The Indo-Gangetic Plain (IGP) is home to 9 % of the global population and is responsible for a large fraction of agricultural crop production in Pakistan, India, and Bangladesh. Levels of fine particulate matter (mean diameter <2.5 µm, PM_2.5) across the IGP often exceed human health recommendations, making cities across the IGP among the most polluted in the world. Seasonal changes in the physical environment over the IGP are dominated by the large-scale south Asian monsoon system that dictates the timing of agricultural planting and harvesting. We use the WRF-Chem model to study the seasonal anthropogenic, pyrogenic, and biogenic influences on fine particulate matter and its constituent organic aerosol (OA) over the IGP that straddles Pakistan, India, and Bangladesh during 2017–2018. We find that surface air quality during pre-monsoon (March–May) and monsoon (June–September) seasons is better than during post-monsoon (October–December) and winter (January–February) seasons, but all seasonal mean values of PM_2.5 still exceed the recommended levels, so that air pollution is a year-round problem. Anthropogenic emissions influence the magnitude and distribution of PM_2.5 and OA throughout the year, especially over urban sites, while pyrogenic emissions result in localised contributions over the central and upper parts of IGP in all non-monsoonal seasons, with the highest impact during post-monsoon seasons that correspond to the post-harvest season in the agricultural calendar. Biogenic emissions play an important role in the magnitude and distribution of PM_2.5 and OA during the monsoon season, and they show a substantial contribution to secondary OA (SOA), particularly over the lower IGP. We find that the OA contribution to PM_2.5 is significant in all four seasons (17 %–30 %), with primary OA generally representing the larger fractional contribution. We find that the volatility distribution of SOA is driven mainly by the mean total OA loading and the washout of aerosols and gas-phase aerosol precursors that result in SOA being less volatile during the pre-monsoon and monsoon season than during the post-monsoon and winter seasons.

Few studies have examined exposure disparity to ambient air pollution outside North America and Europe. Moreover, very few studies have investigated exposure disparity in terms of individual-level data or at multi-temporal scales. This work aims to examine the associations between individual- and neighbourhood-level economic statuses and individual exposure to PM2.5 across multi-temporal scales. The study population included 742,220 mobile phone users on a weekday in Shenzhen, China. A geo-informed backward propagation neural network model was developed to estimate hourly PM2.5 concentrations by the use of remote sensing and geospatial big data, which were then combined with individual trajectories to estimate individual total exposure during weekdays at multi-temporal scales. Coupling the estimated PM2.5 exposure with housing price, we examined the associations between individual- and neighbourhood-level economic statuses and individual exposure using linear regression and two-level hierarchical linear models. Furthermore, we performed five sensitivity analyses to test the robustness of the two-level effects. We found positive associations between individual- and neighbourhood-level economic statuses and individual PM2.5 exposure at a daytime, daily, weekly, monthly, seasonal or annual scale. Findings on the effects of the two-level economic statuses were generally robust in the five sensitivity analyses. In particular, despite the insignificant effects observed in three of newly selected time periods in the sensitivity analysis, individual- and neighbourhood-level economic statuses were still positively associated with individual total exposure during each of other newly selected periods (including three other seasons). There are statistically positive associations of individual PM2.5 exposure with individual- and neighbourhood-level economic statuses. That is, people living in areas with higher residential property prices are more exposed to PM2.5 pollution. Findings emphasize the need for public health intervention and urban planning initiatives targeting socio-economic disparity in ambient air pollution exposure, thus alleviating health disparities across socioeconomic groups.