20 October 2020

The effects of reducing food losses and food waste on global food insecurity, natural resources, and greenhouse gas emissions

Abstract

The Food and Agriculture Organization of the United Nations (FAO) has estimated that in 2010–2012, 868 million people were undernourished worldwide. At the same time, FAO reported that approximately 1.3 billion tons of food were lost or wasted globally in 2007, which was equivalent to approximately one-third of the food produced for human consumption at the time. Food losses and waste deprive the poor living in developing regions of opportunities to access food, cause significant depletion of resources such as land, water, and fossil fuels, and increase the greenhouse gas emissions associated with food production. In the present study, the effects of reducing food losses and waste on global food security, natural resources, and greenhouse gas emissions were evaluated using a food trade model operating under the assumption that in 2007, developed regions, as defined by the FAO, would reduce food losses and waste by up to 50 % during the stages of postharvest handling and storage, processing and packaging, distribution, and consumption. The results obtained show quantitatively that reductions in food losses in developed regions decrease the number of undernourished people in developing regions by up to 63 million, leading to decreases in the harvested area, water utilization, and greenhouse gas emissions associated with food production.

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Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7

Notes

  1. 1.

    The FAO revised its methodology for assessing food in security in the 2012 edition of the report “The State of Food Insecurity in the World” (FAO et al. 2012). The present study is based on the revised methodology and data.

  2. 2.

    Lipinski et al. (2013) estimated that 32 % by weight of the food produced for human consumption was lost or wasted worldwide in 2009. When converted into calories, global food losses and waste amount to approximately 24 % of all food intended for people.

  3. 3.

    Food losses and food waste are defined in the FAO’s report (Gustavsson et al. 2011) as follows:

    Food waste or loss is measured only for products that are directed to human consumption, excluding feed and parts of products that are not edible. According to this definition, food losses or waste are the masses of food lost or wasted in the part of food chains leading to “edible products going to human consumption.” Therefore, food that was originally meant for human consumption but which leaves the human food chain is considered food loss or waste even if it is then directed to a non-food use (feed, bioenergy, etc.).

  4. 4.

    Parfitt et al. (2010) define food loss as the decrease in edible food mass throughout the supply chain and note that these losses occur during the production, postharvest and processing stages of the food supply chain, while food losses occurring at the end of the food chain (retail and final consumption) represent “food waste.”

  5. 5.

    From April 2012 to March 2014, interim reduction targets for food losses per unit sales were set for 16 sectors of the food industry, including food manufacturers, food wholesalers, and food retailing (MAFF 2013).

  6. 6.

    Japanese food losses and waste are considered to be smaller but still substantial when converted into calories.

  7. 7.

    At least 1.9 tons of CO2 per unit of food waste are estimated to be emitted in Europe throughout the life cycle of food waste, which includes agricultural steps, food processing, transportation, storage, consumption, and end-of life impacts (European Commission 2010).

  8. 8.

    The GAMS/PATH is a Newton-based solver that is available as a GAMS subsystem, providing a tool to solve a mixed complementarity problem (MCP).

  9. 9.

    In the present model, stocks are treated as exogenous variables according to the PEATSim model (Stout and Abler 2003). However, in the dynamic PEATSim model (Somwaru and Dirkse 2012), stocks are modified to endogenous variables specified as a function of those in the previous period and world food prices.

  10. 10.

    The decreased number of undernourished people was estimated for 128 developing countries in the present study because, for example, “the Rest of Western Africa” region in the modified PEATSim model consists of 12 countries (Table 1). In this case, it is assumed that the rates of change of dietary energy supply (DES) for those 12 countries equal that of “the Rest of Western Africa” region in the estimate of the number of undernourished people in each country.

  11. 11.

    MDER is defined as follows: in a specified age and sex group, the amount of dietary energy per person is that amount that is considered adequate to meet the energy needs for a minimum acceptable weight for a person’s attained height, maintain a healthy lifestyle and perform light physical activity. The minimum per-person energy requirement for the entire population is the weighted average of the minimum energy requirements of the different age and sex groups in the population (FAO 2012).

  12. 12.

    The dietary energy supply refers to the amount of food available for human consumption, expressed in kilocalories (kcal) per day. The actual food consumption may be lower than this quantity because it reflects both food consumed and food wasted.

  13. 13.

    Green, blue, and grey water footprints are defined by Hoekstra et al. (2011) as follows:

    The blue water footprint is the volume of surface and groundwater consumed as a result of the production of a good or service. Consumption refers to the volume of fresh water used and then evaporated or incorporated into a product. It also includes water abstracted from surface water or groundwater in a catchment and returned to another catchment or the sea. It is the amount of water abstracted from the groundwater or surface water that does not return to the catchment from which it was withdrawn.

    The green water footprint is the volume of rainwater consumed during the production process. This is particularly relevant for agricultural and forestry products (products based on crops or wood), for which it represents the total rainwater evapotranspiration (from fields and plantations) plus the water incorporated into the harvested crop or wood.

    The grey water footprint of a product is an indicator of freshwater pollution that can be associated with the production of a product over its full supply chain. It is defined as the volume of fresh water that is required to assimilate the load of pollutants based on natural background concentrations and existing ambient water quality standards. It is calculated as the volume of water that is required to dilute pollutants to such an extent that the quality of the water remains above accepted water quality standards.

  14. 14.

    Food sectors used for calculating CO2 emissions in GTAP 8 are as follows: 1. paddy rice, 2. wheat, 3. cereal grains nec, 5. oil seeds, 6. sugar cane, sugar beet, 9. bovine cattle, sheep and goats, horses, 10. animal products nec, 11. raw milk, 19. bovine meat products, 20. meat products nec, 21. vegetable oils and fats, 22. dairy products, 23. processed rice, and 24. sugar.

  15. 15.

    The FAOSTAT Emissions Agriculture database contains the following 8 sub-domains: agriculture total, enteric fermentation, manure management, rice cultivation, synthetic fertilizers, manure applied to soils, manure left on pasture, crop residues, cultivated organic soils, and burning crop residues.

  16. 16.

    “Fruits and vegetables” and “fish and seafood” are excluded from the modified PEATSim model because these commodities are not treated in the original model (Stout and Abler 2003). However, the percentages of these foods in the dietary energy supply (kcal/person/day) are not very high worldwide, according to the FAO’s food balance sheet in 2007: 6 % for “fruits and vegetables” and 1 % for “fish and seafood.” In addition, only 11 % of produced “fruits and vegetables” were traded globally in 2007. These low percentages suggest that excluding these commodities did not greatly affect the results of the present study.

  17. 17.

    Losses in the postharvest handling and storage, processing, distribution, and consumption stages are defined by Gustavsson et al. (2011) as follows:

    (1) Postharvest handling and storage losses include losses due to spillage and degradation during handling, storage and transportation between farm and distribution. For bovine, pork and poultry meat, losses refer to death during transport to slaughter and condemnation at the slaughter house. For milk, losses refer to spillage and degradation during transportation between farm and distribution. (2) Processing losses includes losses due to spillage and degradation during industrial or domestic processing, e.g., juice production, canning and bread baking for vegetable commodities and products. Losses may occur when crops are sorted, if they are judged unsuitable for processing, or during washing, peeling, slicing or boiling, or during process interruptions and accidental spillage. For bovine, pork and poultry meat, losses refer to trimming spillage during slaughtering and additional industrial processing, e.g., sausage production. For fish, losses refer to losses during industrial processing such as canning and smoking. For milk, losses refer to spillage during industrial milk treatment (e.g., pasteurization) and milk processing into, e.g., cheese and yogurt. (3) Distribution losses include losses and waste in the market system, e.g., at wholesale markets, supermarkets, retailers and wet markets. (4) Consumption losses include losses and waste during consumption at the household level.

  18. 18.

    As mentioned in Appendix 3, other utility, processing, and consumer demands in the developed regions decrease after reducing food losses and food waste and are fixed at the lower levels during simulation processes.

  19. 19.

    The dietary energy supply for Brazil was 3,197 kcal per person per day in 2007, which decreases by 8.5 kcal due to income decline (5.1 kcal for sugar, 1.4 kcal for rice, and 1.6 kcal for livestock products).

  20. 20.

    The global harvested area for primary crops increased by 0.7 % (10.0 Mha) per year on average for the period 2000–2011 (FAO 2012).

  21. 21.

    Crop yield is modeled as a constant-elasticity function of the producer price in the PEATSim model.

  22. 22.

    The harvested areas of rice increase in South-Eastern Asia, and those of tropical oilseeds increase in Oceania.

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Acknowledgments

This research was funded by a Grant for Risk Solutions in Engineering Systems from the Graduate School of Decision Science and Technology and the Solutions Research Laboratory at the Tokyo Institute of Technology.

Author information

Affiliations

  1. Graduate School of Decision Science and Technology, Tokyo Institute of Technology, W9-100, 2-12-1 Ohkayama, Meguro-ku, Tokyo, 152-8552, Japan
    • Yosuke Munesue
    •  & Takesato Fushima
  2. National Institute for Environmental Studies, Social and Environmental Systems Division, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan
    • Toshihiko Masui

Corresponding author

Correspondence to Yosuke Munesue.

Appendices

The per capita income for region r in the base year 2007, pcINC r,base, is defined as follows:

$$ {text{pcINC}}_{text{r,base}} = {text{GDE}}_{text{r,base}} /{text{POP}}_{text{r, base}} $$

(1)

where GDEr,base is the GDE and POPr,base is the total population in the base year.

After the reduction of food losses and food waste in developed regions, per capita income in developing regions, pcINCr, is recalculated simply by revising the GDEr as follows:

$$ {text{pcINC}}_{text{r}} = {text{GDE}}_{text{r}} /{text{POP}}_{text{r,base}} $$

(2)

$$ begin{aligned} {text{GDE}}_{text{r}} & = sumlimits_{i} {left( {{text{AgGDE}}_{{{text{CN}}_{{i,{text{base}}}} }}, { cdot },frac{{{text{PC}}_{i}, { cdot },{text{QF}}_{i} }}{{{text{PC}}_{{i,{text{base}}}}, { cdot },{text{QF}}_{{i,{text{base}}}} }}} right)} \ & quad + sumlimits_{i} {left( {{text{AgGDE}}_{{{text{EX}}_{{i,{text{base}}}} }}, { cdot },frac{{{text{PW}}_{i}, { cdot },{text{QEX}}_{i} }}{{{text{PW}}_{{i,{text{base}}}}, { cdot },{text{QEX}}_{{i,{text{base}}}} }}} right)} \ & quad – sumlimits_{i} {left( {{text{AgGDE}}_{{{text{IM}}_{{i,{text{base}}}} }}, { cdot },frac{{{text{PW}}_{i}, { cdot },{text{QIM}}_{i} }}{{{text{PW}}_{{i,{text{base}}}}, { cdot },{text{QIM}}_{{i,{text{base}}}} }}} right)} + {text{RtGDE}}_{text{r,base}} \ end{aligned} $$

(3)

where PC i and PW i are consumer and world prices; QF i , QEX i and QIM i are consumer demand, exports and imports, respectively, for food commodity i after the reduction of food losses and food waste in developed regions; and AgGDE_CN i,base, AgGDE_EX i,base, and AgGDE_IM i,base are agricultural consumption, exports, and imports, respectively, in the base year. RtGDEr,base is determined by subtracting these agricultural terms from gross domestic expenditure, GDEr,base values taken from the GTAP8 database (Narayanan et al. 2012).

Although the expenditure for the other goods (RtGDEr) is assumed to be constant at the base year level in the formula (3), it could be reduced due to food wastage reduction in developed regions for the following two relations. First, RtGDEr could be reduced due to the price decrease of food considering substitution between food and the other goods. Generally, the more substitutable with other goods, the more elastic to the price the demand of good tends to be. As is shown in Table 13, food demand is less elastic to the price than the other goods are, which means food has little substitution goods. Therefore, RtGDEr might be reduced slightly due to the decreases of food prices in developing regions. Secondly, RtGDEr could be reduced due to agricultural income reduction arising from the decreases of food price and food production in developing regions because the other goods are more elastic to income than food is (Table 13). Consequently, GDEs (GDPs) in developing regions could be reduced further due to the decrease of RtGDEr, which leads to the increase in the number of undernourished people for developing regions.

Table 13 Income and price elasticities for aggregate consumption categories

Full size table

In 2012, the FAO methodology for estimating the prevalence of undernourishment went through a review to choose the most appropriate model to describe the dietary energy consumption of the population and improve the estimation of its parameters. A skew-normal distribution (Azzalini 1985) was adopted as a result of this review (FAO, WFP, IFAD 2012). In the model, the proportion of undernourished individuals in the total population is defined by the following cumulative distribution function:

$$ F({text{MDER}}) = varPhi left( {frac{{{text{MDER}} – xi }}{omega }} right) – 2,{text{Owen}}Tleft( {frac{{{text{MDER}} – xi }}{omega },alpha } right) $$

(4)

where MDER is the minimum dietary energy requirement (kcal/person/day) and ω, ξ, and α are scale, location, and shape parameters, respectively. Φ is the cumulative distribution function of the standard normal distribution and OwenT is Owen’s T function. These two parameters are defined as follows:

$$ varPhi (x) = frac{1}{2}left[ {1 + {text{erf}}left( {frac{x}{sqrt 2 }} right)} right]( – infty < x < + infty ) $$

(5)

$$ {text{Owen}}T(h,a) = frac{1}{2pi }intlimits_{0}^{a} {frac{{{text{e}}^{{ – frac{1}{2}h^{2} left( {1 + x^{2} } right)}} }}{{1 + x^{2} }}} {text{d}}x( – infty < h,a < + infty ) $$

(6)

where erf is the error function.

The values of the scale, location, and shape parameters are derived from the mean, variance, coefficient of variation (CV), and skewness of the distribution and the food loss rate (Loss), as follows:

$$ {text{Mean}} = {text{DES}}{ cdot }left( {1 – {text{Loss}}} right) = xi + omega delta sqrt {frac{2}{pi };}, {text{where}};delta = frac{alpha }{{sqrt {1 + alpha^{2} } }} $$

(7)

$$ {text{Variance}} = omega^{2} (1 – (2delta^{2} )/pi ) $$

(8)

$$ {text{CV}} = frac{{sqrt {text{Variance}} }}{text{Mean}} $$

(9)

$$ {text{Skewness}} = frac{4 – pi }{2}{ cdot }frac{{left( {delta sqrt {2/pi } } right)^{3} }}{{(1 – 2delta^{2} /pi )^{3/2} }} $$

(10)

where DES is the average dietary energy supply (kcal/person/day), which is computed from the per capita consumption of food commodities (kg/person/year) as the outcome of the modified PEATSim model. Finally, the number of undernourished people is determined by multiplying the proportion of undernourished people by the total population.

In the modified PEATSim model, the regional food balance for each commodity in 2007 is expressed as follows:

$$ {text{QS}}0 + {text{QIM}}0 – {text{QEX}}0 + {text{QSt}}0 = {text{QL}}0 + {text{QR}}0 + {text{QP}}0 + {text{QE}}0 + {text{QF}}0 $$

(11)

where QS0, QIM0, QEX0, and QSt0 on the left-hand side are production, import, export, and stock variation, respectively, and QL0, QR0, QE0, QP0, and QF0 on the right-hand side are feed, seed, other utility, processing, and consumer demand, respectively, derived from the food balance sheets in FAOSTAT (FAO 2012).

In the following formulas for calculating food wastage, QW0 represents food losses in the postharvest handling and storage stages in 2007, derived from “waste” in the commodity balances in FAOSTAT, which is included in the other utility (QE0) in the food balance sheets. QE, QP, and QF are the other utility, processing, and consumer demand, respectively, in developed regions after reduction of food losses and food waste, which are fixed at the reduced levels during simulation processes. R m, R p, R d, and R c are the ratios of waste generation in the milling, processing and packaging, distribution, and consumption stages, respectively, in the SIK report (Gustavsson et al. 2013). R r is the target reduction ratio for food losses and food waste for all food commodities, which is taken as the maximum of 0.5 in the present study. S QE, S QP, and S QF are the maximum reduction quantities for other utility, processing, and consumer demand, respectively, in the model.

Food losses and food waste are generated as follows at each stage of the food supply chain:

Postharvest handling and storage: QW0

Milling: R m · QF0

Processing and packaging: R p · QP0 + R p · (1 − R m) · QF0

Distribution: R d · (1 − R p) · QP0 + R d · (1 − R p) · (1 − R m) · QF0

Consumption: R c · (1 − R d) · (1 − R p) · QP0 + R c · (1 − R d) · (1 − R p) · (1 − R m) · QF0

Therefore, the maximum reduction quantity for each demand is calculated as follows:

Other utility (S QE): QW0

Processing (S QP): [R p + R d · (1 − R p) + R c · (1 − R d) · (1 − R p)] · QP0

Consumer (S QF): [R m + R p · (1 − R m) + R d · (1 − R p) · (1 − R m) + R c · (1 − R d) · (1 − R p) · (1 − R m)] · QF0

Food losses and food waste are generated as follows at each stage of the food supply chain:

Postharvest handling and storage: QW0crop

Processing and packaging: R p · QP0oil + R p/(1 − R p) · QF0oil

Distribution: R d · (1 − R p) · QP0oil + R d · [1 − R p/(1 − R p)] · QF0oil + R d · QF0crop

Consumption: R c · (1 − R d) · (1 − R p) · QP0oil + R c · (1 − R d) · [1 − R p/(1 − R p)] · QF0oil + R c · (1 − R d) · QF0crop

Therefore, the maximum reduction quantity for each demand is calculated as follows:

Other utility (S QE,crop): QW0crop

Processing (S QP,oil): [R p + R d · (1 − R p) + R c · (1 − R d) · (1 − R p)] · QP0oil

Consumer (S QF,oil): {R p/(1 − R p) + R d · [1 − R p/(1 − R p)] + R c · (1 − R d) · [1 − R p/(1 − R p)]} · QF0oil

Consumer (S QF,crop): [R d + R c · (1 − R d)] · QF0crop

Food losses and food waste are generated as follows at each stage of the food supply chain:

Postharvest handling and storage: QW0

Processing and packaging: R p · QP0 + R p · QF0

Distribution: R d · (1 − R p) · QP0 + R d · (1 − R p) · QF0

Consumption: R c · (1 − R d) · (1 − R p) · QP0 + R c · (1 − R d) · (1 − R p) · QF0

Therefore, the maximum reduction quantity for each demand is calculated as follows:

Other utility (S QE): QW0

Processing (S QP): [R p + R d · (1 − R p) + R c · (1 − R d) · (1 − R p)] · QP0

Consumer (S QF): [R p + R d · (1 − R p) + R c · (1 − R d) · (1 − R p)] · QF0

Consequently, other utility, processing, and consumer demands in developed regions after reducing food losses and food waste, namely, QE, QP, and QF, respectively, amount to (QE0 − R r · S QE), (QP0 − R r · S QP), and (QF0 − R r · S QF), respectively, which are fixed at these levels during simulation processes.

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