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Modeling of risk from improper sorting of waste at recycling centers
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.ORCID iD: 0000-0002-0021-5971
2020 (English)In: Waste Management, ISSN 0956-053X, E-ISSN 1879-2456, Vol. 102, no 1, p. 550-560Article in journal (Refereed) Published
Abstract [en]

This study has demonstrated the use of weighted-linear-combination approach in connection with fuzzy set functions of Total Population, Total Distance, Annual income per person and Total number of opening hours of Recycling Centers (RCs), in ArcGIS environment, to generate risk maps and characterize RCs based on risk for improper sorting of waste. Analysis of data shows that there are 73 RCs, at which, risk for improper sorting of waste is highest. On average, there is one RC for every 19,402 individuals in Sweden and a single round trip made by Swedes to nearest RC, results in emission of 1340 ktons of CO2. Furthermore, it is found that strategies needed (e.g. installation of new RCs or shifting of RCs closer to densely populated areas (DPAs) or increase in number of opening hours or availability of pre-visit sorting information etc.), to reduce risk for improper sorting of waste, are different for RCs that are operated under different management forms. Variations in tariffs, limited number of waste fractions to be collected per RC, confusing terminologies, design parameters of RCs and non-implementation of EU Directive 2018/851 with respect to packaging waste, are other factors that are affecting quality of waste sorting at RCs, and are discussed in the article. Results from this research can be utilized to identify site specific needs for improving sorting of waste and to identify priority areas for installation of new RCs.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 102, no 1, p. 550-560
National Category
Environmental Management
Research subject
Natural Science, Environmental Science
Identifiers
URN: urn:nbn:se:lnu:diva-90248DOI: 10.1016/j.wasman.2019.11.017ISI: 000512310800057Scopus ID: 2-s2.0-85075292452OAI: oai:DiVA.org:lnu-90248DiVA, id: diva2:1372507
Funder
Knowledge Foundation, 817-2.1.9Available from: 2019-11-24 Created: 2019-11-24 Last updated: 2021-05-07Bibliographically approved

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Ibrahim, Muhammad Asim

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CiteExportLink to record
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  • apa
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