Environ. Sci. Technol. 2010, 44, 6450–6456
Eutrophication Potential of Food
Consumption Patterns
XIAOBO XUE* AND AMY E. LANDIS
Department of Civil and Environmental Engineering,
University of Pittsburgh, Pittsburgh, Pennsylvania, 15261
Received November 12, 2009. Revised manuscript received
May 25, 2010. Accepted June 11, 2010.
Although the environmental impacts and carbon footprints of
foods are gaining more public attention and scientific debate, few
studies have systematically evaluated the life cycle nitrogen
and phosphorus flows among different food types. Disruption of
natural nitrogen and phosphorus cycles already result in
serious environmental quality degradation and economic losses,
such as loss of fisheries due to hypoxia in the Gulf of
Mexico. This study characterizes the nutrient flows during
food production, processing, packaging, and distribution stages
for eight food types; compares carbon footprints and nitrogen
equivalent footprints of food groups; evaluates solutions to
reduce excessive nitrogen outputs; and estimates effectiveness
and efficiency of possible solutions. Different food groups
exhibit a highly variable nitrogen-intensity; on average, red meat
and dairy products require much more nitrogen than cereals/
carbohydrates. The ranking of foods’ nitrogen footprints is
not consistent with their carbon footprints. For example, dairy
products and chicken/eggs have relatively high nitrogen
footprint and low carbon footprints. Finally, the study evaluates
shifting food consumption patterns. Dietary shifts from dairy
products and red meat to cereals can be an effective approach
for lowering the personal nitrogen footprint.
Introduction
Food production, processing, distribution and consumption
activities have significant social, economic, and environmental impacts (1-8). While vast quantities of foods are
required to satisfy a basic human need every day, food
production also results in natural resources depletion, water
quality degradation, and climate change. Nutrient fluxes from
food supply chains have resulted in water quality degradation
in the form of hypoxia and eutrophication causing loss of
ecosystem services and species extinctions (9-11).
The hypoxic zone in Gulf of Mexico (GOM) mainly caused
by excess nutrients exported from agriculture production in
Mississippi River Basin (MRB) resulted in reduced commercial and recreational fisheries (12). To minimize and
mitigate this hypoxic zone, a task force of federal, state, and
tribal representatives established a goal of reducing the
hypoxic zone size to 5000 km2. Although this task force
recognized the significant role of agriculture in MRB to
achieve this goal, there is concern that increased agricultural
production may further hinder achievement of hypoxic zone
production (13). Therefore, it is important to identify
eutrophication potential of different foods and mitigate their
environmental impacts such as hypoxia in the GOM.
Global warming potential of food production and transportation systems is reported widely for assorted food types
* Corresponding author e-mail: [email protected].
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and different food supply systems (1, 5-8, 14). Previous
studies show that livestock production systems have higher
carbon footprints than crop and vegetable production
systems (8, 15). “Food miles” research focusing on carbon
emissions during food delivery stage advocates localization
of global supply network (5-7, 14). Weber et al. reported the
carbon emissions of food choices, and discovered eating less
red meat and dairy could be a more effective way to lower
an average U.S. household’s food-related climate footprint
than buying local food (8).
Some research has addressed the eutrophication potential
of food production (15-22). For example, Tilman et al.
forecasted that 109 ha of natural ecosystems would be
converted to agriculture by 2050 to meet food demand of
increasing population and consumption. This would be
accompanied by 2.4- to 2.7-fold increases in nitrogen and
phosphorus-driven eutrophication of terrestrial, freshwater,
and near-shore marine ecosystems, and comparable increase
in pesticide use (16). Although advances in agricultural system
management may reduce nutrient losses resulting from
agricultural production, the risk of worsening eutrophication
issues still exists due to continuously increasing food and
biofuel demands in future. In addition to forecasting, the
eutrophication potential from a single food type or a single
sector of food supply chains has been assessed previously
(17-21). However, systematic evaluations of food supply
chains and comparisons of eutrophication footprints
among food types are still lacking.
Recently, life cycle assessments (LCAs) have been utilized
to evaluate and improve the environmental performance of
food production systems. LCA results have been used in the
development of eco-labeling criteria with the aim of informing
consumers of the environmental characteristics of products.
However, most analyses are limited to case studies of either
a single food or a limited set of items (22-27). With large
groups of products, the resources and data availability do
not often allow for detailed analyses. A few studies researched
overall diet but these studies focused on the environmental
relevance of carbon footprint and food consumption patterns
(8). The study of nitrogen and phosphorus inventories over
all food categories has not yet been performed. Additionally,
the effects of reducing eutrophication potential through
shifting food consumption pattern have not been addressed.
Food supply activities should be evaluated from a life
cycle perspective and are simplified into four phases: farming,
processing, packaging, and transportation. Every phase emits
considerable amounts of eutrophication species into the
environment. Farming systems, as a primary stage of food
production, are widely recognized as an important contributor for water quality degradation (15, 17, 18, 28, 29). Aqueous
nitrate (NO3-) and phosphate (PO4-3) emissions from agricultural nonpoint source emissions such as fertilizer runoff
and manure storage systems contribute to eutrophication.
Air emissions such as NH3, N2O, NO and NOx generated from
volatilization and denitrification processes can also contribute to eutrophication potential resulting from agriculture.
Additionally, nitrogen compounds (NOx, N2O) are also
emitted from combustion processes during agricultural
operations and processing of food (17, 18). Food processing
industries generate large amounts of organic materials such
as protein and lipids, high biochemical and chemical oxygen
demands (BOD and COD), and considerable amounts of
dissolved nutrient concentrations (NH4-, NO3-, PO4-3) (2, 4).
Similarly, food packaging can produce both air and water
emissions to the environment (30-32). Transportation results
in nitrogen air emissions, mainly including NH3, N2O, NO,
10.1021/es9034478
 2010 American Chemical Society
Published on Web 07/22/2010
FIGURE 1. System boundary of foods for identifying their
eutrophication potential. Farming production, food processing,
food packaging, and food delivering stages are included in the
system boundary.
NOx, which can also contribute to eutrophication (33, 34).
Thus, it is important to consider all these species during
each stage to evaluate eutrophication potential of food supply
chains.
Food choices and changes in food production may offer
a unique opportunity for consumers to lower their personal
environmental footprints and may offer national improvements in water quality. A systematic evaluation of multiple
food products and their environmental impacts such as
eutrophication potential and carbon footprint is needed to
make informed policy decisions. This paper presents such
an analysis and both combines and compares the results
with food products’ carbon-footprints. Nitrogen and phosphorus emissions and environmental impacts throughout
the life cycle of the food production system including
agricultural production, processing, packaging and distribution stages are quantified using a life cycle approach. This
paper also evaluates strategies that may reduce eutrophication and hypoxia and estimates the reduction of nutrient
outputs due to food consumption pattern shifts.
Materials and Methods
As explained above, LCAs have been employed to investigate
environmental profiles of different foods. Guidelines for
performing LCAs are presented by the International Organization for Standardization’s (ISO) 14040 series (35). The
main phases of an LCA include goal and scope definition,
inventory analysis, impact assessment, and interpretation.
This study utilizes the LCA framework to quantify eutrophication potential over the life cycle of the food production
system. The life cycle inventory evaluates N, P compounds
and BOD/COD contents that contribute to eutrophication.
Eutrophication potential was estimated based on traditional
life cycle impact analysis methods, as described below.
System Boundary. The life cycle stages vary with different
food products. Generally, food LCA stages include farming
production, food processing, packaging, and delivery. Figure
1 shows the boundaries for the researched food groups.
Functional Units. The functional unit is the reference
unit that forms the basis for comparison between different
systems. Most published food LCA research uses mass or
volume based functional units (36). A more sophisticated
way of defining the functional unit is to include quality
aspects, for example, nutrient content of food. The nutrient
content is described by factors like the amount of carbohydrate, fiber, vitamins, minerals, essential amino acids,
energy, fat and protein, or others. In this article, g nitrogen/
kg food is defined as the functional unit to compare nitrogen
profiles of different food groups. Normalized units (g
nitrogen/kcal in food; g nitrogen/$ food) are also employed
to reflect the influences of economic value and energy
content.
Life Cycle inventory (LCI) and Life Cycle Impact Analysis
(LCIA). Several existing tools were used to compile the LCI,
including SimaPro and GREET. SimaPro software developed
by Pré consultants is expandable and transparent software
that integrates inventory data for a broad spectrum of
industrial and economic sectors (37). The greenhouse gases,
regulated emissions, and energy use in transportation
(GREET) model created by Argonne National Laboratories
delineates life cycle energy use and emissions of criteria air
pollutants based on EPA emission factors of transportation
stages (34).
SimaPro software and associated databases including
ecoinvent V2 (38), LCA food (39), Industry data 2.0 (40),
BUWAL250 (41), IDEMAT 2001 (42) were used to compile
nutrient inventory for the food processing and packaging
stages. GREET was employed to account for inventory in the
transportation stage. Additionally, the LCI for the agricultural
stage was created using a variety of data collected from
published articles and SimaPro databases. The LCI data
sources are outlined in Table 1, while detailed data sources
are illustrated in SI. Total nutrient output is equal to the sum
of the nutrient flows from every stage of the food production
system including agriculture, processing, packaging, and
transportation.
Packaging and packing containers can be divided into
two groups: commercial packages and transportation containers. This article only considers commercial packages
(43, 44). Commercial packages protect the product and
guarantee its quantities and composition for direct consumer
purchase. Packages are produced from different materials in
a variety of types, for example, bags, cartons, glassware, cans,
etc. Detailed assumptions of packaging materials for foods
are given in the SI.
Distances and transportation modes for delivering food
subgroups are obtained from literature (8). All GREET default
assumptions are followed to calculate air emissions during
transportation stage (34).
The LCIA was conducted utilizing TRACI (Tool for
Reduction and Assessment of Chemical and other environmental Impacts), which was developed by the U.S. Environmental Protection Agency (33). TRACI is used to calculate
eutrophication potential for the system. TRACI defines
characterization factors (CFs) relating N and P species to
eutrophication potential, thus allowing the LCI data to be
expressed in terms of the TRACI defined reference compound,
N-equivalents.
Monte Carlo analysis (MCA) is used to quantify variability
and uncertainty of the LCI (17, 28, 29). Any independent
variable with a range of estimates or possible values were
assigned a probability distribution. Best-fit probability
distributions were determined using Anderson-Darling tests.
Independent nitrogen equivalent values were collected or
calculated for each LCA stage of every food group. Crystal
Ball 7 software was used to define probability distributions
of nitrogen equivalent values for every stage and to conduct
the MCA (29). The distribution of output variables, as a
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TABLE 1. Stages of Food LCA and Associated Emissions with Eutrophication Potentials
stages
farming
food processing
food packaging
transportation
a
emissions of concern
NH3, NO, N2O, NOx, NO3-, PO4-3,
NH4-,BOD, COD
NH3, NO, N2O, NOx, NO3-, PO4-3,
NH4-, BOD, COD
NH3,NO, N2O,NOx, NO3-,PO4-3,
NH4-,BOD, COD
NO,N2O,NOx
databasea
peer reviewed articles, ecoinvent V2
peer reviewed articles, ecoinvent V2,
LCA food, industry data 2.0, BUWAL250, IDEMAT 2001
ecoinvent V2, LCA food, Franklin US 98,
Industry data 2.0, BUWAL250, IDEMAT 2001
GREET1.8
Peer reviewed articles and use of database is explained and referenced in the Supporting Information.
FIGURE 2. Eutrophication potential of researched food groups by life cycle stage. Stages include the agricultural production, food
processing, food packaging and transportation. Median values within this study are presented in the bar graph. Certainty bars
represent the 10 and 90% confidence intervals.
function of independent values, was generated through MCA,
which repeatedly and randomly samples values from the
probability distributions of independent values. The distribution ranges of total nitrogen equivalent were determined
from distributions of each stage’s nitrogen equivalent value
through the MCA method.
Results
Contribution to Eutrophication Potential at Each Life Cycle
Stage. Figure 2 shows eutrophication potentials for the
different food groups. Red meat has the highest eutrophication potential, followed by dairy products, chicken/eggs
and fish. The cereal and carbohydrate (cereal/carbs) subgroup is identified to have the lowest nutrient footprint
among all food subgroups. While producing, processing,
transporting, and packaging 1 kg of red meat generates on
average 150 g nitrogen-equivalent emissions, around 2.6 g
nitrogen equivalent emissions are released to supply 1 kg
cereal/carbs. The agricultural stage is the largest eutrophication emission sector, which shares more than 70% of total
eutrophication potential for each food group. Both plant
production and animal raising systems are reported to be
responsible for eutrophication-related emissions to surrounding water bodies. Corn and soybean farming systems,
providing feedstock for human diet and animal feed, emit
large amounts of NO3- and PO4-3 into groundwater and
surface water (17, 28, 29). Manures from animal raising
systems contain high nutrient contents. Atmospheric NH3
and N2O, (generated from nitrification/denitrification processes) and aqueous N and P species (transformed or
dissolved from manures) can significantly influence the
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nutrient inventory of food supply chains (19, 45-48). Nutrient
footprints of red meat and dairy products include direct
nutrient emissions from animal raising systems and upstream
nutrient emissions from plant production; this explains the
relative intensity of red meat and dairy products which have
the highest eutrophication potential from a life cycle
perspective.
Eutrophication potentials of food processing stages vary
with processing techniques, while transportation distances
contribute minimally to eutrophication impacts. Processing
dairy products and meat products has important influence
on food’s eutrophication potential. Industrial milk processing
(including liquid milk, milk powder, cheese, butter, etc.)
generates distinct nutrient waste. N and P species in dairy
processing effluents originate from cleaning compounds and
from milk or product spillage during dairy product processing.
Significant amounts of phosphate based cleaners and nitric
acid based cleaners were used during washing procedures
at the end of production cycle, consequently resulting in
high levels of N and P in most dairy wastewater (49). Eide
et.al reported that eutrophication potential of processing
milk ranged from 6.2 to 8.0 g O2/L milk which corresponds
to 0.31 g N/L milk and 0.4 g N/L milk (21, 25, 50). Slaughtering
animals also influences the nutrient inventory significantly.
The major source of nitrogen and phosphorus is from the
protein in the meat particles and blood in the wastewater
from slaughter plants (2). Other sources of nitrogen are the
manure and partially digested feeds from stomachs and
gizzards and intestines, as well as urine (2). The packaging
stages and transportation stages have negligible impact on
eutrophication profiles of food groups. The usage of packing
FIGURE 3. Comparison of normalization factors for
eutrophication potential of food groups. From left to right: by
expenditure (year 2007) and energy content. All values are
shown relative to the value of cereals/carbohydrates.
materials for supplying foods contributes less than 15% of
food groups’ eutrophication profiles. Although transportation
distances can be long, eutrophication potential resulting from
atmospheric NH3 and NOx deposition are relatively small,
representing less than 2% of the total eutrophication potential
for most of good categories.
Comparative results of eutrophication potential among
different food groups inform consumers of the relevance
between lowering eutrophication footprints and food consumption pattern. However, different foods groups have
different prices, different nutrients, and of course are more
or less desirable depending on consumers’ preference. Figure
3 shows a comparison of total impacts with impacts
normalized by expenditure and caloric content. Prices and
calories of different food groups are published by the U.S.
Department of Agriculture (USDA) (51, 52). Results show
that when consumers spend 1 dollar on foods, the supply
chains of those foods emit approximately 0.7-16 g N
equivalent. Similarly, the supply chains produce 0.5-41 g N
equivalent, when 1 kcal of energy is delivered to consumers’
baskets. Cereals/carbs group has the lowest N emissions
normalized by food price and calories. Compared with other
food groups, cereals/carbs group is the most environmentally
friendly choice for reducing nutrient emissions, when the
same amount of expenditure or the same energy content is
considered.
Discussion
Uncertainty in Results. Uncertainty of nutrient inventory
among food groups was assessed using MCA. Results show
that the agricultural systems exhibit considerable variability
and uncertainty in emission profiles due to differences in
geography, climate, and agricultural practices. Uncertainty
in the meat production stage stems from different feed
choices, animal raising practices, farms’ locations and other
factors. The choices of feed intake influence the amount of
nitrogen excreted by animals and nitrogen emitted from feed
production processes (53). Besides feed choices, production
modes also have an impact on eutrophication potential (19).
The uncertainty of eutrophication potential resulting from
pork production was investigated through differentiating the
production modes. The analysis shows that the environmental impacts of current intensive pig production systems
are significantly different from alternative production systems
in France (19). Additionally, the impact of farms’ locations
on eutrophication potential has been quantified by researchers. Kumm et.al found that the nitrate leaching potential is
related to the spatial location of farms in Sweden (54). Farms
in central Sweden (lower precipitation, clay soils) had only
FIGURE 4. Comparison of carbon footprints and nitrogen
equivalent footprints. Carbon footprints are obtained from
Weber et al. (8).
one-third of the leaching level of farms in southwestern
Sweden (higher precipitation, sandy soils). Temperature,
humidity, and soil compositions can greatly influence
denitrifaction/nitrification rates, and P adsorption capacity
of soil particles, consequently influencing the amounts of
nutrients transported into water bodies. The use of average
data to characterize agricultural system may not represent
emissions occurring during “extreme” years (such as rainy
or drought years), and the subsequent environmental impacts
(29). Since the agricultural sector is a dominant contributor
for eutrophication potentials of foods, identifying and
characterizing the uncertainty of nutrient flows in agricultural
systems is important for future research. When aggregate
food groups are researched rather than specific food types
(such as the difference between grass-fed versus grain-fed
meat, organic farming vs conventional farming, etc), uncertainty and variability are enhanced. The constrain of data
availability limited the number of researched food types.
However, the average values and variability evaluation of
the nutrient inventory presented within this research among
food groups are still meaningful in investigating eutrophication footprints of dietary choices.
Comparing Carbon Footprints and Nitrogen Footprints.
Figure 4 compares nutrient footprints and carbon footprints
of different food groups. Food groups close to the origin
have both low carbon footprint and low nitrogen footprint.
For example, cereals/carbohydrates are the most environmentally preferred food types from a carbon and nitrogen
life cycle perspective. By contrast, red meat has the highest
carbon footprint and the highest nitrogen footprint. Dairy
products, fish, and chicken/eggs have relatively higher
nitrogen footprint and lower carbon footprints. In contrast,
sweets, oils, fruits, and vegetables have relatively lower
nitrogen footprints and higher carbon footprints. The
inconsistency between carbon footprints and nitrogen
footprints indicates trade-offs of shifting food consumption
habits and inherent environmental complexities of food
policy decisions. For example, solely minimizing consumers’
C-footprint would suggest that one consume cereals/carbs,
dairy, chicken/eggs, and fish. However, if the N-footprint is
also considered, as shown in Figure 4, dairy products are not
necessarily ideal since they have the second highest eutrophication potential, while fruits and vegetables might be
reconsidered since they have a minimal N-footprint.
Nitrogen Output Reduction Due to Consumption Pattern Shifts. The effect of food consumption pattern shifts on
nitrogen equivalent emissions reduction is estimated assuming (1) eutrophication profiles of foods are unchanged
during consumption shifts, (2) a linear relationship exists
between nutrient output and mass of consumed food for
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FIGURE 5. Eutrophication potential reductions due to
consumption shifts from high nitrogen profile foods to low
nitrogen profile foods. The same caloric contents are
maintained. Baseline is average nitrogen equivalent output
resulting from annual U.S. food consumption per capita (56).
Other lines describe eutrophication potentials of other dietary
consumption scenarios. The legend depicts the ranking of the
food consumption shifts from low N equivalent reduction (e.g.,
the lowest is USDA baseline) to high N equivalent reduction
(e.g., the highest is shifting dairy products to cereal products).
FIGURE 6. Cost reductions due to consumption shifts from high
nitrogen profile foods to low nitrogen profile foods. The same
caloric contents are maintained. Baseline is annual U.S. food
cost per capita in 2007 (51). Other lines describe cost of other
dietary consumption scenarios. The legend depicts the ranking
of the food consumption shifts from high food cost (e.g., the
highest is shifting red meat to fruits/vegetables) to low food
cost (e.g., the lowest is shifting dairy products to cereal
products).
every researched food group, and (3) consumers maintain
constant calorie consumption during food pattern shifts. In
reality, the shift of dietary habits is a relatively slow process
(55, 56). Although technology improvements and policy
incentives have the potential to reduce environmental
footprints of food production and processing on a large scale,
shifting red meat and dairy products to other low nitrogen
intensive food groups may significantly reduce personal
eutrophication potential. Estimated results (Figure 5) show
that food supply chains generate 40 kg nitrogen equivalent
for meeting one person’s food needs annually. Among
possible consumers’ behavioral changes, shifting dairy
products to cereals products is the most effective way to
mitigate personal eutrophication potential from both cost
and nutrient emission perspectives (Figures 5 and 6). A
change in milk has larger eutrophication effect than a change
in red meat consumption because of meat’s higher caloric
density. Shifting 5% of dairy product consumption to cereals
groups and maintaining the same caloric intake can prevent
380 g per capita annual nitrogen equivalent emissions to the
environment. On the extreme, 7630 g of nitrogen equivalent/
year could theoretically be avoided if 100% of dairy products
were replaced by cereals/carbs products.
The fluctuation of food cost as a result of food consumption pattern shifts is estimated based on the same set of
assumptions as discussed previously in addition to the
assumption that (4) the price of food groups remains the
same as the 2007 baseline and (5) a linear relationship exists
between food cost and mass of bought food for every
researched food group. Estimated results (Figure 6) are
calculated in comparison to a baseline of $4840 for meeting
one person’s food needs annually. This study does not
account for cost of dining out. The most economically
effective choice is to shift dairy product consumption to
cereals groups, while shifting red meat to vegetables may
increase cost. Shifting 5% of dairy products to cereals groups
and maintaining the same calories can save $40 annually for
each person. In the extreme case, replacing 100% of dairy
product with cereals/carbohydrate products could save $810.
Outlook. Because of demand for food to support the
expanding world population and changing dietary preferences with development, the application of fertilizers is
predicted to continually increase. This will likely worsen
coastal eutrophication and hypoxia. Effective and efficient
solutions should be employed to reduce nitrogen needs and
environmental nitrogen output to eventually minimize
eutrophication. Changing food purchase behaviors may be
an effective mitigation strategy. If people consume less red
meat and dairy products, the nitrogen usage for food
production will decrease. And surprisingly, shifting away from
dairy products to cereal products achieves larger eutrophication reduction than shifting away from red meat to cereal
products when the same energy content is maintained.
However, complicated environmental impacts of foods
including carbon and nitrogen profiles require overall
environmental evaluation of food choices. Policy decisions
based solely on one aspect of environmental impacts, either
carbon footprint or nitrogen footprint, are likely to result in
trade-offs such as environmental burdens shifting from global
warming to eutrophication impacts.
Additionally, this analysis focused on environmental
impacts of food choice, which is one factor related to food
choices. A variety of factors, such as taste, safety, nutrition
contents, affordability, availability, and environmental concerns may also influence food choices. Food consumption
shifts based only on one factor is unlikely to happen. The
reliability of estimating eutrophication potential reduction
due to consumer behaviors’ changes is impaired when the
importance of other factors have not been adequately
addressed. Although an ideal tool which can quantify the
influences of all factors is not available, simplified approaches
still aid in understanding of the complex nature of food
choices.
Other solutions also exist to reduce eutrophication
potential of foods, for example, optimizing farming practices
during the production stage; improving food processing
techniques; and implementing prevention strategies such
as installing buffer strips, constructing wetlands, or using
other water treatment facilities to remediate nutrient runoff.
Trade-offs exist for every possible solution; a portfolio of
solutions should be suggested to meet the requirements of
abundant food supply, acceptable environmental impacts,
and sustainable social and economic development.
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Acknowledgments
We thank Dr. Melissa Bilec and Dr. Joe Marriot at University
of Pittsburgh for their guidance and helpful suggestions.
Supporting Information Available
Detailed discussion of assumptions and datasources and
additional figures and tables. This material is available free
of charge via the Internet at http://pubs.acs.org.
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