ESTIMATION OF SATELLITE-BASED SO₄²⁻ AND NH₄⁺ COMPOSITION OF AMBIENT FINE PARTICULATE MATTER OVER CHINA USING CHEMICAL TRANSPORT MODEL

We constructed multi-variable random forest models based on 10-fold cross-validation and estimated daily PM_2.5 and O₃ concentration of China in 2005–2017 at a resolution of 1 km. The daily R² values of PM_2.5 and O₃ were 0.85 and 0.77. The meteorological variables can significantly affect both PM_2.5 and O₃ modeling. During 2005–2017, PM_2.5 exhibited an overall downward trend, while O₃ experienced the opposite. The temporal trend of PM_2.5 and O₃ had spatial characteristics during the study period.

Using ground AOD measurements from AERONET, DRAGON-Asia Campaign, and handheld sunphotometers, we evaluated emerging aerosol products from VIIRS, GOCI, and Terra and Aqua MODIS (Collection 6) in East Asia in 2012–2013. We found that satellite aerosol products performed better in tracking the day-to-day variability than the high-resolution spatial variability. VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

The cloud droplet size retrieval of POLDER is accurate even when the measurements are limited. The algorithm can be improved by (1) including the measurements in the primary rainbow region to provide accurate large droplet (>15 µm) retrievals; (2) performing higher-resolution retrieval (42 km × 42 km) to ensure more successful retrievals and reduce the bias introduced by cloud horizontal inhomogeneity.

We demonstrate a post-processing technique to improve MISR-retrieved aerosol optical properties when information content is low. By filtering the list of aerosol mixtures that pass the MISR retrieval acceptance criteria using pre-defined discrepancy thresholds between MISR and GOCART model simulations, the adjusted MISR Angstrom exponent (ANG) and absorbing AOD (AAOD) agree significantly better with sun-photometer validation data, especially when AOD<0.2 for ANG and AOD<0.5 for AAOD.