Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty

Annual global satellite-based estimates of fine particulate matter (PM_2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998–2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM_2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5–3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM_2.5 concentrations exceed 90 μg/m³, with local concentrations of approximately 200 μg/m³ for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM_2.5 concentrations have decreased over the period 2010–2019 by 1.6–2.6 μg/m³/year, with decreases beginning 2–3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM_2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM_2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM_2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.