Search Results (271)

Railways constitute a core component of China’s national comprehensive transportation network, and their spatial organization and temporal accessibility jointly shape transport integration and system efficiency. Identifying their evolution from the dual perspectives of spatial expansion and time compression is therefore of both theoretical and practical significance. Drawing on fractal theory, this study examines the structural characteristics, evolutionary trends, and driving factors of railway networks in China’s five major urban systems from 2014 to 2024 from a “space–time” dual perspective. The results show that railway networks exhibit a staged pattern of “spatial filling preceding temporal correlation”, with a lag of approximately 1–8 years—about 1 year in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), 5 years in the Middle Yangtze River (MYR) region and Beijing–Tianjin–Hebei (BTH), and up to 8 years in the Chengdu–Chongqing (CC) region. In addition, clear regional differences are observed: the Yangtze River Delta (YRD) is polycentric, with the greatest potential, projected to continue rapid spatial growth until 2027 and to remain in a fast-growth phase of temporal correlation; GBA is highly coordinated; BTH is developed but characterized by dual-core agglomeration; CC grows rapidly with lagging functionality; and MYR is corridor-dependent with limited potential. These findings indicate that network functionality does not emerge synchronously with infrastructure expansion, but depends on subsequent improvements in operational organization and service capacity. Compared with single-scale-based indicators, the “spatial distribution–temporal correlation” framework more effectively captures network performance and provides quantitative support for transport optimization and coordinated regional development. Full article

Managing soil heavy metal pollution is pivotal for the sustainable development of the Beijing–Tianjin–Hebei (BTH) urban agglomeration. This study integrated geostatistical methods, Principal Component Analysis, and Positive Matrix Factorization (PMF) to characterize “source–sink” dynamics across diverse Main Functional Zones. Results revealed distinct pollution landscapes: Key Development Zones exhibited high-risk accumulation driven by multi-source superposition, while Ecological-restricted Zones, despite overall low pollution levels, faced significant anomalous enrichment of Cadmium (Cd). Source apportionment confirmed that this spatial differentiation stems from the coexistence of “in situ accumulation” and “source–sink misalignment” mechanisms. The former is driven by high-intensity industrial agglomeration, whereas the latter is governed by cross-boundary atmospheric transport and the topographic blocking of emissions from the plains. This research demonstrates for the first time the joint shaping effect of national spatial planning and natural geographical processes on regional pollution patterns. Accordingly, a precise management framework incorporating source reduction, cross-boundary synergy, and spatial reorganization is proposed, providing a new paradigm for addressing environmental risks caused by unbalanced development in rapidly urbanizing regions. Full article

Surface ozone monitoring remains challenging due to sparse ground networks and limited satellite boundary-layer sensitivity. This study evaluates, for the first time, China’s Environmental Trace Gases Monitoring Instrument II (EMI-II) for estimating surface ozone over the Beijing–Tianjin–Hebei (BTH) region. EMI-II total ozone columns (TOCs) are retrieved using the differential optical absorption spectroscopy (DOAS) algorithm and validated against the TROPOspheric Monitoring Instrument (TROPOMI) (R = 0.96), Geostationary Environment Monitoring Spectrometer (GEMS) (R = 0.97), and the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) ground measurements (R > 0.92, bias < 4%). TOCs are then combined with ERA5 meteorology, satellite NO₂/HCHO, and surface observations within machine learning models, achieving cross-validated R² of 0.94 and RMSE of 12.05 μg/m³ for surface ozone estimation. EMI-II estimates show strong agreement with independent observations (R = 0.91, RMSE = 10.83 μg/m³) and reproduce seasonal gradients, with summer concentrations (131 μg/m³) more than double winter levels (61 μg/m³). Estimation skill is regime-dependent: performance comparable to TROPOMI occurs under strong photochemical activity, while reduced sensitivity occurs under weak radiation and stable boundary layers—consistent with averaging kernel diagnostics. This first comprehensive validation demonstrates that EMI-II, despite vertical sensitivity limitations, provides meaningful surface ozone constraints under favorable atmospheric conditions. The framework is potentially applicable to other regions and sensors under similar conditions, providing a case study for integrating national satellite products into multi-source surface ozone estimation. Full article

Compound Drought and Heatwave (CDH) events increasingly threaten terrestrial carbon uptake, yet the spatiotemporal heterogeneity of Gross Primary Productivity (GPP) responses in urban agglomerations remains unclear. This study analyzed CDH impacts in China’s three major urban agglomerations, namely the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions, using ERA5 and satellite GPP data (GOSIF and FluxSat) for representative CDH years (2007 for BTH; 2022 for YRD and PRD). CDH conditions exhibited a coherent hot–dry coupling, with temperature anomalies of 0.46–1.26 K and soil moisture deficits of −0.042 to −0.169 m³ m⁻³, accompanied by enhanced atmospheric dryness. Pronounced spatial heterogeneity in GPP responses aligned with regional climatic regimes and ecosystem types. The water-limited BTH region exhibited significant GPP deficits, with anomalies of −1.13 Standard Deviations (STD) and −0.96 STD for GPP_FluxSat and GPP_GOSIF, respectively. Conversely, the energy-limited regions showed positive anomalies: the YRD recorded +0.32 and +1.79 STD, while the PRD reached +1.86 and +1.06 STD for GPP_FluxSat and GPP_GOSIF, respectively. Mechanistically, the north–south contrast suggests a transition from water-limited vulnerability to energy-limited resilience, with vegetation traits and management (e.g., potential irrigation buffering in croplands and deeper water access in forests) modulating sensitivity to atmospheric dryness. These findings provide quantitative benchmarks for improving regional carbon-cycle assessments and adaptation planning under increasing compound extremes. Full article

Aerosol optical depth (AOD) is a key indicator for quantifying aerosol radiative effects and evaluating air quality. However, atmospheric chemical transport models often exhibit systematic AOD biases, and model capability for column-integrated optical properties is not always consistent with that for near-surface particulate matter concentrations. Here, we evaluate AOD simulated by the Community Multiscale Air Quality (CMAQ) model over five major urban clusters in China, including the Beijing-Tianjin-Hebei (BTH) region, Fenwei Plain (FWP), Sichuan Basin (SCB), Yangtze River Delta (YRD), and Pearl River Delta (PRD), using satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground-based retrievals from the Aerosol Robotic Network (AERONET), and vertical extinction profiles from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). CMAQ reproduces the major spatial patterns and exhibits relatively small biases in near-surface PM_2.5. However, it persistently underestimates AOD relative to MODIS, with the largest negative bias occurring in April (i.e., a typical spring month). This contrast indicates a pronounced inconsistency between column-integrated aerosol amount and surface mass density. Relative to AERONET, CMAQ shows a negative bias (NMB = −38%), whereas MODIS shows a positive bias (NMB = 56%), suggesting that both model and retrieval uncertainties contribute to the CMAQ–MODIS disagreements. CALIPSO-constrained vertical analysis further suggests that insufficient extinction above the planetary boundary layer (PBL) is an important contributor to the negative AOD bias, although the relative roles of boundary-layer and upper-layer contributions vary across regions, underscoring the importance of accurately representing aerosol vertical transport and optical processes. These results indicate that evaluations based solely on surface observations may fail to fully capture the overall structure of AOD errors, particularly given the clear differences between near-surface mass concentrations and column optical properties, which vary across regions. This also highlights the importance of improving the representation of aerosol vertical transport and optical processes in chemical transport models. Full article

New quality productive forces are increasingly recognized as important drivers of coordinated regional development, with urban agglomerations acting as key vehicles for their spatial implementation. Based on the theory of new quality productive forces, this study takes the 13 cities in the Beijing–Tianjin–Hebei (BTH) urban agglomeration as its research subjects, spanning the period from 2005 to 2023, and constructs a four-dimensional evaluation index system for new quality productive forces covering economic, social, ecological, and technological dimensions. It employs the entropy method to determine indicator weights and calculate development indices for each dimension and utilizes a coupling coordination model to measure the overall and subsystem-level coordination by analyzing their spatiotemporal evolution characteristics. The results indicate a steady upward trend in the overall coordination level, progressing from a low level to an intermediate level, with the state of coordination continuously improving; spatial differentiation is significant, forming a gradient development pattern centered on Beijing, with marked disparities in coordination levels among cities. Subsystem analysis reveals an imbalanced synergy structure: while economic and ecological synergy levels are relatively high, the coupling and synergy between science and technology and the economy and society remain prominent weaknesses. Most cities in Hebei Province lack sufficient scientific and technological innovation capabilities, resulting in a weak supportive role for economic and social development. Based on these findings, this study proposes policy recommendations such as establishing a regional innovation community, promoting the integration of factor markets, and strengthening collaborative governance of the ecological environment, with the aim of leveraging new quality productive forces to drive a qualitative leap in the coordinated development of the BTH urban agglomeration. Full article

Soil organic carbon (SOC) is a key indicator reflecting soil quality and management level. Understanding its spatiotemporal dynamics in cropland is necessary for sustainable land management. Revealing the relationship patterns between SOC (Sampling resolution: 1 km²; analysis resolution: 4 km²) and environmental factors in one period allows inferring SOC distribution in unsampled years, partly compensating for temporal data gaps. This study introduces a season-based crop rotation system (Winter wheat in the first season and summer corn in the next) as independent variables in a machine learning model innovatively, enriching variable selection in SOC inference and improving understanding of SOC accumulation. The Beijing–Tianjin–Hebei (BTH) region, characterized by a typical winter wheat–summer corn rotation system, was selected for analysis. The results show that in 2000, the average SOC was relatively low compared with global levels. Climatic variables were negatively correlated with SOC below the 0.8 quantile but positive above it, which corresponds to the upper 20% of the observed range of each climatic variable. Winter-wheat growth is more important on SOC distribution than summer-corn growth (two annual peaks of NDVI and EVI), showing a positive correlation with SOC, while corn showed a weak correlation and became negative above the 0.8 quantile. In the inferred results, the differences between observed and inferred mean values and their confidence intervals were approximately 0.1. This research provides a reference method for evaluating regional-scale SOC distribution patterns under data-limited conditions by integrating environmental factors and crop rotation characteristics. Full article

With the acceleration of global climate change and urbanization, air pollution, particularly ozone pollution, has become a critical environmental issue, especially in the Beijing–Tianjin–Hebei region of China. This study investigates the spatiotemporal distribution of ozone pollution and its precursors, focusing on formaldehyde as a key indicator of volatile organic compounds. Utilizing high-resolution remote sensing data from the China High-Resolution Air Pollutants dataset and TROPOMI HCHO observations from 2013 to 2022, we employed advanced techniques such as the Kolmogorov–Zurbenko filter and high-value area identification to analyze ozone pollution trends, meteorological influences, and the spatial distribution of HCHO concentrations. Our findings reveal a significant increase in ozone concentrations across BTH, with an annual growth rate of 2.51 μg/m³, peaking during the summer months. The KZ filter decomposition highlighted that short-term and seasonal variations dominate ozone fluctuations, driven by meteorological factors such as solar radiation and temperature. Furthermore, the identification of HCHO HVAs demonstrated that urban agglomeration and expansion zones exhibit higher HCHO concentrations, with VOCs-limited zones showing the most pronounced HCHO levels. The study also introduced the PHV (Percentage Higher than Vicinity) index to quantify anomalous HCHO emissions, providing a robust tool for pinpointing pollution hotspots. Based on these insights, we propose targeted emission control strategies for key regions, including urban expansion zones in Zhangjiakou and non-urban zones in Qinhuangdao, to mitigate ozone pollution effectively. This research offers valuable scientific support for regional air quality management and the formulation of precise pollution control measures in the Beijing–Tianjin–Hebei region. Full article

As the largest urban agglomeration and a critical grain production base in northern China, the Beijing–Tianjin–Hebei (BTH) region faces a sharp conflict between rapid urbanization and cropland conservation. Urban expansion inevitably leads to the loss of high-quality agricultural land, posing dual threats to food security and the terrestrial carbon cycle. To accurately assess the ecological costs of this process, this study integrates the CASA model with a time-weighted cumulative model to quantify the spatiotemporal impacts of urban expansion on cropland NPP in the BTH region from 2001 to 2020. Furthermore, a Geographically Weighted Regression (GWR) model was employed to examine the spatially varying effects of key driving factors on cropland NPP loss. The results indicate that urban land in the BTH region expanded by 45.2% over the past two decades, with 91.04% originating from cropland. Despite an overall upward trend in regional cropland NPP driven by climate change and agricultural intensification, the time-weighted cumulative cropland NPP loss attributable to urban encroachment over 2001–2020 reached 29.24 Tg C, which is equivalent to 0.751× the annual total cropland NPP in 2020 (used as a reference benchmark). Crucially, this expansion exhibits distinct ecological selectivity toward high-quality cropland, meaning that urban development has disproportionately encroached upon highly productive land with productivity levels exceeding the regional average. This selective occupation has led to a structural decline in the region’s potential agricultural production capacity. Additionally, GWR results reveal significant spatial non-stationarity in the relationships between cropland NPP loss and its drivers, revealing differentiated response patterns between plains and mountainous areas in terms of socio-economic drivers and physical constraints. These findings expose the hidden threats of urban expansion to food security, providing a crucial scientific basis for formulating differentiated land management policies and coordinating regional urbanization with cropland protection. Full article

China’s stringent clean air policies have substantially reduced nitrogen oxides (NO_x) emissions, leading to a general decline in nitrogen dioxide (NO₂). However, surface ozone (O₃) pollution remains severe, creating a complex challenge due to the non-linear relationship between O₃ and its precursors. To disentangle the drivers behind these trends, this study quantifies the impacts of interannual variations in top-down constrained NO_x emissions on surface NO₂ and O₃ concentrations from 2014 to 2021 across mainland China and five national urban agglomerations. We employed the WRF-CMAQ model with a fixed-emission simulation approach, using an observationally optimized NO_x emission inventory derived from the assimilation of surface NO₂ measurements. Results reveal that NO₂ reductions were predominantly emission-driven (>80% post-2017), with declines most pronounced in winter. A strong linear consistency was found between interannual changes in top-down NO_x emissions and attributed NO₂ concentration variations, validating the methodology. In contrast, O₃ responses to NO_x reductions were spatially and seasonally heterogeneous, reflecting a non-linear photochemical regime. In major urban agglomerations (e.g., Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD)), NO_x reductions post-2018 showed limited effectiveness in mitigating summertime O₃ and even increased O₃ in spring and autumn, indicating a prevalent VOC-sensitive regime where NO_x reduction can disinhibit O₃ formation. Conversely, certain provinces (e.g., Anhui, Shanxi, Jilin) exhibited O₃ decreases, suggesting a NO_x-sensitive regime. The area benefiting from NO_x reductions expanded steadily in summer after 2017 but not in other seasons. This study confirms the efficacy of NO_x-focused policies for reducing primary NO₂ pollution but highlights that mitigating persistent O₃ requires a strategic shift to synergistic, region-specific control of volatile organic compounds alongside NO_x, informed by local chemical sensitivity. Full article

Ecological network optimization can enhance ecological connectivity, regional ecological stability, and carbon sink capacity. Current research on ecological networks employs single-perspective optimization, which overlooks the synergistic requirements between network topological characteristics and the dual carbon goals. It lacks a comprehensive, systemic optimization framework. Focusing on the Beijing–Tianjin–Hebei region, the work constructs an ecological network by integrating ecosystem services, morphological spatial pattern analysis (MSPA), and circuit theory. A framework integrating barrier removal, structural robustness, and carbon sink enhancement is proposed, incorporating ecological barrier identification, complex network theory, and carbon offset patterns for multi-objective structural and functional optimization. The optimized network is evaluated using structural metrics, robustness analysis, and carbon sequestration validation. The network comprises 41 ecological sources and 102 corridors, exhibiting a dense northwest and sparse southeast distribution. Ecological barriers totaling 565.56 km² are removed to improve connectivity in the region. An edge-addition strategy introduces 12 nodes and 49 edges, enhancing connectivity, stability, and carbon sink capacity. Restoration priorities are set with the phased objectives of removing barriers, connecting topological weak points, and optimizing low-value carbon offset areas. Shifting the focus from structural connectivity to integrated function, the work contributes a methodological framework for advancing ecological security and carbon neutrality in urban agglomerations. Full article

The Beijing–Tianjin–Hebei (BTH) region is one of the most complex and heterogeneous regions in China, where differences in marginal abatement costs across cities jointly shape the effectiveness of regional air quality management. This study develops an integrated analytical framework that combines pollutant-specific abatement cost accounting, optimization of territorial and coordinated emission reduction scenarios, and cooperative game-based cost allocation. Using this framework, we quantify both the total cost-saving potential and the distributional effects of coordinated air pollution control in the BTH region. The results are as follows: (1) Under the territorial governance model, the total cost reaches CNY 22.627 billion, whereas coordinated governance lowers this to CNY 21.647 billion. Joint prevention and control is economically more efficient and produces a globally optimal cost outcome for the region. (2) After redistribution, the final burdens of Beijing (CNY 572 million), Tianjin (CNY 1.154 billion), and Hebei (CNY 19.921 billion) are all lower than their territorial governance costs, ensuring that each region gains from cooperation. (3) Significant differences in marginal removal costs among the three regions, with Hebei exhibiting the highest marginal emission cost and lowest marginal removal cost. Optimal coordinated governance requires Hebei to undertake a greater share of emission reduction, while Beijing and Tianjin reduce less compared with their independent plans. The coordinated model enhances regional resource efficiency, reduces redundant investment, and achieves the same total emission reduction at a lower aggregated cost. Full article

The Beijing–Tianjin–Hebei (BTH) region is a critical political and economic hub in China, which has long faced challenges related to atmospheric conditions. Traditional aerosol optical depth (AOD) monitoring methods suffer from issues of data discontinuity and gaps, limiting the ability for continuous long-term observation of aerosols. Aerosols have significant impacts on climate change and air quality, with AOD serving as a key indicator for characterizing atmospheric particulate concentration. Therefore, this study applied a machine learning model to improve all-day AOD estimation based on ground-level air quality and meteorological data, generating a long-term dataset spanning from 2018 to 2023. The results of the all-day AOD estimation method were evaluated through comparisons with Himawari-8, the Aerosol Robotic Network (AERONET), and the Copernicus Atmosphere Monitoring Service (CAMS). The estimated AOD demonstrated good agreement with AHI data, achieving an annual R² greater than 0.96 and RMSE less than 0.1. Spatially, the estimated AOD also showed strong consistency with AHI, AERONET, and CAMS. Additionally, the annual, seasonal, and hourly distribution characteristics of AOD from 2018 to 2023 were analyzed. Two typical cases of aerosol variation in the BTH region were selected and examined: a dust storm event in 2023 and changes during the Spring Festival in 2021. This method provides continuous data support for air pollution monitoring and control in the BTH region and offers valuable references for pollution prevention efforts. Full article

China has made significant progress in paleontological heritage conservation. However, research and conservation efforts have predominantly focused on exquisitely preserved, movable specimens of high scientific value, leading to the relative neglect of in situ paleontological geosites which are critical for understanding fossil distribution patterns. To address this gap, this study employs a GIS approach to conduct a multifaceted spatial analysis of paleontological geosites in the BTH region as a representative case study. Our results reveal a pronounced spatiotemporal imbalance in the distribution of these geosites. Furthermore, their spatial configuration exhibits significant correlations with key physiographic factors—including elevation, stratigraphic distribution, and slope—as well as socioeconomic indicators such as population density, GDP density, and fiscal self-reliance ratio. This uneven distribution creates substantial conservation challenges, resulting in fragmented governance, a mismatch between local conservation capacities and needs, and potential biases in protection priorities toward specific regions or geological periods. In the BTH region, the distribution patterns of paleontological geosites are jointly shaped by physiographic, socioeconomic, and anthropogenic process factors. Elucidating the relationships between these drivers and the spatial distribution of geosites constitutes a critical foundation for advancing their scientific conservation and sustainable management. Drawing on broader interdisciplinary insights, currently peripheral paleontological heritage can be further transformed into strategic and sustainable resources. Full article

Assessment of water resource spatial equilibrium (WRSE) is crucial for regional sustainable development, yet traditional methods always face difficulties in quantifying systemic differences and resolving their internal uncertainties. Accordingly, this study proposes a novel multi-attribute decision-making (MADM) model that integrates symmetric interaction entropy (SIE) with connection numbers (CNs) within a variable-weight framework. Firstly, information differences between alternatives and an ideal state were quantified by SIE, then these differences were decomposed into certain and uncertain components through the “identity–difference–opposition” (IDO) idea of CNs. In addition, a variable-weight mechanism was incorporated to enhance the model’s adaptability to regional characteristics. Applied to evaluate the WRSE in the Beijing–Tianjin–Hebei (BTH) region from 2014 to 2023, the model reveals that Hebei maintains the most favorable equilibrium state, with a partial identity potential or equal potential, followed by Beijing, while Tianjin predominantly exhibits partial opposite potential due to pronounced conflicts between its resource endowment and industrial structure. The proposed model not only enhances the sensitivity and interpretability of evaluation results but also facilitates the identification of key vulnerable indicators, thereby providing a scientific basis for formulating differentiated regional water governance strategies. Full article