U.S. Environmental Protection Agency
Office of Resource Conservation and Recovery
Documentation for Greenhouse Gas Emission and
Energy Factors Used in the Waste Reduction Model
(WARM)
Organic Materials Chapters
May 2019
Prepared by ICF
For the U.S. Environmental Protection Agency
Office of Resource Conservation and Recovery

-------
THIS PAGE IS INTENTIONALLY LEFT BLANK

-------
WARM Version 15	Table of Contents	May 2019
Table of Contents
1	Food Waste	1-1
2	Yard Trimmings	2-1

-------
WARM Version 15
Food Waste
May 2019
1 FOOD WASTE
1.1 INTRODUCTION TO WARM AND FOOD WASTE
This chapter describes the methodology used in EPA's Waste Reduction Model (WARM) to
estimate streamlined life-cycle greenhouse gas (GHG) emission factors for food waste—including beef,
poultry, grains, bread, fruits and vegetables, and dairy products—beginning at the point of waste
generation.1 The WARM GHG emission factors are used to compare the net emissions associated with
these six organic material types in the following five materials management options: source reduction,
composting, landfilling, combustion, and anaerobic digestion.
Exhibit 1-1, Exhibit 1-2, Exhibit 1-3, Exhibit 1-4, Exhibit 1-5, and Exhibit 1-6 illustrate the general
life cycles and materials management pathways modeled in WARM for beef, poultry, grains, bread,
fruits and vegetables, and dairy products, respectively. In each life-cycle diagram, the end-of-life
pathways are the same for each material, with only the upstream raw material and production stages
differing across food waste types. For background information on the general purpose and function of
WARM emission factors, see the Introduction & Overview chapter. For more information on Source
Reduction, Composting, Landfilling. Combustion, and Anaerobic Digestion see the chapters devoted to
those processes. WARM also allows users to calculate results in terms of energy, rather than GHGs. The
energy results are calculated using the same methodology described here but with slight adjustments,
as explained in the Energy Impacts chapter.
Exhibit 1-1: Life Cycle of Beef in WARM
1 Source reduction factors for grains, bread, fruits and vegetables, and dairy products were incorporated into
WARM version 13 in June 2014; source reduction factors for beef and poultry were added as part of an update to
WARM version 13 in March 2015,
1-1

-------
WARM Version 15
Food Waste
Exhibit 1-2: Life Cycle of Poultry in WARM
Exhibit 1-3: Life Cycle of Grains in WARM

-------
WARM Version 15
Food Waste
Exhibit 1-4: Life Cycle of Bread in WARM
Exhibit 1-5: Life Cycle of Fruits and Vegetables in WARM

-------
WARM Version 15
Food Waste
May 2019
Exhibit 1-6: Life Cycle of Dairy Products in WARM
Food waste falls under the category of "organics" in WARM. Beef, poultry, grains, bread, fruits
and vegetables, and dairy products include uneaten and prepared food from residences, commercial
and non-commercial establishments, and industrial sources (USDA 2012b).Although paper, wood
products, and plastics are organic materials in the chemical sense, these categories of materials have
very different life-cycle and end-of-life characteristics than food waste and are treated separately in the
municipal solid waste (MSW) stream.
WARM also calculates emission factors for four mixed waste categories that include food waste.
These mixed waste categories are provided to represent different types of common food wastes and to
estimate emissions from a range of organic materials in wastes modeled by WARM users. Mixed food
waste is also likely to include individual food waste components not currently modeled in WARM (e.g.,
meat types like pork). For more information on "proxies" that can be used to represent other food types
not included in WARM, see the guidance document "Using WARM Emission Factors for Materials and
Pathways Not in WARM." The mixed waste categories that include food waste are:
•	"Food waste," which is a weighted average of the five main food type emission factors
developed for WARM: beef, poultry, grains, fruits and vegetables, and dairy products.2 The
weighting is based on the relative shares of these five categories in the U.S. food waste stream,
according to the U.S. Department of Agriculture (USDA) Economic Research Service (ERS) Food
Availability (per Capita) Data System - 2010, and as shown in column (c) of
•	Exhibit 1-7.
2 Bread is an extension of the grains emission factor and represents wheat flour that is processed into bread;
therefore, it is not included as a separate component in the weighted average food waste categories in WARM,
1-4

-------
WARM Version 15
Food Waste
May 2019
•	"Food waste (meat only)/' which is a weighted average of the two meat food type emission
factors developed for WARM: beef and poultry. The weighting is based on the relative shares of
these two categories in the U.S. food waste stream according to USDA (2012b) and, therefore,
not meant to be representative of emissions from other types of meat.
•	"Food waste (non-meat)/' which is a weighted average of the three non-meat food type
emission factors developed for WARM: grains, fruits and vegetables, and dairy products. The
weighting is based on the relative shares of these three categories in the U.S. food waste stream
according to USDA (2012b).
•	The "mixed organics category," which is a weighted average of the food waste and yard
trimmings emission factors. The weighting is based on the relative shares of these two
categories in the waste stream, according to the latest version of EPA's annual report,
Advancing Sustainable Materials Management: Facts and Figures, and as shown in column (c) of
Exhibit 1-8.3 For the mixed organics category, WARM models the waste management pathways
relevant to both food waste and yard trimmings (i.e., landfilling, combustion, anaerobic
digestion and composting).
Exhibit 1-7: Relative Shares of Categories of Food Waste Modeled in WARM in the Waste Stream in 2010
(a)
Material
(b)
% of Total Food Waste
Generation
(c)
Weighted Percentage
in WARM
Modeled in WARM
Beef
5.5%
9.3%
Poultry
6.5%
11.0%
Grains
7.8%
13.1%
Fruits and Vegetables
29.3%
49.1%
Dairy Products
10.6%
17.7%
Total Modeled in WARM
59.7%
100%
Other Types
Other meats3
4.2%
NA
Other poultry15
1.1%
Other grains
0.3%
Other fruits and vegetables
19.9%
Other dairy products
0.3%
Other foodsc
14.8%
All Foods
Total
100%
3 Includes veal, pork, and lamb.
b Includes turkey.
c Includes eggs, fish, shellfish, peanuts, tree nuts, coconut, caloric sweeteners, added fats and oils, and dairy fats.
Source: USDA 2012b.
3 Note that, unlike for other materials in WARM, the "food waste" and "mixed organics" categories are based on
relative shares among materials generated rather than recovered. For food waste, this is because detailed data on
the types of foods recovered in the United States are currently unavailable. For mixed organics, WARM assumes
that users interested in composting would be dealing with a food waste and mixed organics category that is closer
to the current rate of generation, rather than the current rate of recovery. Since the fraction of recovered food
waste is so low, if the shares of yard trimmings and food waste recovered were used, the mixed organics factor
would be essentially the same as the yard trimmings factor, rather than a mix of organic materials.
1-5

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-8: Relative Shares of Yard Trimmings and Food Waste in the Waste Stream in 2015
(a)
(b)
(c)
(d)
(e)

Generation (Short
% of Total Organics
Recovery (Short

Material
Tons)
Generation
Tons)
Recovery Rate
Food Waste
39,730,000
53%
2,100,000
5.2%
Yard Trimmings
34,720,000
47%
21,2900,000
61.3%
Source: EPA 2018a.
1.2 LIFE-CYCLE ASSESSMENT AND EMISSION FACTOR RESULTS
The streamlined life-cycle GHG analysis in WARM focuses on the waste generation point, or the
moment a material is discarded, as the reference point and only considers upstream GHG emissions
when the production of new materials is affected by materials management decisions.4 Recycling and
source reduction are the two materials management options that impact the upstream production of
materials, and consequently are the only management options that include upstream GHG emissions.
For more information on evaluating upstream emissions, see the chapters on Recycling and Source
Reduction.
As Exhibit 1-9 illustrates, all of the GHG sources relevant to food waste in this analysis fall under
the raw materials acquisition and manufacturing and end-of-life sections of the life cycle (including
changes in soil carbon storage). WARM does not include recycling as a management option for food
waste, as food waste cannot be recycled in the traditional sense.
Exhibit 1-9: Food Waste GHG Sources and Sinks from Relevant Materials Management Pathways
Materials
GHG Sources and Sinks Relevant to Food Waste
Management

Changes in Forest

Strategies for
Raw Materials Acquisition
or Soil Carbon

Organics
and Manufacturing
Storage
End-of-Life
Source
Offsets
NA
NA
Reduction
•	Transport of raw
materials and products
•	Raw material acquisition
•	Production energy
•	Production process non-
energy
•	Transport of food
productions to retail


Recycling
Not applicable as food waste cannot be recycled
Composting
NA
Offsets
• Increase in soil
carbon storage
Emissions
•	Transport to compost facility
•	Compost machinery
Combustion
NA
NA
Emissions
•	Transport to WTE facility
•	Combustion-related nitrous oxide
Offsets
•	Avoided utility emissions
4 The analysis is streamlined in the sense that it examines GHG emissions only and is not a comprehensive
environmental analysis of all emissions from materials management.
1-6

-------
WARM Version 15
Food Waste
May 2019
Materials
Management
Strategies for
Organics
GHG Sources and Sinks Relevant to Food Waste
Raw Materials Acquisition
and Manufacturing
Changes in Forest
or Soil Carbon
Storage
End-of-Life
Landfilling
NA
NA
Emissions
•	Transport to landfill
•	Landfilling machinery
•	Landfill methane
Offsets
•	Avoided utility emissions due to landfill gas
combustion
•	Landfill carbon storage
Anaerobic
Digestion
NA
Offsets
• Increase in soil
carbon storage
from
application of
digestate to
soils
Emissions
•	Transport to anaerobic digester
•	Equipment use and biogas leakage at anaerobic
digester
•	CH4 and N20 emissions during digestate curing
•	N20 emissions from land application of digestate
Offsets
•	Avoided utility emissions due to biogas to
energy
•	Avoided synthetic fertilizer use due to land
application of digestate
NA = Not applicable
WARM analyzes all of the GHG sources and sinks outlined in
Exhibit 1-9 to calculate net GHG emissions per short ton of food waste materials generated.
GHG emissions arising from the consumer's use of any product are not considered in WARM'S life-cycle
boundaries. Exhibit 1-10 presents the net GHG emission factors for each materials management strategy
calculated in WARM for food waste. Note that while a detailed analysis of food type-specific upstream
GHG emissions has been conducted in WARM, EPA has not yet analyzed differences in GHG emissions by
food waste type in the composting, combustion, landfilling, and anaerobic digestion pathways.
Therefore, the emission factors for those pathways are the same for each food waste type.
Additional discussion on the detailed methodology used to develop these emission factors may
be found in Section 1.4.
Exhibit 1-10: Net Emissions for Food Waste and Mixed Organics under Each Materials Management Option
MTCQ2E/Short Ton)	

Net Source
Net
Net
Net
Net
Net Anaerobic

Reduction
Recycling
Composting
Combustion
Landfilling
Digestion
Material
Emissions
Emissions
Emissions
Emissions
Emissions
Emissions3
Food Waste
-3.66
NA
-0.18
-0.13
0.54
-0.04
Food Waste (non-meat)
-0.76
NA
-0.18
-0.13
0.54
-0.04
Food Waste (meat only)
-15.10
NA
-0.18
-0.13
0.54
-0.04
Beef
-30.09
NA
-0.18
-0.13
0.54
-0.04
Poultry
-2.45
NA
-0.18
-0.13
0.54
-0.04
Grains
-0.62
NA
-0.18
-0.13
0.54
-0.04
Bread
-0.66
NA
-0.18
-0.13
0.54
-0.04
Fruits and Vegetables
-0.44
NA
-0.18
-0.13
0.54
-0.04
Dairy Products
-1.75
NA
-0.18
-0.13
0.54
-0.04
Mixed Organics
NA
NA
-0.16
-0.15
0.21
-0.06
Note: Negative values denote net GHG emission reductions or carbon storage from a materials management practice.
NA = Not applicable.
3 Emission factors for dry digestion with curing of digestate before land application.
1-7

-------
WARM Version 15
Food Waste
May 2019
1.3 RAW MATERIALS ACQUISITION AND MANUFACTURING
For food waste, the GHG emissions associated with raw materials acquisition and manufacturing
(RMAM) are: (1) GHG emissions from energy used during the acquisition and food production processes,
(2) GHG emissions from energy used to transport materials, (3) non-energy GHG emissions resulting
from production processes, and (4) non-energy GHG emissions resulting from refrigerated
transportation and storage. Process non-energy GHG emissions occur during the manufacture and
application of agricultural fertilizers, from the management of livestock manure, and from enteric
fermentation resulting from livestock. Transportation and storage non-energy emissions result from the
fugitive emission of refrigerants.
The RMAM calculation in WARM also incorporates "retail transportation," which includes the
average truck, rail, water, and other-modes transportation emissions required to transport food
products from the production or processing facility to the retail/distribution point. Transportation
emissions for the retail point to the consumer are not included. The energy and GHG emissions from
retail transportation for each food waste type are presented in Section 1.4.1 describing the source
reduction methodology for each food waste type.
EPA excluded emissions from food product packaging production, processing, and disposal from
the food RMAM estimates because (1) food wastes and packaging wastes are frequently managed using
different waste management pathways and (2) emission factors for many common packaging materials
are already separately available in WARM.
The net emissions factors for source reduction of food waste include RMAM "upstream
emissions" and are shown in the section on source reduction.
1.3.1 Beef
The emission factor for beef includes the energy and emissions associated with producing beef
for retail sale, including the upstream impacts of producing livestock feed, cattle raising, enteric
fermentation from cattle, and processing of the beef to prepare it for retail sale. In addition, the
emission factor includes the energy and GHG emissions associated with the transport of beef products
from production to retail sale. According to the USDA ERS loss-adjusted food availability data, beef
constituted approximately five percent of food waste in 2010, as shown in
Exhibit 1-7. Unlike some other food waste categories in WARM, the emission factor in the beef
category is represented solely by beef rather than by a mix of individual food components, as shown in
Exhibit 1-11.
Exhibit 1-11: Beef in the U.S. Food Waste Stream in 2010
Material Modeled in WARM
Loss Rate (Millions of
pounds per year)
Percent of Category
Weighted Percentage in
WARM
Beef
12,777
100%
100%
Source: USDA 2012b.
In order to develop national average estimates of the RMAM GHG emissions associated with
production of beef, several key assumptions were made:
• Due to the large variety of potential products and coproducts from beef cattle (e.g., different
beef cuts, inedible portions of the cattle, further-processed beef products) EPA has not
separately modeled the impacts associated with the varied end-products derived from one
1-8

-------
WARM Version 15
Food Waste
May 2019
animal. Instead, EPA used LCI data in this analysis to estimate the energy and GHG emissions
from a functional unit of one short ton of boneless, edible beef (Battagliese et al., 2013).
•	EPA used LCI data for the production of conventional beef and did not model the production of
organic beef or veal. The LCI data for the beef RMAM included on-farm data for a U.S. research
farm combined with post-farm data aggregated across the U.S. beef industry. The on-farm data
is assumed to be representative of farm production of cattle throughout the entire United
States (Battagliese et al., 2013).
•	EPA estimated energy use and GHG emissions for upstream grain production for cattle feed
using data from Battagliese et al. (2013) rather than the grain production emission factor in
WARM (See Section 1.3.3). This approach was used because LCI data did not allow for
disaggregation of energy and emissions from feed production from the other RMAM inputs for
beef.
1.3.2 Poultry
As shown in Exhibit 1-12, RMAM data for poultry include two components - chicken and turkey
- with the upstream impacts of producing broiler chicken (i.e., domesticated chickens raised specifically
for meat production) representing 85.6 percent of poultry products in the U.S. waste stream according
to the USDA ERS loss-adjusted food availability data from 2010. Turkey, the other component of poultry
waste in the ERS loss-adjusted food availability data, was not included due to limitations acquiring
RMAM data for its production and because it comprised a small share of the overall waste stream.
The poultry RMAM data includes the upstream energy and GHG emissions of all poultry
production processes prior to retail storage and consumer use. For poultry, this includes three upstream
stages: production of poultry feed, poultry production on a broiler farm (including energy use and
emissions for milling feed and housing poultry), and poultry processing. Each stage accounts for
transportation processes, from bringing feed ingredients to the broiler farm up to and including
transportation of final broiler poultry products to retail. Transportation includes energy use and
emissions from refrigeration.
Exhibit 1-12: Poultry in the U.S. Food Waste Stream in 2010
Material
Loss Rate (Millions of
pounds per year)
Percent of Category
Weighted Percentage in
WARM
Modeled in WARM
Chicken
15,134
85.6%
100%
Other Types
Turkey
2,545
14.4%
NA
All Poultry
Total
17,680
100%
Source: USDA 2012b.
In order to develop national average estimates of the RMAM GHG emissions associated with
production of poultry, several key assumptions were made:
•	Due to the large variety of potential products and coproducts from broiler poultry (e.g., different
poultry cuts, inedible portions of the chicken, further-processed poultry products) EPA has not
separately modeled the impacts associated with the varied end-products derived from one
animal. Instead, EPA used LCI data in this analysis to estimate the energy and GHG emissions
from a functional unit of one short ton of processed broiler poultry.
•	The mix of poultry feed inputs in the LCI data used by EPA included 2.5 percent poultry fat and
2.5 percent poultry by-product meal. Because WARM assumes that the functional unit consists
of processed broiler poultry, EPA has not allocated upstream production emissions to poultry fat
and by-product meal. This differs from the approach in the primary sources of LCI data used by
1-9

-------
WARM Version 15
Food Waste
May 2019
EPA (Pelletier, 2008; Pelletier, 2010) but it allows a more consistent methodology with other
food factors in WARM and most closely represents the poultry waste managed by WARM users.
• EPA used LCI data for the production of conventional poultry and did not model the production
of organic poultry. The LCI data for the emission factor are representative of current national
average practices in the United States. The sources for the LCI data used by EPA (Pelletier, 2008;
Pelletier, 2010) represent U.S. average figures using information from the U.S. poultry industry,
academic studies, and peer-reviewed literature.
1.3.3 Grains and Bread
The emission factor for grains includes the upstream impacts of producing wheat flour, corn,
and rice, which together constitute over 96 percent of grains in the U.S. waste stream. The USDA ERS
loss-adjusted food availability data from 2010 was used to determine the relative shares of various fruits
and vegetables within the U.S. waste stream, as shown in Exhibit 1-13. The bread emission factor
supplements the grain emission factor by including the additional energy used to manufacture wheat
flour into bread, which is the predominant use for wheat flour (USDA 2012a). The other grain categories
in the ERS loss-adjusted food availability data were not included either due to limitations acquiring
RMAM data for their production or because they comprised a small share of the overall waste stream.
Estimates of end-product manufacturing energy for corn and rice were not made due to lack of data
availability.
Exhibit 1-13: Relative Shares of Grains in the U.S. Food Waste Stream in 2010
Material
Loss Rate (Millions
of pounds per year)
Percent of Category
Weighted
Percentage in
WARM
Modeled in WARM
Wheat Flour
12,309
65.6%
68.3%
Corn
3,025
16.1%
16.8%
Rice
2,689
14.3%
14.9%
Total Modeled in WARM
18,023
96.1%
100%
Other Types
Oats
609
3.2%
NA
Other grains
130
0.7%
All Grains
Total
18,761
100%
Source: USDA 2012b.
In order to develop national average estimates of the RMAM GHG emissions associated with
production of grains and bread, several key assumptions were made:
•	EPA assumed that all grains modeled would be farmed in the U.S. using conventional (i.e., non-
organic) farming practices. Production of winter wheat in Kansas, corn in Iowa and Illinois, and
rice in Arkansas was assumed to be representative of national production due to those states'
large share of domestic production for each respective grain.
•	The LCI data for the production of grains were insufficient to characterize the full scope of
energy and emissions associated with the production and processing of grains into a finished
form. For this reason, the crop production data for all three grain products was supplemented
with additional processing data for grain drying from the Ecoinvent database (Nemecek and
Kagi, 2007). As the majority of wheat products use wheat flour, the wheat LCI data was further
supplemented with the energy demand associated with wheat milling (Espinoza-Orias, 2011).
•	The grains emission factor includes milling of wheat into flour but assumes that wheat flour,
corn, and rice can be purchased as dried grains without further processing or cooking. The bread
emission factor assumes baking of wheat flour into bread. The emission factor for grains may
1-10

-------
WARM Version 15
Food Waste
May 2019
understate the upstream emissions associated with corn and rice products that have undergone
further processing.
1.3.4 Fruits and Vegetables
The broad category of fruits and vegetables includes a wide variety of cultivars produced
worldwide, all with widely varying inputs, processing stages, and transportation distances. The fruit and
vegetable energy and emission factors consist of a weighted average mix of materials that reflects the
relative contribution of different fruits and vegetables to the total U.S. waste stream. The USDA ERS
loss-adjusted food availability data from 2010 was used to determine the relative shares of various fruits
and vegetables within the U.S. waste stream, as shown below in Exhibit 1-14. The ERS loss-adjusted food
availability data include several more food categories than were included in the final emission factor;
however, these were not included either due to limitations acquiring RMAM data for their production or
because they comprised a small share of the overall waste stream. The remaining fruits and vegetables
included within the emission factor together comprise 59.6 percent of the fruits and vegetables
discarded within the United States in 2010, totaling nearly 68 million pounds annually.
Exhibit 1-14: Relative Shares of Fruits and Vegetables in the U.S. Food Waste Stream in 2010
Material
Loss Rate (Millions
of pounds per year)
Percent of
Category
Weighted
Percentage in
WARM
Modeled in WARM
Potatoes
18,650
16.4%
27.5%
Tomatoes
18,294
16.1%
27.0%
Citrus
14,200
12.5%
21.0%
Melons
6,313
5.6%
9.3%
Apples
5,575
4.9%
8.2%
Bananas
4,705
4.1%
6.9%
Total Modeled in WARM
67,737
59.6%
100%
Other Types
Other vegetables
16,815
14.8%
NA
Other non-citrus fruit
10,428
9.2%
Corn
5,723
5.0%
Lettuce, spinach, and
other greens
5,219
4.6%
Onions
4,116
3.6%
Legumes
2,005
1.8%
Berries
1,667
1.5%
All Fruits and
Vegetables
Total
113,734
100%
Source: USDA 2012b.
In order to develop national average estimates of the RMAM GHG emissions associated with
production of fruits and vegetables, several key assumptions were made:
•	EPA assumed that all of the fruits and vegetables modeled would be farmed in the United
States, with the exception of bananas, using conventional (i.e., non-organic) farming practices.
Foreign-grown bananas were included within this assessment because they are one of the
largest sources of fruit and vegetable waste within the U.S. waste stream. They were assumed
to be produced in Central America using conventional farming practices due to the lack of
suitable climate for their cultivation on a large scale within the U.S..
•	The differences in production impacts across different breeds of fruits and vegetables were not
considered in the analysis. For example, energy and emissions associated with the production of
Fuji apples were assumed to be representative of all apple production in the U.S.. Likewise,
1-11

-------
WARM Version 15
Food Waste
May 2019
RMAM data for the farming of oranges was assumed to be representative of all citrus
production due to lack of data for production of other citrus fruits and food consumption data
showing that oranges comprise 65 percent of citrus fruits consumed in the U.S. in 2012 (Boriss,
2013).
• Because all of the components included in the fruits and vegetable factors can be consumed as
fresh fruits and vegetables and due to the lack of data on fruit and vegetable processing, EPA
has assumed that all fruits and vegetables enter the waste stream as fresh fruits and vegetables.
Processed fruits and vegetables are likely to have a longer shelf life and therefore may comprise
a smaller share of the food waste stream than fresh fruits and vegetables. As a result, the source
reduction factors for fruits and vegetables exclude any potential impacts from freezing, canning,
pickling, or other processing steps. However, the fruits and vegetable factors should be
considered an acceptable proxy for processed fruits and vegetable products.
1.3.5 Dairy Products
The production of dairy products includes the production of upstream animal feed for livestock,
livestock handling, and the processing of milk into other dairy products. Dairy products within the U.S.
waste stream include multiple varieties of milk, cheese, yogurt, and frozen products. The weighted
emission factor for dairy products in WARM includes 97 percent of the dairy products in the waste
stream, as illustrated in Exhibit 1-15. The remaining products were not included due to both data
limitations and because they constituted a small share of dairy food waste.
Exhibit 1-15: Relative Shares of Dairy Products in the U.S. Food Waste Stream in 2010
Material
Per Capita Loss Rate
(lbs/Year)
Percent of
Category
Weighted Percentage
in WARM

1% Milk
6.96
8.8%
9.0%

2% Milk
17.83
22.5%
23.2%

Skim Milk
7.93
10.0%
10.3%

Whole Milk
13.69
17.3%
17.8%

Ice Cream and Frozen Dairy
7.18
9.1%
9.3%
Modeled in WARM
Non-Fat and Dry Milk
1.55
2.0%
2.0%

Generic Milk
8.45
10.7%
11.0%

Cheddar
4.73
6.0%
6.1%

Mozzarella
4.53
5.7%
5.9%

Yogurt
4.12
5.2%
5.4%

Total Modeled in WARM
76.97
97.3%
100%
Other Types
Evaporated Condensed Milk
1.77
2.3%

Eggnog
0.41
0.5%
NA
All Dairy
Total
79.1
100%

Source: USDA 2012b.
In order to develop national average estimates of the RMAM GHG emissions associated with
production of dairy products, several key assumptions were made:
•	EPA used a regional average of milk production from five regions to model "generic milk" as a
stand-in for specialty products such as chocolate milk and buttermilk. Similarly, unflavored "ice
cream" is assumed to be representative of a variety of flavors in the marketplace.
•	EPA used fruit yogurt as a proxy for general yogurt production, as it was the only variant of
yogurt available within the dairy products production dataset, whereas ice cream served as a
proxy for all frozen dairy products.
1-12

-------
WARM Version 15
Food Waste
May 2019
•	"Cheddar" and "mozzarella" cheeses were assumed to be representative of the entire cheese
production process due to their high share of the waste stream.
•	GHG emissions for the production of grains used as cattle feed are based on data specific to
dairy production and therefore do not use the same data sources used to develop the grains and
bread emission factors in WARM.
1.4 MATERIALS MANAGEMENT METHODOLOGIES
Source reduction, landfilling, composting, combustion, and anaerobic digestion are five
management options used to manage food waste.
1.4.1 Source reduction
When a material is source reduced (i.e., less of the material is made), GHG emissions associated
with making the material and managing the post-consumer waste are avoided. As discussed above,
under the measurement convention used in this analysis, source reduction for food waste has negative
RMAM GHG emissions (i.e., it avoids emissions attributable to production) and zero end-of-life
management GHG emissions. For more information, please refer to the Source Reduction chapter.
Exhibit 1-16 presents the inputs to the source reduction emission factor for production of each
food waste type included in WARM. Beef has the lowest net emission factor, implying that the greatest
emissions savings are due to source reduction, owing to the large amount of emissions released during
RMAM of beef.
Exhibit 1-16: Source Reduction Emission Factors for Food Waste (MTCOzE/Short Ton)
Material
Raw Material
Acquisition and
Manufacturing
for Current Mix
of Inputs
Raw Material
Acquisition
and
Manufacturing
for 100%
Virgin Inputs
Forest Carbon
Sequestration
for Current
Mix of Inputs
Forest Carbon
Sequestration
for 100%
Virgin Inputs
Net
Emissions for
Current Mix
of Inputs
Net
Emissions
for 100%
Virgin
Inputs
Food Waste
-3.66
-3.66
NA
NA
-3.66
-3.66
Food Waste (non-
meat)
-0.76
-0.76
NA
NA
-0.76
-0.76
Food Waste (meat
only)
-15.10
-15.10
NA
NA
-15.10
-15.10
Beef
-30.09
-30.09
NA
NA
-30.09
-30.09
Poultry
-2.45
-2.45
NA
NA
-2.45
-2.45
Grains
-0.62
-0.62
NA
NA
-0.62
-0.62
Bread
-0.66
-0.66
NA
NA
-0.66
-0.66
Fruits and
Vegetables
-0.44
-0.44
NA
NA
-0.44
-0.44
Dairy Products
-1.75
-1.75
NA
NA
-1.75
-1.75
NA = Not applicable.
Notes: Negative values denote net GHG emission reductions or carbon storage from a materials management practice.
All food waste materials are assumed to be produced using 100% virgin inputs. Consequently, the source reduction benefits of both the
"current mix of inputs" and "100% virgin inputs" are the same.
Post-consumer emissions are the emissions associated with materials management pathways
that could occur at end of life. When source reducing food waste, there are no post-consumer emissions
because production of the material is avoided in the first place, and the avoided food never becomes
post-consumer. Forest carbon storage is not applicable to food waste, and thus does not contribute to
the source reduction emission factor.
1-13

-------
WARM Version 15
Food Waste
May 2019
1.4.1.1 Developing the Emission Factor for Source Reduction of Beef
To produce beef, energy is directly used for livestock management, beef processing, and retail
transport. Additionally, during the RMAM phase of the product life-cycle, upstream energy is used to
produce cattle feed and other raw material inputs. In general, the majority of the energy for the
production of these materials is derived from fossil fuels, either through the electricity grid or during on-
site combustion of fuel during the farming process. Combustion of fossil fuels results primarily in C02
emissions, with small amounts of N20 also emitted. Producing beef also results in process non-energy
emissions of C02, CH4, and N20, as described below. These process non-energy emissions primarily come
from enteric fermentation by cattle, as well as the upstream impacts of fertilizer production and
application to produce the grains fed to cattle. Exhibit 1-17 shows the results for each component and
the total GHG emission factors for source reduction of beef.
Exhibit 1-17: Raw Material Acquisition and Manufacturing Emission Factor for Production of Beef
MTCChE/Short Ton)
(a)
(b)
(c)
(d)
(e = b + c + d)
Material
Process Energy
Transportation Energy
Process Non-Energy
Net Emissions
Beef
3.88
0.12
26.09
30.09
Beef production. The data for beef production used for developing the beef emission factor was
provided by the National Cattlemen's Beef Association (NCBA), an industry group. The data used in
WARM were derived from the same data used to produce a 2013 study prepared for NCBA by BASF
Corporation, "More Sustainable Beef Optimization Project: Phase 1 Final Report" (Battagliese et al.,
2013). The study provides a cradle-to-grave assessment of beef production in 2007 and 2011 and
measures the environmental impacts and consumer benefits of beef products in multiple categories,
including GHG emissions.
To align the data in Battagliese et al. (2013) with the scope of the source reduction emission
factors in WARM, EPA separated the cumulative upstream energy demand and process non-energy
emissions from beef production from energy and emissions that are outside the scope of source
reduction emission factors in WARM (i.e., retail storage, consumer transport, and retail packaging). The
sorted data set included the upstream cumulative energy demand by energy source and the aggregated
process non-energy emissions sorted by gas. In the study, some impacts of beef production were
allocated to by-products on an economic basis based on their value relative to the beef produced in the
value chain. The by-products allocated economically include products from both feed and beef
production, such as dried distillers' grains, beef tallow, and offal.
EPA calculated the emissions associated with beef production in two separate stages: first,
process energy emissions were calculated by determining the cumulative energy demand for producing
one short ton of beef. Second, process non-energy emissions from producing one short ton of beef were
estimated separately and added to the process energy emissions. Initially, the energy (in units of million
Btu) for beef production was sorted between renewable bio-energy embedded in crops and demand for
energy from fossil fuel combustion and the electricity grid. GHG emissions from bio-energy are treated
as biogenic emissions that do not contribute to the GHG emission factor. The energy and electricity
demand estimated in the data from the Battagliese et al. (2013) report factored in both efficiency losses
in the grid and upstream conversion losses from energy extraction. The process energy used to produce
beef and the resulting emissions are shown in Exhibit 1-18. The beef source reduction factor is meant to
model all beef waste that occurs during consumers use, including losses during preparation and inedible
portions.
1-14

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-18: Process Energy GHG Emissions Calculations for Production of Beef
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Beef
62.25
3.88
The process non-energy emissions from beef production are dominated by CH4 and N20
emissions primarily resulting from enteric fermentation and fertilizer use for feed production,
respectively. Methane comprises approximately 63 percent of non-energy GHG emissions from beef
production, whereas N20 comprises 37 percent. Collectively, the process non-energy emissions exceed
the process energy emissions associated with beef production. Exhibit 1-19 shows the components for
estimating process non-energy GHG emissions for beef.
Exhibit 1-19: Process Non-Energy GHG Emissions Calculations for Production of Beef

co2


c2f6
n2o
Non-Energy

Emissions
CH4 Emissions
CF4 Emissions
Emissions
Emissions
Carbon Emissions

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MTCOzE/Short
Material
Ton)
Ton)
Ton)
Ton)
Ton)
Ton)
Beef
<0.01
0.66
-
-
0.03
26.09
- = Zero emissions.
Retail Transport. The retail transport data for beef products was taken from the same dataset as
the upstream production cumulative energy demand and process non-energy emissions (Battagliese et
al., 2013). The energy demand from transportation, which was not disaggregated from the mix of fuels
used for other process emissions, was assumed to be derived primarily from diesel fuel consumption
during retail transport. This energy demand was scaled by a carbon coefficient for diesel combustion to
estimate the retail transportation GHG emissions.
1.4.1.2 Developing the Emission Factor for Source Reduction of Poultry
To produce poultry, energy is directly used on-site at poultry farms, for poultry processing, and
for retail transport. During the RMAM phase of the product's life-cycle, upstream energy is used to
produce poultry feed. In general, the majority of the energy for the production of these materials is
derived from fossil fuels, either through the electricity grid or via on-site combustion of fuel during the
farming process. Combustion of fossil fuels results primarily in emissions of C02, as well as small
amounts of N20. Additionally, poultry production results in process non-energy emissions of C02, CH4,
and N20, as described below. These process non-energy emissions primarily come from on-farm gaseous
emissions by poultry, as well as the upstream impacts of fertilizer production and application in growing
poultry feed inputs.
To represent poultry source reduction in WARM, EPA used a functional unit of one short ton of
processed broiler poultry.5 Processed broiler poultry refers to the broiler after it has gone through initial
processing to remove trimmings6 from the bird, leaving the bones and meat that are transported to
5	Alternative functional units considered by EPA included one short ton of live weight broiler poultry (before
processing) and one short ton of boneless broiler poultry meat. The functional unit of one short ton of processed
boiler poultry was used because it is consistent with other food factors in WARM and most closely represents the
waste generated from end-use of poultry products.
6	Trimmings consist of poultry processing wastes, such as offal, blood, and feathers. When these waste products
are separated from the broiler, they are processed into poultry fat and poultry by-product meal (BPM) that is used
for animal feed, as described in Pelletier (2008, 2010).
1-15

-------
WARM Version 15
Food Waste
May 2019
retail and purchased by consumers. Exhibit 1-20 shows the results for each component and the total
GHG emission factors for source reduction of poultry.
Exhibit 1-20: Raw Material Acquisition and Manufacturing Emission Factor for Production of Poultry
MTCChE/Short Ton)
(a)
(b)
(c)
(d)
(e = b + c + d)
Material
Process Energy
Transportation Energy
Process Non-Energy
Net Emissions
Poultry
1.31
0.27
0.87
2.45
EPA developed the energy and emission factors suitable for inclusion in WARM using the LCI
data available from Pelletier (2008, 2010). First, energy and non-energy input assumptions, material
processing assumptions, and LCI data were extracted for each source of energy use and GHG emissions.
These sources were then assessed to identify gaps within Pelletier (2008, 2010) that were either outside
of the scope of the studies but within the scope of WARM, or where assumptions and results were not
provided in enough detail to be sufficiently modeled in WARM without supplementary data. EPA
separated the raw data from broiler poultry production into three stages: production of poultry feed,
poultry production on a broiler farm, and poultry processing. Inputs at each stage were separated into
categories for energy-related inputs (i.e., fuel and electricity) and non-energy related inputs (e.g.,
materials). Process conversion assumptions—such as the share of each type of feed going into an
average metric ton of poultry feed, or the conversion rate to turn poultry feed into live weight broiler
poultry—were extracted from the scientific literature and used to develop unit process descriptions at
each stage (Pelletier 2008, 2010).
Where data were not available in Pelletier (2008, 2010) to ensure consistency with WARM'S life-
cycle boundaries, EPA supplemented the LCI data from Pelletier (2008, 2010) with the following data
sources:
•	Corn production energy use and emissions from existing corn energy and emission
factors in WARM, developed from data available in the U.S. Department of Agriculture
(USDA) LCA Digital Commons database.7
•	Fertilizer production energy use and emissions for corn, soy, and synthetic fertilizer
offset by poultry litter (Ecoinvent Centre, 2007).
•	Transportation modes and distances of material inputs for soy production (Ecoinvent,
Centre 2007).
•	Lime and salt production energy use, GHG emissions, and the transportation modes and
distances of inputs and raw material inputs (Ecoinvent Centre, 2007).
•	Transportation modes and distances to processing and retail from the Bureau of
Transportation Statistics (BTS) Commodity Flow Survey (BTS, 2013).
•	The share of live-weight broiler poultry that is diverted to waste products (Ockerman,
2000).
•	Fuel carbon coefficients from the U.S. Greenhouse Gas Inventory (EPA, 2018b).
7 Where possible, EPA has also been consistent with other food factors in WARM. For instance, corn is assumed to make up a
70 percent of poultry feed. Since EPA had already estimated upstream production emissions for corn during the development
of the grain source reduction factor in WARM, the corn LCI data used in the grains factor was incorporated into the poultry
factor.
1-16

-------
WARM Version 15
Food Waste
May 2019
EPA used the LCI data obtained from the LCA Digital Commons database, the Swiss Ecoinvent
version 2 database, and the BTS Commodity Flow Survey to estimate energy demand and GHG
emissions associated with poultry production.
In order to convert embedded emissions from poultry feed into live weight broiler poultry, EPA
used a conversion factor of 1.9 kilograms of poultry feed per kilogram of live weight broiler produced
(Pelletier, 2008). Exhibit 1-21 shows the mix of poultry feed inputs as modeled in WARM based on
assumptions in Pelletier (2008, 2010).
Exhibit 1-21: Mix of Poultry Feed Inputs Assumed for Source Reduction Factor (%)
Corn
Soy
Fishmeal
Chicken Fat
Chicken By-
product Meal
Salt and
Limestone
70%
20%
2.5%
2.5%
2.5%
2.5%
Corn was assumed to make up 70 percent of poultry feed. Because corn production is already
included in WARM as part of the source reduction factor for grains (see Section 1.4.1.3), EPA used
process energy emissions assumptions from on-farm corn production for consistency. Soy production
was assumed to make up 20 percent of poultry feed. EPA calculated process energy emissions from soy
production based on the fuel input mix provided in Pelletier (2010), including petrol, diesel, liquid
petroleum gas (LPG), and grid electricity. To estimate the energy emissions associated with producing
fertilizers used to produce soy, EPA calculated the cumulative energy demand required to produce the
mix of fertilizers needed to grow one kilogram of soybeans based on data available in the Ecoinvent
database (Ecoinvent Centre, 2007). EPA then determined the share that each fuel type contributed to
total energy demand. Each energy source's contribution to the total energy demand was then multiplied
by the fuel-specific carbon coefficients used in WARM to determine the total process energy emissions
associated with the production of fertilizers used in soy production.
Poultry feed was assumed to consist of 2.5 percent fishmeal and 2.5 percent salt and limestone
(Pelletier, 2010). Total energy use and greenhouse gas emissions per kilogram of fishmeal were obtained
from Pelletier (2010). To estimate a fuel breakdown for energy use, EPA assumed that the mix of fuel
inputs into fishmeal was the same as for the other broiler poultry feed inputs due to the similar feed
ingredients used in producing both fishmeal and poultry—including poultry waste by-product feed,
fishmeal, corn, and soy (Pelletier 2010). For salt and limestone, energy use and GHG emissions are based
on data sets from the Ecoinvent version 2 database (Ecoinvent Centre, 2007). Although the datasets are
representative of European production, EPA used data sets that had been converted using U.S.
electricity grid mix assumptions that provide a more representative accounting of energy use and GHG
emissions in the United States.
Poultry feed was assumed to consist of 2.5 percent poultry fat and 2.5 percent poultry by-
product meal (BPM) (Pelletier, 2010). EPA made the decision not to allocate energy use or GHG
emissions to the poultry fat or BPM removed at the processing stage. Rather, EPA's approach allocated
all energy use and emissions from producing live weight broiler poultry to poultry meat and bone
products. EPA used this approach because it reflects the type of poultry products likely to enter the
municipal solid waste stream,8 the remaining trimmings are a waste product that would not have been
produced otherwise, and because poultry fat and BPM is recirculated back into poultry feed as a closed
loop. Waste products account for 28 percent of live-weight broiler poultry, while the remaining share is
poultry meat and bone (Ockerman, 2000). Since EPA's approach did not allocate any emissions to
8 Compared to other meat products, poultry bones are more likely to be included in products available to
consumers and therefore enter the municipal solid waste stream. Therefore, poultry bones are included in the
functional unit used in WARM.
1-17

-------
WARM Version 15
Food Waste
May 2019
poultry fat or BPM, emissions from the production of these inputs were already included in the source
reduction factor and only the additional energy from processing poultry fat and BPM into poultry feed
was added to the source reduction factor.
Some energy and GHG emissions are avoided when poultry litter is applied as a fertilizer,
offsetting the use of synthetic fertilizers. Pelletier (2008, 2010) provided estimates of the amount of
synthetic fertilizers that are avoided through application of poultry litter.9 Using a similar approach as
used for fertilizers for soy production, EPA determined the cumulative energy demand and mix of fuels
for the production of synthetic fertilizers avoided by application of poultry litter using data available in
the Ecoinvent database (Ecoinvent Centre, 2007). Avoided emissions were calculated as described for
soy fertilizers by applying fuel-specific carbon coefficients. The total process energy used to produce
poultry and the resulting emissions are shown in Exhibit 1-22.
Exhibit 1-22: Process Energy GHG Emissions Calculations for Production of Poultry
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Poultry
22.80
1.31
Process non-energy emissions were estimated by EPA for production and application of
fertilizers used in poultry feed production, emissions from poultry litter application as a fertilizer, and
emissions avoided by replacing synthetic fertilizers with poultry litter. Non-energy emissions from
poultry production are generated from fertilizer production—which includes a variety of chemical
processes that release non-fossil fuel carbon dioxide (C02), methane (CH4), and nitrous oxide (N20) into
the atmosphere—and N20 emissions from the application of synthetic fertilizer and poultry litter to
soils. To capture these emissions, EPA isolated the portion of energy-related GHG emissions and
subtracted this from total GHG emissions from fertilizer production, leaving only process non-energy
emissions.
To estimate emissions from the application of fertilizer, to agricultural soils, EPA followed IPCC
(2006b) guidelines using the active ingredients given from Pelletier (2008). EPA used process non-energy
emissions assumptions from on-farm corn production for consistency (see Section 1.4.1.3 for a detailed
description on development of emissions estimates for corn production). To estimate process non-
energy emissions from soy production, EPA calculated the emissions from the application of the
nitrogen-based fertilizer to agricultural soils using IPCC 2006 guidelines (IPCC 2006b). To estimate
process non-energy emissions from the application of poultry litter and the avoided non-energy
emissions from the resulting displaced fertilizer, EPA's methodology followed IPCC (2006b) guidelines,
and applied assumptions on the nitrogen content and the percent of nitrogen emitted from fertilizer
application obtained from Pelletier (2008). Exhibit 1-23 shows the process non-energy emissions
calculations for poultry production.
Exhibit 1-23: Process Non-Energy Emissions Calculations for Production of Poultry

co2


c2f6
n2o
Non-Energy

Emissions
CH4 Emissions
CF4 Emissions
Emissions
Emissions
Carbon Emissions

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MTCOzE/Short
Material
Ton)
Ton)
Ton)
Ton)
Ton)
Ton)
Poultry
0.05
<0.01
-
-
<0.01
0.86
- = Zero emissions.
9 Avoided synthetic fertilizers are provided in kilograms of active ingredients nitrogen (30 kg), phosphorous (30 kg),
and potassium (20 kg) avoided per metric ton of poultry litter.
1-18

-------
WARM Version 15
Food Waste
May 2019
Retail Transport. For this analysis, distribution of poultry products to their final point of sale was
assumed to have two components: the energy and GHG emissions associated with diesel consumed
during vehicle operation and the GHG impact of fugitive refrigerants emitted from refrigerated vehicles.
Fugitive emissions of refrigerants consisted of a mix of 1,1,1,2-Tetrafluoroethane (R-134a),
Chlorodifluoromethane (HCFC-22), Monochloropentafluoroethane (R-155), and 1,1-Difluoroethane
(HFC-152a). Due to lack of data for poultry-specific transportation, the fugitive emissions associated with
refrigerated vehicle transport were assumed to be the same as for refrigerated dairy delivery via a
medium-sized truck (Thoma et al2010). In the Thoma et al. 2010 study, estimates of fugitive emissions
of refrigerants during the transport phase were estimated via a sales-based approach, which equated
purchases of refrigerants for the truck fleet to fugitive refrigerants released via leakage.
EPA estimated the retail transport ton-miles per shipment of poultry based on the Bureau of
Transportation Statistics (BTS) 2012 Commodity Flow Survey (BTS, 2013). The process energy and non-
energy emissions for the transportation of poultry to retail are shown in Exhibit 1-24 and Exhibit 1-25,
respectively.
Exhibit 1-24: Process Energy GHG Emissions Calculations for Transportation of Poultry
Material
Transportation Energy per Short Ton
(Million Btu)
Transportation Energy GHG
Emissions (MTC02E/Short Ton)
Poultry
3.68
0.27
Exhibit 1-25: Non-Energy Emissions Calculations for Transportation of Poultry

co2
ch4
cf4
c2f6
n2o


Emissions
Emissions
Emissions
Emissions
Emissions
Non-Energy Carbon

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
Emissions
Material
Ton)3
Ton)
Ton)
Ton)
Ton)
(MTC02E/Short Ton)
Poultry
0.01
-
-
-
0.00
0.01
- = Zero emissions.
a The estimate of non-energy C02 emissions includes a mixture of various refrigerants, predominantly HFC 143a, HFC 134a,
HFC-125, and HCFC-22, released during refrigerated transport.
1.4.1.3 Developing the Emission Factor for Source Reduction of Grains and Bread
To produce both grains and bread, energy is used during the RMAM phase of the products' life
cycles. In general, the majority of the energy for the production of these materials is derived from fossil
fuels, either through the electricity grid or during on-site combustion of fuel during the farming process.
Combustion of fossil fuels results primarily in emissions of C02, as well as small amounts of N20.
Additionally, producing grains results in process non-energy emissions of C02, CH4, and N20, as
described below. The production of winter wheat, corn, and rice all require different material and
energy inputs, and a weighted average of the three grain types was used to create a single emission
factor for grains. The upstream energy and emissions for wheat flour were combined with the energy
used to prepare bread to develop a second emission factor for bread. Exhibit 1-26 shows the results for
each component and the total GHG emission factors for source reduction of both grains and wheat-
based bread.
Exhibit 1-26: Raw Material Acquisition and Manufacturing Emission Factor for Production of Grains and Bread
MTCChE/Short Ton)
(a)
(b)
(c)
(d)
(e)




Net Emissions
Material
Process Energy
Transportation Energy
Process Non-Energy
(e = b + c + d)
Grains
0.32
0.02
0.28
0.62
Bread
0.34
0.01
0.30
0.66
1-19

-------
WARM Version 15
Food Waste
May 2019
To calculate the production emissions, EPA obtained life-cycle inventory (LCI) data for the three
grain products—wheat, corn, and rice—available in the USDA National Agricultural Library's LCA Digital
Commons database. The Digital Commons database is intended to provide LCI data for use in life-cycle
assessment (LCA) of food, biofuels, and a variety of other biological products. Primary unit process input
and output data have been developed by researchers at the University of Washington Design for
Environment Laboratory under the direction of Dr. Joyce Cooper using USDA National Agricultural
Statistics Service and ERS datasets. Data on bread production was derived from Espinoza-Orias et al.
(2011), which contained data characterizing the energy use associated with producing both white bread
and wholemeal bread.
The LCI data from the Digital Commons datasets only provide material inputs, outputs, and
processes in units of magnitude per unit of agricultural product produced without any estimates of the
energy or GHG impacts associated with production. For example, the LCI data include estimates of the
amount of fertilizers needed for grain production but do not include data on the energy needed for
fertilizer production or the direct GHG emissions from fertilizer application. In order to translate these
values into the actual energy demand and emissions associated with agricultural production, EPA
identified matching unit processes and corresponding LCI data for those materials and processes within
the life-cycle software, SimaPro. The unit processes within the database are taken from the Swiss
Ecoinvent version 2 database and the U.S. LCI Database.
Grains. Several steps were needed to develop energy and emission factors suitable for inclusion
in WARM using the LCI data available from the Digital Commons and other secondary sources.
Translating the upstream LCI data provided by Digital Commons into the SimaPro format required linking
materials and processes in the LCI dataset to existing Ecoinvent or U.S. LCI Database upstream processes
within the software, albeit at the risk of increasing uncertainty. In the process of matching material and
process flows from the Digital Commons LCI files to unit processes in SimaPro, the magnitude of each
process or material contribution (e.g., the amount of combine harvesting needed to produce one short
ton of wheat) from the LCI dataset was preserved. At the end of this stage, each year of grain data
included a unit process output (one short ton of grains) and a series of linked material inputs and
processes, each with their respective GHG emissions and energy demands contributing to the total
impact of producing that unit of grain.
The emissions were calculated in two separate stages: first, energy-derived emissions were
calculated by determining the cumulative energy demand for producing one short ton of each grain.
Second, non-energy emissions were estimated and added to the fossil fuel-derived emissions.
To estimate the energy-derived emissions, EPA calculated the cumulative energy demand for
each dataset within SimaPro through an energy demand impact assessment method in the software.
This method calculated the total life-cycle energy in million Btu required to produce one unit of grain
and then separated the total into several categories, including: petroleum, nuclear power, biomass,
natural gas, coal, and renewables. Each energy source's contribution to the total energy demand was
then multiplied by the fuel-specific carbon coefficients used in WARM for all materials to determine the
total energy-derived emissions associated with the production of one unit of grain. For wheat, additional
energy demand from milling was included due to the fact that over 90 percent of wheat grain used for
food is converted to flour prior to use (USDA, 2012a). The estimate for milling energy expenditure was
taken from Espinoza-Orias et al. (2011) and was assumed to be taken from the national average
electricity grid. The process energy used to produce each individual grain product, the weighted average
of grains, and the resulting emissions are shown in Exhibit 1-27.
1-20

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-27: Process Energy GHG Emissions Calculations for Production of Grains
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Wheat Flour
4.02
0.23
Corn
6.98
0.42
Rice
9.66
0.59
Grains
5.35
0.32
The non-energy emissions came from two components of the grains' life cycle: fertilizer
production and fertilizer application. Fertilizer production includes a variety of chemical processes that
release non-fossil fuel C02, CH4, and N20 into the atmosphere. To capture these emissions, EPA ran an
impact assessment method within SimaPro on the grains' upstream processes that only considered non-
fossil emissions of these gases to isolate the process emissions from fertilizer production.
To estimate the GHG emissions associated with fertilizer application, EPA assessed the total
amount of nitrogen fertilizer applied to each grain, and then used stoichiometry to identify the share of
nitrogen applied in each dataset. From there, EPA utilized the IPCC Tier 1 method for managed soils to
calculate the total amount of N20 and C02 released from fertilizer application, run-off, volatilization, and
leaching (IPCC, 2006b). The IPCC Tier 1 approach was chosen to maintain consistency with other
agricultural LCAs and the International EPD System's Product Category Rules (PCR) for arable crops
(International EPD System, 2013). Exhibit 1-28 shows the components for estimating process non-energy
GHG emissions for each type of grain and the weighted average.
Exhibit 1-28: Process Non-Energy Emissions Calculations for Production of Grains

co2


c2f6
n2o
Non-Energy

Emissions
CH4 Emissions
CF4 Emissions
Emissions
Emissions
Carbon Emissions

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MTCOzE/Short
Material
Ton)
Ton)
Ton)
Ton)
Ton)
Ton)
Wheat Flour
0.04
<0.01
-
-
<0.01
0.30
Corn
0.03
<0.01
-
-
<0.01
0.18
Rice
0.04
<0.01
-
-
<0.01
0.31
Grains
0.04
<0.01
-
-
<0.01
0.28
- = Zero emissions.
The Digital Commons LCI data assumes that the production of each of the three grains included
in WARM leads to the production of one or more co-products. These co-products include corn silage,
corn stover, wheat straw, and rice straw. In keeping with ISO 14044 standards, EPA allocated impacts to
co-products in proportion to the economic value of the products. Using data from the USDA ERS
Commodity Costs and Returns database, EPA determined the economic value per acre of production for
corn, corn silage, rice, wheat, and wheat straw for each of the LCI data years (USDA, 2013). This
provided enough data to determine economic allocation percentages for wheat and wheat straw.
Supplementary data from a 2009 study by van der Voet et al. provided prices for corn stover, allowing
EPA to estimate the allocation percentages for corn, corn silage, and corn stover. However, EPA was
unable to find a reliable source for the economic value of rice straw. An anecdotal article cited rice
straw's value at approximately $10 to $20 per acre, which would translate to allocation of one to three
percent of rice production energy and emissions to rice straw (Smith, 2004).
Bread. Bread production was estimated by taking an estimate of bread production energy
intensity from Espinoza-Orias et al. (2011), which contained LCI data characterizing the energy use
associated with producing bread. For the purposes of this analysis, white bread was chosen as it is more
common than wheat bread. The study found that wheat milling and baking, respectively, had energy
demands of 0.059 kWh and 0.600 kWh per loaf of bread, which was assumed to be 0.8 kg. This equated
1-21

-------
WARM Version 15
Food Waste
May 2019
to 2.55 million Btus of cumulative energy demand to prepare one ton of bread, of which the entirety
was assumed to be taken from the national average electricity grid. To estimate the total farm-to-retail
energy associated with bread, EPA summed the bread production energy emissions with those for
wheat flour, but did not include corn or rice. Corn and rice were excluded from this process because the
energy use data for milling and baking were based on wheat bread production and because wheat-
based bread is the predominant bread category in the United States (USDA, 2012a). The process energy
used to produce bread and the resulting emissions are shown in Exhibit 1-29.
Exhibit 1-29: Process Energy GHG Emissions Calculations for Production of Bread
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Wheat Flour
4.02
0.23
Bread Baking
2.32
0.11
Bread
6.34
0.34
Retail Transport: Retail transport energy and emissions for both bread and grains were
estimated with the Bureau of Transportation Statistics 2012 Commodity Flow Survey, consistent with
other materials in WARM, and are equal across the three types of grains. The average miles traveled to
retail per shipment are derived from the study and converted into transportation energy, which then is
used to estimate GHG emissions from retail transport. The calculations for estimating the transportation
energy emission factor for grains and bread are shown in Exhibit 1-30.
Exhibit 1-30: Transportation Energy Emissions Calculations for Production of Bread and Grains
Material
Average Miles per
Shipment
Retail Transportation
Energy (Million Btu per
Short Ton of Product)
Retail Transportation
Emission Factors (MTC02E
per Short Ton of Product)
Grains
265
0.29
0.02
Bread
169
0.18
0.01
Source: BTS 2013.
1.4.1.4 Developing the Emission Factor for Source Reduction of Fruits and Vegetables
To produce fruit and vegetable products, energy is used both in the acquisition of raw materials
and in the food production process itself. In general, the majority of energy used for these activities is
derived from fossil fuels. Combustion of fossil fuels results in emissions of C02. In addition, producing
and transporting fruits and vegetables also results in process non-energy emissions of CH4, N20, and
refrigerants, as described in detail below. Hence, the RMAM component of the fruits and vegetables
source reduction emission factor consists of process energy, process non-energy emissions in the
acquisition of raw materials, process non-energy emissions in the transport of fruits and vegetables to
retail, and non-energy emissions during transport.
Exhibit 1-31 shows the results for each component and the total GHG emission factors for
source reduction of fruits and vegetables. The process energy used to produce each type of fruit and
vegetable, the weighted average for the fruits and vegetables category, and the resulting emissions are
shown in Exhibit 1-32. Finally, Exhibit 1-33 shows the components for estimating process non-energy
GHG emissions for each type of fruits and vegetables and the weighted average. The methodology used
to calculated these emissions estimates is described below.
Exhibit 1-31: Raw Material Acquisition and Manufacturing Emission Factor for Production of Fruits and
Vegetables (MTCOzE/Short Ton)
(a)
(b)
(c)
(d)
(e = b + c + d)
Material
Process Energy
Transportation Energy
Process Non-Energy
Net Emissions
Fruits and Vegetables
0.21
0.17
0.07
0.44
1-22

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-32: Process Energy GHG Emissions Calculations for Production of Fruits and Vegetables
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Potatoes
1.61
0.09
Tomatoes
3.51
0.23
Citrus
4.27
0.29
Melons
1.67
0.11
Apples
4.25
0.28
Bananas
2.28
0.13
Fruits and Vegetables (weighted average)
2.95
0.19
Exhibit 1-33: Process Non-Energy Emissions Calculations for Production of Fruits and Vegetables

co2
ch4
cf4
c2f6
n2o


Emissions
Emissions
Emissions
Emissions
Emissions
Non-Energy Carbon

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
Emissions
Material
Ton)
Ton)
Ton)
Ton)
Ton)
(MTCOzE/Short Ton)
Potatoes
0.01
-
-
-
<0.00
0.04
Tomatoes
<0.00
<0.00
-
-
<0.00
0.07
Citrus
<0.00
<0.00
-
-
<0.00
0.05
Melons
<0.00
<0.00
-
-
<0.00
0.04
Apples
-
<0.00
-
-
<0.00
0.01
Bananas
0.02
<0.00
-
-
<0.00
0.10
Fruits and Vegetables






(weighted average)
0.01
<0.00
-
-
<0.00
0.06
- = Zero emissions.
Data used to develop the source reduction emission factor for fresh fruits and vegetables in
WARM came primarily from three sources. Data for the production of apples, melons, tomatoes, and
oranges came from the University of California Cooperative Extension's (UCCE) sample cost production
studies (Fake et al., 2009; O'Connell et al., 2009; Stoddard et al., 2007; Wunderlich et al., 2007). These
studies are intended as hypothetical guides for farmers to produce crops, and include yield projections
and sample requirements for fuel, fertilizers, irrigation, and plant protection products.10 Data for the
production of bananas was acquired from a 2010 life-cycle assessment (LCA) conducted by Soil and
More International, on request of the Dole Food Company (Luske, 2010). The banana LCA study
characterizes the cradle-to-retail GHG emissions associated with banana production in Costa Rica and
retail in Western Europe. In developing the source reduction emission factor, EPA used supplementary
data to model international shipping and retail transport to the United States. Lastly, the data for potato
production was acquired from the Ecoinvent 2.0 database, available within the SimaPro LCA Software.
The primary fruit and vegetable production datasets were supplemented with data from a
variety of sources. Retail transport for domestically-produced fruits and vegetables was informed by the
Bureau of Transportation Statistics (BTS) 2012 Commodity Flow Survey (BTS, 2013). Loss rates for the
transport of fresh fruits and vegetables from production to retail were derived from USDA Economic
Research Service (ERS) loss-adjusted food availability data (USDA, 2012b). In order to evaluate the
impacts from retail transport of bananas produced in Central America to the United States, Luske (2010)
was supplemented by disaggregated data for the ocean transport of bananas to various ports in the
10 Practices described in the production studies are based on real-world production practices considered typical for
the crop and area, but may not apply to every situation. The sample cost of production studies for a variety of
commodities are available from the University of California-Davis, at: http://coststudies.ucdavis.edu/.
1-23

-------
WARM Version 15
Food Waste
May 2019
United States (Bernatz, 2009). The cumulative energy demand and non-energy GHG emissions from
upstream materials and processes, such as harvesting and fertilizer production, were informed by unit
processes from the Ecoinvent 2.0 database, available within SimaPro.
Apples, Oranges, Melons, and Tomatoes. Production of apples, oranges, melons, and tomatoes
were all characterized in the UCCE's Cost and Return datasets in terms of expected yields and
recommended inputs. In order to translate the material and process inputs estimated by the UCCE, EPA
extracted the expected yields and material and process inputs from each study and normalized them by
the expected yield of the plot of land to provide inputs in a functional unit per unit of fruits and
vegetables (e.g., short tons of urea fertilizer per short ton of apples produced). Next, EPA linked each
input to a unit process from either the Ecoinvent 2.0 or the U.S. LCI database within SimaPro. For
example, each liter of diesel or short ton of fertilizer required per acre of apple cultivation was
translated into liters of diesel or short tons of fertilizer per short ton of fruits and vegetables in the U.S.
LCI database. At the end of this stage, each fruit or vegetable dataset within SimaPro included a unit
process output (one short ton of a given fruit or vegetable) and a series of material inputs and
processes, each linked to its GHG emissions and energy demands, which collectively contribute to the
total impact of producing that unit of fruit or vegetable.
The emissions were calculated in two separate stages: first, energy-derived emissions were
calculated by determining the cumulative energy demand for producing one short ton of each type of
fruit or vegetable. Second, non-energy emissions were estimated and added to the fossil fuel-derived
emissions.
To estimate the energy-derived emissions, EPA calculated the cumulative energy demand for
each of the assembled datasets within SimaPro through an energy demand impact assessment method
in the software. This method calculated the total life-cycle energy in mega joules (MJ) required to
produce one unit of fruit or vegetable and then determined the share of each fuel type contributed to
total energy demand, including: petroleum, nuclear power, biomass, natural gas, coal, and renewables.
Each energy source's contribution to the total energy demand was then multiplied by the fuel-specific
carbon coefficients used in WARM for all materials to determine the total energy-derived emissions
associated with the production of one unit of fruit or vegetable.
The non-energy emissions came from two components of the fruit and vegetable life cycle:
fertilizer production and fertilizer application. Fertilizer production includes a variety of chemical
processes that release non-fossil fuel carbon dioxide (C02), methane (CH4), and nitrous oxide (N20) into
the atmosphere. To capture these emissions, EPA ran an impact assessment method within SimaPro on
the fruits and vegetables' upstream processes that only considered non-fossil emissions of these gases
to isolate the process emissions from fertilizer production.
To estimate the GHG emissions associated with fertilizer application, EPA assessed the total
amount of nitrogen fertilizer applied to each crop, and then used stoichiometry to identify the share of
nitrogen applied in each dataset. From there, EPA utilized the IPCC Tier 1 method for managed soils to
calculate the total amount of N20 and C02 released from fertilizer application, run-off, volatilization, and
leaching (IPCC, 2006b). The IPCC Tier 1 approach was chosen to maintain consistency with other
agricultural LCAs and the International EPD System's Product Category Rules (PCR) for arable crops
(International EPD System, 2012).
Refrigerated road transport is also assumed for apples, oranges, melons, and tomatoes
transported to retail in the United States (see "Retail Transport" sub-section below).
Bananas. The source reduction emission factor for bananas was developed using a similar
process to the emission factors developed from the UCCE's datasets, utilizing a 2010 LCA of banana
1-24

-------
WARM Version 15
Food Waste
May 2019
production in Costa Rica (Luske, 2010). EPA compiled the material and process inputs for banana
production and normalized them by the expected yield of bananas to provide inputs in a functional unit
per unit of fruit (e.g., short tons of urea fertilizer per short ton of bananas). The normalized inputs were
then translated into unit processes within SimaPro for cumulative energy demand and non-energy
emissions analysis. Fertilizer emissions were estimated using the IPCC Tier 1 approach using the fertilizer
inputs provided by Luske (2010). See the above sub-section (Apples, Oranges, Melons, and Tomatoes)
for more information on this process.
Unlike the other components of the fruit and vegetable energy and emission factors, bananas
are shipped internationally in specially-made, refrigerated cargo containers to prevent over-ripening
prior to sale. The average transportation distance to the United States was multiplied by a separate
factor for emissions per ton-kilometer of refrigerated ocean cargo transport (BSR, 2012). Additionally,
due to the role of refrigeration in the ocean transport of bananas, EPA incorporated the estimate of
fugitive refrigerant emissions during processing and transport in Luske (2010), summarized in Exhibit
1-34. In addition to refrigerated ocean transport, refrigerated road transport is also assumed for
bananas transported domestically after they are imported into the United States (see "Retail Transport"
sub-section below).
Exhibit 1-34: Fugitive Refrigerant Emissions for International Transport of Bananas



Emissions


Global Warming
(MTC02e/Short Ton of
Refrigerant
Percent of Total
Potential (GWP)a
Bananas)
Pentafluoroethane (HFC-125a)
44%
2,800
7.81E-03
1,1,1-Trifluoroethane (HFC-143a)
52%
3,800
9.23E-03
1,1,1,2-Tetrafluoroethane (HFC-134a)
4%
1,300
7.10E-04
Total
100%
3,260
1.77E-02
Source: Luske 2010.
a GWP values are based on the IPCC Second Assessment Report (IPCC SAR).
Potatoes. Unlike the emission factors for bananas and the fruits and vegetables characterized by
the UCCE, a unit process for potatoes was already available within the SimaPro life-cycle software as
part of the Ecoinvent 2.0 database. The unit process included a co-product of potato leaves; however, in
the dataset, it was allocated at 0.0 percent due to its low economic value. Consequently, it was not
included in this analysis.
As described in the "Apples, Oranges, Melons, and Tomatoes" sub-section above, EPA
conducted a cumulative energy demand and non-energy emissions assessment in order to export the
data in a format suitable for import into WARM.
As with the other components of the fruits and vegetables source reduction emission factors,
EPA estimated the GHG emissions associated with fertilizer application. EPA extracted the amounts of
nitrogen fertilizer and liming materials applied to the potato crops from the Ecoinvent unit process data
and utilized the IPCC Tier 1 method for managed soils to calculate the total amount of N20 and C02
released from fertilizer application, run-off, volatilization, and leaching.
Retail Transport. For this analysis, distribution of fruits and vegetables to their final point of sale
was assumed to have two components: the energy and GHG emissions associated with fossil fuel
combustion from vehicle operation and the GHG impact of fugitive refrigerants emitted from
refrigerated vehicles. The GHG emissions from vehicle operation were a product of diesel fuel
combustion. Fugitive emissions of refrigerants consisted of a mix of 1,1,1,2-Tetrafluoroethane (R-134a),
Chlorodifluoromethane (HCFC-22), Monochloropentafluoroethane (R-155), and 1,1-Difluoroethane
(HFC-152a). Due to lack of data for fruit and vegetable-specific transportation, the fugitive emissions
1-25

-------
WARM Version 15
Food Waste
May 2019
associated with refrigerated vehicle transport were assumed to be the same as for refrigerated dairy
delivery via a medium-sized truck (Thoma et al., 2010). In the Thoma et al. 2010 study, estimates of
fugitive emissions of refrigerants during the transport phase were estimated via a sales-based approach,
which equated purchases of refrigerants for the truck fleet to fugitive refrigerants released via leakage.
Retail transport ton-miles per shipment for all fruits and vegetables were informed by the
Bureau of Transportation Statistics (BTS) 2012 Commodity Flow Survey (BTS, 2013). Bananas were
assumed to have land-based domestic transport in addition to refrigerated ocean transport, as
described in the "Bananas" sub-section above. The process energy and non-energy emissions for the
transportation of fruits and vegetables to retail are shown in Exhibit 1-35 and Exhibit 1-36, respectively.
Exhibit 1-35: Process Energy GHG Emissions Calculations for Transportation of Fruits and Vegetables
Material
Transportation Energy per Short Ton
(Million Btu)
Transportation Energy GHG
Emissions (MTC02E/Short Ton)
Fruits and Vegetables
2.12
0.15
Exhibit 1-36: Non-Energy Emissions Calculations for Transportation of Fruits and Vegetables
Material
co2
Emissions
(MT/Short
Ton)3
ch4
Emissions
(MT/Short
Ton)
cf4
Emissions
(MT/Short
Ton)
c2f6
Emissions
(MT/Short
Ton)
n2o
Emissions
(MT/Short
Ton)
Non-Energy Carbon
Emissions
(MTC02E/Short Ton)
Fruits and
Vegetables
0.01
_
—
—

0.01
- = Zero emissions.
a The estimate of non-energy C02 emissions includes a mixture of various refrigerants, predominantly HFC 143a, HFC 134a,
HFC-125, and HCFC-22, released during refrigerated transport.
Retail transport of perishables such as fruits and vegetables also results in losses due to spoilage
and physical damage to the produce that would render it unfit for sale. Loss rates for the transport of
fresh fruits and vegetables from production to retail were derived from USDA Economic Research
Service (ERS) loss-adjusted food availability data (USDA, 2012b). Loss rates for each fruit and vegetable
in the analysis were compiled from USDA (2012b) and then re-weighted based on each product's share
of the waste stream. An overview of the individual and weighted loss rates for fruit and vegetable
transport to retail is presented in Exhibit 1-37. The loss rates were specific to losses incurred strictly
during the transport of fresh fruits and vegetables instead of a weighted mix of fresh and processed
fruits and vegetables in order to maintain consistency with the scope and methodology used to develop
the food waste source reduction emission factors in WARM. The calculated weighted loss rate of 7.1
percent (shown in the final row in Exhibit 1-37) was applied to both production and transportation
emissions of all fruits and vegetables modeled in WARM, indicating that for every 1,000 short tons of
fruits and vegetables sold at retail, 1,076 short tons had left the production site (indicating a loss of 7.1
percent of the original amount). This factor increased GHG emissions from production and transport by
approximately 7.6 percent.
Exhibit 1-37: Loss Rates for Transport of Fruits and Vegetables from Production to Retail

Total Losses
Percent of
Individual Loss
Weighted Loss
Fruit and Vegetable Category
(Millions of Pounds)
Category
Rate
Rate
Potatoes
18,650
27.5%
4.0%
1.1%
Tomatoes
18,294
27.0%
15.0%
4.1%
Citrus
14,200
21.0%
3.7%
0.8%
Melons
6,313
9.3%
9.2%
0.9%
Apples
5,575
8.2%
4.0%
0.3%
Bananas
4,705
6.9%
0.0%
0.0%
Fruits and Vegetables (weighted average)
67,737
100%
NA
7.1%
1-26

-------
WARM Version 15
Food Waste
May 2019
Source: USDA 2012b.
1.4.1.5 Developing the Emission Factor for Source Reduction of Dairy Products
To produce dairy products, energy is used during the acquisition of RMAM phase of the
products' life cycle. In general, the majority of the energy for the production of these materials is
derived from fossil fuels, either through the electricity grid or during on-site combustion of fuel during
the farming process. Combustion of fossil fuels results primarily in emissions of C02, as well as small
amounts of N20. Additionally, dairy production results in in process non-energy emissions of C02, CH4
and N20, as described below. Dairy products have a high share of non-energy process emissions of CH4
from enteric fermentation by dairy cattle. Refrigerated transport of dairy products to retail also results
in small amounts of high-global warming potential (GWP) refrigerant emissions. The broad category of
dairy foods includes a wide variety of products with differing inputs and processing stages. While dairy
products can have differing upstream energy and emissions impacts, the emission factor described in
this section considers a weighted average of dairy products commonly found in U.S. municipal waste.
Exhibit 1-38 shows the results for each component and the total GHG emission factors for source
reduction of dairy products.
Exhibit 1-38: Raw Material Acquisition and Manufacturing Emission Factor for Production of Dairy Products
MTCChE/Short Ton)
(a)
(b)
(c)
(d)
(e = b + c + d)
Material
Process Energy
Transportation Energy
Process Non-Energy
Net Emissions
Dairy Products
0.81
0.05
0.89
1.75
The LCI data for dairy production used for developing the dairy products emission factor was
provided by the Innovation Center for U.S. Dairy, an industry group. The Innovation Center conducted its
own LCA for dairy production (Thoma et al., 2010). The Innovation Center's LCA's scope is larger than
the scope used to develop the WARM energy and emission factors, covering the cradle-to-grave life-
cycle of dairy products including retail storage, consumer use, and disposal. Dairy production is linked to
several other systems that produce products outside the scope of this specific LCA, including feed co-
products (e.g., dried distillers' grains) and beef. In the data set from the Innovation Center, impacts for
most co-products are allocated economically. However, causal allocation is used for both beef based on
feed nutrient content and for corn silage based on crop nitrogen requirements determined from
reported yield.11 Causal mass balance is used for different fat-content milks during production (Thoma et
al., 2010). Because the Innovation Center's data set already allocated impacts to co-products, EPA did
not further modify the data to account for impacts from products outside the scope used in WARM.
Dairy Products. To align the dairy production LCI data with WARM, the LCI data had to be made
consistent with the scope of the food waste factors in WARM. This involved removing portions of the
unit processes in SimaPro that were outside the scope of the analysis, such as retail storage, consumer
transport, packaging, and consumer use (e.g., cooking and consumer food loss). Through this process,
EPA created a series of unit processes for specific dairy products (e.g., skim milk, ice cream) that only
included the material inputs and process flows prior to retail stocking and sales. For consistency with
other energy and emission factors in WARM, EPA also used LCI data for product transportation from
production to retail, as described below.
11 Within the framework of the ISO 14040 standard for life-cycle assessment, causal allocation refers to the
allocation of environmental impacts based on the physical relationships between materials and their
environmental burdens. In this instance, it refers to isolating the energy flows to the cattle system that go towards
milk production from those directed towards meat production.
1-27

-------
WARM Version 15
Food Waste
May 2019
The emissions were calculated in two separate stages: first, energy-derived emissions were
calculated by determining the cumulative energy demand for producing one short ton of the weighted
average dairy total. Second, non-energy emissions were estimated and added to the fossil fuel-derived
emissions.
To estimate the energy-derived emissions, EPA calculated the cumulative energy demand for
the weighted dairy average using the cumulative energy demand impact assessment method in
SimaPro. This method resulted in an estimate of the total life-cycle energy in million Btu required to
produce one short ton of weighted average dairy products. EPA then separated the total energy
consumption into the fuel categories used for generating the energy, including petroleum, nuclear
power, biomass, natural gas, coal, and renewables. EPA then multiplied each energy source's
contribution to the total energy demand by the fuel-specific carbon coefficients used in WARM for all
materials to determine the total energy-derived emissions associated with the production of one short
ton of dairy product. The process energy used to produce dairy products and the resulting emissions are
shown in Exhibit 1-39.
Exhibit 1-39: Process Energy GHG Emissions Calculations for Production of Dairy Products
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Dairy Products
13.61
0.81
The bulk of the non-energy production emissions came from three components of the dairy life
cycle: enteric fermentation, fertilizer production, and fertilizer application. To capture these emissions,
EPA ran an impact assessment method within SimaPro on the upstream dairy production processes that
only considered non-fossil emissions of these gases in order to avoid double-counting process emissions
from the energy-derived emissions, which are separately calculated within WARM. Exhibit 1-40 shows
the components for estimating process non-energy GHG emissions for dairy products.
Exhibit 1-40: Process Non-Energy Emissions Calculations for Production of Dairy Products

co2


c2f6
n2o
Non-Energy

Emissions
CH4 Emissions
CF4 Emissions
Emissions
Emissions
Carbon Emissions

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MTCOzE/Short
Material
Ton)
Ton)
Ton)
Ton)
Ton)
Ton)
Dairy Products
0.04
0.03
-
-
<0.01
0.88
Retail Transport: The Innovation Center dataset includes complete LCI data on the retail
transportation process for dairy products including energy and emissions from onboard refrigeration
equipment to prevent spoilage. Because these data were available in the Innovation Center dataset and
because refrigeration is an essential part of the transport of these milk-based products, EPA used these
data to develop the retail transport energy and emissions estimates for WARM. This approach differs
from the methodology used for estimating retail transport for other materials currently in WARM, which
rely on average commodity retail transportation distances provided by the U.S. Census Bureau data and,
for materials other than fruits and vegetables, do not involve refrigerated transport. EPA estimated the
energy-derived emissions from transport by calculating the cumulative energy demand within the
software. Non-energy emissions, which were in the form of fugitive refrigerants, were evaluated with
the non-fossil-derived GHG emissions impact assessment method within the software. The process
energy and non-energy emissions for the transportation of dairy products to retail are shown in Exhibit
1-41 and Exhibit 1-42, respectively.
1-28

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-41: Process Energy GHG Emissions Calculations for Transportation of Dairy Products
Material
Process Energy per Short Ton
(Million Btu)
Process Energy GHG Emissions
(MTCOzE/Short Ton)
Dairy Products
0.65
0.05
Exhibit 1-42: Non-Energy Emissions Calculations for Transportation of Dairy Products

co2


c2f6
n2o
Non-Energy

Emissions
CH4 Emissions
CF4 Emissions
Emissions
Emissions
Carbon Emissions

(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MT/Short
(MTC02E/Short
Material
Ton)3
Ton)
Ton)
Ton)
Ton)
Ton)
Dairy Products
0.01
-
-
-
-
0.01
- = Zero emissions.
a The estimate of non-energy C02 emissions includes a mixture of various refrigerants, predominantly HFC 143a, HFC 134a,
HFC-125, and HCFC-22, released during refrigerated transport.
1.4.2	Recycling
Recycling, as modeled in WARM (i.e., producing new products using end-of-life materials), does
not commonly occur with the food waste types modeled in WARM. Therefore, WARM does not consider
GHG emissions or storage associated with the traditional recycling pathway for food waste.
1.4.3	Composting
1.4.3.1 Developing the Emissions Factor for the Composting of Food Waste
Composting food waste results in increased carbon storage when compost is applied to soils.
The net composting emission factor is calculated as the sum of emissions from transportation,
processing of compost, the carbon storage resulting from compost application, and the fugitive
emissions of methane (CH4) and nitrous oxide (N20) produced during decomposition.12 WARM currently
assumes that carbon dioxide (C02) emissions that occur as a result of the composting process are
biogenic and are not counted (for further explanation, see the text box on biogenic carbon in the
Introduction and Background chapter). Exhibit 1-43 details these components for food waste and mixed
organics. For additional information on composting in WARM, see the Composting chapter. The three
emission sources and one emission sink resulting from the composting of organics are:
•	Nonbiogenic C02 emissions from collection and transportation: T ransportation of yard trimmings
and food scraps to the central composting site results in nonbiogenic C02 emissions.13 In
addition, during the composting process the compost is mechanically turned, and the operation
of this equipment also results in nonbiogenic C02 emissions.
•	Carbon Storage: When compost is applied to the soil, some of the carbon contained in the
compost does not decompose for many years and therefore acts as a carbon sink.
•	Fugitive CH4 and N20 emissions: microbial activity during composting decomposes waste into a
variety of compounds, which generates small amounts of CH4 and N20 gas, a net contributor to
the GHG emissions associated with the composting pathway.
12	These fugitive emission sources were added in June 2014 to WARM Version 13.
13	Transportation emissions from delivery of finished compost from the composting facility to its final destination
were not counted.
1-29

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-43: Components of the Composting Net Emission Factor for Food Waste and Mixed Organics

Composting of Post-Consumer Material




(GHG Emissions in MTC02E/Short Ton)




Raw Material






Acquisition and


Compost

Net Emissions

Manufacturing
Transportation
Compost
CH4and
Soil Carbon
(Post-
Material Type
(Current Mix of Inputs)
to Composting
CO?
n2o
Storage
Consumer)
Food Waste
NA
0.02
-
0.05
-0.24
-0.18
Mixed Organics
NA
0.02
-
0.07
-0.24
-0.16
NA = Not applicable.
3 Yard trimmings are a 50%, 25%, 25% weighted average of grass, leaves, and branches, based on U.S. generation data from EPA (2015b).
Transportation energy emissions occur when fossil fuels are used to collect and transport yard
trimmings and food scraps to a composting facility, and then to operate the composting equipment that
turns the compost. To calculate these emissions, WARM relies on assumptions from FAL (1994), which
are detailed in Exhibit 1-44.
Exhibit 1-44: Emissions Associated with Transporting and Turning Compost

Diesel Fuel
Required to Collect and
Transport One Ton
(Million Btu)a
Diesel Fuel Required to
Turn the Compost Piles
(Million Btu)a
Total Energy
Required for
Composting
(Million Btu)
Total C02 Emissions
from Composting
(MTCOzE)
All Material Types
0.04
0.22
0.26
0.02
3 Based on estimates found on Table 1-17 on page 1-32 of FAL 1994.
WARM currently assumes that carbon from compost remains stored in the soil through two
main mechanisms: direct storage of carbon in depleted soils (the "soil carbon restoration" effect)14 and
carbon stored in non-reactive humus compounds (the "increased humus formation" effect).15 The
carbon values from the soil carbon restoration effect are scaled according to the percentage of compost
that is passive, or non-reactive, which is assumed to be 52 percent (Cole, 2000). The weighted soil
restoration value is then added to the increased humus formation effect in order to estimate the total
sequestration value associated with composting. The inputs to the calculation are shown in Exhibit 1-45.
Exhibit 1-45: Soil Carbon Effects as Modeled in Century Scenarios (MTCOzE/Short Ton of Organics)
Scenario
Soil Carbon Restoration
Increased Humus
Formation
Net Carbon
Flux3
Unweighted
Proportion of C
that is Not Passive
Weighted
estimate
Annual application of 32
tons of compost per acre
-0.04
48%
-0.07
-0.17
-0.24
3 The net carbon flux sums each of the carbon effects together and represents the net effect of composting a short ton of yard trimmings in
MTCO2E.
The nonbiogenic C02 emissions from transportation, collection, and compost turning are added
to the compost carbon sink in order to calculate the net composting GHG emission factors for each
14	EPA evaluated the soil carbon restoration effect using Century, a plant-soil ecosystems model that simulates
long-term dynamics of carbon, nitrogen, phosphorous, and sulfur in soils. For more information, see the
Composting chapter.
15	EPA evaluated the increased humus formation effect based on experimental data compiled by Dr. Michael Cole
of the University of Illinois. These estimates accounted for both the fraction of carbon in the compost that is
considered passive and the rate at which passive carbon is degraded into CO2. For more information, see the
Composting chapter.
1-30

-------
WARM Version 15
Food Waste
May 2019
organics type. As Exhibit 1-43 illustrates, WARM estimates that the net composting GHG factor for all
organics types is the same for all sources of compost.
1.4.4 Combustion
1.4.4.1 Developing the Emissions Factor for the Combustion of Food Waste
Combusting food waste results in a net emissions offset (negative emissions) due to the avoided
utility emissions associated with energy recovery from waste combustion. The combustion net emission
factor is calculated as the sum of emissions from transportation of waste to the combustion facility,
nitrous oxide (N20) emissions from combustion, and the avoided C02 emissions from energy recovery in
a waste-to-energy (WTE) plant. Although combustion also releases the carbon contained in food waste
in the form of C02, these emissions are considered biogenic and are not included in the WARM net
emission factor. Exhibit 1-46 presents these components of the net combustion emission factor for food
waste and mixed organics. WARM assumes the same emission factors for all food waste types. For
additional information on combustion in WARM, see the Combustion chapter. The two emissions
sources and one emissions offset that result from the combusting of food waste are:
•	C02 emissions from transportation of waste. Transporting waste to the combustion facility and
transporting ash from the combustion facility to a landfill both result in transportation C02
emissions.
•	Nitrous oxide emissions from combustion. Waste combustion results in measurable emissions of
nitrous oxide (N20), a GHG with a high global warming potential (EPA, 2018b).
•	Avoided utility C02 emissions. Combustion of MSW with energy recovery in a WTE plant also
results in avoided C02 emissions at utilities.
Exhibit 1-46: Components of the Combustion Net Emission Factor for Food Waste and Mixed Organics
(MTCOzE/Short Ton)	

Raw Material
Acquisition and
Manufacturing
(Current Mix of
Inputs)
Transportation
to Combustion
C02 from
Combustion
N20 from
Combustion
Utility
Emissions
Steel
Recovery
Offsets
Net
Emissions
(Post-
Consumer)
Food Waste
NA
0.01
-
0.04
-0.18
-
-0.13
Mixed
Organics
NA
0.01
_
0.04
-0.20
_
-0.15
NA = Not applicable
For the C02 emissions from transporting waste to the combustion facility, and ash from the
combustion facility to a landfill, EPA used an estimate of 60 lbs C02 per ton of MSW for transportation of
mixed MSW developed by FAL (1994). EPA then converted the Franklin Associates estimate from pounds
of C02 per ton of mixed MSW to MTC02e per ton of mixed MSW and applied it to estimate C02
emissions from transporting one short ton of mixed MSW and the resulting ash. WARM assumes that
transportation of food waste uses the same amount of energy as transportation of mixed MSW.
Studies compiled by the Intergovernmental Panel on Climate Change (IPCC) show that MSW
combustion results in measurable emissions of N20, a GHG with a high global warming potential (IPCC,
2006a). The IPCC compiled reported ranges of N20 emissions, per metric ton of waste combusted, from
six classifications of MSW combustors. WARM averages the midpoints of each range and converts the
units to MTC02e of N20 per ton of MSW. Because the IPCC did not report N20 values for combustion of
individual components of MSW, WARM uses the same value for food waste and mixed organics.
1-31

-------
WARM Version 15
Food Waste
May 2019
Most WTE plants in the United States produce electricity and only a few cogenerate electricity
and steam (EPA, 2006). In this analysis, EPA assumes that the energy recovered with MSW combustion
would be in the form of electricity, as shown in Exhibit 1-47. The exhibit shows emission factors for mass
burn facilities (the most common type of WTE plant). EPA used three data elements to estimate the
avoided electric utility C02 emissions associated with combustion of waste in a WTE plant: (1) the energy
content of each waste material, (2) the combustion system efficiency in converting energy in MSW to
delivered electricity, and (3) the electric utility C02 emissions avoided per kilowatt-hour (kWh) of
electricity delivered by WTE plants.
Exhibit 1-47: Utility GHG Emissions Offset from Combustion of Food Waste
(a)
(b)
(c)
(d)
(e)



Emission Factor for Utility-




Generated Electricity
Avoided Utility GHG per

Energy Content
Combustion
(MTCOzE/
Short Ton Combusted

(Million Btu per
System Efficiency
Million Btu of Electricity
(MTCOzE/Short Ton)
Material
Short Ton)
(%)
Delivered)
(e = b x c x d)
Food Waste
4.7
17.8%
0.21
0.18
To estimate the gross GHG emissions per ton of waste combusted, EPA sums emissions from
combustion N20 and transportation C02. These emissions were then added to the avoided utility
emissions in order to calculate the net GHG emission factor, as shown in Exhibit 1-46. WARM estimates
that combustion of food wastes results in a net emission reduction.
1.4.5 Landfilling
1.4.5.1 Developing the Emissions Factor for the Landfilling of Food Waste
Landfilling food waste can result in either net carbon storage or net carbon emissions,
depending on the specific properties of the waste material. The landfilling emissions factor is calculated
as the sum of emissions from transportation of waste to the landfill and operation of landfill equipment,
methane emissions from landfilling, and the carbon storage resulting from undecomposed carbon
remaining in landfills. Exhibit 1-48 presents these components of the landfilling emission factor for food
waste and mixed organics. WARM assumes the same emission factors for all food waste types. For
additional information on landfilling in WARM, see the Landfilling chapter. The two emissions sources
and one emissions sink that result from the landfilling of food waste are:
•	Transportation of food waste. Transportation of food waste to landfill results in anthropogenic
C02 emissions, due to the combustion of fossil fuels in the vehicles used to haul the wastes.
•	Methane emissions from landfilling. When food waste is landfilled, anaerobic bacteria degrade
the materials, producing CH4 and C02, collectively referred to as landfill gas (LFG). Only the CH4
portion of LFG is counted in WARM, because the C02 portion is considered of biogenic origin
and therefore is assumed to be offset by C02 captured by regrowth of the plant sources of the
material.
•	Landfill carbon storage. Because food waste is not completely decomposed by anaerobic
bacteria, some of the carbon in these materials remains stored in the landfill. This stored carbon
constitutes a sink (i.e., negative emissions) in the net emission factor calculation.
1-32

-------
WARM Version 15	Food Waste	May 2019
Exhibit 1-48: Landfilling Emission Factors for Food Waste and Mixed Organics (MTCChE/Short Ton)
Material Type
Raw Material
Acquisition and
Manufacturing
(Current Mix of Inputs)
Transportation
to Landfill
Landfill
ch4
Avoided C02
Emissions from
Energy Recovery
Landfill
Carbon
Storage
Net Emissions
(Post-
Consumer)
Food Waste
-
0.02
0.66
-0.05
-0.09
0.54
Mixed Organics
-
0.02
0.53
-0.04
-0.30
0.21
Note: The emission factors for landfill Cm presented in this table assume that the methane management practices and decay rates at the
landfill are an average of national practices.
Negative values denote GHG emission reductions or carbon storage.
NA = Not applicable; upstream raw material acquisition and manufacturing GHG emissions are not included in landfilling since the life-cycle
boundaries in WARM start at the point of waste generation and landfilling does not affect upstream GHG emissions.
Transportation energy emissions occur when fossil fuels are used to collect and transport food
waste to a landfill, and then to operate the landfill equipment. To calculate these emissions, WARM
relies on assumptions from FAL (1994). EPA then converted the Franklin Associates estimate from
pounds of C02 per ton of mixed MSW to MTC02E per ton of mixed MSW and applied it to estimate C02
emissions from transporting one short ton of mixed MSW. WARM assumes that transportation of food
waste uses the same amount of energy as transportation of mixed MSW.
WARM calculates CH4 emission factors for landfilled materials based on the CH4 collection
system type installed at a given landfill. There are three categories of landfills modeled in WARM: (1)
landfills that do not recover LFG, (2) landfills that collect the LFG and flare it without recovering the flare
energy, and (3) landfills that collect LFG and combust it for energy recovery by generating electricity.
The Excel version of WARM allows users to select component-specific decay rates based on different
assumed moisture contents of the landfill and landfill gas collection efficiencies for a series of landfill
management scenarios. The tables in this section show values using the national average moisture
conditions, based on the national average precipitation at landfills in the United States and for landfill
gas collect efficiency from "typical" landfill operations in the United States. The decay rate and
management scenario assumed influences the landfill gas collection efficiency. For further explanation,
see the Landfilling chapter.
Exhibit 1-49 shows the emission factors for each LFG collection type based on the national
average landfill moisture scenario and "typical" landfill management operations. Overall, landfills that
do not collect LFG produce the most CH4 emissions. Food waste readily degrades in landfills, and
consequently emits the most CH4of all organic materials in landfills. The emissions generated per short
ton of material drop by over half for food waste if the landfill recovers and flares CH4 emissions. These
emissions are even lower in landfills where LFG is recovered for electricity generation because LFG
recovery offsets emissions from avoided electricity generation.16
Exhibit 1-49: Landfill CH4 Emissions for Three Different Methane Collection Systems: National Average Landfill
Moisture Conditions, Typical Landfill Management Operations, and National Average Grid Mix (MTC02e/Wet
Short Ton)
Material
Landfills without LFG
Recovery
Landfills with LFG Recovery
and Flaring
Landfills with LFG Recovery
and Electric Generation
Food Waste
1.62
0.63
0.52
Note: Negative values denote GHG emission reductions or carbon storage.
16 These values include a utility offset credit for electricity generation that is avoided by capturing and recovering
energy from landfill gas to produce electricity. The utility offset credit is calculated based on the non-baseload GHG
emissions intensity of U.S. electricity generation, because it is non-baseload power plants that will adjust to
changes in the supply of electricity from energy recovery at landfills.
1-33

-------
WARM Version 15
Food Waste
May 2019
A portion of the carbon contained in food waste does not decompose after disposal and remains
stored in the landfill. Because this carbon storage would not normally occur under natural conditions
(virtually all of the carbon in the organic material would be released as C02, completing the
photosynthesis/respiration cycle), this is counted as an anthropogenic carbon sink. The carbon storage
associated with each material type depends on the initial carbon content, the extent to which that
carbon decomposes into CH4 in landfills, and temperature and moisture conditions in the landfill. The
background and details of the research underlying the landfill carbon storage factors are detailed in the
Landfilling chapter.
Exhibit 1-50 shows the carbon storage factor calculations for landfilled food waste.
Exhibit 1-50: Calculation of the Carbon Storage Factor for Landfilled Food Waste
(a)
(b)
(c)
(d)
(e)

Ratio of Carbon Storage
Ratio of Dry
Ratio of Carbon Storage to


to Dry Weight (grams of
Weight to
Wet Weight (grams of
Amount of Carbon

Carbon Stored/dry
Wet
Carbon/wet gram of Material)
Stored (MTC02E per Wet
Material
gram of Material)3
Weight
(d = b x c)
Short Ton)
Food Waste
0.10
0.27
0.03
0.09
3 Based on estimates developed by James W. Levis, Morton Barlaz, Joseph F. DeCarolis, and S. Ranji Ranjithan at North Carolina State University;
see Levis et al. (2013).
The landfill CH4 and transportation emissions sources are added to the landfill carbon sink in
order to calculate the net GHG landfilling emission factors for food waste, shown in the final three
columns of Exhibit 1-51 for landfills equipped with different LFG collection systems. The final net
emission factors indicate that food waste results in net emissions, due to relatively high CH4 emissions
and low carbon storage in landfills.
Exhibit 1-51: Components of the Landfill Emission Factor for the Three Different Methane Collection Systems
Typically Used In Landfills (MTCOzE/Short Ton)
(a)
(b)
Net GHG Emissions from CH4
Generation
(c)
(d)
(e)
Net GHG Emissions from
Landfilling
(e = b + c + d)








Landfills



Landfills




with LFG


Landfills
with LFG

GHG
Landfills
Landfills
Recovery

Landfills
with LFG
Recovery

Emissions
without
with LFG
and

without
Recovery
and
Net Landfill
From
LFG
Recover
Electricity

LFG
and
Electric
Carbon
Transpor-
Recover
y and
Generatio
Material
Recovery
Flaring
Generation
Storage
tation
y
Flaring
n
Food Waste
1.62
0.63
0.52
-0.09
0.02
1.39
0.54
0.42
Note: Negative values denote GHG emission reductions or carbon storage.
1.4.6 Anaerobic Digestion
1.4.6.1 Developing the Emissions Factor for the Anaerobic Digestion of Food Waste
The anaerobic digestion emissions factor is calculated as the sum of emissions from
transportation of waste to the anaerobic digester and operation of anaerobic digester equipment,
methane emissions from anaerobic digesting, the carbon storage resulting from applying the digestate
to soil, the net electricity export to grid, and fertilizer offsets. Both wet and dry digestion is applicable
1-34

-------
WARM Version 15
Food Waste
May 2019
for food waste. Exhibit 1-52 presents these components of the dry anaerobic digestion emission factor
for food waste with digestate curing and Exhibit 1-53 with digestate directly applied to land. Exhibit 1-54
contains the GHG sources and sinks for wet digestion with digestate curing and Exhibit 1-55 with
digestate directly applied to land. For additional information on anaerobic digestion in WARM, see the
Anaerobic Digestion chapter. The three emissions sources and three emissions sink that result from the
anaerobically digesting food waste are:
•	Transportation Energy. WARM includes emissions associated with transporting and anaerobic
digestion of the material. Transportation energy emissions occur when fossil fuels are
combusted to collect and transport material to the anaerobic digestion facility, to transport
digestate for land application, and to operate on-site equipment for curing and spreading
digestate.
•	Process Energy. Preprocessing includes grinding, screening, and mixing the feedstock before
they are fed into the reactor. The emissions associated with electricity and diesel consumption
during preprocessing and operation are assessed in WARM for both wet and dry digesters.
WARM estimates the emissions associated with two scenarios for digestate beneficial use:
curing the digestate and applying the resulting compost to agricultural lands, or directly applying
digestate to agricultural lands without curing.
•	Avoided Utility Emissions. Methane biogas is produced during the digestion process and
collected for combustion. WARM models the recovery of biogas for electricity generation and
assumes that this electricity offsets non-baseload electricity generation in the power sector.
•	Avoided Fertilizer Application. The application of digestate to agricultural lands can offset a
portion of the synthetic fertilizer application needed for agricultural lands due to its high
nutrient content. WARM includes avoided fertilizer offsets for both nitrogen and phosphorous in
synthetic fertilizers.
•	Process Non-Energy. Fugitive emissions occur at the digester, during the curing process, and
after land application.
•	Soil Carbon Storage. Similar to carbon from compost applied to agricultural lands, EPA assumes
that carbon from digestate applied to agricultural lands remains stored in the soil through two
main mechanisms: direct storage of carbon in depleted soils and carbon stored in non-reactive
humus compounds.
Exhibit 1-52: Dry Anaerobic Digestion Emission Factors for Food Waste with Digestate Curing (MTCOzE/Short
Ton)


Avoided
Avoided

Process

Net Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Food Waste
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Food Waste (meat only)
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Food Waste (non-meat)
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Beef
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Poultry
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Grains
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Bread
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Fruits and Vegetables
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Dairy Products
0.02
-0.14
-0.01
-0.03
0.12
0.00
-0.04
Mixed Organics
0.02
-0.09
-0.01
-0.09
0.11
0.00
-0.06
Negative values denote GHG emission reductions or carbon storage.
1-35

-------
WARM Version 15
Food Waste
May 2019
Exhibit 1-53: Dry Anaerobic Digestion Emission Factors for Food Waste with Direct Land Application
(MTCChE/Short Ton)







Net


Avoided
Avoided

Process

Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Food Waste
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Food Waste (meat only)
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Food Waste (non-meat)
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Beef
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Poultry
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Grains
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Bread
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Fruits and Vegetables
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Dairy Products
0.02
-0.14
-0.02
-0.08
0.12
0.00
-0.10
Mixed Organics
0.02
-0.09
-0.01
-0.22
0.09
0.00
-0.21
Exhibit 1-54: Wet Anaerobic Digestion Emission Factors for Food Waste with Digestate Curing (MTCOzE/Short
Ton)














Net


Avoided
Avoided

Process

Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Food Waste
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Food Waste (meat only)
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Food Waste (non-meat)
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Beef
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Poultry
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Grains
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Bread
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Fruits and Vegetables
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Dairy Products
0.01
-0.12
-0.02
-0.03
0.10
0.00
-0.06
Mixed Organics
NA
NA
NA
NA
NA
NA
NA
Exhibit 1-55: Wet Anaerobic Digestion Emission Factors for Food Waste with Direct Land Application
(MTCChE/Short Ton)







Net


Avoided
Avoided

Process

Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Food Waste
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Food Waste (meat only)
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Food Waste (non-meat)
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Beef
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Poultry
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Grains
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Bread
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Fruits and Vegetables
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Dairy Products
0.01
-0.12
-0.03
-0.08
0.08
0.00
-0.14
Mixed Organics
NA
NA
NA
NA
NA
NA
NA
WARM accounts for the GHG emissions resulting from fossil fuels used in vehicles collecting and
transporting waste to the anaerobic digestion facility. Diesel is used for transporting the feedstock and
1-36

-------
WARM Version 15
Food Waste
May 2019
solids to the anaerobic digester. To calculate the emissions, WARM relies on the assumptions in NREL's
US Life Cycle Inventory Database (USLCI) (NREL 2015). The NREL emission factor assumes a diesel, short-
haul truck.
The recovery of heat and electricity from the combusted biogas offsets the combustion of other
fossil fuel inputs. WARM assumes that the combusted biogas produces electricity that offsets non-
baseload electricity generation. Electricity generation from combustion of biogas is assumed to be
unavailable for 15 percent of operation time and the process is assumed to be 29 percent efficient (EPA,
2013). Exhibit 1-56 and Exhibit 1-56 show the amount of methane generated and the net electricity
exported to the grid, respectively.
Exhibit 1-56: Methane Generation, Treatment, and Use by Material Type for Dry Digestion
Material
Mass of
Methane
Generated
(kg/ton)
Mass of
Methane
Leaked
(kg/ton)
Mass of
Methane
Flared
(kg/ton)
Mass of
Methane
Combusted
for Energy
(kg/ton)
Energy from
Combusted
Methane
(MMBtu/ton)
Electricity
Generation
(kWh/ton)
Net Electricity
to the Grid
(kWh/ton)
Food Waste
60.0
1.18
8.80
50.0
2.37
201.4
183
Mixed Organics
41.1
0.81
6.03
34.3
1.62
138
120
Exhibit 1-57: Methane Generation, Treatment, and Use by Material Type for Wet Digestion
Material
Mass of
Methane
Generated
(kg/ton)
Mass of
Methane
Leaked
(kg/ton)
Mass of
Methane
Flared
(kg/ton)
Mass of
Methane
Combusted
for Energy
(kg/ton)
Energy from
Combusted
Methane
(MMBtu/
ton)
Electricity
Generation
(kWh/ton)
Energy
Available to
Heat Digester
(MMBtu/
ton)
Energy
Required to
Heat Reactor
(MMBtu/
ton)
Food
Waste
60.0
1.18
8.80
50.0
2.37
201.4
1.26
0.14
If the digestate is cured before land application, the solids are aerobically cured in turned
windrows. The resulting compost is then screened, transported to agriculture lands, and used in place of
a portion of the conventional nitrogen and phosphorus fertilizer that would be needed for the same
agricultural lands. Diesel fuel is consumed during this process. If the digestate is not cured, it is directly
applied to agricultural lands.
EPA assumed that digestate applied to agricultural land allows for some synthetic fertilizer use
to be avoided. WARM includes avoided fertilizer offsets for land application of the digestate generated
from anaerobic digestion but not for compost generated from composting due to the difference in
feedstocks used for each material management pathway, as shown in Exhibit 1-58. Further information
can be found in Anaerobic Digestion chapter.
Exhibit 1-58: Nitrogen and Phosphorous Fertilizer Offset by Material Type
Material
Nitrogen Fertilizer
Offset
(kg N/ton)
Phosphorous
Fertilizer Offset
(kg P/ton)
Nitrogen
Fertilizer Offset
(MTC02e/ton)
Phosphorous
Fertilizer Offset
(MTC02e/ton)
Food Waste
1.084
1.286
-0.009
-0.002
Mixed Organics
0.873
1.074
-0.007
-0.002
WARM calculates the carbon storage impact of direct storage of carbon in depleted soils and
carbon stored in non-reactive humus compounds separately and then sums them to estimate the
carbon storage factor associated with each short ton of organics composted. For more information on
1-37

-------
WARM Version 15
Food Waste
May 2019
carbon storage calculations, see the Composting chapter, which includes information on the Century
model framework and simulations.
To estimate the gross GHG emissions per ton of waste combusted, EPA sums emissions from
transportation, processing and operations, and fugitive emissions. These emissions were then added to
the avoided utility emissions, avoided fertilizer application, and soil carbon storage in order to calculate
the net GHG emission factor, shown in Exhibit 1-52, Exhibit 1-53, Exhibit 1-54, and Exhibit 1-55. WARM
estimates that anaerobic digestion of yard trimmings results in a net emission reduction for both the
curing and non-curing scenarios.
1.5 LIMITATIONS
The results of the analysis presented in this chapter are limited by the reliability of the various
data elements used. This section details limitations, caveats, and areas of current and future research.
1.5.1 Source Reduction
EPA will conduct follow-on research to continue to refine and improve the accuracy of the food
waste emission factors.
•	The food waste factors assume conventional production practices and therefore do not capture
any potential differences in life-cycle impacts from organic production practices.
•	The LCI data used to model beef production is based on on-farm data from the largest research
farm in the U.S. combined with post-farm data for the entire U.S. beef industry (Battagliese et
al., 2013). The study authors intend to expand the next phase of the research effort to reflect
regional differences in beef production throughout the United States, though the overall impact
of these regional differences on the final findings is uncertain.
•	For poultry production, GHG emissions have been allocated to both poultry meat and bones.
EPA chose this allocation method to be consistent with other WARM food waste factors and to
represent the waste materials that users of WARM are most likely to generate. However, there
are other allocation methods not represented here, including allocating emissions only to
boneless poultry meat or to the entire live weight mass of the broiler, resulting in emissions also
being allocated to poultry fat and BPM products that are reprocessed into poultry feed.
•	EPA's peer review process for the poultry source reduction factors brought to EPA's attention
the growing use of distiller's grains as a potential input to poultry feed. Distiller's grains have not
been included at this point because these were not included as a feed input in the underlying
LCI data used to develop the poultry source reduction. EPA will continue to evaluate information
on the use of distiller's grains as it becomes available and consider this information for possible
future updates to the poultry factors.
•	For grain production, upstream energy demand and emissions associated with fertilizer
production for nitrogen-based fertilizers are determined from a unit process for a weighted
production mix of nitrogen fertilizers used in the U.S. In the future, EPA may consider the
possibility of breaking this out into impacts by each specific type of nitrogen fertilizer and
incorporate more recent LCI data for fertilizer production.
•	Fertilizer-related soil emissions were estimated for poultry, grains, fruits, and vegetables using
the IPCCTier 1 Method. In the future, EPA will investigate how use of the IPCC Tier 1 method
1-38

-------
WARM Version 15
Food Waste
May 2019
may differ from the current methodology for estimating emissions from soils from fertilizer use
in the U.S. EPA's Inventory of U.S. Greenhouse Gas Emissions and Sinks report.
•	Impacts from co-products of fruit and vegetable products were not included in this analysis due
to data limitations. For apples, oranges, melons, and tomatoes, the primary RMAM datasets did
not include any information about co-products. However, differences between the amount of
fruits and vegetables harvested in these scenarios and the final amount available for sale
indicates that a portion of the production was unsalable. Due to a lack of data on the pathways
for these fruits and vegetables and their assumed value, EPA determined that the impacts from
any possible co-products are outside the scope of this effort.
•	Luske (2010) determined that approximately 10 percent (by mass) of the bananas produced
within the scope of its assessment were unsuitable for international sale and sold to a separate
distributor for a much lower price for local distribution. Relative to the price of the bananas
destined for international sale, these bananas had approximately 0.3 percent of the value of the
entire yield. Because of the low value and lack of distribution to the U.S., EPA deemed that
impacts from this co-product were outside of the scope of analysis.
•	Though Luske (2010) reported its own estimate for the life-cycle emissions for banana
production, EPA supplemented the data and applied a different methodology to maintain
consistency with the other fruits and vegetables within the weighted emission factor and with
the scope of WARM. First, to narrow the scope of the data to cradle-to-retail, EPA did not assess
the impacts of retail storage at the destination country. Second, to make the dataset more
relevant to bananas sold within the United States, EPA did not utilize the ocean transport data
for bananas shipped to Belgium and Germany from the study. Instead, EPA assumed an average
transportation distance from Central American banana plantations to U.S. ports, acquired from
a separate study on fruit transportation distances (Bernatz, 2009). On average, the port-to-port
shipment distance to the United States from Guatemala and Costa Rica, the two largest
suppliers of bananas, was approximately 3,094 kilometers per shipment.
•	Food products that are discarded at any point from primary production through retail transport
could generate GHG impacts through decomposition during landfilling or composting. However,
this potential source of GHG emissions is not included in the WARM fruits and vegetables source
reduction emission factor for various reasons. First, the fruits and vegetables that are lost or
otherwise discarded at the point of production may simply be left on the field and are
accounted for in the soil emissions calculations described above. Secondly, USDA (2012b) does
not distinguish between the food loss rates at primary production versus those during
transportation, and therefore it is unclear what share of the food waste loss occurs during retail
transport itself. In its 2010 tomato packaging sustainable materials management study, EPA also
found that information on losses at farm and in distribution was limited and in some cases
conflicting (EPA, 2010). EPA assumes that the share of food waste loss during retail transport is
small and that the corresponding GHG impact of its disposal would not have a large impact on
the final emission factor.
•	Due to lack of available data, emissions from the release of fugitive refrigerants during
refrigerated transportation of poultry and fruits and vegetables were estimated based on data
developed specific to dairy products (Thoma et al., 2010). However, the emissions burden from
fugitive refrigerants likely varies across the different food types modeled in WARM. EPA will
continue to evaluate the possibility of incorporating refrigerated transport data and
assumptions specific to different food types modeled in future updates .
1-39

-------
WARM Version 15
Food Waste
May 2019
1.5.2	Composting
•	Due to data and resource constraints, the analysis considers a small sampling of feedstocks and
a single compost application (cropland soil). EPA analyzed two types of compost feedstocks-
yard trimmings and food scraps—although sewage sludge, animal manure, and several other
compost feedstocks also may have significant GHG implications. Similarly, it was assumed that
compost was applied to degraded agricultural soils growing corn, despite widespread use of
compost in specialty crops, land reclamation, silviculture, horticulture, and landscaping.
•	This analysis did not consider the full range of soil conservation and management practices that
could be used in combination with application of compost, and the impacts of those practices on
carbon storage. Research indicated that adding compost to agricultural soils in conjunction with
various conservation practices enhances the generation of soil organic matter to a much greater
degree than applying compost alone. Examples of these conservation practices include
conservation tillage, no-till, residue management, crop rotation, wintering, and summer fallow
elimination.
•	In addition to the carbon storage benefits of adding compost to agricultural soils, composting
may lead to improved soil quality, improved plant productivity, improved soil water retention,
and cost savings. As discussed earlier, nutrients in compost tend to foster soil fertility (Brady and
Weil, 1999). In fact, composts have been used to establish plant growth on land previously
unable to support vegetation. In addition to these biological improvements, compost also may
lead to cost savings associated with avoided waste disposal, particularly for feedstocks such as
sewage sludge and animal manure.
•	This analysis did not consider the differences in compost emissions resulting from composting
different food waste types. In the future, EPA may consider researching the development of
food type-specific composting factors for WARM.
1.5.3	Landfilling
•	WARM currently assumes that 87 percent of MSW landfill CH4 is generated at landfills with LFG
recovery systems (EPA, 2018b). The net GHG emissions from landfilling each material are quite
sensitive to the LFG recovery rate, so the application of landfill gas collection systems at landfills
will have an effect on lowering the emission factors presented here over time. WARM is
updated annually to account for changes in the percent of MSW landfill CH4 that is collected at
U.S. landfills.
•	This analysis did not consider the differences in landfill emissions resulting from landfilling
different food waste types. In the future, EPA may consider researching the development of
food type-specific landfilling factors for WARM.
1.5.4	Combustion
•	Opportunities exist for the combustion system efficiency of WTE plants to improve over time. As
efficiency improves, more electricity can be generated per ton of waste combusted (assuming
no change in utility emissions per kWh), resulting in a larger utility offset, and the net GHG
emissions benefit from combustion of MSW will increase.
•	The reported ranges for N20 emissions from combustion of organics were broad. In some cases,
the high end of the range was 10 times the low end of the range. Research has indicated that
N20 emissions vary with the type of waste burned. In the absence of better data on the
1-40

-------
WARM Version 15
Food Waste
May 2019
composition and N20 emissions from food waste combustion on a national scale in the United
States, the average value used for food waste should be interpreted as an approximate value.
•	This analysis used the non-baseload mix of electricity generation facilities as the proxy for
calculating the GHG emissions intensity of electricity production that is displaced at the margin
from energy recovery at WTE plants and LFG collection systems. Actual avoided utility GHG
emissions will depend on the specific mix of power plants that adjust to an increase in the
supply of electricity, and could be larger or smaller than estimated in these results.
•	This analysis did not consider the differences in combustion emissions resulting from
combusting different food waste types. In the future. EPA may consider researching the
development of food type-specific combustion factors for WARM.
1.5.5 Anaerobic Digestion
•	WARM assumes that the biogas generated during anaerobic digestion is used in an internal
combustion engine to generate electricity which is used to offset grid electricity. Multiple other
uses have been identified for the biogas through EPA's review of literature and stakeholder
engagement. These uses were not modeled here.
•	WARM assumes that the digestate generated during anaerobically digesting organic waste is
applied to agricultural land; however, EPA's review of literature and stakeholder engagement
identified other uses for digestate beyond land application. These have not been addressed
within WARM.
•	In discussions with stakeholders and in EPA's review of literature, it was indicated that there was
little evidence that different anaerobic digestion reactor configurations have significantly
different methane yields. However, the net GHG emissions from anaerobically digesting yard
trimmings are sensitive to methane yield assumptions. EPA believes that the modeling approach
used in WARM provides reasonable estimates of the GHG emissions that represent a wide range
of anaerobic digestion configurations.
1.6 REFERENCES
Barlaz, M.A. (2008). Memorandum to Parties Interested in Carbon Sequestration from Municipal Solid
Waste: "Corrections to Previously Published Carbon Storage Factors." February 27, 2008.
Barlaz, M.A. (2005). Letter to Randy Freed, ICF International: "Decomposition of Leaves." June 29, 2005.
Barlaz, M.A. (1998). Carbon storage during biodegradation of municipal solid waste components in
laboratory-scale landfills. Global Biogeochem. Cycles, 12 (2): 373-380.
Battagliese, T., Andrade, J., Schulze, I., Uhlman, B., and Barcan, C. (2013). More Sustainable Beef
Optimization Project. Phase 1 Final Report, June 2013. Submitted by BASF Corporation.
Bernatz, G. (2009). Apples, Bananas, and Oranges: Using GIS to Determine Distance Travelled', Energy
Use, and Emissions from Imported Fruit. Volume 11, Papers in Resource Analysis. 16 pp. Saint
Mary's University of Minnesota Central Services Press. Winona, MN.
Bernatz, G. (2013). Personal email correspondence with Nikita Pavlenko, ICF. July 12, 2013.
Boriss, H. (2013). "Citrus Profile." Agricultural Marketing Resource Center.
Brady, N., & R. Weil. (1999). The Nature and Properties of Soils. Upper Saddle River, NJ: Prentice Hall.
1-41

-------
WARM Version 15
Food Waste
May 2019
BSR. (2012). Clean Cargo Working Group Global Trade Lane Emissions Factors. Business for Social
Responsibility (BSR). August 2012.
Bureau of Transportation Statistics. (2013). "2012 Commodity Flow Survey." Retrieved from:
http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/commodity flow survey/i
ndex.html.
Cole, M. (2000). Personal communication between Dr. Michael Cole, University of Illinois, and Randy
Freed, ICF Consulting, July 3, 2000.
Ecoinvent Centre. (2007). Ecoinvent data v2.0. Ecoinvent reports No.1-25, Swiss Centre for Life Cycle
Inventories, Diibendorf, 2007. Retrieved from: www.ecoinvent.org.
EPA. (2018a). Advancing Sustainable Materials Management: Facts and Figures 2015. (EPA530-F-18-
004).Washington, DC: U.S. Government Printing Office. Retrieved from
https://www.epa.gov/facts-and-figures-about-materials-waste-and-recvcling/advancing-
sustainable-materials-management.
EPA. (2018b). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 - 2016. (EPA 430-R-18-004).
Washington, DC: U.S. Government Printing Office. Retrieved from
https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventorv-report-archive.
EPA. (2015). Advancing Sustainable Materials Management: Facts and Figures 2013. (EPA530-R-15-002).
Washington, DC: U.S. Government Printing Office. Retrieved from
http://www.cta.tech/CorporateSite/media/environment/eCycle/2013 advncng smm rpt.pdf.
EPA. (2013). The Landfill Methane Outreach Program (LMOP) LFGE Benefits Calculator. Available online
at: http://www.epa.gov/lmop/proiects-candidates/lfge-calculator.html.
EPA. (2010). Evaluating the Environmental Impacts of Packaging Fresh Tomatoes Using Life-Cycle
Thinking & Assessments Sustainable Materials Management Demonstration Project. Final
Report. Prepared for the U.S. Environmental Protection Agency. October 29.
EPA. (2006). Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and
Sinks. Washington, DC: U.S. Environmental Protection Agency.
EPA. (1998). AP-42 Emission Factors for Municipal Solid Waste Landfills - Supplement E. Washington, DC:
U.S. Environmental Protection Agency.
Espinoza-Orias, N., H. Stichnothe, and A. Azapagic. (2011). "The Carbon Footprint of Bread".
International Journal of Life Cycle Assessment, (2011) 16:351-365.
Fake, C., K.M. Klonsky, and R.L. De Moura. (2009). Sample Costs to Produce Mixed Vegetables. University
of California Cooperative Extension. VM-IR-09. Retrieved from:
http://coststudies.ucdavis.edu/files/MixedVeglR09.pdf.
FAL. (1994). The Role of Recycling in Integrated Solid Waste Management to the Year 2000. Franklin
Associates Ltd. (Stamford, CT: Keep America Beautiful, Inc.), September.
Harrington, K. (1997). Personal communication between Karen Harrington, Minnesota Office of
Environmental Assistance, and ICF Consulting, October 1997. Value reported by an RDF facility
located in Newport, MN.
International EPD System. (2013). "Product Category Rules: Arable Crops (Multiple CPC-Codes)." June
12, 2013. Retrieved from:
http://www.environdec.com/en/PCR/Detail/?Pcr=8804#.UrlW9NJDuSo.
1-42

-------
WARM Version 15
Food Waste
May 2019
International EPD System. (2012). Product Category Rules—Fruits and Nuts. Version 1.0. August 23rd,
2012. Retrieved from: http://www.environdec.com/en/PCR/Detail/?Pcr=8235.
IPCC. (2006a). 2006IPCC Guidelines for National Greenhouse Gas Inventories, Volume 5: Waste, Chapter
3: Solid Waste Disposal. Intergovernmental Panel on Climate Change. Retrieved from
http://www.ipcc-nggip.iges.or.ip/public/2006gl/vol5.html.
IPCC. (2006b). "IPCC Guidelines for National Greenhouse Gas Inventories: N20 Emissions from Managed
Soils, and C02 Emissions from Lime and Urea Application". Retrieved from: http://www.ipcc-
nggip.iges.or.jp/public/2006gl/pdf/4 Volume4/V4 11 Chll N2Q&CQ2.pdf.
ISO. (2006). International Standard 14044: Environmental management - Life Cycle Assessment -
Requirements and guidelines. International Organization for Standardization. First edition. July
7, 2006.
Kim, D., G. Thoma, D. Nutter, F. Milani, R. Ulrich, and G. Norris. (2013). "Life cycle assessment of cheese
and whey protein in the USA." International Journal of Life Cycle Assessment; 18:1019-1035.
Levis, J. W., Barlaz, M. A., DeCarolis, J. F., Ranjithan, S. R. (2013). What is the optimal way for a suburban
U.S. city to sustainably manage future solid waste? Perspectives from a Solid Waste
Optimization Life-cycle Framework (SWOLF). Environ. Sci. Technol., submitted.
Luske, B. (2010). Comprehensive Carbon Footprint Assessment Dole Bananas. Soil and More
International. Retrieved from: http://dolecrs.com/uploads/2012/Q6/Soil-More-Carbon-
Footprint-Assessment.pdf.
Miller, D. and Y. Wang, eds. (2013). "Carbon and Water Footprint of U.S. Milk, From Farm to Table."
International Dairy Journal; 31 (Supplement 1): S1-S100.
National Agriculture Statistics Service (NASS). (2013). "NASS Quick Stats: Grain Yield and Production by
State". Retrieved from: http://www.nass.usda.gov/Quick Stats/.
Nemecek, T., and Kagi, T. (2007). Life Cycle Inventories of Agricultural Production Systems. Ecoinvent
Report No. 15. Retrieved from: http://db.ecoinvent.org/reports/15_Agriculture.pdf .
O'Connell, N.V., C.E. Kallsen, K.M. Klonsky, and R.L. De Moura. (2009). Sample Costs to Establish an
Orange Orchard and Produce Oranges. University of California Cooperative Extension. OR-VS-09.
Retrieved from: http://coststudies.ucdavis.edu/files/orangevs2009.pdf.
Ockerman, H.W., Hansen, C. L. 2000. Animal By-Product Processing and Utilization (Boca Raton: CRC
Press, 2000). Retrieved from:
http://books.google.co.in/books?id=luhZQK 5ielC&printsec=frontcover#v=onepage&q&f=false.
Pelletier, N. 2008. "Environmental performance in the US broiler poultry sector: Life cycle energy use
and greenhouse gas, ozone depleting, acidifying and eutrophying emissions," Agricultural
Systems 98 (2008): 67-73.
Pelletier, N. 2010. What's at Steak? Ecological Economic Sustainability and the Ethical, Environmental,
and Policy Implications for Global Livestock Production (Dalhousie University, 2010).
Piers Industry Blog. (2013). "U.S. Banana Imports Jump 12% in Q1 2013." Retrieved from:
http://content.piers.com/blog/us-banana-imports-rise-sharply.
Smith, C. (2004). "New Market for Baled Rice Straw." American Agriculturist. Retrieved from:
http://farmprogress.com/story-new-market-for-baled-rice-straw-9-2951.
1-43

-------
WARM Version 15
Food Waste
May 2019
Stoddard, C.S., M. LeStrange, B. Aegerter, K.M. Klonsky, and R.L. De Moura. (2007). Sample Costs to
Produce Fresh Market Tomatoes. University of California Cooperative Extension. TM-SJ-07.
Retrieved from: http://coststudies.ucdavis.edu/files/tomatofrmktsi07.pdf.
Thoma, G., et al. (2010). "Global Warming Potential of Fluid Milk Consumed in the US: A Life Cycle
Assessment." Innovation Center for U.S. Dairy and University of Arkansas.
USDA. (2013). "Commodity Costs and Returns." U.S. Department of Agriculture Economic Research
Service. Retrieved from: http://www.ers.usda.gov/data-products/commoditv-costs-and-
returns.aspx#.UqtabtJDuSp.
USDA. (2012a). "Estimating Wheat Supply and Food Use." U.S. Department of Agriculture Economic
Research Service. Retrieved from: http://www.ers.usda.gov/topics/crops/wheat/estimating-
wheat-supplv-and-use.aspx#.U5HRAHJdXlY.
USDA. (2012b). "Food Availability (per Capita) Data System - 2010." U.S. Department of Agriculture
Economic Research Service. Retrieved from: http://www.ers.usda.gov/data-products/food-
availabilitv-(per-capita)-data-svstem.aspx#.UqoMEtJDvv4.
USDA LCA Digital Commons. Retrieved from: https://www.lcacommons.gov/.
Van der Voet, E., G. Huppes, and H.A. Udo de Haes. (2009). Allocation Issues in LCA Methodology: A Case
Study of Corn Stover-Based Fuel Ethanol. International Journal of Life Cycle Assessment, 14, 529-
539. Retrieved from:
https://openaccess.leidenuniv.nl/bitstream/handle/1887/15394/chapter%202.pdf?sequence=l
4.
Wunderlich, L., K.M. Klonsky, and R.L. De Moura. (2007). Sample Costs to Establish and Produce Apples.
University of California Cooperative Extension. AP-IR-07. Retrieved from:
http://cecentralsierra.ucanr.edu/files/60510.pdf.
1-44

-------
WARM Version 15
Yard Trimmings
May 2019
2 YARD TRIMMINGS
2.1 INTRODUCTION TO WARM AND YARD TRIMMINGS
This chapter describes the methodology used in EPA's Waste Reduction Model (WARM) to
estimate streamlined life-cycle greenhouse gas (GHG) emission factors for yard trimmings beginning at
the point of waste generation. The WARM GHG emission factors are used to compare the net emissions
associated yard trimmings in the following four materials management options: composting, landfilling,
combustion, and anaerobic digestion. Exhibit 2-1 shows the general outline of materials management
pathways for these materials in WARM. For background information on the general purpose and
function of WARM emission factors, see the Introduction & Overview chapter. For more information on
Composting, Landfilling, Combustion, and Anaerobic Digestion, see the chapters devoted to those
processes. WARM also allows users to calculate results in terms of energy, rather than GHGs. The energy
results are calculated using the same methodology described here but with slight adjustments, as
explained in the Energy Impacts chapter.
Exhibit 2-1: Life Cycle of Yard Trimmings in WARM
f	">
Yard trimmings fall under the category of "organics" in WARM. Although paper, wood products,
and plastics are organic materials in the chemical sense, these categories of materials have very
different life-cycle and end-of-life characteristics than yard trimmings and are treated separately in the
municipal solid waste (MSW) stream. Yard trimmings are grass clippings, leaves, and branches. WARM
also calculates emission factors for a mixed organics category, which is a weighted average of the food
waste and yard trimmings emission factors for the waste management pathways relevant to both
materials (i.e., landfilling, combustion, composting, and anaerobic digestion). For more information, see
the Food Waste chapter. The weighting is based on the relative prevalence of these two categories in
the waste stream, according to the latest (2015a) version of EPA's annual report, Advancing Sustainable
Materials Management: Facts and Figures, and as shown in column (c) of Exhibit 2-2.17
17 Note that, unlike for other materials in WARM, the "mixed" category is based on organics' relative prevalence
among materials generated rather than recovered. This is because WARM assumes that users interested in
2-1

-------
WARM Version 15	Yard Trimmings	May 2019
Exhibit 2-2: Relative Prevalence of Yard Trimmings and Food Waste in the Waste Stream in 2015
(a)
(b)
(c)
(d)
(e)

Generation (Short
% of Total Organics
Recovery (Short

Material
Tons)
Generation
Tons)
Recovery Rate
Food Waste
39,730,000
51%
2,100,000
5.3%
Yard Trimmings
34,720,000
44%
21,290,000
61.3%
Source: EPA (2018a).
2.2 LIFE-CYCLE ASSESSMENT AND EMISSION FACTOR RESULTS
The streamlined life-cycle GHG analysis in WARM focuses on the waste generation point, or the
moment a material is discarded, as the reference point and only considers upstream GHG emissions
when the production of new materials is affected by materials management decisions.18 Recycling and
source reduction are the two materials management options that impact the upstream production of
materials, and consequently are the only management options that include upstream GHG emissions.
For more information on evaluating upstream emissions, see the chapters on Recycling and Source
Reduction.
WARM does not include recycling or source reduction management options for yard trimmings.
Yard trimmings cannot be recycled in the traditional sense and sufficient data are not currently available
to model the material and energy inputs for trees and grass prior to becoming yard trimmings waste. As
Exhibit 2-3 illustrates, most of the GHG sources relevant to yard trimmings in this analysis are contained
in the waste management portion of the life cycle assessment, with the exception of increased soil
carbon storage associated with composting of yard trimmings.
Exhibit 2-3: Yard Trimmings GHG Sources and Sinks from Relevant Materials Management Pathways
Materials
Management
Strategies for Yard
Trimmings
GHG Sources and Sinks Relevant to Yard Trimmings
Raw Materials
Acquisition and
Manufacturing
Changes in Forest or Soil
Carbon Storage
End of Life
Source Reduction
Not modeled in WARM due to data limitations
Recycling
Not applicable since yard trimmings cannot be recycled
Composting
Not applicable
Offsets
• Increase in soil carbon
storage
Emissions
•	Transport to compost facility
•	Compost machinery
Combustion
NA
NA
Emissions
•	Transport to WTE facility
•	Combustion-related nitrous oxide
Offsets
•	Avoided utility emissions
composting would be dealing with a mixed organics category that is closer to the current rate of generation, rather
than the current rate of recovery. Since the fraction of recovered food waste is so low, if the shares of yard
trimmings and food waste recovered were used, the mixed organics factor would be essentially the same as the
yard trimmings factor, rather than a mix of organic materials.
18 The analysis is streamlined in the sense that it examines GHG emissions only and is not a comprehensive
environmental analysis of all emissions from materials management.
2-2

-------
WARM Version 15
Yard Trimmings
May 2019
Materials
Management
Strategies for Yard
Trimmings
GHG Sources and Sinks Relevant to Yard Trimmings
Raw Materials
Acquisition and
Manufacturing
Changes in Forest or Soil
Carbon Storage
End of Life
Landfilling
NA
NA
Emissions
•	Transport to landfill
•	Landfilling machinery
•	Landfill methane
Offsets
•	Avoided utility emissions due to
landfill gas combustion
•	Landfill carbon storage
Anaerobic
Digestion
NA
Offsets
Increase in soil carbon
storage from application of
digestate to soils
Emissions
•	Transport to anaerobic digester
•	Equipment use and biogas leakage at
anaerobic digester
•	CH4 and N20 emissions during
digestate curing
•	N20 emissions from land application
of digestate
Offsets
•	Avoided utility emissions due to
biogas to energy
•	Avoided synthetic fertilizer use due to
land application of digestate
NA = Not applicable
WARM analyzes all of the GHG sources and sinks outlined in Exhibit 2-3 to calculate net GHG
emissions per short ton of organic materials generated. GHG emissions arising from the consumer's use
of any product are not considered in WARM'S life-cycle boundaries. Exhibit 2-4 presents the net GHG
emission factors for each materials management strategy calculated in WARM for organic materials.
Additional discussion on the detailed methodology used to develop these emission factors is
presented in sections 2.4.1 through 2.4.6.
Exhibit 2-4: Net Emissions for Yard Trimmings and Mixed Organics under Each Materials Management Option
(MTCChE/Short Ton)	
Material
Net Source Reduction
(Reuse) Emissions for
Current Mix of Inputs
Net
Recycling
Emissions
Net
Composting
Emissions
Net
Combustion
Emissions
Net
Landfilling
Emissions
Net Anaerobic
Digestion
Emissions3
Yard Trimmings
NA
NA
-0.15
-0.17
-0.18
-0.09
Grass
NA
NA
-0.15
-0.17
0.13
-0.06
Leaves
NA
NA
-0.15
-0.17
-0.52
-0.14
Branches
NA
NA
-0.15
-0.17
-0.50
-0.22
Mixed Organics
NA
NA
-0.16
-0.15
0.21
-0.06
Note: Negative values denote net GHG emission reductions or carbon storage from a materials management practice.
NA = Not applicable.
3 Emission factors for dry digestion with curing of digestate before land application.
2.3 RAW MATERIALS ACQUISITION AND MANUFACTURING
WARM does not consider GHG emissions associated with raw materials acquisition or
manufacturing for yard trimmings because this life-cycle stage is only applicable to the source reduction
and recycling pathways, which are not modeled in WARM for yard trimmings, as discussed above.
2-3

-------
WARM Version 15
Yard Trimmings
May 2019
2.4 MATERIALS MANAGEMENT METHODOLOGIES
Landfilling, composting, combustion, and anaerobic digestion are the four management options
used to manage yard trimmings. Residential and commercial land management activities such as
landscaping and gardening generate yard trimmings, which are typically either composted onsite,
shredded with a mulching mower and used for landscaping onsite, or placed on the curb for transport to
central facilities for either combustion, composting landfilling, or anaerobic digestion. Since 1990, many
municipalities have implemented programs and policies designed to divert yard trimmings from landfills,
and as a result, yard trimmings are increasingly composted or mulched onsite or collected for mulching
and composting at a central facility (EPA, 2018a).
2.4.1	Source Reduction
Unlike food waste, yard trimmings do not generally require extensive material or fossil fuel
energy inputs prior to becoming waste. While some material and energy inputs are used during the life
of trees and grasses (i.e., fuel for lawn mowing, fertilizers), sufficient data needed to model raw material
acquisition and production emissions or storage from yard trimmings are not currently available.
Therefore, WARM does not consider GHG emissions or storage associated with source reduction of yard
trimmings.
2.4.2	Recycling
Recycling, as modeled in WARM (i.e., producing new products using end-of-life materials), does
not commonly occur with the yard trimmings materials modeled in WARM. Therefore, WARM does not
consider GHG emissions or storage associated with the traditional recycling pathway for yard trimmings.
However, yard trimmings can be converted to compost, a useful soil amendment, as described in section
2.4.3.
2.4.3	Composting
2.4.3.1 Developing the Emissions Factor for the Composting of Yard Trimmings
Composting yard trimmings results in increased carbon storage when compost is applied to
soils. The net composting emission factor is calculated as the sum of emissions from transportation,
processing of compost, the carbon storage resulting from compost application, and the fugitive
emissions of methane (CH4) and nitrous oxide (N20) produced during decomposition.19 WARM currently
assumes that carbon dioxide (C02) emissions that occur as a result of the composting process are
biogenic and are not counted (for further explanation, see the text box on biogenic carbon in the
Introduction and Background chapter). Exhibit 2-5 details these components for yard trimmings and
mixed organics. For additional information on composting in WARM, see the Composting chapter. The
two emission sources and one emission sink resulting from the composting of organics are:
• Nonbiogenic C02 emissions from collection and transportation: T ransportation of yard trimmings
to the central composting site results in nonbiogenic C02 emissions.20 In addition, during the
composting process the compost is mechanically turned, and the operation of this equipment
also results in nonbiogenic C02 emissions.
19	These fugitive emission sources were added in June 2014 to WARM Version 13.
20	Transportation emissions from delivery of finished compost from the composting facility to its final destination
were not counted.
2-4

-------
WARM Version 15
Yard Trimmings
May 2019
•	Fugitive Emissions ofCH4 and N20: Microbial activity during composting decomposes waste into
a variety of compounds, which generates small amounts of CH4 and N20 gas, a net contributor
to the GHG emissions associated with the composting pathway (for more information on
fugitive emissions, please refer to the Composting chapter).
•	Carbon Storage: When compost is applied to the soil, some of the carbon contained in the
compost does not decompose for many years and therefore acts as a carbon sink.
Exhibit 2-5: Components of the Composting Net Emission Factor for Yard Trimmings and Mixed Organics

Composting of Post-Consumer Material



(GHG Emissions in MTC02E/Short Ton)



Raw Material Acquisition


Compost

Net Emissions

and Manufacturing
Transportation
Compost
CH4 and
Soil Carbon
(Post-
Material
(Current Mix of Inputs)
to Composting
CO?
n2o
Storage
Consumer)
Yard






Trimmings3
NA
0.02
-
0.07
-0.24
-0.15
Grass
NA
0.02
-
0.07
-0.24
-0.15
Leaves
NA
0.02
-
0.07
-0.24
-0.15
Branches
NA
0.02
-
0.07
-0.24
-0.15
Mixed






Organics
NA
0.02
-
0.07
-0.24
-0.16
NA = Not applicable.
3 Yard trimmings are a 50%, 25%, 25% weighted average of grass, leaves, and branches, based on U.S. generation data from EPA (2015a).
Transportation energy emissions occur when fossil fuels are used to collect and transport yard
trimmings to a composting facility, and then to operate the composting equipment that turns the
compost. To calculate the emissions, WARM relies on assumptions from FAL (1994) for the equipment
emissions and NREL's US Life Cycle Inventory Database (USLCI) (NREL, 2015). The NREL emission factor
assumes a diesel, short-haul truck. Exhibit 2-6 provides the emissions associated with transporting and
turning compost.
Exhibit 2-6: Emissions Associated with Transporting and Turning Compost
Material
Diesel Fuel
Required to Collect and
Transport One Ton
(million Btu)a
Diesel Fuel Required to
Turn the Compost Piles
(million Btu)a
Total Energy
Required for
Composting (million
Btu)
Total C02 Emissions
from Composting
(MTCOzE)
All Material Types
0.04
0.22
0.26
0.02
3 Based on estimates found on Table 1-17 on page 1-32 of FAL (1994).
WARM currently assumes that carbon from compost remains stored in the soil through two
main mechanisms: direct storage of carbon in depleted soils (the "soil carbon restoration" effect)21 and
carbon stored in non-reactive humus compounds (the "increased humus formation" effect).22 The
carbon values from the soil carbon restoration effect are scaled according to the percentage of compost
that is passive, or non-reactive, which is assumed to be 52 percent (Cole, 2000). The weighted soil
21	EPA evaluated the soil carbon restoration effect using Century, a plant-soil ecosystems model that simulates
long-term dynamics of carbon, nitrogen, phosphorous, and sulfur in soils. For more information, see the
Composting chapter.
22	EPA evaluated the increased humus formation effect based on experimental data compiled by Dr. Michael Cole
of the University of Illinois. These estimates accounted for both the fraction of carbon in the compost that is
considered passive and the rate at which passive carbon is degraded into CO2. For more information, see the
Composting chapter.
2-5

-------
WARM Version 15
Yard Trimmings
May 2019
restoration value is then added to the increased humus formation effect in order to estimate the total
sequestration value associated with composting. The inputs to the calculation are shown in Exhibit 2-7.
Exhibit 2-7: Soil Carbon Effects as Modeled in Century Scenarios (MTCOzE/Short Ton of Organics)
Scenario
Soil Carbon Restoration
Increased Humus
Formation
Net Carbon
Flux3
Unweighted
Proportion of C
that is Not Passive
Weighted
estimate
Annual application of 32
tons of compost per acre
-0.04
48%
-0.07
-0.17
-0.24
3 The net carbon flux sums each of the carbon effects together and represents the net effect of composting a short ton of yard trimmings in
MTCO2E.
The nonbiogenic C02 emissions from transportation, collection, and compost turning are added
to the compost carbon sink in order to calculate the net composting GHG emission factors for each
organics type. As Exhibit 2-5 illustrates, WARM estimates that the net composting GHG factor for yard
trimmings is the same for all sources of compost.
2.4.4 Combustion
2.4.4.1 Developing the Emissions Factor for the Combustion of Yard Trimmings
The combusttion of organics results in a net emissions offset (negative emissions) due to the
avoided utility emissions associated with energy recovery from waste combustion. The combustion net
emission factor is calculated as the sum of emissions from transportation of waste to the combustion
facility, nitrous oxide emissions from combustion, and the avoided C02 emissions from energy recovery
in a waste-to-energy (WTE) plant. Although combustion also releases the carbon contained in yard
trimmings in the form of C02, these emissions are considered biogenic and are not included in the
WARM net emission factor. Exhibit 2-8 presents these components of the net combustion emission
factor for each organic material. For additional information on combustion in WARM, see the
Combustion chapter. The two emissions sources and one emissions offset that result from the
combusting of organics are:
•	C02 emissions from transportation of waste. Transporting waste to the combustion facility and
transporting ash from the combustion facility to a landfill both result in transportation C02
emissions.
•	Nitrous oxide emissions from combustion. Waste combustion results in measurable emissions of
nitrous oxide (N20), a GHG with a high global warming potential (EPA, 2018b).
•	Avoided utility C02 emissions. Combustion of MSW with energy recovery in a WTE plant also
results in avoided C02 emissions at utilities.
Exhibit 2-8: Components of the Combustion Net Emission Factor for Yard Trimmings and Mixed Organics
(MTCOzE/Short Ton)	

Raw Material







Acquisition and





Net

Manufacturing




Steel
Emissions

(Current Mix of
Transportation
C02 from
N20 from
Utility
Recovery
(Post-
Material
Inputs)
to Combustion
Combustion
Combustion
Emissions
Offsets
Consumer)
Yard Trimmings
NA
0.01
-
0.04
-0.21
-
-0.17
Grass
NA
0.01
-
0.04
-0.21
-
-0.17
Leaves
NA
0.01
-
0.04
-0.21
-
-0.17
Branches
NA
0.01
-
0.04
-0.21
-
-0.17
Mixed Organics
NA
0.01
-
0.04
-0.20
-
-0.15
2-6

-------
WARM Version 15
Yard Trimmings
May 2019
NA = Not applicable
For the C02 emissions from transporting waste to the combustion facility, and ash from the
combustion facility to a landfill, EPA used an estimate of 60 lbs C02 per ton of MSW for transportation of
mixed MSW developed by FAL (1994). EPA then converted the Franklin Associates estimate from pounds
of C02 per ton of mixed MSW to MTC02E per ton of mixed MSW and applied it to estimate C02
emissions from transporting one short ton of mixed MSW and the resulting ash. WARM assumes that
transportation of yard trimmings and mixed organics uses the same amount of energy as transportation
of mixed MSW.
Studies compiled by the Intergovernmental Panel on Climate Change (IPCC) show that MSW
combustion results in measurable emissions of N20, a GHG with a high global warming potential (IPCC,
2006). The IPCC compiled reported ranges of N20 emissions, per metric ton of waste combusted, from
six classifications of MSW combustors. WARM averages the midpoints of each range and converts the
units to MTC02E of N20 per ton of MSW. Because the IPCC did not report N20 values for combustion of
individual components of MSW, WARM uses the same value for yard trimmings and mixed organics.
Most WTE plants in the United States produce electricity and only a few cogenerate electricity
and steam (EPA, 2006). In this analysis, EPA assumed that the energy recovered with MSW combustion
would be in the form of electricity, as shown in Exhibit 2-9. The exhibit shows emission factors for mass
burn facilities (the most common type of WTE plant). EPA used three data elements to estimate the
avoided electric utility C02 emissions associated with combustion of waste in a WTE plant: (1) the energy
content of each waste material, (2) the combustion system efficiency in converting energy in MSW to
delivered electricity, and (3) the electric utility C02 emissions avoided per kilowatt-hour (kWh) of
electricity delivered by WTE plants.
Exhibit 2-9: Utility GHG Emissions Offset from Combustion of Yard Trimmings
(a)
(b)
(c)
(d)
(e)



Emission Factor for Utility-
Avoided Utility GHG per

Energy Content
Combustion
Generated Electricity (MTCO2E/
Short Ton Combusted

(Million Btu per
System
Million Btu of Electricity
(MTCOzE/Short Ton)
Material
Short Ton)
Efficiency (%)
Delivered)
(e = b x c x d)
Yard Trimmings
5.6
17.8%
0.21
0.21
To estimate the gross GHG emissions per ton of waste combusted, EPA summed emissions from
combustion N20 and transportation C02. These emissions were then added to the avoided utility
emissions in order to calculate the net GHG emission factor, shown in Exhibit 2-9. WARM estimates that
combustion of yard trimmings results in a net emission reduction.
2.4.5 Landfilling
2.4.5.1 Developing the Emissions Factor for the Landfilling of Yard Trimmings
Landfilling organics can result in either net carbon storage or net carbon emissions, depending
on the specific properties of the organic material. The landfilling emissions factor is calculated as the
sum of emissions from transportation of waste to the landfill and operation of landfill equipment,
methane emissions from landfilling, and the carbon storage resulting from undecomposed carbon
remaining in landfills. Exhibit 2-10 presents the components of the landfilling emission factor for each
yard trimmings material. For additional information on landfilling in WARM, see the Landfilling chapter.
The two emissions sources and one emissions sink that result from the landfilling of organics are:
2-7

-------
WARM Version 15
Yard Trimmings
May 2019
•	Transportation of organic waste. Transportation of yard trimmings to landfill results in
anthropogenic C02 emissions, due to the combustion of fossil fuels in the vehicles used to haul
the wastes.
•	Methane emissions from landfilling. When yard trimmings are landfilled, anaerobic bacteria
degrade the materials, producing CH4 and C02, collectively referred to as landfill gas (LFG). Only
the CH4 portion of LFG is counted in WARM, because the C02 portion is considered of biogenic
origin and therefore is assumed to be offset by C02 captured by regrowth of the plant sources of
the material.
•	Landfill carbon storage. Because yard trimmings are not completely decomposed by anaerobic
bacteria, some of the carbon in them remains stored in the landfill. This stored carbon
constitutes a sink (i.e., negative emissions) in the net emission factor calculation.
Exhibit 2-10: Landfilling Emission Factors for Yard Trimmings and Mixed Organics (MTCChE/Short Ton)

Raw Material






Acquisition and


Avoided C02
Landfill
Net Emissions

Manufacturing
Transportation
Landfill
Emissions from
Carbon
(Post-
Material Type
(Current Mix of Inputs)
to Landfill
ch4
Energy Recovery
Storage
Consumer)
Yard Trimmings
NA
0.02
0.36
-0.02
-0.54
-0.18
Grass
NA
0.02
0.27
-0.02
-0.14
0.13
Leaves
NA
0.02
0.28
-0.02
-0.79
-0.52
Branches
NA
0.02
0.60
-0.05
-1.06
-0.50
Mixed Organics
NA
0.02
0.53
-0.04
-0.30
0.21
Note: The emission factors for landfill Cm presented in this table assume that the methane management practices and decay rates at the
landfill are an average of national practices.
Negative values denote GHG emission reductions or carbon storage.
NA = Not applicable; upstream raw material acquisition and manufacturing GHG emissions are not included in landfilling since the life-cycle
boundaries in WARM start at the point of waste generation and landfilling does not affect upstream GHG emissions.
Transportation energy emissions occur when fossil fuels are used to collect and transport yard
trimmings to a landfill, and then to operate the landfill equipment. To calculate the emissions, WARM
relies on assumptions from FAL (1994) for the equipment emissions and NREL's US Life Cycle Inventory
Database (USLCI) (NREL, 2015). The NREL emission factor assumes a diesel, short-haul truck. EPA then
converted the Franklin Associates estimate from pounds of C02 per ton of mixed MSW to MTC02E per
ton of mixed MSW and applied it to estimate C02 emissions from transporting one short ton of mixed
MSW. WARM assumes that transportation of yard trimmings uses the same amount of energy as
transportation of mixed MSW.
WARM calculates CH4 emission factors for landfilled materials based on the CH4 collection
system type installed at a given landfill. There are three categories of landfills modeled in WARM: (1)
landfills that do not recover LFG, (2) landfills that collect the LFG and flare it without recovering the flare
energy, and (3) landfills that collect LFG and combust it for energy recovery by generating electricity.
The Excel version of WARM allows users to select component-specific decay rates based on different
assumed moisture contents of the landfill and landfill gas collection efficiencies for a series of landfill
management scenarios. The tables in this section show values using the national average moisture
conditions, based on the national average precipitation at landfills in the United States and for landfill
gas collect efficiency from "typical" landfill operations in the United States. The decay rate and
management scenario assumed influences the landfill gas collection efficiency. For further explanation,
see the Landfilling chapter.
Exhibit 2-11 depicts the emission factors for each LFG collection type based on the national
average landfill moisture scenario and "typical" landfill management operations. Overall, landfills that
2-8

-------
WARM Version 15
Yard Trimmings
May 2019
do not collect LFG produce the most CH4 emissions. The emissions generated per short ton of material
drop by approximately half for yard trimmings if the landfill recovers and flares CH4 emissions. These
emissions are even lower in landfills where LFG is recovered for electricity generation because LFG
recovery offsets emissions from avoided electricity generation.23
Exhibit 2-11: Landfill ChU Emissions for Three Different Methane Collection Systems, National "Average" Landfill
Moisture Conditions, Typical Landfill Management Operations, and National Average Grid Mix (MTCOzE/Wet
Short Ton)
Material
Landfills without LFG
Recovery
Landfills with LFG Recovery
and Flaring
Landfills with LFG Recovery
and Electric Generation
Yard Trimmings
0.73
0.35
0.29
Grass
0.51
0.25
0.23
Leaves
0.59
0.26
0.22
Branches
1.30
0.65
0.44
Note: Negative values denote GHG emission reductions or carbon storage.
A portion of the carbon contained in yard trimmings does not decompose after disposal and
remains stored in the landfill. Because this carbon storage would not normally occur under natural
conditions (virtually all of the carbon in the organic material would be released as C02, completing the
photosynthesis/respiration cycle), this is counted as an anthropogenic carbon sink. The carbon storage
associated with each material type depends on the initial carbon content, the extent to which that
carbon decomposes into CH4 in landfills, and temperature and moisture conditions in the landfill. The
background and details of the research underlying the landfill carbon storage factors are detailed in the
Landfilling chapter. As Exhibit 2-12 illustrates, branches and leaves result in the highest amount of
carbon storage.
Exhibit 2-12: Calculation of the Carbon Storage Factor for Landfilled Yard Trimmings
(a)
(b)
(c)
(d)
(e)

Ratio of Carbon

Ratio of Carbon Storage


Storage to Dry Weight

to Wet Weight (grams of


(grams of Carbon
Ratio of Dry
Carbon/wet gram of
Amount of Carbon Stored

Stored/dry gram of
Weight to
Material)
(MTCOzE per Wet Short
Material
Material)3
Wet Weight
(d = b x c)
Ton)
Yard Trimmings



0.54
Grass
0.24
0.18
0.04
0.14
Leaves
0.39
0.62
0.24
0.79
Branches
0.38
0.84
0.32
1.06
Note: Yard trimmings are calculated as a weighted average of grass, leaves and branches, currently based on an estimate in the Facts and
Figures report for 2007 (EPA, 2008, p. 58). This information is not updated annually by EPA.
3 Based on estimates developed by James W. Levis, Morton Barlaz, Joseph F. DeCarolis, and S. Ranji Ranjithan at North Carolina State University;
see Levis et al. (2013).
The landfill CH4 and transportation emissions sources are added to the landfill carbon sink in
order to calculate the net GHG landfilling emission factors for each yard trimmings material, shown in
the final three columns of .
Exhibit 2-13 for landfills equipped with different LFG collection systems. The final net emission
factors indicate that landfilling leaves and branches results in a net carbon sink. This negative net
23 These values include a utility offset credit for electricity generation that is avoided by capturing and recovering
energy from landfill gas to produce electricity. The utility offset credit is calculated based on the non-baseload GHG
emissions intensity of U.S. electricity generation, because it is non-baseload power plants that will adjust to
changes in the supply of electricity from energy recovery at landfills.
2-9

-------
WARM Version 15
Yard Trimmings
May 2019
emission factor is due to the fact that these materials do not readily degrade in landfills and a
substantial fraction of the carbon in these materials remains in the landfill permanently.
Exhibit 2-13: Components of the Landfill Emission Factor for the Three Different Methane Collection Systems
Typically Used In Landfills (MTCOzE/Short Ton)	
(a)

(b)

(c)
(d)

(e)







Net GHG Emissions from

Net GHG Emissions from CH4



Landfilling


Generation




(e = b + c + d)








Landfills



Landfills



Landfills
with LFG


Landfills
with LFG

GHG
Landfills
with
Recovery

Landfills
with LFG
Recovery

Emissions
without
LFG
and

without
Recovery
and
Net Landfill
From
LFG
Recover
Electricity

LFG
and
Electric
Carbon
Transpor-
Recover
y and
Generatio
Material
Recovery
Flaring
Generation
Storage
tation
y
Flaring
n
Yard








Trimmings
0.73
0.35
0.29
-0.54
0.02
0.21
-0.18
-0.24
Grass
0.51
0.25
0.23
-0.14
0.02
0.39
0.11
0.09
Leaves
0.59
0.26
0.22
-0.79
0.02
-0.18
-0.52
-0.56
Branches
1.30
0.65
0.44
-1.06
0.02
0.26
-0.38
-0.61
Note: Negative values denote GHG emission reductions or carbon storage.
2.4.6 Anaerobic Digestion
2.4.6.1 Developing the Emissions Factor for the Anaerobic Digestion of Food Waste
The anaerobic digestion emissions factor is calculated as the sum of emissions from
transportation of waste to the anaerobic digester and operation of anaerobic digester equipment,
methane emissions from anaerobic digesting, the carbon storage resulting from applying the digestate
to soil, the net electricity export to grid and fertilizer offsets. Due to the high amount of preprocessing
that would be required, EPA assumed that wet digester operators do not use yard trimmings as a
feedstock. Therefore, dry digestion is the only digestion option for yard trimmings and mixed organics.
Exhibit 2-14: Dry Anaerobic Digestion Emission Factors for Yard Trimmings with Digestate Curing
(MTCChE/Short Ton) presents these components of the anaerobic digestion emission factor for yard
trimmings and mixed organics with digestate curing and Exhibit 2-15 with digestate directly applied to
land. For additional information on anaerobic digestion in WARM, see the Anaerobic Digestion chapter.
The three emissions sources and three emissions sink that result from the anaerobically digesting food
waste are:
•	Transportation Energy. WARM includes emissions associated with transporting and anaerobic
digestion of the material. Transportation energy emissions occur when fossil fuels are
combusted to collect and transport material to the anaerobic digestion facility, to transport
digestate for land application, and to operate on-site equipment for curing and spreading
digestate.
•	Process Energy. Preprocessing includes grinding, screening, and mixing the feedstock before
they are fed into the reactor. The emissions associated with electricity and diesel consumption
during preprocessing and operation are assessed in WARM for dry digesters. WARM estimates
the emissions associated with two scenarios for digestate beneficial use: curing the digestate
and applying the resulting compost to agricultural lands, or directly applying digestate to
agricultural lands without curing.
2-10

-------
WARM Version 15
Yard Trimmings
May 2019
•	Avoided Utility Emissions. Methane biogas is produced during the digestion process and
collected for combustion. WARM models the recovery of biogas for electricity generation and
assumes that this electricity offsets non-baseload electricity generation in the power sector.
•	Avoided Fertilizer Application. The application of digestate to agricultural lands is able to offset a
portion of the synthetic fertilizer application needed for agricultural lands due to its high
nutrient content. WARM includes avoided fertilizer offsets for both nitrogen and phosphorous in
synthetic fertilizers.
•	Process Non-Energy. Fugitive emissions occur at the digester, during the curing process, and
after land application.
•	Soil Carbon Storage. Similar to carbon from compost applied to agricultural lands, EPA assumed
that carbon from digestate applied to agricultural lands remains stored in the soil through two
main mechanisms: direct storage of carbon in depleted soils and carbon stored in non-reactive
humus compounds.
Exhibit 2-14: Dry Anaerobic Digestion Emission Factors for Yard Trimmings with Digestate Curing (MTCOzE/Short
Ton)







Net


Avoided
Avoided

Process

Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Yard Trimmings
0.02
-0.04
-0.01
-0.16
0.09
0.00
-0.09
Grass
0.02
-0.04
-0.01
-0.04
0.07
0.00
0.00
Leaves
0.02
-0.02
-0.01
-0.24
0.10
0.00
-0.14
Branches
0.02
-0.06
-0.01
-0.31
0.13
0.00
-0.22
Mixed Organics
0.02
-0.09
-0.01
-0.09
0.11
0.00
-0.06
Negative values denote GHG emission reductions or carbon storage.
Exhibit 2-15: Dry Anaerobic Digestion Emission Factors for Yard Trimmings with Direct Land Application
(MTCChE/Short Ton)







Net


Avoided
Avoided

Process

Emissions

Process
Utility
Fertilizer
Soil Carbon
Non-
Transportation
(Post-
Material
Energy
Emissions
Application
Storage
Energy
Energy
Consumer)
Yard Trimmings
0.02
-0.04
-0.01
-0.38
0.06
0.00
-0.35
Grass
0.02
-0.04
-0.01
-0.10
0.06
0.00
-0.06
Leaves
0.02
-0.02
-0.01
-0.58
0.06
0.00
-0.53
Branches
0.02
-0.06
-0.01
-0.75
0.07
0.00
-0.73
Mixed Organics
0.02
-0.09
-0.01
-0.22
0.09
0.00
-0.21
WARM accounts for the GHG emissions resulting from fossil fuels used in vehicles collecting and
transporting waste to the anaerobic digestion facility. Diesel is used for transporting the feedstock and
solids to the anaerobic digester. To calculate the emissions, WARM relies on assumptions NREL's US Life
Cycle Inventory Database (USLCI) (NREL, 2015). The NREL emission factor assumes a diesel, short-haul
truck.
The recovery of heat and electricity from the combusted biogas offsets the combustion of other
fossil fuel inputs. WARM assumes that the combusted biogas produces electricity that offsets non-
baseload electricity generation. Electricity generation from combustion of biogas is assumed to be
unavailable for 15 percent of operation time and the process is assumed to be 29 percent efficient (EPA,
2013). The methane generated, and electricity exported to the grid is shown in Exhibit 2-16.
2-11

-------
WARM Version 15	Yard Trimmings	May 2019
Exhibit 2-16: Methane Generation, Treatment, and Use by Material Type for Dry Digestion




Mass of




Mass of
Mass of
Mass of
Methane
Energy from



Methane
Methane
Methane
Combusted
Combusted
Electricity
Net Electricity

Generated
Leaked
Flared
for Energy
Methane
Generation
to the Grid
Material
(kg/ton)
(kg/ton)
(kg/ton)
(kg/ton)
(MMBtu/ton)
(kWh/ton)
(kWh/ton)
Yard Trimmings
20.7
0.41
3.04
17.3
0.81
69.6
51.5
Grass
20.5
0.41
2.99
17.06
0.81
68.8
50.6
Leaves
13.1
0.26
1.91
10.9
0.52
44.0
25.9
Branches
28.9
0.58
4.26
24.1
1.14
97.1
78.9
Mixed Organics
41.1
0.81
6.03
34.3
1.62
138
120
If the digestate is cured before land application, the solids are aerobically cured in turned
windrows. The resulting compost is then screened, transported to agriculture lands, and used in place of
a portion of the conventional nitrogen and phosphorus fertilizer that would be needed for the same
agricultural lands. Diesel fuel is consumed during this process. If the digestate is not cured, it is directly
applied to agricultural lands.
EPA assumed that digestate applied to agricultural land allows for some synthetic fertilizer use
to be avoided. WARM includes avoided fertilizer offsets for land application of the digestate generated
from anaerobic digestion but not for compost generated from composting due to the difference in
feedstocks used for each material management pathway, shown in Exhibit 2-17. Further information can
be found in Anaerobic Digestion chapter.
Exhibit 2-17: Nitrogen and Phosphorous Fertilizer Offset by Material Type

Nitrogen Fertilizer
Phosphorous
Nitrogen
Phosphorous

Offset
Fertilizer Offset
Fertilizer Offset
Fertilizer Offset
Material
(kg N/ton)
(kg P/ton)
(MTC02e/ton)
(MTC02e/ton)
Yard Trimmings
0.643
0.844
-0.005
-0.001
Grass
0.628
0.323
-0.005
-0.001
Leaves
0.626
1.218
-0.005
-0.002
Branches
0.691
1.511
-0.006
-0.002
Mixed Organics
0.873
1.074
-0.007
-0.002
WARM calculates the carbon storage impact of direct storage of carbon in depleted soils and
carbon stored in non-reactive humus compounds separately and then sums them to estimate the
carbon storage factor associated with each short ton of organics composted. For more information on
carbon storage calculations, see the Composting chapter, which includes information on the Century
model framework and simulations.
To estimate the gross GHG emissions per ton of waste combusted, EPA summed emissions from
transportation, processing and operations, and fugitive emissions. These emissions were then added to
the avoided utility emissions, avoided fertilizer application, and soil carbon storage in order to calculate
the net GHG emission factor, shown in Exhibit 2-14: Dry Anaerobic Digestion Emission Factors for Yard
Trimmings with Digestate Curing (MTCChE/Short Ton) and Exhibit 2-15. WARM estimates that anaerobic
digestion of yard trimmings results in a net emission reduction for both the curing and non-curing
scenarios.
2-12

-------
WARM Version 15
Yard Trimmings
May 2019
2.5 LIMITATIONS
The results of the analysis presented in this chapter are limited by the reliability of the various
data elements used. This section details limitations, caveats, and areas of current and future research.
2.5.1	Composting
EPA is currently conducting research into process emissions from composting, carbon storage
due to compost application, and other issues that are relevant to these calculations.
•	As in the other chapters of this report, the GHG impacts of composting reported in this chapter
evaluate emissions relative to other possible disposal options for yard trimmings (i.e., landfilling
and combustion). This assumes that yard trimmings will be collected for end-of-life
management by one of these alternative materials management practices. Yard trimmings,
however, can also be simply left on the ground to decompose. This pathway is not modeled in
WARM, because EPA would need to analyze the effect of decomposing yard trimmings in their
home soil—and the associated soil carbon storage benefits—to develop absolute GHG emission
factors for composting yard trimmings at a central facility relative to a baseline of leaving yard
trimmings on the ground where they fall.
•	Due to data and resource constraints, the analysis considers a small sampling of feedstocks and
a single compost application (cropland soil). EPA analyzed two types of compost feedstocks-
yard trimmings and food waste—although sewage sludge, animal manure, and several other
compost feedstocks also may have significant GHG implications. Similarly, it was assumed that
compost was applied to degraded agricultural soils growing corn, despite widespread use of
compost in specialty crops, land reclamation, silviculture, horticulture, and landscaping.
•	This analysis did not consider the full range of soil conservation and management practices that
could be used in combination with application of compost, and the impacts of those practices on
carbon storage. Research indicates that adding compost to agricultural soils in conjunction with
various conservation practices enhances the generation of soil organic matter to a much greater
degree than applying compost alone. Examples of these conservation practices include
conservation tillage, no-till, residue management, crop rotation, wintering, and summer fallow
elimination.
•	In addition to the carbon storage benefits of adding compost to agricultural soils, composting
may lead to improved soil quality, improved plant productivity, improved soil water retention,
and cost savings. As discussed earlier, nutrients in compost tend to foster soil fertility (Brady and
Weil, 1999). In fact, composts have been used to establish plant growth on land previously
unable to support vegetation. In addition to these biological improvements, compost also may
lead to cost savings associated with avoided waste disposal, particularly for feedstocks such as
sewage sludge and animal manure.
2.5.2	Landfilling
•	WARM currently assumes that 87 percent of MSW landfill CH4 is generated at landfills with LFG
recovery systems (EPA, 2018b). The net GHG emissions from landfilling each material are quite
sensitive to the LFG recovery rate, so the application of landfill gas collection systems at landfills
will have an effect on lowering the emission factors presented here over time. WARM is
updated annually to account for changes in the percent of MSW landfill CH4 that is collected at
U.S. landfills.
2-13

-------
WARM Version 15
Yard Trimmings
May 2019
2.5.3	Combustion
•	Opportunities exist for the combustion system efficiency of WTE plants to improve over time. As
efficiency improves, more electricity can be generated per ton of waste combusted (assuming
no change in utility emissions per kWh), resulting in a larger utility offset, and the net GHG
emissions benefit from combustion of MSW will increase.
•	The reported ranges for N20 emissions from combustion of organics were broad. In some cases,
the high end of the range was ten times the low end of the range. Research has indicated that
N20 emissions vary with the type of waste burned. In the absence of better data on the
composition and N20 emissions from organics combustion on a national scale in the United
States, the average value used for yard trimmings should be interpreted as an approximate
value.
•	This analysis used the non-baseload mix of electricity generation facilities as the proxy for
calculating the GHG emissions intensity of electricity production that is displaced at the margin
from energy recovery at WTE plants and LFG collection systems. Actual avoided utility GHG
emissions will depend on the specific mix of power plants that adjust to an increase in the
supply of electricity, and could be larger or smaller than estimated in these results.
2.5.4	Anaerobic Digestion
•	WARM assumes that the biogas generated during anaerobic digestion is used in an internal
combustion engine to generate electricity which is used to offset grid electricity. Multiple other
uses have been identified for the biogas through EPA's review of literature and stakeholder
engagement. These uses were not modeled here.
•	WARM assumes that the digestate generated during anaerobically digesting organic waste is
applied to agricultural land; however, EPA's review of literature and stakeholder engagement
identified other uses for digestate beyond land application. These have not been addressed
within WARM.
•	In discussions with stakeholders and in EPA's review of literature, it was indicated that there was
little evidence that different anaerobic digestion reactor configurations have significantly
different methane yields. However, the net GHG emissions from anaerobically digesting yard
trimmings are sensitive to methane yield assumptions. EPA believes that the modeling approach
used in WARM provides reasonable estimates of the GHG emissions that represent a wide range
of anaerobic digestion configurations.
2.6 REFERENCES
Barlaz, M.A. (2008). Memorandum to Parties Interested in Carbon Sequestration from Municipal Solid
Waste: "Corrections to Previously Published Carbon Storage Factors." February 27, 2008.
Barlaz, M.A. (2005). Letter to Randy Freed, ICF International: "Decomposition of Leaves." June 29, 2005.
Barlaz, M.A. (1998). Carbon storage during biodegradation of municipal solid waste components in
laboratory-scale landfills. Global Biogeochem. Cycles, 12 (2): 373-380.
Brady, N., & R. Weil. (1999). The Nature and Properties of Soils. Upper Saddle River, NJ: Prentice Hall.
Cole, M. (2000). Personal communication between Dr. Michael Cole, University of Illinois, and Randy
Freed, ICF Consulting, July 3, 2000.
2-14

-------
WARM Version 15
Yard Trimmings
May 2019
EPA. (2018a). Advancing Sustainable Materials Management: Facts and Figures 2015. (EPA530-F-18-
004).Washington, DC: U.S. Government Printing Office. Retrieved from
https://www.epa.gov/facts-and-figures-about-materials-waste-and-recycling/advancing-
sustainable-materials-management.
EPA. (2018b). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 - 2016. (EPA 430-R-18-004).
Washington, DC: U.S. Government Printing Office. Retrieved from
https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventorv-report-archive.
EPA. (2013). The Landfill Methane Outreach Program (LMOP) LFGE Benefits Calculator. Available online
at: http://www.epa.gov/lmop/proiects-candidates/lfge-calculator.html.
EPA. (2008). Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and
Figures for 2007. United States Environmental Protection Agency, Office of Solid Waste. EPA530-
R-08-010. Retrieved from http://www.epa.gov/epawaste/nonhaz/municipal/pubs/msw07-
rpt.pdf.
EPA. (2006). Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and
Sinks. Washington, DC: U.S. Environmental Protection Agency.
EPA. (1998). AP-42 Emission Factors for Municipal Solid Waste Landfills - Supplement E. Washington, DC:
U.S. Environmental Protection Agency.
FAL. (1994). The Role of Recycling in Integrated Solid Waste Management to the Year 2000. Franklin
Associates Ltd. (Stamford, CT: Keep America Beautiful, Inc.), September.
Harrington, K. (1997). Personal communication between Karen Harrington, Minnesota Office of
Environmental Assistance, and ICF Consulting, October 1997. Value reported by an RDF facility
located in Newport, MN.
IPCC. (2006). 2006IPCC Guidelines for National Greenhouse Gas Inventories, Volume 5: Waste, Chapter
3: Solid Waste Disposal. Intergovernmental Panel on Climate Change. Retrieved from
http://www.ipcc-nggip.iges.or.ip/public/2006gl/vol5.html.
2-15

-------