Decreasing water footprint of energy sectors for Beijing-Tianjin-Hebei urban urban agglomeration
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更新:2024-04-09 16:44:11 浏览:880次
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摘要
Previous studies have extensively investigated the spatial-temporal changes in water usage within energy sectors and the factors driving these changes. Nevertheless, certain knowledge gaps persist. Firstly, there has been no implementation of an assessment concerning the water use of energy sectors at the city level, incorporating both quantity and quality considerations. Secondly, the factors influencing changes in quality-induced water scarcity resulting from energy consumption have not been explored to date. To address these gaps, this study combined a nested city-level MRIO with SDA to evaluate the changes in water use of the energy sector for the Beijing-Tianjin-Hebei (BTH) urban agglomeration and driving forces behind these changes from both quantity and quality perspectives through the blue and grey water footprint calculation.
This evaluation plays a crucial role in advancing sustainable development within the broader framework of water-energy integrated resource management for the BTH urban agglomeration with serious both quantity and quality-induced water scarcity. Moreover, the Coordinated Development of the BTH region stands out as a crucial strategy for China. With a population of 100 million people and a GDP representing 8.42% of the national total in 2020, the BTH region plays a vital role in the economic landscape of North China. The BTH region is composed of 13 cities, encompassing 2 municipalities (Beijing and Tianjin) and 11 prefecture-level cities within Hebei Province. The interlinkage among cities in the BTH region, as well as the interplay between the BTH region and other Chinese regions, along with their effects on water use of the energy sectors, as examined through the nested MRIO approach in this study, play a pivotal role in realizing the targets of regional coordinated development.
关键词
water footprint; water-energy nexus; multi-regional input output model; structural decomposition analysis
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