[Application of spatial autocorrelation analysis to the COD, SO2 and TSP emission in Jiangsu province].
Spatial autocorrelation is an effective tool of spatial statistics, which is used to disclose the spatial structure of regional disparity. There are two different scales to measure regional spatial dependence: global spatial autocorrelation and local spatial autocorrelation. Based on environmental data of 13 cities in Jiangsu province from 1990 to 2006, the regional disparity of COD, SO2 and TSP emission was discussed by using spatial autocorrelation analysis methods. The results show that total emission of COD and TSP decreased respectively from 596 353 t and 1 101 404 t in 1990 to 291 762 t and 704734 t in 2006, while total emission of SO2 kept steady. In 2006, Global Moran's I of COD, SO2 and TSP emission was 0.465 7, 0.214 2 and 0.510 1 respectively. It is identified that positive spatial autocorrelation is presented and spatial aggregation pattern of COD, SO2 and TSP emission are appeared. However, spatial aggregation pattern of COD emission appears earlier than that of SO2 and TSP, and spatial aggregation degree of COD is also higher than that of SO2 and TSP. There are different spatial patterns between southern and northern Jiangsu. In southern Jiangsu, Global Moran's I of COD, SO2 and TSP emission had increased to 0.499 7, 0.320 2 and 0.298 3 up to 2006, and spatial aggregation pattern appeared remarkably. In northern Jiangsu, most of the Global Moran's I were less than -0.2, and spatial aggregation pattern disappeared accordingly. High cluster region of COD emission is Suzhou, Wuxi and Changzhou, and high cluster region of SO2 emission is Suzhou and Wuxi. However, spatial pattern of TSP emission does not change much and five cities of southern Jiangsu (Suzhou, Wuxi, Changzhou, Zhenjiang, Nanjing) are still the high cluster region. The last, the research provides an important cognition to regional environment disparity and macro-environmental strategy, and a significant means to harmonious society and eco-province construction in Jiangsu province.
Zhao
Xiao-Feng
XF
Laboratory of Environmental Geography in Land Resources and Tourism Sciences Department, Nanjing University, Nanjing 210093, China. zhao-xf@126.com
Huang
Xian-Jin
XJ
Zhang
Xing-Yu
XY
Zhu
De-Ming
DM
Lai
Li
L
Zhong
Tai-Yang
TY
D000393:Air Pollutants / Q000032:analysis*; D002681:China; D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods*; D009930:Organic Chemicals / Q000032:analysis*; D010316:Particle Size; D013458:Sulfur Dioxide / Q000032:analysis*
D000393:Air Pollutants; D009930:Organic Chemicals; D013458:Sulfur Dioxide