供需视角下广东虚拟水-能-碳演变、耦合与驱动

    Evolution, coupling, and driving of virtual water-energy-carbon in Guangdong Province from a supply-demand perspective

    • 摘要: 水-能-碳协同管理是区域可持续发展的重要挑战,亟须系统性的分析框架来揭示其复杂的演变、耦合与驱动机制。以中国经济高速增长与转型的典型缩影——广东省为例,构建了一个融合供给侧与需求侧双重视角的分析框架。研究基于1997~2017年广东省投入产出表与资源环境数据,综合运用环境投入产出分析、斯皮尔曼秩相关分析与对数平均迪氏指数(LMDI)分解,系统探究了广东省长时序虚拟水-能-碳的演变规律、耦合关系、总体与多阶段驱动效应。研究发现:①虚拟水消耗与经济增长实现绝对脱钩,而虚拟能消耗与虚拟碳排放仍处于相对脱钩状态;②需求结构向省际调出主导转型,并显著加剧了虚拟能-碳压力;③虚拟能-碳呈现高度协同性,而虚拟水分别与虚拟能、虚拟碳关联较弱且具有产业与需求异质性;④驱动分解显示,产业效率提升是减缓虚拟水-能-碳总量增长的关键,而经济规模扩张是主要驱动力量,后期产业结构优化产生节能减排效益,但需求结构转型部分抵消了该效益。研究所构建的系统性分析框架与发现,不仅可为广东省的资源环境协同管理提供参考,亦可为长三角、京津冀等面临类似挑战的工业化与转型区域提供借鉴。

       

      Abstract: The synergistic management of water, energy, and carbon (W-E-C) is a critical challenge for regional sustainable development, necessitating a systematic analytical framework to reveal their complex evolution, coupling, and driving mechanisms. Taking Guangdong Province-a typical epitome of China′s rapid economic growth and transformation-as a case study, this research constructed an analytical framework integrating both supply-side and demand-side perspectives. Based on Guangdong′s input-output tables and resource-environmental data from 1997 to 2017, this study comprehensively employed environmental input-output analysis, Spearman′s rank correlation analysis, and Logarithmic Mean Divisia Index (LMDI) decomposition to systematically investigate the long-term evolution, coupling relationships, and overall and multi-stage driving effects of the virtual W-E-C nexus. The findings reveal that: ① Virtual water consumption achieved absolute decoupling from economic growth, while virtual energy consumption and virtual carbon emissions remained in relative decoupling. ② The demand structure shifted towards interprovincial transfers as the dominant component, significantly exacerbating virtual energy and carbon pressures. ③ Virtual energy and carbon exhibited high synergy, whereas virtual water showed weaker linkages with both virtual energy and virtual carbon, demonstrating significant sectoral and demand heterogeneity. ④ Decomposition analysis revealed that improvements in industrial efficiency were the key factor slowing the growth of the total virtual W-E-C, while economic scale expansion was the primary driver. In the later stages, industrial structure optimization yielded energy-saving and emission-reduction benefits, which were partially offset by demand structure transformation. The systematic analytical framework and findings not only provide references for the collaborative management of resources and environment in Guangdong, but also offer insights for other industrialized and transitioning regions facing similar challenges, such as the Yangtze River Delta and the Beijing-Tianjin-Hebei region.

       

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