Missing Food, Missing Data?: A Critical Review of Global Food Losses and Food Waste DataShow others and affiliations
2017 (English)In: Environmental Science and Technology, ISSN 0013-936X, E-ISSN 1520-5851, Vol. 51, no 12, p. 6618-6633Article in journal (Refereed) Published
Abstract [en]
Food losses and food waste (FLW) have become a global concern in recent years and emerge as a priority in the global and national political agenda (e.g., with Target 12.3 in the new United Nations Sustainable Development Goals). A good understanding of the availability and quality of global FLW data is a prerequisite for tracking progress on reduction targets, analyzing environmental impacts, and exploring mitigation strategies for FLW. There has been a growing body of literature on FLW quantification in the past years; however, significant challenges remain, such as data inconsistency and a narrow temporal, geographical, and food supply chain coverage. In this paper, we examined 202 publications which reported FLW data for 84 countries and 52 individual years from 1933 to 2014. We found that most existing publications are conducted for a few industrialized countries (e.g., the United Kingdom and the United States), and over half of them are based only on secondary data, which signals high uncertainties in the existing global FLW database. Despite these uncertainties, existing data indicate that per-capita food waste in the household increases with an increase of per-capita GDP. We believe that more consistent, in-depth, and primary-data-based studies, especially for emerging economies, are badly needed to better inform relevant policy on FLW reduction and environmental impacts mitigation.
Place, publisher, year, edition, pages
2017. Vol. 51, no 12, p. 6618-6633
Keywords [en]
Food supply, Supply chains, Sustainable development, Critical review, Data inconsistencies, Emerging economies, Industrialized countries, Mitigation strategy, Political agenda, Reduction targets, Secondary datum, Environmental impact
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-30872DOI: 10.1021/acs.est.7b00401Scopus ID: 2-s2.0-85021643135OAI: oai:DiVA.org:ri-30872DiVA, id: diva2:1139000
Note
Funding details: 71233007, NSFC, National Natural Science Foundation of China; Funding text: This work is funded by National Natural Science Foundation of China (key program, project no. 71233007), National Key Research and Development Plan of China (project no. 2016YFE0113100), and the Danish Agency for Science, Technology and Innovation (International Network Programme, reference nos. 5132-00029B and 6144-00036). We thank Yao Liu for research assistance.
2017-09-062017-09-062023-05-23Bibliographically approved