Decoding population PM_2.5 exposure in China: interplay of emissions, meteorology, and inequality (2013-2020)

Over the past decade, China has significantly improved air quality by integrating environmental policies with economic growth. Yet, environmental inequality remains a major challenge to social equity and sustainable development. This study examines the socioeconomic impacts of PM_2.5 exposure using population data from 1,317 county towns across 32 provinces (2013-2020), employing meteorological normalization and population-weighted exposure indices. The findings reveal that lower-income regions (L4) achieved the highest PM_2.5 reduction (54%), whereas wealthier regions (L1-L3), despite higher pollution levels, saw lower reductions (45-50%), highlighting an unequal emission reduction burden. PM_dw exhibits more stable spatiotemporal patterns than PM_2.5, offering clearer insights into emission trends. Despite overall improvements, residents in less-developed areas still face higher exposure, while urban centers, benefiting from more resources, experience increased health risks. Vulnerable populations-including coal miners, the educated, women, and the older adult-disproportionately suffer from high exposure levels. Meteorological conditions have generally mitigated PM_2.5 exposure, with the most significant dispersion effect in 2018. Notably, meteorology's role in mitigating inequality in occupational exposure significantly decreased from 43.7% in 2013 to 4.5% in 2019, while its exacerbating effect on urban-rural inequality, contributing 43.7% in 2010, drastically reduced by 2020, even shifting to a slight alleviating role. To achieve equitable environmental governance and robust pollution control, policies must not only address regional economic disparities and prioritize protection for disadvantaged communities but also account for the complex and evolving modulating role of meteorological conditions on exposure inequality.