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中国水-能源-粮食(W-E-F)压力的特征、区域差异及影响因素:基于达古姆基尼系数分解和PGTWR模型的证据

Characteristics, regional differences, and influencing factors of China's water-energy-food (W-E-F) pressure: evidence from Dagum Gini coefficient decomposition and PGTWR model.

作者信息

Xiao Wei, He Miao

机构信息

School of Economics, Hebei University, Baoding, 071002, China.

Research Centre of Resources Utilization and Environmental Conservation, Hebei University, Baoding, 071002, China.

出版信息

Environ Sci Pollut Res Int. 2023 May;30(24):66062-66079. doi: 10.1007/s11356-023-27010-4. Epub 2023 Apr 25.

Abstract

Water, energy, and food security are global concerning issues especially in China. To promote regional environmental management cooperation as well as find resource security influencing factor differences among regions, this paper calculates the water-energy-food (W-E-F) pressure, find W-E-F pressure's regional differences, and the influencing factors by Dagum Gini coefficient decomposition and geographically and temporally weighted regression model for panel data (PGTWR). First, the temporal trend of W-E-F pressure is decreasing and then increasing during 2003-2019; pressure in the eastern provinces is significantly higher than in other provinces and structurally energy pressure is the dominant resource pressure in W-E-F in most provinces. Besides, inter-regional differences are the main source of regional differences in China's W-E-F pressure, particularly for the inter-regional differences between eastern regions and other regions. In addition, there are obvious spatio-temporal heterogeneity effects of population density, per capita GDP, urbanization, energy intensity, effective irrigated area, and forest cover on W-E-F pressure. Balancing regional development gaps and developing differentiated resource pressure mitigation strategies based on the characteristics of different regional drivers are of great importance.

摘要

水、能源和粮食安全是全球性的重要问题,在中国尤为如此。为促进区域环境管理合作,并找出各地区资源安全影响因素的差异,本文通过达古姆基尼系数分解以及面板数据地理加权回归模型(PGTWR)计算水-能源-粮食(W-E-F)压力,找出W-E-F压力的区域差异及其影响因素。首先,2003-2019年期间W-E-F压力的时间趋势是先下降后上升;东部省份的压力明显高于其他省份,且在结构上能源压力是大多数省份W-E-F中主要的资源压力。此外,区域间差异是中国W-E-F压力区域差异的主要来源,特别是东部地区与其他地区之间的区域间差异。此外,人口密度、人均GDP、城市化、能源强度、有效灌溉面积和森林覆盖率对W-E-F压力存在明显的时空异质性影响。平衡区域发展差距,并根据不同区域驱动因素的特点制定差异化的资源压力缓解策略至关重要。

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