DRIVERS FOR REDUCING POLLUTION & CARBON IN YANGTZE RIVER DELTA BASED ON DUAL-NESTED LMDI

doi:10.13776/j.cnki.resourcesindustries.20240830.001

Resources & Industries ›› 2024, Vol. 26 ›› Issue (5): 37-46.DOI: 10.13776/j.cnki.resourcesindustries.20240830.001

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DRIVERS FOR REDUCING POLLUTION & CARBON IN YANGTZE RIVER DELTA BASED ON DUAL-NESTED LMDI

FAN Yuanhua, WANG Shijin

（School of Business, Jiangsu Normal University, Xuzhou 221116, China）

Received:2024-05-14 Revised:2024-06-17 Online:2024-10-20 Published:2024-10-20

基于双层嵌套LMDI的长三角减污降碳驱动因素研究

范远华，王世进

（江苏师范大学商学院，江苏徐州 221116）

通讯作者: 王世进，博士、教授，主要从事环境经济与管理研究。E-mail：wangshijin2008@126.com
作者简介:范远华，硕士生，主要从事环境经济与管理研究。E-mail：fanyuanhua2023@hotmail.com
基金资助:
国家社科基金重点项目(23AGL029)；2022年江苏高校“青蓝工程”资助项目（苏教师函[2022]29号）；2023年徐州市政策引导类计划（软科学研究）项目（KC23097)；江苏师范大学2024年研究生科研创新计划项目（2024XKT1401）。

Abstract

Abstract: Synergy of pollution & carbon reduction is a key path to China's green low carbon quality development. It is still unclear that how their synergy and harness between air pollutants represented by SO₂ & CO₂ and green house gas reduction drivers is. This paper, based on 34 prefectures' 2006 to 2020 data in Yangtze River delta, uses LMDI model to decompose SO₂ & CO₂ emission drivers with the results nested with pollution & carbon-reduction synergy model, and measures their contribution and synergy of pollution & carbon-reduction drivers in energy, economy and environment. Effects of energy structural intensity, economic development and population size play a synergy on SO₂ & CO₂ reduction in Yangtze River delta, of which only energy structural intensity is positive, other drivers are negative or of no synergy. To advance China's green low carbon quality growth, this paper presents suggestion on fulfilling drivers of synergy in pollution & carbon-reduction along with the potentials of non-synergy factors.

Key words: Logarithmic Mean Divisia Index, pollution &, carbon-reduction, synergy, Yangtze River delta prefectures

摘要： 减污降碳协同增效是推动我国绿色低碳高质量发展的重要措施。以SO₂和CO₂为代表的空气污染物和温室气体协同减排的驱动因素之间的协同程度及其管控对策尚不明晰。本研究基于2006—2020年长三角地区34个地级市统计数据，运用LMDI模型对SO₂和CO₂排放的驱动因素分解，再与减污降碳协同评价模型进行嵌套，对能源、经济、环境等驱动因素的减污降碳贡献度和协同效应进行核算。研究结果显示：能源结构强度效应、经济发展效应和人口规模效应对长三角地区的SO₂和CO₂具有协同减排作用，其中仅能源结构强度效应表现为减污降碳正向协同，其他驱动因素对SO₂和CO₂的减污降碳作用呈负向协同或不协同。因此，为推动我国长三角地区绿色低碳高质量发展，在发挥协同型因素的减污降碳作用的同时也要兼顾挖掘非协同型因素的减排潜力。

关键词: 对数迪氏指数法, 减污降碳, 协同治理, 长三角地级市

CLC Number:

F205

FAN Yuanhua, WANG Shijin. DRIVERS FOR REDUCING POLLUTION & CARBON IN YANGTZE RIVER DELTA BASED ON DUAL-NESTED LMDI[J]. Resources & Industries, 2024, 26(5): 37-46.

范远华, 王世进. 基于双层嵌套LMDI的长三角减污降碳驱动因素研究[J]. 资源与产业, 2024, 26(5): 37-46.

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DRIVERS FOR REDUCING POLLUTION & CARBON IN YANGTZE RIVER DELTA BASED ON DUAL-NESTED LMDI

基于双层嵌套LMDI的长三角减污降碳驱动因素研究

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