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1、Food Waste Index Report 2024Think Eat SaveTracking Progress to Halve Global Food Waste 2024 United Nations Environment ProgrammeISBN:Job number:This publication may be reproduced in whole or in part and in any form for educational or non-profit services without special permission from the copyright

2、holder,provided acknowledgement of the source is made.The United Nations Environment Programme would appreciate receiving a copy of any publication that uses this publication as a source.No use of this publication may be made for resale or any other commercial purpose whatsoever without prior permis

3、sion in writing from the United Nations Environment Programme.Applications for such permission,with a statement of the purpose and extent of the reproduction,should be addressed to unep-communication-directorun.org.DisclaimersThe designations employed and the presentation of the material in this pub

4、lication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country,territory or city or area or its authorities,or concerning the delimitation of its frontiers or boundaries.Mention of a commercial company or

5、 product in this document does not imply endorsement by the United Nations Environment Programme or the authors.The use of information from this document for publicity or advertising is not permitted.Trademark names and symbols are used in an editorial fashion with no intention on infringement of tr

6、ademark or copyright laws.The views expressed in this publication are those of the authors and do not necessarily reflect the views of the United Nations Environment Programme.We regret any errors or omissions that may have been unwittingly made.Maps,photos and illustrations as specifiedDesign and l

7、ayout:Fabrice Belaire(figures&layout)and Beverley McDonald,UNEP(cover design).Suggested citation:United Nations Environment Programme(2024).Food Waste Index Report 2024.Nairobi.Production:United Nations Environment Programme https:/www.unep.org/resources/publication/food-waste-index-report-2024Finan

8、cial support from the Swiss Federal Office for Agriculture(FOAG-BLW)and the United States Environmental Protection Agency(USEPA)to conduct the research on which this report is based is gratefully acknowledged.Supported by:AcknowledgementsAuthors:Hamish Forbes,Eloise Peacock,Nettie Abbot,Michael Jone

9、s(WRAP).UNEP Focal Point:Clementine OConnor.Acknowledgements:Aditi Ramola(International Solid Waste Association),Claire Turner(WRAP),Dany Ghafari(UNEP),Donovan Storey(UNEP),Ekaterina Poleshchuk(UNEP),Emily Chang(Institute of Economics,Taiwan,China),Felicitas Schneider(Thnen-Institut,Germany),Gustavo

10、 Porpino(Embrapa,Brazil),Irene Fagotto(UNEP),Jonathan Bruenggel(Federal Office of Environment of Switzerland),Martina Otto(UNEP),Masaki Yabitsu(UN-Habitat),Richard Swannell(WRAP),Thembelihle Ndukwana(Department of Trade and Industry,South Africa),Tom Quested(WRAP).Publication Date:March 27th 2024Thi

11、s report was developed in the context of the One Planet Network Sustainable Food Systems Programme.UNEP extends its thanks to the Federal Office of Agriculture of Switzerland and to the United States Environmental Protection Agency for their support in the development of this report.Food Waste Index

12、 Report 2024|UNEP|IIIList of abbreviations and acronyms CGCSA Consumer Goods Council of South Africa EU European Union FAO Food and Agriculture Organization of the United Nations FLI Food Loss Index GDP Gross domestic product JICA Japan International Cooperation Agency J-PRISM II Japanese Technical

13、Cooperation Project for Promotion of Regional Initiative on Solid Waste Management in Pacific Island Countries Phase II MSW Municipal solid waste NDC Nationally Determined Contribution POS Point of sale PPP Public-private partnership SAGO Saudi Grains Organisation SDG Sustainable Development Goal SD

14、G 12.3 Sustainable Development Goal 12,target 12.3 UNEP United Nations Environment Programme UN-Habitat United Nations Human Settlements Programme UNSD United Nations Statistics Division U.S.EPA United States Environmental Protection Agency WaCT Waste Wise Cities Tool WRAP Waste and Resources Action

15、 ProgrammeIV|UNEP|Food Waste Index Report 2024Definitions“Food waste”is defined as food and the associated inedible parts removed from the human food supply chain.“Removed from the human food supply chain”means one of the following end destinations:co/anaerobic digestion;compost/aerobic digestion;la

16、nd application;controlled combustion;sewer;litter/discards/refuse;or landfill.“Food”is defined as any substance whether processed,semi-processed or raw that is intended for human consumption.“Food”includes drink,and any substance that has been used in the manufacture,preparation or treatment of food

17、.Therefore,food waste includes both:“edible parts”:i.e.the parts of food that were intended for human consumption,and“inedible parts”:components associated with a food that are not intended to be consumed by humans.Examples of inedible parts associated with food could include bones,rinds and pits/st

18、ones.“Food loss”is defined as all the crop and livestock human-edible commodity quantities that,directly or indirectly,completely exit the post-harvest/slaughter production/supply chain by being discarded,incinerated or otherwise,and do not reenter in any other utilization(such as animal feed,indust

19、rial use,etc.),up to,and excluding,the retail level.Losses that occur during storage,transport and processing,also of imported quantities,are therefore all included.Losses include the commodity as a whole with its non-edible parts decrease in edible mass at the production,post-harvest and processing

20、 stages of the food chain(Food and Agriculture Organization of the United Nations 2022).The Food Waste Index tracks the global and national generation of food and inedible parts wasted at the retail and consumer(household and food service)levels.UNEP is its custodian.In contrast to the Food Loss Ind

21、ex,the Food Waste Index measures total fresh mass of food waste(rather than specific commodities).Food Waste Index Report 2024|UNEP|VTable of contents ACKNOWLEDGEMENTS.III LIST OF ABBREVIATIONS AND ACRONYMS.IV DEFINITIONS.V LIST OF TABLES,FIGURES AND BOXES.VIII EXECUTIVE SUMMARY.XI The state of food

22、 waste worldwide.XII Measuring and reporting Sustainable Development Goal target 12.3.XVII Reducing food waste through a collaborative approach.XIX Conclusions.XX1 INTRODUCTION.21.1 The Food Waste Index and Sustainable Development Goal target 12.3.21.2 How the Food Waste Index is calculated.41.3 Str

23、ucture of the report.52 INDEX LEVEL 1:EXISTING DATA AND MODELLING.72.1 Level 1 estimates of food waste:what and why?.72.2 Summary of the methodology.82.3 Results:data coverage.10Summary of datapoints.10Summary of countries with data.11High confidence estimates.15Key narratives around data availabili

24、ty.162.4 Results:regional breakdowns.17Latin America and the Caribbean.17West Asia.24Africa.26Asia and the Pacific.29Europe.33North America.352.5 Food waste amounts:measured estimates and extrapolation.37Food waste estimates by country income level.37Food waste estimates by region.45Global estimates

25、.46VI|UNEP|Food Waste Index Report 20243 INDEX LEVELS 2 AND 3:MEASURING FOOD WASTE AT THE NATIONAL LEVEL.493.1 Overview of data collection.493.2 Measuring total food waste generated.51Stages to form a national estimate.51Retail.56Food service.58Household.663.3 Edible and inedible waste.71Classifying

26、 inedible parts.71Applying the classification.723.4 Destinations of surplus and waste.74Retail.76Food service.76Household.773.5 Food manufacturing.80Scope.80Measurement methods.82Sampling and scaling.824 SOLUTIONS FOCUS:PUBLIC-PRIVATE PARTNERSHIPS.844.1 The public-private partnership model.874.2 Sta

27、keholders.89Private sector.89Public sector.90Third parties.904.3 Implementing a public-private partnership.91Developing a public-private partnership:Five-step model.91Financing a public-private partnership.93Examples:Brazil and Colombia.964.4 Conclusion.985 CONCLUSIONS.100 BIBLIOGRAPHY.101 ANNEX 1:B

28、USINESS CASE STUDY.117 ANNEX 2:TABLE OF DATAPOINTS.119 Household datapoints.119 Food service datapoints.148 Retail datapoints.157 ANNEX 3:TABLE OF HOUSEHOLD ESTIMATES.166Food Waste Index Report 2024|UNEP|VIIList of tablesTable 1:Estimates of global food waste in 2022.XIITable 2:Total data coverage b

29、y sector,and change from Food Waste Index Report 2021.XIVTable 3:Average food waste in kilograms per capita per year,by World Bank income grouping.XIVTable 4:Number of national and subnational datapoints included in the Food Waste Index Report 2024.XVTable 5:Appropriate methods of measurement for di

30、fferent sectors.XVIIITable 6:Total data coverage by sector(and change from the Food Waste Index Report 2021).10Table 7:Number of datapoints,by scope of study(and change from the Food Waste Index Report 2021).11Table 8:Number of countries with data,by World Bank income classification (and change from

31、 the Food Waste Index Report 2021).11Table 9:Number of countries with data,by region(and change from the Food Waste Index Report 2021).12Table 10:Share of population in countries with some identified data on food waste,by region.14Table 11:Newly added countries with“high confidence”estimates.15Table

32、 12:Household food waste datapoints in Latin America and the Caribbean.18Table 13:Data coverage in G20 countries.22Table 14:Household food waste datapoints in the West Asia region.25Table 15:Household food waste datapoints in Africa.27Table 16:Household food waste datapoints in the Asia Pacific regi

33、on.30Table 17:Summary of datapoints in North America.35Table 18:Average food waste(in kilograms per capita per year),by World Bank income grouping.37Table 19:Summary of the share of food waste considered“edible”in cited studies.43Table 20:Food waste categories applied in Watanabe(2012)in Malaysia,an

34、d the assumed edible/inedible composition.44Table 21:Disaggregation within food waste categories in two studies.44Table 22:Average household waste(kilograms per capita per year)in each region,derived from studies.45Table 23:Estimates of global food waste in 2022.46Table 24:Comparison of two“framewor

35、ks”for quantification in businesses from the perspective of national governments.53Table 25:Appropriate methods of measurement for different sectors.53Table 26:Subsectors within retail sector.56Table 27:Comparison of measurement methodologies in the retail sector.57Table 28:Example of normalization

36、factors and what data would be needed to scale in the retail sector.58Table 29:Categorization of subsectors within food service.60Table 30:Guidance for prioritizing food service subsectors in the absence of data.61Table 31:Comparison of measurement methods in food service.62Table 32:Comparison of sa

37、mpling units in food service.63Table 33:Comparison of normalization and scaling factors in food service.64Table 34:Comparison of methods for collecting household food waste for measurement.67Table 35:Comparison of the two main situations in which“inedible parts”arise.72Table 36:ISIC,REV.4.,divisions

38、 relevant for“Manufacturing”.80Table 37:ISIC,REV.4.,classes relevant to“Manufacturing”.81Table 38:Table of normalization and scaling factors in the“Manufacturing”sector.83Table 39:Seed funding used to develop existing food waste reduction public-private partnerships.95VIII|UNEP|Food Waste Index Repo

39、rt 2024List of figuresList of boxesFigure 1:Tracking progress on SDG 12.3:Food Loss Index and Food Waste Index.XIFigure 2:Summary of Level 1 modelling methodology.XIIIFigure 3:Scope of the Food Waste Index(Levels 2 and 3)adapted from the Food Loss and Waste Accounting and Reporting Standard.3Figure

40、4:Food Waste Indices for two hypothetical countries.5Figure 5:Summary of Level 1 modelling methodology.8Figure 6:Distribution of household datapoints in the Latin America and the Caribbean region.18Figure 7:The five municipal planning areas in the city of Rio de Janeiro.20Figure 8:Annual household f

41、ood waste per capita in high-,medium-and low-income groups in Rio de Janeiro.21Figure 9:Distribution of household datapoints in the West Asia region.25Figure 10:Distribution of household datapoints in the Africa region.28Figure 11:Summary of household food waste datapoints in Kenya.28Figure 12:Distr

42、ibution of household datapoints in the Asia Pacific region.31Figure 13:Food waste per capita in Japan over time.32Figure 14:Food waste estimates across Europe.33Figure 15:Evaluation of the different research methods of papers evaluated in a 2023 review of articles that reported on household food was

43、te during the COVID-19 pandemic.36Figure 16:Box-plot distribution of high confidence and medium confidence household food waste estimates for countries.38Figure 17:Relationship between household food waste and GDP per capita and year.39Figure 18:Correlation between household food waste measurements

44、and average temperature in country.39Figure 19:Box-plot distribution of high confidence and medium confidence food service and retail estimates for all countries.41Figure 20:Household food waste estimates(kilograms per capita per year)for countries with both rural and urban datapoints.41Figure 21:Ex

45、ample of UNEP data capture form from 2023 pilot exercise.50Figure 22:Common process for adjusting food waste measurements to form national estimates.51Figure 23:Example equation to building an estimate of the number of meals served through existing data.64Figure 24:Number of NDCs mentioning food los

46、s or waste.70Figure 25:Best practice guide for integrating food loss and waste into Nationally Determined Contributions.70Figure 26:Food and food waste destinations,adapted from the Food Loss and Waste Protocol Standard.75Figure 27:Qualities of the public-private partnership model.87Figure 28:Framew

47、ork for food waste public-private partnership.88Figure 29:Food waste public-private partnerships and exploratory work across the world.88Figure 30:Five key steps for developing a public-private partnership.91Figure 31:Illustrative figure of lower-and higher-level PPP funding and the situations in wh

48、ich they might apply.93Figure 32:Overview of funding requirements and key milestones.94Figure 33:Timescale for Brazil and Colombia public-private partnership.97Box 1:Why so few retail and food service estimates?.13Box 2:Country profile:Brazil .20Box 3:G20 countries.22Box 4:Country profile:Kenya.28Bo

49、x 5:Country profile:Japan.32Box 6:Household food waste and COVID-19.36Box 7:Example of sampling units,normalizing and scaling.51Box 8:Worked example:Retail.59Box 9:Worked example:Food service.65Box 10:Worked example:Household sampling.69Box 11:Food waste in Nationally Determined Contributions.70Box

50、12:Worked example:Household food waste destinations.77Box 13:Food waste diary guidance.79Box 14:The Courtauld Commitment.85Box 15:Australian Food Pact.86Box 16:The South African Food Loss and Waste Initiative.86Box 17:Exploring the intersection between food waste and justice,equity,diversity and inc

51、lusion.98Food Waste Index Report 2024|UNEP|IXFood waste is a market failure that results in the throwing away of more than US$1 trillion worth of food every year.It is also an environmental failure:food waste generates an estimated 810 per cent of global greenhouse gas emissions(including from both

52、loss and waste),and it takes up the equivalent of nearly 30 per cent of the worlds agricultural land.The conversion of natural ecosystems for agriculture has been the leading cause of habitat loss.Just as urgently,food waste is failing people:even as food is being thrown away at scale,up to 783 mill

53、ion people are affected by hunger each year,and 150 million children under the age of five suffer stunted growth and development due to a chronic lack of essential nutrients in their diets.Sustainable Development Goal 12,target 12.3(herein,SDG 12.3)captures a commitment to halve per capita global fo

54、od waste at the retail and consumer levels and to reduce food loss across supply chains by 2030.As custodian of the Food Waste Index,the United Nations Environment Programme(UNEP)tracks global food waste occurring at the retail,food service and household levels;meanwhile,the Food and Agriculture Org

55、anization of the United Nations(FAO)is custodian of the Food Loss Index,which tracks food loss occurring along the post-harvest supply chain up to and excluding the retail level(Figure 1).SDG 12.3 has a key role to play in the delivery of other Sustainable Development Goals,including those around Ze

56、ro Hunger(SDG 2),Sustainable Cities(SDG 11)and Climate Action(SDG 13).The connection between food waste and biodiversity loss,moreover,is now recognized in the Kunming-Montreal Global Biodiversity Framework,which specifically calls out halving global food waste by 2030 in target 16.Executive summary

57、Figure 1:Tracking progress on SDG 12.3:Food Loss Index and Food Waste Index12.312.3.1(a)Food Loss12.3.1(b)Food Waste“halve per capita global food waste at the retail and consumer levels.”“reduce food losses along producon and supply chains,including post-harvest losses.”“By 2030,Food Loss Index-focu

58、s on supply Food Waste Index-focus on demandCustodians of 12.3 indicators:FAO&UNEPFood Waste Index Report 2024|UNEP|XIA substantial increase in data availability and coverage was observed in the household sector,with 194 datapoints across 93 countries(Table 2).This represents a near doubling in the

59、number of countries with some type of estimate(up from 52 countries in the Food Waste Index Report 2021),with particularly notable growth in the coverage of low-and middle-income countries.An estimated 85 per cent of the global population resides in a country where there is at least some data on hou

60、sehold food waste.This improvement in coverage strengthens confidence in the food waste estimates.Table 2:Total data coverage by sector,and change from Food Waste Index Report 2021INCLUDED IN 2024 REPORT (CHANGE FROM 2021 REPORT)HOUSEHOLDFOOD SERVICERETAILTOTALNumber of datapoints194(+103)49(+17)45(

61、+16)288(+136)Number of countries93(+41)41(+18)45(+22)102(+48)Despite a near doubling of data coverage,there has been increased convergence in the average per capita household food waste,with the average observed household food waste in high income,upper-middle income and lower-middle income countrie

62、s varying by just 7 kilograms per capita per year(Table 3).5Table 3:Average food waste in kilograms per capita per year,by World Bank income groupingINCOME GROUPHOUSEHOLDFOOD SERVICERETAILHigh income countries 812113Upper-middle income countries 88Insufficient dataLower-middle income countries 86Ins

63、ufficient dataLower income countries Insufficient dataInsufficient dataMost new food waste estimates are at the city or other subnational levels.Countries with disaggregated data for urban and rural areas are relatively rare,but typically show lower levels of food waste in rural areas.This may be be

64、cause rural areas have greater circularity in their food systems(including feeding scraps to animals and composting),and special attention is needed to help circularity thrive in the city.5 The household food waste global average is lower than any of the income group averages presented in Table 1 be

65、cause the income-group averages are a simple mean of estimates from countries with datapoints.In other words,it does not account for population size of different countries.The total amount wasted,and the global averages,however,do account for population size.There is increased confidence in the conc

66、lusion from the Food Waste Index Report 2021 that household per capita food waste generation is broadly similar across country income groups.Food waste is an urban issue.With more than half of the global population now living in urban areas,the role of local governments in tackling food waste is exp

67、ected to only increase in the coming years.Local government engagement in addressing the food waste issue should be scaled up and prioritized.National governments working closely with cities will ensure that policies are put in place and efforts are sustained to get food out of landfills and into ci

68、rcular and productive use.XIV|UNEP|Food Waste Index Report 2024Countries in the G20 should leverage their economic and political influence to take significant action on food waste.This starts with accurate measurement and reporting through the Food Waste Index.Table 4:Number of national and subnatio

69、nal datapoints included in the Food Waste Index Report 2024INCLUDED IN 2024 REPORT(CHANGE FROM 2021 REPORT)HOUSEHOLDFOOD SERVICERETAILNumber of national datapoints49(+11)40(+16)40(+13)Number of municipal and subnational datapoints145(+92)9(+1)5(+3)(change from Food Waste Index Report 2021)Among the

70、G20,only Australia,Japan,the United Kingdom,the United States and the European Union have food waste estimates suitable for tracking progress to 2030,while in Brazil activities to develop a robust baseline are under way.Most G20 countries do not have data suitable for tracking progress.As a communit

71、y of the worlds largest economies,the G20 has significant potential to demonstrate successful pathways to SDG 12.3 delivery as Japan and the United Kingdom are doing and to lead by example,connecting the fight against hunger and the triple planetary crisis of climate change,pollution and biodiversit

72、y loss.The G20 also has considerable influence on consumer behaviour:by promoting awareness and education on food waste,the G20 can encourage sustainable consumption across the globe.How is“food”defined?Why are inedible parts included?How much could have been eaten?For the purposes of the Food Waste

73、 Index,“food waste”is defined as food and the associated inedible parts removed from the human food supply chain in the following three sectors:retail,food service and households.As a result,the estimates include both“edible”and“inedible”parts of food.There are three key reasons why“inedible”parts a

74、re worthy of attention:1.The distinction between what is“edible”or“inedible”is often not clear-cut.Many animal parts or fruit and vegetable skins may be removed in some cultures,or for some uses,while being commonly eaten in others.Chicken feet,for example,are commonly consumed in some parts of the

75、world but not in others.Even within a particular culture,the“edibility”may depend on the degree of processing,and perceptions of edibility due to personal preference can vary within one family.For example,orange peel can“become”edible through processing into marmalade.2.The“upcycling”of food allows

76、re-integration of“inedible”parts back into the human supply chain.These could either be for direct human consumption,such as integrating brewers spent grains into bakery products and high-protein snacks,or by diverting“inedible”food surplus to animal feed where it is safe to do so.A circular food sy

77、stem involves useful applications of all parts,and through circular approaches,parts normally considered“inedible”can help improve food security.3.From a practical perspective,the recommended methods to measure food waste(see chapter 2)are first applied to all food waste,from which edible parts coul

78、d subsequently be disaggregated.It is challenging to accurately measure edible food waste without also measuring inedible parts.SDG Indicator 12.3.1(b)allows the separate reporting of inedible parts where they have been measured.Food Waste Index Report 2024|UNEP|XVData on the edible fraction of food

79、 waste across different countries,and on the causes of food waste in homes worldwide,remains very limited.Very few countries have accurate data that include the share of waste that is“edible.”Among those that do,the share that is“edible”varies between 31 per cent and 77 per cent.Even if food waste i

80、s assumed to be at the bottom of this range globally,the quantities of edible food that are wasted are staggering.This further reinforces the crucial role that food waste reduction has to play in improving food security worldwide.This conservative estimate of the amount of edible food waste amounts

81、to the equivalent of 1.3 meals per person impacted by hunger,per day.What about the retail and food service sectors?There has been little change in the availability and coverage of data on food waste in the retail and food service sectors,with an ongoing lack of accurate nationwide data outside of h

82、igh-income countries.This is a major data gap that is driven in part by the difficulty in accurately measuring multiple subsectors(both the food service and retail sectors contain multiple qualitatively different settings)and by the challenges in scaling estimates by appropriate national factors(suc

83、h as the amount of food served in a particular subsector).As more countries start to measure their food waste in the retail and food service sectors,and as their measurements cover more subsectors than currently,food waste estimates are expected to increase due to broader coverage.It is critical to

84、address this data gap through increased measurement,and reducing food waste in these settings can help businesses reduce costs in their operation and waste disposal.Even if all of the food wasted in households globally contained just 25 per cent edible parts a very conservative estimate,lower than a

85、ny of the observed rates of edibility from countries where it has been measured then the equivalent of 1 billion meals of edible food is being wasted every single day in households worldwide.This is likely a minimum estimate,and the real amount could be much higher.Data for the retail and food servi

86、ce sectors remains insufficient,particularly in low-and middle-income countries.These represent substantial data gaps that should be addressed for a more complete understanding of global food waste.These unknown quantities could be substantial.XVI|UNEP|Food Waste Index Report 2024Measuring and repor

87、ting Sustainable Development Goal target 12.3What are the two SDG 12.3 indicators?SDG 12.3 covers food and inedible parts that exit the supply chain and thus are lost or wasted.This is tracked through two indicators:Indicator 12.3.1(a),the Food Loss Index,measures losses for key commodities in a cou

88、ntry across the supply chain,up to but not including retail.The FAO is its custodian.Indicator 12.3.1(b),the Food Waste Index,measures food and inedible parts wasted at the retail and consumer levels(food service and households).The United Nations Environment Programme(UNEP)is its custodian.In contr

89、ast to the Food Loss Index,the Food Waste Index measures total food waste(rather than loss or waste associated with specific commodities).The Food Waste Index also allows countries to measure and report on food loss and waste generated in manufacturing processes,which would not be captured under key

90、 commodity losses by the Food Loss Index.The results presented in the Food Loss Index and in the Food Waste Index cannot be directly compared or summed due to different reference points.The Food Loss Index covers production,which includes(human)food,seed and feed for livestock.The Food Waste Index c

91、overs food available for human consumption,which may take place after a degree of processing or conversion of feed into animal products.How do countries measure and report on food waste?To report on SDG 12.3 indicator 12.3.1(b),the Food Waste Index,countries will fill out a separate table of the UNS

92、D-UNEP Questionnaire on Environment Statistics(waste section)shared with Member States(environment ministries)by UNEP and the United Nations Statistics Division(UNSD).To complete measurement in line with Food Waste Index requirements,Member States are invited to:Define a scope i.e.select the sector(

93、s)they are able to report on Select suitable methods to measure food waste(net fresh mass)Conduct studies using the chosen method(s)Scale measurement from representative studies into national estimates Report food waste for the Food Waste Index Repeat studies regularly(at least every four years)usin

94、g a consistent methodology.Food Waste Index Report 2024|UNEP|XVIITable 5:Appropriate methods of measurement for different sectorsSECTORMETHODS OF MEASUREMENTManufacturing (if included)Direct measurement(for food-only waste streams)Waste composition analysisVolumetric assessmentMass balanceRetail Cou

95、nting/scanningFood service Diaries(for material going down sewer,home composted or non-waste destinations)HouseholdTable 5 illustrates suitable methods for food waste measurement by sector.This report expands on the guidance for measurement as outlined in the Food Waste Index Report 2021.In particul

96、ar,it expands on:How to prioritize which subsectors to study in the retail and food service sectors;How to determine the sample size and sampling unit;and How to scale measurements conducted at a sampling unit into national estimates.These are explained in detail in chapter 3.Use the Food Waste Inde

97、x guidance provided in this report to measure food waste consistently.Report baselines and progress towards halving food waste at regular intervals through the UNSD-UNEP Questionnaire on Environment Statistics(waste section).XVIII|UNEP|Food Waste Index Report 2024The Food Waste Index Report 2024 int

98、roduces a“Solutions Focus”chapter that spotlights approaches that can deliver food waste reductions at scale.The first solution in this series explores public-private partnerships(PPPs).As food waste is an issue throughout the entire supply chain,PPPs bring stakeholders together to collaborate and d

99、eliver a shared goal,thus overcoming some of the challenges of a fragmented food system.PPPs connect businesses with government and policy makers in a pre-competitive space,allowing best practice to be shared while driving innovation for long-term,holistic change.Food waste PPPs require signatories

100、to measure and report their food waste for monitoring purposes,which provides important data that can be used to demonstrate the business case to invest in food waste reduction.PPPs are typically designed at the country level,but in very large countries they can be subregional(for example,the Pacifi

101、c Coast Food Waste Commitment).Sector-specific industry agreements at the regional level also can play a role,such as the International Food Waste Coalition focusing on food waste in the hospitality sector.PPPs have a proven track record of delivering food waste reductions.The Courtauld Commitment i

102、n the United Kingdom was initiated in 2005,and the current phase,Courtauld Commitment 2030,aims to deliver farm-to-fork reductions in food waste,greenhouse gas emissions and water stress through collaborative action across the entire UK food chain.Actions have resulted in a 27 per cent reduction in

103、household food waste per capita and a 23 per cent reduction in total food waste per capita between 2007 and 2018(Devine et al.2023).Cost-benefit analysis of the Courtauld Commitment 20152018,including government spending and operational costs,suggests that there is a 7:1 benefit-to-cost ratio(see ch

104、apter 4).Reducing food waste through a collaborative approachWhat does a public-private partnership look like?The framework for a food waste PPP uses a“Target,Measure,Act”approach,with four complementary parts:1.Strategy and commitment:The aims and objectives of the PPP are laid out,including a coll

105、ectively agreed target and a delivery roadmap to ensure that targets can be achieved.2.Collaborative activity:Members should collaborate through action-orientated working groups,projects,campaigns and reporting.3.Outputs:Outputs should support the delivery of targets;this includes guidance to suppor

106、t wide adoption of the PPP,industry recommendations and pilot activity to test approaches in a local context.4.Impact:The impact of these actions are captured on an annual basis to inform progress towards targets.Food and drink organizations are at the heart of a PPP,and the public sector and third

107、parties also play a pivotal role.The roles and responsibilities of the different stakeholders are discussed in section4.2.What are the steps to developing a public-private partnership?There are five key steps for developing a PPP,taken from a model developed by REFRESH(2021):1.Initiation and set-up:

108、Conduct an exploratory study to assess the readiness and willingness of stakeholders to develop a PPP,and design an implementation plan.2.Ambitions,goals and targets:Set a target for businesses,including interim targets.These should be in line with the 50 per cent reduction of SDG target 12.3.3.Gove

109、rnance and funding:Establish a Steering Committee or independent Secretariat to oversee day-to-day management of the agreement.4.Establishing actions:Establish a roadmap or delivery plan,targeting priority areas or“hotspots”of waste.Businesses adopt their own action plans,focusing on their own opera

110、tions,engaging customers/consumers and their supply chain.5.Measurement and evaluation:The Secretariat captures,anonymizes and aggregates data from businesses to assess progress towards the targets,and publicly reports on this progress.Food Waste Index Report 2024|UNEP|XIXBy following this five-step

111、 process,stakeholders in a PPP are able to define the most appropriate and viable solutions for their business,sector and country context.In some cases,these may be operational changes to improve food forecasting;in other situations,the focus may be on facilitating redistribution to those in need.Th

112、e complex challenge of food loss and waste requires a systemic approach.Effective collaboration through a PPP is one potential solution to reducing food loss and waste,alleviating food insecurity and delivering environmental benefits.To take a collective approach is to recognize that no one actor ca

113、n solve the problem alone,and that collaboration can create a movement that is more than the sum of its parts.ConclusionsReducing food waste is an opportunity to reduce costs and to tackle some of the biggest environmental and social issues of our time:fighting climate change and addressing food ins

114、ecurity.This report shows that global food waste datapoints have doubled since 2021 yet few countries have robust baselines suitable for tracking progress to 2030.Across the globe,governments,cities,food businesses,researchers and non-governmental organizations of all sizes have a role to play in jo

115、int efforts to change practices and behaviours;target hotspots;innovate;and deliver SDG 12.3.Countries that have been tackling this issue for many years are invited to step up efforts to share their experiences and resources with countries that are just getting started.Halving food waste is a job th

116、at is too large for any one stakeholder.However,it can be achieved through concerted,collaborative effort to commit to the SDG 12.3 target,accurately measure food waste,and most importantly act to achieve food waste reduction.Develop structures for multi-stakeholder collaboration on food loss and wa

117、ste reduction,targeting hotspots and working together around shared interim goals.XX|UNEP|Food Waste Index Report 2024Food waste is a hugely important global issue.Estimates suggest that well over US$1 trillion worth of food is wasted each year(World Bank 2020).This represents more than one-third of

118、 all the food that is produced globally,using over a quarter(28 per cent)of the worlds agricultural area(Food and Agriculture Organization of the United Nations FAO 2013).This waste has devastating effects on both the planet and people.In 2022,an estimated 29.6 per cent of the global population was

119、moderately or severely food insecure,and up to 783 million people were affected by hunger,around 122 million more than in 2019(FAO 2023a).Reducing food waste can increase food availability for those who need it.Food waste also is responsible for an estimated 810 per cent of greenhouse gas emissions(

120、FAO 2013).As environmental impacts accrue across the life cycle of food products,food waste at the consumer level presents the highest burden.In 2021,the United Nations Environment Programme(UNEP)published the initial Food Waste Index Report,shedding new light on the magnitude of food waste and on t

121、he prevalence of household food waste on all continents,irrespective of country income levels.Introduction011.1The Food Waste Index and Sustainable Development Goal target 12.3Sustainable Development Goal 12,target 12.3(hereafter“SDG 12.3”)is a commitment to halve per capita global food waste at the

122、 retail and consumer levels and to reduce food losses along production and supply chains,including post-harvest losses.The focus is on both food and its inedible parts that exit the supply chain and thus are lost or wasted.This is further split into two indicators:Indicator 12.3.1(a),the Food Loss I

123、ndex,measures losses for key commodities in a country across the supply chain,up to and not including retail.The FAO is its custodian.This indicator is not discussed in detail in the present report,except to describe its boundary with the Food Waste Index.Indicator 12.3.1(b),the Food Waste Index,mea

124、sures food and inedible parts wasted at the retail and consumer levels(household and food service).UNEP is its custodian.In contrast to the Food Loss Index,the Food Waste Index measures total food waste(rather than specific commodities).For this reason,the three sectors covered by the Food Waste Ind

125、ex are:food retail,food service and households.The Food Waste Index also allows countries to report on food loss in manufacturing that is not captured by the Food Loss Index(for example,where more than one commodity is combined to produce complex food products).This is an optional supplementary repo

126、rting area,a“Level 3”methodology(see later discussion).Wholesale food remains under the Food Loss Index and therefore should not be reported under the Food Waste Index.2|UNEP|Food Waste Index Report 2024Figure 3:Scope of the Food Waste Index(Levels 2 and 3)adapted from the Food Loss and Waste Accoun

127、ting and Reporting Standard12 monthsFoodInedible partsCo/anaerobicdigestionCompost/aerobicControlledcombustion Land applicationLandfillRefuse/discardsSewerEntire country=1.Retail2.Food service3.HouseholdAnimal feedBiomaterial/processingNot harvestedFood category GeographyLifecycle stage Measurementc

128、onductedsector-by-sector,on foodwaste from allcommoditiesManufacturingfood losses canbe reportedwhere multiplecommoditiescombinedduringprocessingPackagingexcluded fromestimatesAll food andbeverages TIMEFRAMETIMEFRAMEMATERIAL TYPEMATERIAL TYPEDESTINATIONDESTINATIONBOUNDARYBOUNDARYRELATEDISSUESRELATED

129、ISSUESSource:Hanson et al.2016.The scope of the Food Waste Index is Illustrated in Figure 3:Scope of the Food Waste Index(Levels 2 and 3)adapted from the Food Loss and Waste Accounting and Reporting Standard.Animal food and feed and bioprocessed materials are not classified as food waste,as these ma

130、terials are deemed not to have been removed from the human food supply chain.6 Definitions of the destinations of food waste are provided in section 3.4.6 Note that animal food(for pets)is included alongside feed(for livestock),although animal food is not technically kept in the human food supply ch

131、ain.Neither is considered waste so should not be reported in the Food Waste Index,and the figures in this report exclude this wherever possible.This is an additional clarification from the Food Waste Index Report 2021 and is discussed in section .Food Waste Index Report 2024|UNEP|3The Food Waste Ind

132、ex has a three-level methodology,increasing in the accuracy and usefulness of data,but also increasing in the resources required to undertake these levels:Level 1 uses modelling to estimate food waste and is relevant for Member States that have not yet undertaken their own measurement.Level 1 involv

133、es extrapolating data from other countries to estimate food waste in each sector for a given country.The estimates for these countries are approximate:they are sufficient to provide insight into the scale of the problem and to make a case for action,but inadequate to track changes in food waste over

134、 time.They are intended as a short-term support while governments develop capacity for national measurement(consistent with Level 2).UNEP has calculated Level 1 estimates on behalf of countries,and they are presented in chapter 2 of this report.Level 2 is the recommended approach for countries and i

135、nvolves measurement of food waste.The nature of the measurement will vary according to sector and circumstance.It will be either undertaken by national governments or derived from other nationwide studies undertaken in line with the framework described in this report.Level 2 generates primary data o

136、n actual food waste generation and fulfils the requirement for tracking food waste at a national level,in line with SDG 12.3.Level 3 provides additional information to inform policy and other interventions designed to reduce food waste generation.This includes:the disaggregation of data by destinati

137、on,edible/inedible parts;reporting of manufacturing food loss not covered by the Food Loss Index(e.g.where more than one commodity is combined to produce complex food products),and additional destinations such as sewers or home composting.Measurement and reporting by countries are required at Levels

138、 2 or 3,with data submitted to the United Nations Statistics Division(UNSD).Chapter 3 provides considerable additional guidance into how countries should approach measurement in a manner consistent with SDG 12.3.1.2 How the Food Waste Index is calculatedFor each sector within a country,the level of

139、food waste is expressed as an index relative to the level of food waste in the baseline year.A value of:100 would indicate the same level of food waste in that sector as the baseline year;and 50 would indicate that food waste in that sector had halved since the baseline year,consistent with the targ

140、et of SDG 12.3.The indices for each sector are not combined into a single Food Waste Index.This allows the granular data for individual sectors to be more easily communicated.It also alleviates issues if a country is unable to report on all sectors in a single reporting cycle.The first indices for c

141、ountries with suitable data will be published in the next Food Waste Index Report,once those countries have reported the data to the United Nations.The Level 1 estimates presented in the present report are not suitable for tracking changes over time4|UNEP|Food Waste Index Report 2024Example:Food Was

142、te Indices for two hypothetical countriesFigure 4 provides a worked example of the household Food Waste Index for two hypothetical countries.In both cases,the baseline year is 2022.Country 1 has 87 kilograms per capita of household food waste in 2022;because this is the first year of measurement,thi

143、s is defined as 100 in the Food Waste Index.By 2030,this has reduced to 60 kilograms per capita:a value of 69 in the Food Waste Index.This represents a reduction of 31 per cent:good progress,but insufficient to meet the 50 per cent reduction for SDG 12.3(b),represented by the blue dotted line.Countr

144、y 2 has a baseline value of 84 kilograms per capita per year,which is defined as 100 in the Food Waste Index for this country.By 2030,this country has achieved SDG 12.3(b)for this sector,with food waste at less than half the baseline level(41 kilograms per capita per year).Therefore,the final Food W

145、aste Index value for Country 2 is a value less than 50.Figure 4:Food Waste Indices for two hypothetical countries02040608010020222024202620282030Country 1Food waste index baseline equals 100Country 250%reduction in food waste1.3 Structure of the reportThis report serves three primary functions,sprea

146、d across the three main chapters.Chapter 2 provides a summary of known data on food waste in the retail,food service and household sectors worldwide.As in the Food Waste Index Report 2021,this data is used to extrapolate data from other countries to estimate food waste in each sector for a given cou

147、ntry.These“Level 1”estimates are approximate but are sufficient to provide insight into the scale of the problem and to make a case for action.By combining these estimates for each country,new estimates of the amount of food waste globally in the retail,food service and household sectors can be form

148、ed.In chapter 3,the report outlines guidance for how countries should measure and report food waste for SDG indicator 12.3.1(b).This is greatly expanded on from the Food Waste Index Report 2021.The guidance explains the data reporting template from the United Nations Statistics Division(UNSD)and UNE

149、P and outlines considerations for how measurement can be made accurate and achievable in varying national and cultural circumstances.In chapter 4,the report shifts from measuring food waste,to how to reduce it.The first of a new“Solutions Focus”series looks at public-private partnerships for food wa

150、ste reduction:what they are,how they work and guidance for their adoption.Subsequent Food Waste Index report publications will turn a spotlight to different areas for food waste action.Throughout the report,short boxes explore other relevant topics to food loss and waste,such as the impact of COVID-

151、19 restrictions on household food waste(Box 6),integrating food loss and waste targets into Nationally Determined Contributions(Box 11),and the integration of justice,equity,diversity and inclusion in food waste reduction activities(Box 17).Food Waste Index Report 2024|UNEP|52.1Level 1 estimates of

152、food waste:what and why?Although data remains limited,there have been growing efforts to quantify food waste both nationally and within cities in recent years.This section builds on the dataset of the Food Waste Index Report 2021,adding new and newly identified food waste data around the world.It as

153、sesses the availability of food waste estimates in the three following sectors:Retail Food service HouseholdA Level 1(modelled)estimate for each sector has been calculated for all Member States of the United Nations.7 These Level 1 estimates are derived from:Existing datapoints from studies carried

154、out in a Member State(where applicable),or Extrapolations based on the estimates observed in other countries,where no estimate is available from a given Member State.Most Level 1 estimates are not sufficiently accurate to track changes over time and to report progress on SDG 12.3.They are indicative

155、 estimates,which provide a sense of scale of the issue.They support a countrys case for action to tackle food waste and prioritization of different sectors,while the government works towards more accurate measurement(consistent with Level 2 or Level 3).This section contains:An overview of the method

156、ology used(section ),with full detail given in the Appendix.The coverage of food waste data globally(section ),with information on the sector and on the income level of a country and region.Information is also provided on the level of confidence in datapoints obtained.A deep-dive into data coverage

157、for each UNEP regional group(section 2.4):Africa,Latin America and the Caribbean,Asia and the Pacific,West Asia,North America and Europe.Global estimates of food waste in the three assessed sectors(section 2.5).Estimates of individual countries,whether these are datapoints from existing studies or e

158、xtrapolations from other countries data,are reported in Annex 3(Table of household estimates)and in the Appendix.7 Estimates are calculated for every country or area appearing in the United Nations Statistics Division(UNSD)M49 standard.All territories with both an M49 code and a UN estimate of popul

159、ation are included.In total,estimates for 233 countries or areas are estimated.An additional 16 countries or areas(total 249)are included in the M49 standard but without population estimates on https:/data.un.org so had no estimates calculated.Index Level 1:Existing data and modelling02Food Waste In

160、dex Report 2024|UNEP|72.2Summary of the methodologyThe methodology for the calculation of Level 1 estimates in the Food Waste Index Report 2024 follows the five steps taken in the Food Waste Index Report 2021(Figure5).Additional resources:Based on the above methodology,a database of food waste estim

161、ates was created and is available for download as supplementary information to this report.This is not an exhaustive list of the studies that were considered,and,in the cases of high confidence estimates,only the latest data is included.A separate resource is provided in the Appendix that covers stu

162、dies that may be of use to food waste practitioners within a country,but that cannot be used to infer national food waste at this point in time.These are particularly relevant in the food service and retail sectors,where studies may have been conducted within a particular subsector.This is discussed

163、 further in the Appendix.Figure 5:Summary of Level 1 modelling methodologySEARCH AND COLLATE EXISTING DATAFILTER DATA ON SCOPE AND APPLICABILITY TO CURRENT STUDYS NEEDS ADJUST SOME DATA FOR CONSISTENCYEXTRAPOLATE FOR COUNTRIES WITHOUT DATAASSIGN CONFIDENCE RATING TO ESTIMATE8|UNEP|Food Waste Index R

164、eport 2024A summary of the methodology is given below.Full details of the methodology are provided in the Appendix.Search and collate existing data:An online literature review was performed to collect recent estimates of food waste across the world.Online databases,both academic and non-academic,wer

165、e used to search for possibly relevant published estimates of food waste(net fresh mass)at a sectoral level(household,food service,retail).These searches focused on evidence published since the Food Waste Index Report 2021 but also contained searches of earlier dates to capture any evidence not iden

166、tified in the previous study.Studies carried out both at the national level and at the subnational level were included.Estimates of food waste were extracted from relevant studies.In addition,data was gathered from two reporting exercises:the European Unions first data report on food waste across th

167、e EU-27 and the UNEP pilot data gathering for SDG 12.3.The European Union data is discussed in section 2.4.Filter data:Only studies that involved direct measurement of food waste or using data from other studies that involved direct measurement were considered.This is in line with the aim to track l

168、evels of food waste over time,which requires reasonably accurate data while avoiding methodologies with substantial biases.As a result,studies that formed estimates based on proxy data or waste factors not derived from direct measurement were not included.Due to known issues related to the underrepo

169、rting of total mass in food waste diary studies,they were also excluded from the analysis.Removing diaries is a change from the Food Waste Index Report 2021,given increasing data availability,to encourage countries to use more robust methods.Adjust some data:Some datapoints were adjusted to make the

170、m comparable with the majority of studies.For example,studies that presented only the edible share of food waste were adjusted by estimating the inedible share using data from other studies that included this disaggregation.Extrapolate for countries without data:All estimates were normalized to give

171、 the amount of food waste per capita per year.The adjusted,normalized(per capita)estimates were used for the calculation of regional,country income group and global averages.The adjusted,normalized per capita estimates were also used to extrapolate estimates for countries with no relevant study usin

172、g data from nearby countries and those of a similar income level.If neither were available,global data was used.This process is described in more detail in the Appendix.For the purposes of national and global estimates,these per capita food waste estimates were scaled by 2022 UN population data by c

173、ountry,forming Level 1 estimates of food waste in 2022.Therefore,per capita datapoints from a range of years are normalized into total food waste estimates for a single year.Assign confidence rating:Each Level 1 estimate was assigned a confidence rating.This rating indicates the degree to which the

174、estimate is suitable for tracking national food waste over time:High confidence indicates that the estimate is highly likely to be suitable for tracking.Medium confidence estimates have the possibility for identifying larger trends in food waste but may miss smaller changes,or may be applicable only

175、 to a subnational population,such as a particular city.The distinction between high and medium confidence is based on methodological details,such as geographic coverage,sample size and whether the figure required adjustment.Low and very low confidence estimates are based on extrapolation from other

176、countries,with the confidence level determined by the number of countries in the income group and region that inform the extrapolation.It cannot be stressed enough that the confidence rating is not a judgement on the quality of the study undertaken.It is an assessment based on the reviewers understa

177、nding of the study of how robust the estimate of food waste is for tracking food waste at a national level in the given country.Food Waste Index Report 2024|UNEP|92.3Results:data coverageSummary of datapointsThis section describes the extent and coverage of studies containing relevant estimates of f

178、ood waste.Information is presented by sector,by the income group8 of the country and by region.A total of 288 datapoints9 were used in this analysis.This represents nearly double the number of datapoints included in the Food Waste Index Report 2021(152 datapoints).This growth is driven primarily by

179、new information on the household sector,where more than two-thirds of the additional datapoints were identified.The increase in datapoints is reflected by an increase in geographical coverage,with the number of countries with estimates in at least one sector nearly doubling from the Food Waste Index

180、 Report 2021(Table 6).In the retail and food service sectors,the increase in datapoints has been driven in large part by the publication of food waste data across the EU-27,which was reported to the European Commission and published by Eurostat.As a result,retail and food service estimates are still

181、 concentrated in high-income countries,with few nationwide estimates available in other income groupings.By contrast,in the household sector,the growth has primarily been in subnational studies(Table 7).A substantial share(29 per cent,n=42)of subnational studies came from studies by UN-Habitat and t

182、he“Waste Wise Cities tool”and guidance,which is based on the monitoring methodology for SDG indicator 11.6.1 and can generate relevant household food waste information for the Food Waste Index at the same time.Another large part of the new household data emerged from the identification of academic a

183、nalyses that have been published in the literature,both since the Food Waste Index Report 2021 and before it(but not previously identified).Notably,the greater coverage of household estimates does not reflect the generation of nationally representative baselines by governments or national agencies.M

184、ost(76 per cent)of the newly identified household studies are not sufficiently robust for tracking at the national level due to their limited geographic scope.New nationwide studies were identified in 11 UN Member States;however,more work is needed to generate robust,nationally representative data i

185、n most countries.Table 6:Total data coverage by sector(and change from the Food Waste Index Report 2021)INCLUDED IN 2024 REPORT (change from 2021 report)HOUSEHOLDFOOD SERVICERETAILTOTALNumber of datapoints194(+103)49(+17)45(+16)288(+136)Number of countries93(+41)41(+18)45(+22)102(+48)8“Income group”

186、refers to World Bank classification,for the 2024 fiscal year.There are four categories:Low-income countries,defined as those with Gross National Income(GNI)per capita of US$1,135 or less;lower-middle income countries,with a GNI per capita between$1,136 and$4,465;upper-middle income countries,with a

187、GNI per capita between$4,466 and$13,845;and high-income countries,with a GNI per capita of$13,846 or more.9“Datapoint”refers to an individual estimate in a study included in the calculation.Some countries have multiple datapoints due to having multiple studies from different time periods or differen

188、t subnational areas.10|UNEP|Food Waste Index Report 2024Table 7:Number of datapoints,by scope of study(and change from the Food Waste Index Report 2021)INCLUDED IN 2024 REPORT (change from 2021 report)HOUSEHOLDFOOD SERVICERETAILTOTALNumber of national datapoints49(+11)40(+16)40(+13)129(+40)Number of

189、 municipal and subnational datapoints145(+92)9(+1)5(+3)159(+96)A full list of the datapoints can be found in Annex 2(Table of datapoints).This describes the countries in which the studies were conducted,methodological details and the confidence level assigned to each datapoint.Summary of countries w

190、ith dataThis section focuses on the number of countries with measured datapoints.In countries with more than one datapoint for the same sector,where there is no obvious reason to prefer one to another(such as methodological robustness or geographic coverage),the average of multiple datapoints is tak

191、en.Table 8 presents the number of estimates for all sectors based on countries World Bank income groupings.As in the Food Waste Index Report 2021,in all sectors the majority of datapoints are from high income countries.The growth in countries with datapoints in 2024 is driven in large part by the Eu

192、ropean Commissions data reporting exercise,which covered all EU-27 countries,some of which did not have estimates in the Food Waste Index Report 2021.The high income category is also the largest income grouping,so it would be expected that more countries have data there.There has been notable growth

193、 in the number of countries with household estimates across all income groupings,particularly the lower-middle income and low income groupings,where the number of countries represented has more than doubled,although starting from a low base.In the case of low-income countries,the number of countries

194、 with data remains very low and is unlikely to be representative.As a result of a lack of confidence,these figures are not presented separately in the results.Table 8:Number of countries with data,by World Bank income classification(and change from the Food Waste Index Report 2021)WORLD BANK INCOME

195、GROUPTOTAL NUMBER OF COUNTRIES IN GROUPHOUSEHOLDFOOD SERVICERETAILHigh income countries8142(+14)32(+14)35(+15)Upper-middle income countries5321(+9)8(+5)8(+6)Lower-middle income countries5423(+13)1(-1)*2(+1)Lower income countries266(+4)0(0)0(0)Not covered by World Bank groups351(+1)0(0)0(0)*One food

196、service datapoint was removed due to being particularly old and insufficiently representative.Food Waste Index Report 2024|UNEP|11The same data is presented according to regional distribution in Table 9.10 There remain uneven distributions of data between regions,but this shows for the household sec

197、tor at least substantial growth of identified datapoints in multiple regions.Notably,some regions with very small numbers of datapoints or none at all in the Food Waste Index Report 2021 now have many more countries represented.In particular,Northern Africa,Melanesia and Micronesia all now have iden

198、tifiable estimates,which are beneficial for improving the regional extrapolations.The addition of some datapoints from small island states improves the understanding of household food waste in different food environments.Only Central Asia and Polynesia remain as subregions without any estimates.Sect

199、ion 2.4 provides a descriptive summary of the data in each region.Table 9:Number of countries with data,by region(and change from the Food Waste Index Report 2021)REGIONHOUSEHOLDFOOD SERVICERETAILNorthern Africa3(+3)0(0)0(0)Sub-Saharan Africa14(+6)1(0)2(+1)Latin America and the Caribbean10(+6)1(+1)3

200、(+3)Northern America2(0)2(+1)2(+1)Central Asia0(0)0(0)0(0)Eastern Asia5(+3)2(0)2(+1)South-eastern Asia8(+5)1(0)1(0)Southern Asia7(+3)1(0)0(0)Western Asia9(+3)3(+2)3(+1)Eastern Europe6(+3)6(+6)6(+5)Northern Europe9(+2)9(+2)9(+4)Southern Europe8(+3)7(+5)8(+5)Western Europe7(+1)7(+1)7(+1)Australia and

201、New Zealand2(0)1(0)2(0)Melanesia2(+2)0(0)0(0)Micronesia1(+1)0(0)0(0)Polynesia0(0)0(0)0(0)Total93(+41)41(+18)45(+22)The regional distribution remains very uneven in the non-household sectors,with many lacking usable data.This is not to suggest that no work is being undertaken in these sectors and cou

202、ntries;in many cases,measurements have taken place for some subsectors(such as hotels or restaurants)but are lacking the disaggregation or scaling required to form a nationally representative estimate.This is discussed further in Box 1.As a result of these differences in the availability of data,man

203、y uncertainties remain about food waste generation in these sectors.This is particularly the case in low income countries and for the food service and retail sectors in all middle-income and low-income countries.10 For the purposes of this report,the regional disaggregation used was the subregions a

204、s per UNSD classification.12|UNEP|Food Waste Index Report 2024Box 1:Why so few retail and food service estimates?While the number of estimates for household food waste have increased,there is a notable absence of usable estimates for the retail and food service sectors,particularly in middle-and low

205、-income countries.However,this does not mean that there is no data.Often,some data is available,but it may require additional work to form a sector-specific national estimate.There are two key sources of existing data that countries may be able to use to help them form national estimates,described h

206、ere and in more depth in the Appendix:1.Measurements in particular subsectors that need scaling:The retail and food service sectors are made up of a variety of subsectors,representing different establishment types.In the retail sector,for example,in any given country there may be supermarkets and hy

207、permarkets,smaller convenience stores or traditional retailers,outdoor or occasional farmers markets and specialist retail such as butchers,bakers or greengrocers.While in some countries,the large majority of sales will go through supermarket channels,in other countries there may be a more balanced

208、diversity of establishments,with some forms being common in urban areas or particular regions.The same can be said for food service:there are restaurants,canteens and catering in a variety of establishments including offices,schools and hospitals;event catering such as conferences or weddings;street

209、 markets and mobile food vendors;and food provision for care home residents or prisoners,among others.It is common for research studies to be conducted at a single establishment type or subsector:academics may study restaurants or schools,but they are unlikely to have the resources to do both at the

210、 same time.In such cases,the results from these subsector studies may offer normalized estimates at the level of one or more sampling units.If appropriately scaled(see section 3.2),these studies may contribute to national estimates.However,studying one subsector alone cannot form a national estimate

211、 for the entire sector,and additional research may be required in other relevant subsectors to generate a more complete picture.A non-exhaustive list of research papers identified during the research for the Food Waste Index 2024 which focuses on particular subsectors,can be found in the Appendix.Th

212、is resource may be of use to researchers and government officials in those countries to prioritize where additional research is required.2.Waste composition of“commercial”waste:It is common for studies of municipal solid waste to be conducted by collecting waste from the source.In such studies,waste

213、 often has been collected from specific establishments.This is sometimes called“commercial”or“industrial,commercial and institutional”waste.However,these results may be presented at an aggregated level,such as the total waste arisings for all commercial enterprises,or an average waste composition ac

214、ross all businesses.As a result,specific estimates for the retail and food service sectors cannot be derived from these headline results.The raw data underlying existing reports could be rearranged to support reporting on SDG 12.3.For example:if waste generation and composition was recorded at the l

215、evel of specific businesses,it may be possible to split the businesses between“retail,”“food service”and“other”categories and to aggregate the data differently.Revisiting and repurposing existing data could therefore be a cost-effective way for countries with no current estimates for food service an

216、d retail to form estimates.This includes studies in Jamaica(Inter-American Development Bank IDB et al.2022),Mexico(Aguilar,Moreno and Moreno Prez 2017),Ethiopia(Japan International Cooperation Agency JICA 2022)and the Solomon Islands(Environment Unit n.d.).This data may also be able to inform the de

217、velopment of accurate sample sizes(see section 3.2).Food Waste Index Report 2024|UNEP|13While the proportion of countries with some food waste estimates is relatively low,the estimates found are generally concentrated in more populous countries.In households,for example,coverage by country is less t

218、han 50 per cent,but the population of countries with at least some household data covers 85 per cent of the global population(Table 10).Even if smaller countries with more limited resources are not able to directly measure their own food waste,the understanding of global food waste will benefit from

219、 direct measurement and reporting in the worlds largest countries.The G20 countries,as the largest economies and representing around two-thirds of the global population,have a particular role to play in advancing food waste measurement and action(Box 3).Table 10:Share of population in countries with

220、 some identified data on food waste,by regionHOUSEHOLDFOOD SERVICERETAILNorthern Africa50%0%0%Sub-Saharan Africa66%5%6%Latin America and the Caribbean75%19%59%Northern America100%100%100%Central Asia0%0%0%Eastern Asia98%95%95%South-eastern Asia92%5%5%Southern Asia94%0%0%Western Asia43%19%16%Eastern

221、Europe75%75%75%Northern Europe100%100%100%Southern Europe94%55%94%Western Europe100%100%100%Australia and New Zealand100%83%100%Melanesia8%0%0%Micronesia21%0%0%Polynesia0%0%0%Total85%36%40%When interpreting Table 10,it should be noted that,for a country to be considered to have an estimate,there mer

222、ely needs to be one study meeting the requirements for inclusion(see section 2.2).In many cases,a large country has a single,geographically focused study(e.g.focusing on a city)that has been included but that may not provide an estimate sufficiently accurate for the country to allow tracking of food

223、 waste over time.Even in countries with reported medium confidence estimates,additional work is needed to form nationally representative measurements that are sufficiently robust for tracking.14|UNEP|Food Waste Index Report 2024High confidence estimatesThe above discussion does not differentiate bet

224、ween high confidence and medium confidence estimates.These are classifications given to the datapoints based on their likelihood of being suitable for tracking national levels of food waste.They are not commentary on the quality of the research undertaken.High confidence estimates are likely to be s

225、uitable for tracking national levels of food waste.They are developed using a robust methodology,covering a substantial part of the country and with no adjustment of the data required to align with the current studys purposes.Medium confidence estimates are measured using methodologies that may be s

226、uitable for detecting larger changes in food waste,but are not geographically representative.They include datapoints from cities used to represent a country,or datapoints requiring adjustment to align with the current studys purposes.As discussed in this report,most of the newly added data was drive

227、n by subnational estimates.Only four countries that did not previously have estimates in the Food Waste Index Report 2021 have had newly identified data considered to be sufficiently robust for high confidence classification.These are summarized in Table 11,with descriptions of the studies provided

228、in Annex 2(Table of datapoints).Table 11:Newly added countries with“high confidence”estimatesCOUNTRYSECTORSOURCEArgentinaRetail(We Team,Consumer Goods Forum and GS1 Argentina 2021)BhutanHousehold(Bhutan National Statistics Bureau 2021)QatarHousehold(UNEP Regional Office for West Asia 2022)JamaicaHou

229、sehold(IDB et al.2022)In addition to this,in Europe,data reported to the European Commission and published through Eurostat are available for the first time across all sectors.The guidelines provided for measurement methods are consistent with the Food Waste Index,although there are some differences

230、 in sectoral scope as the“retail”and“processing and manufacturing”sectors include some data that would instead be reported to the Food Loss Index(such as wholesale).However,because 2022 was the first year in which the EU data was released,not all countries may have adequately followed this guidance,

231、and methodological information for each datapoint was not available at the time of writing.As a result,data from Eurostat has not been assigned a confidence rating at this point.EU-27 countries reporting in line with European Commission requirements should be able to use this data for reporting on S

232、DG 12.3 as well,in some cases with minor adjustments.Tables with the datapoints included for each sector can be found in Annex 2(Table of datapoints).Food Waste Index Report 2024|UNEP|15Key narratives around data availabilityBuilding on the Food Waste Index Report 2021,some further key narratives ca

233、n be drawn around the global availability of data:There is a substantial and growing body of evidence about the extent of household food waste worldwide.Most of the worlds population lives in a country in which there is at least some empirical evidence about the extent of household food waste.Some o

234、f the data gaps observed in the Food Waste Index Report 2021 have been at least partly filled through recently conducted studies.As discussed later(see section 2.5),when analysed this extensive data further reinforces the conclusions drawn in the Food Waste Index Report 2021 around the broad consist

235、ency worldwide in the quantities of household food waste per capita.However,this wide data availability for the household sector is subject to the caveat that most of the available data is not from nationally representative baseline studies.Despite the wealth of household studies,few are suitable fo

236、r tracking progress to SDG 12.3 on a national basis.The majority of the data comes from small instances of subnational studies in urban areas,particularly in low-and middle-income countries.These are very valuable insights,but substantial variation is observed within studies in the same country,incl

237、uding between urban and rural populations(see section 2.5).A comprehensive understanding of household food waste in a country and how it varies within that country relies on more consistent,large-scale baseline studies being undertaken.The methodology for doing so is discussed in chapter 3.A third k

238、ey narrative from this data overview is the ongoing challenge to generate nationally representative estimates of food waste in the retail and food service sectors.For low-and middle-income countries,there are still very few estimates reported that give insight into waste in these sectors.As discusse

239、d in Box 1,this is not necessarily due to a lack of research in these countries,but rather points to the need for additional work to pick apart existing data and to scale it to form robust national estimates.The methodological guidance provided in chapter 3 expands on how countries should measure re

240、tail and food service food waste in an accurate and cost-effective manner.Sharing learnings from EU-27 countries that have been required to undertake measurement and produce estimates for these sectors would be valuable to help improve the process for other countries.16|UNEP|Food Waste Index Report

241、20242.4 Results:regional breakdownsThis section provides a breakdown of identified data across different world regions.These are grouped according to the regional classification of UNEP.Latin America and the CaribbeanIn Latin America and the Caribbean,a total of 23 datapoints were included,measuring

242、 food waste in 11 countries.Of these datapoints,19 were household estimates(Table 12),1 was from food service and 3 were from retail.Other than the household estimate for Jamaica and the retail estimate for Argentina,all datapoints are classified as medium confidence.The Dominican Republic and Jamai

243、ca are the only Caribbean countries included in the sample.The household study in Jamaica took food waste samples of 250 kilograms each from four waste disposal sites from trucks collecting waste from households,one in each watershed in Jamaica,over three seasons(IDB et al.2022).The results present

244、weighted averages for Jamaica as a whole:the representative samples and adjustment mean that this method would be suitable for tracking food waste over time.11One household estimate for the Dominican Republic(Garca 2018)is the highest household estimate in the region,at 207 kilograms per capita per

245、year.This study sampled 87 households from three socioeconomic groups in Salcedo Municipality over seven days.A second household estimate for the Dominican Republic(UN-Habitat 2021a)includes a similar sample size but produces a much lower estimate of 113 kilograms per capita per year.There is no cle

246、ar methodological reason for the differences in estimates,except for regional differences from studies in two different cities.The substantial variation observed in different studies and locations(see in particular Belize,the Dominican Republic and Ecuador in Table 12)reinforces the need for nationa

247、lly representative studies.A number of the studies identified in Latin America and the Caribbean came through the work of students in published theses or dissertations,such as in Peru(Cutipa 2016;La Rosa Caballero 2022)and Ecuador(Auquilla 2015;Castro 2023).Although constrained to small geographic a

248、reas,these studies show the importance of universities in furthering information-gathering,whether for national or municipal-level decision-making.More systematic searches of university publications may identify further,similar work.The household estimates observed across the region(Table 12 and Fig

249、ure 6)are highly divergent.It is currently unclear whether these reflect real differences between countries and regions within countries,as many of the studies had small samples or were confined to particular small locations.More representative nationwide baseline studies will help improve confidenc

250、e in the data in the region(see chapter 3 for guidance on conducting measurement).There were four non-household estimates identified,two of which were from Mexico(Garduo et al.2023).In the Mexico study,questionnaire surveys were distributed to actors across the food chain,including 52 in the food se

251、rvice businesses and 50 to wholesale and retail businesses.Surveys asked for perceptions of wastage rates by specific products(for example,the percentage of bread wasted)and these were then used to assign waste generation rates that were scaled by representative business data.Authors highlight that

252、the analysis is limited by being built on the perceptions of the stakeholders.The high figures(64 kilograms per capita for food service,45 kilograms per capita for retail)may be a result of very high tourism in the study region of Baja California Sur.The Argentina study(We Team,Consumer Goods Forum

253、and GS1 Argentina 2021)el segmento de autoservicios y supermercados tuvo,sobre el total de ventas,un 4,76%promedio de merma operativa equivalente a unas 123.434 toneladas(ao 2019 collected data on sales and wastage of 16 food categories from supermarkets representing 41 per cent of the total market

254、share.The data was projected over the remaining market share to estimate the entire sector nationwide.Although additional data on other retail avenues would be welcome,the supermarket estimate is sufficiently robust to be judged as suitable for tracking.11 Waste sampled from collection rounds does h

255、ave risks of contamination by small businesses,which should be mitigated where possible(see section 3.2 for more on household food waste measurement methods).In this particular example,waste collection trucks collected only from households and were followed by people on bikes documenting the number

256、of households and,where possible,the number of residents in households,increasing the accuracy of what was captured.Food Waste Index Report 2024|UNEP|17Table 12:Household food waste datapoints in Latin America and the CaribbeanCOUNTRYSOURCESTUDY AREAFOOD WASTE ESTIMATE (kg/capita/year)Belize(IDB 201

257、1)San Ignacio/Santa Elena95(IDB 2011)Caye Caulker45(IDB 2011)San Pedro36(IDB 2011)Belize City34Brazil(Gilbert and Ricci 2023)Rio de Janeiro94Colombia(JICA 2013a)Bogota70Dominican Republic(Garca 2018)Salcedo Municipality207(UN-Habitat 2021a)Santo Domingo113Ecuador(Auquilla 2015)Zaracay,Santo Domingo1

258、58(Castro 2023)Balsapamba,San Miguel34Jamaica(IDB et al.2022)086Mexico(Kneller et al.2019)094(Ojeda-Bentez,Vega and Marquez-Montenegro 2008)Mexicali126(Aguilar,Moreno and Moreno Prez 2017)Berriozbal,Chiapas71(Aguilar Virgin et al.2010)Ensenada,Baja California129Panama(JICA 2003)Panama City101Peru(La

259、 Rosa Caballero 2022)Punta Hermosa,Lima91(Cutipa 2016)Macusani84Venezuela(Snchez et al.2014)Chacao,Miranda State93Figure 6:Distribution of household datapoints in the Latin America and the Caribbean regionNote:Where multiple datapoints exist,the mean(average)is taken,and where only one datapoint exi

260、sts,this is treated as the“average.”18|UNEP|Food Waste Index Report 2024Box 2:Country profile:BrazilIn 2023,Brazil began developing a household food waste baseline,together with ISWA,ABRELPE,Comlurb,and UNEP,to understand the amounts and types of food discarded by households.This baseline,including

261、data from three different areas of the country,will support SDG 12.3 reporting and inform the development of Brazils National Organic Waste Strategy.The first results,from the city of Rio de Janeiro,have been delivered.Rio de Janeiro is the second most populous city in Brazil,with over 13 million pe

262、ople in the metropolitan area.According to data published by the City of Rio de Janeiro,the city produces around 4,800 tonnes of household food waste on a daily basis,which is collected and disposed of by the municipal urban cleaning company,Comlurb(Prefeitura da Cidade do Rio de Janeiro 2021).City

263、data suggests that half(51 per cent)of household solid waste is classified as organic(food or garden waste),and less than 2 per cent of this waste is currently recycled(mainly cardboard,cans and plastics).Comlurb collects around 2,000 tonnes of food waste annually from municipal schools and large ge

264、nerators such as supermarkets and restaurants.The social enterprise Ciclo Orgnico(Organic Cycle)collects food waste from households for compost,although the service is targeted towards families in high-income areas.Rio de Janeiro is developing a food strategy,responding in part to COVID-19s impact o

265、n the food system,that will support the creation of a specific food waste measurement strategy,with an initial focus on households.This planning and research presents a framework and opportunity to build expertise that will help Brazil track food waste in the future.The 2023 study conducted in Rio d

266、e Janeiro involved 102 households,with 86 actively participating,in all five areas of the municipality(Figure 7).These households were selected and categorized based on income,dwelling type,residential area and number of residents.Each household sorted its waste into three categories:food waste(frui

267、t and vegetables,meat,dairy and bakery products),packaging materials and residual waste.To minimize bias,participants,aware of the waste study,were not informed that the focus was on food specifically.Waste was collected over eight days,with the first days waste excluded.20|UNEP|Food Waste Index Rep

268、ort 2024Three income groups were sampled across the municipality(Figure 8):Income Group 1:up to R$5,000 Income Group 2:between R$5,000 and R$10.000,and Income Group 3:above R$10,000.Food waste accounted for 62 per cent of the total waste collected,which is 11 per cent higher than the citys estimates

269、 for organic waste(Prefeitura da Cidade do Rio de Janeiro 2021).This variance may stem from differences in classification,methodologies and sample sizes.*On average,the median amount of food waste is 212 grams per person per day or 77 kilograms per person per year,close to the global average of 81 k

270、ilograms in this report.Household food waste per capita and household income level did not appear to be correlated.Based on the studys findings,food waste minimization campaigns for family meal practices,a separate food waste collection scheme,and exploring home composting options for fruit and vege

271、table waste may be relevant for Rio de Janeiros Food Strategy.Food waste collection schemes should target densely populated areas or residences with multiple occupants,and an initial focus on fruit and vegetable waste may offer the most potential.Behaviour change campaigns could prioritize greengroc

272、ers for information dissemination,which can be reinforced at communal collection sites to increase exposure multiple times a week.Waste reduction campaigns for family meal preparation should involve all family members,including children,and provide guidance on portion sizes and leftover management t

273、o further enhance waste minimization efforts.*Comlurb carries out annual household waste analyses using aggregated samples and by sorting food waste into a single category,not four separate subcategories as was the case in this research.Figure 8:Annual household food waste per capita in high-,medium

274、-and low-income groups in Rio de JaneiroTHE STUDY FOUND THE FOLLOWING:FOOD WASTE CATEGORIES(%BY MASS)WERE:EDIBLE AND INEDIBLE FRACTIONS WERE:Food waste was 62%by mass of total household waste,significantly more than the fractions for packaging and residual waste fractions.No correlation was found be

275、tween income group and per capita food waste generation.Median per capita food waste generation was 77kg/capita/yearFruit and vegetables:62%Meat:11%Dairy:11%Bakery:16%Edible 39%Inedible61%Inedible fruit and vegetables were the largest fraction,at 81%of all fruit and vegetable waste generated or 73%o

276、f all inedible food waste.Food Waste Index Report 2024|UNEP|21Box 3:G20 countriesAs a community of the worlds largest economies,the G20 has an important role to play in demonstrating leadership in food waste measurement and reduction.Representing around two-thirds of the global population,the G20 co

277、untries delivering SDG 12.3 in their countries will be pivotal to global success.The current coverage of data is mixed,as illustrated in Table 13.Table 13:Data coverage in G20 countriesHOUSEHOLDFOOD SERVICERETAILArgentinaNo identified dataNo identified dataHigh confidence datapointAustraliaHigh conf

278、idence datapointHigh confidence datapointHigh confidence datapointBrazil1 medium confidence datapointNo identified data1 medium confidence datapointCanadaHigh confidence datapoint1 medium confidence datapoint1 medium confidence datapointChina3 medium confidence datapoints6 medium confidence datapoin

279、ts1 medium confidence datapointFranceEurostat-reported data*Eurostat-reported data*Eurostat-reported data*GermanyEurostat-reported data*Eurostat-reported data*Eurostat-reported data*India7 medium confidence datapointsNo identified dataNo identified dataIndonesia10 medium confidence datapointsNo iden

280、tified dataNo identified dataItalyEurostat-reported data*No identified dataEurostat-reported data*JapanHigh confidence datapointHigh confidence datapointHigh confidence datapointMexico4 medium confidence datapoints1 medium confidence datapoint1 medium confidence datapointRepublic of Korea1 medium co

281、nfidence datapointNo identified dataNo identified dataRussian Federation1 medium confidence datapoint1 medium confidence datapoint1 medium confidence datapointSaudi ArabiaHigh confidence datapointNo identified dataHigh confidence datapointSouth Africa6 medium confidence datapointsNo identified dataN

282、o identified dataTrkiyeNo identified dataNo identified dataNo identified dataUnited KingdomHigh confidence datapointHigh confidence datapointHigh confidence datapointUnited States of AmericaHigh confidence datapointHigh confidence datapointHigh confidence datapointEuropean UnionHas instituted common

283、 measurement and reporting,see“Europe”section for a summary of data.African UnionNo common measurement and reporting,see“Africa”section for a summary of data.*Data reported on Eurostat has not been assigned a confidence rating due to missing metadata.22|UNEP|Food Waste Index Report 2024Six G20 count

284、ries(Australia,Canada,Japan,Saudi Arabia,the United Kingdom,the United States)have datapoints for household food waste that have been classified as high confidence,suitable for tracking purposes.These estimates come from a range of government bodies and authoritative independent organizations:Canada

285、s estimate is from Environment and Climate Change Canada(2019),involving a synthesis of 56 different waste compositional analyses.The United States estimate is from the U.S.Environmental Protection Agency EPA(2023),which combines waste generation factors from other studies with relevant scaling stat

286、istics.Japans estimate is from the Ministry of the Environment(UNEP 2023),derived from annual surveys of each municipalitys waste compositional data.Australias estimate comes from a 2021 study by The Food and Agribusiness Growth Centre(Bontinck,Grant and Lifecycles 2021),which uses data from state a

287、udits as part of a mass balance model of the whole supply chain.Saudi Arabias estimate is from the Saudi Grains Organisation(SAGO)waste composition analysis(2019).The United Kingdoms estimate is from WRAP,conducted through a mixture of local authority food waste collections and waste compositional a

288、nalysis data(Devine et al.2023).A further four G20 members(France,Germany,Italy and all other EU-27 countries)have datapoints from Eurostat,for which a confidence rating cannot currently be given.Although European Commission measurement requirements are broadly consistent with UNEP(SDG indicator 12.

289、3.1(b),the methodologies used for specific datapoints were not yet published at the time of writing,so cannot be verified(see“Europe”section for more detail).The sectoral scope of EU-reported data may also differ with the inclusion of wholesale in the retail category,so the retail results may be ove

290、rstated.In most countries with some high confidence data,there is data for every sector.This is likely due to at least one organization having clear responsibility for food waste quantification,whether a ministry,national agency or independent organization.By contrast,the countries with multiple med

291、ium confidence data have estimates largely based on ad hoc studies published by researchers in academic journals.China,Mexico,the Russian Federation and South Africa all have nationwide household studies,but these are classified as medium confidence for different reasons.The Mexican study is discuss

292、ed in the“Latin America and the Caribbean”section.The nationwide Chinese study(Xue et al.2021)combines two approaches,including scaling up estimates from studies conducted in rural and urban areas based on national populations,but it only looks at edible waste and so has been adjusted for comparabil

293、ity.Across China,estimates range from 28 kilograms per capita per year at the lowest to 150 kilograms per capita per year at the highest,based on 196 samples of household food waste in urban municipal solid waste(Zhang et al.2020).The nationwide Russian study(Tiarcenter 2019)cites what is assumed to

294、 be a waste composition analysis,but the original source data and information on the calculations used could not be identified.The South African national study(Chakona and Shackleton 2017)”plainCitation”:”(Chakona and Shackleton 2017 combines a literature review of waste compositional analyses acros

295、s three cities(Cape Town,Johannesburg and Rustenburg)and scales this nationally,according to different income groups.This study gave an estimate of 27 kilograms per capita per year,while other studies in specific areas of South Africa varied from 8 to 134kilograms per capita per year.Given this larg

296、e variation,this was not considered an estimate in which we could have high confidence.India,Indonesia and the Republic of Korea have subnational estimates only,while Argentina and Trkiye have no estimates for household food waste(although Argentina has a nationwide estimate for retail food waste).I

297、n countries with multiple medium confidence estimates for household food waste,substantial variance is observed.This variance,especially in China and South Africa,but also in India,Indonesia,and Mexico,demonstrates the need for representative national food waste studies in these countries.G20 countr

298、ies have a significant opportunity to take initiative in the measurement,reporting and reducing of food waste.Firstly,G20 countries can take a leading role in international cooperation and policy development to deliver SDG 12.3.By taking action on food waste,they can lead the way in developing inter

299、national agreements and standards for reducing food waste and improving food sustainability.They have the means and capacity to lead by example in addressing global challenges.Tackling food waste sends a powerful message about responsible consumption and production,setting a precedent for other coun

300、tries to follow.Secondly,G20 countries have a substantial influence on global consumer trends.By promoting awareness and education about food waste at home,they can encourage sustainable consumption patterns that resonate globally.G20 countries thus have the economic and political influence,as well

301、as the responsibility,to take significant action on food waste.By doing so,they can have a substantial positive impact on the environment,economy,and global food security while setting an example for the rest of the world to follow.Food Waste Index Report 2024|UNEP|23West AsiaIn West Asia,21 datapoi

302、nts were found in 9 countries(Table 14 and Figure 9).Of these datapoints,15 were household estimates,3 were retail and 3 were food service estimates.Only the estimates for Saudi Arabia and Qatar are classified as high confidence,suitable for tracking.In addition to the nationwide estimates for house

303、hold food waste in Israel,Saudi Arabia and Bahrain that were already identified in the Food Waste Index Report 2021,further nationwide studies in Cyprus and Qatar were identified.In the Qatar study(see Appendix to this report),food waste estimates were taken from 437 households across ten zones of Q

304、atar in two eight-day phases including Ramadan.The differing Ramadan and non-Ramadan estimates were scaled to a year-wide estimate based on the number of holidays or religious occasions per year and the number of regular days.Waste rates were scaled by different housing types to reflect the variety

305、of household types.Given the methodology,sample days and approach to scaling in the study,this study was classified as high confidence.Estimates for Cyprus are from Eurostat,meaning that a confidence rating cannot currently be given to the data.Although European Commission requirements are consisten

306、t with the Food Waste Index,the methodologies used have not been verified(see“Europe”section for more detail).Data for Cyprus has been flagged by Eurostat as being“estimated,”but it is unclear in what way.The Eurostat metadata mentions that information came from 68 households,but no further informat

307、ion was given.Leket Israel and BDO publish yearly nationwide studies of food waste in Israel.Only the latest,covering 2021,was included in the Food Waste Index data model.The food waste estimates in these reports(Leket Israel 2019;Leket Israel 2020;Leket Israel 2021;Leket Israel 2022)come from three

308、 sources:a“bottom-up”value chain model,using weighted data from the Central Bureau of Statistics in the relevant year;a national survey of the composition of household garbage conducted by the Ministry of Environmental Protection for 2012/13;and research on household garbage in Israel therefore not

309、always a new direct measurement of food waste.These are therefore classified as medium confidence.These studies also provide food waste estimates for the food service and retail estimates but are classified as medium confidence for the same reason as the household estimates.Although there is no nati

310、onwide study of household food waste in Iraq,there are five subnational studies,with food waste estimates ranging from 85 to 190 kilograms per capita per year.This includes one study(Aziz et al.2011)proper waste management systems that consider both the quantity and composition of domestic solid was

311、te are strongly required to address the increasing amount of solid waste.Unfortunately,these essential data are not easily available.The present study sought to gather data on the quantity and composition of domestic solid waste collected from different quarters in Erbil,and the feasibility of recyc

312、ling these wastes.The solid waste generation rate(GR that was not included in the Food Waste Index Report 2021 and that provides the highest estimate of household food waste in West Asia(190 kilograms per capita per year).For this study,researchers collected waste from 72 households,with the number

313、of days waste collected varying between households.The total number of sample days in this study is low(around 130),and although“food”is explicitly identified,there is no category for other organics,so it is possible the estimate includes some non-food organic waste.The only non-household estimates

314、identified,aside from those already mentioned from Cyprus(Eurostat 2023)and Israel(Leket Israel 2019;Leket Israel 2020;Leket Israel 2021;Leket Israel 2022),were a food service estimate from Iraq(Filimonau et al.2023)and a retail estimate from Saudi Arabia(SAGO 2019).Saudi Arabias baseline study(SAGO

315、 2019),conducted by Saudi Grains Organisation,included extensive direct measurement,with more than 7,000 samples across 13 regions.However,wholesale was not disaggregated from retail.This makes it unclear how many samples were specifically from retail and means that wholesale has been included in th

316、e retail food waste figure.The Iraq study(Filimonau et al.2023)sampled 18 restaurants over four consecutive days in 2021,and then scaled this to an Iraq-wide estimate based on the total number of food service operators.This study has several limitations:the small sample size,measuring only in restau

317、rants rather than other food service subsectors,the fact that data was collected during COVID-19 restrictions and may not be representative of normal conditions,and the fact that only edible food waste was included,requiring further adjustment for inedible food waste.24|UNEP|Food Waste Index Report

318、2024Table 14:Household food waste datapoints in the West Asia regionCOUNTRYSOURCESTUDY AREAFOOD WASTE ESTIMATE (kg/capita/year)Bahrain(Alayam 2018)Nationwide132Cyprus(Eurostat 2023)Nationwide71Georgia(Denafas et al.2014)Kutaisi101Iraq(Al-Rawi and Al-Tayyar 2013)Mosul85(Al-Masudi and Al-Haydari 2015)

319、Karbala142(Sulaymon,Ibraheem and Graimed 2010)Al-Kut City138(Yasir and Abudi 2009)Nassiriya163(Aziz et al.2011)Erbil190Israel(Elimelech,Ayalon and Ert 2018)Haifa94(Elimelech,Ert and Ayalon 2019)Haifa Municipality(Neve Shaanan,Ramat Remez,and Yizraelia)89(Leket Israel 2022)Nationwide107Lebanon(UN-Hab

320、itat unpublished)Tyre128Qatar(UNEP Regional Office for West Asia 2022)Nationwide93Saudi Arabia(SAGO 2019)Nationwide105Syrian Arab Republic(Noufal et al.2020)Homs172Figure 9:Distribution of household datapoints in the West Asia region.Note:Where multiple datapoints exist,the mean(average)is taken,and

321、 where only one datapoint exists,this is treated as the“average.”Food Waste Index Report 2024|UNEP|25AfricaFor the Africa region,there are 52 datapoints from 17 countries(Table 15 and Figure 10).The Africa region is split into two subregions,Northern Africa and Sub-Saharan Africa.For Northern Africa

322、,data was identified from three countries with a total of eight datapoints,six of which come from across six different regions in Egypt.A lack of data for Northern Africa was highlighted in the Food Waste Index Report 2021,a situation that has been improved upon.However,all datapoints identified are

323、 medium confidence due to being studies of smaller municipal areas and not representative national studies.For Sub-Saharan Africa,44 datapoints were identified from 14 countries,41 of which are household estimates.Seven household food waste estimates were identified in Kenya and five in South Africa

324、.As in the Food Waste Index Report 2021,the only household estimate in the Africa region to be judged as high confidence is for Ghana,where over 1,000 households across ten districts had their waste categorized for five weeks(Miezah et al.2015).A wide range of estimates exist for household food wast

325、e in the Africa region,with seven of the estimates for household food waste in the region being among the highest identified globally(top 10 per cent of datapoints).The UN-Habitat Waste Wise Cities Tool(WaCT)survey in Iramba District,Tanzania(UN-Habitat 2023a)is the highest reported household food w

326、aste figure in the dataset at 245 kilograms per capita per year.This datapoint comes from a UN-Habitat study;the WaCT guidance suggests a sample size of 90 households collecting waste for one week.Other studies conducted in Tanzania observed considerably lower waste rates(Table 15).The Iramba Distri

327、ct has many households engaged in agriculture,leading them to generate significant post-harvest waste from crops in their municipal waste due to a lack of other recovery activities(UN-Habitat personal communication).A comprehensive,nationally representative study would be needed to understand averag

328、e generation across the country.Three of the highest estimates are from a single study in Egypt:Abdallah et al.(2020)with the aim of finding the waste generation rates and composition in correlation with key socioeconomic features such as household income,family size,and electricity consumption.The

329、per capita waste generation rates were found to range between 0.63 and 0.82 kg/day,and the waste was composed mostly of food(4170%collected waste from four different regions,Gharbiya,Asyout,Kafr El-Sheikh,and Qena,which are geographically distributed.The study collected all generated waste from 300

330、households in the urban centre of each region over the course of eight consecutive days,discarding the first day.Composition analysis was then conducted on around one-quarter of the samples collected from each region.The authors do not provide an explanation as to why the food waste estimates are so

331、 high.It remains unclear whether these high levels of waste reflect edible food being disposed of,or greater generation of inedible parts due to cooking from scratch.More research is needed that disaggregates food waste to better understand the situation in different countries.The higher rates of fo

332、od waste could also reflect the climate,with a relationship being observed between average temperature and household food waste in a country(see section 2.5).Two studies were identified exploring non-household food waste;one evaluating household and retail food waste in Zimbabwe(JICA 2013b)and anoth

333、er that looks at retail,food service and household food waste in Kenya(JICA 2010).Both were conducted by the Japan International Cooperation Agency.The latter study was included in the Food Waste Index Report 2021 auditing waste from 90 food service and retail institutions in Nairobi,whereas the former evaluates retail food waste in Chitungwiza,Zimbabwe.The study collected samples from nine establ