Publications

Xu, JH; Jiang, H; Xiao, ZY; Wang, B; Wu, J; Lv, X (2016). Estimating Air Particulate Matter Using MODIS Data and Analyzing Its Spatial and Temporal Pattern over the Yangtze Delta Region. SUSTAINABILITY, 8(9), 932.

Abstract
The deteriorating air quality in the Yangtze delta region is attracting growing public concern. In this paper, seasonal estimation models of the surface particulate matter (PM) were established by using aerosol optical thickness (AOT) retrievals from the moderate resolution imaging spectro-radiometer (MODIS) on board NASA's Terra satellite. The change of the regional distribution of the atmospheric mixed layer, relative humidity and meteorological elements have been taken into account in these models. We also used PM mass concentrations of ground measurements to evaluate the estimation accuracy of those models. The results show that model estimation of PM2.5 and PM10 mass concentrations were in good agreement with the ground-based observation of PM mass concentrations (p < 0.01, the R-2 value of the PM2.5 concentrations experimental model for four seasons are 0.48, 0.62, 0.61 and 0.52 respectively. The R-2 value of PM10 concentrations experimental model for four seasons are 0.57, 0.56, 0.64 and 0.68 respectively). At the same time, spatial and temporal variations of PM2.5 and PM10 mass concentrations were analysed over the Yangtze delta region from 2000 to 2013. The results show that PM2.5 and PM10 show a trend of increase in the Yangtze delta region from 2000 to 2013 and change periodically. The maximum mass concentration of PM2.5 and PM10 was in January-February, and the minimum was in July-August. The highest values of PM2.5 and PM10 mass concentration are in the region of urban agglomeration which is grouped to a delta-shaped region by Shanghai, Hangzhou and Nanjing, while the low values are in the forest far away from the city. PM mass concentration over main cities and rural areas increased gradually year by year, and were increasing more quickly in urban areas than in rural areas.

DOI:
10.3390/su8090932

ISSN:
2071-1050