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Socio-economic development drives solid waste management performance in cities: A global analysis using machine learning.
Velis, Costas A; Wilson, David C; Gavish, Yoni; Grimes, Sue M; Whiteman, Andrew.
Afiliación
  • Velis CA; School of Civil Engineering, University of Leeds, Leeds LS2 9JT, SW7 2AZ, UK. Electronic address: c.velis@leeds.ac.uk.
  • Wilson DC; Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK.
  • Gavish Y; School of Civil Engineering, University of Leeds, Leeds LS2 9JT, SW7 2AZ, UK.
  • Grimes SM; Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK.
  • Whiteman A; Resources and Waste Advisory Group Ltd., Wren House, AL1 1NG, UK.
Sci Total Environ ; 872: 161913, 2023 May 10.
Article en En | MEDLINE | ID: mdl-36781141
ABSTRACT
Mismanaged municipal solid waste (MSW), the major source of plastics pollution and a key contributor to climate forcing, in Global South cities poses public health and environmental problems. This study analyses the first consistent and quality assured dataset available for cities distributed worldwide, featuring a comprehensive set of solid waste management performance indicators (Wasteaware Cities Benchmark Indicators - WABI). Machine learning (multivariate random forest) and univariate non-linear regression are applied, identifying best-fit converging models for a broad range of explanatory socioeconomic variables. These proxies describe in a variety of ways generic levels of progress, such as Gross Domestic Product - Purchasing Power per capita, Social Progress Index (SPI) and Corruption Perceptions Index. Specifically, the research tests and quantitatively confirms a long-standing, yet unverified,

hypothesis:

that variability in cities' performance on MSW can be accounted for by socioeconomic development indices. The results provide a baseline for measuring progress as cities report MSW performance for the sustainable development goal SDG11.6.1 indicator median rates of controlled recovery and disposal are approximately at 45 % for cities in low-income countries, 75 % in lower-middle, and 100 % for both upper-middle and high-income. Casting light on aspects beyond the SDG metric, on the quality of MSW-related services, show that improvements in service quality often lag improvements in service coverage. Overall, the findings suggest that progress in collection coverage, and controlled recovery and disposal has already taken place in low- and middle-income cities. However, if cities aspire to perform better on MSW management than would have been anticipated by the average socioeconomic development in their country, they should identify ways to overcome systemic underlying failures associated with that socioeconomic level. Most alarmingly, 'business as usual' development would substantially increase their waste generation per capita unless new policies are found to promote decoupling.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Sci Total Environ Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Sci Total Environ Año: 2023 Tipo del documento: Article