The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Analysing global food waste problem: pinpointing the facts and estimating the energy content
Open accessAbstract
Food waste is a global problem. Each year food worth billions of dollars is wasted by the developed economies of the world. When food is wasted, the problem does not end at that point. More than 95% of the food waste ends at landfill sites, where converted into methane, carbon dioxide and other greenhouse gasses by anaerobic digestion. The impact of food waste to climate change is catastrophic. Food waste problem tends to increase in next 25 years due to economic and population growth mainly in Asian countries. In addition, when food wastes buried at landfill sites their energy content is lost. Although food waste is a huge problem, its global size and extent has recently become a hot topic in the academic community. This paper summarises the size of the global food waste problem together with the estimation of the amount of energy lost when food wastes dumped at landfill sites. Calculations in this study also revealed that energy lost at landfill sites equals to 43% of the delivered energy used for the preparation of foods in the US, 37% of the hydroelectric power generation of Japan, and more than 100% of the current annual renewable energy demand of UK industries.
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Cites
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“This amount is equal to 27% of the edible food available for human consumption [5].”
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Cited by
Bioconversion of food waste to energy: A review
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A comprehensive review on food waste anaerobic digestion: Research updates and tendencies
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Novel Approaches in the Valorization of Agricultural Wastes and Their Applications
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Metadata
- Authors
- Melikoglu, M., Lin, C., & Webb, C.
- Venue
- Open Engineering
- Publisher
- Walter de Gruyter GmbH
- Published
- 2013-04-11
- Volume
- 3
- Issue
- 2
- Pages
- 157-164
- ISSN
- 2081-9927 (ISSN-L)
- 2391-5439
- OpenAlex
- W2027066643
- Cited by
- 314
- References
- 17
- FWCI
- 10.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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