Research On Spatial Interpolation Method Of Air Quality Index Based On

In recent years, with the frequent fog and haze, the public of china got more and more attention to the air quality. The new standard of air quality issued in 2012, with the Air Quality Index (AQI) to replace the existing air pollution index (API) for air quality status was described quantitatively. PM2.5, which is closely related with the formation of haze, and ozone, reflect photochemical pollution caused by motor vehicle exhaust, were incorporated into the evaluation system of AQI. Jiangsu which is the province with a large population of China, due to its social and economic development status and urban planning needs, have put forward higher requirements on the air quality. Therefore, it has important practical significance to explore the characteristics of temporal and spatial distribution of the air quality index of Jiangsu Province, to establish the air quality index prediction model within the province.This study, basing on the daily AQI data of Jiangsu Province from January 2013 to February 2014, analyzed the province’s air quality. First of all, to the provincial capital of Nanjing as an example, the characteristics of AQI changed in different seasons, the weekdays and weekends differences were analyzed, and using the method of combining qualitative analysis and quantitative analysis considered air temperature and precipitation factors to AQI. Secondly, the spatial autocorrelation of AQI were explored, to understand the AQI’s feature of spatial cluster. By the method of the histogram, QQ-normal distribution map, trend analysis, explored and analyzed the AQI data for 2013. Finally, multiple spatial interpolation method were compared, basing on the prediction accuracy to select the most appropriate model to analyze the spatial distribution of the province’s AQI, and the compliance rate AQI forecast. The main conclusions are as follows:Summer 2013 is the best year-round air quality time in Jiangsu Province, as well as in Nanjing. Nanjing weekday AQI was much higher than the weekend. There was a weekend effect. Also, linear correlations between temperature and AQI. precipitation and AQI of Nanjing were existed. AQI of Jiangsu Province between the various monitoring sites displayed strong spatial autocorrelation properties. Suzhou, Taizhou and Nantong showed "High High" spatial cluster consecutively in July 2013 and August 2013. The overall AQI trend of Jiangsu Province from west to east first decreased by a slight, and then increased gradually. The north-south direction was relatively stable. By the evaluation of accuracy of various interpolation models, the GPI model had minimum RMS, but kriging surface was more clearly in the local details. Distribution of the province’s AQI, along the coast from inland to coastal areas was gradually reduced. The highest AQI value was in Xuzhou.To create AQI probability map which exceeded the threshold value 100, the most important feature is the ability to easily identify areas of excessive AQI, so that the public have a more intuitive feel for the air condition, but also provide effective reference for government departments about air quality forecasting and early warning.