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基于脱钩分析探讨用水与城市化的区域协调关系——以京津冀地区为例。

Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing-Tianjin-Hebei Region.

机构信息

College of Geography and Environment, Shandong Normal University, Jinan 250014, China.

出版信息

Int J Environ Res Public Health. 2022 Jun 1;19(11):6793. doi: 10.3390/ijerph19116793.

DOI:10.3390/ijerph19116793
PMID:35682376
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9180552/
Abstract

Understanding the potential association between the urbanization process and regional water shortage/pollution is conducive to promoting the intensive utilization of local water resources. In this study, the water footprint model was used to estimate water utilization status in terms of both water quantity (virtual water footprint (VWF)) and water quality (grey water footprint (GWF)) in the Beijing-Tianjin-Hebei region (China) during 2004-2017. Their potential coordination relationship with the local urbanization process represented by the gross domestic product (GDP), population (POP), and built-up area (BA) was examined using the Tapio decoupling model. The results showed that from 2004 to 2017, (1) VWF in Beijing and Tianjin showed non-significant decreasing trends, with reductions of 1.08 × 10 and 1.56 × 10 m, respectively, while that in Hebei showed a significant increasing trend, with an increase of 5.74 × 10 m. This indicated a gradually increasing water demand in Hebei and decreasing demand in Beijing and Tianjin. In all three regions, the agricultural sector accounted for a relatively high proportion of VWF compared to other sectors. (2) GWF in Beijing, Tianjin, and Hebei all showed declining trends, with reductions of 2.19 × 10, 2.32 × 10, and 1.66 × 10 m, respectively, indicating considerable local water quality improvement. The domestic sector contributed as the main component of GWF in Beijing, while agriculture was the main contributor in Hebei. The major contributor in Tianjin transitioned from the domestic (before 2015) to the agricultural sector. (3) We found good coordination between VWF and GDP in all three regions, as their local economic development was no longer overly dependent on water consumption. However, the expansion of urban built-up area or population would bring about accelerated depletion of water resources. (4) GWF in the three provinces showed good coordination with GDP, POP, and BA in most years, implying that the development of urbanization no longer strongly caused the pollution of water resources. In sum, policymakers should focus on improving agricultural irrigation efficiency and residents' awareness of water conservation, so as to gradually achieve sustainable water resource management in the BTH region.

摘要

理解城市化进程与区域水资源短缺/污染之间的潜在关联,有利于促进当地水资源的集约化利用。本研究采用水足迹模型,估算了 2004-2017 年京津冀地区的水量(虚拟水足迹(VWF))和水质(灰水足迹(GWF))用水状况。利用Tapio 脱钩模型,考察了以国内生产总值(GDP)、人口(POP)和建成区面积(BA)表示的当地城市化进程与它们的潜在协调关系。结果表明,从 2004 年到 2017 年:(1)北京和天津的 VWF 呈非显著减少趋势,分别减少了 1.08×10 和 1.56×10m,而河北则呈显著增加趋势,增加了 5.74×10m。这表明河北的水需求逐渐增加,而北京和天津的需求减少。在这三个地区,农业部门的 VWF 占比较高。(2)北京、天津和河北的 GWF 均呈下降趋势,分别减少了 2.19×10、2.32×10 和 1.66×10m,表明当地水质有较大改善。国内部门是北京 GWF 的主要组成部分,而农业是河北的主要贡献者。天津的主要贡献者从国内(2015 年之前)向农业部门转变。(3)我们发现,在这三个地区,VWF 与 GDP 之间存在良好的协调关系,因为当地经济发展不再过度依赖于水资源消耗。然而,城市建成区或人口的扩张会加速水资源的消耗。(4)在大多数年份,京津冀地区的 GWF 与 GDP、POP 和 BA 之间表现出良好的协调,这意味着城市化的发展不再强烈导致水资源的污染。总之,政策制定者应注重提高农业灌溉效率和居民的节水意识,以逐步实现京津冀地区水资源的可持续管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/de61f8a1f121/ijerph-19-06793-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/ab45f3163a04/ijerph-19-06793-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/e876fcb2dafb/ijerph-19-06793-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/06ca7b52361d/ijerph-19-06793-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/98a576de00c0/ijerph-19-06793-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/66581b53a976/ijerph-19-06793-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/82f25040d623/ijerph-19-06793-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/8ebed99554bc/ijerph-19-06793-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/2dcafce2ba64/ijerph-19-06793-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/de61f8a1f121/ijerph-19-06793-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/ab45f3163a04/ijerph-19-06793-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/e876fcb2dafb/ijerph-19-06793-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/06ca7b52361d/ijerph-19-06793-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/98a576de00c0/ijerph-19-06793-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/66581b53a976/ijerph-19-06793-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/82f25040d623/ijerph-19-06793-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/8ebed99554bc/ijerph-19-06793-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/2dcafce2ba64/ijerph-19-06793-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a516/9180552/de61f8a1f121/ijerph-19-06793-g009.jpg

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