摘要：AbstractAir quality information is scarce in low‐ and middle‐income countries. This study describes the application of moderate cost approaches that can provide spatial and temporal information on concentrations of particulate matter (PM) needed to assess community and occupational exposures. We evaluated PM levels at the Agbogbloshie e‐waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations, obtaining both optical and gravimetric measurements, local meteorological data and satellite aerosol optical depth. Due to overload issues, the gravimetric 24‐hr samplers were modified for periodic sampling and some optical data were screened for quality assurance. Exceptionally high concentrations (e.g., 1‐hr average PM10exceeding 2000 μg/m3) were sometimes encountered near combustion sources, including open fires at the e‐waste site and spoil piles. 24‐hr PM2.5levels averaged 31, 88 and 57 μg/m3at upwind, e‐waste and downwind sites, respectively, and PM10averaged 145, 214 and 190 μg/m3, considerably exceeding air quality standards. Upwind levels likely reflected biomass burning that is prevalent in the surrounding informal settlements; levels at the e‐waste and downwind sites also reflected contributions from biomass combustion and traffic. The highest PM levels occurred in evenings, influenced by diurnal changes in emission rates, atmospheric dispersion and wind direction shifts. We demonstrate that moderate cost instrumentation, with some modifications, appropriate data cleaning protocols, and attention to understanding local sources and background levels, can be used to characterize spatial and temporal variation in PM levels in urban and industrial areas.Key PointsAmbient particulate matter was monitored onsite, upwind and downwind of an e‐waste site in Ghana using gravimetric and optical measurementsE‐waste site emissions increased 24‐hr PM2.5levels by 57 μg/m3over upwind levels of 31 μg/m3, and some exceptionally high levels were measuredModerate cost methods can measure air quality and source impacts given attention to study design, sampler performance and local influences
