经济快速发展地区土地利用生态风险评价——以昆山市为例

本文从土地利用视角,在传统生态风险评价框架改进基础上,构建风险三要素评价模型并对昆山地区综合生态风险空间分异分级进行分析,研究结果表明:①风险源强度极点为玉山镇,主因在于工业污染强度大、建设用地比例高以及路网密度大等;较高的镇包括陆家、千灯、花桥和周市;较低的镇包括张浦、淀山湖和巴城;最低的为周庄与锦溪,主因来自在于其旅游重镇及重要粮食作物产区的地位;②受体暴露度最大为巴城与周市,玉山、张浦、锦溪、周庄其次,淀山湖相对较低;陆家、千灯和花桥最低,受体暴露度大的区域发生潜在生态风险的可能性更大;③风险效应值最高为玉山镇;陆家、千灯、花桥和周市较高,张浦、淀山湖和巴城较低,周庄与锦溪的最低;风险源强与风险效应存在极高相关性,相关系数达0.961;④综合生态风险的高风险区位于玉山镇;巴城、周市、陆家较高风险;张浦、千灯、花桥和淀山湖较低;周庄和锦溪则最低,昆山综合生态风险值的空间分布呈现以玉山为极点,自北向南递减趋势。

Assessment of Land Use Ecological Risks in Rapidly Developing Regions: A Case Study on Kunshan City

Based on a traditional ecology risk assessment framework and referring to certain assessment modes of relative risk assessment models abroad, an index system with regard to assessment on land use ecology risks was developed by accounting for three aspects, including the strength of risk sources, the exposure degree of risk receptors and the risk effect. Taking the town as a study unit, an assessment model consisting of the three elements of ecology risks was proposed using the principal component analysis (PCA). Values of the assessment for each unit were obtained by the assessment model, and then comprehensive ecology risk values for each unit were calculated. In addition, the authors performed an analysis on spatial distribution and classification for the three elements of ecology risks and calculated comprehensive ecology risk values. Results are given as follows. First, the highest risk source strength was found to be in Yushan Town which is located in the urban area of Kunshan City. The main reasons for this could be ascribed to the highest strength of industrial pollution emissions and the highest proportion of land for construction. It was suggested that Lujia, Qiandeng, Huaqiao and Zhoushi were towns showing relatively higher values of risk source strength. Zhangpu, Dianshanhu, Bacheng, Zhouzhuang and Jinxi showed relatively lower values of risk source strength since these towns are important tourism regions and grain production areas suffering from relatively lower industrial pollution emissions and having the lowest proportion of land for construction. Second, Bacheng and Zhoushi exhibited the highest values of receptor exposure and the towns having relatively higher values of receptor exposure included Yushan, Zhangpu, Jinxi and Zhouzhuang. Dianshanhu showed a lower value of receptor exposure. Lujia, Qiandeng and Huaqiao showed the lowest values as for receptor exposure. In general, the value for receptor exposure reflects possible risks given the same risk sources. As such, the areas showing higher values of receptor exposure might expose in higher ecology risks. Third, Yushan showed the highest value of risk effect. The towns having higher values of risk effect contained Lujia, Qiandeng, Huaqiao and Zhoushi. Zhanpu, Dianshanhu and Bacheng showed relatively lower values of risk effect and Zhouzhuang and Jinxi showed the lowest ones. It was also found that there exists very high correlation between the value of risk resource and the value of risk effect, showing a correlation coefficient of 0.961. Forth, there existed four types of spatial distribution for the comprehensive ecological risk value in Kunshan. Yushan showed the highest risk zone and relatively higher risk zones included Bacheng, Zhoushi and Lujia. Zhangpu, Qiandeng, Huaqiao and Dianshanhu had relatively lower risk values. Zhouzhuang and Jinxi showed the lowest risk values. Regarding spatial distribution of the comprehensive ecology risk, the values showed a decreasing trend from the north to the south in Kunshan City.