Investigating the nexus between energy, socio-economic factors and environmental pollution: A geo-spatial multi regression approach

被引:8
|
作者
Bhatti, Uzair Aslam [1 ,5 ]
Tang, Hao [1 ,5 ]
Khan, Asad [2 ]
Ghadi, Yazeed Yasin [6 ]
Bhatti, Mughair Aslam [3 ,4 ]
Khan, Khalid Ali [7 ,8 ]
机构
[1] Hainan Univ, Sch Sch Informat & Commun Engn, Haikou 570100, Hainan, Peoples R China
[2] Guangzhou Univ, Metaverse Res Inst, Sch Comp Sci & Cyber Engn, Guangzhou 510006, Guangdong, Peoples R China
[3] Nanjing Normal Univ, Sch Geog, Nanjing 210023, Peoples R China
[4] Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing 210023, Peoples R China
[5] Hainan Univ, State Key Lab Marine Resource Utilizat South China, Haikou 570100, Hainan, Peoples R China
[6] Al Ain Univ, Dept Comp Sci, Al Ain, U Arab Emirates
[7] King Khalid Univ, Res Ctr Adv Mat Sci RCAMS, Unit Bee Res & Honey Prod, POB 9004, Abha 61413, Saudi Arabia
[8] King Khalid Univ, Appl Coll, POB 9004, Abha 61413, Saudi Arabia
基金
中国国家自然科学基金;
关键词
Fine Particulate Matter; Yangtze River Basin; Yellow River Basin; Spatial econometric analysis; Socioeconomic factors; GEOGRAPHICALLY WEIGHTED REGRESSION; RIVER ECONOMIC BELT; CO2; EMISSIONS; PM2.5; CONCENTRATIONS; KUZNETS CURVE; CHINA; URBANIZATION; INDUSTRY; GROWTH; PERSPECTIVE;
D O I
10.1016/j.gr.2024.02.007
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The Yellow River Basin (YRB) and Yangtze River Basin (YZRB) stand as pivotal regions in China, holding paramount importance in both economic development and environmental security. However, the rapid pace of climate change and extensive human activities have dramatically reshaped these areas, leading to substantial alterations in natural landscapes and urban ecosystems. To ensure sustainable socioeconomic growth, a profound understanding of the intricate interplay between socioeconomic factors and the emission of fine particulate matter (FPM) is imperative, along with an exploration of the underlying mechanisms governing these relationships. n this comprehensive study, we conducted spatial autocorrelation and spatial panel regression analyses, leveraging panel data encompassing the years from 2002 to 2021, derived from provincial -level administrative units within the YZRB and YRB. By adopting a holistic approach that considers comprehensive features and spatial effects, our research contributes substantively to the existing literature concerning the YZRB and YRB areas. Our analysis unveiled a notable decline in pollutant emissions over the course of the study period, yet it became evident that socioeconomic and energy -related factors continued to exert significant influence on FPM levels. Furthermore, we identified pronounced positive spatial autocorrelations in FPM emissions, suggesting a need for regionally tailored environmental management strategies. Employing various statistical tests, we rigorously examined the spatial autocorrelation patterns among the regions. Results from our random effect regression model and Geographically Weighted Regression (GWR) approach underscored the significant impact of socioeconomic and natural factors on FPM concentrations. Importantly, the magnitudes of these impacts exhibited variations contingent upon the specific river basin type. Within the YZRB, our findings emphasize the relevance of urbanization metrics, such as urban population, urban green space, Gross Domestic Product (GDP), and economic spending, which displayed positive and statistically significant relationships with FPM concentrations. Conversely, in the YRB, the utilization of energy resources and natural assets emerged as pivotal determinants. (c) 2024 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:308 / 325
页数:18
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