LCA Consider a Spherical Man

8/10/2019 LCA Consider a Spherical Man

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Consider a Spherical Man

A Simple Model to Include Human Excretion

in Life Cycle Assessment of Food Products

Ivan Munoz,Llorenc Mila i Canals, andRoland Clift

Keywords:

carbon cycle

fecesindustrial ecology

nutrients cycle

urine

wastewater

Summary

Emissions derived from human digestion of food and subse-quent excretion are very relevant from a life cycle perspective,

and yet they are often omitted from food life cycle assessment

(LCA) studies. This article offers a simple model to allocate

and include these emissions in LCAs of specific foodstuffs.

The model requires basic food composition values and calcu-

lates the mass and energy balance for carbon, water, nutrients

(mainly nitrogen [N] and phosphorus [P]), and other inorganic

substances through different excretion paths: breathing, feces,

and urine. In addition to direct excretion, the model also allo-

cates some auxiliary materials and energy related to toilet use,

such as flushing and washing and drying hands. Wastewater

composition is also an output of the model, enabling water

treatment to be modeled in LCA studies. The sensitivity of

the model to food composition is illustrated with different

food products, and the relative importance of excretion in a

products life cycle is shown with an example of broccoli. The

results show that this model is sensitive to food composition

and thus useful for assessing the environmental consequences

of shifts in diet. From a life cycle perspective, the results show

that postconsumption nutrient emissions may dominate the

impacts on eutrophication potential, and they illustrate howthe carbon cycle is closed with the human emissions after food

preparation and consumption.

Address correspondence to:

Llorenc Mila i Canals

SEAC, Unilever Colworth

Colworth House, Sharnbrook

Bedfordshire MK44 1LQ, United Kingdom

[email protected]

c 2008 by Yale UniversityDOI: 10.1111/j.1530-9290.2008.00060.x

Volume 12, Number 4

www.blackwellpublishing.com/jie Journal of Industrial Ecology 521


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Introduction

Food is a basic human need, recognized as

one of our most resource-demanding and pollut-

ing daily activities when the complete life cy-

cle of food is considered. Food production causesmany environmental impacts through its sup-

ply chain, which includes agricultural produc-

tion, storage, several transport steps, processing,

cooking and consumption, and waste disposal.

Several studies have identified food as one of

the main contributors to the environmental im-

pact of private consumption at both the na-

tional and the international level (Nijdam et al.

2005; Tukker et al. 2006). It is not surprising,

then, that life cycle assessment (LCA) studies

are increasingly directed at food to find ways to

make its production and consumption patterns

sustainable.

LCA has been applied to many different food

products, including basic carbohydrate foods,

fruits and vegetables, dairy products, meat, fish,

and alcoholic and nonalcoholic drinks, among

others (Foster et al. 2006). Although some prac-

titioners have conducted full LCAs for partic-

ular products or product groups (Andersson and

Ohlsson 1998; Jungbluth et al. 2000; Ziegler et al.2003), many studies tend to focus on a partic-

ular stage of the products life cycle, such as

agriculture (Anton et al. 2004; Mila i Canals

et al. 2006), industrial processing (Sonesson,

Mattsson, et al. 2005), transport (Mila i Canals

et al. 2007; Sim et al. 2007), retailing (Carlson

and Sonesson 2000), industrial processing and

packaging (Hospido et al. 2006), home storage

and processing (Sonesson et al. 2003; Sonesson,

Anteson, et al. 2005; Sonesson, Mattsson, et al.

2005), and waste management (Sonesson et al.

2004; Lundie and Peters 2005).

Human digestion and excretion remains the

least studied life cycle stage of food products; so

far, only nutrients in food have been included. In

their case study on seafood, Ziegler and colleagues

(2003) included nutrients in the food and their

fate through sewage treatment. Sonesson and col-

leagues (2004) studied the importance of post-

consumption waste treatment in the life cycle of

food products, proposing a systematic procedurefor modeling the nutrients balance. Nonethe-

less, besides nutrients, published studies have not

covered human metabolism and excretion as a

whole.

The biochemical transformations undergone

by food in the human body give rise to differ-

ent pollutants released to air and water, which

should be included within the system boundariesof a complete food LCA, similar to the way food

waste is treated when it is landfilled or composted.

Therefore, why has human excretion been sys-

tematically omitted by LCA practitioners up to

date? We can envisage at least three reasons for

this:

1. It is not necessary in case studies compar-

ing similar products, because the environ-

mental burdens would also be similar.

2. LCA is a tool intended to support decisionmaking at many levels in the food chain;

it can guide decisions about producing or

consuming more or less organic food, fresh

or frozen products, and so forth, but human

metabolism is a constraint, something we

can hardly influence and therefore must

accept as a limitation. In particular, LCA

has been traditionally used mostly for sus-

tainable production, and hence the focus

has been on cradle-to-gate studies.

3. There are no available models to calculate

the environmental burdens of this stage as

a function of the type of food; that is, there

is no allocation procedure analogous to

those developed for other multi-input pro-

cesses, such as solid waste and wastewater

treatment(Doka and Hischier 2005). Even

though Sonesson and colleagues (2004)

suggest some hints for calculating post-

consumption emissions from food, to our

knowledge, these have not been used inany published food LCA studies.

As pointed out by Andersson (2000) and

Sonesson and colleagues (2004), the relevance

of including human excretion depends on the

goal of the study. Digestion and excretion are

clearly relevant when the aim is to close the bal-

ance of materials in the life cycle or to com-

pare the environmental effects of different diets

(Jungbluth et al. 2000; Alfredsson 2002; Kytzia

et al. 2004) or ways to provide food (Sonesson,Mattsson, et al. 2005) due to the dependence of

excretionemissionson foodcomposition. Human

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excretion should also be included in attributional

food LCA studies, which aim to identify the life

cycle hot spots.1

In this work, we address this methodologi-

cal gap by providing a simple model to calcu-

late product-related life cycle inventories of hu-man excretion. The title of this article refers to

the spherical cow metaphor, where a theoretical

physicist started a calculation on a dairys pro-

duction with Consider a spherical cow. . .. This

metaphor is often used to refer to simplified sci-

entific models of reality, which help understand

more complex problems. The article sets out the

model fundamentals, tests the model with differ-

ent food types, and positions it in the context of

the whole life cycle of a particular product, broc-

coli. The final section discusses the results and

highlights the main conclusions of the article.

Model Description

The model has been designed as a MS Ex-

cel spreadsheet, a comprehensive description of

which is offered by Munoz and colleagues (2007).

Figure 1 Modeled system. COD = chemical oxygen demand; BOD = biological oxygen demand.

General Structure and System Boundaries

The model can be divided in two main parts:

The first addresses the global balance of materials

and energy in the human body as a consequence

of ingestion of food with a specific composition,

whereas the second part concerns the auxiliary

materials and energy associated with toilet use.

Figure 1 shows a flow diagram of the system mod-

eled and its boundaries.

It is worth noting that the only emissions

to nature calculated by this model are to air,

mainly from respiration, whereas the wastewater

containing human excrement and toilet paper is

considered as an output to the technosphere. It

is assumed that toilets discharge wastewater to a

sewer connected to a wastewater treatment plant.This means that, to determine the final emis-

sions to the environment, an additional model

for wastewater treatment must be used. Several

models are available (Dalemo 1997; Jimenez-

Gonzalez et al. 2001; Doka 2003) to calculate

inventories of wastewater treatment for user-

defined wastewaters. If a scenario with no sewage

treatment is considered, the emissions quantified

Mu noz et al., Human Excretion in LCA of Food Products 523


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by the human excretion model must be taken as

the final mass of pollutants released to the aquatic

environment.

Food Composition

Any kind of food, including plain water, can

be assessed by the model, as long as its compo-

sition is known. The input parameters to be de-

fined, as g/100 g on a fresh weight basis, are the

following:

water content;

protein content;

fat content, including all lipids (saturated

and nonsaturated fatty acids, cholesterol,

etc.);

carbohydrate content, including all sugars

and starch;

Fiber content, including lignin, pectin, and

cellulose;

alcohol;

organic acids not covered by any of the

above categories, such as acetic acid or lac-

tic acid;

inorganic elements, such as phosphorus,

sodium, chloride, magnesium, potassium,iron, and heavy metals.

Raw and cooked food composition can be

found in handbooks such as that published by

the UK Food Standards Agency (2002). It is im-

portant to consider the composition of the food as

it is ingested, because cooked or boiled food can

have a very different composition as compared to

raw food. As an example, broccoli loses 30% of

Figure 2 Overview of the fate of food constituents in the human body as considered in the model.

its protein and 39% of its carbohydrate content

when boiled (Food Standards Agency 2002).

Inorganic constituents must also be included,

especially if they represent a significant part

of the food. The occurrence of toxic organic

compounds, such as pesticide residues, is nottaken into account because the added complex-

ity that would be introduced by their modeling

in the human body is out of the scope of this ar-

ticle. In fact, pesticides (and other substances)

metabolites are not even considered in sophisti-

cated pesticide fate models in LCA. Only heavy

metals are included in the food composition, but

it is important to bear in mind that the purpose

of this model is to obtain a life cycle inventory;

impacts on human toxicity of exposure to heavy

metals in food are not assessed.

Human Metabolism Modeling

One of the basic assumptions of the model is

that a steady-state person is considered. This

means that all material entering the body as food

is excreted, including proteins and fat. No accu-

mulation of fat or synthesis of additional proteins

is considered; this is in accordance with the anal-

ysis of Sonesson and colleagues (2004). Food isentirely converted to excretion products and ex-

pelled from the body in one of the following flows:

breath, urine, feces, and skin/sweat.

Figure 2 shows an overview of the transforma-

tions and fate of food entering the human body

according to this model. Food constituents are

divided into four categories: water, degradable

material, nondegradable material, and inorgan-

ics. The model considers as degradable organic



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Table 1Elemental composition of organic constituents in food

Elemental composition (kg/kg)Food

constituents C H O N S Comments

Protein 0.47 0.07 0.29 0.15 0.02 Average C, H, N, O, and S content in each of

the 20 amino acids: alanine, arginine,asparagine, aspartic acid, cysteine, glutamic

acid, glutamine, glycine, histidine, isoleucine,

leucine, lysine, methionine, phenylalanine,

proline, serine, threonine, tryptophan,

tyrosine, valine

Fat 0.77 0.12 0.12 0.00 0.00 Based only on triglycerides, which constitute

more than 90% of total fat intake in western

diets (Boron and Boulpaep 2003). As C, H,

and O content in two triglycerides used as

models: triglyceride of palmitic acid, oleic acid,

alpha-linoleic acid, and triglyceride of palmiticacid, palmitic acid, palmitoleic acid.

Carbohydrate 0.42 0.06 0.52 0.00 0.00 Average obtained by the sum of C, H, and O

content of the following carbohydrates:

fructose, sucrose, maltose, lactose, and starch

Alcohol 0.52 0.13 0.35 0.00 0.00 Based on the empirical formula of ethanol,

C2H5OH

Organic acids 0.40 0.07 0.53 0.00 0.00 Based on the empirical formula of acetic acid,

CH3COOH. The weight fractions are equally

valid for lactic acid, C 3H6O3, and for any

carbohydrate with formula (CH2O)nFiber 0.44 0.06 0.49 0.00 0.00 Dietary fiber includes lignins, pectins, and

cellulose (Boron and Boulpaep 2003). Thecomposition of fiber is based on the empirical

formula of cellulose (C6H10O5)n

Note: C = carbon; H = hydrogen; O = oxygen; N = nitrogen; S = sulfur.

materials all the organic constituents listed in

the section on food composition above, with the

exception of fiber (nondegradable organic mat-

ter in figure 2). For carbohydrates, particularly

starch, the availability for digestion seems to be

lower in processed and reheated food (Clifford

2007); this might introduce differences between,

for example, ready-meal and home-prepared ver-

sions of the same foodstuffs. This has not been

taken into account in the model, however: All

organic degradable materials are assumed to be

fully available for digestion.

Inorganics and water are not subject to any

chemical transformation; the latter is partitioned

between air and wastewater, whereas the for-

mer are assumed to report entirely to wastewa-ter. The main transformation described by the

model is that undergone by degradable organic

material as a result of human digestion. To

model this transformation, a general biochem-

ical reaction has been defined, which, in turn,

requires the chemical composition of the reac-

tants to be defined. Table 1 summarizes the av-

erage elemental composition of the food con-

stituents and how they have been estimated. The

data in table 1, with the exclusion of fiber, are

used along with food composition to estimate a

weighted empirical formula for digestible organic

matter.

Nondegradable material is basically excreted

via feces without taking part in any human

metabolic process. An allowance has been made

for fiber, however, as well as for degradable or-

ganic matter, to be converted to methane by thecolon bacterial flora. This is further described in

the next section.



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The overall biochemical reaction proposed for

degradable organic matter is shown in equation 1.

This equation implies that organic degradable

matter is converted, by cell respiration, to car-

bon dioxide and water, whereas some carbon is

lost in urea (CH4ON2) and feces (C2H4O). Tosimplify the calculations, it is assumed that all

nitrogen from protein degradation ends up in

urea, so that feces contain only carbon, hydro-

gen, and oxygen, in molar proportions similar to

those in activated sludge in wastewater treatment

plants. All sulphur ends up as sulphate, reported

as H2SO4. Some sulphur will actually be ex-

creted via growth of hair and nails, but this has

been omitted from the model in the interest of

simplicity.

CaHb OcNdSe + A O2 B C O2

+C H2 O + D C H4 ON2

+ E H2 S O4 + F C2 H4 O (1)

where

E = e (2)

D = d /2 (3)

F = 0.055a (4)

B = a D F (5)

C = (b 4D 2E 4F )/2 (6)

A= (C + D + 4E + 2F + 2B c)/2 (7)

For equation 1 to be solved, the share of car-

bon incorporated in either carbon dioxide (B) or

feces (F) has to be defined. We have done this

by calculating a balance for degradable carbon in

the human body, with the following assumptions:

Alveolar volume in respiratory system is

350 milliliters (mL),2 of which 5% is car-

bon dioxide (Boron and Boulpaep 2003).

Breathing rate is taken as the average

of 12/min (Boron and Boulpaep, 2003)

and 20/min (Marieb 1995). This leads

to an average output of 195 grams car-bon/person/day as carbon dioxide exhaled.

Urine production is 1.5 L/day (Boron and

Boulpaep 2003), with a dry weight of 5%

(Mara 2003) and a carbon content 14% in

dry weight (Feachem et al. 1983). The car-

bon loss in urine follows as 11 g/person/day.

Feces production is around 0.15 kilogram

(kg)3 per day, with a dry matter content

of 25% and a carbon content of 50% inthe dry matter (Feachem et al. 1983). This

gives 19 g C, from which the contribution of

nondegradable fiber must be excluded. Av-

erage intake of fiber is 15 g/person/day, with

a carbon content of 44% (table 1). If we

assume that fiber is excreted in feces with-

out any transformation, the contribution of

fiber to carbon in feces is 7 g. Therefore,

the output of degradable carbon via feces is

19 7 = 12 g C/person/day.

These calculations lead to a loss of degradable

carbon via feces of 5.5% (equation 4). It is worth

noting that a similar amount is lost via urine,

around 90% of the amount of carbon effectively

used by cell respiration and transformed to carbon

dioxide. This balance has omitted several carbon

flows that were estimated and found to be negli-

gible: carbon dioxide and methane via intestinal

gas, and methane expelled via lungs; altogether,

these account for less than 0.1% of the carbonoutput.

The fate of each of the final products obtained

in equation 1 is defined in the model as follows:

Carbon dioxide is entirely emitted to atmo-

sphere via the lungs.

Urea, sulphate, and feces are expelled as

liquid and solid excreta: urea dissolved in

urine, and feces as solid, whereas sulphate

seems to be almost entirely excreted in

urine (Florin et al. 1991).

Water will be emitted both as a liquid and

as a gas. To determine the share of each,

we have used the water balance suggested

by Boron and Boulpaep (2003), according

to which 64% of the water output corre-

sponds to the liquid phase (60% by urine

and 4% by feces), whereas the remaining

36% corresponds to the air phase (22% by

skin/sweat and 14% by breathing). In ad-

dition to the water produced by cell respi-ration, the model must also determine the

fate of water originally present in food, usu-

ally a much larger quantity. The fate factors



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already above also apply to the water in

food.

Fiber is the only category of organic con-

stituents in food not affected by the biochemical

transformation in equation 1. Fiber is assumed tobe emitted to wastewater via feces with no chem-

ical transformation except methane production,

as described below.

Methane Emissions

Besides cell respiration, the only additional

chemical transformationconsidered by the model

is the formation of methane by colonic bacteria.

In carbon terms, the amounts may seem negligi-

ble (see above), but from a greenhouse gas per-

spective they may not be. For this reason, an at-

tempt has been made to estimate the amount of

methane emitted by the human body due to the

activity of anaerobic bacteria in the intestine.

Human cells have no metabolicpathway capa-

ble of producingor metabolizing methane.There-

fore, the model attributes all methane production

to the action of intestinal bacteria and assumes

that all methane is excreted in intestinal gas or

exhaled breath (Bond et al. 1971). Methane pro-duction varies widely among individual humans:

Some subjects, approximately one third of the

population, continually produce large quantities

of this gas, whereas others consistently excrete lit-

tle or no methane at all. This appears to be related

to the presence or absence of methane-producing

flora: Familial (not necessarily genetic) factors

play an important role in determining whether

a subject produces methane (Levitt and Bond

1980).4

According to Bond and colleagues (1971), the

average methane excretion rate of methane pro-

ducers is 0.33 mL/min and 0.45 mL/min via lungs

and intestine gas, respectively. If a pressure of

1 atmosphere (atm)5 and a body temperature of

310 kelvin (K)6 are considered, this suggests that

a methane producer emits 0.52 g C in CH 4 per

day, or 0.69 g CH4per day. If this is corrected to

take into account that only 33% of the popula-

tion are considered to be significant methane pro-

ducers, we obtain an average emission of 0.17 g C-CH4per person per day, or 0.23 g CH4per person

per day. This implies that around 0.08% of the

total carbon emitted by the human population is

in the form of methane.

Degradable organic material contributes to

methane production, but so does dietary fiber.

Tomlin and colleagues (1991) found that a fiber-

rich diet implies an increase in intestinal gas pro-duction as compared to a fiber-free diet. Bond and

colleagues (1971), however, found that methane

production is insensitive to changes in nonab-

sorbable carbon intake, whereas the production

of other gases, in particular hydrogen, is clearly

enhanced by fiber intake. In view of this uncer-

tainty, the model allocates methane emissions to

all carbohydrates present in the food ingested on

the basis of carbon content, regardless of whether

they are digestible.

Metabolic Energy Balance

With regard to the energy balance of the over-

all process, the chemical energy stored in all the

inputs and outputs to and from the human body

is calculated, on the basis of their heating values.

The model uses the upper heating value, because

most water is excreted as the liquid, whereas even

the vapor emissions (exhaling and perspiration)

actually pass through the skin and lung surfacesas liquid. Upper heating values are calculated for

food, methane, urea, and feces derived from both

degradable and nondegradable organic material

(fiber). All the remaining materials (oxygen, wa-

ter, carbon dioxide, sulphate, and phosphorus)

are assigned a null energy content. The heat

content calculation is based on elemental com-

positions according to the formula proposed by

Michel (1938):

Upper Heating Value (MJ/kg)

= 9.8324O + 124.265H

+ 34.016C + 19.079S + 6.276N (8)

whereC,H,O,N, andSare the mass fractions of

each element. The figures obtained with equation

8 for the energy input in fiber-rich food will be

higher than those reported in food labels, which

normally exclude the calorific value of fiber be-

cause it is nonabsorbable and not actually di-

gested.The difference between the energy input and

output, each calculated with equation 8, is the



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fraction of energy effectively used by the cells

in their metabolic processes. The model assumes

this energy to be emitted eventually to the envi-

ronment as heat.

Allocation of Technosphere Processes

Using the toilet to evacuate liquid and solid

excretion products implies, directly or indirectly,

the use of ancillary materials and energy. The

model allocates these processes to food intake

on the basis of mass of excretion products. The

following basic assumptions are made:

Every time the toilet is used, it is flushed.

After each toilet use, hands are washed withsoap and water at ambient temperature.

At home toilets, hands are dried by means

of a towel, whereas at workplace toilets,

hands are dried by means of a hot air

blower.

Towel production is excluded because of

the long service life of the towel, but wash-

ing and drying at home are included.

Transport of ancillary materials (soap, de-

tergent, toilet paper) is not included.

A set of parameters have been defined and

given default values intended to be representative

of UK conditions (table 2). The user can modify

the parameter values to make them representa-

tive of other regions or scenarios.

The different environmental burdens can be

calculated per person per day with the data in

table 2. Next, these figures are divided by the

average daily solid plus liquid excreta production

by an average person, which is taken as 1.65 kg,made up of 1.5 kg (i.e., 1.5 L) urine and 0.15 kg

feces. The allocation to food intake on the basis

of food excreta is finally carried out by means of

equation 9:

Toilet related burden

kg food intake

=Toilet related burden

kg solid and liquid excreta

kg solid and liquid excreta

kg food intake

(9)

Model Output

The output of the human excretion model

consists of a disaggregated inventory table includ-

ing inputs from nature (oxygen), inputs from the

technosphere (food itself and those related to toi-

let use), outputs to nature (emissions to air from

respiration and digestion), and outputs to the

technosphere (wastewater). The pollutionload of

the resulting wastewater is expressed in the model

by the parameters total organic carbon (TOC),

biological oxygen demand (BOD), chemical oxy-

gen demand (COD), N-total, P-total, and other

inorganic elements. A small amount of these pol-

lutants arises from toilet use (hands washing with

soap, towel washing, etc.), but the highest share

is related to human excreta; they are calculatedby the model as follows:

TOC is determined from the carbon con-

tent in the solid and liquid excretion prod-

ucts, namely fiber, and products of equa-

tion 1: feces and urea. COD and BOD are

estimated from TOC according to the fol-

lowing ratios (Doka 2007): TOC/BOD =

0.641, and TOC/COD = 0.479. It must

be noted that these three parameters are

related; just one of themCOD in thisworkmust be used in the eutrophication

potential, because otherwise we would be

double counting carbon emissions.

Nitrogen from human metabolism is con-

sidered in the model to be excreted only as

urea. Thus, from the amount of urea pro-

duced and its empirical formula, the nitro-

gen released into wastewater is calculated.

Phosphorus and other inorganics are just

expressed as the initial amounts in food,because they are not subject to any trans-

formation in the model.

We can calculate the concentration of pol-

lutants in wastewater by dividing the amounts

released by the total water discharged, including

water from toilet use and water in the food it-

self and resulting from digestion (see equation 1).

Impacts related to wastewater treatment and the

final amount of pollutants released to the envi-

ronment must be subsequently modeled by theLCA practitioner, using, for example, the models

suggested in the General Structure and System



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Table 2Parameters and default values used for allocation of toilet use processes

Default

Parameter value Comments

Toilet flush volume

(L)

11 Measured volume of a standard toilet tank at the University of

SurreyHand-washing water

use (L/wash)

1.5 Assumption

Toilet uses

(times/day)

5 Assumption; this includes both urination and defecation

Toilet uses at home

(%)

57 This parameter is used to estimate the share of hand drying by

means of a cotton towel. The remaining 33% is assumed to

be done at work with a hot air blower. The value is an

assumption based on the following figures: 5 working days

per week, 2 weekend days per week. In a working day, three

toilet trips are made at the workplace, and two at home. On

weekends, all toilet trips are made at home.

Toilet paper use(kg/day/person)

0.02 Calculated with the following data: tissue paper consumptionin Western Europe in 2004 was 4.1 million tonnes, of which

62% was toilet tissue, and 18% was consumed in the United

Kingdom and Ireland (European Tissue Symposium, 2005).

The population of the United Kingdom and Ireland in 2004

was 63,727,560 (Eurostat 2007).

Hand-washing

(liquid) soap use

(g/wash)

3.3 Measured weight at University of Surrey toilet was 100 g liquid

soap dispensed per 60 pushings. The figure considers two

dispenser pushings per wash.

Electric hot air

blower power

(kW)

2 Average power of a hand dryer (Handryers.net 2005)

Time needed to dry

hands (s)

30 Average drying time of a hand dryer (Handryers.net 2005)

Towel weight (kg) 0.35 Assumed for a cotton towel

Number of persons

per household

2.4 Average for the United Kingdom (Office for National

Statistics 2007)

Frequency of towel

washing (days)

7 Assumption

Power demand of

washing machine

(kWh/kg towel)

0.43 Washing of the cotton towel (Group for Efficient Appliances

1995)

Detergent use by

washing machine(g/kg towel)

45 135 g detergent for a typical 3-kg load. Process related to

washing of the cotton towel (Group for Efficient Appliances1995)

Water use by

washing machine

(L/kg towel)

17.2 Washing of the cotton towel (Group for Efficient Appliances

1995)

Power demand of

towel drier

(kWh/kg towel)

0.7 Drying of the cotton towel (Group for Efficient Appliances

1995). Average of three technologies: air vented tumble

driers, condenser tumble driers, and condenser washer driers

Hand-washing

wastewater

composition

(mg/L)

COD: 400 Representative averages from several studies (Eriksson et al.

2002)

Continued



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Table 2Continued

Default

Parameter value Comments

BOD: 190

N-total: 10P-total: 1

Laundry wastewater

composition

(mg/L)

COD: 1270 Representative averages from several studies (Eriksson et al.

2002)

BOD: 260

N-total: 10

P-total: 25

Note: COD = chemical oxygen demand; BOD = biological oxygen demand; N-total = nitrogen total; P-total =

phosphorus total. One kilowatt (kW) 56.91 British Thermal Units (BTU)/minute 1.341 horsepower

(HP).

Boundariessection of this article. Table 3 shows

an example of an inventory table obtained for

a particular product, namely boiled broccoli, by

applying the model to the composition for this

product given in table 4.

Results

Model Sensitivity to Different Food Types

The sensitivity of the model to food compo-

sition has been tested on eight food products

commonly present in daily western diets, with

typical compositions given in table 4: bread, broc-

coli, apple, chicken meat, beer, cheese, a choco-

late snack, and coffee. Selected inventory results

are given in figure 3. Rather than comparing the

environmental performance of these food items,

the following discussion aims at exploring how

the model responds to extremely different data

inputs.

Figure 3 shows that some parameters are

highly variable from one food type to another,

whereas others remain quite similar. The amount

of solid and liquid excretion products emitted to

wastewater (figure 3a), for example, is rather sim-

ilar for all these food products, in the range 0.5

to 0.65 kg per kg food, primarily because water

is one of the main components in food and 64%

of the water is assumed to report to urine andfeces regardless of the food type. Nevertheless,

foods with low water content, such as the choco-

late snack or the parmesan cheese, lead to similar

values. This is explained by the fact that one of

the main outputs of the organic degradation reac-

tion, as shown in equation 1, is also water. If the

mass of excretion products per kilogram ingested

is broadly comparable for all foods, then the en-

vironmental burdens from the technosphere pro-

cesses described above (e.g., wastewater volume,

figure 3d) will also be similar for all food products,

because all these processes are allocated on thebasis of the amount of solid and liquid excretion

products.

Carbon dioxide emissions due to respiration

(figure 3b), conversely, are highly variable de-

pending on the food type; between coffee and the

chocolate snack, for instance, there is a difference

of three orders of magnitude. This is clearly re-

lated to the degradable carbon content in food,

which is very high in dry foods, such as cheese

and chocolate, and very low in drinks, such as

coffee or beer. Methane emissions (figure 3c) fol-

low a pattern similar to that for carbon dioxide

emissions, because this pollutant is allocated on

the basis of carbon content in food. In this case,

not only degradable carbon but also nondegrad-

able carbon (present as fiber) contributes; how-

ever, we see in table 4 that in most of the food

products considered, the main source of carbon is

other than fiber.

The volume of wastewater discharged to the

sewer (figure 3d) shows a similar pattern for allfoodstuffs. Across all products, the quantity of

wastewater is 20 to 26 liters per kilogram of food,



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F O R U M

Table 3 Inventory table for excretion of boiled broccoli

Inputs and outputs Comments

InputsFrom natureOxygen (g) 71 Oxygen needed for cell respiration of degradable constituents in

food (carbohydrates, fat, and protein)From the technosphereBroccoli, boiled in

unsalted water (g)

985 Grams of food ingested

Toilet paper (g) 7.8 Allocated on the basis of solid plus liquid excreta mass

Tap water (L) 24.4 Toilet flushing plus hand washing, plus towel washing, allocated

on the basis of solid plus liquid excreta mass

Soap (g) 6.5 Hand washing, allocated on the basis of solid plus liquid excreta

mass

Detergent (g) 0.36 Detergent for washing machine used for towel washing, which, in

turn, has been used to wash hands

Power (kWh) 0.023 Electricity for hot air blower, washing machine, and drier. Allthese processes are related to hand drying

OutputsTo natureAir emissions:

Carbon dioxide (g) 80 Produced by catabolism of degradable constituents in food

(carbohydrates, fat, and protein)

Methane (g) 0.037 Produced by colonic bacteria. Degradation of all

carbon-containing compounds, including fiber

Water (g) 337 36% of all water ingested or produced by catabolism is evaporated

by the body through skin or breathing. Main source of water

here is the initial content in food, but there is also water

produced in cell respirationHeat (MJ) 1.0 Energy actually used by metabolic processesTo the technosphereToilet paper (g) 7.8 Present in wastewater

Wastewater volume (L) 25 Sum of solid plus liquid excreta plus tap waterWastewater emissions from food:

Urea (g) 9.8 All nitrogen in food is assumed to be included here

N-urea (g) 4.6 Urea expressed as nitrogen mass

TOC (g) 13 Carbon content in urea and fiber

BOD (g) 21 Related to carbon content from urea and fiber

COD (g) 28 Related to carbon content from urea and fiber

Sulphate (g) 2.2 From protein metabolism

P-total (g) 0.57 Inorganic constituents in food are 100% allocated to solid plus

liquid excreta.

Na (g) 0.13 Inorganic constituents in food are 100% allocated to solid plus

liquid excreta.

K (g) 1.7 Inorganic constituents in food are 100% allocated to solid plus

liquid excreta.

Ca (g) 0.4 Inorganic constituents in food are 100% allocated to solid plus

liquid excreta.

Cl (g) 0.23 Inorganic constituents in food are 100% allocated to solid plus

liquid excreta

Continued



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F O R U M

Table 3Continued

Inputs and outputs Comments

Wastewater emissions from toilet use:

BOD (g) 0.59 Related to gray wastewater: hand washing and towel washing

COD (g) 1.3 Related to gray wastewater: hand washing and towel washingN-total (g) 0.030 Related to gray wastewater: hand washing and towel washing

P-total (g) 0.0064 Related to gray wastewater: hand washing and towel washing

Note: N, P, Na, K, Ca, and Cl refer to the elemental symbols. COD =chemical oxygen demand; BOD =biological

oxygen demand; N-total = nitrogen total; P-total = phosphorus total.

Megajoule (MJ) = 106 joules (J, SI) 239 kilocalories (kcal) 948 British Thermal Units (BTU).

associated mainly with toilet use (flushing, wash-

ing hands, etc.).

The mass of pollutants discharged to the sewer

(figure 3e) shows a different picture. In this case,big differences are seen between products, up to

two orders of magnitude in all three parameters.

There is a clear relationship between protein con-

tent and discharge of urea and sulphate, as pro-

teins are the only food constituents containing

nitrogen and sulphur in their empirical formula.

Carbonaceous organic matter, measured as COD,

is related not only to proteins but also to fiber and

degradable organic matter in general. This figure

shows only the amount of pollutants derived fromsolid and liquid excretion products, whereas the

contribution of toilet use (gray wastewater from

hands washing and towel washing) is excluded.

Table 4Composition of several food products, in grams per 100 g edible portion

Coffee, White

Broccoli, Roasted Lager Chocolate Parmesan Apple, infusion, bread,

Component boiled chicken beer snack cheese nonpeeled average sliced

Water (g) 91.1 65.3 93 2 27.6 84.5 98.3 38.6Protein (g) 3.1 27.3 0.3 7.5 36.2 0.4 0.2 7.9

Fat (g) 0.8 7.5 Tr 26 29.7 0.1 Tr 1.6

Carbohydrate (g) 1.1 0 Tr 63 0.9 11.8 0.3 46.1

Fiber (g) 2.3 0 Tr N 0 1.8 0 1.9

Alcohol (g) 0 0 4 0 0 0 0 0

P (g) 0.057 0.2 0.019 0.2 0.68 0.011 0.007 0.095

Na (g) 0.013 0.1 0.007 0.12 0.756 0.003 Tr 0.461

K (g) 0.17 0.3 0.039 0.33 0.152 0.12 0.092 0.137

Ca (g) 0.04 0.017 0.005 0.2 1.025 0.004 0.003 0.177

Cl (g) 0.023 0.088 0.02 0.21 1.26 Tr 0.003 0.829

Source: Food Standards Agency (2002).Note: P, Na, K, Ca, and Cl refer to the elemental symbols. Tr = trace (considered as zero); N = no reliable information

(considered as zero).

Nonetheless, table 3 shows that the contribution

of toilet use is one order of magnitude lower for

the particular case of broccoli.

Finally, as expected, the energy content offood is also highly variable (shown in parenthe-

ses on top of the bars in figure 3f), as also is the

energy efficiency of the human body, depending

on the composition of food. The efficiencies go as

high as 95% for beer and as low as 63% for broc-

coli. The most energy-efficient foods appear to be

alcoholic drinks, due to the ethanol content, and

also fat- and carbohydrate-rich foods, whereas the

least efficient are those containing a high share

of proteins, such as chicken, and especially, fiber,as in the case of broccoli. Proteins show a lower

efficiency due to an important energy loss in the

form of urea, whereas the human body is simply



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F O R U M

Figure 3 Selected model results for several food products.

unable to digest the fiber in fiber-rich foods and

use its chemical energy.

Importance of Human-Excretion-Related

Impacts in the Overall Life Cycle

of Foodstuffs

Figure 4 shows the cradle-to-grave results for

consumption in the United Kingdom of 1 kg

broccoli grown in Spain. Details of the life cy-

cle modeling for these crops are provided by Mila

i Canals and colleagues (2008). The excretion

and wastewater stage includes the emissions de-

scribed in this article in addition to the treat-

ment of the wastewater described in table 3; the

latter has been modeled as described by Munoz

and colleagues (2007). Global warming potential(GWP) and eutrophication potential (EP) have

been assessed according to the CML2001 method

(Guinee et al. 2002); in addition, the inventory

indicators water use (WU) and primary energy

use (PEU) are shown in figure 4.

EP (figure 4a) is dominated by the home

and excretion and wastewater stages, which con-

tribute 32% and 45%, respectively, to the total

EP related to the broccoli life cycle. The former

contributes due to the loss of nitrogen and phos-

phorus from broccoli to the boiling water during

cooking. Nitrogen and phosphorus are not effec-

tivelyremoved in the sewage plant and so become

emissions to aquatic ecosystems; note that these

figures assume that only 11% of wastewater is

treated in plants equipped with nutrient-removal

processes, because this is the current situation in

the United Kingdom (Munoz et al. 2007). Also,

there is the contribution from leachate emissionsfrom landfilling of food waste (uneaten broccoli;

see the top section in the Homebar in figure 4a).



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F O R U M

Figure 4 Contribution of different life cycle stages and items to eutrophication potential, global warming

potential, water use, and primary energy use for consumption in the United Kingdom of 1 kg Spain-grown

broccoli. WWT = wastewater.

Nonetheless, wastewater treatment of feces and

urine creates the biggest contribution to EP; this

is mostly due to nitrogen and phosphorus com-

pounds.

In the case of GWP (figure 4b), the contribu-

tion from the excretion and wastewater phase is

not as significant as in the nutrient-related im-

pact. Energy use at home (mainly for boiling

the broccoli) dominates GWP through carbon

dioxide (CO2) emissions, whereas fertilizer re-

lated nitrous oxide (N2O) and CO2 from fueluse by farm machinery dominate the cropping

stage. The GWP reduction in cultivation, due to

the C embodied in broccoli through photosyn-

thesis (seen as a negative bar in Figure 4b), is

almost entirely reemitted to the atmosphere dur-

ing the excretion and wastewater stage. The re-

maining C is emitted in the landfilled food waste

and/or remains in the landfill or sewage sludge

from wastewater.

Concerning WU (figure 4c), the croppingstage is clearly the most important one, as it is

responsible for 73% of theoverall water consump-

tion. Broccoli is an irrigated crop in Spain, using

something less than 200 L/kg. The contributions

of the home (15%) and excretion and wastewater

(9%) stages are not negligible, however. It must

be highlighted that the water use associated with

the home stage is mainly cooling water used in

electricity production, rather than water actually

used in the kitchen for cooking. Although the

contribution of these two stages may seem low,

it must be borne in mind that if UK-grown broc-

coli were considered, these relative contributionswould be much higher, because in the United

Kingdom broccoli is rain fed.

Finally, PEU (figure 4d) is clearly dominated

by the home stage, due to the electricity and gas

consumed for broccoli cooking, which account

for 65% of the PEU. Retail and distribution and

cropping are responsible for 22% and 11%, re-

spectively. In this case study, it is concluded

that human excretion and further wastewater

treatment have a negligible contribution from aPEU perspective. Nevertheless, it is interesting

to observe that the PEU of toilet use processes



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F O R U M

(production and delivery of toilet paper, soap,

tap water, etc.) is three times higher than that

related to treating the fecal wastewater in the

sewage plant.

Discussion and Conclusions

Human excretion has proven to be signifi-

cant in the overall life cycle of food products.

Particularly for the nutrient-related EP, emis-

sions from postconsumer wastewater treatment

areof paramount importance, together with other

home-related nutrient losses through boiling wa-

ter and food waste. This is crucial, as it is often

concluded from partial LCA studies, cradle-to-

gate or cradle-to-retail, that EP is dominated by

the cropping stage. Obviously, nutrient emissions

from agriculture merit attention due to their dif-

fuse nature and the fact that it is possible to reduce

them. Nonetheless, nutrient emissions from do-

mestic activities should not be overlooked. The

results obtained in this work suggest the impor-

tance of educating consumers on healthy cook-

ing to avoid flushing so much of the foods nutri-

ent content down the drain (e.g., 30% of proteins

and 34% of phosphorus are lost to the water whenbroccoli is boiled). The amount of nutrients lost

in the cooking stage will vary significantly with

food type, particularly with foodstuffs that are

eaten raw (e.g., lettuce, fruit); in this case, there

would be less nutrient loss in the kitchen but

more releases after treatment of fecal wastewater.

It should be noted that the contribution of excre-

tion and wastewater to GWP would also be more

significant for foodstuffs that are eaten raw (i.e.,

when no energy is used for cooking). In addi-

tion, the contribution from the distribution stage

is relatively high, and the relative importance of

excretion is thereforereduced in theexample pre-

sented here because broccoli is transported over

2,600 kilometers (km).7

The model presented here provides a tool to

enable human excretion to be included in food

LCAs. This tool might also be of interest for other

environmental analysis methods, such as mate-

rial flow analysis and substance flow analysis, as

the model can be used to close the balances forcarbon, nitrogen, and phosphorus, among other

substances present in food.

Concerning the application of this model to

regions different from the United Kingdom and

other western countries, we can make a distinc-

tion between human body modeling, on the one

hand, and toilet use and wastewater treatment

plants, on the other. The default values usedhere to model the latter are representative of

the United Kingdom, but they can be modified

at will by the user. The balances obtained from

human body modeling are based on figures from

western sources but should be generally applica-

ble. For most of the variables included, data from

different regions have not been found, but the

model should give reasonable estimates of emis-

sions from the macronutrients in food.

The case study presented here can be con-

sidered as an attributional LCA. Our model has

proven to be useful in highlighting the relative

importance of excretion in a food products life

cycle. Nevertheless, it has also been shown to be

very sensitive to food composition, which sug-

gests that it may also be useful in consequential

LCA, dealing with such topics as the environ-

mental assessment of dietary shifts. Until now,

only the comparative environmental impacts of

producing the ingredients for different diets have

been assessed; this study shows that differencesrelated to excretion emissions from different diet

compositions may also be important, particularly

when changes in the balance of macronutrients

(proteins, fats, carbohydrates, fiber) occur. Future

research should check the significance of the ex-

cretion stage for a range of food products. In addi-

tion, the model could be developed further to al-

lowfor differing N content in proteins from differ-

ent sources (e.g., to distinguish between animal-

based and plant-based proteins); however, ini-

tial exploration of variations in protein/N factors

suggests that the resultant changes in excretion

impacts are likely to be small.

Acknowledgements

This research was carried out under

project RES-224-25-0044 (http://www.bangor.

ac.uk/relu), funded as part of the UK Rural

Economy and Land Use (RELU) programme.

Dr. Mila i Canals acknowledges GIRO CT(http://www.giroct.net) for its logistic support.

The authors kindly thank Prof. Mike Clifford for



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F O R U M

his useful comments on the model, Gabor Doka

for his support in wastewater treatment modeling,

and the three anonymous reviewers who have

provided constructive comments on this article.

Notes

1. Depending on the goal of the study, LCAs

are usually classified as follows (Weidema, 2003):

Attributional: life cycle assessments of the ac-

countancy type, typically applied for hot-spot

identification, for product declarations, and for

generic consumer information. This would cor-

respond to the type of study carried out in our

article.

Consequential: they study the environmental

consequences of possible (future) changes be-

tween alternative product systems, typically ap-

plied in product developmentandin public policy

making. This type of LCA would correspond to a

case study dealing with diet shifting.

2. One milliliter (mL) = 103 liters (L)

0.034 fluid ounces.

3. One kilogram (kg, SI)2.204 pounds (lb).

4. The presence of mercaptans in intestinal

gas is regarded as a local environmental quality

issue and not included in the model.5. One atmosphere (atm) 760 torr 14.70

pounds/inch2.

6. 310 K 36.85 C 98.33 F.

7. One kilometer (km, SI) 0.621 miles

(mi).

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About the Authors

Ivan Munozwas a research fellow at the Cen-

tre for Environmental Strategy, University ofSurrey, Surrey, United Kingdom, at the time the

article was written. He is currently a researcher

at the Department of Hydrogeology and Analy-

tical Chemistry, University of Almeria, Almeria,

Spain.Llorenc Mila i Canalswas a research fel-

low at the Centre for Environmental Strategy,

University of Surrey, at the time the article was

written. He is currently life cycle analysis man-

ager within Unilevers Safety and Environmental

Assurance Centre (SEAC) group, Unilever Col-worth, Colworth, United Kingdom. Roland Clift

is distinguished professor of environmental tech-

nology in the Centre for Environmental Strat-

egy at the University of Surrey and president-

elect of the International Society for Industrial

Ecology.


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