Green development efficiency measurement and influencing factors analysis in the Yangtze River economic Belt, China

中游 上游(联网) 长江 中国 绿色发展 托比模型 地理 环境科学 环境工程 经济 计量经济学 计算机网络 计算机科学 考古 石油工业
作者
Shiyi Peng,Yajing Yu
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:162: 112025-112025 被引量:13
标识
DOI:10.1016/j.ecolind.2024.112025
摘要

This study focuses on improving environmental protection and facilitating coordinated economic and social development in the Yangtze River Economic Belt (YREB). Examining the progress of green development in 11 provinces and cities within the YREB. The Super SBM model and the GML index model were utilized to assess the green development efficiency of these regions from 2008 to 2021. Additionally, the spatial distribution, evolutionary trends, and determinants of green development were explored through hot and cold spot analysis, kernel density estimation, the random forest RF method, and the Tobit model.Findings indicate that the overall green development efficiency in these provinces and cities is relatively notable, with the upstream and downstream areas exhibiting higher efficiency compared to the midstream regions. Shanghai and Zhejiang have emerged as frontrunners in green development. Analysis of hot and cold spots revealed that hot spots are predominantly located in the Yangtze River Delta, while sub-cold spots extend upstream, forming concentrated and contiguous cold spot areas in the midstream reaches. Kernel densities show that green development is more efficient overall and in particular in upstream and downstream areas. In contrast, the midstream regions have witnessed a decline in this efficiency. Regarding influencing factors, ecological environmental protection is identified as a direct influence on the efficiency of green development. Furthermore, the degrees of economic advancement, governmental support, and investment in pioneering science and technology exert substantial influence on green development..
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Owen应助MU采纳,获得10
刚刚
科研通AI6.2应助leo采纳,获得10
刚刚
Dicecrea完成签到,获得积分10
刚刚
1秒前
杨小小发布了新的文献求助10
1秒前
充电宝应助咸鱼璋采纳,获得10
1秒前
CodeCraft应助stth采纳,获得30
1秒前
2秒前
2秒前
3秒前
3秒前
3秒前
3秒前
3秒前
3秒前
4秒前
4秒前
4秒前
Hui发布了新的文献求助20
4秒前
wys发布了新的文献求助10
5秒前
三三三应助疯狂的凡柔采纳,获得10
5秒前
简单发布了新的文献求助10
5秒前
xu发布了新的文献求助10
5秒前
6秒前
axiba完成签到,获得积分10
6秒前
不能多说话完成签到,获得积分10
6秒前
6秒前
rzw发布了新的文献求助10
6秒前
7秒前
Amani_Nakupenda完成签到,获得积分10
7秒前
7秒前
阿垚发布了新的文献求助10
7秒前
刘贺发布了新的文献求助10
8秒前
拥你入怀发布了新的文献求助10
8秒前
谦让大娘完成签到,获得积分10
8秒前
朴素砖家完成签到,获得积分10
8秒前
雪域完成签到,获得积分10
8秒前
8秒前
LLL发布了新的文献求助10
9秒前
杨小小完成签到,获得积分10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Cognitive Psychology in a Changing World 800
内視鏡的に摘除しえた十二指腸乳頭部腫瘍の2例 660
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Neuroscience of Language 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7683755
求助须知:如何正确求助?哪些是违规求助? 9247467
关于积分的说明 19947265
捐赠科研通 7256550
什么是DOI,文献DOI怎么找? 3288508
关于科研通互助平台的介绍 2445841
邀请新用户注册赠送积分活动 2292554