长江流域资源与环境 >> 2024, Vol. 33 >> Issue (5): 971-981.doi: 10.11870/cjlyzyyhj202405006

• 自然资源 • 上一篇    下一篇

南水北调中线工程受水区灰水足迹荷载系数时空变化及驱动因素研究

吴梦   

  1. (南阳师范学院经济与管理学院,河南 南阳 473061)
  • 出版日期:2024-05-20 发布日期:2024-05-29

Spatial-temporal Variation and Driving Factors of Grey Water Footprint Loading Coefficient in Water-Receiving Area of Central Route of the South-to-North Water Diversion Project

WU Meng   

  1. (School of Economics and Management, Nanyang Normal University, Nanyang 473061, China)
  • Online:2024-05-20 Published:2024-05-29

摘要: 控制水污染程度、提高水环境质量有利于南水北调中线工程高质量发展。在核算南水北调中线工程20个受水城市灰水足迹的基础上,计算各受水城市灰水足迹荷载系数,分析其时空分布特征,并利用对数平均迪氏指数(Logarithmic Mean Divisia Index,LMDI)模型对其驱动因素进行分解。结果表明:(1)2009~2020年南水北调中线工程受水区灰水足迹降幅达到24.54%,水环境质量得到一定改善;从灰水足迹的构成来看,农业占比最高,其次是生活,工业占比最低,且农业源、工业源污染的有效控制是受水区灰水足迹总量整体下降的主要原因。(2)在中线工程通水后,受水区灰水足迹荷载系数有所降低,但是水资源总量仍然远远不能满足水污染物的稀释需求,水环境压力巨大;各受水城市灰水足迹荷载系数存在显著不同,地区内部尤其是河南省内部的差异是受水区灰水足迹荷载系数不平衡的主要来源。(3)资本深化效应、资源禀赋效应及经济活度效应对灰水足迹荷载系数主要表现为正向驱动效应,而资本产出效应、经济环境效应则表现为负向驱动效应。各受水城市要继续走绿色发展道路,促进南水北调中线工程水资源可持续利用。

Abstract: Controlling water pollution and improving water environment quality is conducive to the high-quality development of the South-to-North Water Diversion Project's Central Route. On the basis of calculating the grey water footprint of 20 water-receiving cities of the Project's Central Route, this paper calculated the grey water footprint load coefficient of each water-receiving city, analyzed the spatial-temporal distribution characteristics. The Logarithmic Mean Divisia Index model was used to decompose the driving factors. The results showed that: (1) From 2009 to 2020, the grey water footprint in water-receiving area decreased by 24.54%, and the water environment quality was improved; From the perspective of the composition of grey water footprint, agriculture accounted for the highest proportion, followed by living, and industry for the lowest. Moreover, the effective control of pollution from agricultural and industrial sources was the main reason for the overall decline of the total grey water footprint. (2) After the water supply of the Central Route, the grey water footprint load coefficient of the water-receiving area decreased to certain extent. However, the total amount of water resources still failed to meet the dilution demand of water pollutants, and hence, the water environment pressure was large. The load coefficient of grey water footprint in water-receiving cities was significantly different. The difference within the regions, especially within Henan Province, was the main source of the unbalance of grey water footprint load coefficient. (3) The capital deepening effect, resource endowment effect and economic activity effect mainly showed positive effects on the grey water footprint load coefficient, while the capital output and economic environment effects showed negative driving effects. All water-receiving cities should continue to take the road of green development and promote the sustainable utilization of water resources in the South-to-North Water Diversion Project's Central Route.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 张鑫, 陈志刚. 经济增长激励、官员异质性与城市工业污染:以长三角地区为例[J]. 长江流域资源与环境, 2018, 27(07): 1314 .
[2] 郭政, 董平, 陆玉麒, 黄群芳, 马颖忆. 长三角集装箱港口体系演化及影响因素分析[J]. 长江流域资源与环境, 2018, 27(07): 1340 .
[3] 蓝希, 刘小琼, 郭炎, 陈昆仑. “长江经济带”战略背景下武汉城市水环境承载力综合评价[J]. 长江流域资源与环境, 2018, 27(07): 1345 .
[4] 罗能生, 王玉泽.彭郁, 李建明. 长江中游城市群生态效率的空间关系及其协同提升机制研究[J]. 长江流域资源与环境, 2018, 27(07): 1349 .
[5] 刘钢, 刘坤琳, 汪玮茜, 赵爽. 水质感知视角下水库移民满意度分析——基于有序逻辑回归的实证研究[J]. 长江流域资源与环境, 2018, 27(07): 1355 .
[6] 戢晓峰, 刘丁硕. 基于3D理论与SEM的县域交通可达性与空间贫困的耦合机制[J]. 长江流域资源与环境, 2018, 27(07): 1360 .
[7] 张大鹏, 曹卫东, 姚兆钊, 岳洋, 任亚文. 上海大都市区物流企业区位分布特征及其演化[J]. 长江流域资源与环境, 2018, 27(07): 1365 .
[8] 佘颖, 刘耀彬. 国内外绿色发展制度演化的历史脉络及启示[J]. 长江流域资源与环境, 2018, 27(07): 1370 .
[9] 姚琳, 沈竞, 温新龙, 高超. WRF模式参数化方案对江西山地风电场的风模拟研究[J]. 长江流域资源与环境, 2018, 27(07): 1380 .
[10] 伍文琪, 罗贤, 黄玮。李运刚. 云南省水资源承载力评价与时空分布特征研究[J]. 长江流域资源与环境, 2018, 27(07): 1385 .