Environmental Impacts and Hotspots of Food Losses: Value Chain

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Environmental Impacts and Hotspots of Food Losses: Value Chain Analysis of Swiss Food Consumption Claudio Beretta, Matthias Stucki, and Stefanie Hellweg Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b06179 • Publication Date (Web): 01 Sep 2017 Downloaded from http://pubs.acs.org on September 4, 2017

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Environmental Science & Technology

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Environmental Impacts and Hotspots of Food

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Losses: Value Chain Analysis of Swiss Food

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Consumption

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Claudio Beretta a*, Matthias Stucki b, Stefanie Hellweg a

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a

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(Switzerland)

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b

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Wädenswil (Switzerland)

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*Corresponding author. Tel.: +41 44 633 69 69; Fax: +41 44 633 15 79; e-mail address:

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ETH Zurich, Institute of Environmental Engineering, John-von-Neumann-Weg 9, 8093 Zurich

ZHAW Wädenswil, Life Sciences und Facility Management, Einsiedlerstrasse 29, 8820

[email protected].

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KEYWORDS

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Life Cycle Assessment, Food Losses, Food loss Prevention, Food Loss Treatment

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ABSTRACT

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Reducing food losses and waste is crucial to making our food system more efficient and

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sustainable. This is the first paper that quantifies the environmental impacts of food waste by

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distinguishing the various stages of the food value chain, 33 food categories that represent the

ACS Paragon Plus Environment

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whole food basket in Switzerland, and including food waste treatment. Environmental impacts

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are expressed in terms of climate change and biodiversity impacts due to water and land use.

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Climate change impacts of food waste are highest for fresh vegetables, due to the large amounts

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wasted, while the specific impact per kg is largest for beef. Biodiversity impacts are mainly

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caused by cocoa and coffee (16% of total) and by beef (12%). Food waste at the end of the food

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value chain (households and food services) causes almost 60% of the total climate impacts of

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food waste, because of the large quantities lost at this stage and the higher accumulated impacts

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per kg of product. The net environmental benefits from food waste treatment are only 5-10% of

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the impacts from production and supply of the wasted food. Thus, avoiding food waste should be

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a first-line priority, while optimizing the method of treatment is less relevant.

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INTRODUCTION

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Twenty to thirty percent of the environmental impacts of an individual’s consumption are caused

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by food.1 At the same time, approximately one third of all food produced for human

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consumption is lost or wasted.2 According to Ceren et al.3 the amount of avoidable food waste

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and losses (FW) is growing globally, with non-CO2 greenhouse gas (GHG) emissions (CH4,

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N2O) having increased by more than 3 times from 1965 to 2010. The ongoing expansion of

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cropland and pastures, that is driven by FW among other things, is a primary source of

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ecosystem degradation and biodiversity loss (e.g. Donald and Evans4). With respect to climate

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change, not only agricultural production, but also emissions from consumer transport of

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purchased food and consumer preparation can have a large impact on overall results.5 Therefore,

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it is relevant to know at which stage of the food value chain (FVC) the food is wasted.6


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The direct global economic cost of total FW is about USD 1 trillion each year. In addition,

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environmental costs reach around USD 700 billion and social costs around USD 900 billion.7 As

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negative environmental, social and economic impacts of FW are becoming more apparent,

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tackling the problem of FW is increasingly crucial to achieve more sustainable consumption.8

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In recent years several countries have attempted to quantify FW at different levels of the FVC.

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Recent studies for FW quantification have been done in Austria9, Germany10, the UK11 for the

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household level and in Norway for the whole FVC.12, 13 In Switzerland we analyzed FW across

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the whole FVC in 2012, based on primary data from 43 companies and institutions and data from

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literature.14

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The FAO quantified the carbon footprint of the production of wasted food at 700 kg CO2-

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eq/cap/a on a continental and global level, without benefits from FW treatment.7 Scherhaufer et

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al.15 estimate the environmental impacts of FW with LCA at the EU level. These studies

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identify environmental data on a product category level and data on recovery and disposal

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options for FW, especially for the valorization as animal feed, to be relevant data gaps for further

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research.

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A study analyzing the environmental impacts of FW over the whole FVC that distinguishes

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the stages of the FVC, detailed food categories, and includes FW treatment, is still lacking in

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literature. Therefore, the goal of the present paper is to update the mass flow analysis by Beretta

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et al.14, to complement it with an environmental assessment of the complete FVC (agriculture,

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trade, processing, retail, food services, households) and FW recovery and treatment, and to

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compare the results with literature (supplementary information [SI] 12). This helps to identify the


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most relevant FW flows, as a basis to develop effective measures to lower the impact of FW in

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the future.

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METHODS

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Definition of food waste. In this paper FW refers to food which is originally produced for

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human consumption but then directed to either a non-food use or waste disposal. In contrast to

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the FUSIONS definitional framework16, food diverted to animal feeding is included due to its

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environmental relevance (the production of the food is usually more environmentally relevant

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than the production of the feed which can be substituted). Unavoidable FW, which cannot be

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avoided with realistic efforts and current technologies (e.g. losses from cleaning production lines

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using best practice methods) or which consists of inedible parts of food (bones, shells, peels,

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residues), is per definition not considered in the potential of food waste prevention (more details

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in the definitions in the SI).

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Modeling the food value chain. In order to quantify the environmental impacts of FW and to

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compare them with the impacts of food consumption, we created a model of the whole Swiss

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food value chain (FVC), covering agricultural production (including fishery), trade, processing,

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retail, the food service sector, private households, and FW disposal.

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The first part of the model consists of a mass and energy flow analysis of all the food that is

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consumed in Switzerland. This approach covers FW in foreign agricultural production of

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imported products and excludes Swiss FW related to exports, with the advantage that the per

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capita results can be compared with other countries without distortion between net importing and

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net exporting countries.17 The mass flow analysis (MFA) of Beretta et al.14 was updated,

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integrating recent literature and distinguishing 33 instead of only 28 food categories (SI 1.1)


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because of substantial differences in environmental impacts and FW amounts between these

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additional categories (exotic/citrus table fruits and juices, legumes, nuts/seeds/oleiferous fruits,

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cocoa/coffee/tea). Major updates related to FW in agricultural production of exotic fruits, in

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milk, dairy, and cereal processing, in the FVC of potatoes, in the retail and the food service

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sector, and the mass flows for FW treatment (SI 1.2). The reference period for food consumption

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is 2011-2012.

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The second part of the model consists of a life cycle assessment (LCA) of the FVC and FW

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treatment, using the software Simapro 8.218 and additional Excel calculations for the assessment

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of land and water use impacts. We use attributional LCA because of our primary goal to quantify

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the present environmental impacts of FW and to identify current environmental hotspots of FW.

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We mainly base our life cycle inventories (LCI) on the LCA databases ecoinvent 3.2

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“allocation recycled content” (www.ecoinvent.org), World Food LCA Database 3.019, Agri

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Footprint 2015 (www.agri-footprint.com), AGRIBALYSE v1.2 (www.ademe.fr), a food inventory

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collaboration with ZHAW and Eaternity20, 21, and data from the Swiss Federal Office of Energy

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SFOE.22 The World Food LCA Database, which includes datasets not yet published in ecoinvent

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3.3, and AGRIBALYSE are linked to the ecoinvent 2 database, which may provide some

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inconsistency. However, the differences between ecoinvent v2 and v3.2 “recycled content” are

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irrelevant for most agricultural products.23 For agricultural food production, most LCA

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datasets listed in SI 3.1 are used in their original version, however some are modified according

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to the methodology documented in the subsequent sections and the SI. Land occupation data is

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taken from Pfister et al.24 for food crops and animal feed. For animal products, pasture and crop

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land occupation is calculated based on Scherer and Pfister25 Blue water consumption (irrigation

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water from surface or groundwater resources) is based on Pfister et al.24 and Pfister and Bayer26.


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Water use (34 l/kg) and electricity consumption (18.8 MJ/kg) in food services are estimated

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based on data from SV Group27, and include cooking, cooling, ventilation, lighting, and cleaning

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based on measurements in 15 gastronomic businesses. The numbers tend to be over-estimated,

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since total electricity and water use (including cafeteria, production of snacks, desserts etc.) are

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allocated to the main meals only. The average portion of main meals is estimated at 500g.28 The

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transport distances are also based on estimations from SV Group, where half of the food is

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delivered by the main supplier over an average distance of 90 km by a chilled 18t lorry and the

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rest by local suppliers over an estimated distance of 45 km by 3.5-8t lorry, half of it as chilled

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transport.28 Load factors are taken from ecoinvent 3.2 and the World Food LCA Database 3.0.

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Electricity consumption at household level is based on a survey among 1200 Swiss households,

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analysing cooking, baking, refrigerating, freezing, and dish washing.29 As a simplification, the

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minority of Swiss households that cook with gas or wood is not modeled separately.

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Infrastructure is not included, since it was found not to be relevant in the mentioned household

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activities.19 The main four means of transport for shopping (car, bus, tram, bicycle) are modeled,

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covering 89% of the shopping tours. The remaining 11% is done by foot, train, motorcycle, and

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others. The distances are based on data from the Swiss Federal Statistical Office.30 Half of all the

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rides for shopping are assumed to be done for food purchases and allocated to food products

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proportionally to mass. The resulting shopping distances are 1.1 km/kg of food by car, 0.14

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km/kg by bus and tram, each, and 0.03 km/kg by bicycle (SI 3.2.3). The methodology and

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assumptions for the life cycle assessment in transport, the processing industry, and in retail

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are described in SI 3.2.

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The inventory of FW treatment is mainly based on ecoinvent 3.231 and LCA datasets published

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by the SFOE

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, which are adapted to individual food categories. We apply system expansion


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(avoided burden approach) for useful co-products of FW treatment. As reference systems for the

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substitution, we use the Swiss electricity consumption mix, heat from natural gas, fertilizer

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(inorganic nitrogen [N], phosphorus [P], and potassium [K]), peat (improved soil effect), and

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animal feed for swine. The substitution of forage is modeled with an optimization tool defining

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an optimal feed mixture of barley, wheat, soy grits, phosphate, and lysine supplements.33 For

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incineration we assume average electric and thermal efficiency of Swiss incineration plants, for

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anaerobic digestion we model the biogas yield and then calculate the electricity and heat output

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according to typical Swiss facilities. Individual food categories are differentiated based on

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energy and water content. For anaerobic digestion and composting, inorganic fertilizer is

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substituted based on the content and the utilization rates of N, P, and K for compost, liquid, and

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solid digestate. The improved soil effect is quantified with peat substitution in growth media

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based on typical compost densities. Peat and fertilizer substitution in private gardens is based on

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surveys reporting utilization and replacement rates.34, 35 As a simplification, FW arising in the

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FVC of imported products is assumed to be treated equally to FW arising in Switzerland. Since

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the corresponding processes are of minor relevance for the overall results, this simplification was

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deemed acceptable. The contribution of different components of FW treatment (e.g. substitution

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of heat, energy, peat, heavy metal emissions, etc.) to the environmental impacts and benefits of

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different FW treatment options (composting, anaerobic digestion, feeding) is documented in the

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SI 4.3.

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Allocation of environmental impacts to food consumption and losses. A part of the

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environmental impacts of agricultural food production is allocated economically to by-products

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(e.g. leather, fish bycatch, bonemeal fed to animals). The other impacts and the impacts of the

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supply of food and the treatment of the unavoidable FW are then attributed to consumption and


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losses proportionally to the metabolizable energy of the consumed food and avoidable FW. The

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impacts and benefits of the treatment of the avoidable FW are fully allocated to the losses since

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they would be avoided with FW prevention (SI 2.2).

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Metabolisable energy is a relatively good, simple measure for the original nutritional value of

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wasted food and for how much food can be substituted by avoiding FW (avoided burden

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approach). Economic allocation would not be appropriate in the case of FW, because FW does

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not have market prices reflecting its potential value for consumers. We assume that the wasted

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products originate from the same mix of countries as the consumed products within a food

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category. The impacts attributed to FW depend on the stage of the FVC where the food is lost,

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since the impacts of the upstream FVC up to the point where the wasted food is accounted for, in

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addition to the impacts of the treatment, and the credits from substituted products (fertilizer,

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animal feed, etc.) are attributed to the losses (SI 2.2).

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Life cycle impact assessment (LCIA). The LCA is completed for climate change impacts with

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the methods global warming potential 100a36 and global temperature change potential 100a37,

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and for the regionalized land and water impacts on biodiversity. Biodiversity loss was assessed

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here because it is the planetary boundary most exceeded38 and because land and water use are

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primary drivers of biodiversity loss.39 Agricultural activities for producing food are the

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dominating driver of both land- and water-use impacts40, and, hence, these impacts are essential

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to assess in the context of FW. In choosing these indicators, we also follow the recent global

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guidance document of the UNEP-SETAC Life Cycle Initiative on Life Cycle Impact

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Assessment37 for two of the indicators used in this study (climate change according to IPCC36

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and land-occupation biodiversity impacts according to Chaudhary et al.41, using the updated

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country-aggregated characterization factors published in Frischknecht et al.37). For Water


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consumption we deviated from these guidelines in order to be able to use a method that is

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compatible to the land-use assessment26, 25 and to keep the discussion to two main indicators. In

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the Supporting Material we additionally provide the LCIA results for eutrophication, which is

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also an important category for agricultural products, as well as the aggregated LCIA scores

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according to the method Recipe42 and Method of Ecological Scarcity43 (SI 4.1). Global

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biodiversity loss considers endemic species richness and is expressed in global potentially

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disappeared fraction of species (gPDF).41, 37

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RESULTS AND DISCUSSION

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Overview of the life cycle impacts of Swiss food consumption and losses. Figure 1 shows

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GHG impacts of Swiss food consumption. The vertical flows on the top represent the impacts

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arising at the various stages of the FVC, the flows at the bottom the net environmental benefits of

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FW treatment, considering credits from the substitution of resources and energy (forage,

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fertilizer, electricity, heat, improved soil effect). The horizontal flows visualize the cumulated

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impacts of the upstream processes of the FVC, including FW treatment. The attribution to

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consumption (green) and waste (red) is based on the metabolizable energy content of the food

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and the avoidable FW. The results show that the agricultural production of an average Swiss

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consumer’s food basket (SI 1.1) represents the most relevant stage of the FVC. The second

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largest impact fraction is caused by households (66% of the GHG are from car rides for

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shopping, only 6% from public transport for shopping and 28% from electricity consumption for

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refrigeration, cooking, and dish washing). The trade and the processing industry cause similar

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total emissions as households. Food services and retail cause ~10% of emissions compared to


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agricultural production. More than half of the net environmental benefits of the treatment of

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avoidable FW are coming from feeding, 30% from anaerobic digestion, 8% from composting

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(fertilizer and peat substitution), and the rest mainly from incineration. The total impacts of

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consumed food, including consumption in households and food services and food donations,

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amount to 1.5 t CO2-eq, the net impacts of FW to 0.49 t CO2-eq. In household food consumption

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15% of the emissions are caused by FW at household level, 10% by FW at the previous stages of

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the FVC, and 75% by actual food consumption. In food services, the respective numbers are

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12%, 9%, and 79%. Food donation institutions save food with value chain impacts of 2 kg CO2-

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eq/cap/a. For the storage and distribution of food they emit 0.2 kg CO2-eq/cap/a (8% of the saved

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emissions) (Figure 1).

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Figure 1. GHG impacts of Swiss food consumption, including the production and treatment of avoidable and unavoidable FW. The size of the arrows is proportional to the impact; however, small flows are highlighted with a black line for better visibility.


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Figure 2. Share of FW and final consumption (a) and share of FW arising at the various stages of the FVC (b) in terms of mass, metabolizable energy, and impacts on climate change and global biodiversity.

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In terms of climate change the FW related emissions are estimated to be 25% of the total

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emissions of consumed food. The share is lower than for energy (34%) and for mass (37%)

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(Figure 2), because products with a high GHG impact per kg of food (e.g. animal products) tend

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to be wasted less than average. In terms of biodiversity, the share of impacts caused by FW is

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similar as in terms of GHG (28%).

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When analysing the importance of FVC stages, the GHG contribution of FW caused by

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households (51%) and food services (8% of total FW) is higher than in terms of energy (39%,

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6%) and mass (36%, 4%). The main reason is the cumulation of impacts along the FVC. The

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losses in the processing industry are highest in terms of energy (34%), whereas in terms of GHG

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they only make up 17%. This means that the losses are environmentally less relevant than

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average losses (Figure 2); notably cereals declassified for animal feeding have relatively high

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calorific values, but low environmental impacts per kg due to substitution effects. Regarding

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biodiversity most impacts are caused in agricultural production, since land and water use are


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relatively low in the later stages of the FVC. This explains why the early stages of the FVC cause

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higher and the later stages lower impact shares than in terms of GHG.

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Hotspots of environmental relevance. If different product categories are compared, the major

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GHG emissions [GWP 100a, IPCC36] attributed to the average FW of Swiss consumers are

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caused by fresh vegetables (mainly tomatoes, cucumbers, and lettuce), dairy products, beef and

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pork, and bread and pastries (Figure 3a; the horizontal red lines show the net GHG impacts of

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production, supply, and treatment for food categories with treatment savings of more than 1 kg

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of CO2-eq/cap/a). However, the emissions per kg of FW are highest for beef, chocolate and

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coffee, and animal products in general (Figure 3b). The high relevance of vegetable, bread, and

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dairy waste is therefore mainly caused by high FW amounts (high FW rates as illustrated in

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Figure 3c combined with large amounts consumed), whereas the relevance of beef is mainly

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caused by high impacts per kg (relatively low FW rate in Figure 3c). Graph a) in Figure 3 also

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shows that the food losses with the highest impacts are arising in households (red) for most food

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categories. Exceptions are cheese (whey losses in processing), fresh vegetables (over-production

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and sorting by cosmetic norms in agricultural production), and breads and pastries (cereals

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declassified for animal feeding). The relatively high impacts from losses in the processing of oils

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and fats are uncertain since they are based on estimations of average oil crop losses in Europe.2

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The treatment of FW leads to net GHG savings in all food categories. However, they are low

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compared to the impacts allocated to the production and supply of the food that is wasted (Figure

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3a; note that the negative and positive vertical axes are not scaled equally). Only in the case of

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cereals the substitution of feed can save a relevant amount of emissions (about 90% of the

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climate impacts of agricultural production of the cereals that are fed to animals, illustrated with

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the negative bar in Figure 3a). The reason is that the production of bread cereals only has about


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10% higher GHG impacts than the production of the modeled, substituted feed (barley and soy

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grits; details in SI 3.3.6). In the case of whey used for animal feeding the environmental benefits

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from feed substitution are also relevant, especially if fed to calves and shoats instead of swine

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(illustrated with a shaded bar in Figure 3a) because of the specific protein composition of

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whey44. Figure 3b shows that the specific GHG emissions per kg of FW vary more between food

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categories than between the stages of the FVC where they arize. Generally, they increase along

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the FVC because of the accumulation of impacts. However, for fish the FW impacts in

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processing are lower than in agricultural production because of the credits for feeding fish to

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animals (Figure 3b). If the environmental impacts are analyzed per kcal of FW, fresh and other

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vegetables and exotic fruits become more relevant than in the per-kg-perspective, since they have

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a relatively low calorific content (SI 7.1.1). In Figure 3b we show the per-kg-perspective since it

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may be easier to perceive the mass of FW than its calorific content. Figure 3c shows the amount

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of losses relative to the consumed food. The loss rate of vegetal oils, processed vegetables, and

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of nuts and seeds is lower in terms of energy than in terms of mass because of losses before

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processing (lower calorific content), in the dairy industry because whey and buttermilk have

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lower calorific contents than cheese and butter.


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a)

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kg CO2-eq/cap/a plant products: 253

production and supply of food waste

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meat & fish: 121

124 120 100

90 whey fed to calves and shoats

80

72

53

60 44

35

40

29 21

20

20

15

19

18

-0.4 -0.1

-3

-1.7

-3.9

-0.4 -0.7 -3.8

-1.7 -3.1

18

16

8.5

7.8 6.5 6.2 7.5 5.2 3.0 3.0 2.2 1.7 0.4 0.1

20

food waste treatment

dairy & eggs: 120

-1.0 -0.6 -0.8 -0.5 -0.1 -0.0 0.0

-0.1 -0.2 -0.4 -0.5 -0.1 -0.4 -3.7

-8

-6.9

-13 -14

-18 -23

kg CO2-eq/kg of food waste

b) kg CO2-eq/kg of food waste

150 100 50 150 00 100 50

25 25 20 15

21 21.3

9.5

10 9.5

10.0 3.3 3.3

3.2 3.2 1.8 1.7 1.2 0.7 0.5 1.7 1.8 0.9 12.7

97%

6.2

94%

107%

4.9 2.9 2.6 2.5 2.4 2.6 2.4 18% 31% 29% 29% 0.4 0.1 18% 11% 18% 23% 14%

5 3.2 3.2 5 2.2 1.6 1.2 1.1 0.9 0.9 0.7 0.6 3.2 0.9 1.0 2.2 g CO2-eq/kcal of food waste 1.2 0.9 1.0 1.2 1.6 0.6 0.7 0.9 1.1 0.6 0.6 0.5 0.7 0 0 c) % of14consumption by mass 200% 11.6 12 181% by energy 180% 10 160% 137% 130% 128% 140% 8 120% 88% 6 100% 4.6 73% 76% 80% 3.4 66% 4 64% 67% 65% 2.7 60% 38% 1.2 1.2 1.3 1.2 2 40% 19% 0.4 0.5 0.9 0.3 0.2 0.3 16% 20% 0 0%

6.9

6.9 6.0 6.0

53%

10 10

Agricultural Production Agricultural Production Trade Trade Processing Processing Food Service Food Service Retail Retail Households Households

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Figure 3. a) GHG emissions (GWP 100) per person and year caused by the production and supply of food that is wasted at the various stages of the FVC and GHG savings from FW treatment. b) GHG emissions per kg of FW from the production, supply, and treatment of food, including credits for FW treatment. The results are shown for food wasted in agricultural production, the processing industry, and in households. c) Relative FW amounts compared to final consumption (=100%) by mass and energy. The corresponding results for global temperature change (GTP 100) are shown in Fig. S27 in the SI.

276 277

Regarding biodiversity impacts the results show that cocoa waste from Swiss consumption in

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2012 has the highest impacts on global biodiversity with about 26x10-7 gPDF-eq*a (16% of

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total FW impact), even though the food loss estimates are relatively low with 600 g/p/a (0.18%

280

of total FW) (Figure 4). A reason for the high impacts of cocoa is the relatively low yield of 40

281

g/m2/a and the provenance from tropical areas with high endemic species richness. Other

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relevant food categories are beef, wheat, coffee, grapes, and sunflowers each contributing 4 -

283

11% to total FW impacts. The biodiversity impacts from water use are generally lower than for

284

land use, with almonds, grapes, and olives being the top contributors (Figure 4).

10^-7 gPDF-eq*a 30 16%

25 20 15 10 5

Biodiversity impacts from water use

11%

Biodiversity impacts from land use 7.3% 7.2% 4.9% 4.0% 3.7% 3.5% 3.5% 2.8% 2.4% 2.1% 1.8%

1.5% 1.4%

0

285


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Figure 4. Global biodiversity impacts of the top 15 products contributing to land and water use of total Swiss food losses, with respective shares of the total FW impacts.

289

Regionalized impacts. In contrast to GHG emissions, the environmental impacts of land and

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water use depend on the location. Figure 5b) shows the share of imported products for total FW

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(42% by mass and 47% by energy). Regarding land occupation, 66% of the area and 79% of the

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biodiversity impacts are occurring outside Switzerland. Similarly, for water consumption and the

293

related impacts on biodiversity, the vast majority of impacts in agricultural production is taking

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place in countries exporting food to Switzerland (>90%). For water use the main reason is that

295

water scarcity is low in Switzerland and small amounts of irrigation water from surface or

296

groundwater resources are consumed. For biodiversity the number of endemic species is low in

297

Switzerland compared to many countries that export food products to Switzerland.

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Figure 5. Share of the amounts (mass and energy) and the environmental impacts (land use, blue

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water use, biodiversity) of domestically produced a) food consumed and b) FW occurring in

302

Switzerland.

303 304

Data quality and sensitivities. The data quality of the rates of FW for all food categories has

305

been extensively characterized in Beretta et al.14, following a pedigree approach.45 FW rates in

306

the agricultural production of cereals, sugar, eggs, and canned fruits were identified as

307

particularly uncertain.14 With regard to the composition of the food basket, the most sensitive

308

food categories with regard to climate change impacts (GWP 100 and GTP 100) can be seen in

309

Figure 3b and SI, with beef, pork, and coffee and cocoa being most sensitive. The uncertainty of

310

the life cycle inventory of agricultural products is analyzed in section 11 in the SI with a

311

pedigree approach. The results are presented in SI 17 and show that most datasets are appropriate

312

in terms of geographical correlation, reliability, and product specifications in order to describe

313

the food categories of the Swiss food basket; major uncertainties are related to the agricultural

314

production of rice, berries, and exotic and citrus fruits. The uncertainties in the biodiversity

315

assessment methods are reported with confidence intervals by Chaudhary et al.41. Further

316

uncertainties of the analysis are discussed in SI 11.3.

317

Indirect effects of behavioural changes. The environmental effects allocated to FW in this

318

study reflect the direct potential savings of FW prevention, i.e. the benefits of producing less

319

food, of treating less FW, and the impacts of replacing the recovered co-products from FW.

320

However, the indirect effects of related consumers’ changed behaviour are not included.

321

Preventing FW can potentially have five consequences: (I) buying less food and spending the

322

saved money on alternative products and services with an additional impact, (II) spending the


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323

money on more expensive food, (III) donating the saved money, (IV) reducing income by

324

working less or saving the money, or (V) eating more food. According to Martinez-Sanchez et

325

al.46 the rebound effects of FW prevention may be highly relevant, depending on the type of

326

activity on which the money saved is spent. Salemdeeb et al.47 estimate that rebound effects may

327

reduce GHG savings from FW prevention by up to 60%. Therefore, a holistic approach is needed

328

when developing FW prevention policies in order to mitigate rebound effects.47

329

Comparison with literature. This study represents the first detailed environmental assessment

330

of the complete FVC of Swiss food consumption, focussing particularly on FW. However, in

331

other countries several previous studies on MFA/EFA or on the environmental assessment of

332

parts of the FVC exist (see introduction) and can be compared to our results. FW quantification

333

is consistent with other studies at most stages of the FVC (SI 12). However, for household FW

334

the reported amounts differ significantly from each other. Since methodologies and definitions

335

differed between studies, most numbers are not directly comparable. Household FW in this study

336

is based on UK numbers by Quested and Johnson48, because in Switzerland a quantitative

337

analysis of all relevant streams of FW disposal (e.g. incineration, biomass collection, garden

338

compost, pet feed) is still lacking and Quested and Johnson’s methodology is judged as most

339

reliable while considering all streams of FW disposal.

340

The life cycle impacts of food consumption reported by Eberle and Fels49 for Germany and by

341

Jungbluth et al.50 for Switzerland in terms of climate change and Ecological Scarcity ecopoints

342

are mostly consistent with our results (SI 12). In terms of climate change we estimate the FW

343

related emissions to be 25% of the total emissions of consumed food, which is rather high

344

compared to Scherhaufer et al.15 who estimate the FW related GHG emissions at 16% to 22% of

345

the total emissions of consumed food. A reason for the lower number in Scherhaufer et al.15 may


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346

be that their system boundary does not include animal feed as food loss due to lack of data.

347

Concerning FW, FAO7 identified global hotspots of environmentally relevant FW flows and,

348

similarly to our results for Switzerland, found wastage of cereals, vegetables, and meat to be

349

most important. Our results for the impacts of FW are also similar to those reported by Schott

350

and Cánovas5, but they deviate from values reported by FAO7 for Europe, by Eberle and Fels49

351

for Germany, and by Hamilton et al.51 for Norway by about 20-50%; however, differences

352

between countries (e.g. FW going to landfill), system boundaries (e.g. exclusion of agricultural

353

FW), and methodologies (e.g. in quantifying household FW) may explain most deviations

354

(detailed comparison in SI 12).

355

Policy implications and practical relevance of the results. FW in Switzerland causes 4 mio t

356

CO2-eq, about 4% of the emissions of the total carbon footprint of Swiss consumption52, or

357

50% of the 1t CO2-eq/cap target (promoted as a political target in the ETH Zurich energy

358

strategy and widely adopted as a vision to prevent climate warming above 2 degrees celsius;

359

more details in SI 12).53 The main climate change impacts are generated from agricultural

360

production, especially for animal products with high impacts per kg. The impacts of the later

361

stages of the FVC are also relevant; for some products with relatively low impacts from

362

production, e.g. potatoes, they are even dominant. Thus, the environmental relevance of FW

363

increases along the FVC and varies a lot depending on the product. The hotspot along the FVC is

364

FW at the household level due to relatively high volumes and the accumulation of impacts along

365

the FVC. Therefore the consumers are key actors to be addressed in FW prevention policies. In

366

the UK the “Love Food Hate Waste campaign” (LFHW; www.lovefoodhatewaste.com) and an

367

agreement with the food industry to help consumers reduce FW (the “Courtauld Commitment”)

368

have avoided an estimated 1.3 million tonnes of household food and drink waste, which


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369

corresponds to a 23% reduction of avoidable FW between 2007 and 2012.11 Assuming the same

370

reduction in all food categories wasted in Swiss households, 23% of the 253 kg CO2-eq/p/a

371

caused by household FW (red flow in Figure 1) could potentially by avoided. In terms of climate

372

change, the most relevant food categories are fresh vegetables and cereals (high FW amounts)

373

and meat and cheese (high specific impacts). In terms of biodiversity, the highest impacts of FW

374

are caused from cocoa, beef, wheat, and coffee. Consumer awareness and FW prevention

375

strategies should therefore focus on these food groups. In the FVC of cereals and dairy products,

376

notably bread cereals declassified to animal feed and whey and buttermilk may provide high

377

environmental benefits if valorized as food.44 Since the impacts on biodiversity are largely

378

taking place outside of Switzerland, FW prevention should also be communicated as a question

379

of responsibility towards the rest of the world and strategies for FW prevention should include

380

the supply chains of imported products, notably cold chains which affect the potential life period

381

of products.

382

The treatment of FW mainly leads to environmental benefits, but compared to the impacts of

383

production they are low (7.9% of the GHG). For the optimization of FW treatment, today the

384

environmentally best option for products with high calorific and nutrient contents (e.g. bread,

385

cereals and dairy) is feeding to livestock (SI 7.6). For oils and fats, anaerobic digestion and

386

incineration are most favourable; however, the major benefits are related to the substitution of

387

natural gas for heating and may decrease in future scenarios with more renewable energy. For the

388

other FW categories, composting and anaerobic digestion are environmentally more favourable

389

than incineration, but only if potential benefits from the substitution of inorganic fertilizer and

390

peat with high-quality compost and digestate are taken into account. Higher compost and

391

digestate availability may also lead to increased eutrophication.54


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392

Finally, the importance of tackling FW at the consumers’ level is not only sustained by its high

393

potential environmental benefits, but also by the fact that consumers and stakeholders alike

394

perceive FW as obviously unethical, making it a good starting point for individual consumers to

395

become engaged in sustainability.55 If communicated in the light of sustainability, the danger of

396

additional impacts from increased alternative consumption can be turned into the chance of

397

higher environmental awareness in all consumption activities.

398

Outlook. This paper identifies hotspots of environmental relevance for FW prevention and

399

treatment. It therefore serves as a basis to prioritize activities tackling the problem of FW. For

400

the quantification of the potential environmental benefits of specific measures and especially for

401

monitoring the performance of FW prevention further analyzes are needed. The present study is

402

an important basis to develop such measures, as it helps to prioritize and identify the

403

environmentally most important FW flows, products, and stages of the value chain.

404

ASSOCIATED CONTENT

405

SI Supporting Information: Documentation of the methodology; additional results of the study

406

(including other impact categories, MFA, comparison of food categories, regionalized

407

biodiversity assessment, economical relevance, food donations); data reliability assessment;

408

comparison with literature; inventories of food loss rates, MFA (also provided as excel file) and

409

LCI

410

The Supporting Information is available free of charge on the ACS Publications website at DOI:

411

….

412

AUTHOR INFORMATION


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413

Corresponding Author

414

Phone: ++41 44 633 69 69, e-mail: [email protected]

415

Author Contributions

416

The manuscript was written through contributions of all authors. All authors have given approval

417

to the final version of the manuscript.

418

Funding Sources

419

ETH was supported by the Swiss Federal Office for Agriculture (FOAG) and the Federal Office

420

for the Environment (FOEN).

421

ACKNOWLEDGMENT

422

We thank all organizations and contact people for delivering information. A special thank you

423

goes to the Federal Offices providing the financial support for this publication. We also thank to

424

Laura Scherer who supported us with her extensive expertize on the land use and biodiversity

425

impacts from crops and animal products.

426

ABBREVIATIONS AND TERMS

427 428 429 430 431 432 433 434 435 436 437 438 439 440 441

AD gPDF FVC FW GHG GTP GWP IPCC LCA LCI LCIA SFOE WFLDB ZHAW

Anaerobic digestion global Potentially Disappeared Fraction of Species 56 Food value chain (food supply chain) Avoidable food losses and waste, including possibly avoidable 11 Greenhouse Gas Global Temperature Change Potential37 Global Warming Potential36 Intergovernmental Panel on Climate Change Life Cycle Assessment Life Cycle Inventory Life Cycle Impact Assessment Swiss Federal Office of Energy World Food LCA Database Zürcher Hochschule für Angewandte Wissenschaften


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442 443 444 445

Food waste, food wastage, food loss In literature these terms are used with different meanings. However, since the definitions are not consistent and the differentiation is not relevant, in this paper the terms are used as synonyms.

446

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447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484

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Table of Contents Graphic and Synopsis

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climate impacts

consumed food avoidable food waste


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Environmental Impacts and Hotspots of Food Losses: Value Chain

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