Methodology

waste reduction and valorization under consideration of market and trade feedbacks, and to identify synergies and tradeoffs between food waste reduction strategies (Goossens et al., 2019). With this study, we contribute to existing research by jointly assessing food waste reduction and valorization and by investigating sustainability tradeoffs at food system level.

theory (Britz and Witzke, 2014). The consumption side is represented by an average national consumer. Trade flows are modelled in a two-stage demand system which differentiates domestic sales and imports (Armington, 1969).

This global model is linked to regional programming models for EU regions maximizing farm income subject to market prices. The availability of land, compliance with agricultural policies, and the interplay of soil nutrient needs, feed requirements in line with animal nutrition, and livestock production serve as boundary conditions for EU agricultural production in the modelling system. Environmental indicators (Section 3.6) are calculated for the scenario-specific agricultural production settings (Britz and Witzke, 2014; Leip et al., 2015). Further details on the modelling setup are provided in Appendix C.

3.3.2 Consumer food waste representation in the Baseline

Food group specific consumer food waste shares in our CAPRI Baseline are informed by existing research for European countries (Vanham et al., 2015) and other world regions (FAO, 2011). The food group specific waste shares from FAO (2011) only consider edible waste and report meat related waste on a carcass weight basis (Gustavsson et al., 2013). Thus, we recalculate these waste shares given the information regarding avoidable and unavoidable waste in Vanham et al. (2015). Consequentially, we end up with a set of food group and world region specific waste shares that differentiate avoidable and unavoidable waste parts.

We interpret avoidable food waste as food that is or was edible for humans, in contrast to inedible food parts like e.g., some fruit kernels, which we refer to as unavoidable food waste. We acknowledge prevailing differences in perceptions of edibility (FLW Protocol, 2016), but cannot account for this given the level of product aggregation in the model. Consumer food waste captures retail, services and household food waste, which is not distinguished in CAPRI. Lastly, we consider recent evidence by Verma et al. (2020) who reveal considerable underestimation of consumer food waste in previous research. Therefore, we align wasted calories to represent the relation to affluence estimated by Verma et al. (2020) while keeping the contribution of food groups and the distribution of avoidable versus

unavoidable waste as previously outlined (for implementation details refer to Appendix C). Historical food demand in CAPRI is informed by available food per capita provided by Eurostat and FAO food balance sheets which includes waste at the consumer stage (FAO, 2001). We convert available food quantities to calories and apply the previously outlined steps to distinguish waste from intake shares. We are aware of the roughness of this approach considering likely if not obvious differences in calorie contents for avoidable and unavoidable food waste. Food waste collection and treatment are yet beyond the boundaries of the modelling system (Figure 3.6 in Appendix C).

3.3.3 FWcut scenario – reducing avoidable consumer food waste In our food waste scenarios we test two potential EU policies. First, we simulate a successful food waste reduction campaign (e.g., an EU wide information campaign about food waste impacts) having resulted in a 50%

reduction of avoidable consumer food waste (FWcut). We implement this as a preference shift, i.e. halving the purchases of previously wasted but edible food in the Baseline. In the implementation we ensure that food intake does not directly increase as a means of reducing waste, but can only be affected indirectly via market feedbacks. Since the reduction of food waste is implemented as an exogenous shock on the Baseline food waste share, market feedbacks that reduce food prices can partly counteract the reduction of food waste quantities.

3.3.4 FWfeed scenario – valorizing plant-based food waste as pig feed With our second policy scenario, we explore the impact of a change in EU legislation toward allowing and promoting plant-based consumer food waste to be used as pig feed (FWfeed). The available biomass is linked to the food waste arising at the consumption stage within the respective EU member state in the current simulation. Food-specific energy and protein contents available to pig nutrition are aligned to those underlying in van Hal et al.

(2019) (Table 3.2 in Appendix C). In the whole EU, plant-based food waste biomass sums up to 96.000 tons fresh matter in 2030 in this scenario, replacing between 5% and 100% of net energy and between 3% and 100%

of crude protein required for pig fattening across EU member states depending on a country’s food waste composition and pig feed demand in our Baseline. Current pig production systems in the EU do not rely on the use of food waste as feed. Given the novelty of this potential feed product, historic market data are missing for model calibration and simulation procedures. Instead, we assume that political incentives to valorize occurring consumer food waste lead to a complete utilization of available FWF within a country by pig production activities at no input cost for the farmer. In our simplified scenario assessment, FWF is not subject to inter-country trade.

In order to disentangle synergies and tradeoffs, we furthermore assess the two presented policies in combination (FWcombi). The halved available consumer food waste reduces the plant-based food waste biomass available as pig feed. Remaining consumer food waste quantities that are not directed to pig feed are assumed to be handled by existing treatment facilities as in the Baseline, which are outside the model boundaries.

3.3.5 Sensitivity analysis on FWF costs and available quantities We do not account for governmental or technical implementation costs at farm stage related to FWF in the FWfeed scenario. However, we acknowledge FWF costs to be a relevant and uncertain variable in this assessment. Therefore, we explore different levels of arising costs to the farmers in a sensitivity analysis (FWfeedSens). In Japan and South-Korea FWF is delivered at 40–60% of the cost of conventional feed based on commercial blends (zu Ermgassen et al., 2016). Feed costs can be lowered when using left over feed in broiler diets (Cho et al., 2004). Producers tend to be willing to pay only a small price for processed food waste as alternative pig feed due to lower feed conversion ratios than for conventional feed (Spinelli and Corso, 2000). While processing, control and transportation of FWF are not explicitly captured in our model, related costs arising at these value chain steps are implicitly captured in the FWF prices farmers may be facing.

In our FWfeed and FWcombi scenarios we use all potentially available plant-based food waste in a country as feed, but based on real-life examples from Japan and South Korea a more realistic scenario would be to only use

35–45% of the food waste as feed (Ng et al., 2017; zu Ermgassen et al., 2016). In our sensitivity analysis, we therefore also test varying available FWF amounts in combination with different prices. The maximum FWF price we assume equals the average producer price for conventional feed in the 2030 Baseline for each EU member state and is imposed on a net energy basis. Of this maximum (100%) we test further price levels in quantile steps.

The maximum FWF amount is all plant-based food waste biomass as it is available in the FWfeed scenario.

3.3.6 Food system feedbacks

Food system feedbacks resulting from the imposed food waste policy changes are assessed with respect to economic, social and environmental impacts. Economic feedbacks include those on food and feed purchases, production activities, trade, and related prices. It should be noted that consumer prices are generally higher than producer prices as these subsume additional markups along the supply chain. Producers’ income is subject to their production costs, demand for their products, and prices they retrieve from selling on the markets, plus possible revenues from other potential income streams (e. g., tourism, , direct marketing to consumers). Changing prices are of social relevance since they affect the accessibility of food. In addition to food availability (i.e., market food supply in the model), we capture impacts on two food security dimensions. Agricultural emissions to the atmosphere, nitrogen surpluses and agricultural land use changes are the environmental impacts investigated in this study. These impacts are calculated for the projected production activity changes related to the specific scenarios by referring to emission inventories and nutrient balances based on IPCC (2006) and Leip et al. (2011). For comparison purposes, we use the product-based emission coefficients in CAPRI (Weiss and Leip, 2012) to calculate the emission reduction potential in our food waste reduction scenario that could be expected when market feedbacks are not considered. Figure 3.1 provides an overview of the food waste representation, scenario design, and indicators used in this study.