In recent decades China has experienced high-level PM_2.5 pollution and then visible air quality improvement. To understand the air quality change from the perspective of decompose aerosol optical depth (AOD), we adopted two statistical methods of Empirical Orthogonal Functions (EOF) and Non-negative matrix Factorization (NMF) to AOD retrieved by MODIS over China and surrounding areas. Results showed that EOF and NMF identified the important factors influencing AOD over China from different angles: natural dusts controlled the seasonal variation, and anthropogenic emissions have larger contribution to AOD magnitude. To better observe the interannual variation of different sources, we removed seasonal cycles from original data and conducted EOF analysis on AOD monthly anomalies. Results showed aerosols from anthropogenic sources had the greatest contribution (27%) to AOD anomalies nationwide and took an obvious downward trend, and natural dust was the second largest contributor with contribution of 17%. In the areas surrounding China, the eastward aerosol transport due to prevailing westerlies in spring significantly influenced the AOD variation over West Pacific with the largest contribution of 21%, whereas the aerosol transport from BTH region in winter had relative greater impact on the AOD magnitude. After removing seasonal cycles, biomass burning in South Asia became the most important influencing factor on AOD anomalies with contribution of 10%, as its interannual variability was largely affected by El Niño. Aerosol transport from BTH was the second largest contributor with contribution of 8% and showed a decreasing trend. This study showed the downtrend of AOD over China since 2011 was dominated by aerosols from anthropogenic sources, which in a way confirmed the effectiveness of air pollution control policies.

MODIS,AOD,EOF,Non-Negative Matrix Factorization (NMF)