Exploring PM2.5 variations from a low-cost sensor network in Greater Kampala, during COVID-19 imposed lockdown restrictions: Lessons for policy

Abstract

Air pollution is considered a major public health risk globally, and the global South including sub-Saharan Africa face particular health risks, but there is limited data to quantify the level of pollution for different air quality contexts. The COVID-19 lockdown measures led to reduced human activities, and provided a unique opportunity to explore the impacts of reduced activities on urban air quality. This paper utilises calibrated data from a low-cost sensor network to explore insights from the diverse ambient air quality profile for four urban locations in Greater Kampala, Uganda before and during lockdown from March 31 to May 5 2020, highlighting the uniqueness of air pollution profiles in a sub-Saharan African setting. All locations saw year to year improvements in 24-hour mean PM2.5 between 9 μg/m3 and 25 μg/m3 and correlated well with reduction in traffic (up to approx. 80%) and commercial activities. The greatest improvement was observed in locations close to major transport routes in densely populated residential areas between 8:00 pm and 5:00 am. This suggests that the reduction in localised pollution sources such as nocturnal polluting activities including traffic and outdoor street cooking characteristic of fast-growing cities in developing countries, coupled with meteorological effects led to amplified reductions that continued well into the night, although meteorological effects are more generalised. Blanket policy initiatives targeting peak pollution hours could be adopted across all locations, while transport sector regulation could be very effective for pollution management. Likewise, because of the clustered and diffuse nature of pollution, community driven initiatives could be feasible for long-term mitigation.

Applying machine learning for large scale field calibration of low‐cost PM2.5and PM10air pollution sensors

“…Populations in cities in low and middle-income countries (LMICs) are among those at high risk of exposures to levels that greatly exceed the WHO health guidelines. [4][5][6][7] While there is increasing evidence on the effects of ambient air pollution on human health, many cities in LMICs lack reliable high-resolution and long-term datasets to quantify the scale and magnitude of the problem and its impacts. Ambient air quality data collection is done using reference grade monitors (usually government-managed), for example, the Beta Attenuation Monitor (BAM) which measures Particulate Matter (PM).…”