PM_2.5 retrieval from satellite-observed aerosol optical depth (AOD) is still challenging due to the strong impact of meteorology. We investigate influences of meteorology changes on the inter-annual variations of AOD and surface PM_2.5 in China between 2006 and 2017 using a nested 3D chemical transport model, GEOS-Chem, by fixing emissions at the 2006 level. We then identify major meteorological elements controlling the inter-annual variations of AOD and surface PM_2.5 using multiple linear regression. We find larger influences of meteorology changes on trends of AOD than that of surface PM_2.5. On the seasonal scale, meteorology changes are beneficial to AOD and surface PM_2.5 reduction in spring (1–50%) but show an adverse effect on aerosol reduction in summer. In addition, major meteorological elements influencing variations of AOD and PM_2.5 are similar between spring and fall. In winter, meteorology changes are favorable to AOD reduction (−0.007 yr⁻¹, −1.2% yr⁻¹; p < 0.05) but enhanced surface PM_2.5 between 2006 and 2017. The difference in winter is mainly attributed to the stable boundary layer that isolates surface PM_2.5 from aloft. The significant decrease in AOD over the years is related to the increase in meridional wind speed at 850 hPa in NCP (p < 0.05). The increase of surface PM_2.5 in NCP in winter is possibly related to the increased temperature inversion and more stable stratification in the boundary layer. This suggests that previous estimates of wintertime surface PM_2.5 using satellite measurements of AOD corrected by meteorological elements should be used with caution. Our findings provide potential meteorological elements that might improve the retrieval of surface PM_2.5 from satellite-observed AOD on the seasonal scale.

As the concentration of fine particles (PM_2.5) is declining, ozone (O₃) concentration has been increasing in China in recent years. To collaboratively control PM_2.5 and O₃, it is critical to understand the relationship between the two and identify major controlling factors. We use a convergent cross-mapping method to detect the causal relationship between daily PM_2.5 and maximum daily 8 h average (MDA8) O₃ concentrations in Beijing, Taizhou, Shenzhen and Chengdu, China, in the four seasons in 2015–2021. In addition, we also examined causal effects of atmospheric oxidation capacity, precursors and meteorological elements on PM_2.5 and MDA8 O₃ in the four cities. PM_2.5 and MDA8 O₃ are strongly positively correlated and show bidirectional causal relationships during the Beijing and Taizhou summer and in the four seasons in Shenzhen, due mainly to the strong photochemical reactions in the daytime. During the Beijing winter, PM_2.5 and MDA8 O₃ show bidirectional causal relationships, but the two are significantly negatively correlated, driven by NO₂ and relative humidity. Weak bidirectional, unidirectional and no causal effects between PM_2.5 and MDA8 O₃ are detected in other seasons in the four cities. In these seasons and cities, the top three causal factors of PM_2.5 differ from those of MDA8 O₃. Season-, city- and pollutant-specific control measures of PM_2.5 and MDA8 O₃ are required.

World Health Organization updated the target of annual mean NO₂ from 40 μg m⁻³ to 10 μg m⁻³ in 2021 based on new evidences that showed statistically independent effects of long-term exposure to ambient NO₂ and mortality. We estimate the excess deaths associated with long-term exposure to ambient NO₂ (DAAN) from non-accidental disease (NAD), cardiovascular disease (CVD) and respiratory disease (RD) in China in 2013–2020 using a counterfactual analytic framework adopted by Global Burden Disease. We use relative risk (RR) values based on a meta-analysis, and assume a linear concentration-response (C-R) function and a threshold value of 10 μg m⁻³. DAAN from NAD vary in 279 (95% Cl: 189–366) to 339 (95% Cl: 231–442) thousand in 2013–2020, comparable to excess deaths attributed to long-term exposure to ambient O₃ in China. DAAN from NAD changes by −43%–+220% using different RR values, C-R function shapes, and threshold values. DAAN from RD reduces while those from CVD increases significantly in 2013–2020. DAAN from RD account for ∼10% of total DAAN. We found that the reduction of NO₂ concentration and baseline mortality of NAD offsets the adverse effects of population growth and aging in 2013–2017. In 2017–2020, the contribution from air pollution reduction surpasses the adverse effects of population growth and aging in most regions. We suggest that continuing the reduction rate of NO₂ emissions in 2013–2020 would offset the effects of population growth and aging in 2020–2030. Faster reduction of NO₂ sources is required to reduce DAAN in Liaoning, Shanxi, Shanghai, and Anhui, where DAAN from NAD, CVD and RD increased in 2013–2020. Our results should be interpreted with caution because the causality support of long-term exposure to ambient NO₂ on mortality from toxicological studies is not firm yet, and NO₂ is possibly just a marker of traffic-related pollutants.

We identified controlling factors of the inter-annual variations of surface PM_2.5–aerosol optical depth (AOD) relationship in China from 2006 to 2017 using a nested 3D chemical transport model—GEOS-Chem. We separated the contributions from anthropogenic emission control and meteorological changes by fixing meteorology at the 2009 level and fixing anthropogenic emissions at the 2006 level, respectively. Both observations and model show significant downward trends of PM_2.5/AOD ratio (η, p < 0.01) in the North China Plain (NCP), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) in 2006–2017. The model suggests that the downward trends are mainly attributed to anthropogenic emission control. PM_2.5 concentration reduces faster at the surface than aloft due to the closeness of surface PM_2.5 to emission sources. The Pearson correlation coefficient of surface PM_2.5 and AOD (r_PM-AOD) shows strong inter-annual variations (±27%) but no statistically significant trends in the three regions. The inter-annual variations of r_PM-AOD are mainly determined by meteorology changes. Except for the well-known effects from relative humidity, planetary boundary layer height and wind speed, we find that temperature, tropopause pressure, surface pressure and atmospheric instability are also important meteorological elements that have a strong correlation with inter-annual variations of r_PM-AOD in different seasons. This study suggests that as the PM_2.5–AOD relationship weakens with reduction of anthropogenic emissions, validity of future retrieval of surface PM_2.5 using satellite AOD should be carefully evaluated.