首页|基于双层嵌套LMDI的长三角减污降碳驱动因素研究

基于双层嵌套LMDI的长三角减污降碳驱动因素研究

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

Logarithmic Mean Divisia Indexpollution & carbon-reductionsynergyYangtze River delta prefectures

范远华、王世进

展开 >

江苏师范大学商学院,江苏 徐州 221116

对数迪氏指数法 减污降碳 协同治理 长三角地级市

2024

资源与产业
中国地质大学(北京) 中国地质调查局 国土资源部人力资源开发中心

资源与产业

CSTPCDCHSSCD
影响因子:1.097
ISSN:1673-2464
年,卷(期):2024.26(5)