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Keywords = BTH (Beijing–Tianjin–Hebei)

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29 pages, 8743 KiB  
Article
Coupled Simulation of the Water–Food–Energy–Ecology System Under Extreme Drought Events: A Case Study of Beijing–Tianjin–Hebei, China
by Huanyu Chang, Naren Fang, Yongqiang Cao, Jiaqi Yao and Zhen Hong
Water 2025, 17(14), 2103; https://doi.org/10.3390/w17142103 - 15 Jul 2025
Viewed by 413
Abstract
The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated [...] Read more.
The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated development scenarios and extreme climate stress. A 500-year precipitation series was reconstructed using historical drought and flood records combined with wavelet analysis and machine learning models (Random Forest and Support Vector Regression). Results show that during the reconstructed historical megadrought (1633–1647), with average precipitation anomalies reaching −20% to −27%, leading to a regional water shortage rate of 16.9%, food self-sufficiency as low as 44.7%, and a critical reduction in ecological river discharge. Under future recommended scenario with enhanced water conservation, reclaimed water reuse, and expanded inter-basin transfers, the region could maintain a water shortage rate of 2.6%, achieve 69.3% food self-sufficiency, and support ecological water demand. However, long-term water resource degradation could still reduce food self-sufficiency to 62.9% and ecological outflows by 20%. The findings provide insights into adaptive water management, highlight the vulnerability of highly coupled systems to prolonged droughts, and support regional policy decisions on resilience-oriented water infrastructure planning. Full article
(This article belongs to the Special Issue Advanced Perspectives on the Water–Energy–Food Nexus)
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18 pages, 3695 KiB  
Article
Incorporating Electricity Consumption into Social Network Analysis to Evaluate the Coordinated Development Policy in the Beijing–Tianjin–Hebei Region
by Di Gao, Hao Yue, Haowen Guan, Bingqing Wu, Yuming Huang and Jian Zhang
Energies 2025, 18(14), 3691; https://doi.org/10.3390/en18143691 - 12 Jul 2025
Viewed by 279
Abstract
This study examines the impact of the Beijing–Tianjin–Hebei (BTH) coordinated development policy on the regional industrial network structure, with a focus on the significance of electricity consumption data in social network analysis (SNA). Utilizing a gravity model integrated with electricity consumption data, this [...] Read more.
This study examines the impact of the Beijing–Tianjin–Hebei (BTH) coordinated development policy on the regional industrial network structure, with a focus on the significance of electricity consumption data in social network analysis (SNA). Utilizing a gravity model integrated with electricity consumption data, this research employs centrality analysis and Lambda analysis to compare changes in the steel industry network before and after policy implementation. The findings reveal that traditional models relying solely on indicators such as population and Gross Domestic Product (GDP) fail to comprehensively capture regional economic linkages, whereas incorporating electricity consumption data enhances the model’s accuracy in identifying core nodes and latent connections. Post policy implementation, the centrality of Beijing and Tianjin increased significantly, reflecting their transition from production hubs to centers for research and development (R&D) and management, while Shijiazhuang’s pivotal role diminished. This study also uncovers a “core–periphery” structure in the BTH urban network, where core cities (Beijing, Tianjin, and Shijiazhuang) dominate resource allocation and information flow, while peripheral cities exhibit uneven development. These results provide a scientific basis for optimizing regional coordinated development policies and underscore the critical role of electricity consumption data in refining regional economic analysis. Incorporating electricity consumption data into the gravity model significantly enhances its explanatory power by capturing hidden economic ties and improving policy evaluation, offering a more accurate and dynamic assessment of regional industrial linkages. Full article
(This article belongs to the Special Issue Energy Markets and Energy Economy)
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19 pages, 7589 KiB  
Article
Analysis of PM2.5 Transport Characteristics and Continuous Improvement in High-Emission-Load Areas of the Beijing–Tianjin–Hebei Region in Winter
by Yuyao Qiang, Chuanda Wang, Xiaoqi Wang and Shuiyuan Cheng
Sustainability 2025, 17(14), 6389; https://doi.org/10.3390/su17146389 - 11 Jul 2025
Viewed by 328
Abstract
The air quality in the Beijing–Tianjin–Hebei region of China has markedly improved in recent decades. Characterizing current PM2.5 transmission between cities in light of the continuous reduction in emissions from various sources is of great significance for the formulation of future regional [...] Read more.
The air quality in the Beijing–Tianjin–Hebei region of China has markedly improved in recent decades. Characterizing current PM2.5 transmission between cities in light of the continuous reduction in emissions from various sources is of great significance for the formulation of future regional joint prevention and control strategies. To address these issues, a WRF-CAMx modeling project was implemented to explore the pollution characteristics from the perspectives of transport flux, regional source apportionment, and the comprehensive impact of multiple pollutants from 2013 to 2020. It was found that the net PM2.5 transport flux among cities declined considerably during the study period and was positively affected by the continuous reduction in emission sources. The variations in local emissions and transport contributions in various cities from 2013 to 2020 revealed differences in emission control policies and efforts. It is worth noting that under polluted weather conditions, obvious interannual differences in PM2.5 transport fluxes in the BTH region were observed, emphasizing the need for more scientifically based regional collaborative control strategies. The change in the predominant precursor from SO2 to NOx has posed new challenges for emission reduction. NOx emission reductions will significantly decrease PM2.5 concentrations, while SO2 and NH3 reductions show limited effects. The reduction in NOx emissions might have a fluctuating impact on the generation of SOAs, possibly due to changes in atmospheric oxidation. However, the deep treatment of NOx has a positive effect on the synergistic improvement of multiple air pollutants. This emphasizes the need to enhance the reduction in NOx emissions in the future. The results of this study can serve as a reference for the development of effective PM2.5 precursor control strategies and regional differentiation optimization improvement policies in the BTH region. Full article
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22 pages, 4465 KiB  
Article
Urban Expansion Scenario Prediction Model: Combining Multi-Source Big Data, a Graph Attention Network, a Vector Cellular Automata, and an Agent-Based Model
by Yunqi Gao, Dongya Liu, Xinqi Zheng, Xiaoli Wang and Gang Ai
Remote Sens. 2025, 17(13), 2272; https://doi.org/10.3390/rs17132272 - 2 Jul 2025
Cited by 1 | Viewed by 362
Abstract
The construction of transition rules is the core and difficulty faced by the cellular automata (CA) model. Dynamic mining of transition rules can more accurately simulate urban land use change. By introducing a graph attention network (GAT) to mine CA model transition rules, [...] Read more.
The construction of transition rules is the core and difficulty faced by the cellular automata (CA) model. Dynamic mining of transition rules can more accurately simulate urban land use change. By introducing a graph attention network (GAT) to mine CA model transition rules, the temporal and spatial dynamics of the model are increased based on the construction of a real-time dynamic graph structure. At the same time, by adding an agent-based model (ABM) to the CA model, the simulation evolution of different human decision-making behaviors can be achieved. Based on this, an urban expansion scenario prediction (UESP) model has been proposed: (1) the UESP model employs a multi-head attention mechanism to dynamically capture high-order spatial dependencies, supporting the efficient processing of large-scale datasets with over 50,000 points of interest (POIs); (2) it incorporates the behaviors of agents such as residents, governments, and transportation systems to more realistically reflect human micro-level decision-making; and (3) by integrating macro-structural learning with micro-behavioral modeling, it effectively addresses the existing limitations in representing high-order spatial relationships and human decision-making processes in urban expansion simulations. Based on the policy context of the Outline of the Beijing–Tianjin–Hebei (BTH) Coordinated Development Plan, four development scenarios were designed to simulate construction land change by 2030. The results show that (1) the UESP model achieved an overall accuracy of 0.925, a Kappa coefficient of 0.878, and a FoM index of 0.048, outperforming traditional models, with the FoM being 3.5% higher; (2) through multi-scenario simulation prediction, it is found that under the scenario of ecological conservation and farmland protection, forest and grassland increase by 3142 km2, and cultivated land increases by 896 km2, with construction land showing a concentrated growth trend; and (3) the expansion of construction land will mainly occur at the expense of farmland, concentrated around Beijing, Tianjin, Tangshan, Shijiazhuang, and southern core cities in Hebei, forming a “core-driven, axis-extended, and cluster-expanded” spatial pattern. Full article
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18 pages, 6408 KiB  
Article
Contrasting Impacts of Urbanization and Cropland Irrigation on Observed Surface Air Temperature in Northern China
by Xiaoyu Xu, Shiguang Miao, Yizhou Zhang and Jingjing Dou
Remote Sens. 2025, 17(13), 2256; https://doi.org/10.3390/rs17132256 - 30 Jun 2025
Viewed by 227
Abstract
Urbanization and cropland irrigation modify land surface water and energy budgets in different ways; however, few observational studies have explicitly quantified their contrasts. Using high-resolution observations from over 2000 surface weather stations and urban and irrigation fraction data, this study investigated the individual [...] Read more.
Urbanization and cropland irrigation modify land surface water and energy budgets in different ways; however, few observational studies have explicitly quantified their contrasts. Using high-resolution observations from over 2000 surface weather stations and urban and irrigation fraction data, this study investigated the individual and combined effects of urbanization and cropland irrigation on surface air temperature over the Beijing–Tianjin–Hebei (BTH) region in China, where highly urbanized areas and heavily irrigated croplands exist together. The results indicate that (1) the daytime irrigation cooling (with surface air temperature decreasing by ~0.1–0.5 °C at irrigated stations) was non-negligible in late autumn, early winter, and later spring months, when winter wheat irrigation mainly occurred over the BTH region, while a slight warming was observed at many irrigated stations during the nighttime. By contrast, urban warming was most pronounced in the nighttime, especially in winter, and the daytime warming at urban sites was much weaker and comparable to the magnitude of cooling induced by concurrent irrigation for winter wheat. (2) Collectively, the vast stretches of irrigated croplands helped mitigate urban warming, and their combined effect on the daytime surface air temperature over the whole region resulted in a slight cooling of ~0.2 °C in some of the winter wheat-growing months. (3) The contrasting temperature changes due to urbanization and irrigation were spatially variable. Beijing was predominantly characterized by urban warming, while Shijiazhuang, with extensive irrigation, exhibited irrigation cooling (or slight warming) during the daytime (or nighttime) in most of the winter wheat-growing months, which could be a possible contributor to the daytime cooling (or stronger nighttime warming) at urban sites. This work highlights the temperature contrasts between urban areas and surrounding irrigated croplands, as well as the potential role of extensive irrigation in mitigating (or enhancing) daytime (or nighttime) urban warming. Full article
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26 pages, 17971 KiB  
Article
Can the Coordinated Development of Land Urbanization and Population Urbanization Promote Carbon Emission Efficiency? A Multi-Scale Heterogeneity Analysis in China
by Hanlong Gu, Qi Liu, Ming Cheng, Chongyang Huan, Bingyi Wang and Jiaqian Wu
Land 2025, 14(7), 1317; https://doi.org/10.3390/land14071317 - 20 Jun 2025
Viewed by 349
Abstract
Coordinating development of land urbanization and population urbanization (CDLUPU) to enhance carbon emission efficiency (CEE) is a critical challenge for developing countries experiencing accelerated urbanization. The coupled coordination model and super efficiency SBM are employed to estimate the levels of CDLUPU [...] Read more.
Coordinating development of land urbanization and population urbanization (CDLUPU) to enhance carbon emission efficiency (CEE) is a critical challenge for developing countries experiencing accelerated urbanization. The coupled coordination model and super efficiency SBM are employed to estimate the levels of CDLUPU and CEE across 276 prefecture-level cities from 2010 to 2021. Furthermore, we utilize kernel density estimation and Spatial Durbin Model (SDM) to explore the spatio-temporal distribution characteristics and spatial effects. The results indicate that CDLUPU levels exhibited a sustained upward trend with diminishing regional disparities, whereas CEE displayed a pattern of initial growth followed by decline. Spatial analyses revealed a consistent gradient structure for both CDLUPU and CEE, characterized by radiation decay from southeastern coastal hubs toward interior hinterlands. CDLUPU exerts a significant positive direct impact and spatial spillover effect and indicates that the spillover effects on peripheral regions are substantially stronger than local effects. Regional heterogeneity analysis reveals that CDLUPU negatively affects CEE in eastern China, the Yangtze River Delta (YRD) is more pronounced, but it positively impacts central and western China, as well as Beijing–Tianjin–Hebei (BTH) and Chengdu–Chongqing (CY). Regarding indirect effects, eastern China shows significant positive impact on CEE, and similarly in the YRD. However, central China exhibits a negative effect, whereas BTH shows the opposite trend. Western China and CY show statistically insignificant results. This study offers policy insights for China to coordinate new urbanization strategy and achieve the “dual carbon goal”. Full article
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28 pages, 1981 KiB  
Article
Technology Spillovers, Collaborative Innovation and High-Quality Development—A Comparative Analysis Based on the Yangtze River Delta and Beijing-Tianjin-Hebei City Clusters
by Yan Qi and Yiwei Liu
Sustainability 2025, 17(12), 5587; https://doi.org/10.3390/su17125587 - 17 Jun 2025
Viewed by 476
Abstract
Exploring the mechanism of science and technology innovation spillover effect and collaborative innovation on the high-quality development of urban agglomerations is of great practical significance for implementing the innovation-driven development strategy. Based on the panel data of prefecture-level cities from 2012 to 2020, [...] Read more.
Exploring the mechanism of science and technology innovation spillover effect and collaborative innovation on the high-quality development of urban agglomerations is of great practical significance for implementing the innovation-driven development strategy. Based on the panel data of prefecture-level cities from 2012 to 2020, this study uses web crawler technology to obtain cooperative invention patent data, combines the social network analysis method to construct collaborative innovation networks, constructs a high-quality development indicator system from six dimensions such as the degree of marketization and the industrial system, and adopts the spatial Durbin model to reveal the regional innovation spillover effect. The comparative study based on the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) urban agglomerations found the following: (1) There is significant spatial heterogeneity in science and technology innovation, with the YRD showing a positive spillover trend and BTH showing a significant negative spillover trend; (2) The collaborative innovation network shows differentiated characteristics, with the YRD having a higher density of the network and forming a multi-centered structure, and BTH maintaining the pattern of single-core radiation; (3) There is a horse-tracing effect in high-quality development, with the average score of YRD The average score of YRD is significantly higher than that of Beijing-Tianjin-Hebei, and the indicators of several dimensions are better. Based on these conclusions, city clusters should further strengthen the construction of collaborative innovation networks among cities and enhance the capacity of neighboring cities to undertake innovation, to give full play to the spillover effect and driving effect of innovation on high-quality development. Full article
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38 pages, 11189 KiB  
Article
Evaluating Sustainability of Water–Energy–Food–Ecosystems Nexus in Water-Scarce Regions via Coupled Simulation Model
by Huanyu Chang, Yong Zhao, Yongqiang Cao, Guohua He, Qingming Wang, Rong Liu, He Ren, Jiaqi Yao and Wei Li
Agriculture 2025, 15(12), 1271; https://doi.org/10.3390/agriculture15121271 - 12 Jun 2025
Cited by 4 | Viewed by 1476
Abstract
Complex feedback mechanisms and interdependencies exist among the water–energy–food–ecosystems (WEFE) nexus. In water-scarce regions, fluctuations in the supply or demand of any single subsystem can destabilize the others, with water shortages intensifying conflicts among food production, energy consumption, and ecological sustainability. Balancing the [...] Read more.
Complex feedback mechanisms and interdependencies exist among the water–energy–food–ecosystems (WEFE) nexus. In water-scarce regions, fluctuations in the supply or demand of any single subsystem can destabilize the others, with water shortages intensifying conflicts among food production, energy consumption, and ecological sustainability. Balancing the synergies and trade-offs within the WEFE system is therefore essential for achieving sustainable development. This study adopts the natural–social water cycle as the core process and develops a coupled simulation model of the WEFE (CSM-WEFE) system, integrating food production, ecological water replenishment, and energy consumption associated with water supply and use. Based on three performance indices—reliability, coupling coordination degree, and equilibrium—a coordinated sustainable development index (CSD) is constructed to quantify the performance of WEFE system under different scenarios. An integrated evaluation framework combining the CSM-WEFE and the CSD index is then proposed to assess the sustainability of WEFE systems. The framework is applied to the Beijing–Tianjin–Hebei (BTH) region, a representative water-scarce area in China. Results reveal that the current balance between water supply and socio-economic demand in the BTH region relies heavily on excessive groundwater extraction and the appropriation of ecological water resources. Pursuing food security goals further exacerbates groundwater overexploitation and ecological degradation, thereby undermining system coordination. In contrast, limiting groundwater use improves ecological conditions but increases regional water scarcity and reduces food self-sufficiency. Even with the full operation of the South-to-North Water Diversion Project (Middle Route), the region still experiences a 16.4% water shortage. By integrating the CSM-WEFE model with the CSD evaluation approach, the proposed framework not only provides a robust tool for assessing WEFE system sustainability but also offers practical guidance for alleviating water shortages, enhancing food security, and improving ecological health in water-scarce regions. Full article
(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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22 pages, 22952 KiB  
Article
Time-Series Modeling of Ozone Concentrations Constrained by Residual Variance in China from 2005 to 2020
by Shoutao Zhu, Bin Zou, Xinyu Huang, Ning Liu and Shenxin Li
Remote Sens. 2025, 17(9), 1534; https://doi.org/10.3390/rs17091534 - 25 Apr 2025
Viewed by 318
Abstract
Satellite retrievals can capture the spatiotemporal variation of O3 over a large area near the surface. However, due to the unstable functional relationships between variables across spatiotemporal scales, the outlier predictions will reduce the accuracy of the prediction model. Therefore, a validated [...] Read more.
Satellite retrievals can capture the spatiotemporal variation of O3 over a large area near the surface. However, due to the unstable functional relationships between variables across spatiotemporal scales, the outlier predictions will reduce the accuracy of the prediction model. Therefore, a validated residual constrained random forest model (RF-RVC) is proposed to estimate the monthly and annual O3 concentration datasets of 0.1° in China from 2005 to 2020 using O3 precursor remote-sensing data and other auxiliary data. The temporal and spatial variations of O3 concentrations in China and the four urban agglomerations (Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD) and Sichuan–Chongqing (SC)) were calculated. The results show that the annual R2 and RMSE of the RF-RVC model are 0.72~0.89 and 8.4~13.06 μg/m3. Among them, the RF-RVC model with the temporal residuals constraint has the greatest performance improvement, with the annual R2 increasing from 0.59 to 0.8, and the RMSE decreasing from 17.24 μg/m3 to 10.74 μg/m3, which is significantly better than that of the RF model. The North China Plain is the focus of ozone pollution. Summer is the season of a high incidence of ozone pollution in China, YRD, PYD, and SC, while pollution in the PRD is delayed to October due to the monsoon. In addition, the trend of the O3 and its excess proportion in China and the four urban agglomerations is not satisfactory; targeted measures should be taken to reduce the risk of environmental ozone. The research findings confirm the effectiveness of the residual constraint approach in long-term time-series modeling. In the future, it can be further extended to the modeling of other pollutants, providing more accurate data support for health risk assessments. Full article
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24 pages, 7896 KiB  
Article
How Does Land Urbanization Affect Carbon Emissions in China? Evidence from 209 Cities and Three Heterogeneous Regions in the East of the Hu Line of China
by Hanlong Gu, Xueting Chen, Haohang Sun, Chongyang Huan and Bingyi Wang
Land 2025, 14(4), 910; https://doi.org/10.3390/land14040910 - 21 Apr 2025
Cited by 1 | Viewed by 697
Abstract
Land urbanization (LU) is a defining feature of China’s urbanization process and has led to significant carbon emission challenges. To clarify the interaction mechanism between LU and carbon emissions (CEs), this study examines the temporal and spatial characteristics of LU and CEs as [...] Read more.
Land urbanization (LU) is a defining feature of China’s urbanization process and has led to significant carbon emission challenges. To clarify the interaction mechanism between LU and carbon emissions (CEs), this study examines the temporal and spatial characteristics of LU and CEs as well as the direct and spatial spillover effects in the east of the Hu Line. Specifically, three representative regions are selected for heterogeneity analysis: the Three Northeast Provinces region (TNP), the Beijing–Tianjin–Hebei region (BTH), and the Southeast Coastal region (SC). The findings are as follows: (1) Both LU and CEs exhibited consistent upward trends, with average annual growth rates of 4.3% and 3.5%, respectively. (2) Empirical results demonstrate that the direct and indirect effect coefficients of LU on CEs are 0.129 and −0.224, respectively. (3) The direct effect of LU on CEs is significantly positive in both the TNP and the SC, with respective coefficients of 0.336 and 0.177. Notably, a positive spatial spillover effect is observed exclusively in the TNP, with a coefficient of 0.174. In contrast, LU exerts no significant influence on CEs in the BTH. The research findings offer valuable insights into the formulation of differentiated urbanization policies and effective carbon emission reduction policies. Full article
(This article belongs to the Special Issue Land Use Policy and Food Security: 2nd Edition)
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17 pages, 14325 KiB  
Article
Unveiling the Spatial Inequality of Accessibility to High-Quality Healthcare Resources in the Beijing–Tianjin–Hebei Urban Agglomeration of China: A Focus on the Impacts of Intercity Patient Mobility
by Yandi Wang, Lin Chen, Binglin Liu and Zhuolin Tao
ISPRS Int. J. Geo-Inf. 2025, 14(4), 168; https://doi.org/10.3390/ijgi14040168 - 11 Apr 2025
Cited by 2 | Viewed by 921
Abstract
The equality of accessibility to high-quality healthcare resources is an important issue in the development of urban agglomerations. However, comprehensive consideration of the impacts of intercity patient mobility and multilevel transportation networks is still lacking. This study develops a novel directional two-step floating [...] Read more.
The equality of accessibility to high-quality healthcare resources is an important issue in the development of urban agglomerations. However, comprehensive consideration of the impacts of intercity patient mobility and multilevel transportation networks is still lacking. This study develops a novel directional two-step floating catchment area method for measuring spatial accessibility to high-quality hospitals in the Beijing–Tianjin–Hebei (BTH) urban agglomeration. This method emphasizes the direction of intercity patient mobility caused by the hierarchy of high-quality healthcare resource distributions. Empirical analyses were conducted based on subdistrict-level population census data in 2020, 3-A hospital data from healthcare commissions, and door-to-door travel time data via multilevel intercity transportation networks from online maps in 2023. The analyses revealed obvious spatial inequalities in accessibility to high-quality healthcare resources in the BTH urban agglomeration, which is primarily caused by intercity inequality. Intercity patient mobility, however, can significantly mitigate the spatial inequality of healthcare accessibility within the BTH urban agglomeration. Moreover, it was determined that intracity first-mile and last-mile transfer transportation is the major barrier to intercity healthcare seeking and accessibility. This study has valuable implications for the planning and management of high-quality healthcare resources and intercity patient mobility in the BTH urban agglomeration. The developed methods are useful for measuring healthcare accessibility and inequality at the urban agglomeration scale. Full article
(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T)
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20 pages, 2968 KiB  
Article
Urban Spatial Management and Planning Based on the Interactions Between Ecosystem Services: A Case Study of the Beijing–Tianjin–Hebei Urban Agglomeration
by Yue Hu, Xixi Xu, Xuening Huang, Ying Li, Jiaxi Cao, Yimeng Yan, Xiaodan Hu and Shuhong Wu
Remote Sens. 2025, 17(7), 1258; https://doi.org/10.3390/rs17071258 - 2 Apr 2025
Viewed by 618
Abstract
Understanding the intricate relationships among ecosystem services (ESs) and clarifying their driving factors are essential prerequisites for establishing effective ecosystem management strategies. Therefore, we plotted the spatial-temporal distribution of five ESs in the Beijing-Tianjin-Hebei (BTH) urban agglomeration and analyzed their interactions in terms [...] Read more.
Understanding the intricate relationships among ecosystem services (ESs) and clarifying their driving factors are essential prerequisites for establishing effective ecosystem management strategies. Therefore, we plotted the spatial-temporal distribution of five ESs in the Beijing-Tianjin-Hebei (BTH) urban agglomeration and analyzed their interactions in terms of trade-offs, synergies, and bundles. We identified the primary drivers impacting ESs and proposed recommendations for urban spatial management and planning. The result revealed that (1) between 2000 and 2020, the supply of soil conservation increased the most, by 52.56%, and habitat quality decreased the most, by 6.92%; (2) four ES pairs were synergies and six ES pairs exhibited trade-offs, with three ES pairs showing decreased synergies and two ES pairs showing increased trade-offs; (3) the main factors influencing the driving forces of ESs were precipitation, cropland area ratio, and forest area ratio; and (4) the spatial-temporal analysis of ES interactions determined that ESs exhibiting decreasing synergies should be prioritized in ecosystem management, suggesting that the spatial planning of ecosystems should be based on ES bundles. Thus, this study provides guidance for regional ecosystem spatial planning and management. Full article
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20 pages, 11814 KiB  
Article
Self-Organizing Map-Based Classification for Fire Weather Index in the Beijing–Tianjin–Hebei Region and Their Potential Causes
by Maowei Wu, Chengpeng Zhang, Meijiao Li, Wupeng Du, Jianming Chen and Caishan Zhao
Atmosphere 2025, 16(4), 403; https://doi.org/10.3390/atmos16040403 - 30 Mar 2025
Viewed by 446
Abstract
Understanding the characteristics of wildfires in the Beijing–Tianjin–Hebei (BTH) region is crucial for improving the monitoring of local wildfire danger. Our investigation first establishes the spatial distributions of fire weather index (FWI) distributions and satellite-observed wildfire occurrences. The FWI provides a reasonably accurate [...] Read more.
Understanding the characteristics of wildfires in the Beijing–Tianjin–Hebei (BTH) region is crucial for improving the monitoring of local wildfire danger. Our investigation first establishes the spatial distributions of fire weather index (FWI) distributions and satellite-observed wildfire occurrences. The FWI provides a reasonably accurate representation of wildfire danger in the BTH region. Through Self-Organizing Maps (SOM) clustering analysis, we identify nine distinct spatial patterns in FWI composites. Notably, the annual frequency of SOM modes 2 and 7 has shown a significant increasing trend over the past 40 years. The spatial distribution of the highest FWI values in these two modes is in the southern and central BTH regions, respectively. Subsequently, we examine the relationship between FWI variations and atmospheric circulation patterns. A synoptic analysis indicates that the increased fuel availability index observed in SOM modes 2 and 7 can be primarily attributed to two key factors. One is a post-trough system, which is marked by a decrease in water vapor transport. The other is a high-pressure system, which is associated with higher temperatures and drought conditions. Finally, the relative contributions of the fuel available index and the wildfire spread rate index to the FWI are quantified using a partial differential approach. The variations in the fuel available index are the primary drivers of the high FWI values in these two SOM patterns. This study underscores the importance of analyzing the synergistic effects of multiple atmospheric circulation patterns on the fuel availability index, which is critical for improving wildfire danger prediction at different timescales in the BTH region. Full article
(This article belongs to the Special Issue Fire Weather and Drought: Recent Developments and Future Perspectives)
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30 pages, 5923 KiB  
Article
Electric Power Consumption Forecasting Models and Spatio-Temporal Dynamic Analysis of China’s Mega-City Agglomerations Based on Low-Light Remote Sensing Imagery Incorporating Social Factors
by Cuiting Li, Dongmei Yan, Shuo Chen, Jun Yan, Wanrong Wu and Xiaowei Wang
Remote Sens. 2025, 17(5), 865; https://doi.org/10.3390/rs17050865 - 28 Feb 2025
Cited by 1 | Viewed by 781
Abstract
Analyzing the electric power consumption (EPC) patterns of China’s mega urban agglomerations is crucial for promoting sustainable development both domestically and globally. Utilizing 2017–2021 NPP/VIIRS low-light remote sensing imagery to extract total nighttime light data, this study proposed an EPC prediction method based [...] Read more.
Analyzing the electric power consumption (EPC) patterns of China’s mega urban agglomerations is crucial for promoting sustainable development both domestically and globally. Utilizing 2017–2021 NPP/VIIRS low-light remote sensing imagery to extract total nighttime light data, this study proposed an EPC prediction method based on the K-Means clustering algorithm combined with multiple indicators integrated with socio-economic factors. Combining IPAT theory, regional GDP and population density, the final EPC prediction models were developed. Using these models, the EPC distributions for Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) urban agglomerations in 2017–2021 were generated at both the administrative district level and the 1 km × 1 km grid scale. The spatio-temporal dynamics of the EPC distribution in these urban agglomerations during this period were then analyzed, followed by EPC predictions for 2022. The models showed a significant improvement in prediction accuracy, with the average MARE decreasing from 30.52% to 7.60%, 25.61% to 11.08% and 18.24% to 12.85% for the three urban agglomerations, respectively; EPC clusters were identified in these areas, mainly concentrated in Langfang and Chengde, Shanghai and Suzhou, and Dongguan; from 2017 to 2021, the EPC values of the three urban agglomerations show a growth trend and the distribution patterns were consistent with their economic development and population density; the R2 values and the statistical values for the 2022 EPC predictions using the improved classification EPC models reached 0.9692, 0.9903 and 0.9677, respectively, confirming that the proposed method can effectively predict the EPC of urban agglomerations and is applicable in various scenarios. This method provides a timely and accurate spatial update of EPC dynamics, offering fine-scale characterization of urban EPC patterns using night light images. Full article
(This article belongs to the Special Issue Big Earth Data in Support of the Sustainable Development Goals)
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24 pages, 21665 KiB  
Article
Effects of Emission Variability on Atmospheric CO2 Concentrations in Mainland China
by Wenjing Lu, Xiaoying Li, Shenshen Li, Tianhai Cheng, Yuhang Guo and Weifang Fang
Remote Sens. 2025, 17(5), 814; https://doi.org/10.3390/rs17050814 - 26 Feb 2025
Viewed by 743
Abstract
Accurately assessing the impact of anthropogenic carbon dioxide (CO2) emissions on CO2 concentrations is essential for understanding regional climate change, particularly in high-emission countries like China. This study employed the GEOS-Chem chemical transport model to simulate and compare the spatiotemporal [...] Read more.
Accurately assessing the impact of anthropogenic carbon dioxide (CO2) emissions on CO2 concentrations is essential for understanding regional climate change, particularly in high-emission countries like China. This study employed the GEOS-Chem chemical transport model to simulate and compare the spatiotemporal distributions of XCO2 of three anthropogenic CO2 emission inventories in mainland China for the 2018–2020 period and analyzed the effects of emission variations on atmospheric CO2 concentrations. In eastern China, particularly in the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) regions, column-averaged dry air mole fractions of CO2 (XCO2) can exceed 420 ppm during peak periods, with emissions from these areas contributing significantly to the national total. The simulation results were validated by comparing them with OCO-2 satellite observations and ground-based monitoring data, showing that more than 70% of the monitoring stations exhibited a correlation coefficient greater than 0.7 between simulated and observed data. The average bias relative to satellite observations was less than 1 ppm, with the Emissions Database for Global Atmospheric Research (EDGAR) showing the highest degree of agreement with both satellite and ground-based observations. During the study period, anthropogenic CO2 emissions resulted in an increase in XCO2 exceeding 10 ppm, particularly in the North China Plain and the YRD. In scenarios where emissions from either the BTH or YRD regions were reduced by 50%, a corresponding decrease of 1 ppm in XCO2 was observed in the study area and its surrounding regions. These findings underscore the critical role of emission control policies in mitigating the rise in atmospheric CO2 concentrations in densely populated and industrialized areas. This research elucidates the impacts of variations in anthropogenic emissions on the spatiotemporal distribution of atmospheric CO2 and emphasizes the need for improved accuracy of CO2 emission inventories. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
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