoming N lost as N2O
Low
Base-Low
nh3
N
5.8E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
Medium-Low
nh3
N
8.1E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
High-Low
nh3
N
1.1E-03
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
Base-Base
nh3
N
5.4E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
Medium-Base
nh3
N
7.5E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
High-Base
NH3
N
1.0E-03
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
Base-High
nh3
N
5.0E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
A-5
-------
Appendix A - Detailed LCI Calculations and Background Information
Table A-l. Composting Emission Factors by Feedstock-AD Scenario
Kmission
Scenurio
Feedstock-
AI) Scenario
Kmission
Species
Klcmcnl
LCI
Kmission
Kiiclor
LCI Units
Loss of
Incoming
Klcmcnl to
CIICs
Units
Low
Medium-High
nh3
N
7.0E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Low
High-High
nh3
N
9.5E-04
kg NH3/m3 wastewater
1.20%
% of incoming N lost as NH3
Base
Base-Low
CH4
C
1.2E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
Medium-Low
CH4
C
1.6E-02
kg CLLi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
High-Low
CH4
c
2.3E-02
kg CHym3 wastewater
0.82%
% of incoming C lost as CH4
Base
Base-Base
CH4
c
1.1E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
Medium-Base
CH4
c
1.5E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
High-Base
CH4
c
2.1E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
Base-High
CH4
c
1.0E-02
kg CLLi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
Medium-High
CH4
c
1.4E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
High-High
CH4
c
1.9E-02
kg CHi/m3 wastewater
0.82%
% of incoming C lost as CH4
Base
Base-Low
n2o
N
1.7E-03
kg N20/m3 wastewater
2.68%
% of incoming N lost as N2O
Base
Medium-Low
n20
N
2.3E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
High-Low
n2o
N
3.3E-03
kg NiO/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
Base-Base
n20
N
1.6E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
Medium-Base
n2o
N
2.2E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
High-Base
n20
N
3.0E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
Base-High
n2o
N
1.4E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
Medium-High
n2o
N
2.0E-03
kg N20/m3 wastewater
2.68%
% of incoming N lost as N2O
Base
High-High
n2o
N
2.7E-03
kg N20/m3 wastewater
2.67%
% of incoming N lost as N2O
Base
Base-Low
nh3
N
3.3E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
Medium-Low
nh3
N
4.5E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
High-Low
nh3
N
6.3E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
Base-Base
NH3
N
3.0E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
Medium-Base
nh3
N
4.2E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
A-6
-------
Appendix A - Detailed LCI Calculations and Background Information
Table A-l. Composting Emission Factors by Feedstock-AD Scenario
Kmission
Scenurio
Feedstock-
AI) Scenario
Kmission
Species
Klcmcnl
LCI
Kmission
Kiiclor
LCI Units
Loss of
Incoming
Klcmcnl to
CIICs
Units
Base
High-Base
nh3
N
5.8E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
Base-High
nh3
N
2.8E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
Medium-High
nh3
N
3.9E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
Base
High-High
nh3
N
5.3E-03
kg NH3/m3 wastewater
6.70%
% of incoming N lost as NH3
High
Base-Low
CH4
C
3.6E-02
kg CHym3 wastewater
2.50%
% of incoming C lost as CH4
High
Medium-Low
CH4
C
5.0E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
High-Low
CH4
c
6.9E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
Base-Base
CH4
c
3.3E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
Medium-Base
CH4
c
4.6E-02
kg CH4/m3 wastewater
2.50%
% of incoming C lost as CH4
High
High-Base
CH4
c
6.3E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
Base-High
CH4
c
3.1E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
Medium-High
CH4
c
4.4E-02
kg CHi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
High-High
CH4
c
5.8E-02
kg CLLi/m3 wastewater
2.50%
% of incoming C lost as CH4
High
Base-Low
n2o
N
2.9E-03
kg NiO/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Medium-Low
n20
N
4.1E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
High-Low
n2o
N
5.7E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Base-Base
n20
N
2.7E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Medium-Base
n2o
N
3.8E-03
kg NiO/m3 wastewater
4.65%
% of incoming N lost as N2O
High
High-Base
n2o
N
5.2E-03
kg NiO/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Base-High
n2o
N
2.5E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Medium-High
n3o
N
3.5E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
High-High
n2o
N
4.8E-03
kg N20/m3 wastewater
4.65%
% of incoming N lost as N2O
High
Base-Low
nh3
N
6.2E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
Medium-Low
NH3
N
8.6E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
High-Low
nh3
N
1.2E-02
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
A-7
-------
Appendix A - Detailed LCI Calculations and Background Information
Table A-l. Composting Emission Factors by Feedstock-AD Scenario
Kmission
Sccnurio
Feedstock-
AI) Scenario
Kmission
Species
Klcmcnl
LCI
Kmission
Kiiclor
LCI Units
Loss of
Incoming
Klcmcnl to
GlIGs
Units
High
Base-Base
nh3
N
5.7E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
Medium-Base
nh3
N
8.0E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
High-Base
nh3
N
1.1E-02
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
Base-High
nh3
N
5.3E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
Medium-High
nh3
N
7.4E-03
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
High
High-High
nh3
N
1.0E-02
kg NH3/m3 wastewater
12.74%
% of incoming N lost as NH3
All
Base-Low
CO
C
1.0E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Medium-Low
CO
C
1.4E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
High-Low
CO
c
1.9E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Base-Base
CO
c
9.2E-04
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Medium-Base
CO
c
1.3E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
High-Base
CO
c
1.8E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Base-High
CO
c
8.6E-04
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Medium-High
CO
c
1.2E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
High-High
CO
c
1.6E-03
kg CO/m3 wastewater
0.04%
% of incoming C lost as CO
All
Base-Low
NMVOCs
n.a.
1.9E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
Medium-Low
NMVOCs
n.a.
2.7E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
High-Low
NMVOCs
n.a.
3.7E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
Base-Base
NMVOCs
n.a.
1.8E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
Medium-Base
NMVOCs
n.a.
2.4E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
High-Base
NMVOCs
n.a.
3.4E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
Base-High
NMVOCs
n.a.
1.6E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
Medium-High
NMVOCs
n.a.
2.3E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
All
High-High
NMVOCs
n.a.
3.1E-04
kg NMVOCs/m3 wastewater
n.a.
n.a.
A-8
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Appendix A - Detailed LCI Calculations and Background Information
Electricity Scaling Factors for Feedstock-AD Scenarios
Baseline electricity consumption is scaled for the following units based on the following factors, which are calculated based on
the relative increase in the appropriate flow or loading rate attributable to the Feedstock-AD scenario for each piece of equipment. For
example, the Medium Feedstock-Low AD scenario yields a 56 percent increase in solids treated at the BFP. Electricity use is scaled
up by a factor of 1.56.
Table A-2. Electricity Scaling Factors for Units Affected by Feedstock-AD Scenarios
Kquipmcnt
Base
Feedstock
-Low AD
llnse
Feedstock
-liiise Al)
liiise
Feedstock
-Nigh Al)
Medium
Feedstock
-Low Al)
Medium
Feedstock
-liiise Al)
Medium
Feedstock
-Nigh Al)
High
Feedstock
-Low Al)
High
Feedstock
- liiise Al)
High
Feedstock
-Nigh Al)
Swing Tank, aeration
1.00
1.00
1.00
1.02
1.02
1.02
1.05
1.05
1.05
Sludge Pump (1)
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Sludge Pump (2)
1.00
1.00
1.00
1.25
1.25
1.25
1.50
1.50
1.50
Sludge Pump (3)
1.00
1.00
1.00
1.25
1.25
1.25
1.50
1.50
1.50
Raw Sludge Transfer Pump
1.00
1.00
1.00
1.04
1.04
1.04
1.07
1.07
1.07
GBT Air compressor
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Gravity Belt Thickener
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
GBT Booster Pump
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
CHEM FEED - Polymer BFP
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
CHEM FEED - Polymer GBT
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Blend Tank Mixer
1.00
1.00
1.00
1.04
1.04
1.04
1.07
1.07
1.07
Coarse Bubble Diffused Aeration
1.00
1.00
1.00
1.25
1.25
1.25
1.50
1.50
1.50
BFP Feed Pump No. 1
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Drum Drive
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Belt Drive
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Spray Pump
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Screw Conveyor Drive
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Belt Conveyor Drive
1.11
1.00
0.96
1.56
1.38
1.32
2.18
1.89
1.79
Digested Sludge Transfer Pump
1.00
1.38
1.89
1.11
1.56
2.18
0.96
1.32
1.79
A-9
-------
Appendix A - Detailed LCI Calculations and Background Information
Infrastructure Calculations
All infrastructure calculations are based on a unit lifespan of 40 years, which is assumed
to be a conservative estimate of unit lifespan. Some of these units have already been in existence
beyond 40 years, while others have yet to be built. The actual value varies by unit, and as unit
lifespan increases the results will show a proportional decrease in impacts associated with
infrastructure. If infrastructure impacts were expected to be more prominent in the results, a
greater attention to the details of infrastructure assumptions would be required. In this analysis,
the impacts from infrastructure are intended to highlight the general magnitude of infrastructures
contribution to wastewater treatment impacts, keeping in mind the previous caveats and the
necessity to omit the materials associated with mechanical systems such as pumps and blowers.
Concrete estimates are based on unit dimensions as read from engineering design
documents associated with each of the units in question. Concrete values are based on the
volume of unit walls and floor slabs, and are calculated in cubic meters of concrete per cubic
meter of wastewater treated over the assumed 40-year infrastructure lifespan. The following is an
example of such a calculation for the parshall flume:
Total wall length = L = 108.9 feet (varies by unit)
Wall height = H = 5.5 feet (varies by unit)
Wall thickness = W = 10in/12in = 0.8 feet (varies by unit)
Volume = LxWxH = 499.1 ft3 - 35.3 ft3/m3 = 14.1 m3
Concrete (m3 concrete/m3 wastewater) = 14.1 m3/(40 x 1,381,676 m3/yr)
Gravel estimates are based on unit area and the depth of crushed stone required for the
foundation. The following is an example of such a calculation for the parshall flume included the
assumed values used for all units:
Porosity = q = 0.6 (same for all units)
Specific Gravity = 2.7 (same for all units)
Unit Area = A = 435 ft2
Gravel Depth = d = 2 feet
Gravel (kg/m3) = [(A x d) x (1- g) + 35.3 ft3/m3 x (s.g. x 1000 kg/m3)]/(40 yrs x 1,381,676
m3/yr)
= 4.72E-4 kg/m3
Earthwork estimates are calculated using the unit area, assumed depth of excavation, and
a safety factor. The following is an example of such a calculation for the parshall flume:
Unit Area = A = 435 ft2
Excavation Depth = d = 2 feet
Safety Factor = SF = 0.3
Earthwork (m3/m3 wastewater) = A x d x SF = 435ft2 x 2ft x 0.3
Rebar quantities are based on rebar spacing values as specified in the engineering design
documentation. Engineering drawings specified horizontal spacing, vertical spacing, rebar size,
= 2.56E-07 m3/m3
= 6.96E-7 m3/m3
A-10
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Appendix A - Detailed LCI Calculations and Background Information
and the number of layers per wall. Total length of each rebar size for each unit was measured
from the documents and a standard weight for each rebar size was used to determine the quantity
of rebar steel as reported in Table A-3.
Table A-3. Rebar Weight per Linear Foot1
Rod
INurn her
Rebar size (in)
(Ih per linear loot)
kjl/linear ft
2
0.250 = 1/4"
0.17
0.08
3
0.375 = 3/8"
0.38
0.17
4
0.500= 1/2"
0.67
0.30
5
0.625 = 5/8"
1.04
0.47
6
0.750 = 3/4"
1.5
0.68
7
0.875 = 7/8"
2.04
0.93
8
1.000= 1"
2.67
1.21
9
1.128= 1 1/8"
3.4
1.54
10
1.270 = 1 1/4"
4.3
1.95
11
1.410= 13/8"
5.31
2.41
14
1.693 = 1 3/4"
7.65
3.47
18
2.257 = 2 1/4"
13.6
6.17
References:
1 Engineering Toolbox 2016
Piping quantities are also taken from the engineering design documents are assigned to
units within the plant. Pipe sizing is provided in the planning documents. In a few cases, the
pipes are labeled to be made of PVC, in all other cases the piping is assumed to be made of low-
alloy steel. Total length of each pipe size for each unit was measured from the documents and a
standard weight for each pipe size, Table A-4, was used to determine the quantity of piping
required.
Table A-4. Pipe Weight per Linear Foot
Pipe Material
Size, diameter (in)
k^/linear loot
Concrete1
27
146
Metal2
18
42
Metal2
8
13
Metal2
12
23
Metal2
4
5
Metal2
10
19
Metal2
3
4
Concrete1
24
120
Metal2
6
10
PVC3
6
2
PVC3
4
1
References:
1 Turner Co. 2011
2 Saginaw Pipe 2016
3USPC 2016
A-ll
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Appendix A - Detailed LCI Calculations and Background Information
Historic Influent and Effluent Characteristics
Figure A-l through Figure A-4 show historic influent and effluent water quality records
for the legacy WWTP from October 2011 to August 2014 (BEGWS 2016).
25
20
G
"u 15
ft
S
$ <> S> & N* * _\*
Month-Year
Effluent
•Influent
Figure A-l. Bath influent and effluent wastewater temperatures between October 2011 and
August 2014 (monitored).
70
jp 50
40
oo
S 30
20
10
V *n «0 V) try
Month-Year
'Influent NH3
•Effluent NH3
Figure A-2. Bath influent and effluent ammonia concentrations (as NH3) October 2011 to
October 2015 (monitored).
A-12
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Appendix A - Detailed LCI Calculations and Background Information
1200
1000
800
oo
E,
GO
00
H
400
200
c*4$4¦#4°<$cf ^^>c?
V
•Influent TSS
•Effluent TSS
Figure A-3. Bath influent and effluent total suspended solids (TSS) concentrations (mg/L)
October 2011 to October 2015 (monitored).
700
6h 400
C?V $ 4 ^ / C?V' 4 4 ^ / C?V' 4 4 ^ ^ /
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AEPA
United States
Environmental Protection
Agency
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT NO. G-35
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Washington, DC 20460
Official Business
Penalty for Private Use
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