4.7 Article

'Wasteaware' benchmark indicators for integrated sustainable waste management in cities

Journal

WASTE MANAGEMENT
Volume 35, Issue -, Pages 329-342

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.wasman.2014.10.006

Keywords

Benchmark indicators; Performance monitoring; Solid waste management; Governance; Developing countries; Recycling rates

Funding

  1. UN-Habitat
  2. GIZ

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This paper addresses a major problem in international solid waste management, which is twofold: a lack of data, and a lack of consistent data to allow comparison between cities. The paper presents an indicator set for integrated sustainable waste management (ISWM) in cities both North and South, to allow benchmarking of a city's performance, comparing cities and monitoring developments over time. It builds on pioneering work for UN-Habitat's solid waste management in the World's cities. The comprehensive analytical framework of a city's solid waste management system is divided into two overlapping 'triangles' - one comprising the three physical components, i.e. collection, recycling, and disposal, and the other comprising three governance aspects, i.e. inclusivity; financial sustainability; and sound institutions and proactive policies. The indicator set includes essential quantitative indicators as well as qualitative composite indicators. This updated and revised 'Wasteaware' set of ISWM benchmark indicators is the cumulative result of testing various prototypes in more than 50 cities around the world. This experience confirms the utility of indicators in allowing comprehensive performance measurement and comparison of both 'hard' physical components and 'soft' governance aspects; and in prioritising 'next steps' in developing a city's solid waste management system, by identifying both local strengths that can be built on and weak points to be addressed. The Wasteaware ISWM indicators are applicable to a broad range of cities with very different levels of income and solid waste management practices. Their wide application as a standard methodology will help to fill the historical data gap. (C) 2014 Elsevier Ltd. All rights reserved.

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