城市蔓延
面板数据
中国
社会经济地位
高效能源利用
三角洲
环境科学
地理
经济地理学
城市规划
计量经济学
数学
土木工程
人口
工程类
人口学
航空航天工程
考古
社会学
电气工程
作者
Shuanjin Wang,Jieyu Wang,Chuanglin Fang,Shijie Li
出处
期刊:Cities
[Elsevier]
日期:2018-08-24
卷期号:85: 117-129
被引量:180
标识
DOI:10.1016/j.cities.2018.08.009
摘要
The improvement of CO2 emission efficiency is of great significance to realizing energy-saving and emission reduction targets and achieving low-carbon development. While it is increasingly recognized that urban form could significantly influence the CO2 emissions of urban areas, few studies have been able to quantify the implications of urban form in relation to CO2 emission efficiency. The purpose of this paper is thus to contribute to existing literature by empirically quantifying how urban form influences CO2 emission efficiency. CO2 emission efficiency in this study is presented in terms of CO2 economic efficiency (CEE) and CO2 social efficiency (CSE). Firstly, we calculated the CEE and CSE of nine cities in the Pearl River Delta (Guangzhou, Shenzhen, Zhuhai, Foshan, Jiangmen, Zhaoqing, Huizhou, Dongguan, and Zhongshan) using locally important socioeconomic variables over the period 1990–2013. Then, seven landscape metrics were selected in order to quantify three dimensions of urban form (extension, irregularity, and compactness) using remote sensing data. Finally, panel data models were utilized to estimate the associations between urban form and CO2 emission efficiency. We identified a negative correlation between urban sprawl and CEE as well as CSE, a finding that indicates that urban growth decreases CO2 economic efficiency. Further, increasing irregularity in the form of cities was found to decrease both CEE and CSE—a larger degree of irregularity, in other words, results in lower CO2 emission efficiency. Conversely, urban compactness was identified as having a significant positive influence on both CEE and CSE, indicating that the compact development of cities can actually help to improve CO2 emission efficiency. The findings of this study hold important implications for building low-carbon cities in China.
科研通智能强力驱动
Strongly Powered by AbleSci AI