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Policy Analysis
Assessment of food waste prevention and recycling strategies using a multi-layer systems approach Helen A. Hamilton, M. Samantha Peverill, Daniel B. Müller, and Helge Brattebo Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03781 • Publication Date (Web): 23 Oct 2015 Downloaded from http://pubs.acs.org on October 24, 2015
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Environmental Science & Technology
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Assessment of food waste prevention and recycling
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strategies using a multi-layer systems approach
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Helen A. Hamilton*†, M. Samantha Peverill†, Daniel B. Müller†, Helge Brattebø†
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† Industrial Ecology Programme and Department of Energy and Process Engineering,
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Norwegian University of Science and Technology, NO-7491, Trondheim, Norway
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*Ad: Sem Sælands vei 7, Trondheim, Norway; Tel: +47 45002105; email:
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[email protected] 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Food waste (FW) generates large upstream and downstream emissions to the environment and unnecessarily consumes natural resources, potentially affecting future food security. The ecological impacts of FW can be addressed by the upstream strategies of FW prevention or by downstream strategies of FW recycling, including energy and nutrient recovery. While FW recycling is often prioritized in practice, the ecological implications of the two strategies remain poorly understood from a quantitative systems perspective. Here, we develop a multi-layer systems framework and scenarios to quantify the implications of food waste strategies on national biomass, energy, and phosphorus (P) cycles, using Norway as a case study. We found that (i) avoidable food waste in Norway accounts for 17% of food sold; (ii) 10% of the avoidable food waste occurs at the consumption stage, while industry and retailers account for only 7%; (iii) the theoretical potential for system wide net process energy saving is 16% for FW prevention and 8% for FW recycling; (iv) the theoretical potential for system wide P saving is 21% for FW prevention and 9% FW recycling; (v) while FW recycling results in exclusively domestic nutrient and energy savings, FW prevention leads to domestic and international savings due to large food imports; (vi) most effective is a combination of prevention and recycling, however, FW prevention reduces the potential for FW recycling and therefore needs to be prioritized to avoid potential overcapacities for FW recycling.
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1. INTRODUCTION
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Food wastage, amounting to one third of global food production1, has severe environmental
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implications as food production systems generate emissions to the environment and rely on a
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host of natural resources for operation. The unnecessary use of land, water, minerals and energy
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to produce wasted food exacerbates resource scarcity and, with expected population growth,
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could result in significant food security issues.2 One key environmental problem that has
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received a substantial amount of research and policy attention is climate change.1,3 The
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production of wasted food results in greenhouse gas emissions that could lead to adverse climate
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impacts. A lesser studied but critical environmental problem is the over consumption and loss of
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scarce, yet essential nutrients such as phosphorus (P). While P is a finite resource that is central
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for food production, it also acts as a pollutant if accumulated in vulnerable aquatic environmental
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compartments.4
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Measures for addressing food waste vary widely, however, two common food waste (FW)
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strategies include FW prevention and FW recycling.5 These management strategies are often
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chosen from an environmental perspective with the aim of reducing the environmental impacts
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of food systems. At the global level, FW initiatives are, in general, shaped by waste hierarchy
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principles where FW prevention is prioritized as the most sustainable solution followed by reuse,
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recycling/recovery and lastly disposal.1,6 Because of this, FW prevention is considered the ‘best
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practice’ approach and, thus, the most effective method for reducing food waste.5 While this may
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hold true in many cases, socio-metabolic studies have challenged the waste hierarchy and have
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shown that it does not necessarily lead to economic, social and environmentally sustainable
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outcomes.7 This is because the waste hierarchy is a generic principle that lacks a coherent
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description of the critical mass and energy flows within a system and, instead, takes a singular,
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narrow focus on waste management. In the case of food waste, such an approach does not allow
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for a systems-specific understanding and the quantification of the effect of targeted management
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strategies on nutrient and energy systems. Overall, there is a lack of socio-metabolic studies to
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test the waste hierarchy principle for food.
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Contrary to the above, the current Norwegian food waste management practices tend to favor
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FW recycling. In Norway, food waste is viewed as a potential renewable energy feedstock and,
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thus, an opportunity for reducing greenhouse gas emissions through biogas production.8,9 This
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method is heavily encouraged by the state through funding the development of biogas
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infrastructure and the establishment of economic incentives for biogas production.10–12
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According to the Oslo municipality13, the displacement of fossil fuels by biogas has resulted in a
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13% reduction in CO2 emissions from Oslo’s transportation sector and has been identified as a
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crucial part of making Norway a low carbon society.11 Nevertheless, while food waste recycling
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has resulted in climate benefits, this approach lacks a larger systems perspective that includes the
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entire food chain and consideration for other crucial resources, such as phosphorus (P). Because
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Norway lacks primary P resources and their current P systems are inefficient, improved domestic
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P management is of particular importance.14
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The above highlights that, at a national level, we lack an analytical framework for supporting
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priority setting for food waste management. In order to make management decisions, it is crucial
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to understand and quantify the implications of food waste strategies. Therefore, we develop and
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apply a systems approach for Norwegian agriculture to assess and quantify the effects of targeted
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food waste strategies from a multi-resource perspective. Here, we quantify the theoretical
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maximum savings that food waste recycling and prevention provides in order to inform policy
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about sustainable directions for addressing food waste that minimize the impacts and optimize
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the use of P and energy. The following research questions will be addressed:
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(1) What are the strengths and weaknesses of the developed multi-layer substance flow
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analysis (SFA) modeling approach for providing a better understanding of the
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interlinkages in a multi-resource system?
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(2) What are the current dry matter, energy and phosphorus balances in the Norwegian food system? What are the largest potentials for saving energy and phosphorus? (3) What are the theoretical maximum savings of food waste recycling and food waste prevention for the energy and phosphorus balances? (4) Based on the above, how can our results inform food waste policy for systems-wide optimization of phosphorus and energy?
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2. MATERIALS AND METHODS
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2.1. System definition. Energy and P are closely coupled through biomass, as biomass contains
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both P and energy. Because of this, we used a multi-layer substance flow analysis (SFA)
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framework, that quantifies the flows and stocks of substances throughout our defined system15,
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for Norwegian agriculture, where three layers are represented. The ‘mother’ layer contains the
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biomass system (tons DM/year) and the two ‘child’ layers include the energy and P balances.
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The energy layer consists of both the gross energy (GE) of the biomass, a function of the mother
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layer and calculated as the higher heating value (HHV in joules/year), and the process energy
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(PE) needed to transform the goods, e.g. electricity, oil, etc, (joules/year). The P layer represents
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the P contained in the biomass layer (tons P/yr). DM – over wet weight - was used in order to
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remove inconsistencies related to the varying water content of organic products. This increases
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the robustness of the model and allows for a DM-based quantification of the GE within the
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products as well as P concentration.
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This study analyzes the agriculture system of Norway, which represents a typical example of an
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industrialized country that has domestic agriculture and an increased focus on nutrient
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management.14 This system is defined to include trade, plant production, animal husbandry, food
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processing, human consumption, waste management and biogas production. Transportation was
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not considered due to the high uncertainty and lack of transport data within food and biogas
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production. Detailed information regarding the system definition can be found in the supporting
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material.
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2.2. Data, definitions and quantification. Primary data inputs were predominantly sourced
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from national statistics, reports and scientific articles. The reference system is based on averaged
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data from 2009-2011, with the P system based on Hamilton and colleagues.14 Each flow was
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individually calculated, unless otherwise stated, and the results were left unreconciled in order to
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assess all mass balance inconsistencies [indicative of uncertainty] in relation to the relevant
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process flows. This allows for full transparency of uncertainty and error within the model, as
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reconciled results mask this information. Further information related to the data, data sources and
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analytical solutions can be found in the supporting material, however, the following information
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needs highlighting: Norway imports a substantial amount of phosphates (94,000 tons P/yr) for
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the production of mineral fertilizers to primarily serve the international market.14 This, however,
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was not included in the study because these large trade flows mask subtle changes within
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domestic consumption and, here, we focus on analyzing scenarios for handling domestically
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produced avoidable food waste (AFW). Therefore, only P and PE for domestically produced and
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consumed fertilizer was included. More information related to the trade of P for mineral fertilizer
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production in Norway can be found in Hamilton and colleagues.14 The PE for fertilizer
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production was based on Kongshaug and colleagues16 and was calculated using data for the
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nitrophosphate process, the P fertilizer production route both used and developed in Norway, and
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the PE needed for mining phosphate rock (excluding transportation). Net primary production
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(NPP) was included for the energy balance and was calculated using mass balance. Additionally,
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we assumed that returned secondary P to agricultural soils displaces the demand for mineral P
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fertilizers. This implies that secondary P has the same quality or plant availability as primary P,
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which, in reality, is not the case. P quality varies widely amongst secondary products14 however,
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we assumed 100% mineral fertilizer equivalents for secondary P in order to analyze the best case
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scenario. Norway has large aquaculture and fisheries sectors that significantly influence the
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Norwegian P cycle.14 These sectors were not included in the analysis due to the same reasons as
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for mineral P fertilizer trade. Norwegian fish production primarily serves the international
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market and, thus, the large trade flows mask changes within domestic consumption. Therefore, in
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this model, domestically consumed fish is included as a food import.
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Because definitions related to food waste lack harmonization throughout literature, the following
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paragraphs clarify how we use these terms in our work. AFW follows the definition of Hanssen
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and colleagues17, “all edible food that should have been eaten but due to different reasons cannot
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be sold or utilized, both before it is discarded and ends up as waste and when it has become
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waste.” AFW does not include unavoidable food waste such as bones, shells, peels and
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residues.18,19 AFW data were based off of Hanssen and Schakenda19 and were calculated for the
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following steps in the food value chain: food processing, wholesale, retail and human
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consumption. These values were used as a basis for conducting scenario work.
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In this work, AFW prevention is defined as measures taken to reduce the quantity of avoidable
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food waste which in turn reduces the environmental impacts of food production.3 In effect, this
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means improving the material and energy efficiency of the system by using less resources to feed
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a given population. AFW recycling, on the other hand, refers to the production of compost,
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bioenergy, animal feed or secondary fertilizers from food waste.20
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2.3. Scenarios. Two scenarios were developed to quantitatively compare the theoretical
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maximum system-wide energy and phosphorus resource savings of AFW recycling (S1) and
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AFW prevention (S2) with a reference baseline scenario (S0). For S1, the transfer coefficients
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from the baseline model were held constant and all AFW was assumed to be recycled through
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the production of biogas with subsequent use as secondary fertilizers. Food waste can technically
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be recycled in a number of ways including use as animal feed or compost, however, due to the
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strict restrictions on feed for animals and compost giving minimal benefits21, these options were
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not explored. Furthermore, all returned P was assumed to displace primary P. In reality, this is
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not the case, as the plant availability of secondary products is often inferior compared to mineral
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fertilizers22. Regarding the uncertainty within the scenarios, because the transfer coefficients
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from the base model were held constant, the relative error between the base model and the
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scenarios remained the same.
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S2 was run under the constraint of perfect food utilization, where food demand was equal to food
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supply. The elimination of AFW results in a decreased demand for agricultural land due to lower
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production. This surplus land can be used for various purposes including reducing food imports,
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export oriented agriculture, forestry, infrastructure development and biogas feedstock
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production. We did not analyze the alternative uses for the excess agricultural land in this
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analysis and, thus, assumed no rebound effects from its displacement. AFW was broken down
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based on the fractions that were animal versus plant products allowing for savings to be scaled in
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relation to their relevant process efficiencies. Recycling from S0 was held constant in order to
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analyze pure AFW prevention versus AFW recycling and not a combination of the two. All
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AFW was assumed to be domestically produced and, thus, food trade for human consumption
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was held constant. Due to the low degree of food self-sufficiency, this assumption overestimates
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the impact of the scenarios on Norwegian agriculture. Because Norway’s food production is
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heavily oriented towards animal products, where the impacts are higher, this overestimation is
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larger for plant than animal products.
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2. RESULTS
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The DM mass balance for the Norwegian agriculture-based food processing, human consumption
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and waste subsystems (figure 1) show that cumulative AFW (in red) accounts for roughly 17%
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of sold food. The largest losses of AFW were found at human consumption with 92 kt DM/year.
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In fact, these losses were more than AFW from food processing, wholesale and retail combined
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(63 kt DM/yr) and roughly 10% of total consumer purchased food. Food processing, retail and
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human consumption were significant contributors to AFW, with 33 kt DM/ yr, 29 kt DM/yr and
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92 kt DM/yr respectively, while losses from wholesale were comparably negligible (1 kt DM/yr).
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With approximately 1100 kt DM/yr of food sold by wholesale and imports of 780 kt DM/yr, the
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degree of self-sufficiency lies at about 30% in Norway. However, domestically produced food
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has a high share of animal products and is exported in large amounts (360 kt DM/yr).
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For the baseline energy scenario (figure 2), we found the largest energy flows were grazing (41
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PJ/yr), net inputs to plant production (32 PJ/yr) and manure (26 PJ/yr). Additionally, these
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results highlighted that about 80% of domestically produced plants is used for animal feed (17
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PJ/yr) while 20% of produced plants go to human consumption (4 PJ/yr). The highest energy
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recovery potential was found to be manure at 26 PJ/yr, as this secondary resource can be used as
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biogas feedstock. In terms of PE, the cumulative baseline PE was 14.5 PJ/yr and this was small
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as compared to the biomass flows. However, in terms of waste, cumulative PE was more than
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double exported waste and waste to incineration combined (7 PJ/yr). Additionally, compared to
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cumulative AFW, cumulative PE was about three and a half times as large with 14.5 PJ/yr versus
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4 PJ/yr. The largest PE consumer was food processing at 10 PJ/yr.
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The AFW recycling scenario only significantly affected a few flows relative to the base scenario.
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Organic waste for biogas production increased from 1 PJ/yr to 5 PJ/yr due to the diversion of
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AFW to biogas production. Similarly, produced biogas increased from 1 PJ/yr to 4 PJ/yr and the
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return of residuals to agriculture increased from 0.4 PJ/yr to 0.9 PJ/yr. While the relative return
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of biogas residuals increased substantially from the base scenario to the AFW recycling scenario,
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this had a minimal effect on the net inputs to plant production (32.3 PJ/yr versus 32.0 PJ/yr). The
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increase in biogas production was coupled with an increase in biogas PE of 0.4 PJ/yr to 1 PJ/yr
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and cumulative PE from 14.5 PJ/yr to 15.2 PJ/yr.
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The AFW prevention scenario resulted in considerable savings relative to the base scenario. The
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net inputs to plant production reduced by 19% from 32 PJ/yr to 26 PJ/yr. Similarly, plants for
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human consumption reduced from 4 PJ/yr to 1 PJ/yr. This was due to the high fraction of plant
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products in AFW, with the largest fraction of AFW being fresh fruit and vegetables, and the
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assumption that trade was held constant. Plants for feed reduced by 12% (17 PJ/yr to 15 PJ/yr)
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and animal products decreased by 9% (11 PJ/yr to 10 PJ/yr). Processing wastes decreased from 2
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PJ/yr to 1 PJ/yr and organic household waste decreased from 11 PJ/yr to 2 PJ/yr. This was due to
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the drastic decrease in food waste as a result of prevention measures. While produced biogas
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decreased substantially from 1 PJ/yr to 0.2 PJ/yr, this was met with a decrease in cumulative PE
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from 14.5 PJ/yr to 13.6 PJ/yr.
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For the baseline P scenario (figure 2), we found that the largest P flows were manure (12 kt
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P/yr), grazing (7.8 kt P/yr) and imported mineral P (7.8 kt P/yr). Similar to energy, the results
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showed the high fraction of produced plants for animal husbandry feed (4.2 kt P/yr) versus plants
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for human consumption (0.9 kt P/yr). The flow with the highest theoretical potential for P
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recovery is manure, however, this is unfeasible due to the spatial distribution between P deficits
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and P surpluses as discussed in Hamilton and colleagues14, requiring long and costly transport
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distances. The net addition of P to agriculture soil stocks (NAS) for the baseline was determined
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to be 10 kt P/yr.
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The AFW recycling scenario resulted in a 6% decrease of imported mineral P (7.8 kt P/yr to 7.3
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kt P/yr) due to the return of P in biogas residuals that displaced primary P consumption (increase
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from 0.4 kt P/yr to 0.9 kt P/yr). This resulted in a 17% decrease of NAS from 10 kt P/yr to 8.3 kt
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P/yr. Organic waste to biofuels increased from 0.4 kt P/yr to 1 kt P/yr. Exported waste decreased
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relative to the base scenario from 1.7 kt P/yr to 1.6 kt P/yr and waste to incineration/landfill
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decreased from 2.7 kt P/yr to 2.4 kt P/yr.
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The AFW prevention scenario resulted in a substantial reduction in the throughput of P.
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Imported mineral P decreased by 14% (7.8 kt P/yr to 6.7 kt P/yr) due to the reduced demand for
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plant products for human consumption (from 1 kt P/yr to 0.5 kt P/yr) and animal husbandry feed
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(4.3 kt P/yr to 4.0 kt P/yr). Similarly, grazing decreased by about 4% (7.8 kt P/yr to 7.5 kt P/yr)
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and manure decreased by 8% (12 kt P/yr to 11 kt P/yr) due to the reduced demand for animal
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products. While the return of food processing waste and sewage sludge decreased from 1.8 kt
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P/yr and 1.3 kt P/yr and residuals from 0.4 kt P/yr to 0.3 kt P/yr, this was met with as much as a
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33% reduction in the NAS (10 kt P/yr to 6.7 kt P/yr). Additionally, exported waste and waste to
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incineration/landfill decreased by 27% (4.4 kt P/yr to 3.2 kt P/yr, combined).
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The domestic energy requirement was higher for the AFW recycling scenario, closely followed
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by the baseline scenario while the AFW prevention scenario most effectively reduced cumulative
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energy demand. However, the domestic energy requirement indicator needs to be interpreted
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(figure 4) with caution, because it does not include PE for waste incineration, landfill and waste
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export. Overall, for both energy and P, AFW prevention resulted in the lowest impacts. The
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primary reason for this was the reduced demand for animal and plant products, resulting in both
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reduced upstream production impacts and downstream waste treatment impacts. Combined, this
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resulted in savings beyond the gains from producing secondary products (biogas and secondary
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fertilizer from sewage sludge and food processing wastes) from AFW recycling. Therefore,
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while AFW recycling does provide savings relative to the baseline, the effect is minimal. Based
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on our results, AFW prevention is preferable for the highest reductions in overall energy and P
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impacts compared to the present.
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4. DISCUSSION
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To our knowledge, this study presents the first quantitative comparison of food waste recycling
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versus food waste prevention from both an energy and phosphorus perspective using a systems
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approach. In this work, we have used a multi-layer method to assess how these strategies
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propagate throughout the entire agriculture system of Norway.
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4.1. Analytical Framework. While the study makes use of mass and energy balance principles,
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it is still limited by data availability, particularly within the waste sector. Data gaps in the waste
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sector could be due to unreported waste statistics which could have subsequently lead to the
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large mass balance inconsistencies (MBI). The P system was primarily based on Hamilton and
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colleagues14, therefore, more information regarding the P uncertainty can be found there. One
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notable uncertainty for P, however, is related to the NAS calculations. NAS was calculated via
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mass balance and this approach includes a significant amount of uncertainty, as hidden waste
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flows could be masked. In addition, the assumption that secondary products equal 100% mineral
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fertilizer equivalents significantly influences the NAS calculation because this assumption
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implies that plants can utilize returned secondary P products. In reality, this is not the case as the
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plant availability of secondary products is variable, often with high fractions of plant unavailable
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P.14 Therefore, the NAS P savings for the AFW recycling scenario relative to the base scenario
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are likely overestimated.
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Regarding the energy system, data gaps were most prevalent for PE. Data for slaughterhouse PE,
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for example, were unavailable which resulted in an underestimation of the PE for meat products.
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In addition, transportation was not included in this model due to data gaps. According to Pöschl,
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Ward, and Owende23, the transportation and collection of biogas feedstock in the form of
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municipal solid waste (which includes food waste) accounts for a substantial amount, 32% in
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their case, of the total PE required for biogas production.
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underestimations within PE consumption, we hypothesize that the net gains for biogas
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production in the AFW recycling scenario are overestimated and, if transport and other process
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energies were accounted for, the net gains would either be lower or even negative.
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An additional limitation of the model is the trade assumptions. We assumed that there was no
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change in imports/exports for the scenarios and, thus, held trade constant. This was due to a lack
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of understanding regarding the origin of the wasted food, as these values were aggregated with
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domestically produced food waste, as well as a lack of knowledge regarding the demand,
Considering the above
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consumption and losses of P abroad. Without these insights, the impacts were assumed to occur
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within Norway, when, in reality, the savings are split between Norway and abroad.
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Nevertheless, despite these limitations and the aforementioned data gaps, the overall modeling
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approach was robust. The layering approach allowed for mass balance to be maintained within
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and throughout the layers, allowing for cross-checking between the mass, nutrient and energy
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layers. This layered approach enabled us to simultaneously analyze impacts for different
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environmental indicators which greatly increases its policy relevance. Therefore, while the
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developed model had limitations, it provided enough detail to confidently conclude that, overall,
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AFW prevention has a much higher savings potential as compared to AFW recycling. We cannot
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conclude, however, on where these savings may occur, either in Norway or abroad, as the
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emissions embodied in trade are poorly understood.
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4.2. AFW Recycling vs AFW Prevention. There is a tendency to employ AFW recycling due to
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its ability to produce a marketable, value added renewable transportation fuel that can displace
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fossil fuels.24 In this study, however, we found that the incurred upstream costs for AFW
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recycling via biogas production (e.g. the PE for the production of mineral fertilizer, food
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processing, storage, etc. totaling 3 PJ/yr) quickly diminish the net benefits of producing biogas (4
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PJ/yr of produced biogas with net energy benefits equaling less than 1 PJ/yr). According to the
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Ministry of Petroleum and Energy25, the Norwegian energy demand for transportation was 62
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TWh in 2010. If we consider the total theoretical maximum output of biogas from avoidable food
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waste [not the net energy benefits], AFW recycling still only represents about 2% of Norway’s
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energy demand for transportation. Therefore, the use of agriculture and food to address energy
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needs can only contribute to a limited extent and, furthermore, AFW prevention strategies result
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in overall lower cumulative impacts for energy (figure 4).
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Regarding P, through this study, we have shown that agriculture plays a central role in the
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consumption and losses of P and that the use of agriculture to produce wasted food significantly
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exacerbates P systems. Our results indicate that this is even the case when secondary P from food
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waste recycling is returned to agriculture, as the upstream consumption and losses of P are not
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made up for by the return of secondary P, even when assuming the theoretical maximum savings
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of 100% recycling and 100% mineral P substitution. Currently, P recycling from Norwegian
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biogas production is far from optimized which is primarily due to the lack of a market for
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secondary fertilizer, as primary P fertilizer remains economical and the general attitude towards
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secondary fertilizer is negative.26 In order to determine the extent to which AFW recycling and
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AFW prevention can address the consumption of primary P, one can look into the fraction of
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mineral P that is displaced through these measures. Norway’s average 2009-2011 demand for
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mineral P in the form of inorganic fertilizers was about 8 kilotons P/yr. With theoretical
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maximum food waste recycling, the demand decreased by 8% through the return of secondary P
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products. When preventing avoidable food waste, however, the demand decreased by 21%.
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Therefore, from this study, we show that AFW recycling provides minimal P and energy savings,
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while the benefits for P and energy increase substantially when using a preventative approach.
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AFW recycling is focused on downstream, end-of-pipe actions while prevention behaves as a
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multiplier with significant upstream and downstream savings.
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4.3. Policy implications. We have found that overall P and energy use can be reduced more
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effectively with prevention strategies as compared to recycling strategies and that prevention
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strategies are particularly important from a P perspective. Food waste recycling only provided
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minimal energy returns, when considering upstream consumption. While food waste prevention
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did significantly reduce biogas production amounts, this was almost met with upstream
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reductions in PE and more than met with reductions in primary production (food and feedstuff),
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making the total throughput of energy lower. Therefore, our work shows that policy and
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incentives should prioritize food waste prevention and that most savings can be had through a
338
combination of both prevention and recycling.
339
When developing strategies to address food waste, it is important that policies do not begin with
340
end-of-life measures (EOL) first, as is the case in Norway today. There is a risk that if EOL
341
measures are prioritized, infrastructure (e.g. biogas facilities) develops to reflect this and creates
342
a lock-in effect. Future food prevention measures could then, for example, result in
343
overcapacities for biogas facilities and lead to lobbies against waste reduction, as the biogas
344
plants are reliant on the production of food waste to operate. Therefore, it is important to address
345
both food waste prevention and food waste recycling, with a prioritization for prevention due to
346
its ability to provide the most savings.
347
While Norwegian endeavors to reduce food waste do exist18, clear goals and targets for
348
addressing food waste at the national level have not been set.11 According to the High Level
349
Panel of Experts on Food Security and Nutrition27, in order for actors within the food chain to
350
effectively reduce food waste, coordinated policies and regulation frameworks are essential. In
351
Norway, however, current strategies for handling food waste primarily revolve around biogas
352
production despite only providing minimal benefits and negatively impacting other resources.8,12
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In order to address this, it is important to first understand why this is the case. Why is our current
354
system set up in a manner that results in negative benefits?
355
4.3.a. Why is the current structure this way? According to the House of Lords24, the answer lies
356
in economics. Our current society is shaped to favor the throughput of materials, with the
357
production of marketable goods, e.g. food and biogas, providing profitability for businesses.
358
Because of this, there is a ‘clear temptation’ to incentivize and prioritize the use of food waste
359
for energy recycling over food waste prevention. This can be seen in the 2015 Norwegian state
360
budget that funneled 10 million Norwegian Kroner (~1.5 million USD) to biogas pilot projects
361
and research in order to fulfill Norwegian biogas strategy targets.12,28 While it is important to
362
clarify that this biogas strategy does discuss the need to utilize other feedstock apart from food
363
waste, newly built infrastructure, e.g. the Romerike, Hadeland and Ringerike biogas facilities
364
opened in 2012 and 2014, are designed to receive and handle, in total, 70,000 tons of
365
organic/food waste. Together, these two facilities have received 9.3 million Norwegian Kroner
366
(~1.3 million USD) in public funding. For comparison, merely 700,000 Norwegian Kroner
367
(~100,000 USD) from the Norwegian budget went to the largest food waste prevention project,
368
ForMat.29
369
One reason for the prioritization above, could be due to a lack of a systems approach during
370
policy development. Fragmented analyses, without a systems context, result in fragmented policy
371
recommendations. If one only analyzes methods for handling wastes (end of pipe), without
372
regards to upstream impacts, results will often reflect the benefit of producing secondary value
373
added goods such as biofuels. Only through the use of a systems approach that includes all
374
upstream impacts and alternative scenarios, can system’s-wide accumulated costs be weighed
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against its benefits with room for implementing unforeseen measures. With narrow system
376
boundaries, even policies meant to increase sustainability get skewed. A multi-indicator
377
analytical framework approach would help to avoid such situations.
378
4.b. How can our results inform policy? While our model does point to the largest contributors to
379
avoidable food waste within the system, e.g. human consumption and food processing, it is
380
important to not mix up the source of avoidable food waste with the cause, as often the cause and
381
the source of food waste are far removed from one another. An example of this is reduced shelf
382
life due to mishandling produce during harvest and packaging.27 In this case, while the food
383
waste occurs downstream in retail, it is the upstream mishandling during processing that causes
384
it. Another example includes the lack of knowledge regarding ‘best-by date’ labels. Because
385
information related to the meaning of these labels is difficult to access and the current labeling
386
system is confusing, consumers often mistake “use by dates”, which refer to highly perishable
387
goods that pose a risk to human health if consumed after a certain period, with “best before
388
dates” which merely indicate a food’s reduction in quality but not safety.30 This results in a
389
substantial amount of food waste at the household, while the cause is upstream during the
390
labeling and sale of food in wholesale and retail.
391
Therefore, due to the lack of information flows, our research cannot pinpoint exactly which
392
processes and which mechanisms should be used to prevent food waste most effectively. It can,
393
however, be a first step to show the urgency for a macro level preventative policy approach.
394
Here, we have presented, from a P and energy standpoint, the results of a best case prevention
395
scenario, and in order to approach this ideal, we need a coordinated preventative policy.27 A
396
recommended starting point would be to reconsider the economic incentives in place for
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recycling food waste and, instead, implement market-based instruments, in form of e.g. tax
398
exemptions or compensation mechanisms, that incentivize the prevention of wasted food in all
399
sectors of the value chain. Other interesting methods to explore include suasive approaches that
400
encourage improvement through the distribution of information and regulatory approaches, that
401
require change by enforcing penalties for non-compliers.31
402 403 404
ASSOCIATED CONTENT
405
Supporting Information. Detailed description of the system definition, analytical solutions to
406
the system, data sources. This material is available free of charge via the Internet at
407
http://pubs.acs.org.
408
AUTHOR INFORMATION
409
Corresponding Author
410
*(H.A.H) Phone: +47-450-02105; email:
[email protected] 411
Present Addresses
412
† Industrial Ecology Programme and Department of Energy and Process Engineering,
413
Norwegian University of Science and Technology, NO-7491, Trondheim, Norway
414
Author Contributions
415
The manuscript was written through contributions of all authors. All authors have given approval
416
to the final version of the manuscript.
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Notes
418
ACKNOWLEDGMENTS
419
We would like to acknowledge the institutions and contacts that helped to provide data and
420
information.
421
ABBREVIATIONS
422
AFW, avoidable food waste; DM, dry matter; GE, gross energy; HHV, higher heating value; kj,
423
kilojoules; MBM, meat bone meal; NPK fertilizer, nitrogen phosphorus potassium fertilizer;
424
NPP, net primary production; SFA, substance flow analysis; P, phosphorus; PE, process energy;
425
WWT, wastewater treatment.
426
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Mitigation of Food Wastage: Societal costs and benefits; Food and Agriculture Organization of the United Nations, 2014; http://www.fao.org/3/a-i3989e.pdf.
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Guidelines on the preparation of food waste prevention programmes; European Commission DG ENV: Paris, France, 2011; http://ec.europa.eu/environment/waste/prevention/guidelines.htm.
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Cordell, D.; Drangert, J.-O.; White, S. The story of phosphorus: Global food security and food for thought. Glob. Env. Chang. 2009, 19, 292–305.
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Toolkit: Reducing the Food Wastage Footprint; Food and Agriculture Organization of the United Nations, 2013; http://www.fao.org/docrep/018/i3342e/i3342e.pdf.
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Roadmap to a Resource Efficient Europe; European Commission: Brussels, Belgium, 2011; http://ec.europa.eu/environment/resource_efficiency/about/roadmap/index_en.htm.
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Brunner, P. H.; Fellner, J. Setting priorities for waste management strategies in developing countries. Waste Manag. Res. 2007, No. 25, 234–240.
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(8)
Potensialstudie for biogass i Norge [Norway’s biogas potential]; Østfoldforskning and Norwegian University of Life Sciences, 2008; http://www2.enova.no/minas27/publicationdetails.aspx?publicationID=373.
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(9)
Biogas and waste management in Norway; Avfall Norge, 2012; http://www.ieabiogas.net/files/daten-redaktion/download/publications/workshop/10/Henrik Lystad_Biogas and Waste Management in Norway.pdf.
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The Norwegian Environmental Agency, Biogass reduserer klimagassutslipp [Biogas reduces greenhouse gas emissions]. 2013. http://www.miljodirektoratet.no/no/Nyheter/Nyheter/Oldklif/2013/April_2013/Biogass_reduserer_klimagassutslipp_/ (accessed May 20, 2002).
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Avfall Norge, Statsbudsjettet 2015 [The State Budget 2015]. 2014. http://www.avfallnorge.no/aktuellavfallspolitikk.cfm?pArticleId=34978&pArticleCollecti onId=3653 (accessed Feb 1, 2015).
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Underlagsmateriale til tverrsektoriell biogass - strategi; Klima- og ForurensningsDirektoratet [The Climate and Pollution Agency]: Oslo, Norway, 2013; www.miljodirektoratet.no/old/klif/publikasjoner/3020/ta3020.pdf.
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Ruter, Nå kjører bussen på ditt bananskall [Now we can drive from your banana peels]. 2015. https://ruter.no/om-ruter/presse/pressemeldinger/na-kjorer-bussen-pa-dittbananskall/ (accessed Jun 18, 2015).
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Hamilton, H. A.; Brod, E.; Hanserud, O. S.; Gracey, E. O.; Vestrum, M. I.; Bøen, A.; Steinhoff, F. S.; Müller, D. B.; Brattebø, H. J. Ind. Ecol. 2015.
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(15) Brunner, P. H. Substance Flow Analysis as a Decision Support Tool for Phosphorus Management. J. Ind. Ecol. 2010, 14 (6), 870–873.
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Phosphate fertilizers. Ullman’s Encyclopedia of Industrial Chemistry [Online]; Wiley, Posted March 26, 2014. http://onlinelibrary.wiley.com/doi/10.1002/14356007.a19_421.pub2/abstract (accessed Jan 15, 2015).
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Food Wastage in Norway: Status and Trends 2009-13; Østfoldforskning [Ostfold Research], Kråkerøy, Norway, 2013; http://www.fao.org/fsnforum/cfs-hlpe/sites/cfshlpe/files/resources/Food%20Waste%20in%20Norway%202013%20%20Status%20and%20trends%202009-13.pdf.
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Matsvinn i Norge: Status og utviklingstrekk 2009-13 [Food waste in Norway: Status and Trends 2009-13]; Østfoldforskning [Ostfold Research]: Format; Kråkerøy, Norway, 2013; http://ostfoldforskning.no/uploads/dokumenter/publikasjoner/713.pdf.
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Nyttbart matsvinn i Norge 2011 [Usable food waste in Norway 2011]; Østfoldforskning [Ostfold Research]; Kråkerøy, Norway, 2011; http://ostfoldforskning.no/uploads/dokumenter/publikasjoner/707.pdf.
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USDA, U.S. Food Waste Challenge. 2013. http://www.usda.gov/oce/foodwaste/faqs.htm (accessed Jan 1, 2015).
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Utilisation of co-streams in the Norwegian food processing industry: A multiple case study; Bioforsk; Ås, Norway, 2014; http://www.bioforsk.no/ikbViewer/Content/110773/Bioforsk RAPPORT 9 (82).pdf.
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Brod, E.; Haraldsen, T. K.; Breland, T. A. Fertilization effects of organic waste resources and bottom wood ash : results from a pot experiment. 2012, No. April, 332–347.
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Pöschl, M.; Ward, S.; Owende, P. Evaluation of energy efficiency of various biogas production and utilization pathways. Appl. Energy 2010, 87 (11), 3305–3321.
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(24)
Counting the Cost of Food Waste: EU Food Waste; 10th Report of Session 2013-14; House of Lords, European Union Committee: London, UK, 2014; http://www.publications.parliament.uk/pa/ld201314/ldselect/ldeucom/154/15402.htm.
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(26) Operations & Experience of the Ecopro Co-digestion Plant; Cambi AS: Asker, Norway, 2008.
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(27)
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(28) Regjeringen [The Norwegian Government], 10 millioner til pilotprosjekt for biogass [10 billion Norwegian Kronor for biogas pilot project]. 2015. https://www.regjeringen.no/nb/aktuelt/10-millioner-til-pilotprosjekt-forbiogass/id2408630/ (accessed Apr 18, 2015).
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(29)
Regjeringen [The Norwegian Government], Vil redusere matsvinnet [Want to reduce food waste]. 2014. https://www.regjeringen.no/no/aktuelt/Vil-redusere-matsvinnet/id764629/ (accessed May 20, 2015).
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(30)
How to apply date labels to help prevent food waste; Waste and Resources Action Programme (WRAP): Banbury, UK, 2012. http://www.wrap.org.uk/sites/files/wrap/Info%20Sheet%20Date%20Labels%20final.pdf.
Food losses and waste in the context of sustainable food systems; The High Level Panel of Experts on Food Security and Nutrition: Rome, Italy, 2014; http://www.fao.org/3/ai3901e.pdf.
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(31)
Stimulating social innovation through policy measures; Food Use for Social Innovation by Optimising Waste Prevention Strategies (FUSIONS); 2014. http://www.eufusions.org/index.php/publications?download=4:fusions-definitional-framework-for-foodwaste-executive-summary.
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Other veg. waste 6 MBM 46 Poultry waste 1
Donations 6.4%
21
33 1000
14
8
12
81
130 92
Organic waste collection
110
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180 31 50
Waste management 150
Waste to inc./ landfill 180
Digestate to fertilizer 34 Waste to bioenergy 50
Incineration/landfill
20
Secondary fertilizer
Exported sludge
WWT
Respiration
Exported food
480
Biogas production
Sewage sludge
Sold food
Org. waste to bioenergy
29
Org. waste to agriculture
1
Human consumption
Secondary feed products
Imported food
Wastewater
Org. waste to incineration/landfill
900
Retail 900
Service waste
Carrot waste 0.7 Potato waste 3 Food products
Household waste
Meat products 72 Eggs and dairy 210
300
Avoidable Food Waste
5
Avoidable Food Waste
240 4
Exported waste
220
Fruit 150
Avoidable Food Waste
Plant products Other veg.
780
Proc. waste to fertililizer
Animal products Carrots
26
Proc. waste to inc./landfill
Eggs and milk
Proc. waste to bioenergy
Potatoes 13
Exp. proc. waste
Animal fat
Avoidable Food Waste
0.7
Feed M
Other veg. to feed
Wholesale M
Potato waste to feed 7
Waste M
210
Food Processing
Exported food
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110
61 90
Rejects 0.4
Biogas 16
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Animal Husbandry
Food Processing
Animal prod.
1
0.1
Digestate 0.4
Heat 0.1
4
Waste to incineration/landfill
4
1
Organic waste Wast ewater
10
2 3
Wast e
0.2
0.3
ACS Paragon Plus Environment
0.1
Digestate
FP waste & sewage sludge
26
Respiratory heat
10
Heat
Secondary Feed 0.4
Respiratory heat
24
2.6
Processing waste 1
3
1
0.1
1
Heat Rejects/Loss Digestate
Exported Waste
2
2
Biogas Production
Waste Management
Human Consumption
30
Heat
Heat
Exported Waste 3
3
FP waste & sewage sludge 2
FP waste & sewage sludge
22
Food Processing
1
Plants for food
Biogas
Animal and plant prod. 9
37
Plants for feed 15
1
Respiratory heat 26 26
Respiratory heat
10
0.5
Secondary Feed
Animal Husbandry Animal prod.
Grazing
5
Exp. Imp. food food
10
PE
3
13
Plant production
Manure
Wast e
2
26
Imp. feedstuff PE
0.8
0.2
26
Respiratory heat
3
Heat
Heat
1
Plants for food
Mineral
6 3
35
17
4
NPP fertilizer PE PE
10
Processing waste
Organic waste Wast ewater
Waste to incineration/landfill
Plants for feed
Heat
S1: AFW Recycling
Animal an d plan t prod. 13
Biogas Production
Waste Management
Human Consumption
11
41
Manure
S2: AFW Prevention
Food Processing
Animal prod.
Biogas
PE
1.5
3
Animal Husbandry
Grazing
Exp. Imp. food food
Exported Waste 1.2
14
Plant production
PE
Waste to incineration/landfill
PE
1
22
Imp. feedstuff
7
PE
10
Mineral fertilizer PE
1
26
0.1
32
NPP
Respiratory heat
3
Heat
Heat 1
Manure Manure
Secondary Feed 0.5
4
Plants for food
Wast e
6 3
Processing waste 2
35
Heat
Plants for feed 17
Organic waste Wast ewater
Biogas Production
Waste Management
Human Consumption
Animal and plant prod. 13
41
Biogas
PE
11
7
S0: Baseline
Grazing
22
10
Plant Production
Exp. Imp. food food
PE
3
1
0.2
32
14
Imp. feedstuff PE
Mineral
NPP fertilizer PE PE
7
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Environmental Science & Technology Imp. feedstuff
4.9
Animal prod. 4.8
Soil Stock
Human Consumption
Animal prod. 4.5 4
Grazing
7.5
Soil Stock
Manure 11
Animal and plant prod.
Organic waste 1.5 Wast ewater 2.6
2.7
Waste
Rejects/loss 0.1 Residuals 0.9
Biogas Production 0.4
2 1.5 1.8
Plants for food
Processing waste
Secondary Feed 0.02
Runoff 1
0.5 6.7
P accumulation
Fertilizer
Plants for feed
Waste Management
ACS Paragon Plus Environment
Rejects/loss 0.03 Residuals 0.4
Food Processing
1.4
Animal Husbandry
4.9
0.8
5.8
0.2
6.7
S2: AFW Prevention
Exp. Imp. food food
Imp. feedstuff
Plant production
2.4
2
Manure 12
Imp. mineral P Deposition
1
2.6
Exported Waste
1.2
Plants for food
Runoff
P accumulation
8.3
Processing waste
Waste
2.6
1.8
7.8
Wast ewater
2.5
FP waste & sewage sludge
Grazing
Organic waste Animal and plant prod.
Biogas Production
FP waste & sewage sludge 1.3 Discharge 0.1 Waste to incineration/landfill
4.2
Waste Management
Secondary Feed 0.03
S1: AFW Recycling
Plants for feed
0.9
Rejects/loss 0.05 Residuals 0.4
FP waste & sewage sludge
Human Consumption
Exported Waste 1.6
Food Processing
0.8
Animal Husbandry
Animal prod. 4.8 Fertilizer
1.7
1.8
2
Exp. Imp. food food
6.3
Plant production
0.4
2.6
12
Imp. feedstuff
0.2
7.3
Imp. mineral P Deposition
Biogas Production
Waste
2.6
Secondary Feed
Soil Stock
Manure
2.5
Wast ewater
0.03
Plants for food
Runoff 1.2
P accumulation
10
Processing waste
4.9
S0: Baseline
0.9
Organic waste Animal and plant prod.
Fertilizer Plants for feed 4.2 7.8 Grazing
Waste Management
Human Consumption
Exported Waste
Food Processing
Discharge 0.1 Waste to incineration/landfill
Animal Husbandry
Discharge 0.1 Waste to incineration/landfill
Plant production
Exp. Imp. food food 0.8
6.3
0.2
7.8
Imp. mineral P Deposition
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Animal Husbandry Animal products
Plants for feed
Food Processing
Imp. food
Imp. feedstuff
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Waste Human Consumption Management
Exp. food
Organic waste
Animal and plant prod.
Wastewater
Processing waste
Manure
ACS Paragon Plus Environment
Exported Waste
Soil Stock
Food Waste Recycling Strategies Biofuel residuals
Food Waste Prevention Strategies
Runoff
Plants for food
FP waste & sewage sludge
Grazing
Waste to incineration/landfill
Plant production
NAS
Deposition
Imp. P fertilizer
Environmental Science & Technology