Spatiotemporal Characteristics of Carbon Emissions from Construction Land and Their Decoupling Effects in the Yellow River Basin, China

Land, Год журнала: 2025, Номер 14(2), С. 320 - 320

Опубликована: Фев. 5, 2025

Carbon emissions (CE) from expanding construction land (CL), a vital territory for human production and habitation, have contributed to climate change worldwide. The Yellow River Basin (YRB), an essential economic region energy supply base in China, is experiencing rapid urbanization, the contradiction between development ecological protection increasingly acute. Consequently, thorough examination of spatial temporal features carbon (CECL) its decoupling growth (EG) crucial maintaining region. This study adopts IPCC emission coefficient approach measuring CECL YRB 2010 2021. variation were revealed using ArcGIS software standard deviation ellipse (SDE) model. effect EG was analyzed Tapio model innovatively combined with Logarithmic Mean Divisia Index (LMDI) method explore influence five main drivers on effect. found that: (1) rose 2.463 billion tons 3.329 layout “high east low west”. (2) SDE distributed direction “northeast southwest”, gravity center’s moving path “northwest northeast northwest”; (3) weak (WD) state EG; (4) output (CL) scale are two factors inhibiting CECL, while intensity effect, population density structure elements motivating CECL. provides specific references bases China other countries regions similar levels promoting green ecologically friendly initiatives achieving low-carbon utilization regional sustainable development.

Язык: Английский

Coupling Coordination Evaluation and Optimization of Water–Energy–Food System in the Yellow River Basin for Sustainable Development

Systems, Год журнала: 2025, Номер 13(4), С. 278 - 278

Опубликована: Апрель 10, 2025

Understanding the coupling mechanisms and coordinated development dynamics of water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on Yellow River Basin, conducting a comprehensive analysis system’s influencing factors. A structured evaluation framework established, integrating entropy weight–TOPSIS method, coordination degree model, spatial correlation analysis. Empirical conducted using data from nine provinces (regions) along 2003 to 2022 assess spatiotemporal evolution level. The Tobit regression model employed quantify impact various factors degree. Results indicate that index WEF in Basin exhibits an overall upward trend, with remaining at high level extended period, up 0.231 0.375. interdependence among three major systems strong (0.881–0.939), while has increased over time despite fluctuations, qualitative leap not yet been achieved. follows distribution pattern midstream > downstream upstream, characterized by predominantly However, frequently remains forced or below, general trend upstream. From 2008, positive autocorrelation was observed across provinces, indicating agglomeration effect. By 2022, most were clustered “high-high” “low-low” areas, reflecting minimal regional differences. Key positively include economic levels, industrial structure upgrading, urbanization, transportation networks, technological innovation negatively affects coordination. Based these findings, it recommended strengthen balanced development, optimize layout structures, improve inter-regional resource circulation mechanism, promote deep integration production practices address bottlenecks hindering system. Policy recommendations are proposed provide strategic references socioeconomic thereby achieving high-quality growth region.

Язык: Английский

Spatiotemporal Dynamic Evolution of PM2.5 Exposure from Land Use Changes: A Case Study of Gansu Province, China

Land, Год журнала: 2025, Номер 14(4), С. 795 - 795

Опубликована: Апрель 7, 2025

Air pollution is a major trigger for chronic respiratory and circulatory diseases. As key component of air pollution, fine particulate matter (PM2.5) exposure largely determined by land use type population density. However, simultaneous consideration their spatiotemporal distribution lacking in existing studies on PM2.5 exposure. In this paper, we first assess the dynamic evolution patterns Gansu Province, China, from 2000 to 2020, using transfer matrix degree. Population-weighted (PWE) then evaluated each at provincial, city, county levels, with seasonal variations analyzed. Spatial autocorrelation analysis finally performed explore exposure, whereas standard deviation ellipses gravity center migration models highlight spatial characteristics shifting trends. Experimental results showed that 2010 was turning point annual provincial level an initial increase followed decrease. Construction had highest forest lowest (except 2005). Exposure levels pattern: higher winter spring lower summer autumn. At city southern indicated continuous decline across all types since 2000. exhibited strong positive correlation, fluctuating convergence. This study comprehensively analyzes multi-scale differences various types, contributing provide scientific evidence decision-making support mitigating enhancing coordinated control administrative levels.

Язык: Английский