Environmental Pollution, Journal Year: 2024, Volume and Issue: unknown, P. 125424 - 125424
Published: Dec. 1, 2024
Language: Английский
Environmental Pollution, Journal Year: 2024, Volume and Issue: unknown, P. 125424 - 125424
Published: Dec. 1, 2024
Language: Английский
Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 96, P. 104663 - 104663
Published: May 21, 2023
Language: Английский
Citations
61PLoS ONE, Journal Year: 2023, Volume and Issue: 18(2), P. e0280225 - e0280225
Published: Feb. 28, 2023
The growth of the digital economy has created new forms inequality opportunity. This paper studies whether development expands income gap between urban and rural areas from theoretical empirical. research based on panel data 202 cities 2011 to 2019 in China shows that: (1) Although can promote improvement both absolute levels, it a greater positive impact residents' levels than residents', resulting widening urban-rural gap. (2) analysis action mechanism reveals that employment information service industry depth finance use are two crucial mechanisms for widen areas. (3) spatial Durbin model(SDM) error model(SEM) three weight matrices show is also characterized by spillover, will have negative neighboring regions as well. (4) main conclusions still hold after robustness quasi-natural experiments strategy "Broadband China" selection historical instrumental variables. helpful understand effects, characteristics
Language: Английский
Citations
57Atmosphere, Journal Year: 2024, Volume and Issue: 15(6), P. 671 - 671
Published: May 31, 2024
With the ongoing advancement of globalization significantly impacting ecological environment, continuous rise in Land Surface Temperature (LST) is increasingly jeopardizing human production and living conditions. This study aims to investigate seasonal variations LST its driving factors using mathematical models. Taking Wuhan Urban Agglomeration (WHUA) as a case study, it explores characteristics employs Principal Component Analysis (PCA) categorize factors. Additionally, compares traditional models with machine-learning select optimal model for this investigation. The main conclusions are follows. (1) WHUA’s exhibits significant differences among seasons demonstrates distinct spatial-clustering different seasons. (2) Compared geographic spatial models, Extreme Gradient Boosting (XGBoost) shows better explanatory power investigating effects LST. (3) Human Activity (HA) dominates influence throughout year positive correlation LST; Physical Geography (PG) negative Climate Weather (CW) show similar variation PG, peaking transition; Landscape Pattern (LP) weak LST, winter while being relatively inconspicuous summer transition. Finally, through comparative analysis multiple constructs framework exploring features aiming provide references guidance development WHUA regions.
Language: Английский
Citations
27Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 106, P. 105348 - 105348
Published: March 13, 2024
Language: Английский
Citations
26Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 452, P. 142219 - 142219
Published: April 11, 2024
Language: Английский
Citations
15Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 107, P. 105466 - 105466
Published: April 22, 2024
Language: Английский
Citations
12Urban Climate, Journal Year: 2023, Volume and Issue: 51, P. 101637 - 101637
Published: Aug. 2, 2023
Language: Английский
Citations
20Urban Climate, Journal Year: 2023, Volume and Issue: 51, P. 101660 - 101660
Published: Aug. 22, 2023
Language: Английский
Citations
18Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 354, P. 120391 - 120391
Published: Feb. 15, 2024
Language: Английский
Citations
8Ecological Informatics, Journal Year: 2023, Volume and Issue: 78, P. 102293 - 102293
Published: Sept. 17, 2023
Language: Английский
Citations
15