Synergistic relationship and interact driving factors of pollution and carbon reduction in the Yangtze River Delta urban agglomeration, China

被引:0
作者
Min An
Meng Fan
Ping Xie
机构
[1] China Three Gorges University,Key Laboratory of Geological Hazards on Three Gorges Reservoir Area
[2] Ministry of Education,College of Economics & Management
[3] China Three Gorges University,undefined
来源
Environmental Science and Pollution Research | 2023年 / 30卷
关键词
Carbon emissions; PM2.5; Coordinated governance; Multi-factor interaction;
D O I
暂无
中图分类号
学科分类号
摘要
The urban agglomeration is the most concentrated region of economy, population, and industry. It is also the key area of carbon emissions (CE) and air pollution management. CE and air pollution have the possibility of collaborative governance due to the same root and the same source of them. To achieve the goal of sustainable development, it is important to study the coordinated relationship of CE and atmosphere pollutants in urban agglomerations. However, most researches have ignored the synergistic relationship between CE and air pollutants. Furthermore, there is limited current study on the driving factors of the synergistic relationship between air pollutants and CE. To fill these research gaps, we first explore the spatial-temporal evolvement law of CE and PM2.5 utilizing satellite remote sensing data sets. Secondly, we analyze the synergistic relationship of CE and PM2.5 in the Yangtze River Delta (YRD) urban agglomeration using the coupling coordination degree (CCD) model from 2000 to 2020. At last, we further study the influencing factors of the synergistic relationship of CE and PM2.5 based on the geo-detector model. The findings display that (1) in 2020, the total CE in the YRD urban agglomeration is 2.24 billion tons, accounting for 22.5% of China, but its growth rate has gradually dropped to 7.25%. Besides, the PM2.5 concentration shows a waving upward-downward tendency. In 2020, the range of higher PM2.5 regions significantly decreased, and air quality gradually improved. (2) The CCD of PM2.5 and CE is at the coordination level in general (CCD > 0.6) between 2000 and 2020, which can realize the coordinated governance of pollution and carbon reduction. (3) Digital elevation model (DEM), topographic relief (RDLS), and population density have a higher degree of influence on the synergistic relationship between CE and PM2.5. Besides, the interaction of topographic and socio-economic factors is the main driving factor between the two. This paper can provide a referral for decision-makers to synergistically make plans for pollution and carbon reduction and facilitate the sustainable development of urban agglomerations.
引用
收藏
页码:118677 / 118692
页数:15
相关论文
共 226 条
[1]  
An M(2022)Spatiotemporal change of ecologic environment quality and human interaction factors in three gorges ecologic economic corridor, based on RSEI Ecol Indic 141 109090-771
[2]  
Xie P(2020)Using a distributed air sensor network to investigate the spatiotemporal patterns of PM2.5 concentrations Environ Pollut 264 114549-983
[3]  
He W(2020)Mapping the essential urban land use in Changchun by applying random forest and multi-source geospatial data Remote Sens 12 2488-1503
[4]  
Wang B(2020)Influence of meteorological conditions on PM2.5 concentrations across China: a review of methodology and mechanism Environ Int 139 105558-1099
[5]  
Huang J(2019)Examining the synergistic effect of CO2 emissions on PM2.5 emissions reduction: evidence from China J Clean Prod 223 759-418
[6]  
Khanal R(2019)How does urbanization influence PM2.5 concentrations? Perspective of spillover effect of multi-dimensional urbanization impact J Clean Prod 220 974-170
[7]  
Cao R(2021)Influencing factors of PM2.5 and O3 from 2016 to 2020 based on DLNM and WRF-CMAQ Environ Pollut 285 117512-17200
[8]  
Li B(2018)Tackling air pollution, climate change, and NCDs: time to pull together Lancet 392 1502-81
[9]  
Wang Z(2018)Atmospheric dynamics and ozone cycle during sea breeze in a Mediterranean complex urbanized coastal site J Appl Meteorol Climatol 57 1083-151
[10]  
Peng Z-R(2021)Carbon emission efficiency of China’s industry sectors: from the perspective of embodied carbon emissions J Clean Prod 283 124655-531