Team Prudent Protein
Final Report, Spring 2016
Environment 159
Professor Deepak Rajagopal
Pars Parikh
Adam Gushansky
Apsara Perera
Jerry Chi
Michael Morrison
1
Table of Contents
Executive Summary……………………………………………………………………………….2
Goal and Scope…………………………………………………………………………………....2
Overview of Literature…..………………………………………………………………………...3
Process Flow Diagrams and Methodology ……..………………………………...……………....4
Life-cycle Inventory…………………………………………………………………………….....5
Table B1: Water withdrawals per gram of protein and per Calorie……………………….5
Table B2: Greenhouse-gas emissions per gram of protein and per Calorie………...…….5
Table B3: Energy consumption per gram of protein and per Calorie……………………..6
Impact Analysis…………………………………………………………………………………...6
Sensitivity and Uncertainty Analysis…...…………………………………………………………6
Figure F1: Change in gallons of water per kilogram of protein by resource……………..7
Table B4: Comparison of resources and uses between Soybeans and Corn……………....7
Table B5: Comparison of payments and subsidies between Soybeans and Corn………....8
Results and Conclusions…………………………………………………………………………..9
Limitations of Work……………………………………………………………………………...10
References ……………………………………………………………………………………….12
Team Member Responsibilities…………………….…………………………………..………..12
Appendix…………………………………………………………………………………………13
Figure A1: Water-resource intensity of soybean and other oilseed processing, followed by
poultry and egg production……………………………………………………………………....11
Figure A2: Greenhouse-gas emissions stemming from soybean and other oilseed
processing, followed by poultry and egg production….………………………………………....12
Figure A3: Energy intensity of soybean and other oilseed processing, followed by
poultry and egg production……………………………………………………………………....14
Figure A4: Domestic greenhouse-gas emissions stemming from the agricultural sector
since 1990……………………………………………………………………………………......15
Figure A5: Sensitivity of water-resource intensity for soybean and oilseed processing as
well as poultry and egg production………………………………………………………….…...18
Figure A6: The cost profile for daily consumption of a 25 year old average male…..…18
2
Executive Summary
Climate change is the biggest global threat of the 21st century. Atmospheric greenhousegas concentrations are the highest in human history, and scientists, engineers, and serial
entrepreneurs are actively innovating methods to mitigate the effects of global warming. This
colossal task, however, is not just for the few brilliant minds, but for the rest of us. On an
individual level, we need to do our part – and that starts with evaluating the decisions that we
make every day, particularly as they relate to food.
What we eat has a tremendous impact on our overall ecological footprint. The
Environmental Protection Agency (EPA) notes that nine percent of the United States’
greenhouse-gas emissions are attributable to the agricultural sector (EPA, 2016). Despite what
we know about the environmental impacts stemming from the agricultural sector, the broad
consumer base is not doing nearly enough – in fact, greenhouse-gas emissions from agriculture
have increased over the last 25 years (Figure A4). More than anything, consumers lack sufficient
data to make informed decisions. A life-cycle analysis can provide a straightforward, visual
approach to connect the consumer to the environmental impact of his or her choices.
Our functional unit is simply one gram of protein. We are analyzing three environmental
impacts of $1 million of economic activity in each of the 1) soybean and oilseed processing and
2) poultry and egg production sectors per gram of protein. Carnegie Mellon’s EIOLCA tool
provides us with our primary source of data from which we construct process flow diagrams and
calculate the environmental burden of the respective sectors. Then, after performing multiple unit
conversions, we arrive at our results, which are expressed in impact per gram of protein. The
step-by-step calculations can be found later in the paper.
The team’s bottom-line results are rather complex, supporting the notion that choices
with respect to food are difficult to model. Comprehending these choices requires a deep
understanding of the multi-faceted benefits that food provides. Nonetheless, we found that more
protein is produced per dollar of economic activity in poultry than soy, and that poultry is less
greenhouse-gas intensive compared to soy production. However, per dollar, one can feed more
people by growing soy, which is also far-less water- and greenhouse-gas intensive than poultry.
Goal and Scope
The purpose of this paper is to independently analyze and compare the environmental
impacts of consuming protein from plant-based sources (soybean) and animal-based sources
(poultry) with the hope of encouraging consumers to make informed decisions with respect to
food. We have chosen three impact categories – water (the primary focus), energy, and
greenhouse-gas emissions – whose intensity of use have a direct and important effect on overall
sustainability. Ultimately, since this is not a comprehensive analysis for food, we are not looking
to suggest a specific diet or course of action – we are merely looking to provide a piece of
relevant information that the consumer would find useful when making personal choices. Merely
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asking somebody to do something is not nearly as powerful as giving that person the capacity to
come to that conclusion on his or her own.
Since the topic of food is infinitely complex, the scope of work is a crucial component in
defining our research. In this paper, we forgo differentiating between organic and inorganic
products, and limit our data to domestic processes. We also omit land use as an impact category,
even though it is an important factor in conducting a comprehensive analysis. (More efficient
land use means more arable land to grow food.) Our data is also best suited to analyze life-cycle
processes up to the point of purchase. We conduct a preliminary sensitivity analysis for the
cooking methods of tofu and chicken, but only through empirical methods (such as researching
recipes) rather than theoretical ones. Lastly, we omit waste management entirely in our analysis,
due to time constraints and an unwillingness to study the human digestive system.
Overview of Literature
Several reports, articles, and blog posts provided scientific, cultural, and global context
for this comparative analysis. Since the scope of this analysis was narrowed to specifically
compare poultry and eggs to soy-based protein and their water footprints, there was not a single
source to provide the exact information needed; therefore an aggregate of multiple sources was
used to supplement each other and aid in making assumptions for the sake of this assessment.
The article reporting the United Nations recommendation for a reduction in meat and
dairy consumption is broad in its claim that “a vegetarian diet was better for the planet.” Without
getting into specifics of the ideal vegetarian diet, the article goes on to list some of the negative
impacts the meat and dairy industry has on the environment, such as high water consumption,
land use, and greenhouse gas emissions (Carus, 2010). This article shows that the meat and dairy
industry and its impacts have become a serious global issue especially with rapid population
growth.
Research on soy production show that the soy industry is negatively affected by climate
change but also contributes to it with its water and land demands (WWF, 2016). For desirable
crop yields, soybeans typically need more water than what is provided from natural precipitation
so irrigation systems are often put in place, which is why soybeans have high water consumption
rates (Agronomic Highlight, 2015).
Recipes gave valuable information for the sensitivity analysis such as cook time and
commonly used ingredients that may have impacts on the environment themselves. Common
recipes for chicken would involve more cooking oil (All Recipes) while some recipes for tofu
would require a longer cooking time and thus consume more electricity or gas (Minimalist
Baker, 2013). It is also important to note that tofu can be consumed raw which would cut out
cooking fuel or oil.
Health and fitness blog articles, though perhaps not as reliable, provided insight into how
the health and fitness world compares animal based protein to plant based protein.
Livestrong.com, a popular health and fitness site wrote about their own cost-benefit analysis
4
between meat and soy-based protein. Their conclusion was that although meat contains a higher
concentration of protein, there are other hidden costs associated with consuming either protein
source. When consuming meat, one would ingest more saturated fats and cholesterol whereas
when consuming soy-based protein, one would ingest less iron and more carbohydrates. It is
important to note that half of the carbohydrates consumed from soy-based protein would also be
dietary fiber which aids in weight management (Coleman, 2015). Other sources discussed the
importance of “complete proteins” which are proteins that contain all nine essential amino acids
that the body does not produce naturally. Soybeans are one of the few plants that naturally
contain all essential amino acids which would supplement the argument that consuming meat is
not necessary to ingest “complete proteins.” Additionally, “complete proteins” can be made by
pairing certain complementary foods within a twenty-four hour period (English, 2015). These
factors should be important to consumers who are concerned about making environmentally
conscious decisions while still minding their health.
The general trend observed was that reporting on the meat and dairy industry focused
more on greenhouse gas emissions and water use (Mother Jones, 2015) compared to reporting on
soybeans that focused primarily on water and land use (Agronomic Highlight, 2015). With the
global population expected to increase by over 2 billion people by the year 2050 (United
Nations, 2015), the agricultural industry needs to shift to use resources more efficiently to feed
the world without continuing to degrade the environment. These sources, though not all scientific
exemplify the global trend of how environmental impacts are becoming more critical in making
decisions on food and nutrition.
Process Flow Diagrams and Methodology
The process flow diagrams are constructed using the EIOLCA 2002 Producer data. We
chose one gram of protein as our functional unit because it represents an important nutritional
component of our daily diet that is often scrutinized with respect to a plant-based diet. Poultryand soy-based protein are both complete proteins (contain all of the essential amino acids),
which further justifies the chosen unit as a reasonable point of comparison.
One gram of protein as a functional unit also contains its inherent weaknesses. For one,
protein is just one of a myriad factors we consider when making choices about food. This
consideration is discussed at length in the Limitations of Work section. Similarly, the functional
unit does not take into account the amount of product that needs to be consumed in order to get
one gram of protein.
The process flow diagrams yields results in units of impact per $1 million of economic
activity for each sector. Then, we multiply the results by the average cost of each product per
pound of food to arrive at impact per mass of food. (Recent rates of eggs, cuts of chicken, and
turkey were collected from the United States Department of Agriculture (USDA, 2016) and
averaged to represent the broad category.) The average cost of tofu per pound is calculated by
5
standardizing the retail price per ounce of different types and brands of tofu (soft, firm, extra
firm) found at the supermarket. Finally, we divide the by density of protein per mass, and end up
with units of impact per gram of protein.
Since we solely utilized EIOLCA and hence could not collect data at a higher resolution,
our findings come from multi-output systems. Instead of using a combination of cumbersome
methods to allocate impacts to each sub-sector, we considered the data in the aggregate. This is
also discussed in the Limitations of Work section.
Life-cycle Inventory
We conducted impact analyses on water withdrawals, Global Warming Potential, and
energy using EIOLCA. Therefore, we have three base-case scenarios to present, all quantifying
the amount of resources required per gram of protein or per Calorie.
Price
per lb.
Calories
Protein (g)
Water (gal)
Water (gal) per Water (gal)
Protein (g)
per Calorie
Tofu
$1.92
1814
43
175
4.11
0.1
Poultry
$1.79
1361
104
483
4.63
0.3
33.3%
-58.7%
-63.8%
-11.2%
-66.7%
Net Result 7.3%
Table B1: Water withdrawals per gram of protein and per Calorie, respectively.
Price
per lb.
Calories
Protein
(g)
GHG
(g CO2)
GHG (g CO2)
per Protein (g)
GHG (g CO2)
per Calorie
Tofu
$1.92
1814
43
4900
28.68
2.7
Poultry
$1.79
1361
104
4200
14.48
3.33
Net Result
7.3%
33.3%
-58.7%
16.7%
98.1%
-18.9%
Table B2: Greenhouse-gas emissions (represented by Global Warming Potential) per gram of
protein and per Calorie, respectively.
6
Price
per lb.
Calories
Protein
(g)
Energy
(MJ)
Energy (MJ)
per Protein (g)
Energy (MJ)
per Calorie
Tofu
$1.92
1814
43
30
0.22
0.02
Poultry
$1.79
1361
104
40
0.12
0.03
33.3%
-58.7%
-25.0%
83.3%
-33.3%
Net Result 7.3%
Table B3: Energy consumption per gram of protein and per Calorie, respectively.
Impact Analysis
We produced process flow diagrams for each of the three impact categories. For practical
purposes, the six diagrams can each be accessed via Appendix A. The data suggests that, per
gram of protein produced, poultry is more energy- and water-intensive, whereas soy has less
protein per mass and emits more greenhouse gases. The price per pound also favors poultry, but
this is before federal and state subsidies are considered. (More on this is found in the Sensitivity
and Uncertainty Analysis section.)
These results are expected in some ways and surprising in others. Water withdrawals for
poultry are uncharacteristically high due to the sheer amount of grain that must be produced to
feed livestock. There is also a significant energy footprint associated with raising and cultivating
these grains. On the other hand, soy must go through intensive processing, and furthermore
indirectly contributes to global warming by way of deforestation.
We also calculated that more calories are produced per $1 million of economic activity in
soy than poultry. This can be interpreted in several ways. For someone who is on a high-protein,
low-Calorie diet, poultry might seem like a more attractive option. But for someone who is on a
tight budget, or looking to cut down on fat intake, soy seems like a more attractive option. It all
depends on what nutritional components (as well as taste!) are desired in a given meal.
Sensitivity and Uncertainty Analysis
Naturally, the major source of uncertainty for our results is the quality of data. Figure F1
displays the sensitivity of changing the water withdrawal measures for Stage 1 inputs for both
soy and poultry. For both sectors, grain farming has the highest sensitivity. This is notably
concerning, since we presume that farming processes for certain grains (particularly soy, due to
increased demand) have become a lot more efficient in the time since this data was taken (2002).
7
Figure F1: Change in gallons of water per kilogram of protein by resource
We also consider the role of government subsidies in creating model uncertainty. Both
soybean and corn are prominent sources for livestock feed with the latter being far more
prevalent. The demographics of the two can be found in the figure below.
2014
Total
Acreage for
All
Purposes
Total
Acreage for
Livestock
Feed
% of
Harvest
Fed to
Livestock
% of
Harvest
Sold to
Humans
Fed to
Livestock
(tons)
Sold to
Humans
(tons)
Soybean
83,061,000
69,189,813
83.30%
16.70%
52,619,369
10,608,684
Corn
90,597,000
83,136,000
91.76%
8.24%
497,568,960
44,654,085
Table B4: Comparison of resources and uses between Soybeans and Corn
In 2014, farmers in the U.S. committed a similar amount of acreage to the production of
both soybean and corn. Despite that, the quantity of corn harvested is far greater than the
quantity of soybean harvested. Nonetheless, we are not comparing corn to soybean here, instead,
we are comparing soybean to corn-fed poultry. Of the corn produce, 91.8% is used as livestock
feed (USDA, 2014). Assuming all corn was processed for ethanol before being converted to
livestock feed, the other 8.2% of corn produce is sold to humans (USDA, 2014). On the other
hand, of the soybean produce, 83.3% is fed to animals that are eventually harvested, leaving
16.7% to be sold in the markets (USDA, 2014). Consequently, corn is the lead receiver of
government subsidies because it is the number one food source for livestock as well as a source
for ethanol. The figure below highlights the numbers behind government subsidies given to
8
farmers producing soybean and corn. While the numbers do not account for all the subsidies,
they account for a majority given between 1995 and 2014.
Table B5: Comparison of payments and subsidies between Soybeans and Corn
The nutritional value provided by soybean and poultry is comparable; however, poultry requires
almost four and a half times as much resources in the form of taxpayer dollars to stay costcompetitive.
Results and Conclusions
From a lifecycle-inventory perspective, poultry is preferable for efficient protein intake.
Per dollar, poultry also is more energy-efficient, less greenhouse-gas intensive, and is cheaper
per pound to produce. For the latter metric, one caveat is that the analyzed natural resources are
undervalued in society (or in the case of carbon emissions, almost totally externalized). Farmers
with water rights utilize their own wells, and are also sold water at highly discounted prices.
Food choices are also far more complex than protein content. It is important to consider
the Calorie content, vitamins, minerals, sugar, fats, and other crucial health components when
consuming food. Our results are based off of the EIOLCA 2002 producer data, but recent data
has shown that soy production has become a lot more efficient over the past 15 years compared
to poultry production. This is in part due to an increase in the demand for soy.
After conducting a thorough analysis of the lifecycle of protein derived from tofu and
from poultry, several factors between the two have been distinguished. First, the density of
protein is higher for poultry than for tofu, making it a more attractive option when considering
protein strictly. On the other hand, tofu has a higher calorie content making it a better option to
meet the dietary needs of a growing human population. Nonetheless, there are several metrics
that favor tofu such as the water consumption per protein and calorie. Similarly, the emissions
per gram of protein are strictly in favor of poultry. In the end, there are multiple angles to view
the two from but the one that holds the most weight is the difference in price of per pound of
product and the resources required in the production of the two commodities respectively.
Specifically, the fact that on average one pound of tofu is 13 cents more expensive than one
pound of poultry, but on average, the production of poultry receives forty-one times as much
money in the form of subsidies than the production of tofu leads to the conclusion that natural
resources are under-priced in society.
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Limitations of Work
Our primary limitation extends far beyond the scope of this project. An analysis on the
environmental impacts of consuming protein is certainly useful for the typical consumer to an
extent, but the sobering reality is that our choices with respect to food are much more complex
than simply protein content. Additional life cycle assessments need to be performed for soybean
and poultry that analyze the environmental burden per Calorie, gram of fat, sugar, and specific
vitamins and minerals. Then, one would need to combine all of this information and present it in
a cohesive way that can influence consumer choices.
Furthermore, even when people have a general idea of the environmental impacts and
nutritional content of various foods, we still make choices that defy this knowledge! Factors like
convenience, taste, texture, and cultural significance all play a role in determining what people
will eat. This is where the lifecycle analysis comes up short. It is difficult to simply identify all of
the different influencing factors, let alone quantify and compare them. As many would attest,
altering one’s diet is no simple task – especially for humans, habitual creatures, who eat on
average three meals per day. Changing what we eat is far more complex than taking shorter
showers or turning off the lights, which partly explains why food can be regarded as a sensitive
subject. Despite these shortcomings, LCA without question has a role in shifting the nation’s
agricultural practices. It can make production more efficient, as well as give consumers more bits
of information to ponder the next time they pay a visit to the cafeteria.
Our team also encountered some challenges during the data-collection process. The data
we gathered from Carnegie Mellon’s EIOLCA tool is from 2002. Since then, demand for soybased products has increased drastically – in 2013, soybean revenues exceeded $4.5 billion, and
more than 50% of sales came from energy bars and meat alternatives, both of which were
sparsely available 15 years ago (source). Increased consumer demand, coupled with
advancements in technology, lead to the notion that soy production has become much more
efficient since 2002. Farming practices in the livestock sector, while also more efficient than ever
before, are more-or-less similar to those in recent years.
In determining the environmental burden of these products, our analysis fails to take into
account the waste management aspect of the lifecycle. We clearly denoted this limitation in our
scope of work, however when presenting information to a consumer, it is better to show the
complete picture. Similarly, although we considered the impacts of different cooking methods
for both soybean and chicken in one of our sensitivity analyses, we used an insignificant sample
size (one internet-based recipe for each method) in coming to our conclusions. Thankfully, the
environmental burden of cooking these foods is almost negligible compared to their production.
Lastly, our results were skewed by way of multi-output systems. The two sectors we analyzed
from EIOLCA were 1) soybean and other oilseed processing and 2) poultry and egg production.
Our original goal was to simply compare chicken with soy, but we did not encounter data at this
resolution. With a bit more time and effort, we could have used one of the methods discussed
during lecture – likely allocation, for practical purposes – to decouple the desired data from the
aggregate, which we used in producing our bottom-line results.
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References
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n.d. Web. 24 May 2016.
● Carus, Felicity. "UN Urges Global Move to Meat and Dairy-free Diet." The Guardian.
Guardian News and Media, 02 June 2010. Web. 24 May 2016.
● "Chicken Stir-Fry Recipe." Allrecipes. N.p., n.d. Web. 24 May 2016.
● Coleman, Erin. "Soy Protein Vs. Meat Protein." LIVESTRONG.COM.
LIVESTRONG.COM, 22 June 2015. Web. 02 June 2016.
● Company, Monsanto. "Water Use in Soybean & Irrigation Timing for Maximizing Yield
Potential." Agronomic Highlight (n.d.): n. pag. REA Hybrids. Web.
● "Crop Production 2014 Summary." (2015): n. pag. United States Department of
Agriculture, Jan. 2015. Web. 1 June 2016.
● "Easy Deep Fried Tofu Recipe." About.com Food. N.p., n.d. Web. 24 May 2016.
● "Easy Grilled Chicken - Damn Delicious." Damn Delicious RSS2. N.p., 23 June 2015.
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● English, Nick. "10 Complete Proteins Vegetarians Need to Know About."Greatist.
Greatist, 29 Apr. 2015. Web. 02 June 2016.
● "EWG's Farm Subsidy Database." Conservation Efforts in the United States. Look into
How Much Money the United States Department of Agriculture (USDA) Spent on
Conservation Programs. N.p., 2014. Web. 02 June 2016.
● "Greenhouse Gases." US Environmental Protection Agency. N.p., n.d. Web. 01 June
2016.
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2016.
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farming, egg production." Hyline: Drinking water, chickens, genetics, poultry, eggs,
diseases, technology, breeds, farming, egg production. N.p., n.d. Web. 08 May 2016.
● Mekonnen, M. M., and A. Y. Hoekstra. "Volume Information." Pacific Affairs 69.4
(1996): 619-28. UNESCO-IHE. Institute for Water Education, 1 Dec. 2010. Web. 10 May
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June 2016.
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● Plumer, Brad. "The $956 Billion Farm Bill, in One Graph." Washington Post. The
Washington Post, 28 Jan. 2014. Web. 02 June 2016.
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● "Soy & Climate Change." WWF Conserves Our Planet, Habitats, & Species like the
Panda & Tiger. N.p., n.d. Web. 08 May 2016.
● "Soy Facts." Information About Soya, Soybeans. Soya Tech, n.d. Web. 02 June 2016.
● "USDA ERS - Meat Price Spreads." USDA ERS - Meat Price Spreads. N.p., n.d. Web. 18
May 2016.
● "Veggie Tofu Stir Fry | Minimalist Baker Recipes." Minimalist Baker. N.p., 22 Oct.
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● United Nations. "World Population Prospects." Key Findings and Advance Tables (n.d.):
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● Wilson, Jeff, Lydia Mulvany, and Megan Durisin. "Too Much Corn With Nowhere to Go
as U.S. Sees Record Crop." Bloomberg.com. Bloomberg, 22 Aug. 2014. Web. 02 June
2016.
Team Members and Responsibilities
Pars Parikh: project management, sensitivity analysis, life-cycle inventory.
Adam Gushansky: project management, executive summary, limitations of work.
Jerry Chi: process flow diagrams, impact analysis, data visualization.
Michael Morrison: process flow diagrams, results and conclusions, functional unit.
Apsara Perera: overview of literature, methodology, references, formatting.
Appendix A
Figure A1: Water-resource intensity of soybean and other oilseed processing, followed by
poultry and egg production. Taken from EIOLCA (2002 data).
12
Figure A2: Greenhouse-gas emissions stemming from soybean and other oilseed processing,
followed by poultry and egg production. Taken from EIOLCA (2002 data).
13
14
15
Figure A3: Energy intensity of soybean and other oilseed processing, followed by poultry and
egg production. Data taken from EIOLCA (2002 data).
16
Figure A4: Domestic greenhouse-gas emissions stemming from the agricultural sector since
1990.
17
Figure A5: Sensitivity of water-resource intensity for soybean and oilseed processing as well as
poultry and egg production.
Figure A6: The cost profile for daily consumption of a 25 year old average male.