Greenhouse Gas Emissions in the United States Food System: Current

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Cite This: Environ. Sci. Technol. XXXX, XXX, XXX−XXX

Greenhouse Gas Emissions in the United States Food System: Current and Healthy Diet Scenarios Claudia Hitaj,*,† Sarah Rehkamp,† Patrick Canning,† and Christian J. Peters‡ †

Economic Research Service, U.S. Department of Agriculture, Washington, DC 20250, United States Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts 02111, United States

‡

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S Supporting Information *

ABSTRACT: We estimate the impact on greenhouse gas emissions (GHGE) of shifting from the current average United States diet to four alternative diets that meet the 2010 Dietary Guidelines for Americans (DGA). In contrast to prior studies, which rely on process-based life-cycle-analysis GHGE estimates from the literature for particular food items, we combine a diet model, an environmentally extended input−output model of energy use in the U.S. food system, and a biophysical model of land use for crops and livestock to estimate food system GHGE from the combustion of fossil fuels and from biogenic sources, including enteric fermentation, manure management, and soil management. We find that an omnivore diet that meets the DGA while constraining cost leaves food system GHGE essentially unchanged relative to the current baseline diet (985 000 000 tons of CO2 eq or 3191 kilograms of CO2 eq per capita per year), while a DGAcompliant vegetarian and a DGA-compliant omnivore diet that minimizes energy consumption in the food system reduce GHGE by 32% and 22%, respectively. These emission reductions were achieved mainly through quantity and composition changes in the meat, poultry, fish; dairy; and caloric sweeteners categories. Shifting from current to healthy diets as defined by the DGA does not necessarily reduce GHGE in the U.S. food system, although there are diets, including two presented here and by inference many others, which can achieve a reduction in GHGE.

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INTRODUCTION Every day, consumers make choices about what they eat, taking into account taste, nutrition, availability, safety, and cost, among other factors. Increasingly, consumers are also interested in the impact of food production on the environment, as shown by the growth in the organic industry1 and the emergence of other labels certifying sustainable production practices or packaging.2,3 One such environmental impact is greenhouse gas emissions (GHGE), the focus of our paper. In particular, we analyze how switching from current to healthy diets as defined by the Dietary Guidelines for Americans (DGA) of the U.S. Department of Health and Human Services (HHS) and the U.S. Department of Agriculture (USDA) affects GHGE and whether complementary factors exist between the dual goals of healthier eating and reducing GHGE. There exists rich literature on the environmental impact of diets that differ in terms of regional focus, environmental metrics and diet scenarios considered, and data used. Some studies analyze the environmental impact of following national dietary recommendations, such as in Germany,4 Sweden,5 and the United Kingdom.6 Other studies model a reduction in meat consumption7−9 or a switch from current to healthy diets with a focus on health outcomes.10 Still others focus on food waste,11,12 energy use in the food system at a national level13−16 and within cities,17 or the effect of levying GHGE taxes on food commodities and prices.18,19 The most-relevant © XXXX American Chemical Society

studies for our analysis estimate the change in GHGE from shifting U.S. diets to conform to the DGA, finding an increase in food system GHGE of 12%20 and 11%.21 Both of these studies20,21 rely on a meta-analysis of the literature for the United States and other developed countries for their processbased life-cycle analysis (LCA) estimates of GHGE embodied in individual food commodities and do not account for costs of alternative diets. Our approach is unique from prior work in that we estimate GHGE directly at each point in the food supply chain using three data-rich models. We combine a diet model, an environmentally extended input−output model of energy use in the food system, and a biophysical model of land use for crops and livestock to estimate GHGE from the combustion of fossil fuels and from biogenic sources. The diet-optimization model accounts for how consumers would change their diet to satisfy the DGA, modeled as constraints in dietary composition (food patterns), calories, and nutrients for each age and gender cohort. The analysis proceeds at a high level of detail because we model over 4000 as-consumed food items and dishes (e.g., a pepperoni pizza), and we also account for the costs of alternative diets. We use Received: December 5, 2018 Revised: April 4, 2019 Accepted: April 9, 2019

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DOI: 10.1021/acs.est.8b06828 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Environmental Science & Technology the term “healthy” to refer to diets that meet the DGA because the goal of the DGA is to “improve the health of...current and future generations by facilitating and promoting healthy eating”.22 The multiregional environmental input−output (MEIO) model of energy use in the food system, developed in refs 14 and 23, has the benefit of measuring energy consumption not only on the farm but also through the various stages of production, processing, and retailing to more fully account for emissions post-farm-gate than commonly contained in LCA estimates. The model gives energy consumption in Btu across 187 processes and 6 stages for 6 fuel sources: coal, natural gas, petroleum products, electricity, ethanol, and other renewable fuel. Prior work has included some breakouts of emission sources but has not presented a well-defined supply chain breakout. We apply a technique widely used in industry supply chain studies to measure GHGE by supply chain stages to gain insights that are obscured by an aggregate analysis. Finally, the Foodprint model, a biophysical model of land use and livestock supply based on refs 24 and 25, allows us to account for soil carbon emissions for food and livestock feed production, and livestock emissions from enteric fermentation and manure management. Together, these three models account for non-linearities in how changes in consumption translate to changes in production as well as to allocate emissions generated throughout the food production system to 65 food commodities defined by the Food Intakes Converted to Retail Commodities Databases (FICRCD).26 We analyze the GHGE associated with five different example diets: a baseline diet, which represents current, average consumption patterns in the United States using food intake data from the 2007−08 National Health and Nutrition Examination Survey (NHANES),27 as well as four modelderived diets that meet the 2010 DGA,22 including a vegetarian diet and three different omnivore diets, one with and one without a budget constraint and a third one that minimizes energy consumption, measured in Btu, in the food-production system (min-Btu diet). While many combinations of food items can meet the dietary guidelines for a healthy diet, our diet model uses optimization to design our diet scenarios. For example, we model an omnivore diet that would be most similar to the baseline diet, minimizing the difference between the two diets while satisfying the requirements for the 2010 DGA. At this point, it was not possible to combine the two optimization models of energy and land use into a single model to determine a diet that minimizes GHGE. We include the minBtu diet, which minimizes energy use, because it sheds light on which food items are selected when minimizing GHGE from fossil fuel combustion in the food system and because it illustrates the effects of a tax on GHGE from fossil fuel combustion alone (without a similar tax on biogenic GHGE). Similarly, the vegetarian diet can be interpreted as approximating a diet that minimizes biogenic emissions from the livestock sector. Together, these two diets illustrate the extremes of reducing either biogenic or fossil fuel emissions.

Table 1. Model Objective Function and Constraints, Organized by Diet Scenario model objective function healthy omni w/o budget constraint healthy omni healthy vegi min-Btu

model constraints

minimize difference calories, nutrients, USDA food from baseline patterns minimize difference calories, nutrients, USDA food from baseline patterns, cost minimize difference calories, nutrients, lacto-ovo from baseline vegetarian adaptation of USDA food patterns, cost minimize energy calories, nutrients, USDA food (Btu) in food patterns, cost production

recall data from NHANES and the characteristics of the individual food items. The use of a mathematical optimization model to determine diets is a key methodological advancement of this work. We design the DGA-compliant diets at a level of detail such that the foods are in their as-consumed form (e.g., a pepperoni pizza) rather than at a commodity level, which is common in the literature. We are also able to estimate the embodied energy (in British thermal units) in each food item by linking the NHANES data with the multi-regional environmental input−output (MEIO) model described in the following section. Building on previous work in refs 14 and 23, the diet model selects the diet that minimizes the difference between current consumption, represented by 2007−08 National Health and Nutrition Examination Survey (NHANES) food intake data27 and a healthy diet as defined by the 2010 DGA.22 The selected healthy diets thus represent the shortest route to eating healthy within the diet and/or budget constraints of each scenario. For the energy-efficient scenario, a second objective function minimizes energy use embodied in food to create a healthy diet that represents the minimum Btu required to meet the DGA (min-Btu diet). The model constraints in all scenarios include the USDA Food Patterns,28 the nutrient constraints (Appendix 5 in ref 22), calorie constraints (Appendix 6 in ref 22), and, for some diet scenarios, also a cost constraint that maintains or reduces the wholesale cost of the baseline diet. These constraints are weighted on the basis of the age and gender demographics of the NHANES participants. The 4000+ individual food items in NHANES used in the diet modeling are converted to FICRCD categories using the Food Intakes Converted to Retail Commodities26 index for reporting and linking to the MEIO and Foodprint models. A description of the diet model, further details on converting food items in NHANES to FICRCD categories, and a discussion of the suitability of NHANES as compared to other food intake data sets are contained in the Supporting Information. The calorie constraint in the model is a caloric target for the moderately active activity level (Appendix 6 in ref 22), weighted by the national age−gender makeup from the NHANES data. We allow a ±5% deviation from the target to give the model flexibility to solve. Calories in our alternative diets are higher than in the baseline diet but still within the calorie constraints. Population-weighted average daily per capita calories amounted to 2070 for the baseline diet and 2211 for the healthy omnivore diet without a budget constraint, 2181 for the healthy omnivore (“healthy omni”)

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METHODS Modeling DGA-Compliant Diets. We model four diets that meet the 2010 DGA (see Table 1 for the model objective function and constraints for each of the diet scenarios). The diet modeling is done at the food-item level using the dietary B


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linked to both the baseline and the healthy diet scenarios into total embodied energy use estimates by type of energy commodity and across each supply chain stage. The MEIO model accounts for the Btu used for food production to meet food consumption, thereby incorporating the environmental impact during production of food loss. We do not account for further GHGE from food waste that has gone to landfills. Estimates from the literature for this source of GHGE range from 16.11 million tons of CO2eq in 200911 to 41.69 million tons of CO2eq in 2010.20 While FEDS is able to account for energy use in the operation of home kitchens and trips to the grocery store, we do not include emissions from this source, estimated at 311 million tons of CO2eq in 2007,14 because we are unable to assign energy use at the household stage to particular food groups. GHGE from Fossil-Fuel Combustion. Emission rates from fossil fuel combustion vary across fuel source but also by activity according to the efficiency of the combustion engine. Rather than assuming a single emission rate for each fuel, we use specific emission rates for each activity, such as natural gas consumption for cooking in food service versus for packaging production in pulp paper and paperboard mills. MEIO gives coal energy consumed by a particular subsector of the manufacturing industry, but it is unclear whether the coal is in the form of coal or coke. EIA’s Manufacturing Energy Consumption Survey 30 provides data on the relative consumption of “coal” and “coke and breeze” by NAICS industry code, such as “grain and oilseed milling” or “sugar manufacturing.” We compute an average GHG emission rate for each subsector based on the relative use of coal versus coke and breeze. The same applies to the manufacturing industry’s use of petroleum, which can take the form of residual fuel oil, distillate fuel oil, liquid propane gas and natural gas liquids. For petroleum used as gasoline or diesel in the transportation industry, we applied GHGE coefficients from ref 31 weighted by fuel consumption. For example, the GHGE rate for petroleum consumption in commercial truck transportation is the weighted (by fuel consumption) average emission rate of medium- and heavy-duty trucks using diesel as well as those for trucks using gasoline. For GHGE produced in the power generation sector, we use the state-level emission rates provided in the EPA’s Emissions and Generation Resource Integrated Database (eGRID) for the year 2007.32 These emission rates vary across states and are based on the power generation and emissions of the power plants within a state. The MEIO model accounts for transmission line losses in its estimates of electricity consumption in British thermal units. Details on the incorporation of sulfur hexafluoride (SF6) emissions from transmission and distribution equipment are given in section S3 in the Supporting Information. Another potent group of GHGs we partly account for that is not directly tied to fossil fuel combustion are hydrofluorocarbons (HFCs) that are used as coolants in refrigeration and air conditioning. The global warming potential of most HFCs are typically more than 1000 times greater than that of carbon dioxide. Leakages during manufacturing, maintenance, regular operation, and disposal result in HFC emissions. Leakage rates range from 7% per year for industrial refrigeration, food processing, and storage, 10% of coolant per year for commercial refrigeration, and 15% for transport refrigeration.33

diet, 2214 for the healthy vegetarian (“healthy vegi”) diet, and 2183 for the healthy min-Btu diet. Given the ongoing concern about the rates of overweight and obesity in the United States, it may seem counter-intuitive that the alternative diets would have slightly higher calorie levels than the baseline diet. However, energy intake tends to be underestimated by 24 h recall data, like NHANES, due to under-reporting by some participants.29 In addition, our alternative diets assume a level of activity that may be higher than is typical for the average American. Consequently, our results are more illustrative of a shift in dietary composition rather than a reduction in caloric consumption. As a result of model limitations on caloric intake and assumptions on activity level, actual GHGE emissions in the baseline diet could be higher than our estimate, while GHGE in the alternative diets could be lower. Modeling Diet-Related Fossil-Fuel Combustion. Multiregional environmental input−output (MEIO) models extend conventional input−output multiplier analysis to consider the physical flows linked to gross domestic product for materials of environmental consequence. Based on the Food Environmental Data System (FEDS), we employ the MEIO model,14,23 which extends the official U.S. System of National Accounts (SNA) published by the Bureau of Economic Analysis to represent key attributes of the U.S. food system that are obscured in the SNA. For example, energy use in the food system is captured with specific data on electricity and natural gas use by type of wholesale and retail merchant because merchants in the food trades are substantially more energy-intensive than other trade merchants. Other extensions concern a decoupling of the food service and electric power industries to more accurately trace the flow of foods and fossil fuels through the system as well as the use of a matrix reduction procedure that facilitates supply chain decomposition analysis of fossil fuel combustion (see section 2.2 in ref 23). The data needs of MEIO are large, such that 2007 is the most recent year for which detailed input− output accounts are available (as of this writing). To facilitate a link between MEIO and the diet model (discussed above), MEIO uses food industry data to expand the number of consumer food commodities from the 22 covered in the 2007 SNA to a total of 74 commodity groups, which are further broken out into at-home (e.g., grocery stores) and away-from-home (e.g., restaurants) purchases (see appendix Table A.1 in ref 14). For example, the SNA expenditure category “Processed Fruits and Vegetables” are disaggregated into multiple expenditure categories based on product shipment data from the 2007 U.S. Economic Census. MEIO represents all U.S. annual production broken out into 344 industry aggregates (see appendix Table A.2 in ref 14), and international imports are also categorized into these 344 commodity groups. For each industry and commodity, annual 2007 production and imports are allocated to states in the United States. For production, energy use per unit of output are calculated using EIA’s State Energy Data System (SEDS), which reports state data on energy use for more than 10 primary fuel sources by type of end user (see appendix Table B.2 in ref 14 for listing of SEDS data allocations in MEIO). These calculations produce 344 state-level energy flow multipliers for each of 6 energy commodities (coal, natural gas, petroleum products, electricity, ethanol, and other renewable fuel). These multipliers and the other model features are used to translate gross state output by industry C


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complete livestock system, both production animals (such as finished cattle) and support animals (such as beef cows and replacement heifers). Parameter estimates of feed efficiency per unit of food output come from a separate model,25 and these estimates implicitly account for the animal inventories required per unit of food output. The revised Foodprint makes these assumptions explicit by calculating the number of animals associated with the per capita intake in each diet scenario. This is done using the livestock inventory estimates per unit food output from ref 25 with the intake estimates entered into Foodprint. Biogenic Emission Factors. Livestock inventory and crop acreage, to which GHGE coefficients are applied, come from Foodprint. Soil management nitrous oxide and methane emission factors are given in Table S4. They range from 340 kg CO2eq per acre of nitrous oxide emissions for soybeans to 1000 kg CO2eq per acre for corn, with the highest per acre emissions rate at 3508 kg CO2eq methane emission per acre for rice production. Table S5 shows the methane and nitrous oxide emission factors based on ref 37 from enteric fermentation and manure management for 34 different categories of livestock (beef and dairy cattle, broilers, layers, turkeys, and swine) at various stages in their production cycle.

While HFC emissions are occurring throughout the food system in which refrigeration is necessary, we are only able to account for them in the transportation sector in which specific HFC emission rates are available.34 We are unable to tie HFC emissions from manufacturing and distribution to particular processes and food items, as would be necessary for our study. Accounting for HFC emissions from outside the transportation sector would therefore increase our estimate of total GHGE from the food sector (see ref 35 for a review of the environmental impacts of refrigeration in the food system). For the baseline diet, we estimate HFC emissions from transportation at 1.77 MMT CO2eq. For comparison, HFC emissions in commercial refrigeration amounted to 41.6 MMT CO2eq in 2015.36 Including these emissions from commercial refrigeration would increase our GHGE estimate for the baseline diet by 4%. For 22% of natural gas, petroleum, and coal consumption, we have an activity- or industry-specific GHGE rate from a variety of government data sources, as detailed in Table S2. If we include electricity consumption, for which we allow the GHGE rate to vary across states, we have activity-specific GHGE rates for 70% of natural gas, petroleum, coal, and electricity consumption. For the remainder, we assume an industry average carbon dioxide, methane, and nitrous oxide emission rates for each type of fuel (Table S3). Foodprint Model. The U.S. Foodprint Model (referred to hereafter as “Foodprint”) is a biophysical simulation model that calculates the per capita land requirements of complete diets and the potential population fed (or “carrying capacity”) from the agricultural land of the conterminous United States.24 Starting with an estimate of dietary intake by food group, Foodprint determines the quantities of food and agricultural commodities required to supply a given amount of intake after accounting for losses and waste that occur in food preparation, distribution, and processing. The land requirement for producing each food commodity in the diet is calculated based on nationally representative estimates of crop yield, grazing land productivity, and livestock feed efficiencies. A land requirement for the complete diet is also calculated that adjusts for the multi-use nature of certain crops (e.g., soybeans produce both vegetable oil and high-protein livestock feed) and prevents double-counting. A complete description of the model is provided by ref 24. To support the calculation of GHGE associated with agricultural land use and livestock inventories, two revisions were made to Foodprint. First, the categories of food intake were expanded. The original Foodprint represents intake in 23 categories and then decomposes intake from food groups into food commodities tracked in the USDA Loss-Adjusted Food Availability Data (LAFA). The revised Foodprint enters intake of the approximately 65 FICRCD food commodity categories. Because not all of the FICRCD categories map to exactly one LAFA commodity, Foodprint distributes intake of all aggregate FICRCD commodity categories to the appropriate LAFA commodity categories in proportion to their respective consumption in the food supply. Thereafter, the calculations in the revised Foodprint are identical to the original 2016 version. The second change to Foodprint adds a calculation not performed in the original version (namely, the animal inventory required to support a given diet). In Foodprint, feed requirements for producing animal-based foods are calculated based on feed efficiency ratios that account for the

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RESULTS AND DISCUSSION Diet Composition. Relative to the baseline diet, the healthy omnivore diet requires a more than doubling of both dairy and nuts (Table 2). The category totaling meat (beef and pork), poultry, and fish remains almost unchanged between the baseline and the healthy omnivore diets. A closer examination reveals quite substantial changes in consumption within the category: the healthy omnivore diet more than triples the

Table 2. Percent Change in Grams Relative to Baseline Diet, Organized by FICRCD Food Groupa food group dairy total fluid milk butter cheese yogurt other dairy meat, poultry, and fish beef pork chicken turkey fish eggs nuts grain fruit vegetables fat and oils caloric sweeteners

healthy omni w/o budget constraint

healthy omni

healthy vegi

minBtu

144 191

149 198

211 282

65 94

-80 −77 107 −88 14

−81 −85 131 −85 6

−82 −96 32 −95 −100

−92 −99 153 −100 −23

2 −2 −55 61 282 −5 79 15 101 60 −10 −68

−6 −16 −51 75 233 20 108 15 79 59 −3 −69

−100 −100 −100 −100 −100 71 229 17 91 57 −18 −71

46 −100 −100 −100 185 323 −93 15 107 39 19 −92

a

Note: More detailed data on mean grams per capita for all FICRCD categories for each diet scenario are contained in Table S1.

D


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Figure 1. GHGE for different diet scenarios, organized by emissions source.

quantity of fish and increases the quantity of turkey by 75% while reducing the quantity of beef, pork, and chicken by 6%, 16%, and 51%, respectively, over the baseline diet. The 51% reduction in chicken, a relatively lean meat, may have to do with the caloric density, nutrient content, and other food attributes of commonly consumed foods that include chicken as an ingredient, such as chicken nuggets or fried chicken. The quantity of turkey, another lean meat, did in fact increase. Fruits and vegetables increase by almost 60% and 80% while caloric sweeteners decline by 70%. Whether these changes in food quantities result in increasing or decreasing GHGE from food production is unclear a priori and is explored further below. The vegetarian and min-Btu diets differ quite substantially from the healthy omnivore diet in the amount of nuts, eggs, meat, poultry, fish, and dairy. The vegetarian diet substitutes nuts, eggs, and dairy for meat, poultry, and fish. The min-Btu diet is an omnivore diet that meets the healthy diet requirements but minimizes energy use in the food system. The objective function in the min-Btu model does not account for nonfossil fuel GHGE. A diet that minimizes GHGE from both fossil fuel and biogenic sources would likely choose different foods to meet the food patterns component for meat, poultry, and eggs. The substantial reductions in GHGE realized in the vegetarian diet suggest a minimum GHGE model may replace the beef consumption in the min-BTU model with some combination of nuts, eggs, and dairy. However, the min-Btu diet can illustrate, for example, the potential effects of taxing carbon emissions from fossil fuel consumption, such as those included in proposed carbon tax legislation introduced in the U.S. Congress between 2014 and 2016. Such a tax would cause the cost of food items that are energy intensive in production to increase, with the result that consumers would shift away from these food items and toward items that minimize energy consumption, i.e., food items contained in the min-Btu diet.

The min-Btu diet is a substantial departure from current American consumption. Not only are the number of food items reduced in this diet, but also, there is a shift toward lessprocessed, fewer-ingredient food items. Less corn, wheat, and other grains are in the min-Btu diet, while rice increases 6-fold over the baseline diet (see Table S1 for mean grams per capita by FICRCD category for each diet scenario). The min-Btu diet also has a smaller increase in dairy, mainly through a shift of fluid milk almost entirely into skim milk and a greater increase in yoghurt. All meat consumption is in the form of beef, while pork and poultry are zeroed out. Eggs, another protein source, increase 4-fold over the baseline diet. Beef and egg products are selected into the min-Btu diet because, along with the other foods that comprise the total diet, they are energy-efficient in terms of meeting the nutrient and other constraints in the DGA. The min-Btu diet serves the purpose of illustrating the potential for reducing GHGE from minimizing energy use in the food system, and is, though technically healthy, not necessarily as palatable as the baseline. GHG Emissions. Current consumption patterns (baseline diet) in the United States contribute 985 million tons of CO2eq to GHGE: 15% of total US emissions in 2017 or 13% in 2007. We include emissions from farm production through points of consumer purchase, including food service (restaurants) but excluding home kitchen operations and trips to the grocery store. About 44% of these emissions are direct agricultural emissions (Figure 1), including soil management (21%), enteric fermentation (17%), and manure management (6%). Through enteric fermentation and manure management, direct emissions from livestock account for nearly a quarter of total GHGE from food production. Meat, poultry, egg, and dairy consumption contribute to GHGE directly through livestock enteric fermentation and manure management, accounting for nearly a quarter of total GHGE in the baseline diet. Indirect livestock-related emissions include soil management emissions from growing livestock feed. This latter category accounts for 41% of livestock-related E


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Table 3. GHGE from Livestock Production for the Baseline Diet in Grams of CO2eq per Gram of Retail Food Weight and in Grams of CO2eq per Gram of Proteina units grams of CO2eq per gram of retail food weight

grams of CO2eq per gram of protein

soil management enteric fermentation beef pork turkey chicken dairy eggs beef pork turkey chicken dairy eggs

22.05 1.77 1.57 1.61 0.31 0.88 110.19 10.39 7.25 8.77 5.33 7.02

manure management fossil fuel combustion

18.26 0.31 0.00 0.00 1.31 0.00 91.26 1.82 0.00 0.00 22.32 0.00

1.38 3.23 0.23 0.23 1.14 0.62 6.92 18.96 1.05 1.24 19.31 4.93

4.96 9.46 7.12 5.92 2.02 2.29 208.37 31.17 8.31 10.02 46.97 11.95

total 46.66 14.77 8.92 7.76 4.78 3.79 416.74 62.33 16.61 20.03 93.93 23.90

a

Note: Soil management emissions come from growing feed for livestock. More details on how GHGE per gram of retail weight and per gram of protein are calculated can be found in section S4 in the Supporting Information.

healthy vegetarian diet, the largest proportion among the 4 diet scenarios analyzed. The min-Btu diet reduces GHGE by 22%. Direct agricultural emissions under the min-Btu diet are one-third higher than under the baseline diet, but emissions from fossil fuel combustion are 65% lower. The large reduction in emissions from fossil fuel combustion is by design, as the min-Btu diet is determined by minimizing energy use throughout the food system. The 41% increase in enteric fermentation emissions stems from substituting beef for pork and poultry, while the 33% increase in soil management emissions is related to the increase in corn and soybeans used as feed for chicken layers (eggs) and the increase in hay and pasture for beef cattle. We find that the majority of GHGE occur at the farm stage, with the remainder occurring in the processing, packaging, transportation, and retail stages (Table 4). In the healthy

emissions and 18% of total diet-related GHGE. Almost 70% of these livestock-related biogenic emissions come from beef consumption, followed by dairy, pork, poultry, and eggs. Table 3 shows the emissions intensity of the different livestock products in GHGE per retail food weight and per gram of protein for the baseline diet. Beef has the greatest GHGE per retail food weight and per gram of protein, followed by pork, turkey, and chicken. When comparing the GHGE of meat and poultry to dairy and eggs, retail weight is not necessarily an intuitive metric. We also compute GHGE per gram of protein because this macronutrient is a smaller or larger fraction of the total weight depending on the form of the food. Using this metric, dairy products (averaged across fluid milk, cheese, butter, yogurt, and other dairy products based on current consumption) contribute more to GHGE per gram of protein than pork, turkey, chicken, or eggs. GHGE for turkey and chicken are concentrated in the post-farm stage: GHGE from fossil fuel combustion on the farm and in post-farm processing and distribution account for 80% and 76% of total GHGE for turkey and chicken, compared with 11% and 42% for beef and dairy, respectively. Without including a budget constraint that limited spending to at or below the level of spending for the baseline diet, the healthy omnivore diet would increase GHGE by 12%. This is in line with the work in refs 20 and 21, which estimated that GHGE would increase by 11−12% for Americans switching from current to healthy diets as defined by the 2010 DGA while (in contrast with our modeled scenarios) holding calories constant and without accounting for costs. Following ref 14, the diets considered below are all modeled with a budget constraint, which was not always binding, as detailed in section S2 in the Supporting Information, and we focus on these healthy diets for the remainder of the article. The healthy omnivore diet decreased GHGE only very slightly by 0.4% relative to the baseline diet. As with the baseline diet, direct, biogenic GHGE from agriculture accounted for just under 44% of total emissions. GHGE values under the healthy vegetarian diet are 32% lower than under the baseline diet, achieved through an almost 60% reduction in direct agricultural emissions overall, coming mainly from enteric fermentation and soil management due to the elimination of meat and poultry from the diet. Emissions from manure management make up 8% of total GHGE for the

Table 4. Percent of Total GHGE for Different Diet Scenarios, Organized by Production Stage stage

baseline

healthy omni

healthy vegi

min-Btu

farm and agribusiness food processing packaging transportation retail trade food services

53.7 14.3 5.8 7.0 8.0 11.2

55.4 12.7 5.1 7.6 8.4 10.8

41.6 19.8 7.8 10.0 12.5 8.3

80.6 5.0 2.0 3.4 3.3 5.8

omnivore diet, 55% of GHGE occur at the farm stage with food processing (13%) and food services in restaurants and cafeterias (11%) as the next highest emission stages. Most studies either focus solely on the farm stage38−40 or use LCA estimates from the literature that lump together GHGE from farm to retail.4−6,20,21 To our knowledge, our study is the first to break out GHGE by these six stages. It builds on research by Weber et al.,41 who estimated that the “food production” stage, which, in their study, also includes processing and packaging but excludes biogenic emissions, accounted for 83% of food-related GHGE, with transportation accounting for 11% and final delivery from producer to retail for 4%. Despite including biogenic emissions in our estimate of farm-stage GHGE, our finding of quite substantial post-farm GHGE (46% in the baseline diet) is driven by the role of fossil fuels in the U.S. food system and is consistent with an F


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Figure 2. GHGE for different diet scenarios, organized by food group.

Figure 3. Percent change in GHGE and quantity (grams) relative to the baseline diet, organized by FICRCD food group for the Healthy Omnivore diet.

as protein shakes, coffee, and tea, as the second-largest category in terms of emissions at 20%. Not all changes in quantities of particular food groups result in commensurate changes in GHGE. Figure 3 shows, for the healthy omnivore diet, the change in quantities relative to the baseline diet for each food group along with the change in GHGE. Vegetables and fruits increased by 60% and 80%, respectively, while GHGE in those categories increased by less than half of those percentages. This result can be attributed mainly to a reduction in fossil-fuel consumption post-farm-gate

extensive literature on energy use in the U.S. food system. Energy use in food production is found to occur mainly in the post-farm stages and is estimated at 70%,42 80%,14 or 90%43 of total energy use through points of consumer purchase. In all omnivore diets, GHGE from animal products (dairy, meat, poultry, fish, and eggs) account for more than three-fifths of total emissions, while emissions from fruits and vegetables remain at or under 15% (Figure 2). In the healthy vegetarian diet, emissions from dairy and eggs make up about 36% of total GHGE, with the other category, which includes beverages such G


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masks quite substantial changes in quantity consumed and thus GHGE within the category. Notably, fish consumption triples and turkey consumption increases 75%, while chicken, pork, and beef consumption all decline. Changes in GHGE over the baseline diet are mostly concomitant with changes in quantity with the exception of pork. The quantity of pork declines 16%, while GHGE increases 32%. This result is due to the healthy omnivore diet selecting forms of pork that resulted in 50% greater emissions post-farm despite the 16% reduction in swine livestock required (and thus 16% reduction in biogenic emissions). For example, pork chops are a top food item in the healthy omnivore diet, while bacon is a popular food item in the baseline diet. The change in GHGE of the three healthy diets relative to the baseline diet is driven mainly by changes in meat, poultry, fish, and dairy quantity and composition. Table 6 allocates the net change in GHGE to the relevant food groups. GHGE from caloric sweeteners declines in all three healthy diets. In the healthy omnivore diet, GHGE from fat and oils, meat, poultry, and fish, and beverages and seeds decline, while emissions from the other food groups all increase, with the largest increase occurring in the dairy category. Together, these decreases and increases balance out, such that GHGE in the healthy omnivore diet decline by only 0.4% relative to emissions in the baseline diet. While dairy, nut, vegetable, and beverage quantities and associated GHGE increase in the healthy vegetarian diet relative to the baseline diet, the decline in GHGE from the meat, poultry, and fish food group help drive overall GHGE for the vegetarian diet below those for the baseline diet. For the min-Btu diet, increased emissions are registered only for meat, poultry, fish, and eggs, while emissions from all other food groups decline. Comparison with Existing Literature. Our results of 3191 kg CO2eq per capita per year for the baseline diet are higher than most other estimates in the literature, which range from 131419 to 228244 and 3070 kilograms of CO2eq per capita per year.41 However, our results are similar to the 3744 kilograms of CO2eq per capita per year estimate from another recent study employing an economic input−output LCA framework,45 and our estimate of biogenic emissions (1409 kilograms of CO2eq per capita per year) comes close to the EPA estimate of emissions from agriculture of 1379 kilograms of CO2eq per capita per year for the year 2007.37 Table S6 provides a comparison of studies estimating the GHGE of U.S. diets.

because the healthy omnivore diet selects fruit and vegetable items that are either lessprocessed or require less energy for transportation, packaging, retail trade, or in food services than the baseline diet. For vegetables, GHGE from the production of packaging declined by 24%, while for fruits, GHGE declined in each stage post-farm-gate, most notably by 37% and 71% in food processing and packaging, respectively. For example, the healthy omnivore diet reduces apple juice by 14% while increasing the quantity of apples by 80%. While the healthy omnivore diet increases the quantity of eggs by 20% over the baseline diet, GHGE from eggs actually declines by 2%. The reduction in GHGE from eggs comes despite a 20% increase in manure management and feedrelated soil management emissions, such that the overall reduction in GHGE from eggs can be attributed again mainly to a reduction in fossil fuel consumption post-farm-gate, including an almost-80% reduction in emissions from the food processing stage. We further explore GHGE from the dairy and the meat, poultry, and fish categories for the healthy omnivore diet in Table 5. The quantity of dairy more than doubles, but much of Table 5. Percent Change in Quantity (Grams) and GHGE for the Healthy Omni Diet Relative to the Baseline Diet by Selected FICRCD Food Groups total dairy total fluid milk butter cheese yogurt other dairy total meat, poultry, fish beef pork chicken turkey fish

quantity

GHGE

149 198 −81 −85 131 −85 6 −6 −16 −51 75 233

14 193 −64 −77 174 −71 2 −8 26 −52 63 243

a

Note: Biogenic emissions are assigned to the dairy subcategories on the basis of milkfat content.

that increase is in the form of fluid milk and yogurt. Overall, these increases combined with a decrease in more emissionsintense dairy products, such as butter and cheese, result in only a 14% increase in GHGE from this category. Similarly, while overall GHGE from the meat, poultry, and fish category increased only 2% over the baseline diet, this slight increase

Table 6. Composition of Change in GHGE (MMT CO2eq) Relative to the Baseline Diet, Organized by FICRCD Food Group FICRCD

healthy omni

healthy vegi

min-Btu

dairy meat, poultry, fish eggs nuts grain fruit vegetables fat and oils caloric sweeteners other: beverages, seeds overall

21.3 9.9 −0.4 10.6 3.8 12.6 11.7 −6.3 −38.4 −28.8 −4.0 (−0.4%)

54.0 −432.1 7.1 20.0 9.9 9.6 24.5 −8.6 −35.3 34.4 −316.4 (−32.1%)

−71.6 49.5 50.1 −5.9 −35.7 −12.8 −47.7 −8.9 −51.7 −82.3 −216.9 (−22.0%)

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STRENGTHS AND LIMITATIONS A number of previous studies have considered the impact on GHGE of switching from current to healthy diets that conform to the DGA.20,21 A strength of our study is that it combines a diet model with two large models of the U.S. food production system to estimate GHGE from both biogenic and fossil fuel sources while accounting for the costs of alternative diets. The MEIO model applies GHGE coefficients to fossil fuel consumption in the food system by fuel, stage, and production process. The MEIO model is also linked to a detailed model of food consumption, such that all food consumption choices made across over 4000 food and beverage items (and their accompanying nutrition attributes) are linked to 74 food commodity groups modeled in the MEIO. This facilitates diet scenario optimization models at a very detailed level and allows for incorporation of the costs for alternative diets, which was shown to be determinative in GHG emission outcomes from these alternative diets. This linked MEIO-diet model is combined with the U.S. Foodprint model, which incorporates non-linearities in how pasture and hayland are allocated for beef and dairy production and how dairy production adapts to changes in the mix of dairy products consumed. A different analytical approach to measuring food-system GHGE, which is outside of the economic accounting structures of environmental input−output analysis, is known as processbased life cycle assessment (LCA), a form of meta-analysis. The researcher identifies and uses LCA GHGE estimates from the literature, often across multiple studies with potentially different assumptions and study regions, rather than constructing estimates from more primary data. A metaanalysis will typically identify a boundary comprising the salient domestic processes within the food system life cycle. Within these boundaries, a piecemeal approach to compiling primary and secondary data sources for measuring GHGE is carried out and often involves making informed assumptions about the application of more narrowly defined data to processes outside of its own boundary definitions. If the boundaries are carefully defined and reliable data sources are available, results from applying the EIO and meta-analysis methods to the same research question should converge. One appealing feature of a meta-analysis is the ability to compare results for specific product alternatives, such as organic versus conventional fresh produce. Although the MEIO approach is unlikely to distinguish among product alternatives such as organic versus conventional, it is comprehensive in terms of its boundary definitions (the entire domestic economy) and in terms of the consistency of its data sources. This is because the MEIO accounts are compiled from the official System of National Accounts (SNA). Like most other member countries of the United Nations, the United States follows the economic accounting guidelines developed by the United Nations Statistical Commission.46 The MEIO for this study was constructed from the 2007 detailed Benchmark SNA for the United States. The approach in this study allows for the measurement of prices and the identification of supply chain stages, from farm inputs through points of consumer purchase. Both the MEIO and the meta-analysis are typically built up from data sources that are objectively measured and statistically reliable. However, integration of multiple data sources that are compiled into a data system for purposes of LCA make the carrying forward of reliability measures from the various

components of the system extremely challenging. This fact provides an argument that there is a need for both approaches to LCA studies. When results from both approaches to the same or similar questions converge, an ad hoc measurement of reliability is obtained. When results of the two approaches diverge, this finding can inform evaluations of the two applications. A limitation of our study is that, as of this writing, 2007 is the most recent year for which detailed input−output accounts are available. Our study thus assumes that food is produced in the 2007 food system and that primary factor supply curves are perfectly elastic, i.e., that changes in food consumption do not affect food prices and the way the food items are produced, which would affect GHGE. It is worth noting that the diet with the most severe changes to food choices (min-Btu), which is the diet likely to generate price effects in factor markets due to extreme changes in farm commodity production requirements, also turns out to cost substantially less than the baseline diet (about 65% lower). Given the lower cost, consumers might be more willing to accept the far more limiting food choices associated with this diet. Another limitation of our analysis arises because we are only able to account for emissions from household activities in the baseline diet and cannot link them to the food items in any diet. The min-Btu diet, in particular, might suffer from an emissions leakage problem by choosing food items that require few emissions from processing, packaging, and food service, shifting these instead to food storage and preparation at home. Future research could focus on determining a diet that minimizes both GHGE and differences to the current diet, thereby approximating a min-GHG diet that would be most palatable to the average consumer.

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ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.8b06828.

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Additional details on NHANES and other food intake data sets for dietary modeling, the diet model, sulfur hexafluoride emissions from the power sector, and estimations of GHGE; tables showing mean retail commodity quantity, GHG emission rates, soil-management emission factors, methane and nitrous oxide emission factors, and a comparison of studies estimating the GHG emissions of U.S. diets (PDF)

AUTHOR INFORMATION

Corresponding Author

*Phone: 202-694-5513; e-mail: [email protected]. ORCID

Claudia Hitaj: 0000-0002-6408-9265 Author Contributions

The manuscript was written through contributions of all authors. P.C. conceived of the project, C.H. led the writeup and estimated greenhouse gas emissions, S.R. and P.C. contributed the diet model and the model of energy-use in the food system, and C.P. modeled land use and estimated livestock numbers for the different diets. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. I


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ACKNOWLEDGMENTS The findings and conclusions in this preliminary publication have not been formally disseminated by the U.S. Department of Agriculture and should not be construed to represent any agency determination or policy. We acknowledge three anonymous reviewers for comments that improved this study considerably. C.P.’s contributions were supported, in part, by a cooperative agreement with the USDA (project no. 58-4000-50004). This research was supported in part by the intramural research program of the US Department of Agriculture Economic Research Service.

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Greenhouse Gas Emissions in the United States Food System: Current

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