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Journal of Cleaner Production 19 (2011) 1849e1856

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Journal of Cleaner Production

journal homepage: www.elsevier .com/locate/ jc lepro

Carbon footprint of food e approaches from national inputeoutput statisticsand a LCA of a food portion

Yrjö Virtanen a,*, Sirpa Kurppa a, Merja Saarinen a, Juha-Matti Katajajuuri a, Kirsi Usva a, Ilmo Mäenpää b,Johanna Mäkelä c, Juha Grönroos d, Ari Nissinen d

aMTT Agrifood Research Finland, Jokioinmen, Finlandb Thule Institute of the University of Oulu, FinlandcNational Consumer Research Centre, Finlandd Finnish Environment Institute, Finland

a r t i c l e i n f o

Article history:Received 2 July 2010Received in revised form23 June 2011Accepted 5 July 2011Available online 2 August 2011

Keywords:Carbon footprint of foodNational food systemFood portionEIO-LCA approach

* Corresponding author.E-mail address: yrjo.virtanen@mtt.fi (Y. Virtanen).

0959-6526/$ e see front matter � 2011 Published bydoi:10.1016/j.jclepro.2011.07.001

a b s t r a c t

The aim of the study, on which this paper is based, was to provide guidance to consumers to makeenvironmentally responsible choices in their food consumption, to assist food supply chain stakeholdersto identify the key areas for environmental improvements, and to provide policy makers with a tool formonitoring the potential impacts on climate change resulting from developments within the food sector.At the macro level, the EIO-LCA model was developed specifically for the Finnish food chain; at the microlevel, LCAs were performed on 30 lunch portions. The contribution of the Finnish food chain to climatechange was 14%, which comprised 40% CO2 emissions, 25% CH4 emissions, and 34% N2O emissions. Theshare of impacts from domestic agricultural processes was the highest, at 69%. The impact of a singlelunch portion ranged between 0.65 and 3.80 kg of equivalent CO2. According to the EIO-LCA model, theaverage impact was 7.7 kg CO2 eq/person daily. The consumer phase accounted for between 8 and 47% ofthe climate change impacts for homemade portions. In ready-to-eat portions industry and retail phaseswere emphasized, representing 25e38% of climate change impacts. We present an approach to steer theFinnish food sector onto an environmentally sustainable path; practical tools for consumers and farmerswill especially need to be developed further.

� 2011 Published by Elsevier Ltd.

1. Introduction

Finnish farmers, industry, trade, consumers and administratorsare currently working together to establish Finland as a country ofhigh-quality food products. The foundation of the food chainquality work is the full commitment of the entire food supply chainto a national food quality strategy. Strengthening environmentalresponsibility, the development of responsible productionmethodsand their respective proactive communication are key objectives ofthis strategy.

The CO2 footprint, i.e. the climate change impact of food, isarguably one of the most important issues in improving the envi-ronmental responsibility of the food chain and also the mostintensively discussed in Finland at the moment. Farmers, industry,trade and consumers are all keen to reduce climate change impactbut currently they lack the means to address the problem

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adequately. Therefore, the primary challenge for science is toprovide those involved in the food system with the necessaryinformation and tools to understand and influence key issues suchas the potential for carbon sequestration and the mitigation ofcarbon footprints, including reducing the negative impacts of poorfarming techniques and consumer choices.

Our research approach was founded on an environmentalassessment of the food system based on a national economicinputeoutput model (EIO-LCA) (Hendrickson et al., 2006; Suh et al.,2004), and on process-based LCA models of nutritionally balancedstandard lunch plates. The standard lunch plate is commonly usedin Finland and other western countries to communicate toconsumers how to make healthy food choices and is therefore veryfamiliar to most consumers. The lunch plate model is divided intothree parts; half of the plate consists of vegetables, one quarter ofprotein and one quarter of carbohydrates. Using the lunch plateapproach we projected the environmental impacts of foodconsumption at the micro level, and with the EIO-LCA approach atthe macro level. The lunch plate model was used as a functionalunit in a process-based LCA instead of, for example, the actual

Y. Virtanen et al. / Journal of Cleaner Production 19 (2011) 1849e18561850

consumption of food. This was because the initial target of themicro level approach was to form a communication model forsustainable education in elementary schools (Saarinen et al., 2009,2011). The aimwas, at the micro level, to illustrate how a consumercan alter the environmental impacts of his or her food choices whiletaking into account the nutritional functions of food. It wasconsidered necessary to stress the nutritional attributes of foodsince a significant section of young people are intent on makingradical food choices. There is a concern that they may ignorenutritional qualities of food, e.g. give up eating meat withoutconsidering its nutritional value. However, nutrition is a mainfunction of food, and good nutrition is a dimension of sustainability.Since meat per kg basis is considerably more of a burden on theenvironment than vegetables and plant-based protein (e.g.Steinfeld et al., 2006; Usva et al., 2009) and shifting from an animal-based diet to a plant-based diet is suggested as a solution to reducethe climate impacts of food consumption (Baroni et al., 2006;Carlsson-Kanyama, 1998; Carlsson-Kanyama et al., 2003; Friedl,2007; Pimentel and Pimentel, 2003; Reijnders and Soret, 2003), westudied how the difference between meat and plant-based foodsaltered when all the components of a balanced portion wereconsidered. In addition, we studied how the choice of an alternativecomponent to protein source will affect the final outcome.

The results of the EIO-LCA approach were integrated withresults received from process-based LCAs in order to build upa comprehensive view of the impacts of food consumption inFinland. The approach that was taken adapts a hybrid LCA (Minxet al., 2007), where the IO model has the benefit of giving a totalpicture of the economy, and process specific data are added whereavailable to facilitate as detailed an analysis as possible.

The specific targets set for the study were to assess the totalimpacts attributable to Finnish production and imports of food-stuffs, including their transport, and the specific environmentalimpacts of standard lunch plates. The final objectives were: to assistconsumers in making environmentally responsible choicesregarding future food consumption, to improve the food supplychain by identifying the key areas for improvement in terms ofvarious environmental impacts, and to provide policy makers witha tool for monitoring the development of the food sector withrespect to the potential impacts on climate change.

Impacts of food production were analysed stage by stage overthe whole food chain. Using the micro level approach, the impactsof different ways of food processing were compared: home, publiccatering and industrial processes for ready-to-eat dishes. Theimpacts of household and post-household activities were alsolinked to food consumption. In the macro level approach, thesystem studied covered domestic production, including theimports of raw materials and the imports of food-chain-productsfor end-consumption. Emission estimates for imports were basedon product specific emission data gathered from relevantcommercial and public life cycle inventory (LCI) databases. Forminor import volumes, however, emissions were estimated usingthe respective domestic emission factors. The boundary conditionof the EIO-LCA model was determined as expanded end-consumption of food-chain-products. Thus, it consists of the stan-dard end-consumption of the national accounts and, additionally,of intermediate industrial usage, which included the consumptionof the service sector and other sectors of the economy that produceitems that are not food-chain-products. The activities of the end-consumption and post- end-consumption phases were notincluded in the system.

The differences in the results of the two different approaches,from micro and macro level investigations, and the applicability ofthe respective results for the various societal needs, are discussed.The restrictions of both approaches are highlighted and the

methodology and the results are considered in the context ofcurrent efforts within the Finnish food sector to standardize carbonfootprint calculations. Note is taken of the strategic approaches tothe food system adopted in the UK by the lead organization, Defra(Department for Environment, Food and Rural Affairs) (Defra,2010a) and in Finland by the initiative from the Prime Ministerfor food strategy (Anon., 2010). For the strategic approaches, suchas taxation and incentive bonus systems, the holistic informationon food system behaviour is necessary to secure good quality dataproduction. A discussion of the results in light of other EIO-LCAapproaches, such as the environmental impact assessment modelof the Finnish economy, the ENVIMAT-model (Seppälä et al., 2009,submitted for publication) and British Food System Indicators(Defra, 2010b) is included.

2. Methods and materials

2.1. EIO-LCA approach

The EIO-LCA model used to assess food chain environmentalimpacts was developed specifically for the Finnish food chain(Virtanen et al., 2009). Themodel is based on data from 2005. Muchof the data was obtained from the material flow and environmentalimpact assessmentmodel of the Finnish economy, ENVIMAT-model(Seppälä et al., 2009, submitted for publication).

2.1.1. Structure of the modelThe EIO-LCA model was derived from economic inputeoutput

tables of the Finnish national economy associated with environ-mental emission and characterisation data to compute the envi-ronmental impacts. Theoretically, the model is a linear economicinputeoutput model, which is expanded with environmental data(Hendrickson et al., 2006; Suh et al., 2004). The production sectorsof the model cover the whole Finnish economy and are, by defini-tion, in accordance with the classification applied to the nationalaccount system - except for agriculture, which is disaggregated inorder to increase the resolution for a hot spot analysis. Imports aremodelled product-specifically. The classification of the productsand the logic for their aggregation to higher level sector-productsare the same as that used in the national account system. Themodel includes 912 product titles.

Disaggregation of the domestic agriculture sector was based onreference inputs and reference environmental loads obtained withthe help of a material flow based LCA model, which was built inthe study. Sub-sectors were chosen so that each of them has oneand only one product as their main product. For each sub-sector ofthe agriculture-aggregate a share of each aggregate-input andenvironmental load was allocated that corresponded to its share ofthe total of the respective reference flows. Thus, the modelincludes 190 domestic production sectors, of which 44 representagriculture.

The environmental data consists of economic-sector-specificemission data for domestic production, product-wise emissiondata for imported goods, and emission specific characterizationdata for environmental impact assessment. Most of the environ-mental data were obtained from the ENVIMAT-model. Emissiondata for the domestic agriculture-aggregates were reallocated tothe sub-sectors according to the disaggregation scheme with thehelp of a material flow based LCA model as described above. Theemission data for the domestic production sectors are based onnational emission inventories and, to a minor extent, on activityinformation based estimates (Seppälä et al., 2009). For the largestimport volumes, emission data are life cycle inventory (LCI) datagathered from relevant commercial and public databases andtransformed to monetary value specific for the ENVIMAT-model.

Y. Virtanen et al. / Journal of Cleaner Production 19 (2011) 1849e1856 1851

For the minor import volumes, emissions are estimated with therespective domestic emission factors.

The specificity and accuracy of the EIO-LCAmodel is much lowerthanwith the standard LCA approach. Themodel was accomplishedby expanding the end-use of the food-chain-products (includingmaterial products and services) with their industrial and serviceusage, and removing the end-use of non-food products from thestandard end-use of the national accounts. Sectors that use foodproducts for non-food production, such as the paper industry(starch) and cosmetics industry (sugar), were excluded from theindustrial usage. Inter-sectoral feedback was reduced from thegross usage of the industries included in the industrial usage. Therate of feedback was found to be between 0.3% of catering servicesand 15.8% of vegetables, at an average of 5.8% of the gross demand.Thus, the boundary condition vector of the model was determinedsolely by the end-use of the food-chain-products, which consists ofthe standard end-consumption batch of food products from thenational accounts, and of industrial usage, which includes theintermediate consumption of the service sector and other sectors ofthe economy that produce non-food goods as their main products.The end-use of each non-food product was set to zero in the end-use vector.

Classification of food-chain-products follows the definition offoodstuffs given in the EU foodstuff law (Regulation (EC) No 178/2002) which defines foodstuff as any substance or product inten-ded to be, or reasonably expected to be, ingested by humans.Additionally, catering services are included in food-chain-products.The number of food-chain-products in the end-use vector is 105.

2.2. Lunch plate approach

LCAs were performed on 30 different lunch portions (Saarinenet al., 2009, 2011). The investigated lunch portions followed theplate model. A balanced meal according to the plate model shouldcomprise a quarter of starch, i.e. potatoes, rice, pasta or similar,a quarter of meat, fish, poultry or pulses and half vegetables. Inaddition, a meal should include breadwith vegetable fat spread andfat-free milk or water.

Two criteria were used to ensure nutritional quality of theportions: 1) equal amounts of energy were made available and 2)shares of energy from proteins, fats and carbohydrates werematched with nutritional recommendations. According to therecommendations for young people, 13e15 years of age, theamount of energy in the plates was about 740 kcal (Anon., 2008).While lunch represents one third of daily energy intake, the serv-ings in this project were bigger than portions in the GDA (GuidelineDaily Amount) system for an adult, which is based on 2000 kcal perday. According to national recommendations, the total energyintake as protein should be 10e20%, 25e35% as fat and 50e60% ascarbohydrates (Anon., 2005).

To enhance usability of the model, we ensured that 1) theservings were familiar to the target group and 2) similar servingscould be eaten in the school dining room and at home as a home-made meal or a ready-to-eat dish. Homemade foods were based oncommon recipes, and ready-to-eat foods were based on the actualproducts of one commercial producer. School lunches, in turn, werebased on actual food consumption of one school, and consequentlythe portion size varied slightly. Therefore, results from schoollunches are not directly comparable with each other. They are notconsidered in this paper.

In order to ensure research relevance, we (1) selected diversefoodstuffs with wide-ranging environmental impacts on globalwarming and eutrophication, and (2) tried to ensure that relevantinformation on environmental impacts using the LCA approachwasrealistic.

The servings were based on omnivorous, vegetarian and vegandiets because it is well known that significant differences exist inthe environmental impacts among the main protein sources. Starchwas represented by potato, pasta, rice or barley as a side-dish orcomponent of a main dish. The salad ingredients varied fromoutdoor grown to greenhouse-grown vegetables, and the comple-mentary bread was either dark rye bread or light whole-wheatbread. The amount of bread varied from portion to portion. Theamount of vegetable spread (70% fat) on the bread was fixed at 10%of the quantity of bread. The drink comprised 2 dL of fat-free milk,or water with vegan dishes. Most of the servings are typical Finnisheveryday food. However, vegetarian and vegan dishes in this studyare overrepresented in relation to normal Finnish diets and foodconsumption.

2.2.1. Data sources of the lunch plate approachDomestic production, plant and animal products were modelled

based mainly on primary data collected during the study andprevious studies (Grönroos et al., 2006; Katajajuuri et al., 2004,2007; Katajajuuri, 2007; Usva et al., 2009a; Virtanen et al., 2007).The Finnish farming databank of ProAgria (unpublished) was themost significant data source for plant production procedures. Lifecycle data on fertilizers and lime were from the major producersYara Finland and NordKalk. This data is confidential.

Activity data for models on domestic animal production weregathered from several sources; national statistics (Tike) and thefarming databank of ProAgria (unpublished), publications (e.g.Hepola, 2008; IPCC, 2006; Leeson and Summers, 2005; Lohmann,2008; Perotto et al., 1992; Serenius et al., 2007), guidelines fromMTT (MTT, 2006) and personal communications with experts atMTT. The composition of industrial feed was in line with originaldata from the major producers and data on domestic raw materialsfor feed were from models used in this study.

Activity data on phases after agricultural production werecollected for chain actors from industry and retail. Data on theconsumer phase has been described separately in Kauppinen et al.(2010). The energy profile used for electricity and district heatingwas derived from average Finnish grid data, with the exception ofgreenhouse production where sector-specific statistics were used.

Estimation of N2O and CO2 emissions from the field as well asthe indirect N2O emissions were based on IPCC methods and data(IPCC, 2006). For the indirect N2O emissions NH3 emissions wereestimated based on models from the EEA (European EnvironmentAgency, 2006) and emissions from manure were based on Döhleret al. (2002). Nitrogen leaching, for indirect N2O emissions wasestimated with a model based on empirical Finnish leachingmeasurements made at MTT.

In the impact assessment, characterisation factors of climatechange were based on IPCC (IPCC, 2006) information.

LCI data from the EcoInvent database were used for importedproducts and raw materials. The methods applied are described indetail (in Finnish) in the final report of the study (Saarinen et al.,2011).

3. Results

3.1. EIO-LCA approach

According to the EIO-LCA approach, the food chain accounts for7% of domestic CO2 emissions, 43% of CH4 emissions, 50% of N2Oemissions, 12% of PFC emissions and 69% of NH3 emissions.Respectively, impact contribution of the Finnish food chain onclimate change was 14%, which comprises 40% CO2 emissions, 25%CH4 emissions, 1% PFC emissions, and 34% N2O emissions, of which3% stemmed from NH3 emissions.

Fig. 2. Distribution of the climate change impact of the food chain by the outputs ofdifferent groups of products.

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The life cycle stages of agriculture were predominant in thedomestic greenhouse gas loads of the food chains in Finland. Thecontribution of agriculture in terms of methane, nitrous oxide andammonia emissions exceeds 90%. The contribution of agriculture tocarbon dioxide emissions is 32%. For climate change impacts theshare of agricultural processes is 69%. The energy industrycontributes 12%, trade and transport together 6%, the food pro-cessing industry 5%, and other economic sectors together about 15%of the domestic climate change impact.

The share of imports in the greenhouse gas emissions of thefood chain varies from 21% for PFC emissions to 48% for CO2emissions. For CH4 emissions, imports contribute 27% and N2Oemissions of the imports represent 34% of the total. The share ofimports in the total climate change impact is 39%, of which 62%stems from imports of products from the agriculture and food anddrink industries, 9% from products of energy industries, 8% fromproducts of agro-inputs industries, and the remaining 21% fromimports of products from other economic sectors. The contributionof transport to climate change impact of imports is modest, only<1% of the total impact of imports. This small contribution is due tothe small scale of transportation both in delivery and in the lifecycle supply chain on average. However, data on transports isuncertain and need to be further investigated.

The shares of different end-use sectors of domestic, import andtotal climate change impact of the food chain are shown in Fig. 1.The largest share of the climate change impact of the food chain inFinland results from the output of household consumption. The lowshare of exports shows that food is a minor export activity inFinland, compared with many other countries. For example inDenmark food exports were 17% of merchandise exports in 2008, inIreland 10%, whereas in Finland the corresponding share was 2%(World Bank, 2011).

Contributions of the main product groups to the climate changeimpact of the food chain are shown in Fig. 2. The profiles of contri-bution are quite different between the domestic production and theimports of the food chain. The constitution of the domestic climatechange impact is dominatedby the outputof foodproducts.Non-foodproducts such as energy, fuels, fertilisers and other agro-inputsmakea much bigger contribution to the climate change impact of theimports than they do to domestic production. This indicates that thesupply of the utility inputs lies much on import, as for the supply ofthe food-raw materials is based mostly on the domestic production.

The total climate change impact per final unit output was foundto be highest for domestic meat products, 2.7 kg CO2 eq/euro andlowest for catering and drink services, 0.6 kg CO2 eq/euro. Therespective value for grain products was 1.8, for vegetable products1.5, and for fish 1.0. The average for the whole chain was1.3 kg CO2 eq/euro, for domestic food products 2.0 kg CO2 eq/euro(catering and drinks services not included), and for respectiveimported food products it was 1.8 kg CO2 eq/euro.

The total climate change impact for food per person per day was7.7 kg CO2 eq. Household consumption produces 4.7 kg CO2 eq of

Fig. 1. Distribution of the climate change impact of the food chain by the outputs todifferent end-use sectors.

this. This result appears to be in line with other studies. Forinstance, Girod and De Haan (2010) estimate 4.6 kg CO2 eq perperson per day for household consumption of food in Switzerland.

3.2. Lunch plate approach

The impact of a single lunch portion ranged from 0.65 kg to3.80 kg CO2 eq. That is equivalent to 2e12% of the climate changeimpact for the daily consumption of a Finnish consumer (Fig. 3).According to a very rough estimate based on the lunch plateapproach, taking into account that lunch represents a third of dailyfood consumption with respect to energy, food consumption rep-resented 15e20% of the climate change impact of the annualconsumption of an average Finnish consumer.

Impacts of vegetarian and animal-based portions differed. Inaddition to alternative protein sources, the main differences werebetween alternatives for vegetable components on a lunch plate.Beef and milkebased macaroni casserole were the most burden-some portions. Salad in this portion comprised greenhouse-grownvegetables, which increase the climate change impact significantly.The climate change impact of a broad-bean patty portion waslowest when salad in this portion comprised outdoor grownvegetables. Climate change impact of portions based on chickenand pork were around 2 kg CO2 eq. Salad in these portions was alsomade up of greenhouse-grown vegetables. Climate change impactsof a meat-based portion could be decreased by about 0.57 kg CO2 eqby changing the salad without affecting the nutritional require-ment set in the study.

Climate change impacts of ready-to-eat portions were1.63e2.35 kg CO2 eq, representing an average burden of the totalportion menu.

For an average lunch plate, including animal products, about70% of the carbon footprint originates from raw material produc-tion processes of farming. The substantial contribution of farmingto greenhouse gas emissions is in line with the results of the IOapproach. Shares of other phases of the life cycle, i.e. industry, retailand consumption differed slightly between homemade food andready-to-eat food. For homemade food the consumer phase wasemphasized, accounting for 8e16% of climate change impacts fora meat-based homemade portion, and 11e47% for a plant-protein-based homemade portion. For the ready-to-eat food the industryand retail phases were emphasized, respectively contributing25e38% towards climate change impacts associated with foodportions.

4. Discussion

4.1. Applicability to different societal needs

4.1.1. Climate policyBoth the EIO-LCA and the lunch plate approach offer some

useful insights into the issue of environmental impacts of food.

Fig. 3. Climate impacts of lunches investigated in relation to climate impact of consumption per day and per person in Finland (%) according Nissinen et al. (2007). H at the end ofthe label means homemade and C means convenience food.

Y. Virtanen et al. / Journal of Cleaner Production 19 (2011) 1849e1856 1853

Firstly, it is clear that when effective climate policies are sought,the focus should be on agriculture. However, the problems ofmanaging greenhouse gas emissions from farming and cattlehusbandry can be challenging. It is sometimes difficult to identifythe specific sources and the mechanisms of the emissions becauseof their diffuse and complex nature.

With the help of the information obtained by themodels we canpinpoint the major impact sources in terms of subsystems andenvironmental loads, and hence support environmental policyplanning. We established, for instance, that animal husbandryrepresents a major source of climate change impact for agriculturalproduction in Finland, contributing about three quarters of the totalimpact. Domestic processes are responsible for most of the impact,and sector imports make aminor contribution. Results also indicatethat within cattle husbandry beef andmilk production are themostsignificant contributors to impact, methane being the major emis-sion. The sources of methane emissions are animal metabolism andmanure management. These emissions could be reduced byimplementing policies designed to improve component processes.

Secondly, international trade also plays an important role in theclimate change impact of the food chain. The results of both themacro and micro level models highlight the relationship betweentrade and environmental impacts. They provide a disaggregatedview of the impacts by source, which helps identify the predomi-nant effects. Our findings indicate, for instance, that imports offoodstuffs are responsible for about 60% of the total climate changeimpact of all imports into the Finnish food chain. The remainder ofthe impact is attributable to energy, agro-chemicals and otherproducts used to run the chain. The results also indicate thatproduction dominates the climate change impacts for importedproducts and that the role of international transport is minimal.

This suggests that when planning policies to reduce the negativeeffects of trade on the environment the focus should be on theimpacts of foodstuff production in the producing countries.

4.1.2. Agricultural policy in terms of mitigation of climate changeKey factors that underlie the main issue of economic profit-

ability concern aspects of agricultural policy, including land use,distribution of production (Angus et al., 2009), farm productionstructure, investments, choices of energy use and self-sufficiency infarming inputs. The main emphasis has been on developing greaterchoice regarding renewable energy, which in conjunction withimproved energy efficiency, would have a direct impact on poten-tial climate change.

The high contributions of N2O and CH4 emissions to climatechange impacts of a food chain emphasise the focus on land use,farmland management and farm animals. Improving soil carboncontent improves soil structure, and better soil structuresuppresses N2O emissions. CO2 emissions could be counteredthrough improved carbon sequestration in soil maintained aspasture (Conant et al., 2001; Zeeman et al., 2010) or as forest.Decreasing meat consumption in the Finnish diet, as discussedbelow, does not mean that cattle husbandry should be abandoned.In Finland, biodiversity loss is closely linked to agriculture andforestry. Grazing of ruminants, at least as long as ruminants areallowed to pasture, could maintain endangered biotopes such asmeadows and, even more importantly, pastures that enhancecarbon sequestration. This is an example of the need to developadaptive farming strategies, and to separate national visions of foodproduction from those of food consumption.

Options regarding land use depend on regional productionstructure and investments in farming. Self-sufficiency in farm

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inputs centres on choices on energy, nutrients and animal feed. Allof these can be made into internal farm inputs depending on thestructure of farming and choices of cultivation system. Thus, agri-culture as a complex system represents a challenge, but there isgood reason to exploit EIO-LCA results in a multi-faceted approach.The EIO-LCA approach could be applied at the farm scale and theLCA approach at the product scale.

4.1.3. Corporate societal responsibility - development needs and thefood supply chain

Regulators often follow the development and initiatives of chainactors. As around 15% of the climate impacts from consumptionstem from household food purchases, there is a clear need todecrease greenhouse gas emissions at the consumption andproduction levels. At the supply chain level, voluntary research andmitigation of GHG emission by food supply chain companies are thecore of the Corporate Social Responsibility (CSR) work (Forsman-Hugg et al., 2008). Without measuring climate impacts, develop-ment efforts directed at hot spots are difficult to target. Thedescribed approach represented an ideal opportunity for seekingcontinuous and effective improvements at the wider productionnetwork level. To establish more detailed and specific supply chainimprovements, more supply chain and product-specific bottom-upapproaches should be applied rather than a statistical IO approach.

4.1.4. Responsible consumer choiceIt is known from previous research (e.g. Andersson, 2000;

Ayraamides and Fatta, 2008; Berlin, 2002; Coltro et al., 2006;Dalgaard et al., 2007; Grönroos et al., 2006; Usva et al., 2009a)that climate change impacts per kg of product (or raw food mate-rial) vary between specific vegetable products and beef products bya factor of ten to twenty.

The variation among complete, nutritionally balanced dishesranges by a factor of two to five, and is very significant. Thus thisstudy supports the previous results and conclusions that respon-sible consumers should increase their share of vegetables in thediet (Baroni et al., 2006; Carlsson-Kanyama, 1998; Carlsson-Kanyama et al., 2003; Friedl, 2007; Pimentel and Pimentel, 2003;Reijnders and Soret, 2003). However, eating is a cultural activity.Foods are not mixed randomly, but rather food combinations aretypical for certain cultural groups. Inclusion of that aspect in theenvironmental impact assessment can help us understand theimpacts of our choices more comprehensively and help us to seekalternatives and make improvements. This study should stimulatediscussion about Finnish food culture by raising such issues asseasonality and traditional choices e and partly forgotten e theways to use vegetables that grow well in a cool climate. Addition-ally, there is a need for new recipes to stimulate interest in vege-tarian and vegan cooking.

The study did not include portions composed of raw materialswith the greatest environmental burden, such as beef and rice, asthey are not often eaten as lunch in Finland. The climate impact ofsuch a portion is estimated to be in linewithmincedmeat casserolelunch (which has the greatest burden in the study) if the portionwas standardised by nutritional requirements, i.e. the amount ofbeef is reasonable. It is also estimated that rice would notremarkably increase the environmental burden of the beef and riceportion, because rice as a side-dish of the standardized portionwould not cause much more environmental impact than pasta.

On the basis of the study it can be roughly estimated that foodconsumption represents 15e20% of climate impact of the total dailyconsumption of an average Finnish consumer. One could raisea question; how much would the total climate impact of foodconsumption and the total consumption decrease if consumersadopted eating habits with the least impact on the environment.

The study cannot provide a complete answer because the actualfood consumption has not been considered. However it can beroughly estimated that, as pork and broiler are the most consumedmeat products in Finland, a maximum reduction potential ofclimate impact regarding dietary shift could be around 50%. Thatwould result in a maximum 10% reduction of the climate impact oftotal consumption.

4.1.5. Health policyRecommendations for choices in food consumption based on

climate policy are in close harmony with those for health policy. Inthe struggle against obesity, an increase in vegetable and fibre-richcomponents of the diet is recommended, and consumption ofanimal protein should be decreased from the current levelsconsumed in the western countries.

4.2. Restrictions of both approaches

The EIO-LCAmethod is a robust tool for life cycle assessment. Its‘production nodes’ are aggregates of production units. This makesthe estimates uncertain regarding production units, and conse-quently uncertain in relation to specific products. However, due tothe vast and diverse background of the data it was not practicallypossible to make quantitative estimates of uncertainty. In ourmodel, for instance, one production node aggregate represents‘Production of meat products’, which includes production units forfresh pork, poultry, lamb, beef, sausages, ham, ready-made meat-foodstuffs etc. The results for the impacts from the ‘Production ofmeat products’ thus represent the average impacts for theproduction of the various products. Consequently, the applicabilityof the method for assessing the impacts of specific products islimited by averaging. Increasing the node-resolution throughdisaggregation reduces the uncertainty of the estimates for specificproducts or product groups. In our case disaggregation of agricul-ture substantially improved the estimates for foodstuff groupsbecause agricultural production dominates food chain environ-mental impacts. Disaggregation turned out to be, however, a labo-rious exercise.

The process-based approach applied in the study was foundedon average Finnish agricultural production. It is much more accu-rate than using general data from the databases or publications, andit is very useful for generating consumer information. However, it isnot accurate enough to provide fully traceable information fromagricultural production to consumers and on which consumers canbase their choice at the product level. Consumers are not able torecognise that individual products (e.g. branded products) incertain product groups possibly have very different environmentalimpacts due to their underlying production chains. Accordingly, theuse of average data cannot provide an incentive for an individualfarmer or animal producer to improve their environmentalperformance. Activity-based data from farms would be needed tocreate such an incentive. Usva et al. (2009b) suggested a system forCertified Carbon Footprint of Products, which relies on activity-based data generation. However, such a system has not beenintroduced in Finland or elsewhere.

4.3. Methodologies in the context of carbon footprint calculations

There currently exists one British standard (PAS 2050) forcarbon footprinting. ISO 14040 and 14044 (SFS-EN ISO, 2006)standards and the International Reference Life Cycle Data System(ILCD, 2010) Handbook exist for LCA, and these can be used forcarbon footprinting. WRI & WBCSD Greenhouse Gas ProtocolProduct/Supply Chain Initiative and ISO 14067 Carbon footprint ofproducts standards are currently being worked on. Harmonisation

Y. Virtanen et al. / Journal of Cleaner Production 19 (2011) 1849e1856 1855

efforts among these standards exist, but it seems that no singleharmonised approach will be established in the coming years.Additionally, implementation of any standard can be executed indifferent ways, which might lead to significant differences betweenstudies of the same systems. This makes the situation for decision-makers even more challenging. For such reasons various nationalharmonisation initiatives for carbon footprinting of food productshave been initiated (e.g. Anon., 2009; Katajajuuri et al., submittedfor publication) as well as national and international efforts toestablish calculation rules at product category level, i.e. ProductCategory Rules (PCR) with respect to Environmental ProductDeclarations (EPD) (e.g.). From the methodological point of view,this study highlights the numerous critical LCA questions andchallenges to be addressed in national projects that aim to developharmonised best-practise carbon footprint methods and relatedtools for carbon footprinting of food products (Katajajuuri et al.,submitted for publication)

4.4. Comparison with other EE-IO approaches

The environmentally extended inputeoutput analysis (EE-IO)approach has been exploited by Tucker at al. (2009) in a multina-tional EU initiative. Wiedmann (2009) performed an extensivesurvey of single region and multiple region EE-IO assessments, thegreat majority of which focussed on greenhouse gas emissions, andthe strengths and weaknesses of the EE-IO approach. Huppes andIshikawa (2009) elaborated a 10-step method of how to combinemicro level LCA and macro level hybrid-IO into developing an eco-efficiency analysis of the production/consumption technosphere.Reijnders and Soret (2003) came to a similar conclusion as we did inthis study about the importance of human transition to a moreplant-based diet. In addition, they found that organic meatcompeted with integrated vegetables in terms of environmentalfavourability. In the USA, Weber and Matthews (2008), using theEIO-LCA approach, showed that a diet shift was much moreimportant in lowering the carbon footprint than focussing on long-distance food transportation. In the UK, Barling et al. (2008)combined self-sufficiency with natural resource restrictions andfundamentals of climate change and dietary change.

In Finland, Seppälä et al. (submitted for publication) found withtheir EE-IO model (ENVIMAT) that the imports cause 41%e44% ofthe total climate change impact of the Finnish economy. In ourstudy the respective share for the Finnish food chain was 39%. Forthe specific climate change impact of the products of animalfarming Seppälä et al. (submitted for publication) found it to be4 kg CO2 eq/euro. In our results, the figure varies from 2.1 kg CO2 eq/euro for poultry production to 4.2 kg CO2 eq/euro for beefproduction. For pig production our EIO-LCA model presents3.3 kg CO2 eq/euro. Thus the average intensity figure for theproducts of animal farming would be about the same as the oneproduced by the ENVIMAT-model. Seppälä et al. (2009) found thecontribution of the transports of imported goods to the climatechange impact to be small, less than 1%, which is of the same orderof magnitude as our result for the food chain.

Our results indicate that the contribution of the domestic goodstransport to the climate change impact for the food chain is about4%. Defra (2010b) reports about 9% contribution for all transports inthe whole food chain, including households. To some extent thedifference may be explained by the contribution of the overseastransport, which is included in Defra’s figure. The impact of thecollection by train or lorry transport before shipping in our importcountries could not be assessed in this study. In the domestic foodsector, food processing and retail is exceptionally centralized andinternal logistics of companies was most possibly underestimated.Also the system boundaries for transports are probably broader in

Defra’s report than in ours, in which energy industries or any otherlinked impact sources are not included in the transports. Never-theless, much of the difference remains unexplained, and needs tobe investigated in the future.

The results of this project have already been used in the prep-aration of the Finnish food strategy for 2030 (Anon. 2010), as for themitigation of climate change. The sustainable use of energy, landuse management and novel, competitive technologies have beenemphasized for the primary production in a similar way to earlierpublished Food 2030 and the Indicators for a Sustainable FoodSystem (Defra, 2010a, 2010b). The linkage between healthy andenvironmentally enhancive diet has also been defined in Food2030. In the UK, urban transport is also taken as indicator. What hasnot been mentioned in this study, but emphasized in the strategies,is reducing, reusing and reprocessing waste. From the results of thisstudy, we can however presume that climate impacts of primaryproduction on one hand and households on other hand forma major share of the origins of climate impacts of present foodwaste. Waste, per se, may be formed at any stage of the food chain.

5. Conclusions

This study, taking an approach frommicro andmacro level, gaveconsistent results on the environmental hot spots of the Finnishfood sector. In terms of climate protection, we have to focus onfarming, and in farming to animal production, especially rumi-nants. Of the greenhouse gases, the importance of CH4 and N2O inthe farming stage is prominent, forming two thirds of the climateimpact in animal protein based food portions. The main recom-mendations for food health issues can be combined with recom-mendations for the environmentally advantageous choice of food.In both micro and macro approaches, direct and indirect role offood transportation have to be studied more in depth, and foodwaste should be specified. For assessing the comprehensivesustainability of the food sector, other conventional categories andalso extended LCA categories must be included in the assessment.

In conclusion, we note that there appears to be growing possi-bilities to use the results from EIO-LCA approaches in the foodsector.

Acknowledgements

The results presented here are based on the Finnish studiesKETJUVASTUU and ConsEnv. We wish to acknowledge all thecompanies, ministries, and agencies involved for the financialsupport and active participation in the research.

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