Characterizing particulate air pollution in rural areas of Bangladesh using a network of low-cost sensors

Abstract

This study presents a comprehensive study on characterizing fine particulate matter (PM2.5) pollution levels across Bangladesh through an utilization of a network of low-cost sensors. Prior to deployment in rural sites, the low-cost sensors were calibrated against a reference PM2.5 monitor (Beta Attenuation Monitor, BAM)at DoE continuous air monitoring stations (CAMS). The calibration process involved continuous data collection for one month each during the dry and wet seasons. This rigorous calibration ensured the accuracy and reliability of the collected data. Over a four-month period, comprising two months each in the dry and wet seasons, continuous measurements were collected at 20 rural sites spread across the country. The raw data gathered from these rural deployments were then corrected using calibration models developed from the co-location deployments. The calibration of the low-cost sensors against the reference monitor showed excellent agreement, with consistent sensor-to-sensor performance throughout the calibration process. The linear calibration models achieved a R2 of 0.85 - 0.9, and the normalized root mean square error (RMSE) ranged between 10-15%. The average PM2.5 levels measured across the 20 rural sites were remarkably higher, ranging from 49 to 214µg/m3, in comparison to the WHO interim target-1 of 35µg/m3. Furthermore, a comparison of pollution levels in rural areas with those in Dhaka, one of South Asia's most polluted megacities, revealed that many rural sites exhibited comparable or within 10-20% of Dhaka's pollution levels. This finding suggests that regional pollution is a significant driver of PM2.5 pollution across the country, with local urban sources contributing an additional 10-20%. The study also identified a regional spatial gradient in measured pollution levels, with higher concentrations observed in the western and central parts of Bangladesh compared to the eastern region. This spatial gradient is likely due to the influence of transboundary pollution from neighboring Indian states, particularly the Indo-Gangetic Plain (IGP) states. The study's seasonal analysis demonstrated substantial variation in PM2.5 levels in rural areas. During the wet season, concentrations ranged from 49 to 98µg/m3, while during the dry season, they varied from 55 to 214µg/m3. These seasonal fluctuations are likely driven by meteorological factors, seasonal influx of transboundary air pollution, and seasonal sources. It is evident from the findings of the study that addressing PM2.5 pollution across Bangladesh requires a comprehensive, regional air quality management approach. Such an approach should encompass collaboration between various regions to collectively combat air pollution effectively and safeguard public health. While this study is a significant advancement in understanding PM2.5 pollution in Bangladesh, to gain deeper insights into long-term pollution dynamics, it is crucial to conduct multi-year continuous measurements in rural locations. Additionally, it is essential to characterize the long-term performance of low-cost sensors to ensure their sustainable and effective application in rural areas.