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Life-Cycle Costing of Food Waste Management in Denmark: Importance of indirect effects Veronica Martinez-Sanchez, Davide Tonini, Flemming Møller, and Thomas Fruergaard Astrup Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03536 • Publication Date (Web): 15 Mar 2016 Downloaded from http://pubs.acs.org on March 21, 2016

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Environmental Science & Technology

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Life-Cycle Costing of Food Waste Management

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in Denmark: Importance of indirect effects

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Veronica Martinez-Sanchez*1, Davide Tonini1, Flemming Møller2and Thomas

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Fruergaard Astrup1 1

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Miljoevej, Building 113, 2800 Kgs. Lyngby, Denmark

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Technical University of Denmark, Department of Environmental Engineering,

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Aarhus University, Department of Environmental Science, Frederiksborgvej 399, 4000 Roskilde, Denmark

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*) Corresponding author: [email protected]

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1 ACS Paragon Plus Environment


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ABSTRACT

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Prevention has been suggested as the preferred food waste management solution

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compared to alternatives such as conversion to animal fodder or to energy. In this study

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we used Societal Life-Cycle Costing, as welfare economic assessment, and

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Environmental Life-Cycle Costing, as financial assessment combined with life-cycle

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assessment, to evaluate food waste management. Both LCC assessments included direct

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and indirect effects. The latter were related to income effects, accounting for the

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marginal consumption induced when alternative scenarios lead to different household

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expenses, and the land-use-changes effect associated with food production. Results

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highlighted that prevention, while providing the highest welfare gains as more

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services/goods could be consumed with the same income, could also incur the highest

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environmental impacts if the monetary savings from unpurchased food commodities

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were spent on goods/services with a more environmentally damaging production than

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that of the (prevented) food. This was not the case when savings were used e.g. for

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health care, education, and insurances. This study demonstrates that income effects,

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although uncertain, should be included whenever alternative scenarios incur different

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financial costs. Further, it highlights that food prevention measures should not only

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demote the purchase of unconsumed food but also promote a low-impact use of the

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savings generated.


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INTRODUCTION

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One-third of food produced globally for human consumption is wasted (i.e., 1.3 billion

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Mg of food per year)1 corresponding to an average food waste per capita of 280-300 kg

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per year in Europe and North America. Food waste management hierarchies proposed in

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Europe and United States highlight landfilling as the least preferred option, followed by

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incineration and later by biological treatment alternatives such as (an)aerobic digestion.

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Strategies involving utilization of food waste in other industrial sectors, such as the

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animal fodder industry, are instead favored, while changes in consumer behavior are

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considered most desirable (e.g., prevention of food waste).2,3 Economic and environmental performance in relation to food waste

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management, from production to waste management, has been assessed by different

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means; for example, losses associated with food waste corresponded to 0.8% GDP in

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South Africa,4,5 $390 per capita per year in the United States,6 and the global warming

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equivalent of 7 million cars per year in the UK.7 Life-cycle assessment (LCA) has often

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been used to compare the environmental performance of alternative food waste

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management strategies. For example, anaerobic digestion was found to be

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environmentally preferable to landfilling or comparable with incineration.8–10 In

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addition, valorizing bread waste for use as animal fodder provided better environmental

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performance than anaerobic digestion, based on an exergy LCA,11 while a potential

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reduction in greenhouse gas (GHG) emissions in the order of 800-1400 kg CO2-eq. Mg-

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1

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food waste was estimated following prevention of avoidable food waste.12 While a number of different LCA studies assessing food waste management

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strategies and related impacts can be found in literature, none considers two decisive

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indirect effects. The first is the income effect (also called “rebound effect” in energy

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economics),13,14 associated with the marginal consumption induced or reduced when



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there is a difference in costs to consumers between alternative scenarios providing the

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same service.15 For example, economic savings generated by preventing food waste

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(avoiding food purchase) may be spent on purchasing other goods/services associated

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with environmental impacts. The second effect relates to indirect land-use-changes

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(iLUC) induced by production of food commodities (i.e., upstream impacts associated

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with changes in land needed for arable purposes). While recent LCAs have focused on

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the environmental impacts of iLUC (mainly greenhouse gases), none of the studies have

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considered the associated social costs.

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In an attempt to fill this gap, the aim of this study is to assess the economic and

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environmental performance of key options for food waste management, as highlighted

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in the food waste hierarchy,2,3 including direct and indirect effects. This was done by

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means of an Environmental life-cycle costing (E-LCC) and a Societal LCC (S-LCC).9

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Due to the high uncertainty and variability mainly associated with the indirect effects of

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food waste as well as with food waste composition, this study focuses on providing

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overall trends and relative differences rather than specific absolute values. Hence,

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carefulness should be used when interpreting the results and/or generalizing them to

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other contexts. On this basis, the investigation also identifies and assesses potential

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sources of uncertainty affecting the results. Denmark was used as a case study.

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METHODOLOGY

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Goal and Scope definition

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The functional unit (FU) of this study is: “The management of annual food waste

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generated by Danish households: 1,500,000 single-family housing (SFH) and 1,000,000

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multi-family housing (MFH) units”. The food waste generation was 210 kg household-1

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year-1 for SFM and 143 kg household-1 year-1 for MFH.16–18 In both types of housing,


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vegetable food waste (VFW) accounted for approximately three-quarters and animal-

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derived food waste (AFW) for one-quarter of all food waste, while half of the VFW and

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three-quarters of the AFW were classified as edible (i.e., avoidable) food waste.16–18 The

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remaining food waste was assumed inedible and not avoidable (e.g., bones from meat,

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eggshells, and peels). It should, however, be noted that within the edible food waste

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(e.g., a piece of fruit or vegetable), there were parts that cannot be eaten (e.g., fruits

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peels or vegetable tops) and will be prevented when edible food waste is prevented.

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Four scenarios were assessed:

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I)

Incineration of food waste with mixed municipal solid waste (MSW)

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(Scenario Sc-IN). The energy output of the incineration plant was quantified

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as done in 9 (i.e., taking into account the Lower Heating Value of the food

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waste as well as the overall thermal capacity of the WtE plant), see Table S8

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for details. This scenario is taken as baseline since it is the current treatment

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in most of the Danish municipalities.

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II)

Source segregation of food waste (along with other organic waste found in

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the MSW) and subsequent co-digestion with manure, and incineration of

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non-segregated food waste along with the residual MSW (Scenario Sc-CD),

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see Table S8 for details.

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III)

Source segregation of VFW and treatment to be used as animal fodder. AFW

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and non-segregated VFW are incinerated along with the residual MSW

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(Scenario Sc-AF). Fodder production from food waste is only applicable to

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vegetable and bakery waste, because the EU regulation bans all animal

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proteins in fodder.19–21 Due to the lack of data on source separation of VFW,

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it was assumed that the efficiency was 20% lower than the source separation

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of organic waste, see Table S8 for details.



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IV)

Prevention of 100% of the edible food waste and incineration of the inedible

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food waste along with the residual MSW (Scenario Sc-PR). It is assumed

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that: i) households have the same food intake as in the previous three

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scenarios and ii) prevention campaigns demote purchase of unconsumed

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food (i.e., avoiding edible food waste from the households), but still

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assuming generation of inedible food waste.

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Even though the amount of waste handled in Sc-PR differs from the amounts treated in

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the other three scenarios (i.e., while the first three scenarios manage all food waste

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generated by households, the prevention scenario only handles the inedible part), it

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should be noted that all the scenarios provide the same service (i.e., they provide the

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management of the annual food waste generated in Denmark), as recommended when

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performing waste LCAs including prevention.22,23

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The temporal scope of the assessment was 2015 and the environmental impacts

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were included for a time horizon of 100 years. Even though we used Danish data for

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food waste generation and composition, the results could also be relevant for the rest of

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the EU; further, we included state-of-the-art technologies for the modelling, as these

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technologies most likely will be those affected in the near future.

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System boundaries

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Figure 1 illustrates the system boundaries of the study, the four scenarios (with main

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mass flows) and the distinction between direct and indirect effects applied. While direct

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effects refer to the first order effect associated with consumption of resources within the

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system boundaries (i.e., food production, waste management and surrounding

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production sectors such as the energy sector), the indirect effects refer to second and

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higher order effects associated with the consumption induced/reduced by the different

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household expenses of each scenario (income effects) and with the displacement of 6 ACS Paragon Plus Environment

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ecosystems and change in fertilizers application due to food production (indirect land-

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use-changes).

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Regarding food production, a distinction between edible and inedible food waste

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is needed. The production of food commodities related to inedible food waste was equal

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in all scenarios; consequently, accounting for its production was unnecessary. In

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contrast, the food production associated with edible food waste was only present (and

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accounted for) in the first three scenarios (i.e., Sc-IN, Sc-CD and Sc-AF) since in the

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prevention scenario edible food waste was not generated and consequently its

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production did not occur. For simplicity, the term “food production” refers herein to the

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production of food commodities related only to edible food waste, since the modeling

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only includes such production.

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Costs and impacts related to food production are commodity-dependent (e.g., the

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costs/impacts for production of 1 kg of meat are different from 1 kg of bread).24 Thus, it

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was necessary to identify the food commodities composing the edible food waste (i.e.,

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its composition), which was determined by combining data from Danish waste

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composition16,18 and Danish statistic data on annual household consumption (see Figure

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1 and SI-I for calculation details). A sensitivity analysis was performed to verify the

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results’ robustness with respect to the choice of food commodity using the approach of

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(Table S1).

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Activities related to the use of food by households (e.g. cooking), food

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packaging, and transportation from retailer to the household were excluded from the

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assessment due to lack of data on the percentages of cooked/uncooked food and packed/

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unpacked food as well as on the transportation distance/means from retailer to houses.

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The importance of these activities is discussed in the uncertainty section.

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Identification of marginal processes and technologies

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The assessment follows a consequential approach26–28 aiming at illustrating the

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consequences associated with each scenario. Along with fulfilling the FU, each scenario

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generates co-products which are assessed with system expansion (i.e., expanding the

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system boundary to include additional functions provided by said co-products). In order

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for this to happen, it is necessary to identify those processes/technologies, referred to as

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“marginal” in consequential LCA, likely to respond to changes in the supply induced in

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each scenario.29

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The energy outputs from waste-to-energy conversion (incineration and anaerobic

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digestion) were considered to substitute marginal fossil fuel extraction and combustion.

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Coal-fired power plants were assumed as marginal technologies for electricity

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production, following Danish government’s targets to phase-out coal by 2030.30 This

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choice is assessed in the uncertainty section. Marginal heat was assumed to originate

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from natural gas boilers based on the projections from 31. The digestate produced from

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anaerobic digestion was used as organic fertilizer which substituted mineral fertilizer

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(assumed to be urea, diammonium phosphate and potassium chloride according to the

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demand trends and projected capacity installations),32 based on NPK content of the

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digestate applied on-land. The production of fodder from food waste substituted for

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marginal energy-feed, which was assumed to be based on maize.32 The substitution was

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done on the basis of the energy-feed content of waste fodder relative to maize fodder,

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using Scandinavian Feed Unit (SFU), see SI-IIC for calculation details.

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Indirect effects

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Income effects

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Expenses incurred by households in the incineration scenario (Sc-IN) were taken as a

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baseline, while any net change in the total expenses of households in the remaining 8 ACS Paragon Plus Environment

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scenarios was assumed to affect other forms of consumption (purchase of

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goods/services), the so-called “income effect.” For that, it was necessary to identify the

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marginal consumption associated with the case study, i.e. the mix of goods/services for

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which the purchase would be affected (increased or reduced) by a change in the FU

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expenses (i.e., the cost of food waste management in Denmark in 2015).

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Different methods can be considered for identifying the marginal consumption,

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such as Vringer,33 Binswanger,14 and Hertwich.13 The approach used in this study is

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based on consumer expenditure surveys as recommended by the European

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Commission34 and as done by Thiesen et al.15 For this purpose, Danish consumer

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expenditure data (including the annual expenses of the whole Danish society

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represented by 5 income groups)15,35 was used. The marginal consumption was

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calculated as a weighted average of the change in consumption patterns between

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consecutive income groups. Figure 1 displays the distribution of the income effects (i.e.,

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marginal consumption composition) and Figure S1 the calculation approach.

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Acknowledging the uncertainty associated with the identification of the marginal

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consumption, the assessment includes the potential variation of the results between two

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extreme distributions of the income effect, one maximizing and the other minimizing

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the impact of the marginal consumption. As such, these are defined by the good/service

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with, respectively, the largest and the lowest impact on each impact category (in the

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LCA) and externality costs (in the Societal LCC).

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Indirect Land-Use-Change (iLUC):

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Marginal food demand in Denmark is supplied by the global food market, which

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ultimately incurs iLUC, generating environmental emissions, ecosystem losses, and

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changes in use of labor and real capital changes36–38. To quantify iLUC, different

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approaches have been suggested, ranging from partial and global equilibrium models 9 ACS Paragon Plus Environment


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(e.g.,37,39–42) to causal models (e.g.,32,43 ). Herein we followed the approach of 32, see SI-

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IIIB.

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Assessment methods

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Two assessment methods were applied: E-LCC and a S-LCC,9 summarized in Table S3.

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While the E-LCC includes an economic part and an environmental part, the S-LCC

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merges both in a single indicator (social costs).9

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Both LCCs could be used as stand-alone tools, but some aspects would remain

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unassessed, i.e. only environmental impacts of emissions are included in the

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environmental part of the E-LCC (i.e. in the LCA), and only externalities with available

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accounting prices are included in the S-LCC. Whereas the first is a method limitation

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(whereby further development should be done to include other types of externalities

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such as ecosystem losses), the second is a data limitation (whereby further research

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should be done to estimate accounting prices of critical emissions and resource

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consumption). Overcoming such limitations, both methods would have the same

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capabilities and could be used indistinctly. Given the current status of data and

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development, this study used both LCCs to embrace a wider range of effects.

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Although both LCCs differ in their characteristics (described in the following subsections), the following case study assumptions were used in both tools: i)

The price mechanisms of food commodities (and other products) were not

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affected by changes in food waste management, thus prices of food and other

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marketed goods were the same in all scenarios.

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ii)

It was assumed that households, as waste management system customers,

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pay for the total cost of the system, and their total expenses for the FU are

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assumed constant and equal to the expenses of scenario Sc-IN (baseline).


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iii)

The level of saving in the Danish society was not affected by changes in

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food waste management (e.g., lower expenses for the waste management

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sector were compensated with increases in consumption of other

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commodities, earlier identified with the distribution of the income effect).

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E-LCC: Financial assessment

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The economic part of the E-LCC describes the income flows to provide the FU (i.e.,

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how the income and expenditure of individual actors are affected by the assessed

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change in the system). It includes budget costs and transfers (i.e., taxes, subsidies and

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fees) and distinguishes six actors, namely the waste management sector (WMS), the

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energy sector, the food industry, the agriculture sector that utilize digestate and waste-

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derived fodder, industry affected by income effects, and the State. The expenses of the

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abovementioned actors are assumed to be transferred to the households (as they are the

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customers of all the sectors). Hence household’s expenses correspond to the sum of the

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first five sectors expenses (i.e., WMS, energy sector, food industry, agriculture sector,

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income effect industry) minus the expenses for the State (e.g., taxes paid by households

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are accounted as revenues for the State and cost for households).

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The budget costs of the direct effects include: i) expenses related to the WMS,

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and the production of food; ii) saved expenses related to resources set free in the energy

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sector due to energy generated by the WMS, and in the agriculture sector due to avoided

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use of marginal fertilizer and fodder. Both accounted for in 2013 factor prices (i.e.,

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consumer prices excluding transfers) and summarized in SI-IV and Table S10.9,44 Such

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prices are assumed to internalize all the expenses related to both activities (e.g.,

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expenses related to fuel and seeds are included in the food prices). Transfers related to

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the direct effects include: i) State revenues associated with tax received from the WMS

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and food industry; ii) State losses due to taxes not received from marginal energy, 11 ACS Paragon Plus Environment


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fertilizer, and conventional fodder producers, as well as subsidies given to biogas

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production. It is worth noticing that Danish biogas plants are subsidized and exempted

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from CO2 tax.45 This is common practice in many European countries following

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National Renewable Energy Actions Plans.46

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Regarding indirect effects, iLUC do not cause any financial net consequence,

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since we assumed that the food price remained constant in all the scenarios, hence there

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are no budget costs nor transfers associated. The income effects equalized the

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households’ expenses of all scenarios in line with baseline expenses (Sc-IN) (e.g., the

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income effect of scenario Sc-CD resulted from subtracting its households expenses

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related to direct effects to the household expenses of Sc-IN). The transfers received by

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the State associated with the income effects correspond to the VAT of such

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consumptions.

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E-LCC: Life-Cycle Assessment

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The life-cycle impact assessment was performed with the midpoint based on ILCD

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recommended methods47 and included global warming (GW), photochemical ozone

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formation (POF), marine water eutrophication (EU (mw)), and fossil and mineral

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resource depletion (RD (f) and RD (m)). The assessment was facilitated by the

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EASETECH LCA model.48

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The environmental impacts associated with the direct effects included the

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emissions from WMS, the food production, and the avoided production of (marginal)

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fodder, mineral NPK fertilizers, and energy (SI-IIC describes the inventories used).

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The environmental impacts associated with the income effect were calculated

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using the inventory of each consumption item taken from the Input-Output model for

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EU27.49 Table S4 summarizes the data matching between the statistics on Danish

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consumptions and the EU27 Input-Output categories, while Table S9 details the 12 ACS Paragon Plus Environment

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inventory of each consumption item. Regarding iLUC, it was assumed that the demand

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for 1 Mg of additional food would be met by a combination of intensifying existing

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production (75%) and expansion of arable land (25%), thereby conforming with32. The

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intensification inventory covered the use of N-fertilizer, P-fertilizer and K-fertilizer,

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while for expansion it included carbon and nitrogen losses related to deforestation (see

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Figure S2 and Table S5).

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S-LCC:

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S-LCC is a welfare economic analysis that describes the consequences for persons’

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welfare of re-allocating scarce resources in society (i.e., land, real capital, and labor) to

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provide the FU (i.e., management of food waste).9 The S-LCC includes: i) marketed

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goods and services (herein called “budget costs”) and ii) non-marketed goods

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(externality costs), both accounted for in accounting prices. The latter are indicators of

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the marginal utility (welfare) of each good. The accounting prices of marketed

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goods/services equal factor prices (consumer prices excluding transfers) increased by a

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general tax factor, the Net Tax Factor (NTF).50 The accounting prices of the non-

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market goods (e.g., an emission) represent the “willingness to pay” to avoid its adverse

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effect. To calculate the effect, the dose-response relation for each externality is needed.

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However, when this is unknown, the marginal welfare economic cost of reducing an

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environmental load (the so-called “shadow price” of meeting a target) can be used as a

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proxy for the accounting price. The accounting prices used should represent regional

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conditions related to the point of emission. However, given the scarcity of regional

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dose-response data, and the uncertainty surrounding emission locations, we assumed

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that Danish accounting prices were applicable worldwide, and we therefore adopted the

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values suggested by the Danish EPA50 for all the emissions (Table S11). It should be

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noted, nonetheless, that this is just an assumption employed to illustrate the applied 13 ACS Paragon Plus Environment


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method. A social discount rate of 4%, as suggested in 50, was applied to costs and

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benefits spread over time.

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Direct effects have budget and externality costs associated. Budget costs

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correspond to the marketed goods related to the resources spend/saved in the WMS,

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food production, agriculture, and energy sector corresponding to the factor prices

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increased by the NTF. Externality costs results from: i) the emissions of the LCA

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associated with the same activities times the accounting prices of each emission and ii)

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the welfare consequence for public finances due to a change on public

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expenditure/income compared with the baseline (Sc-IN) times the Tax Distortion Loss,

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assumed to 20%.45,51

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The inclusion of income effects led to two welfare changes, one related to the

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induced/reduced marginal consumption (amount of goods/services that can be

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purchased with the same income), and the other related to emissions from production of

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such goods/services. When the alternative scenario has lower expenses than the

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baseline, there is a welfare gain in consumption due to an increase on resource

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efficiency, and a welfare loss related to emissions generated by the production of the

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consumed goods. The opposite will occur if the baseline is cheaper than the alternative

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scenario. The budget costs of the income effects correspond to the factor prices of such

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consumptions increased with the NTF, and the associated externality cost results from

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the emissions of their productions and the accounting prices of such emissions.

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The iLUC effect is included as: i) environmental consequences associated with

330

emissions from arable land expansion and production intensification, ii) the socio-

331

economic value of ecosystem losses following arable land expansion, and iii) real

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capital and labor changes (Figure S2). For the first, we used emissions from the LCA

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and the accounting prices in Table S11. For the second, literature-based data on 14 ACS Paragon Plus Environment

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ecosystem valuations (52–91), taken from the TEEB database,92 was used to estimate the

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combined ecosystem services value (Table S6). It should, however, be noted that this

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estimation is only a minimum, since it includes only the “use-value” of the non-

337

marketed good (including exploitative uses such as timber harvesting and non-

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conservative uses such as recreational purposes) and not its “non-use” values (i.e.,

339

existence and bequest values). For the third, we assumed the full employment of real

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capital and labor resources that would move in the same direction as land-use (e.g., if

341

the production of “product A” causes conversion of rainforest to cropland, labor and

342

real capital will move from the tourism sector in the rainforest to the agricultural sector)

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thus there is no net change in the use of these resources.

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RESULTS AND DISCUSSION

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Direct Effects

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E-LCC: Economic assessment

347

Figure 2A (I) (Table S12) shows the economic part of the E-LCC (financial assessment)

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related only to direct effects (i.e. excluding income effects and iLUC). Note that

349

expenses are assigned a positive value, while revenues a negative values.

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The food industry incurred the largest costs due to the food production in the

351

first three scenarios (not involving prevention) and zero costs in Sc-PR (as purchases of

352

edible food waste were avoided). While “fish” had the highest intrinsic cost (€ Mg-1

353

food commodity), the largest cost contribution was from “bread” due to its large

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presence (in weight) in the edible food waste composition, see Figure S3A.

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Regarding the WMS, co-digestion (Sc-CD) and conversion to animal fodder (Sc-

356

AF) incurred higher costs than the baseline (incineration; Sc-IN) mainly due to extra

357

collection costs for organic waste; this was also documented in 9. Conversely,

358

prevention (Sc-PR) showed the lowest cost, since edible food waste was not generated, 15 ACS Paragon Plus Environment


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thus handling avoided. As the WMS of all the scenarios generated energy displacing

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conventional fossil sources, corresponding resources in the energy sector were saved.

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The agriculture sector benefitted primarily from the substitution of maize fodder in the

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conversion to fodder scenario (Sc-AF) and, to a lesser extent, from the substitution of

363

mineral fertilizers with digestate in the co-digestion (Sc-CD). These agriculture savings,

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however, along with those in the energy sectors, were minor compared with the

365

costs/savings incurred by the food industry.

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The State benefitted in the scenarios without prevention, since tax revenues were

367

higher than tax exemptions and subsidies. Nonetheless, co-digestion (Sc-CD) showed

368

lower revenues owing to biogas plant subsidies and exemption from CO2 tax. In

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contrast, such benefits were almost null for the prevention scenario (Sc-PR) since State

370

revenues associated with tax received from WMS taxes were cancelled out by the State

371

costs due to not received taxes from the energy sector (see Table S12).

372

Considering only direct effects, households expenses in the scenarios without

373

prevention were around 40 times larger than the expenses in Sc-PR (black rhombus in

374

Figure 2A (I) and Table S12) mainly due to the purchased of unconsumed food.

375

E-LCC: Life Cycle Assessment

376

Figure 2A (II) (Table S13) shows the environmental impacts associated with direct

377

effects. The unit is “characterized impacts per FU” (e.g., t CO2-eq. FU-1). The scenarios

378

without prevention (Sc-IN, Sc-CD, and Sc-AF) showed comparable trends (since most

379

of their impacts came from food production that was equal for all of them), while

380

prevention (Sc-PR) showed much lower impacts owing to the avoided production of

381

edible food waste (now prevented).

382 383

The food production industry generated most of the burdens for all the impact categories in Sc-IN, Sc-CD and Sc-AF. Within the food industry impact, “beef” 16 ACS Paragon Plus Environment

Page 17 of 34


384

appeared to have the highest intrinsic impact on GW, EU (mw), and RD (m) due to

385

methane, dinitrogen oxide, ammonium, and carbon dioxide emissions to air while

386

“Tomato” showed the highest intrinsic impact on RD (f) due to irrigation and

387

consumption of pesticides (Figure S3). Other commodities, albeit with lower intrinsic

388

impacts (e.g., bread, carrots, and tomatoes), nevertheless had significant contributions to

389

the total impact due to their significant presence (in weight) in the edible food waste.

390

These results are in line with Eriksson et al.24

391

S-LCC

392

Figure 2A (III) (Table S15) displays the welfare consequences associated with the direct

393

effects of the four scenarios (losses are positive, gains negative).

394

With regard to the budget costs, the scenarios without prevention (Sc-IN, Sc-

395

CD, and Sc-AF) highlighted large welfare losses due to purchase of unconsumed food

396

(food industry). The WMS incurred welfare losses in all the scenarios, these being

397

higher for Sc-CD and Sc-AF due to collection costs (same as in the economic part of the

398

E-LCC, Figure 2A (I)). The agriculture sector incurred small welfare gains from

399

avoiding use of mineral fertilizers and conventional maize-fodder, while the energy

400

sector incurred welfare gains, since energy production from marginal fuels was reduced

401

owing to energy production from the waste. These gains were lower in the alternative

402

scenarios, since their WMSs generated less energy than the baseline scenario (thus

403

displacing correspondingly less fossil energy).

404

Externality costs related to the emissions (and the tax distortion loss) appeared

405

minor compared to budget costs. This minor influence can be explained by the lack of

406

accounting prices for most emissions and perhaps by the small magnitude of available

407

accounting prices.

408



Page 18 of 34

409

Total Effects (importance of indirect effects)

410

Considering only direct effects (Figure 2A) implies unbalanced money flows, i.e. some

411

money is added or subtracted from the system boundary without any consequence. For

412

simplicity, these money flows were quantified relative to the baseline Sc-IN (status quo)

413

for which the expenses were set to zero. Results showed a decrease of 1226 M€ in the

414

expenses of the prevention scenario Sc-PR (this being cheaper than the baseline Sc-IN)

415

and increases of 34 and 41 M€ in the expenses of scenarios Sc-CD and Sc-AF,

416

respectively (these being more expensive than the baseline Sc-IN). As earlier discussed,

417

if economy is assumed constant, other consumptions should be affected by the change

418

in the expenses of the FU (income effect). The consequences associated with this and

419

with iLUC, along with the direct effects earlier discussed, are illustrated in Figure 2B.

420

E-LCC: Economic assessment

421

Figure 2B (I) (Table S12) shows the economic part of the E-LCC (financial assessment)

422

including direct and indirect effects, in which the four scenarios incurred the same

423

households expenses (i.e. 1255 M€/FU), albeit the economic winners and losers varied.

424

Industries affected by the income effect reduced resource use and production

425

costs in co-digestion (Sc-CD) and conversion to fodder (Sc-AF), since the costs

426

associated with WMS were higher than in the baseline (Sc-IN). In comparison, the same

427

industries in the prevention scenario (Sc-PR) used more resources, since savings from

428

unpurchased food were now spent in this industry.

429

The expenses related to income effects are the same regardless of the

430

distribution of the income effects, i.e. increase/decrease in other consumption in terms

431

of M€ does not depend on the item purchased.


Page 19 of 34


432

E-LCC: Life Cycle Assessment

433

Figure 2B (II) (Table S13) shows the environmental impacts of direct and indirect

434

effects. The unit is “characterized impacts per FU” (e.g., t CO2-eq. FU-1). The error bars

435

show the potential variation of the net impact due to “extreme scenarios” of marginal

436

consumption, i.e. where 100% of the savings are used to purchase the good/services

437

with the largest and the lowest impact within each category (Table S14). Because of the

438

income effects, the prevention (Sc-PR) was the worst alternative in GW, RD (f) and RD

439

(m). “Housing”, “Communication”, and “Leisure” were the most important contributors

440

(>70%) to the income effect. However, when the marginal consumption was “Health

441

care”, “Education” or “Security (e.g. insurances)” (consumptions with the lowest

442

environmental impact on all the categories) the impacts of the prevention scenario were

443

lower than the alternatives. The iLUC impact was significant on GW because of the carbon loss from

444 445

cleared ecosystems (expansion of cropland. Impacts from iLUC were decreased in the

446

conversion to fodder scenario (Sc-AF) thanks to avoiding production of conventional

447

feed through use of waste-derived fodder (thereby partially avoiding iLUC). Details are

448

in Table S13.

449

S-LCC

450

Figure 2B (III) (Table S15) displays the welfare consequences of the four scenarios

451

associated with direct and indirect effects. While the scenarios without prevention (Sc-

452

IN, Sc-CD, and Sc-AF) resulted in welfare losses (social costs), mainly due to

453

purchasing of unconsumed food (food industry), the prevention (Sc-PR) resulted in

454

welfare gains, (social benefits).

455 456

In Sc-PR, the use of the savings brings welfare gains on consumption (budget costs) and losses due to emissions following production of the foods/services 19 ACS Paragon Plus Environment


Page 20 of 34

457

constituting the marginal consumption (namely externality costs). Though this is

458

uncertain, as acknowledged earlier, the error bars in Figure 2B (III) nevertheless

459

highlight that its distribution had a low influence on the S-LCC results. The reason for

460

this is that only the externality costs associated with the income effect are good/services

461

dependent, and such costs were three orders of magnitude lower than budget costs.

462

As shown in Table S15, most externality costs related to emissions were greater

463

in the prevention scenario (Sc-PR) than in the alternatives, mainly due to SO2, NOx and

464

CO2 emitted in the production and consumptions related to the income effects (Tables

465

S15 and S16). Ecosystem losses were the same for the first three scenarios, though

466

slightly smaller in the conversion to fodder scenario (Sc-AF) due to avoiding

467

conventional maize-fodder production.

468

Uncertainties discussion

469

The robustness of the overall conclusions (i.e., eventual change in ranking of the

470

individual scenarios due to a changed assumption) was assessed through sensitivity

471

analyses. This focused on: i) food waste composition, ii) food transport and handling,

472

and iii) choice of marginal fossil energy. In addition, the uncertainty associated with

473

externality costs was also discussed.

474

The alternative food composition, obtained by multiplying the food loss rates

475

from 25 by the average food consumed per household in Denmark (on the basis of the

476

Danish studies25,35,44,93,94; Table S1), showed costs/impacts comparable to the baseline

477

food composition in all impact categories (Figure S3). The ranking among scenarios

478

remained the same.

479

When assuming that food transportation and handling (of the edible food waste)

480

implies an average driving distance of 28 km week-1 households-1 and an electricity

481

consumption per meal of 1 MJ, 95,96 the financial costs of the first three scenarios 20 ACS Paragon Plus Environment

Page 21 of 34


482

(without prevention) increased by about 4%: 20 M€ due to home transportation and 10

483

M€ due to electricity for cooking (under the conservative assumption that all edible

484

food waste is cooked). At the same time, the income effects of the prevention scenario

485

(Sc-PR) increased by 30 M€ to equalize its financial costs to the baseline’s

486

(incineration; Sc-IN). This inclusion also increased the GW of the scenarios without

487

prevention by 80% (2.6 108 kg CO2 related to transportation and 5.9 107 kg CO2 for

488

cooking) and in the prevention scenario by 3%. Under this conservative assumption, the

489

prevention scenario showed similar GW impacts than the alternatives. The ranking of

490

the scenarios in the S-LCC was not affected by this assumption, but the difference

491

between the scenarios increased (i.e., the three scenarios without prevention added 35

492

M€, while the prevention scenario, Sc-PR, increased the social benefit by the same

493

amount in terms of income effects). See SI-VIIE for calculation details.

494

The choice of energy system is acknowledged to be critical for many waste-LCA

495

studies, since the environmental impacts of waste-to-energy technologies are completely

496

dependent upon the assumed energy system. For example, according to 97, net GW

497

savings of incineration may decrease by 30%-107% when changing the marginal energy

498

off-set from coal to natural gas. In our case, assuming a 100% decrease of the

499

environmental benefits associated with energy generation from the WMS (this

500

corresponds to take natural gas as marginal source) increased the net GW impacts by

501

1·108 kg CO2 in the scenarios without prevention and by 6·107 kg CO2 in the prevention

502

scenario (Sc-PR). This, however, did not change the ranking of the scenarios, although

503

the difference between the three scenarios without prevention and the Sc-PR became

504

slightly smaller than with coal as marginal energy source.

505 506

The externality costs associated with emissions may, in this study, be over/under estimated, because Danish accounting prices (estimated based on “actual” emissions at



Page 22 of 34

507

any given point in time and space)95 were applied to LCA emissions (representing

508

“potential” impacts aggregated over time and space). In addition, the value of the

509

estimated “ecosystem losses” varied between 168 and 1643 € ha-1 expanded, and we

510

applied the median (435 € ha-1) in our baseline calculations. When using the max,

511

ecosystem losses could be four times greater, but this would still be minor compared

512

with the costs of marketed goods (budget costs). Nevertheless, it should be noted that

513

this value only represents the “use-value” of the ecosystem, since no data were available

514

for existence and bequest values.

515

Based on this discussion: i) the assessment results appeared robust with respect

516

to the assumptions taken for (edible) food waste composition, energy system (marginal

517

electricity technology), food transportation from retailer to houses as well as food

518

handling, and externality costs of the emissions, because the ranking of the scenarios

519

remained the same when changing each individual assumption; ii) the results of the E-

520

LCC were sensitive to the assumptions regarding the distribution of the income effect

521

(i.e., composition of the marginal consumption) as highlighted by the error bars in

522

Figure 2B (II). In this respect, further research should focus on identifying the use of the

523

savings derived from unpurchased food. In contrast, the results of the S-LCC were

524

robust with regards to the distribution of the income effect, since this only affected

525

externality costs which appeared to be minor compared with the budget costs.

526

Implications for future assessments and waste strategies

527

Limiting the assessment to direct effects, prevention of food waste appeared to be the

528

preferred option in both LCCs due to the resources saved by not producing the

529

(prevented) food commodities. In contrast, when including the indirect effects,

530

prevention appeared to be environmentally worse than the alternatives (in LCA) when

531

monetary savings from unpurchased food commodities were used for goods/services 22 ACS Paragon Plus Environment

Page 23 of 34


532

whose production has larger environmental impacts than those of the (prevented) food.

533

This outcome questions conclusions from previous demonstrating dramatic

534

environmental savings from waste prevention (e.g., Gentil et al.23). The reason for this

535

is that none of the published LCA studies on waste prevention included income effects

536

related to the savings used, thus basically incurring unbalanced money flows within the

537

system boundaries. Yet, if the monetary savings were instead used for low-impact

538

goods/services (such as health care, education, or insurances), the environmental

539

impacts of prevention could be significantly reduced and ultimately be lower than those

540

of the alternative management strategies. Hence, the environmental impacts of the

541

income effects could be reduced if prevention measures were not only aiming at

542

decreasing the purchase of unconsumed food item but also aiming at allocating

543

monetary savings towards low-impact goods/services. As opposed to the environmental

544

assessment, the prevention of food waste showed large welfare gains compared to the

545

alternative management (which all incurred welfare losses) regardless of the income

546

effect distribution.

547

On this basis, acknowledging that the determination of monetary savings and

548

income effects are associated with large uncertainty, this study nevertheless

549

demonstrates that including income effects is critical and has to be done whenever there

550

is a cost-difference between the assessed scenarios.

551

The inclusion of the iLUC appears to be critical only in the LCA, whereas iLUC

552

had a minor importance in the S-LCC. In this context, however, the results also suggest

553

that valuation of the combined ecosystem services, including the non-use value of the

554

ecosystems, could be critical.



Page 24 of 34

555

AUTHOR INFORMATION:

556

Corresponding Author

557

*Address: Miljoevej, Building 113, 2800 Kgs. Lyngby, Denmark; Phone: (0045)

558

45251602; e-mail:[email protected]

559

ACKNOWLEDGMENTS

560

The authors thank Alessio Boldrin from the Technical University of Denmark (DTU)

561

for his helpful comments on a draft version of the manuscript and Lisbeth Brusendorff

562

from DTU for her work on the graphical abstract. Financial support was obtained from

563

the Danish Research Council through the IRMAR project.

564

ASSOCIATED CONTENT:

565

Supporting Information. Food commodities, Marginal products/technologies, Method

566

details, Environmental and economic inventories, Factor prices and names for upstream

567

food commodities, Accounting prices of emissions and Detailed results. The material is

568

available free of charge via the Internet at http://pubs.acs.org

569

570

FIGURE CAPTIONS:

571

Figure 1: Overview of the four scenarios assessed with main mass and energy flows.

572

The food waste composition is divided into inedible and edible food waste for both

573

Vegetable Food Waste (VFW) and Animal Food Waste (AFW). The edible food waste

574

is further disaggregated into the food commodities constituting the baseline

575

composition. Notice that the “food production” activity only includes the production of

576

food commodities related to the edible share of the waste, as the inedible portion is the 24 ACS Paragon Plus Environment

Page 25 of 34


577

same in all four scenarios and it was not modelled. The distribution of the income effect

578

(also called “marginal consumption”) used as baseline assumption is also shown.

579

Figure 2: A) Results including only direct effects; B) Total results, including both direct

580

and indirect effects. I) Economic part of the E-LCC (financial assessment) in M€ per

581

functional unit (FU); II) Environmental part of the E-LCC in characterized impacts per

582

functional unit (FU) for global warming (GW) and photochemical ozone formation

583

(POF) rest of categories are shown in Table S13; III) S-LCC in M€ per functional unit

584

(FU). The error bars illustrate the potential variation of the net impact due to “extreme

585

scenarios” of marginal consumption (i.e., where 100% of the monetary savings are used

586

to purchase the good/services with the largest and the lowest impact within each

587

environmental category).

588



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Graphic abstract 47x26mm (300 x 300 DPI)

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Figure 1: Overview of the four scenarios assessed with main mass and energy flows. The food waste composition is divided into inedible and edible food waste for both Vegetable Food Waste (VFW) and Animalderived Food Waste (AFW). The edible food waste is further disaggregated into the food commodities constituting the baseline composition. Notice that the “food production” activity only includes the production of food commodities related to the edible share of the waste, as the inedible portion is the same in all four scenarios and it was not modelled. The distribution of the income effect (also called “marginal consumption”) used as baseline assumption is also shown. 200x105mm (96 x 96 DPI)



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Life-Cycle Costing of Food Waste Management in ... - ACS Publications

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