With rapid population growth, especially in low-income and middle-income countries, the generation of waste is increasing at an unprecedented rate. For example, annual global waste arising from waste electrical and electronic equipment alone will have increased from 33.8 to 49.8 million tonnes between 2010 and 2018. Despite incineration and other waste treatment techniques, landfill still dominates waste disposal in low-income and middle-income countries. There is usually insufficient funding for adequate waste management in these countries and uptake of more advanced waste treatment technologies is poor. Without proper management, many landfills represent serious hazards as typified by the landslide in Shenzhen, China on 20 December 2015. In addition to formal waste recycling systems, approximately 15million people around the world are involved in informal waste recycling, mainly for plastics, metals, glass and paper. This review examines emerging public health challenges, in particular within low-income and middle-income countries, associated with the informal sector. While informal recyclers contribute to waste recycling and reuse, the relatively primitive techniques they employ, combined with improper management of secondary pollutants, exacerbate environmental pollution of air, soil and water. Even worse, insufficient occupational health measures expose informal waste workers to a range of pollutants, injuries, respiratory and dermatological problems, infections and other serious health issues that contribute to low life expectancy. Integration of the informal sector with its formal counterparts could improve waste management while addressing these serious health and livelihood issues. Progress in this direction has already been made notably in several Latin American countries where integrating the informal and formal sectors has had a positive influence on both waste management and poverty alleviation.
- environmental health
- environmental epidemiology
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Contributors HY undertook preliminary research and produced the first draft. All authors contributed to draft revision and approved the final version.
Funding This work was supported by National Natural Science Foundation of China (41641058), Chongqing R&D Project of the high technology and major industries (1231), National Key Technology R&D Program of China (2016YFC0500106), the Open Research Fund Program of Chongqing Engineering Research Center for Remote Sensing Big Data Application, and Open Research Fund Program of Chongqing Key Laboratory of Karst Environment, Southwest University.
Competing interests None declared.
Provenance and peer review Commissioned; externally peer reviewed.
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