Scientific Publications ‘Wasteaware’ Benchmark Indicators for Integrated Sustainable Waste Management in Cities Published 2014 Share SHARE Facebook share Twitter LinkedIn Copy URL Email Download Download Wasteaware_ISWM_benchmark_indicators-Wilson_et_al- FINAL.pdf en Added on: 08 November, 2025 Breadcrumb Home Resource Library ‘Wasteaware’ Benchmark Indicators For Integrated Sustainable Waste Management In Cities 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.