Lost water and nitrogen resources due to EU consumer food waste

We have quantified consumer food waste for the EU-28 with the associated uncertainty. We have analysed average annual values for the period 1996–2005. During this period, the average population of the EU was 487 million. The methodology is presented below and an overview of the workflow of the methodology is given in figure 1, with explanations of the abbreviations used throughout the manuscript provided in table 1.

Zoom In Zoom Out Reset image size

As a first step, average EU food consumption data have been quantified by taking food supply quantity data (FOOD_SUPPLY) of different product groups from the FAO Food balance sheets (FBS) [27]. These provide data on the amount of food that reaches the consumer in private households, as well as that in the non-household sector, i.e. catering establishments, boarding schools, hospitals, prisons, armed forces' bases and other communities. The data are given on an 'as purchased' basis, i.e. as the food leaves the retail shop or enters the household by other means.

Quantities are provided on the basis of 'primary equivalents'. Within the FAO FBS, food data are standardized in that processed commodities are converted back to their 'primary equivalent'. This is for standardization (different countries report their data to the FAO), simplification and limitation of the number of commodities within the FBS. The latter implies that it is beneficial to reduce the amount of data, and therefore the number of commodities involved, to a level and size more suited to analytical purposes. E.g., instead of listing flour of wheat, bread or pasta separately in the FBS, they are quantified as wheat equivalent. Similarly, meat (reaching consumers in many forms, e.g. for chicken as—amongst others—a whole chicken, chicken filet, sausages or chicken nuggets) is quantified as carcass weight in the FBS.

We have estimated food consumption at the point where it reaches the consumer, using a first correction factor (CORR1) which accounts for product primary equivalent conversion (equation (1)). To calculate total and avoidable wasted food quantities from FOOD_SUPPLY, two correction factors are applied. The first factor (CORR1) accounts for product primary equivalent conversions (equation (1)) and the second for food waste (CORR2).

The specific values for CORR1 have been taken from [28]. For example, the CORR1 of wheat equivalent is 0.8, as only 80% of the original wheat weight remains after conversion to wheat flour. In addition to the first factor values listed in the latter publication, 7.4 milk equivalent has been taken for cheese, as obtained from [3], 7 milk equivalent for cream, and 1 milk equivalent for yoghurt. After applying CORR1, food consumption data (FOOD_CONS) have been quantified.

Total and avoidable quantities of wasted food from FOOD_SUPPLY have been obtained by applying a second correction factor for food waste (CORR2) on food consumption quantities (FOOD_CONS). This factor relates either to total food waste (CORR2_TOT) or to avoidable food waste (CORR2_AV), as we have differentiated between total (WASTE_TOT) and avoidable (WASTE_AV) food waste. The latter excludes non-avoidable food waste (WASTE_NA) such as meat bones, egg shells, fruit stones or the peel of certain fruit and vegetables. Avoidable food waste means food that at some point prior to disposal was edible. The relevant equations (2)–(6) are listed in table 2 below.

Table 2.  Equations used to compute waste amounts (equations (1)–(6)) and related resources (equations (7)–(9)).

FOOD_SUPPLY × CORR1 =		FOOD_CONS	(1)
with:	FOOD_SUPPLY =	Food supply quantity as given in FAO Food Balance Sheets (FBS). Food supply is food (in tonnes) reaching the consumer, i.e. in private households, as well as the food service/catering sector
	CORR1 =	Correction factor 1, which accounts for product primary equivalent conversions
	FOOD_CONS =	Food consumption.
FOOD_CONS × CORR2_TOT =		WASTE_TOT	(2)
FOOD_CONS × CORR2_AV =		WASTE_AV	(3)
FOOD_CONS × CORR2_NA =		WASTE_NA	(4)
With:	CORR2 =	Correction factor 2, which accounts for food waste
	CORR2_TOT =	Correction factor 2, which accounts for total food waste
	CORR2_AV =	Correction factor 2, which accounts for avoidable food waste
	CORR2_NA =	Correction factor 2, which accounts for non-avoidable food waste
	WASTE_TOT =	Amount of total consumer food waste
	WASTE_AV =	Amount of avoidable consumer food waste
	WASTE_NA =	Amount of non-avoidable consumer food waste
WASTE_TOT =		WASTE_AV + WASTE_NA	(5)
FOOD_CONS =		INTAKE + WASTE_TOT	(6)
With:	INTAKE =	Amount of food actually consumed
WASTE_AVCORR =		$\frac{{\rm{WASTE}}\_\text{AV}\;}{1-{\rm{CORR}}2\_{\rm{NA}}}$	(7)
with	WASTE_AVCORR =	Corrected amount of avoidable consumer food waste to relate to the resource footprint (WF or NF) of WASTE_AV
	CORR2_NA =	$\frac{{\rm{WASTE}}\_\text{NA}\;}{{\rm{FOOD}}\_{\rm{CONS}}}\;$ as obtained from (1) and (4):
WFcons,agr of WASTE_AV =		$(\frac{{\rm{WASTE}}\_{{\rm{AV}}}_{{\rm{CORR}}}}{{\rm{FOOD}}\_{\rm{CONS}}})$ × WFcons,agr	(8)
with	WFcons,agr =	WFcons,agr of FOOD_CONS
NF of WASTE_AV=		$(\frac{{\rm{WASTE}}\_{{\rm{AV}}}_{{\rm{CORR}}}}{{\rm{FOOD}}\_{\rm{CONS}}})$ × NF	(9)
With	NF =	NF of FOOD_CONS

Based upon FOOD_CONS, total (WASTE_TOT, equation (2)) and avoidable food (WASTE_AV, equation (3)) waste quantities are thus calculated by means of CORR2_TOT and CORR2_AV. Non-avoidable food waste (WASTE_NA) is the difference between WASTE_TOT and WASTE_AV (equation (5)).

CORR2_TOT and CORR2_AV values have been obtained for the product groups from/based upon six selected national studies, i.e.

• the UK [29],
• the Netherlands [30],
• Denmark [31],
• Finland [32],
• Germany [33],
• Romania [34].

For other EU countries, either no data were found or they were unreliable. These values are shown in table 3 below.

Only estimations of household waste have been quantified in these studies. For the non-household (food service/catering) sector part of FOOD_CONS, the same CORR2 values have been taken.

The most detailed assessment was done in the UK [29] for the year 2007 (a field study of over 2000 households), where a distinction is made between avoidable waste, potentially avoidable waste and unavoidable waste. Where purchased amounts of specific products or product groups are missing, DEFRA (the UK's Department for Environment, Food & Rural Affairs) statistics have been used. Apart from avoidable and non-avoidable food waste, the UK study also identifies potentially avoidable food waste. However, in our study we have added this fraction (CORR2_PA) to avoidable food waste (CORR2_AV) for the UK statistics, as other national studies do not account for potentially avoidable food waste.

Table 3 shows that for some product groups detailed statistics are available for several countries, e.g. for cereals, vegetables, fruit, meat, milk and milk products. For other product groups, statistics are only available for selected countries (e.g. alcoholic beverages or crop oils) and for some product groups, no statistics are available (e.g. sugar or stimulants). The data compiled in table 3 show that for all product groups: (1) CORR2_TOT and CORR2_AV values are highest in the UK (except for milk/milk products where Finland has a higher value); and (2) CORR2_AV values are amongst the lowest in Romania. To account for any uncertainty in the estimations, we have assumed that Romania represents the minimum CORR2 values and the UK the maximum values for EU countries, and that all other values are between these two extremes. Schneider [35] has already pointed out that in Europe, the proportion of household expenditure on food is highest in Eastern Europe (e.g. 44.2% in Romania) and that this might be expected to have a significant impact on food waste behaviour. The UK has already been identified as the EU country with the highest per capita consumer food waste [10].

To compute the CORR2_TOT and CORR2_AV distributions for the EU, based upon the six selected national studies, we have made some assumptions. In particular, we have assumed that the correction factors (CORR2_TOT and CORR2_AV) per product group to calculate WASTE_TOT and WASTE_AV are distributed normally. Their means and standard deviations (as shown in table 4 below) were calculated from the available country data (table 3). To calculate these mean EU values from the six national values, these national values are weighted according to national populations. For example, the values for Germany are weighted at 43% and those of the Netherlands at 8%. For sugar, stimulants, spices and alcoholic beverages the associated correction factors were assumed to be uniformly distributed, as detailed data are missing.

In our study, we used the WF concept. For the purpose of water resources management (e.g. in the EU, as in our study), a geographical WF assessment is relevant. It is important to distinguish between the WF of production (WF_prod) and the WF of consumption (WF_cons) of a region [16]. The first refers to the total use of domestic water resources within the region (for producing goods and services for domestic consumption or export). The second refers to the use of domestic and foreign water resources behind all the goods and services consumed domestically.

Dependent on the authors, a WF comprises either three (blue, green and grey) or two (blue and green) components. As defined in [36], green water is the soil water retained in the unsaturated zone, which is formed by precipitation and is available to plants; blue water refers to water in rivers, lakes, wetlands and aquifers. Irrigated agriculture receives blue water (from irrigation) as well as green water (from precipitation), while rain-fed agriculture only receives green water. Thus, the green WF is the rainwater consumed by crops. The grey WF is an indicator of the degree of water pollution [37]. However, many authors perceive this component critically [24, 38, 39].

To quantify the water resources related to these wasted food amounts, we have used the WF of consumption (WF_cons) concept [16, 37]. In particular, we have assessed the green and blue WF_cons of agricultural products (WF_cons,agr) for wasted food. Therefore, the WF_cons,agr refers to the use of domestic and foreign water resources for all agricultural goods that are consumed domestically. The green WF_cons,agr (WF_cons,agr,gn) represents the consumptive rainwater use for the production of crops and animal products which EU citizens consume. Similarly, the blue WF_cons,agr (WF_cons,agr,bl) represents the consumptive use of water from rivers, lakes and groundwater for this production.

As a first step, the WF_cons,agr of FOOD_CONS needs to be quantified. To assess the WF_cons,agr, we have followed the methodology of the Global Water Footprint Standard developed by the Water Footprint Network [36]. National green and blue WF_cons,agr data are accessed from [16, 40] and aggregated to product groups at the EU level. As a result, the blue and green WF_cons,agr (WF_cons,agr,gn and WF_cons,agr,bl) of FOOD_ CONS are obtained.

As a next step, the WF_cons,agr (WF_cons,agr,gn) and (WF_cons,agr,bl) of avoidable waste amounts (WASTE_AV) needs to be quantified. To do this, first the unavoidable fraction (CORR2_NA) must be added to WASTE_AV because the WF_cons,agr of FOOD_CONS relates to the whole product. Thus we have calculated a new component WASTE_AV_CORR by means of equation (7) (table 2).

When both the WF_cons,agr of FOOD_CONS and WASTE_AV_CORR are calculated, the WF_cons,agr,gn and WF_cons,agr,bl for WASTE_AV are computed using equation (8) (table 2).

To clarify, we present the example of vegetables. Using equation (1), we have calculated the FOOD_CONS value for vegetables as 120.8 kg/cap/yr (table 5). The related WF_cons,agr,gn of this amount is 47 l/cap/d (table 5). With an average avoidable food waste fraction (CORR2_AV) of 20.9% (table 4), we have used equation (3) to calculate the average amount of avoidable consumer fruit waste (WASTE_AV) as 25.3 kg/cap/yr.

In order to calculate the WF_cons,agr,gn of this avoidable food waste, first we added the unavoidable fraction of the amount of waste. For example, when an onion is wasted the avoidable waste quantity (WASTE_AV) is the onion without its skin. The WF_cons,agr,gn of all onions consumed and wasted by EU consumers (FOOD_CONS of onions) relates to the whole product, including the skin. Therefore the skin must be added to the wasted onion to calculate its WF_cons,agr,gn.

For all vegetables, the corrected avoidable waste amount (WASTE_AV_CORR)—which is only useful to calculate the related footprint—is computed by means of equation (7).

WASTE_AV_CORR = $\frac{{\rm{WASTE}}\_\text{AV}\;}{1-{\rm{CORR}}2\_{\rm{NA}}}$ (equation (7)) =$\frac{25.3}{\mathrm{1-0.053}}$ = 26.7 kg/cap/yr

with CORR2_NA = $\frac{{\rm{WASTE}}\_\text{NA}\;}{{\rm{FOOD}}\_{\rm{CONS}}}$ = $\frac{6.4\;}{120.8}$ = 0.053

with WASTE_NA (equation (4)) = FOOD_CONS× CORR2_NA = 120.8 kg/cap/yr × 5.3% = 6.4 kg/cap/yr

The WF_cons,agr,gn of avoidable vegetable waste is then calculated using equation (8):

$$\begin{eqnarray*}&&(\displaystyle \frac{{\rm{WASTE}}\_{{\rm{AV}}}_{{\rm{CORR}}}}{{\rm{FOOD}}\_{\rm{CONS}}})\times {{\rm{WF}}}_{\text{cons},\text{agr}}\\ &&\quad =(\displaystyle \frac{26.7}{120.8})\times 47\;{\rm{l}}/{\rm{cap}}/{\rm{d}}=10.4\;{\rm{l}}/{\rm{cap}}/{\rm{d}}.\end{eqnarray*}$$

To quantify the nitrogen resources related to these wasted food amounts, we have used the NF concept [11, 18, 26]. In particular, we have assessed the nitrogen contained in food (N_cons) and in food production NF (NF_prod) for avoidable food waste. The N_cons quantifies the N-content within a product (based upon the protein content). The NF_prod is any nitrogen that has been used in the food chain and has been lost to the environment as emissions of nitrous oxide, nitric oxide, ammonia or molecular nitrogen to the atmosphere, or as nitrate or organic nitrogen to the hydrosphere before the food product is supplied to the consumer [26].

To assess the nitrogen intake (N_cons) and food production N footprint (NF_prod), we have used the data from [26]. The authors have provided NF factors calculated with the CAPRI model for individual crops and applicable to the quantity of food supplied at the farm gate. The data have been aggregated to the FBS crop groups, and NF_prod has been scaled to also include the losses of reactive nitrogen linked to wastages that occur between the farm gate and supply to the consumer. The quantity of these wastages is also given in the FBS.

The N_cons and NF_prod of avoidable food waste are calculated in analogy to the WF, as shown in equation (9) (table 2). Leip et al [26] also provide detailed data for the EU on the fate of the N surplus, and thus its potential contribution to adverse environmental impacts and associated damage costs [6, 7, 41–47]. Specifically, the shares emitted into the atmosphere as nitrous oxide (N₂O), ammonia (NH₃), nitrogen oxides (NO_x) or dinitrogen (N₂), or released to the hydrosphere via surface run-off or nitrogen leaching have been calculated on the basis of the life-cycle assessment model implemented in the CAPRI model for GHG accounting [48] and extended to cover nitrogen flows [26]. We have used their database of crop-specific emission unit flows to quantify the emissions of reactive nitrogen associated with food consumption in Europe.

As a first step, we calculated the total amount of food reaching consumers (FOOD_CONS) based upon FAO FBS FOOD_SUPPLY values for different product groups and the related water and NFs. These results are presented in table 5.

More particularly, table 5 shows:

• FOOD_SUPPLY values for the EU for different product groups from the FAO FBS;
• FOOD_CONS values after applying the correction factor CORR1 (equation (1)). All food reaching consumers (FOOD_CONS) equals 789 kg/cap/yr;
• The FOOD_CONS related WF_cons,agr,gn and WF_cons,agr,bl values (in l/cap/d). The total (sum of all product groups) WF_cons,agr,gn amounts to 3383 l/cap/d and the WF_cons,agr,bl to 270 l/cap/d. These values have already been presented in [9];
• The N_cons and NF_prod (in kg/cap/yr) values related to FOOD_CONS. The total (sum of all product groups) N_cons amounts to 6.0 kg/cap/yr and the NF_prod to 32.4 kg/cap/yr.

The NF comprises N_cons and NF_prod. Total FOOD_CONS NF_prod (N losses to the environment before the food product is supplied to the consumer) amount to 15.8 Tg N yr⁻¹. About 30% of total N losses occur as molecular nitrogen (N₂). They have no adverse effect on the environment and thus represent inefficient resource use [41] (see table 6 below). The 'nitrogen leaching and runoff' component is dominant (36.4%). These values are comparable with earlier work [45]. Up to 13% of the total losses occur in manure and animal waste, for which data on purposeful reuse in the food chain were not available [26]. These flows have been included here as a conservative estimate, although it is likely that part of this N will be recovered and not dispersed in the environment.

Figure 2 shows the calculated average amounts of food wasted by EU consumers, which consist of waste at the household and food service/catering sector levels. Total and avoidable waste amounts are given. The figure shows:

• Total waste averages 123 kg/cap/yr or 60 million tonnes (Mt) annually. This represents 16% of all food reaching consumers.
• Avoidable consumer food waste averages 97 kg/cap/yr or 47 Mt/yr. This represents 12% of all food reaching consumers.
• The range between minimum and maximum values of both total and avoidable food waste is very wide.
• Avoidable food waste represents by far the largest part of total food waste; non-avoidable food waste represents only a small fraction.

Zoom In Zoom Out Reset image size

The WF_cons,agr of avoidable food waste amounts from EU consumers are presented in figure 3 and table 7. Values per food product group and the total values are both presented. The total WF_cons,agr averages 52 km³ yr⁻¹ for green water and 5 km³ yr⁻¹ for blue water, in absolute volumes, or 294 l/cap/d for green water and 27 l/cap/d for blue water. There is a wide range between minimum and maximum WF_cons,agr amounts as the range in avoidable food waste amounts is large.

Zoom In Zoom Out Reset image size

These average absolute volumes represent 8.2% of the EU green WF_cons,agr and 8.9% of the EU blue WF_cons,agr. They also represent 0.8% of the global green WF_cons,agr and 0.5% of the global blue WF_cons,agr.

The product group that accounts for the largest avoidable food waste WF_cons,agr is meat (average green 18.8 km³ yr⁻¹ or 106 l/cap/d and blue 1.2 km³ yr⁻¹ or 7 l/cap/d), as meat is a very water-intensive product [16, 28].

Other product groups with high amounts of avoidable food waste WF_cons,agr are cereals, cheese and crop oils. The blue WF_cons,agr of wasted fruit is the second largest after meat, i.e. 0.8 km³ yr⁻¹ or 4 l/cap/d, as much of the fruit which is either produced in and imported into the EU is irrigated [24]. Wasted vegetables and sugar also have a substantial blue WF_cons,agr component.

The NF of avoidable food waste amounts from EU consumers is presented in figure 4 and table 8. Both the values per food product group and the total values are presented. The total N_cons averages 0.33 Tg N yr⁻¹ and the NF_prod averages 1.34 Tg N yr⁻¹ in absolute quantities or 0.68 kg N/cap/yr and 2.74 kg N/cap/yr in per capita quantities. In addition, the range between minimum and maximum NF amounts is wide as the range in avoidable food waste amounts is large.

Zoom In Zoom Out Reset image size

These average values represent 11.3% of the N_cons supplied to EU consumers and 8.5% of the EU NF_prod.

The product group that accounts for the largest avoidable food waste NF is meat (average N_cons of 0.07 Tg N yr⁻¹ or 0.14 kg N/cap/yr and NF_prod of 0.76 Tg N yr⁻¹ or 1.55 kg N/cap/yr).

Other product groups with high avoidable food waste NF values are cereals, cheese and milk.