Methods for defining the scopes and priorities for joint prevention and control of air pollution regions based on data-mining technologies

In order to improve the efficiency of joint prevention and control of regional air pollution (JPCAP), we, taking advantage of the big data of long-term pollution, proposed a new method for defining JPCAP scopes based on data-mining technologies and a new method for evaluating JPCAP regions' priorities based on the technique for order preference by similarity to an ideal solution (TOPSIS). And then we applied them to the case of Jointly Prevent and Control the pollutions of particulates smaller than 2.5 μm (PM2.5) and ozone (O3) in 15 cities of the Yangtze River Delta, China. Results showed that the 15 cities of the study region could be subdivided into four JPCAP sub-regions for PM2.5, i.e. R1 = {SZ, WX, CZ, JX, HUZ, SH, NT}, R2 = {YZ, ZJ, TZJ, NJ}, R3 = {HAZ, SX, NB}, and R4 = {TZZ}, and nine for O3, i.e. R1 = {SZ, WX, HUZ}, R2 = {HAZ, JX}, R3 = {SH}, R4 = {NT}, R5 = {YZ, ZJ, TZJ, NJ}, R6 = {CZ}, R7 = {SX}, R8 = {NB}, and R9 = {TZZ}. The priorities order evaluated for the four PM2.5 sub-regions are R1>R2>R3>R4, and the nine O3 sub-regions' order are R3 > R6 > R1 > R7 > R4 > R5 > R2 > R8 > R9. This perfectly match their actual conditions, suggesting that the new methods we developed are scientific and effective.463