Assessment of Spatio-Temporal Variations in PM2.5 Associated Long-Range Air Mass Transport and Mortality in South Asia

Abstract

Fine particulate matter (PM_2.5) is associated with adverse impacts on ambient air quality and human mortality; the situation is especially dire in developing countries experiencing rapid industrialization and urban development. This study assessed the spatio-temporal variations of PM_2.5 and its health impacts in the South Asian region. Both satellite and station-based data were used to monitor the variations in PM_2.5 over time. Additionally, mortality data associated with ambient particulate matter were used to depict the overall impacts of air pollution in this region. We applied the Mann&ndash;Kendall and Sen&rsquo;s slope trend analysis tool to investigate the trend of PM_2.5. At the same time, clustering of backward trajectories was used for identifying the long-range air mass transport. The results revealed that the mean annual PM_2.5 mass concentration was the highest (46.72 &micro;g/m³) in Bangladesh among the South Asian countries during 1998&ndash;2019, exceeding the national ambient air quality standards of Bangladesh (i.e., 15 &micro;g/m³) and WHO (10 &micro;g/m³), while lower PM_2.5 was observed in the Maldives and Sri Lanka (5.35 &micro;g/m³ and 8.69 &micro;g/m³, respectively) compared with the WHO standard. The trend analysis during 1998&ndash;2019 suggested that all South Asian countries except the Maldives experienced an increasing trend (<i>p</i> &lt; 0.05) of PM_2.5. The study showed that among the major cities, the mean annual PM_2.5 value was the highest in New Delhi (110 &micro;g/m³), followed by Dhaka (85 &micro;g/m³). Regarding seasonal variation, the highest PM_2.5 was found during the pre-monsoon season in all cities. The findings of this research would help the concerned governments of South Asian countries to take steps toward improving air quality through policy interventions or reforms. Moreover, the results would provide future research directions for studying the trend and transport of atmospheric PM_2.5 in other regions.