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| 基于污染足迹模型的太湖流域水环境演变的人文驱动力评估——以江苏省常州市为例 | |
| 引用本文： | 焦雯珺,闵庆文,成升魁,袁正,李静,戴忱.基于污染足迹模型的太湖流域水环境演变的人文驱动力评估——以江苏省常州市为例[J].资源科学,2011,33(2):223-229. |
| 作者姓名： | 焦雯珺 闵庆文 成升魁 袁正 李静 戴忱 |
| 作者单位： | 1. 中国科学院地理科学与资源研究所,北京,100101;中国科学院研究生院,北京,100049 2. 中国科学院地理科学与资源研究所,北京,100101 3. 山东师范大学,济南,250014 4. 中国政法大学,北京,100088 |
| 基金项目： | 国家水体污染控制与治理科技重大专项课题：“太湖流域水生态功能分区与质量目标管理技术示范”(编号：2008ZX07526-007)。 |
| 摘 要： | 太湖流域水环境演变过程虽然具有一定的自然背景,但是流域内高强度的人类活动是导致流域水环境质量恶化的主要原因。本文构建了太湖流域污染足迹模型,以流域上游常州市为例,通过定量分析与模拟污染物排放,综合评估水环境演变的人文驱动力。结果表明:①2007年常州市最大污染足迹为69960.75hm2,总污染足迹为167190.37hm2,人文驱动力较大的地区集中在常州市市区以及新北区、武进区、金坛市和溧阳市的中心城镇;②常州市水环境演变的直接人文驱动力主要是有机物、氮和磷污染物的排放,2007年常州市有机物、氮和磷污染足迹分别为34814.01hm2、62415.61hm2和69960.75hm2,有机物、氮和磷污染物的排放比例大致为2:4:4;③常州市水环境演变的间接人文驱动力可以概括为工农业生产和居民生活,2007年常州市工业、生活和农业污染足迹分别为54943.78hm2、75627.14hm2和36619.45hm2,三者对常州市污染物排放的贡献率大致为33%、45%和22%。研究表明,污染足迹模型通过对区域污染物排放的定量模拟,实现了对区域人类活动特征和空间差异的定量分析,充分揭示了各影响因素之间的逻辑关系和贡献差异,实现了太湖流域水环境演变的人文驱动力评估的整体性、层次性和区域差异性。 |
| 关 键 词： | 生态足迹 污染足迹 人文驱动力 污染物排放 太湖流域 |
| 修稿时间： | 1/4/2011 12:00:00 AM |
An Assessment of Human-induced Drivers of Water Environment Changes in the Taihu Lake Basin Based on a Pollution Footprint Model: A Case Study of Changzhou City, Jiangsu Province |
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| JIAO Wenjun,MIN Qingwen,CHENG Shengkui,YUAN Zheng,LI Jing and DAI Chen.An Assessment of Human-induced Drivers of Water Environment Changes in the Taihu Lake Basin Based on a Pollution Footprint Model: A Case Study of Changzhou City, Jiangsu Province[J].Resources Science,2011,33(2):223-229. | |
| Authors: | JIAO Wenjun MIN Qingwen CHENG Shengkui YUAN Zheng LI Jing and DAI Chen |
| Institution: | Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China;Shandong Normal University, Jinan 250014, China;China University of Political Science and Law, Beijing 100088, China |
| Abstract: | Strong human interference has been found to be the major driver of the deterioration of water quality in the Taihu Lake basin. In the present work, the authors constructed a pollution footprint model and applied it to perform a comprehensive assessment on human-induced drivers of water environment changes in Changzhou City situated in the upper streams of the Taihu Lake basin. Results showed that 1) the maximum and total pollution footprints of Changzhou City were 69 960.75 hm2 and 167 190.37 hm2 in 2007; the spatial distribution of them revealed that downtown Changzhou and the centers of its counties had the strongest human-induced drivers; 2) direct human-induced drivers were found to be the discharge of organic pollutants, surplus nitrogen and phosphorus, showing the footprints of 34 814.01 hm2, 62 415.61 hm2, and 69 960.75 hm2 in 2007, accounting for 21%, 37%, and 42% of the total pollution footprint, respectively; 3) indirect human-induced drivers were primarily industrial production and residents living as well as agricultural production; the pollution footprints for them were 54 943.78 hm2, 75 627.14 hm2, and 36 619.45 hm2, accounting for 33%, 45%, and 22% of the total pollution footprint, respectively. It has been shown that pollution footprints are capable of directly reflecting the status and spatial distribution of regional pollutant discharge and also indirectly revealing the characteristics and spatial distribution of regional human activities. The pollution footprint can be an effective approach to assessing both direct and indirect human-induced drivers of regional water environment changes. This paper performed a quantitative analysis of regional human activities and revealed differences in their contributions to regional water environment changes by quantitatively modeling regional pollutant discharge with a pollution footprint model. This has overcome the deficiencies in current studies on human-induced drivers, and provided a basis for further study on their impacts on water environment changes in an all-around way. |
| Keywords: | Ecological footprint Pollution footprint Human-induced drivers Pollutant discharge Taihu Lake basin |
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