An environmental justice analysis of air pollution in India.

Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 µg/m3 (95% CI 0.062 µg/m3, 0.192 µg/m3) and 0.199 µg/m3 (95% CI 0.116 µg/m3, 0.283 µg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.

Spatial and sector-specific contributions of emissions to ambient air pollution and mortality in European cities: a health impact assessment.

BACKGROUND: Ambient air pollution is a major risk to health and wellbeing in European cities. We aimed to estimate spatial and sector-specific contributions of emissions to ambient air pollution and evaluate the effects of source-specific reductions in pollutants on mortality in European cities to support targeted source-specific actions to address air pollution and promote population health. METHODS: We conducted a health impact assessment of data from 2015 for 857 European cities to estimate source contributions to annual PM2·5 and NO2 concentrations using the Screening for High Emission Reduction Potentials for Air quality tool. We evaluated contributions from transport, industry, energy, residential, agriculture, shipping, and aviation, other, natural, and external sources. For each city and sector, three spatial levels were considered: contributions from the same city, the rest of the country, and transboundary. Mortality effects were estimated for adult populations (ie, ≥20 years) following standard comparative risk assessment methods to calculate the annual mortality preventable on spatial and sector-specific reductions in PM2·5 and NO2. FINDINGS: We observed strong variability in spatial and sectoral contributions among European cities. For PM2·5, the main contributors to mortality were the residential (mean contribution of 22·7% [SD 10·2]) and agricultural (18·0% [7·7]) sectors, followed by industry (13·8% [6·0]), transport (13·5% [5·8]), energy (10·0% [6·4]), and shipping (5·5% [5·7]). For NO2, the main contributor to mortality was transport (48·5% [SD 15·2]), with additional contributions from industry (15·0% [10·8]), energy (14·7% [12·9]), residential (10·3% [5·0]), and shipping (9·7% [12·7]). The mean city contribution to its own air pollution mortality was 13·5% (SD 9·9) for PM2·5 and 34·4% (19·6) for NO2, and contribution increased among cities of largest area (22·3% [12·2] for PM2·5 and 52·2% [19·4] for NO2) and among European capitals (29·9% [12·5] for PM2·5 and 62·7% [14·7] for NO2). INTERPRETATION: We estimated source-specific air pollution health effects at the city level. Our results show strong variability, emphasising the need for local policies and coordinated actions that consider city-level specificities in source contributions. FUNDING: Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making 2023-2026 Horizon Europe project.

COVID-19 lockdowns cause global air pollution declines.

The lockdown response to coronavirus disease 2019 (COVID-19) has caused an unprecedented reduction in global economic and transport activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations, using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find declines in the population-weighted concentration of ground-level nitrogen dioxide (NO2: 60% with 95% CI 48 to 72%), and fine particulate matter (PM2.5: 31%; 95% CI: 17 to 45%), with marginal increases in ozone (O3: 4%; 95% CI: -2 to 10%) in 34 countries during lockdown dates up until 15 May. Except for ozone, satellite measurements of the troposphere indicate much smaller reductions, highlighting the spatial variability of pollutant anomalies attributable to complex NOx chemistry and long-distance transport of fine particulate matter with a diameter less than 2.5 µm (PM2.5). By leveraging Google and Apple mobility data, we find empirical evidence for a link between global vehicle transportation declines and the reduction of ambient NO2 exposure. While the state of global lockdown is not sustainable, these findings allude to the potential for mitigating public health risk by reducing "business as usual" air pollutant emissions from economic activities. Explore trends here: https://nina.earthengine.app/view/lockdown-pollution.