Significant Spatial Heterogeneity Research Articles

Burden of chronic obstructive pulmonary disease attributable to ambient ozone pollution across China and its provinces, 1990-2021: An analysis for the Global Burden of Disease Study 2021.

Epidemiological studies have demonstrated a causal relationship between ambient ozone (O3) and mortality from chronic obstructive pulmonary disease (COPD), which is the only outcome considered in the Global Burden of Disease Study 2021 for O3. This study aims to evaluate the temporal trend and spatial distribution of the COPD burden attributable to O3 across China from 1990 to 2021. The ambient O3 concentrations in China were estimated. Based on the methodology framework and standard analytical methods applied in the Global Burden of Disease Study 2021, we estimated the annual number, age-standardized rate, and percentage of deaths and disability-adjusted life-years (DALYs) from COPD attributable to O3 pollution during 1990-2021 at the national and provincial levels in China. In 2021, a total of 125.7 (95% uncertainty interval [UI], 26.4-228.3) thousand deaths and 1917.5 (95% UI, 398.7-3504.6) thousand DALYs from COPD were attributable to ambient O3 pollution in China, accounting for 9.8% (95% UI, 2.1-17.0%) and 8.1% (95% UI, 1.8-14.1%) of the total COPD deaths and DALYs, respectively. Generally, a higher burden was observed among males, the elderly, and the population residing in regions with worse health conditions. The age-standardized rates of COPD deaths and DALYs per 100,000 populations ranged from 0.5 (95% UI, 0-1.4) and 8.1 (95% UI, 0.7-20.9) in Hong Kong to 22.8 (95% UI, 3.9-43.5) and 396.6 (95% UI, 68.9-763.7) in Xizang. From 1990 to 2021, there was a notable decrease in the age-standardized rates of COPD deaths (68.2%, 95% UI, 60.1-74.9%) and DALYs (71.5%, 95% UI, 63.7-77.6%), especially in regions with poor health conditions. However, the attributable numbers and percentages changed relatively marginally. Ambient O3 pollution is a major contributor to the COPD burden in China. Our findings highlight the significant spatial heterogeneity across different provinces and underscore the implementation of geographically tailored policies to effectively reduce O3 pollution and alleviate the associated disease burden.

Coupling Coordination and Influencing Mechanism of Ecosystem Services Using Remote Sensing: A Case Study of Food Provision and Soil Conservation

Understanding the trade-offs and synergies between ecosystem services is essential for effective ecological management. We selected food provisioning and soil conservation services to explore their intrinsic link and trade-offs. We evaluated these services in Minnesota from 1998 to 2018 using multi-source remote sensing data. The coupling coordination degree model (CCDM) was employed to quantify the relationship between these services. The CCDM evaluates the degree of coordination between systems by measuring their interactions. In addition, we used the geographically weighted regression (GWR) model to identify factors influencing this relationship. Our findings reveal that, while Minnesota’s food provision services have shown a significant overall upward trajectory, distinct declines occurred in 2008 and 2018. In contrast, soil conservation services showed considerable variability from year to year, without a clear trend. Over time, the relationship between food provision and soil conservation services evolved from uncoordinated and transitional to more coordinated development. Our analysis indicates that climate–soil indicators (Z1) exert the most significant influence on the coupling coordination degree (CCD), followed by topography (Z3), vegetation quality (Z4), and socio-economic indicators (Z2). This suggests that natural environmental factors have a greater impact than socio-economic factors. Spatial analysis highlights that topography exhibits significant spatial heterogeneity and serves as the primary spatial driving factor. This study explores the trade-offs between food provision and soil conservation ecosystem services in Minnesota, enhancing the understanding of trade-offs among different ecosystem services and providing insights for global sustainable agricultural development.

A Comprehensive Study of Heavy Metals in Centralized Drinking Water Sources of the Yangtze River Basin: Levels, Sources, and Probabilistic Health Risk

The water quality of centralized drinking water sources (CDWSs) in the Yangtze River Basin (YRB) has received widespread public attention. Regrettably, due to the lack of large-scale and high-frequency monitoring data, the trends, sources, and risks of heavy metals (HMs) in the water of CDWSs in the YRB are still unclear. In addition, the correlation between HMs and water quality parameters in natural water has not been established, which greatly affects the efficiency of water management. Herein, we collected data for eight HMs and twelve water quality physical–chemical parameters from 114 CDWSs in 71 prefecture-level cities in the YRB region. An unprecedented spatial distribution map of HMs in the YRB region was drawn, and the response of HMs to water quality and nutrient levels was studied. Overall, the level of HM pollution was low, but the threat of chloride, nitrogen, and phosphorus still exists. The detection rates of the eight HMs ranged from 60.00% (Ti) to 99.82% (Fe), and the mean concentrations were ranked as follows: Fe (36.576 ± 36.784 μg/L) > Mn (7.362 ± 7.347 μg/L) > Ti (3.832 ± 6.344 μg/L) > Co (2.283 ± 3.423 μg/L) > Se (0.247 ± 0.116 μg/L) > Cd (0.089 ± 0.286 μg/L) > Be (0.054 ± 0.067 μg/L) > Tl (0.015 ± 0.012 μg/L). In the large geographic area, the total concentrations of the eight HMs exhibited a fluctuating decay trend over time from 2018 to 2022. Geographically, industrial and agricultural production and geological coupling factors led to significant spatial heterogeneity in HM concentrations in the following order: midstream > downstream > upstream. Importantly, this study proved that Cl−, SO42−, nitrogen, and phosphorus may drive the absorption and transfer of HMs in natural water. Fortunately, exposure to the eight HMs does not cause adverse health effects in humans.

Evolution of landscape patterns and driving forces in rural areas of the Fuchun River Basin

At the optimal analysis granularity and extent, this study reveals the spatiotemporal evolution characteristics of landscape patterns in rural areas of the Fuchun River Basin from 1990 to 2020. It also explores the spatiotemporal differentiation of driving forces using Geodetector and Geographically Weighted Regression. The results indicate that: 1) The optimal analysis granularity for the study area is 30 m × 30 m, and the optimal analysis extent is 200 m. 2) Compared to the 1990s, the past two decades have seen an increased degree of landscape fragmentation, higher isolation, and stronger human disturbance in the study area, with significant differentiation. These changes are most pronounced in the semi-urbanized areas along the river and in the northern regions. 3) Digital Elevation Model and land cover type are the most critical driving factors. Over time, the explanatory power of most driving factors shows an overall increasing trend. 4) There is a significant spatial heterogeneity in the driving forces. The influence of the Digital Elevation Model and slope is stronger in the north and south, weaker in the central region, while the influence of temperature increases from north to south. The impact of land cover type is stronger in the central area and weaker in the periphery. This study provides a reference for the scientific use of land resources and the protection of ecological spaces in rural areas within highly urbanized regions at the basin scale.

Analysis of spatiotemporal evolution characteristics and recovery patterns of mangrove forests in China since 1978

Mangrove ecosystems have garnered significant attention for their pivotal role in the global carbon cycle and their contributions to multiple UN Sustainable Development Goals. In China, the strategic pivot towards comprehensive ecological restoration in mangrove management underscores an urgent need for a nuanced understanding of mangrove evolutionary patterns. However, existing remote sensing-based information on mangrove dynamics exhibits discrepancies, lacking a cohesive and precise understanding. Accordingly, this study utilized high-resolution GaoFen imagery and precise visual interpretation methods to meticulously update an existing mangrove dataset through 2022, ensuring high accuracy and improved timeliness. Building on this, the study conducted a rigorous spatiotemporal analysis of mangrove dynamics from 1978 to 2022, developed an index to assess recovery status, and ultimately proposed targeted recommendations for conservation and restoration. Findings reveal that between 2018 and 2022, China’s mangrove expanse witnessed an average annual net increase of 2.82%, marking an unprecedented high. Breaking down the net change, the rate of gain accelerated, averaging 878.63 ha per year, but it is noteworthy that the losses also increased rapidly, tripling that of the previous period, mainly in regions with intense human activities such as the Pearl River Estuary. This finding complements the general perception of a continuous net increase in mangrove areas, highlighting the paradox of significant contraction occurring alongside rapid expansion. Additionally, by 2022, mangrove extent had recovered to 28,641 ha, essentially returning to the 1978 level, yet characterized by poor stability and significant spatial heterogeneity, with Guangdong and Hainan exhibiting recovery indices below the average. The study emphasizes that the ecosystem’s intrinsic restorative capabilities have emerged as a critical factor in offsetting losses and signaling a positive trend. The latest data provided by this study can offer actionable insights and support for mangrove conservation and restoration initiatives, serving the goal of ecosystem recovery and affirming their indispensable role in environmental governance.

Transitions between Chinese dynasties influenced by spatial-patterned precipitation

Past studies have often associated the transitions of Chinese dynasties with nationwide climate change, overlooking significant spatial heterogeneity in precipitation anomalies across China. Historical changes in spatial precipitation patterns in response to Asian monsoon variability and their societal impact have not been fully explored. In this study, we present a new extended annual laminated speleothem record from central China covering the last 2000 years. By integrating paleoclimatic data from northern and southern China, we reconstructed the history of spatial precipitation patterns dominated by tripole and dipole patterns over the Common Era. Our analysis revealed that although the relationship between the monsoon and precipitation patterns was non-stationary, the positive phases of both patterns occurred more frequently during periods of monsoon weakening on multidecadal to multicentennial timescales. Moreover, the phase and intensity of these precipitation patterns varied across different intervals during the Chinese dynasties. Notably, transitions of unified dynasties often coincide with the simultaneous occurrence of the positive phases of both patterns on multidecadal timescales. This phase configuration of the patterns aligns with prolonged droughts in Eastern China, coinciding with historical records of reduced grain harvests and economic decline. Our findings highlight that historical changes in spatial configuration, rather than the nationwide synchronicity of precipitation anomalies, play a crucial role in Chinese dynastic transitions.

Effect of Regional Housing Hardship on Spatial Variation in Cancer Incidence: Does Housing Stress Increase Cancer Incidence?

Housing hardship can create a range of health issues. However, little attention has been paid to the relationship between housing hardship and cancer incidence. This study examines the Yangtze River Economic Belt (YREB) in China as a case study to develop a model of factors related to housing hardship that can affect cancer incidence. This study employs spatial regression models to investigate the correlation between housing hardship and cancer incidence and further explores the variation in the correlation between urban areas (UAs) and non-urban areas (NUAs). The research conclusions are as follows: (a) a palpable correlation exists between housing hardship and cancer incidence. The housing price-to-income ratio (HPIR) and the rental household proportion (RHP) are positively correlated to cancer incidence, whereas the per capita living area (PCLA) has a negative correlation with cancer incidence. (b) The differences in the impact of housing hardship on cancer incidence between the UAs and the NUAs are reflected mainly in the differences in the PCLA and the RHP. The PCLA has a strong association with cancer incidence in the UAs, whereas the RHP demonstrates a strong correlation with cancer incidence in the NUAs. (c) Significant spatial heterogeneity is observed in housing hardship in the YREB.

Unveiling the spatial heterogeneity of factors influencing physical and perceived recovery disparities under extreme rainstorms: A geographically weighted machine learning approach

Effectively allocating resources to address both the physical recovery of infrastructure and subjective needs of residents is crucial to safeguard the well-being of disaster-affected communities. Traditional recovery strategies often prioritize infrastructure restoration, leading to disparities between physical recovery and residents’ perceived recovery, shaped by multiple factors. However, understanding the factors influencing recovery disparities and their spatial heterogeneity remains challenging. To fill the gap, this study introduces a geographically weighted machine learning model to explore localized variations in factors shaping recovery disparities. By treating recovery disparities as dependent variables, we analyzed 779 communities affected by the “23·7″ extreme rainstorm in Beijing in 2023. The results reveal that 86.1 % of communities exhibit negative recovery disparities, while 13.9 % display positive disparities. All factors exhibit significant spatial heterogeneity of local coefficients (%IncMSE) across regions. Additionally, some factors show nonlinearity and threshold effects, with high vegetation (>6000), intense precipitation (>400 mm), and high population densities (>17,500 people/km2) causing the largest recovery disparities. This study presents a novel framework for disaster recovery planning that addresses both physical restoration and residents’ perceptions, providing insights for policymakers to reduce recovery gaps and promote resilient recovery processes.

Spatial effects of ecological cognition on firewood collection by households in protected areas: An analysis based on the giant panda nature reserves

The issues of unbalanced and inadequate energy development in rural China remain prominent, particularly in areas rich in natural resources, such as nature reserves, where households still tend to rely on traditional energy utilization modes. On one hand, the traditional use of firewood for energy results in low energy efficiency and indoor air pollution; On the other hand, it exacerbates problems such as habitat degradation for wildlife and environmental collapse. Although previous studies have explored rural energy source utilization from varies of aspects, there are still limitations in examining the impact of ecological cognition on household behaviors from a spatial correlation perspective. This study conducts a field survey of rural households in the giant panda nature reserves in Sichuan and Shaanxi Provinces to explore the impact of ecological cognition on rural households' firewood collection behaviors. By incorporating a spatial weight matrix, the study further analyzes the spatial spillover effects and the spatial heterogeneity of ecological cognition on rural households' firewood collection. The results show that: (1) ecological cognition significantly reduces firewood collection behaviors; (2) household income also decreases the consumption of firewood energy; (3) ecological cognition exhibits spatial spillover effects on rural households' firewood collection, indicating that household ecological cognition can impact surrounding households' ecological cognition and indirectly affect their firewood collection behaviors; and (4) significant spatial heterogeneity exists inside and outside the protected area. Ecological cognition significantly influences the firewood utilization of rural households within protected areas through spatial spillover effects, whereas its impact outside the protected areas is minimal. Strengthening forest ecological education to further raise ecological awareness, focusing on low-income households to provide energy subsidies, and utilizing the spatial spillover effects to enhance information dissemination channels are recommended for policy implications.

Spatial expansion characteristics of rural settlements and its response to determinants in Hangzhou Bay Urban Agglomeration, China: Geospatial modeling using multiscale geographically weighted regression (MGWR)

The expansion of rural settlements has become a significant issue in China's progress toward rural revitalization. Understanding the intricate connections between rural settlement expansion and its determinants is crucial. Previous studies have focused on identifying the characteristics and factors that contribute to rural settlement expansion at a fixed study scale, whereas the spatial heterogeneity of the impact of key drivers on rural settlement expansion at different geographical scales has been neglected. The spatial heterogeneity response relationship of driving factors to rural settlement expansion is a key basis for formulating management strategies; however, few studies have focused on this aspect. To address this knowledge gap, we constructed the Intensity–Space–Pattern–Driving research framework and investigated layout changes in rural settlement expansion and the complex spatial non-stationarity relationships between rural settlement expansion and various factors. Taking the Hangzhou Bay Urban Agglomeration as a case study, this study reveals that rural settlements rapidly expanded, which was primarily characterized by edge expansion from 1980 to 2020. Rural settlement expansion exhibited significant spatial heterogeneity across various regions, as evidenced by the shifting center of gravity of expansion, which moved from the northeast to the central region. Furthermore, the expansion direction indicated a trend of spreading from coastal areas to inland regions. These variations were closely linked to factors such as the natural environment, socio-economic conditions, geographic location, and others. Among the factors affecting the expansion of rural settlements, elevation, fractional vegetation cover (FVC) change, distance to factories, road density, and distance to city centers had the most significant response to the spatial heterogeneity of rural settlement expansion, meaning that they presented different directions and thresholds of influence at different spatial scales. This paper quantitatively assessed the impact of each driver at multiple geographic scales and proposed differentiated strategies for optimizing rural settlement layouts according to local conditions. This study reveals the specific characteristics of rural settlement expansion in rapidly urbanizing areas, provides a new analytical framework for a deeper understanding of the spatial heterogeneity of influencing factors, and offers a scientific basis for rural planning and management.

The 15-minute community life circle for older people: Walkability measurement based on service accessibility and street-level built environment – A case study of Suzhou, China

The 15-minute community life circle (15-min CLC) concept focuses on providing accessible services for older adults within a short walking distance. However, few studies have developed a comprehensive evaluation system of 15-min CLC walking accessibility for older people, and little is known about the effects of street-level environment characteristics and human perception on 15-min CLC. This study used the Baidu API and an optimized cumulative opportunity method to measure the 5-, 10-, and 15-min CLC walkability for older adults in Suzhou, China. Street-level characteristics and human perception scores, derived from street view semantic segmentation and deep learning, were incorporated into regression models to assess global and local effects on walkability. The results revealed that there was a significant spatial heterogeneity of CLC walkability in Suzhou. The 5- and 10-min CLCs were found lacking in facilities, particularly senior care services. The regression model showed a positive association between perceived safety and CLC walkability, while the proportion of street vegetation negatively affected walkability. The study suggests enhancing senior care, medical, and leisure facilities, especially within 10-min CLCs. Improving service integration in county-level cities and suburbs, and increasing street vegetation in older urban areas, could further enhance the walking environment for older adults.

Variations and influencing factors of vegetation net primary productivity over 31 years in Wuyishan National Park, China

In this study, the Carnegie–Ames–Stanford approach model was used to estimate the net primary productivity (NPP) of Wuyishan National Park from 1990 to 2020. Variation in NPP in parks was examined, and the influencing factors were identified. NPP showed an increasing trend annually with climate change. The value (625.67 gC m−2 a−1) obtained in this study was higher than the regional value along similar latitudes and coastlines. Affected by the spatial distribution characteristics of vegetation, NPP in the study area exhibited significant spatial heterogeneity, with a distribution of higher values in the northwestern region and lower values in the southeastern region. However, the growth rates showed the opposite trend. The higher growth rate of NPP in the ecological restoration zone was attributed to the ecological conservation efforts undertaken in Wuyishan National Park. Among the various environmental factors, the vapor pressure deficit contributed substantially to NPP temporal distribution, accounting for 25.71%. Terrain factors, which are influenced by the spatial distribution characteristics of vegetation and environmental factors, are important variables that affect the spatial distribution of NPP within the study area. The highest vegetation NPP in Wuyishan National Park was observed in regions with an elevation of approximately 1000 m, slopes ranging from 20° to 40°, and an aspect of approximately 150°. Compared with slope and aspect, elevation provides a stronger explanatory power (R2 = 0.93) for the spatial distribution patterns of vegetation NPP in Wuyi Mountain National Park. This study suggests that Wuyishan National Park has considerable carbon sequestration potential. In the context of climate warming, the favorable aspects of climate warming should be considered, and ecological restoration measures tailored to local conditions should be implemented.Article title mismatch between manuscript and publisher provided information, so we have follow the manuscript. Kindly check and confirm.Variations and influencing factors of vegetation net primary productivity over 31 years in Wuyishan National Park, China

Impact of Paddy Field Expansion on Ecosystem Services and Associated Trade-Offs and Synergies in Sanjiang Plain

In recent decades, the integrity and security of the ecosystem in the Sanjiang Plain have faced severe challenges due to land reclamation. Understanding the impact of paddy field expansion on regional ecosystem services (ESs), as well as revealing the trade-offs and synergies (TOS) between these services to achieve optimal resource allocation, has become an urgent issue to address. This study employs the InVEST model to map the spatial and temporal dynamics of five key ESs, while the Optimal Parameter Geodetector (OPGD) identifies primary drivers of these changes. Correlation analysis and Geographically Weighted Regression (GWR) reveal intricate TOS among ESs at multiple scales. Additionally, the Partial Least Squares-Structural Equation Model (PLS-SEM) elucidates the direct impacts of paddy field expansion on ESs. The main findings include the following: (1) The paddy field area in the Sanjiang Plain increased from 5775 km2 to 18,773.41 km2 from 1990 to 2020, an increase of 12,998.41 km2 in 40 years. And the area of other land use types has generally decreased. (2) Overall, ESs showed a recovery trend, with carbon storage (CS) and habitat quality (HQ) initially decreasing but later improving, and consistent increases were observed in soil conservation, water yield (WY), and food production (FP). Paddy fields, drylands, forests, and wetlands were the main ES providers, with soil type, topography, and NDVI emerging as the main influencing factors. (3) Distinct correlations among ESs, where CS shows synergies with HQ and SC, while trade-offs are noted between CS and both WY and FP. These TOS demonstrate significant spatial heterogeneity and scale effects across subregions. (4) Paddy field expansion enhances regional SC, WY, and FP, but negatively affects CS and HQ. These insights offer a scientific basis for harmonizing agricultural development with ecological conservation, enriching our understanding of ES interrelationships, and guiding sustainable ecosystem management and policymaking.

Spatial-Temporal Changes in Ecosystem Service Value and Its Overlap with Coal Mining Intensity in the Yellow River Basin, China, During 2000–2030

Understanding the ecosystem services and their interaction with coal resource development is crucial for formulating sustainable development policies. In this study, we focused on the Yellow River Basin, characterized by both rich coal resources and ecological fragility. The key findings are that (1) the ecosystem service value (ESV) in the Yellow River Basin exhibited significant spatial heterogeneity during 2000–2030, decreasing from the southeast to northwest, and decreasing the most notably in the southern part of the upper reaches of the river basin; (2) the high-high clustering area of the ESV shifted from the upper-middle reaches in 2000 to the middle-lower reaches in 2020, while the low-low clustering area remained within Inner Mongolia. By 2030, the high-high clustering area is expected to stabilize in southern Shaanxi Province, and the low-low area will potentially spread eastward; (3) the overall ESV is low, and it experienced a significant decline from 2000 to 2020, with water supply emerging as a major limiting factor, although some policy-supported counties had better ecological service values and trends. (4) From 2000 to 2020, the coal mining intensity (CMI) was concentrated in the upper and middle reaches, particularly at the junctions of Shanxi, Shaanxi, and Inner Mongolia, and the pattern remained stable, but local areas experienced increased mining intensity; (5) the overlap of the CMI and ESV primarily exhibited a low-high clustering pattern in the middle and upper reaches of the Yellow River Basin and eastern Ordos City, and a high-high clustering pattern in the middle reaches of the basin in Shanxi Province, which remained stable and slightly expanded from 2000 to 2030; (6) the trade-off between the ecosystem services in the overlap area intensified, especially between the provisioning and support services, and was significantly impacted by the coal mining activities. The findings indicate that the area that overlaps with the coal mining area in the Yellow River Basin has expanded and has had an increasing negative impact on the ESV. It is also essential to address the trade-offs between the provisioning and support services and to implement ecological restoration measures to mitigate the risk of ESV loss. Future efforts should focus on the regions where the CMI and ESV overlap and have poor coordination and the adverse effects of resource extraction on ecosystem services are becoming more pronounced. The results of this study demonstrate that spatial overlap analysis is effective in identifying the hotspots and provides a foundation for developing sustainable and high-quality policies for ecologically fragile basins.

The spatiotemporal patterns and driving factors of cybercrime in the UK during the COVID-19 pandemic

Cybercrime is a complex human behavior and social phenomenon. The COVID-19 pandemic has significantly altered socioeconomic activities, potentially causing changes in crime patterns. However, there has been limited research on how the interaction between the pandemic and socioeconomic factors affects cybercrime. Here we explore the spatiotemporal patterns of police-recorded cybercrime, including fraud and cyber-dependent crime, and employ a machine learning approach to assess the correlation of various factors on cybercrimes at the level of internal regions and police areas within the United Kingdom. Our results show that fraud and cyber-dependent crime are mainly concentrated in London and the southeast region of England. Moreover, following the implementation of the third national lockdown, these areas experienced a noticeable increase, while changes in other regions were not as pronounced. The spatial autocorrelation analysis further suggests that there are significant spatial heterogeneities among regions, with spatiotemporal hotspots centered around London and cold spots mainly concentrated in the northeast of England. Additionally, we found that the identified patterns of fraud and cyber-dependent crime are primarily associated with socioeconomic factors, followed by government containment measures and mobility factors. These findings can help law enforcement and regulatory agencies better understand the social-environmental factors contributing to the prevalence of cybercrime within those areas.

An Improved Machine Learning Framework Considering Spatiotemporal Heterogeneity for Analyzing the Relationship Between Subway Station-Level Passenger Flow Resilience and Land Use-Related Built Environment

The COVID-19 pandemic and similar public health emergencies have significantly impacted global travel patterns. Analyzing the recovery characteristics of subway station-level passenger flow during the pandemic recovery phase can offer unique insights into public transportation operations and guide practical planning efforts. This pioneering study constructs a station-level passenger flow recovery resilience (PFRR) index during the rapid recovery phase using subway AFC system swipe data. Additionally, it develops an analytical framework based on a multiscale geographically weighted regression (MGWR) model, the improved gray wolf optimization with Levy flight (LGWO), and light gradient boosting machine (LightGBM) regression to analyze passenger flow resilience on weekdays and weekends in relation to land use-related built environment types. Finally, SHAP attribution analysis is used to study the nonlinear relationships between built environment variables and PFRR index. The results show significant spatial heterogeneity in the impact of commercial, recreational, and residential land, as well as POI (points of interest) of leisure and shopping on PFRR. On weekdays, the most relevant built environment variables for PFRR are POI of enterprises and shopping numbers. In contrast, the contribution of built environment variables affecting PFRR of weekend is more balanced, reflecting the recovery of non-essential travel on weekends. Most land use-related built environment variables exhibit nonlinear associations with PFRR values. The proposed analytical framework shows significant performance advantages over other baseline models. This study provides unique insights into subway passenger flow characteristics and surrounding land use-related development layouts under the impact of public health emergencies.

Bacterial Diversity in Deep-Sea Sediment of West Pacific Nodule Province

Dense polymetallic nodule fields are found in different areas of the Pacific and Indian Oceans. However, limited knowledge exists about microbial diversity, processes and functions in deep-sea polymetallic nodule sediments. This study investigated microbial diversity, composition and function in sediments from various locations and depths in a western Pacific polymetallic nodule province. Sediment cores were collected, DNA extracted, and the V3–V4 regions of the 16S rRNA gene were sequenced using Illumina MiSeq. The test results show that the abundance and diversity of microbial communities in sediments from different sites vary significantly. The dominant microbial communities at the family level in the three sediment samples were all mainly Marinobacteraceae and Alcanivoracaceae. Sediment samples from core 1 had similar microbial structures and microbial community functions. Surface sediment had higher species richness, diversity and evenness than the middle layer. The dominant phylum at different depths was consistent. There was significant spatial heterogeneity in the microbial community within sediments from polymetallic nodule regions. This study expands on our knowledge of the spatial and vertical distribution of microbial community diversity beneath polymetallic nodules in deep-sea settings.

Particle transport and turbulence modification in unstably stratified mixed convection within a horizontal channel

Particle transport and turbulence modification in an unstably stratified, particle-laden turbulent flow within a horizontal channel is studied via direct numerical simulations combined with Lagrangian point‒particle tracking techniques. Two-way coupling in momentum and energy is considered in dilute gas‒solid flows under mixed convection (synergistic effects of shear and buoyancy). For comparison, simulations of neutral turbulence are also conducted with equivalent parameters. The study reveals that large-scale longitudinal vortical structures induce significant spatial heterogeneity in the spanwise distribution of inertial particles. This heterogeneity is characterized by an increase in the particle concentration on the side of the cold plume and a corresponding decrease on the side of the hot plume. In the context of unstably stratified turbulence, particles reduce the fluid streamwise velocity and promote its profile toward symmetry. This phenomenon contrasts with that observed in neutral flows, where particles induce velocity asymmetry by dragging the upper flow and accelerating the lower flow. A quantitative analysis of the heat flux indicates that particles absorb heat as they settle, thereby reducing the average temperature of the flow. Buoyancy effects slow the settling and reinjection of particles, which in turn diminishes thermal energy absorption. Particles with higher inertia preferentially settle on the cooler plume side, minimizing their participation in heat exchange due to prolonged durations of repeated wall collisions.

Assessment of the interaction between digital infrastructure and ecological resilience: Insights from Yangtze River Delta Urban Agglomeration in China

Exploring the interaction between digital infrastructure (DI) and ecological resilience (ER) is essential to understand whether urban development and the ecosystem have formed an integration trend. First, clarifying the interactive and driving mechanism between DI and ER, the evaluation indicator systems for them are constructed based on the core connotation of DI and the theory of evolutionary resilience. Then, using multiple methods such as the interactive coercion and the Markov chain model, the study reveals the spatiotemporal evolution of DI, ER, and their interactive levels in the Yangtze River Delta Urban Agglomeration (YRDUA)from 2005 to 2021. Furthermore, we employ the optimal parameter-based geographical detector (OPGD) to identify the core driving factors. The results indicate that (1) The comprehensive levels of DI and ER show an upward trend, and both systems have significant spatial heterogeneity. (2) The interactive coercion model verifies a coercive effect and a constraining relationship between DI and ER; notably, the interaction between the two systems is still in its moderate stage. (3) The analysis of driving factors reveals that socioeconomic conditions are the key influencing factors. Additionally, the proportion of cases showing a bi-enhancement type account for 92%, suggesting that the interactive role of the two factors mainly exhibits a multiplier effect. The study provides empirical evidence for solidifying the foundation of digital development, establishing robust ecological safety barriers, and promoting the deep integration of DI and ER, thereby facilitating high-quality regional development.

The evolution patterns and driving factors of urban domestic water pollution utilizing China’s two national pollution source surveys

Characteristics of domestic water pollution are of significant practical importance for implementing targeted urban wastewater treatment strategies. The pollutant source census in China serves as a fundamental undertaking in the study of pollution sources, providing crucial data for the analysis of pollution from domestic sources. This study employs pollution coefficients derived from China's two national pollution source surveys, integrating spatial autocorrelation and center-of-gravity shift analysis methods to investigate the national-scale spatial evolution characteristics of major urban domestic water pollutants, including BOD, TN, TP, and Oils. Furthermore, the impact of urbanization processes in population, economic, social, and spatial dimensions on urban domestic water pollution sources is explored using the multi-scale geographically weighted regression (MGWR) method. The results show that: (1) Urban domestic water pollution exhibits an east-high and west-low distribution pattern, with EHL being the primary region of pollution generation. Compared to 2007, the western region experienced a faster increase in BOD (30% increase), while the eastern region showed a sharper decline in TN (45% decrease) by 2017. (2) The results of spatial autocorrelation show that high-value clusters of urban domestic water pollution are located in the eastern China and around Chongqing, while low-value clusters are extensively distributed in the western region, indicating significant spatial heterogeneity in water pollution. (2) Based on center-of-gravity analysis, pollution displays a discernible migration trend from the northeast to the southwest, with the center located near the border of Henan and Hubei provinces, within the latitudinal and longitudinal range of 32°N–32.79°N and 113.09°E–113.85°E. The migration distances, ranked in descending order, are as follows: Oils (72.23 km) > BOD (65.59 km) > TN (63.9 km) > TP (22.73 km). (3) Significant differences are observed in the effects and spatial regions influenced by urbanization factors across different dimensions. Population and social urbanization exhibit pollution-increasing effects, whereas economic and spatial urbanization demonstrate pollution-reducing effects. These results will deepen our understanding of the spatial differentiation patterns of urban domestic source pollution, providing theoretical guidance for alleviating the pressure of urban pollution management. In addition, this article is an in-depth study of the first two pollution source surveys, which can lay a research foundation for future investigation work.