| 区域COD、SO2及TSP排放的空间自相关分析：以江苏省为例 |
| 摘要点击 2697 全文点击 4184 投稿时间：2008-07-30 修订日期：2008-11-28 |
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| 中文关键词 COD SO2 TSP 空间自相关 全局空间自相关 局部空间自相关 |
| 英文关键词 COD SO2 TSP spatial autocorrelation global spatial autocorrelation local spatial autocorrelation |
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| 中文摘要 |
| 空间自相关分析是空间统计学的一个重要组成部分,是认识空间格局的有效手段.针对研究的空间范围不同,常采用全局空间自相关和局部空间自相关来衡量区域空间自相关程度.利用江苏省1990～2006年13个省辖市COD、SO2和TSP排放量数据,采用空间自相关分析方法对江苏省环境污染排放区域异质性进行了研究.结果表明,江苏省COD和TSP排放总量分别从1990年的596?353 t和1?101?404 t显著下降到2006年的291?762 t和704?734 t, SO2排放量基本保持稳定;江苏省COD、SO2和TSP排放的空间自相关性随时间推移正在发生着变化,到2006年COD、SO2和TSP排放的Global Moran's I分别达到0.465?7、 0.214?2和0.510?1,呈现较显著的正空间自相关趋势,空间上的集聚分布格局业已形成,且COD排放先于SO2和TSP排放在空间呈现集聚格局,空间集聚的程度也较大;苏南与苏北的污染排放格局差异较大,苏南COD、SO2和TSP排放的Global Moran's I值至2006年分别增加到0.499?7、 0.320?2和0.298?3,集聚格局明显,而苏北COD、SO2和TSP排放的Global Moran's I值大部分都低于-0.2,没有表现集聚状态.COD排放的集聚区域变为苏州、无锡和常州,SO2排放的集聚区域变为苏州和无锡,TSP排放的空间格局变化不大,苏南五市一直是TSP排放的集聚区域.空间自相关关系的探讨对于认识江苏省区域环境异质性及环境宏观战略研究具有重要意义,也对江苏省生态省建设和和谐社会构建提供重要参考. |
| 英文摘要 |
| 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 704?734 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. |
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