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Global biodiversity loss by freshwater consumption and eutrophication from Swiss food consumption Laura Scherer, and Stephan Pfister Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b00740 • Publication Date (Web): 02 Jun 2016 Downloaded from http://pubs.acs.org on June 8, 2016
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Environmental Science & Technology
Global biodiversity loss by freshwater
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consumption and eutrophication from Swiss food
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consumption
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Laura Scherer* and Stephan Pfister
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Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland
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*
Institute of Environmental Engineering, ETH Zurich, John-von-Neumann-Weg 9, 8093 Zurich, Switzerland, phone: +41 44 632 31 72, e-mail:
[email protected] 8 9
ABSTRACT
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We investigated water-related resource use, emissions and ecosystem impacts of food
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consumed in Switzerland. To do so, we coupled LCA methodologies on freshwater
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consumption, freshwater eutrophication and the consequent local and global biodiversity
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impacts with Swiss customs data and multi-regional input-output analysis. Most of the
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resource use, emissions and impacts occur outside the national boundaries which illustrates
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the extent of environmental outsourcing facilitated by international trade. Countries that are
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severely affected by Swiss food consumption include Spain, the United States and Ecuador.
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Cocoa, coffee and almonds stood out as products with high impacts. By identifying spatial 1
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hotspots and impactful products, awareness of policy-makers as well as individual consumers
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can be raised and efforts of detailed assessments can be streamlined. However, political and
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economic constraints and the resistance by individual consumers limit the high potential of
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changes in diets and trade relations to decrease the environmental impacts of food.
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TOC ART
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KEYWORDS Biodiversity loss; Freshwater consumption; Freshwater eutrophication; Life cycle assessment (LCA); Multi-regional input-output analysis (MRIO)
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INTRODUCTION
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The world is facing the twin challenges of satisfying a growing food demand while
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reducing its impact on the environment. The global population is growing and with a
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simultaneous increase in affluence there is also a rising calorie intake per capita as well as
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diets changing towards a higher consumption of animal products. While agriculture is 2
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degrading land and water resources, an increase in food production is constrained by the same
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resources and has to compete with biofuel production. Also biodiversity is severely threatened
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by our current food production practices.1,2 Biodiversity not only contributes to the provision
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of ecosystem services to humans such as water purification, flow regulation and carbon
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storage,3 but also has an intrinsic value irrespective of its societal benefits.4 Altogether, there
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are two urgent needs: an increasing food supply and the preservation of biodiversity and
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ecosystem services.
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With advancing globalization, trade gains in importance and leads to increasing spatial
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disconnection between production and consumption.5,6 Switzerland, as many other developed
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countries, is running an ecological deficit and requires external resources from an area about
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six times larger than their own ecologically productive land to produce food, wood products
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and energy.7 More recent studies confirm that more land is occupied abroad to satisfy Swiss
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demand for crops than within its own borders.8,9 Lenzen et al.10 analysed biodiversity loss
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driven by international trade and identified Switzerland as a net importer of biodiversity
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threats and as having a biodiversity footprint that is higher abroad (132 species threats) than
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domestically (56 species threats). The biodiversity in developing countries is especially
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threatened by consumption in developed countries.
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A useful tool to link local consumption to global impacts is the coupling of life cycle
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assessment (LCA) with multi-regional input-output analysis (MRIO).6 LCA is a methodology
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to quantify the environmental impacts of products from “cradle to grave”.11 For some impact
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categories spatially explicit methods were developed, which includes water consumption and
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eutrophication as well as their impacts on biodiversity.12,13 However, the link between the
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production at one location and the consumption elsewhere is missing. MRIO can fill this gap, 3
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as it links various regions by their trade patterns.14 The aspect of water was missing in
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previous studies on Swiss trade with agricultural products.8 In contrast to most studies on
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virtual water trade that only analyse water inventories,15 this study assesses the water-related
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impacts of traded food products. Additionally, direct trade was combined with MRIO and
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FAO data to improve the results of the trade analysis.
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The study aims at estimating the biodiversity impacts caused by Swiss food consumption
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and thereby makes use of the model described above. It tests the hypothesis that Switzerland
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is heavily outsourcing biodiversity impacts9,10 and considers the impact categories water
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consumption and eutrophication due to their high significance in agricultural production. The
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products and countries with the biggest effect on biodiversity loss will be identified.
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METHODS
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Linking food products to crops and countries of origin
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A list of food items produced in, imported to and exported from Switzerland is obtained
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from the Swiss Farmers’ Union (Obrist, personal communication). In addition, the Swiss
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Customs Administration provided a more detailed list of imports into Switzerland including
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the exporting countries (Obrist, personal communication). The food items include derived
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crop products and livestock products. Life cycle inventories are only given for crops so that
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processed products have to be converted to the required crop inputs. Likewise, only direct
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trading partners are given even if they are re-exporters. Therefore some trade origins have to
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be traced back. Product conversions and trade analysis are described below.
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Derived crop products. Crop derived products such as chocolate were assigned to their
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main ingredient which is cocoa beans in this case. The major ingredient and its mass fraction
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(fmass) for all products are obtained from FAO16 and Chapagain and Hoekstra.17 In order to
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avoid double counting where the same crop can produce multiple derived products, economic
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allocation was applied by multiplying the mass of the root product (mrp) needed to produce
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the derived product with its monetary value fraction (fvalue) provided by Chapagain and
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Hoekstra:17
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mrp = mdp · fmass · fvalue (1)
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where mdp is the mass of the derived product.
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Where the above mentioned sources did not provide major ingredients, mass or value
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fractions, own assumptions were established mostly based on product derivations of similar
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products (Supporting information S1).
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Livestock products. For livestock products, the cultivation of animal feed is taken into
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account. The FAO delivers the production volume of different animal products for three
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farming systems (extensive, intensive or mixed) at the global level18 and of meat in general
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for six world regions.19 The two scales were merged to get product- and region-specific shares
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(Supporting Information S1):
f′, = f , ∙ f , / f, f, = f′, /
f′,
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where fsystem,i indicates the fraction of the farming system i (extensive, intensive or mixed)
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for each product in the region, fproduct,i is the product-specific share of the farming system at
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the global scale, fregion,i is the region-specific share of the farming system for meat and fglobal,i 5
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is the global share of the farming system for meat. The animal feeding operation is not distinguished beyond the three farming systems.
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Specifically reported proportions were assumed for Swiss livestock production which
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involves more extensive farming systems than the global average.20 The fraction of
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concentrate feed (fconcentrate) for different animal products, farming systems and 10 world
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regions is obtained from Mekonnen and Hoekstra.21 The remaining feed is roughage and is
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assumed to consist of either mixed grass, alfalfa, clover or grass (not else specified; nes) from
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the country where the animal product was produced. Mekonnen and Hoekstra21 also provide
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feed conversion efficiencies (FCE) for the same categories which enables one to translate the
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feed mass into weight of carcass, milk and eggs. The concentrate feed is composed of nine
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crops (neglecting fish meal and peas) which differ in their fractions (ffeed) according to three
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animal categories (dairy and beef cattle, pigs and poultry) and six world regions22 although in
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reality the composition might differ from country to country or even farm to farm. The mass
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of feed (mfeed) for one of the concentrate feed crops is calculated as:
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m = m ∙ ∑ f, ∙ FCE ∙ f , ∙ f (2)
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and for roughage as:
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m = m ∙ ∑ f, ∙ FCE ∙ #1 − f , & (3)
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where mfeed is the mass of one of the feed crops (e.g. maize), mrp is the mass of the root
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product (e.g. milk) calculated using equation 1.
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Aquatic animal products such as fish are assumed to only cause impacts on freshwater
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resources when they originate from aquaculture in contrast to wild fisheries. The respective
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global fraction is provided by the FAO23 for different products. Fishes are assumed to be fed
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by the same concentrate feed as poultry, but with 65% of the feed conversion efficiency.24 6
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m = m ∙ f' ∙ FCE ∙ f (4)
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Trade analysis. Exports were proportionally subtracted from Swiss production and
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imports. With regards to imported food, the exporting country is not always the producer
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(trade origin A, Figure 1). For instance, Switzerland imports cocoa from Germany, but
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Germany does not cultivate cocoa. Therefore the concerned products are traced back to the
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trade origin (B, Figure 1) using EXIOBASE14 for multi-regional input-output analysis. In
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order to conform to the EXIOBASE data, 343 food items from 194 countries are aggregated
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to 14 food cultivation and 11 food processing industries (Supporting information S1) and 47
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regions (excluding Switzerland). The structural matrix (A) of the economy as available in
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EXIOBASE was inverted25 and multiplied with the Swiss food imports (FI) to result in the
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crop production (CP) required to satisfy the demand for imports:
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CP = (I – A)-1 ·FI (5)
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where A is a square matrix with 1175 rows and columns representing industry-region
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combinations, I is an identity matrix with the same dimensions as A and FI is a vector of
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length 1175. The demand was assigned to the food processing industries, while the crop
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production was taken from the food cultivation industries. The concentrate feed of animal
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products was traced back in the same way, but for each country separately, whereas roughage
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was always assumed to be from the country where the product is produced. Information on
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Swiss feed production is not contained in our databases and was estimated as the difference
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between feed demand and feed imports.
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The food industries and regions were disaggregated to food items and countries. For food
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items the same proportions were assumed as for the corresponding industries; however, some
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of the industries are very broad such as “vegetables, fruit and nuts”. For countries the export 7
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shares26 of producing countries of the food items within a region were considered (trade
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origin C, Figure 1) and where these data were missing production shares26 were used instead
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(trade origin D, Figure 1). For ~19% of the crops where some crop-country combinations are
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invalid, production data had to be used.
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Life cycle assessment
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Freshwater consumption. Crops consume blue water (irrigation water from surface or
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groundwater resources) and green water (precipitation or soil moisture). Since green water is
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only available to plants occupying the land and cannot be transferred to other locations or
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used for non-agricultural purposes, it can be considered a land rather than water use impact.27
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Therefore we only consider impacts of blue water consumption in this study. Blue water
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consumption is given for 160 crops from 160 countries.28,29 We distinguish expected water
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consumption, which represents the geometric mean of full and deficit water consumption
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(variant V1), from deficit water consumption (V2), which represents a minimum estimate.
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Especially for trees in tropical regions such as cocoa, the minimum estimate might be more
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representative.29 If not otherwise specified, expected values (V1) were taken.
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For roughage, we assumed either deficit irrigation (V1) or no irrigation (V2), assuming that
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the grass is often from non-irrigated pastures and expected irrigation would therefore
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overestimate blue water consumption. If neither of the roughage alternatives was produced as
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a crop in the corresponding country, blue water consumption of roughage was also set to zero.
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Water consumption is translated to impacts on biodiversity by characterisation factors
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relating it to precipitation, net primary production and its fraction that is limited by water
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availability. It is expressed as potentially disappeared fraction of species (unit: PDF m2 a / 8
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m3).12 Water consumption and the characterisation factors are both weighted by national crop
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production. Global biodiversity loss additionally considers endemic species richness30 and
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total land area. It is expressed in global PDF (unit: gPDF a / m3) and the data was provided by
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Verones et al.31
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Besides impacts on biodiversity, water scarcity footprints as the product of water consumption and water scarcity indices32 were also investigated (Supporting information S3).
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Freshwater eutrophication. Eutrophication describes the phenomenon of increased faunal
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mortality as a consequence of an over-enrichment of nutrients in the aquatic environment and
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the subsequent oxygen depletion. Freshwater eutrophication is mainly driven by excessive
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emissions of phosphorus. Crop- and country-specific phosphorus emissions are obtained from
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Scherer and Pfister.13 The emissions arise from mobilisation of soil phosphorus by erosion
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and of phosphorus contained in fertilizers by surface runoff, drainage and groundwater
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leaching.
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The emissions are translated to biodiversity impacts by its residence time in freshwater
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bodies (fate factor)33 and a typical effect factor of 200 PDF m3 a / kg P.33,34 Methods to assess
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global biodiversity loss from phosphorus emissions are not yet available. The unit of local
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biodiversity impacts from phosphorus were converted to match that for water consumption
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and enables aggregating the impacts from both categories. We used a conversion factor of
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6.25 PDF m3 a / PDF m2 a, which was derived from the average depth of freshwater
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ecosystems and the ratio of global freshwater volume to global land area.35
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Missing inventories. Some products have been disregarded because i) they could not be
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assigned to any crop for which inventories are given and the inventories are assumed to be
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negligible (popcorn, mushrooms, honey, yeast, vinegar, salt) or ii) their major ingredient was 9
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unknown (infant food, food preparations). These products amount to ~1% of the consumed
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food by mass.
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For some exporting countries listed in the Swiss customs data, water consumption data is
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not provided, as they are not cultivating the crops. It is assumed to equal nearby or associated
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countries. For example, Solomon Islands are assigned to Papua New Guinea and Taiwan to
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China.
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Inventories are also not provided for all crops that are cultivated in Switzerland. For those
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products, the average of the inventories in Germany, Austria, France and Italy was assumed
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and water consumption was scaled with the aridity index36 to take into account that a more
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humid climate generally requires less irrigation. Some products could still not be quantified.
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Therefore, the water consumption of root (nes) was assumed to equal that of potatoes and for
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eggplants, garlic and raspberries values of other nearby countries were taken.
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Sensitivity analysis
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We investigated the effect of not tracing back crop origins, but instead always assuming
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that the crop is grown where the product is imported from (trade origin E, Figure 1). Since
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inventories are not given for countries which do not produce a specific crop, the values of the
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nearest country were assumed. If the nearest producing country was more than 1000 km away
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from the exporting country, the average of the three nearest countries was assumed. Water
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consumption was again scaled with the aridity index.36 For the biodiversity characterization
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factors, country averages were taken. As an alternative sensitivity analysis, the major
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producing exporter (trade origin F, Figure 1), or if unavailable the major producer, was
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assumed as trade origin (G, Figure 1). As mentioned above, for ~19% of the crops where
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some crop-country combinations are invalid production data had to be used.
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RESULTS
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Trade analysis
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Switzerland produced 4.8 Mt of food, imported 5.0 Mt and exported 2.8 Mt in 2012. The
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country is a net food importer, although about half of the food consumed is produced
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domestically (49%). Almost half of the mass of imported food comes from its four
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neighbouring countries Italy, Germany, France and Austria, but Brazil also exports many
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products to Switzerland (Supporting information S2). Switzerland imports a variety of
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products, but above all beverages and wheat (Supporting information S2).
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Over 40% of the product-country combinations of imported food were traced back because
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the exporting country does not produce the food. For instance, Switzerland imports cocoa
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from Germany which, in turn, imports “crops nec” (not else classified, equivalent to not else
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specified), to which cocoa but also coffee and pulses (excluding soya beans) belong, mainly
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from Brazil, Rest of the World (RoW) America and RoW Africa based on EXIOBASE,
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which, based on FAO data, results in Brazil, Ecuador and Ivory Coast as being the biggest
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cocoa exporters to Germany. The implications of the biodiversity impacts due to different
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trade origins are discussed in the following sections.
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Freshwater consumption and eutrophication
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The production of food consumed in Switzerland required almost 1400 million m3 of blue
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water (