Search Results (221)

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 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

The air quality in the Beijing–Tianjin–Hebei region of China has markedly improved in recent decades. Characterizing current PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 precursor control strategies and regional differentiation optimization improvement policies in the BTH region. Full article

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

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

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

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

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

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

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

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

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

In the context of carbon emission reduction, innovation by micro-agents is crucial for regional sustainable development. This paper investigates how micro-agent innovation impacts the sustainable development of industries within a region. To achieve this, we construct an agent-based and input–output (AGIO) model, which combines agent-based simulation at the micro level with the input–output model at the macro level. Using this model, we focus on the Beijing–Tianjin–Hebei (BTH) region, analyzing micro-agent innovation activities and conducting scenario simulations based on three key factors: innovation strength, profitability, and employee motivation. The study examines the effects of micro-agent innovation on the economy, energy, and carbon emissions in the BTH region from 2017 to 2060. The findings indicate that, (1) in terms of economic structure, micro-agent enterprises with higher profitability stimulate faster economic growth compared to the other two factors. Additionally, the innovation strength of micro-agent enterprises has the greatest impact on the industrial structure in Beijing, while profitability most influences Tianjin, and employee motivation has the strongest effect on Hebei. (2) Regarding energy consumption and energy structure, energy consumption declines rapidly after reaching its peak, and the energy structure shifts towards relatively low-carbon sources such as natural gas and electricity. Among the three influencing factors in this study, micro-agent innovation strength has the most significant impact on energy consumption in the industrial sector, with this influence intensifying over time, while profitability has the most pronounced effect on the evolution of the energy structure. (3) Concerning carbon emissions, before the carbon peak, the profitability of micro-agent enterprises exerts the most substantial influence on emissions in the region. After the peak, the impact of innovation strength becomes more pronounced. This research enriches the existing body of knowledge on the complex interplay between micro-level innovation and macro-level sustainable development, while providing valuable insights and actionable policy recommendations for steering regional economic transformation and environmental sustainability amidst the challenges posed by carbon emission reduction. Full article

Industrial heat sources (IHSs) are major contributors to energy consumption and environmental pollution, making their accurate detection crucial for supporting industrial restructuring and emission reduction strategies. However, existing models either focus on single-class detection under complex backgrounds or handle multiclass tasks for simple targets, leaving a gap in effective multiclass detection for complex scenarios. To address this, we propose a novel multiclass IHS detection model based on the YOLOv8-FC framework, underpinned by the multiclass IHS training dataset constructed from optical remote sensing images and point-of-interest (POI) data firstly. This dataset incorporates five categories: cement plants, coke plants, coal mining areas, oil and gas refineries, and steel plants. The proposed YOLOv8-FC model integrates the FasterNet backbone and a Coordinate Attention (CA) module, significantly enhancing feature extraction, detection precision, and operational speed. Experimental results demonstrate the model’s robust performance, achieving a precision rate of 92.3% and a recall rate of 95.6% in detecting IHS objects across diverse backgrounds. When applied in the Beijing–Tianjin–Hebei (BTH) region, YOLOv8-FC successfully identified 429 IHS objects, with detailed category-specific results providing valuable insights into industrial distribution. It shows that our proposed multiclass IHS detection model with the novel YOLOv8-FC approach could effectively and simultaneously detect IHS categories under complex backgrounds. The IHS datasets derived from the BTH region can support regional industrial restructuring and optimization schemes. Full article

The Beijing–Tianjin–Hebei (BTH) region serves as a pivotal engine for China’s economic development and a gathering area for energy consumption and carbon emissions. Its early achievement of carbon peak is of great significance for promoting high-quality development and regional coordinated development. This study constructs a system dynamics model encompassing four primary subsystems, economy, energy, population, and environment, based on an in-depth analysis of the current situation and main characteristics of carbon emissions in the BTH region from 2010 to 2022. We explored the carbon emission reduction effects under different scenarios by simulating a baseline scenario, an industrial structure optimization scenario, an energy structure optimization scenario, an environmental protection scenario, and a coordinated development scenario. The results indicate the following: (1) From 2020 to 2030, carbon emissions from energy consumption in the BTH region is predicted to exhibit a fluctuating downward trend under all five scenarios, with the most rapid decline observed under the coordinated development scenario. (2) Under the single-variable regulation, Beijing achieves the best carbon emission reduction effect under the environmental protection scenario, while Tianjin and Hebei exhibit superior performance under the energy structure optimization scenario. (3) All three regions demonstrate optimal emission reductions under the coordinated development scenario. Finally, this study discusses the carbon emission reduction paths for Beijing, Tianjin, and Hebei, and provides targeted suggestions for their implementation. Full article