Accuracy assessment of CAMS and MERRA-2 reanalysis PM2.5 and PM10 concentrations over China

Rapid industrialization and urbanization significantly contribute to air pollution in China. Essential constituents 
of air pollution are fine and coarse particulate matter which are the total mass of aerosol particles with aerdynamic
diameters smaller than ≤2.5 μm (PM2.5) and ≤10 μm (PM10), respectively. These particles may cause 
severe health effects, and impact the atmospheric environment and climate. However, the limited number of 
ground-based measurements at sparsely distributed air quality monitoring stations hamper long-term air 
pollution impact studies over large areas. Although spatial data on PM2.5 and PM10 are available from reanalysis
models, the accuracy of such data may be reduced in comparison with ground data and may vary regionally and 
seasonally. Therefore, a long-term evaluation of reanalysis-based PM2.5 and PM10 against ground-based
measurements is needed for China. In this study, surface-level PM2.5 and PM10 concentrations from 2014 to 2020 
obtained from the Copernicus Atmospheric Monitoring Service (CAMS), and from the second version of
Modern-Era Retrospective analysis for Research and Applications (MERRA-2) were evaluated using
ground-based measurements obtained from 1675 air quality monitoring stations
distributed across China. High PM2.5 and PM10 (μg/m3) concentrations from ground-based
measurements were observed in many parts of China (including the 
North China Plain: NCP, Yangtse River Delta:YRD, Pearl River Delta: PRD, Central China, Sichuan Basin: SB, and 
northwestern region: Tarim Basin). The patterns of the spatial distributions of PM2.5 and PM10 obtained from 
CAMS and MERRA-2 across China are similar to those of the ground-based monitoring data, but the concentrations
from both models are substantially different. CAMS significantly overestimates PM2.5 and PM10 over 
most regions, in particular over urban and desert areas, whereas MERRA-2 seasonal and annual mean concentrations
were more accurate over the highly polluted areas in central and eastern China. The lowest PM2.5 and 
PM10 concentrations were observed over the Tibetan Plateau and Qinghai, where CAMS and MERRA-2 datasets 
were substantially underestimated. Furthermore, both CAMS and MERRA-2 under-and over-estimate the PM 
concentrations in both low and high pollution conditions. Overall, this study contributes to understanding of the 
reliability of reanalysis data and provides a baseline document for improving the CAMS and MERRA-2 datasets 
for studying local and regional air quality in China.