Environmental Pollution, Год журнала: 2024, Номер unknown, С. 125424 - 125424
Опубликована: Дек. 1, 2024
Язык: Английский
Environmental Pollution, Год журнала: 2024, Номер unknown, С. 125424 - 125424
Опубликована: Дек. 1, 2024
Язык: Английский
Sustainable Cities and Society, Год журнала: 2023, Номер 96, С. 104663 - 104663
Опубликована: Май 21, 2023
Язык: Английский
Процитировано
61PLoS ONE, Год журнала: 2023, Номер 18(2), С. e0280225 - e0280225
Опубликована: Фев. 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
Язык: Английский
Процитировано
57Atmosphere, Год журнала: 2024, Номер 15(6), С. 671 - 671
Опубликована: Май 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.
Язык: Английский
Процитировано
27Sustainable Cities and Society, Год журнала: 2024, Номер 106, С. 105348 - 105348
Опубликована: Март 13, 2024
Язык: Английский
Процитировано
26Journal of Cleaner Production, Год журнала: 2024, Номер 452, С. 142219 - 142219
Опубликована: Апрель 11, 2024
Язык: Английский
Процитировано
15Sustainable Cities and Society, Год журнала: 2024, Номер 107, С. 105466 - 105466
Опубликована: Апрель 22, 2024
Язык: Английский
Процитировано
12Urban Climate, Год журнала: 2023, Номер 51, С. 101637 - 101637
Опубликована: Авг. 2, 2023
Язык: Английский
Процитировано
20Urban Climate, Год журнала: 2023, Номер 51, С. 101660 - 101660
Опубликована: Авг. 22, 2023
Язык: Английский
Процитировано
18Journal of Environmental Management, Год журнала: 2024, Номер 354, С. 120391 - 120391
Опубликована: Фев. 15, 2024
Язык: Английский
Процитировано
8Ecological Informatics, Год журнала: 2023, Номер 78, С. 102293 - 102293
Опубликована: Сен. 17, 2023
Язык: Английский
Процитировано
15