
Street dust represents a source of dual potential risk to stormwater and air quality. It has been well documented that street dust washes into local watersheds and can degrade water quality. Research has also demonstrated that ambient particulate matter (PM10) , which is associated with adverse health outcomes, can arise from resuspension of accumulated street dust. Furthermore, many contaminants, including metals, are present at higher concentrations in the smallest available particles, which are more likely to be resuspended in air and stormwater runoff. Although street cleaning is listed as a best management practice for storm water quality by the EPA, data are limited on the critical parameters (technology, environment, usage), which determine the effectiveness of any street cleaning program, particularly in the peer-reviewed literature. The purpose of the present study was to develop a comprehensive understanding of the efficacy of various street cleaning technologies and practices to protect both water quality and public health. Few studies have compared the effectiveness of street sweeping technologies to remove street dust. Unfortunately, the dearth of comprehensive data on exposure, contaminant concentrations, and efficacy of various sweeping technologies and strategies precludes developing quantitative estimates for potential risk to humans and the environment. Based on the few studies available, regenerative air street sweepers appear to provide the most benefit with regard to collection of small particles and prevention of re-entrainment. It is also clear from the available data that local conditions, climate, and specific needs are critical determinants of the ideal street sweeping strategy (technology, frequency, speed, targeted areas, etc.). Given the critical need for protection of water and air quality in rapidly expanding urban regions (e.g., megacities), further research is necessary to develop best practices for street dust management. Herein, we provide a framework for future experimental studies to support risk-based assessments of street cleaning technologies.
Air Pollutants, Rain, Dust, Risk Assessment, United States, Environmental Policy, Government Regulation, Animals, Humans, Water Pollutants, Sanitation
Air Pollutants, Rain, Dust, Risk Assessment, United States, Environmental Policy, Government Regulation, Animals, Humans, Water Pollutants, Sanitation
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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