Impacts of elevated-aerosol-layer and aerosol type on the correlation of AOD and particulate matter with ground-based and satellite measurements in Nanjing, southeast China

Sci Total Environ. 2015 Nov 1:532:195-207. doi: 10.1016/j.scitotenv.2015.05.136. Epub 2015 Jun 10.

Abstract

Assessment of the correlation between aerosol optical depth (AOD) and particulate matter (PM) is critical to satellite remote sensing of air quality, e.g. ground PM10 and ground PM2.5. This study evaluates the impacts of aloft-aerosol-plume and aerosol-type on the correlation of AOD-PM by using synergistic measurement of a polarization-sensitive Raman-Mie lidar, CIMEL sunphotometer (SP) and TEOM PM samplers, as well as the satellite MODIS and CALIPSO, during April to July 2011 in Nanjing city (32.05(○)N/118.77(○)E), southeast China. Aloft-aerosol-layer and aerosol types (e.g. dust and non-dust or urban aerosol) are identified with the range-resolved polarization lidar and SP measurements. The results indicate that the correlations for AOD-PM10 and AOD-PM2.5 can be much improved when screening out the aloft-aerosol-layer. The linear regression slopes show significant differences for the dust and non-dust dominant aerosols in the planetary boundary layer (PBL). In addition, we evaluate the recent released MODIS-AOD product (Collection 6) from the "dark-target" (DT) and "deep-blue" (DB) algorithms and their correlation with the PM in Nanjing urban area. The results verify that the MODIS-DT AODs show a good correlation (R = 0.89) with the SP-AOD but with a systematic overestimate. In contrast, the MODIS-DB AOD shows a moderate correlation (R = 0.66) with the SP-AOD but with a smaller regression intercept (0.07). Furthermore, the moderately high correlations between the MODIS-AOD and PM10 (PM2.5) are indicated, which suggests the feasibility of PM estimate using the MODIS-AOD in Nanjing city.

Keywords: AOD; Lidar; PM(10); PM(2.5); Satellite.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aerosols / analysis*
  • Air Pollutants / analysis*
  • Air Pollution / statistics & numerical data
  • China
  • Cities
  • Environmental Monitoring*
  • Particulate Matter / analysis
  • Remote Sensing Technology
  • Satellite Imagery*

Substances

  • Aerosols
  • Air Pollutants
  • Particulate Matter