Significant Spatial Heterogeneity Research Articles

Coupling coordination between urbanization and ecosystem services value in the Beijing-Tianjin-Hebei urban agglomeration

While urbanization has increased people's well-being, it has also caused ecological problems, such as resource shortage, land degradation, and environmental pollution. As the highest form of spatial organization at the mature stage of urbanization, an urban agglomeration (UA) can be a key area for studying this urban-ecology interaction. This study integrated the urbanization evaluation, ecosystem services value (ESV) assessment, and optimized coupling coordination degree (CCD) models to explore the coupling coordination of urbanization and ESV at the UA scale. Analyzing data from the Beijing-Tianjin-Hebei UA (BTHUA) from 1985 to 2020 revealed that: (1) urbanization continues to increase and ESV fluctuates; however, both exhibit significant spatial heterogeneity. (2) The CCD is increasing annually but remains relatively low overall; spatially, it is high in the northeast and low in the southwest. (3) The main driving factors of the CCD are urbanization rate and slope, while all five selected factors have a positive effect. (4) Government decision-making can guide the CCD. For which, the development pattern of “One Belt-Four Zones-Multi Cores” and zoning strategies for improving the CCD are proposed. Overall, these findings suggest balancing development and protection to promote the coordinated development of BTHUA and provide valuable insights for enhancing the sustainability of UA.

Addressing Urban Management Challenges for Sustainable Development: Analyzing the Impact of Neighborhood Deprivation on Crime Distribution in Chicago

Urban crime prevention remains a critical challenge intertwined with socioeconomic disparities. This study investigates the spatial nexus between urban deprivation and crime decline in Chicago from 2015 to 2022, addressing the question: How do changes in neighborhood deprivation relate to crime reduction patterns? Using comprehensive crime incident and census tract Area Deprivation Index (ADI) data, this study conducted exploratory spatial analysis, regression modeling, and local bivariate relationship analysis. The findings reveal persistent hotspots of concentrated deprivation on Chicago’s south and west sides, alongside a general citywide crime decline. However, the current research uncovered significant spatial heterogeneity in both deprivation patterns and crime reduction, challenging the achievement of equitable public safety outcomes. Surprisingly, while crime incidents in 2015 and 2022 significantly predicted crime change, ADI scores were not statistically significant predictors in our regression model. Local bivariate analysis exposed diverse relationships between ADI changes and crime rate changes across neighborhoods, with 72.2% of census tracts showing no statistically significant relationship. This underscores the complexity of urban crime dynamics and the importance of local context in understanding these patterns. Our research contributes a nuanced understanding of the intricate relationship between urban deprivation and crime patterns, providing valuable insights for policymakers, law enforcement agencies, and urban planners. These findings highlight the need for integrated, long-term strategies that address both crime prevention and socioeconomic disparities, ultimately fostering safer, more equitable urban environments and informing evidence-based interventions tailored to specific neighborhood contexts.

Identifying the spatiotemporal patterns of drought-flood alternation based on IMERG product in the humid subtropical Poyang Lake basin, China

Study RegionA humid subtropical basin, Poyang Lake Basin, China. Study focusDrought-flood alternation (DFA) is sub-seasonal precipitation anomaly, which has more serious impact on agricultural production, ecology and environment than a single drought or flood event. The study evaluated the suitability of high-resolution satellite-based precipitation product for identifying the DFA event and quantified the spatiotemporal patterns of the frequencies and intensities of DFA at various time scales. New hydrological insights for the regionThe Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) product could effectively identify the DFA events at 1-month scale, with high consistency with the results based on traditional rain-gauge data, however, its performance was not very satisfactory at 3-month and 6-month scales. Drought-to-Flood (DTF) events usually occurred from March to June, while Flood-to-Drought (FTD) events mainly occurred during from July to September. Frequencies and intensities of both DTF and FTD exhibited significant spatial heterogeneity. The lake area was mainly affected by DTF events, and the Ganjiang sub-catchment was mainly affected by FTD events. Especially, the southern part of the basin was a high-risk area affected by DFA, with higher frequencies of both severe DTF and FTD events. Furthermore, although the total area affected by DFA events showed a long-term decreasing trend from 2000 to 2019, the area affected by severe DTF and FTD events was gradually expanding in Poyang Lake basin.

Analysis of nitrogen migration and transformation in the typical deep and large reservoir of the Lancang River — Evidence from nitrogen and oxygen isotopes

The environmental effect resulting from dam construction and the formation of large reservoirs has long been a topic of significant concern. While current research at a macro scale provides a well understanding regarding the evolution of nitrogen nutrient status in river-reservoir ecosystems, the vertical migration and transformation characteristics of nitrogen in reservoirs under changing runoff remain less defined. This study centers on a typical deep reservoir along the Lancang River-Nuozhadu (NZD) Reservoir in April and December. The monitoring reveals a distinct vertical stratification phenomenon in the NZD Reservoir in the vertical profile in April, which can be categorized into a mixed layer (ML) (0–5 m), a thermocline layer (TL) (5–40 m), and an isothermal layer (IL) (>40 m) based on the water temperature. However, little stratification in the profile is occurred in December. The results of nitrogen and oxygen isotopes in April indicate that the biochemical process of nitrogen in the NZD Reservoir is predominantly driven by nitrification. However, different nitrogen biochemical processes are coupled in various stratified regions in the vertical direction. In the ML, simultaneous assimilation of ammonia nitrogen by phytoplankton occurs. In the TL, there is a process of oxidation and decomposition of particulate organic nitrogen due to a significant stratification effect and an extended hydraulic retention time. In the region of minimal dissolved oxygen (30–40 m), simultaneous denitrification may take place. In December, the main process is nitrogen assimilation in reservoir surface (ML). Statistical analysis of environmental factors highlights water temperature (T) and dissolved oxygen (DO) as crucial environmental factors influencing nitrogen migration and transformation within the reservoir. This study suggests that in deep reservoirs experiencing vertical thermal stratification, the characteristics of DO and nitrogen migration and transformation exhibit significant vertical spatial heterogeneity. This phenomenon may lead to diverse ecological environmental effects. Future efforts should focus on enhancing the fine monitoring of stratified water bodies in deep and large reservoirs and analyzing the ecological environmental effects of material cycling in greater detail.

Spatial characteristics of carbon dioxide emission intensity of urban road traffic and driving factors: Road network and land use

Road traffic is a major contributor to global carbon dioxide emissions. The impact of urban road networks and land use on these emissions remains controversial. This study proposed carbon dioxide emission intensity (CEI) based on road network length, analyzed the spatial distribution characteristics of CEI of passenger and freight traffic in the Southern Kanto region of Japan through spatial autocorrelation analysis, and examined the driving effects of urban road network and land use characteristics through Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. The results showed that the CEI of passenger traffic demonstrated more significant spatial heterogeneity than freight traffic, exhibiting a spatial pattern of high-value clustering in the center and low-value clustering in the peripheral area. Road network characteristics are the primary driving factor for CEI of passenger traffic. A road network with lower density, rich branching streets does not necessarily promote the reduction of carbon dioxide emissions. The industrial land proportion exerts a stronger and more extensive driving effect on the CEI of freight traffic than road network characteristics. As a specialized study on carbon dioxide emissions from road traffic, this study provides the decision-making criteria for urban planning strategy and urban management to enhance urban sustainable development.

Research on the distribution and influencing factors of fine mode aerosol optical depth (AODf) in China

Analyzing the distribution and causes of fine mode aerosol optical depth (AODf) is important for assessing the impact of air pollution on human health and sustainable development. Based on remote sensing data and station information, the study uses Theil Sen's method and the Mann-Kendall test to analyze the spatio-temporal distribution and trends of AODf. Meanwhile, the study used the Extreme Gradient Boosting (XGBoost) model and the Shapley Additive Explanations (SHAP) algorithm to analyze the spatial drivers of AODf and interactive effects. The results show a trend of an initial increase followed by a decline in AODf across China and in most city clusters, with AODf peaking around 2011. Areas with high AODf are mainly concentrated in the eastern and central regions. On a seasonal scale, the average AODf is highest in summer (0.25), followed by winter (0.23), autumn (0.21), and spring (0.19). The AODf, mainly in the eastern and central regions, showed rapid increases and decreases in the 2000–2013 and 2013–2020 periods, respectively. Secondly, the most important factor influencing AODf is sulfate (SO4), contributing 54.84%. This is followed by elevation (DEM) at 10.31%. The SO4, organic carbon (OC), and DEM to AODf are 20–54%, 10–44%, and 11–45% respectively at the city cluster level. Lastly, the response thresholds of AODf to the main factors show significant spatial heterogeneity. The thresholds for SO4 and OC to increase AODf are in the range of 5–16 μg/m3 and 1–10 μg/m3, respectively. The study is of great importance for a comprehensive understanding of the variation patterns of AODf and for the formulation of tailored air pollution control policies based on local conditions.

Spatio-Temporal Evolution of Ecological Environment Quality Based on High-Quality Time-Series Data Reconstruction: A Case Study in the Sanjiangyuan Nature Reserve of China

The Sanjiangyuan Nature Reserve of China (SNRC) is recognized as one of the most fragile and sensitive terrestrial ecosystems in China, posing challenges for obtaining reliable and complete Moderate Resolution Imaging Spectro Radiometer (MODIS) data for ecological environment quality (EEQ) monitoring due to adverse factors like clouds and snow. In this study, a complete high-quality framework for MODIS time-series data reconstruction was constructed utilizing the Google Earth Engine (GEE) cloud platform. The reconstructed images were used to compute the Remote Sensing based Ecological Index (RSEI) on a monthly scale in the SNRC from 2001 to 2020. The results were as follows: The EEQ of the study area exhibited a “first fluctuating decline, then significant improvement” trend, with the RSEI values increasing at a rate of 0.84%/a. The spatial pattern of the EEQ displayed significant spatial heterogeneity, characterized by a “low in the west and high in the east” distribution. The spatial distribution pattern of the RSEI exhibited significant clustering characteristics. From 2001 to 2020, the proportion of “high–high” clustering areas exceeded 35%, and the proportion of “low–low” clustering areas exceeded 30%. Poor ecological conditions are mainly associated with population agglomerations, cultivated land, unutilized land, and bare ground, while grasslands and forests have higher RSEI values. The result of the trend analysis revealed a significant trend in RSEI change, with 62.96% of the area significantly improved and 6.31% significantly degraded. The Hurst Index (HI) results indicated that the future trend of the RSEI is predominantly anti-persistence. The proportion of areas where the EEQ is expected to continue improving in the future is 33.74%, whereas 21.21% of the area is forecasted to transition from improvement to degradation. The results showed that the high-quality framework for MODIS time-series data reconstruction enables the effective continuous monitoring of EEQ over long periods and large areas, providing robust scientific support for long time-series data reconstruction research.

Predicting Land Use Changes under Shared Socioeconomic Pathway–Representative Concentration Pathway Scenarios to Support Sustainable Planning in High-Density Urban Areas: A Case Study of Hangzhou, Southeastern China

Amidst the challenges posed by global climate change and accelerated urbanization, the structure and distribution of land use are shifting dramatically, exacerbating ecological and land-use conflicts, particularly in China. Effective land resource management requires accurate forecasts of land use and cover change (LUCC). However, the future trajectory of LUCC, influenced by climate change and urbanization, remains uncertain. This study developed an integrated multi-scenario framework by combining system dynamics and patch-generating land use simulation models to predict future LUCC in high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration Pathway (RCP) scenarios. The results showed the following: (1) From 2020 to 2050, cultivated land, unused land, and water are projected to decrease, while construction land is expected to increase. (2) Future land use patterns exhibit significant spatial heterogeneity across three scenarios. Construction land will expand in all districts of Hangzhou, particularly in the main urban areas. Under the SSP585 scenario, the expansion of construction land is most significant, while it is the least under the SSP126 scenario. (3) Distinct factors drive the expansion of different land use types. The digital elevation model is the predominant factor for the expansion of forest and grassland, contributing 19.25% and 30.76%, respectively. Night light contributes the most to cultivated land and construction land, at 13.94% and 20.35%, respectively. (4) The average land use intensity (LUI) in central urban districts markedly surpasses that in the surrounding suburban areas, with Xiacheng having the highest LUI and Chun’an the lowest. Under the SSP126 scenario, the area with increased LUI is significantly smaller than under the SSP245 and SSP585 scenarios. These findings offer valuable guidance for sustainable planning and built environment management in Hangzhou and similarly situated urban centers worldwide.

Spatiotemporal evolution of carbon emissions and influencing factors in county-level based on nighttime lighting data: a case study in Huaihai economic zone core city

ABSTRACT Driven by China’s carbon peaking and carbon neutrality goals, this study constructs a carbon emission inversion model for 57 county-level in the core city cluster of the Huaihai Economic Zone. It analyzes the spatial-temporal characteristics of carbon emissions in these counties between 2001 and 2021. It also explores the impacts of different socio-economic factors on carbon emissions by adopting geographically and temporally weighted regression methods. The results showed that: (1) From 2001 to 2021, the total carbon emissions of counties increased from 63.42 Mt to 279.89 Mt, and the distribution pattern of the region is “high in the middle and low in the east and west.” (2) Carbon emissions have significant positive spatial correlations, with the global Moran’s I index showing a wave-like downward trend from 0.233 to 0.0954, indicating that the spatial concentration of carbon emissions in different counties is gradually decreasing, and the differences show a trend of narrowing. (3) Significant spatial and temporal heterogeneity is among the influencing factors. It is mainly manifested in population size and industrial structure, while economic scale and technological progress are the dominant factors in carbon emissions. The research results will inform county-level low-carbon development.

Assessing land-use changes and carbon storage: a case study of the Jialing River Basin, China

Land-use change is the main driver of carbon storage change in terrestrial ecosystems. Currently, domestic and international studies mainly focus on the impact of carbon storage changes on climate, while studies on the impact of land-use changes on carbon storage in complex terrestrial ecosystems are few. The Jialing River Basin (JRB), with a total area of ~ 160,000 km2, diverse topography, and elevation differences exceeding 5 km, is an ideal case for understanding the complex interactions between land-use change and carbon storage dynamics. Taking the JRB as our study area, we analyzed land-use changes from 2000 to 2020. Subsequently, we simulated land-use patterns for business-as-usual (BAU), cropland protection (CP), and ecological priority (EP) scenarios in 2035 using the PLUS model. Additionally, we assessed carbon storage using the InVEST model. This approach helps us to accurately understand the carbon change processes in regional complex terrestrial ecosystems and to formulate scientifically informed land-use policies. The results revealed the following: (1) Cropland was the most dominant land-use type (LUT) in the region, and it was the only LUT experiencing net reduction, with 92.22% of newly designated construction land originating from cropland. (2) In the JRB, total carbon storage steadily decreased after 2005, with significant spatial heterogeneity. This pattern was marked by higher carbon storage levels in the north and lower levels in the south, with a distinct demarcation line. The conversion of cropland to construction land is the main factor driving the reduction in carbon storage. (3) Compared with the BAU and EP scenarios, the CP scenario demonstrated a smaller reduction in cropland area, a smaller addition to construction land area, and a lower depletion in the JRB total carbon storage from 2020 to 2035. This study demonstrates the effectiveness of the PLUS and InVEST models in analyzing complex ecosystems and offers data support for quantitatively assessing regional ecosystem services. Strict adherence to the cropland replenishment task mandated by the Chinese government is crucial to increase cropland areas in the JRB and consequently enhance the carbon sequestration capacity of its ecosystem. Such efforts are vital for ensuring the food and ecological security of the JRB, particularly in the pursuit of the “dual-carbon” objective.

Exploring gender norms in Neolithic Northern China: A GIS analysis of the Jiangzhai site

This study employs Geographic Information Systems (GIS) techniques to analyze the Jiangzhai site, a significant Neolithic settlement in northern China. Our aim is to challenge existing biases in gender interpretations of this and similar sites. By examining the distribution of various types of burial goods across different areas of the cemetery, we reveal significant spatial heterogeneity, indicating that mortuary practices at Jiangzhai should not be considered a unified entity. Our findings highlight no universal correlation between gender and grave good distribution: various types of goods are present in both male and female graves. However, in certain areas of the cemetery, specific types of production tools exhibit clear gender preferences. This suggests that gender roles within the Jiangzhai community were flexible and gender was not the central aspect of funerary practices. At Jiangzhai, gender and gender norms were intertwined with other aspects of funerary practices and social identity, influenced by economic structural differences between households. We call for more case studies based on new methods and encourage scholars to continue critically examining past gender narratives.

Temporal and Spatial Variability of Ground Frost Indices in Northeast China

Frost is one of the most frequent, intense, and influential agrometeorological disasters that occurs frequently in Northeast China. The study of the spatiotemporal changes of ground frost is of great significance for farmers and policymakers in Northeast China, as it can inform decisions related to crop selection, planting schedules, and the development of regional climate adaptation plans. In this study, the spatiotemporal changes of frost indices (last spring frost (LSF), first fall frost (FFF), and frost-free period (FFP)) in Northeast China were analyzed from 1961 to 2020. Then, we investigated the mutation characteristics of the frost indices and their correlation with geographical factors. The results revealed that (1) the LSF, FFF, and FFP in Northeast China were concentrated at 120–140 DOY, 260–280 DOY, and 110–170 days, respectively. The spatial distribution of frost indices exhibited significant spatial heterogeneity. (2) The LSF, FFF, and FFP showed significant trends of advancement, delay, and extension, with trends of −1.94 days/10 a, 1.72 days/10 a, and 4.21 days/10 a, respectively. (3) More than 80% of the LSF, FFF, and FFP of the sites showed trends of advancement, delay, and extension, with greater variability in the central part of Heilongjiang Province. (4) The FFF and FFP experienced an abrupt change in the late 1990s. (5) The correlation between latitude and LSF, FFF, and FFP was the strongest, with correlation coefficients of 0.77, −0.79, and −0.78, respectively. This study provides a comprehensive understanding of the changing characteristics of ground frost indices that impact agricultural production in Northeast China against the backdrop of climate change. The findings hold significant scientific value in guiding the adaptation of agricultural production layouts in Northeast China to the evolving climatic conditions.

Particle-ozone complex pollution under diverse synoptic weather patterns in the Yangtze River Delta region: Synergistic relationships and the effects of meteorology and chemical compositions

There is considerable academic interest in the particle-ozone synergistic relationship (PO) between fine particulate matter (PM2.5) and ozone (O3). Using various synoptic weather patterns (SWPs), we quantitatively assessed the variations in the PO, which is relevant to formulating policies aimed at controlling complex pollution in the air. First, based on one-year sampling data from March 2018 to February 2019, the SWPs classification of the Yangtze River Delta (YRD) was conducted using the sum-of-squares technique (SS). Five dominant SWPs can be found in the YRD region, including the Aleutian low under SWP1 (occurring 45 % of the year), a tropical cyclone under SWP2 (21 %), the tropical cyclone and western Pacific Subtropical High (WPSH) under SWP3 (15.4 %), the WPSH under SWP4 (6.9 %), and a continental high pressure under SWP5 (3.1 %). The phenomenon of a “seesaw” between PM2.5 and O3 concentrations exhibited significant spatial heterogeneity, which was influenced by meteorological mechanisms. Second, the multi-linear regression (MLR) model and the partial correlation (PCOR) analysis were employed to quantify the effects of dominant components and meteorological factors on the PO. Meteorological variables could collectively explain only 33.0 % of the PM2.5 variations, but 58.0 % for O3. O3 promoted each other with low concentrations of PM2.5 but was inhibited by high concentrations of PM2.5. High relative humidity (RH) was conducive to the generation of PM2.5 secondary components and enhanced the radiative effects of aerosols and the negative correlation of PO. In addition, attention should be paid to assessing the combined effects of precursor levels, weather, and chemical reactions on the particle-ozone complex pollution. The control of O3 pollutants should be intensified in summer, while the focus should be on reducing PM2.5 pollutants in winter. Prevention and control measures need to reflect the differences in weather conditions and pollution characteristics, with a focus on RH and secondary components of PM2.5.

Vegetation response to large-scale mountain excavation and city construction projects on the Loess Plateau of China

Since 2012, the “Mountain Excavation and City Construction” (MECC) project has been implemented extensively on the Loess Plateau of China, transforming gullies into flat land for urban sprawl by leveling loess hilltops to fill in valleys. However, this unprecedented human activity has caused widespread controversy over its unknown potential ecological impacts. Quantitative assessment of the impacts of the MECC project on the vegetation is key to ecological management and restoration. Taking the largest MECC project area on the Loess Plateau, Yan'an New District (YND), as the study area, this study investigated the spatiotemporal pattern of vegetation dynamics before and after the implementation of the MECC project using a multitemporal normalized difference vegetation index (NDVI) time series from 2009 to 2023 and explored the response of vegetation dynamics to the large-scale MECC project. The results showed that the vegetation dynamics in the YND exhibited significant spatial and temporal heterogeneity due to the MECC project, with the vegetation in the project-affected areas showing rapid damage followed by slow recovery. Vegetation damage occurred only in the project-affected area, and 84 % of these areas began recovery within 10 years, indicating the limited impact of the large-scale MECC project on the regional vegetation. The strong correlation between vegetation dynamics and the MECC project suggested that the destruction and recovery of vegetation in the project-affected areas was mainly under anthropogenic control, which highlights the importance of targeted ecological policies. Specifically, the MECC project induced local anthropogenic damage to the plant population structure during the land creation period, but regeneration and rational allocation of the vegetation were achieved through urbanization, gradually forming a new balanced ecological environment. These findings will contribute to a full understanding of the response of vegetation to such large-scale engineering activities and help local governments adopt projects or policies that facilitate vegetation recovery.

Quantifying and spatializing the island landsenses ecological condition using a two-dimensional model

Achieving the harmonious development of the “social-ecological” system is a crucial aspect of the global sustainable development goals. Landsenses ecology is an emerging concept that emphasizes sustainable land use planning and comprehensive management. Islands serve as ideal study areas setting for studying the landsenses ecology due to their vulnerability as ecosystems exposed to significant human activities. To assess the condition and spatial distribution of landsenses ecology, we established a quantitative evaluation framework that encompassed eight factors across two perceptions - physical and psychological. Our study focused on two islands situated in southeast China, which, despite their proximity, demonstrate remarkable differences in terms of natural and economic characteristics. The results revealed a significant spatial heterogeneity in the landsenses ecological condition on both islands. Nan'ao island (NAI) exhibited higher values for physical (0.5) and psychological (0.243) perceptions compared to Dongshan island (DSI), which was primarily attributed to varying natural environments and topographic factors. Notably, elevation and slope demonstrated strong correlations with landsenses ecological condition, acting as critical determinants of island development. Finally, using beaches as an example, we examined the impact of landsenses ecological conditions about the tourist resources of the islands. This study contributes to the development of scientifically informed urban and tourism planning processes by providing decision-makers with valuable insights.

Spatial pattern and attribution of ecosystem drought recovery in China

Under the backdrop of global climate change, frequent drought events pose a severe and persistent threat to the normal functioning of ecosystems. Drought recovery time, the time it takes for an ecosystem to return to its pre-drought state, is a crucial metric for drought impact and ecosystem stability. However, most previous studies have focused on the drought recovery time of the region as a whole or a specific type of ecosystem. The differences in drought recovery time among different ecosystems and their driving factors are largely unknown. Therefore, this study utilizes multi-source fused Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) data and Gross primary productivity (GPP) data to construct drought and ecosystem indicators. Subsequently, the drought recovery time under different climates and ecosystem types in China from 2002 to 2017 is analyzed. Finally, the factors influencing the differences in drought recovery time among ecosystems are discussed in detail. The results indicate that there is significant spatial heterogeneity in drought recovery time among ecosystems in China, with the forest ecosystems in the Northeast and Southwest regions having the longest recovery time. The recovery time of forest ecosystems (4.32 months) is longer than that of cropland (4.07 months) and grassland (3.79 months) ecosystems, but there are also significant differences in the recovery time for the same ecosystems under different climate types. The differences in drought recovery time among different ecosystem types are primarily influenced by temperature and precipitation during drought recovery, and the response of ecosystems to drought. These results provide scientific support for adopting differentiated management strategies for different ecosystem types to cope with future climate change.

Plant-level green transformation strategy in China's cement industry: Considering energy conservation and emission reduction co-benefits

The green transformation strategy is critical for achieving the emission mitigation targets in China's cement study. However, previous studies have focused on the nationwide industry level and overlooked the significant differences in the cement plants, remaining the risk of difficulties in implementing the proposed strategy. To overcome this problem, this study proposes a framework for plant-level green transformation strategy based on the industry-level emission mitigation pathway and a plant-level cement database. The strategy indicates the cement plants that need to be shut down, be retrofitted, and promote technologies. Results show that 1005 clinker and 3706 cement production plants should be shut down or retrofitted, while 60%+ of the plants should take denitrification and dust removal technologies in 2019–2035. The plant-level strategy can achieve energy conservation and CO2, SO2, NOx, and PM reductions by 40.0–79.9%, demonstrating the existence of the co-benefits. As only 4.1%–25.0% of the plants contribute half of the energy conservation and emission reduction effects, the plant-level strategy leads to significant spatial heterogeneity of the co-benefits. For example, the energy conservation and emission reduction potential in the five largest cement producer cities varies from over 30%. In addition, the total fixed investment is 99.6 billion Chinese Yuan (CNY) and the highest cost is 12.8 billion CNY/a, which will not cause heavy economic burdens to the industry. This study bridges the industrial-level planning and plant-level implementation of the green transformation strategy, whose methodology supports the synergic energy conservation and emission reduction in China's cement industry and beyond.

Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay

Urban areas contribute to over 80% of carbon dioxide emissions, and considerable efforts are being undertaken to characterize spatiotemporal variations of CO2 (carbon dioxide) at a city, regional, and national level, aiming at providing pipelines for carbon mission reduction. The complex underlying surface composition of urban areas makes process-based and physiology-based models inadequate for simulating carbon flux in this context. In this study, long short-term memory (LSTM), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) were employed to develop and investigate their viability in estimating carbon flux at the ecosystem level. All the data used in our study were derived from the long-term chronosequence observations collected from the flux towers within urban complex underlying surface, along with meteorological reanalysis datasets. To assess the generalization ability of these models, the following statistical metrics were utilized: coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). Our analysis revealed that the RF model performed the best in simulating carbon flux over long time series, with the highest R2 values reaching up to 0.852, and exhibiting the smallest RMSE and MAE values at 0.293 μmol·m−2·s−1 and 0.157 μmol·m−2·s−1. As a result, the RF model was chosen for simulating carbon flux at spatial scale and assessing the impact of urban impervious surfaces in the simulation. The results showed that the RF model performs well in simulating carbon flux at the spatial scale. The input of impervious surface area index can improve the performance of the RF model in simulating carbon flux, with R2 values of 84.46% (with the impervious surface area index in) and 83.74% (without the impervious surface area index in). Furthermore, the carbon flux in Fengxian District, Shanghai, exhibited significant spatial heterogeneity: the CO2 flux in the western part of Fengxian District was less than in the eastern part, and the CO2 flux gradually increased from the west to the east. In addition, we creatively introduced the diurnal impervious surface area index based on the Kljun model, and clarified the influence of impervious surface on the spatiotemporal simulation of CO2 flux over the complex urban underlying surface. Based on these findings, we conclude that the RF models can be effectively applied for estimating carbon flux on the complex underlying urban surface. The results of our study reduce the uncertainty in modeling carbon cycling in terrestrial ecosystems, and make the variety of models for the carbon cycling of terrestrial ecosystems more diverse.

Exploring the spatial-temporal evolution characteristics of extreme heat events and driving factors in seven geographic regions of China (1980–2021)

Extreme heat events in China are occurring more frequently due to global warming. However, there is a lack of comprehensive studies analyzing the movement direction and factor interaction of extreme heat events in different regions of China. Based on daily temperature data from 2252 meteorological stations in China from 1980 to 2021, three extreme heat indicators were calculated: Hot days (SU35), Tropical nights (TR20), and Extreme maximum temperature (TXx). The study updated and compared the characteristics of spatiotemporal evolution and driving factors of extreme heat events in China and its seven geographical regions.The results show that: (1) SU35 and TR20 increase faster in summer, while TXx increases faster in winter. Nighttime high-temperature events have increased at a faster rate. (2) Extreme heat events in North, Northeast, and Northwest China have gradually moved southward and eastward, while in Central, East, and South China, such events have moved northward. (3) In northeast and northwest China, the Atlantic Multi-decadal Oscillation (AMO) is a strong driving force for extreme heat events, while urbanization is the most potent driving force in the remaining regions. The interaction between urbanization and atmospheric circulation, including AMO, Pacific Decadal Oscillation (PDO), and East Atlantic/West Russia (EA/WR), is non-linear or double factor enhancement and exhibits significant spatial heterogeneity. These results will be significant for urban adaptation to climate change and sustainable development.

Revealing bovine schistosomiasis in Malawi: Connecting human and hybrid schistosomes within cattle

In Malawi, the putative origin of a newly described Schistosoma haematobium-mattheei hybrid human schistosome was assessed upon a seminal molecular parasitological survey of cattle. Using miracidia hatch test (MHT) and carcass inspection at slaughter, mean prevalence of bovine schistosomiasis was 49.1% (95% CI: 43.7–54.6%) and 10.3% (95% CI: 6.0–16.2%) respectively, though significant spatial heterogeneity was noted. Approximately 2.0% of infected cattle, and only those from Mangochi District, shed S. haematobium-mattheei and/or S. haematobium in faeces. To quantify schistosome (re)infection dynamics, where a S. haematobium-mattheei hybrid was present, we undertook a novel pilot GPS-datalogging sub-study within a specific herd of cattle (n = 8) on the Lake Malawi shoreline, alongside a praziquantel (40 mg/kg) treatment efficacy spot check. At sub-study baseline, all GPS-tagged cattle had proven daily water contact with the lake. Each animal was patently infected upon MHT, with older animals shedding less miracidia. At one month review, whilst parasitological cure was 100.0%, from six weeks onwards, (re)infection was first noted in the youngest animal. By three-month review, all animals were patently (re)infected though only miracidia of S. mattheei were recovered, albeit in much lower numbers. To conclude, infection with S. mattheei is particularly common in cattle and demonstrates a previously cryptic burden of bovine schistosomiasis. Within Mangochi District, bovine transmission of both S. haematobium-mattheei hybrids and S. haematobium are now incriminated, with unequivocal evidence of contemporary zoonotic spill-over. Future control of urogenital schistosomiasis here in the southern region needs to develop, then successfully integrate, a One Health approach with appropriate mitigating strategies to reduce and/or contain bovine schistosomiasis transmission.