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The high land surface temperature (LST) and fine particulate matter (PM 2.5) pose significant threats to urban ecological environment. LST and PM 2.5 are closely related, and land use/cover change (LUCC) has a significant influence on them. However, there is a lack of multi-scale analysis of their relationship under the background of LUCC. Therefore, this study designed a multi-scale analysis framework, adopted the Pearson correlation analysis, bivariate Moran's I and coupling coordination degree (D) to examine the relationship between LST and PM 2.5 in different land use types based on remote sensing data, and analyzed the influencing factors by Geodetector. The results showed that LST and PM 2.5 have a positive correlation, and their correlation would decrease with the research scale expansion, with the absolute values of Moran's I ranging from 0.229 to 0.577, 0.415–0.754 and 0.551–0.852 at national, urban agglomeration and city scales, respectively. LST, PM 2.5 and their correlation were lower in forest and water at the three scales, while they were the highest in construction land, and the difference in D values was about 0.3. Furthermore, the normalized difference vegetation index (NDVI) and construction land area played the most important role in spatial patterns of this relationship, followed by population and GDP. At last, the cost analysis of environmental pollution reduction was performed, and this study could provide support for proper public health policy-making and environmental protection in different regions. • The relationship between LST and PM 2.5 in different land use types at multi-scale was discussed. • There is a positive correlation between LST and PM 2.5 , and the interaction would decrease with the research scale expansion. • The interaction between LST and PM 2.5 was the highest in construction land, and the lowest in forest. • The influence degree of NDVI and night-time lights was higher than that of GDP and population. [ABSTRACT FROM AUTHOR]

Non-Grain Production (NGP) on cropland emerges from complex interactions of human activities and environmental changes, posing an important threat to China's national food security. Exploring the driving forces of NGP and impact patterns is crucial to improve existing cropland protection policies. This study analyzes the relationship between the change of industrial structure and NGP in the Yangtze River Economic Belt (YREB)from 2000 to 2019 by using a spatial econometric model and a threshold effect model. Through the exploration of spatiotemporal evolution, the complex relationship between the change of industrial structure and the non-grain conversion of cultivated land is revealed. The results show that the change of industrial structure in the YREB affects the transformation of cultivated land use to a certain extent, and there is an obvious spatial spillover effect. At the same time, through the application of the threshold effect model, the threshold points affecting the relationship between industrial structure change and NGP conversion are found, which guides the formulation of relevant policies. Based on the research results, policy recommendations with regional differences are put forward to promote the coordinated development of land use protection and food security. Our study has important theoretical and practical significance for in-depth understanding of sustainable development and food security in the YREB and similar regions. • The impact of industrial structure changes on the non-grain production (NGP) of cropland are explored though evidence. • There is a spatial spillover effect of industrial structure changes on NGP. • Thresholds for the impact of industrial structure on NGP at different stages of economic development are existed. • Adjustment of industrial structure is an effective means to prevent further expansion of NGP. [ABSTRACT FROM AUTHOR]

Landscape change s driven by anthropogenic activities often have negative impacts on ecosystems, jeopardizing the provision of vital services that sustain biotic elements and wildlife. Predicting the effects of such transformations is crucial for developing strategies to mitigate ecological damage. This study explores the interaction of land use changes and habitat quality estimates in the Upper Paraguay River Basin in Brazil, using the InVEST Habitat Quality model to estimate spatiotemporal landscape trends and evaluate the potential impact of land use policies for the future. Under a business-as-usual scenario by 2050, potential land use changes are simulated for shaping habitat quality, habitat degradation, and habitat rarity estimates as landscape proxies for biodiversity conservation. Results show an extensive expansion of pastures through deforestation, leading to progressive habitat degradation with a significant decay in the predicted and observed habitat quality. The habitat quality index estimates show a spatial decrease from 0.78 to 0.57 for the 1989–2050 period. The same trend is observed in protected areas for the period 2019–2050, with an increase of anthropogenic land use and a decrease of the habitat quality from 0.80 to 0.57 in conservation units, and from 0.75 to 0.53 in indigenous lands. For improved conservation outcomes, this work introduces new insights for shaping environmental actions that can be flagged as sustainable land management practices and ecological perspectives towards spatial pressures at different scales. Therefore, government institutions responsible for the protection of conservation units and indigenous communities can be informed about potential land use impacts on their territories. The findings suggest that incorporating additional scenario trends and climate-related variables could be a valuable direction for future studies to extend further the modelling approaches explored in this work. • Landscape changes threaten biodiversity in Brazil's Upper Paraguay River Basin. • Habitat quality is projected to sharply decline by 2050. • Protected areas are predicted to lose 20% of natural land cover under a BAU scenario. • Conservation units and indigenous lands face high-risk from anthropogenic pressures. • A shift to sustainable and innovative agro-pastoral practices is suggested. [ABSTRACT FROM AUTHOR]

It is essential for sustainable development worldwide to reduce carbon emissions (CE), however, how land use patterns in coal resource-based regions (CRBRs) affect CE remains less explored. Based on socioeconomic data and GlobeLand30, this study evaluated and predicted the influence of land use patterns on CE in Shanxi Province from 2000 to 2030. The key findings are as follows: (1) From 2000 to 2020, the area of cropland in the study area decreased by 4.85 × 105 ha and the area of construction land increased by 4.38 × 105 ha, with the increase in construction land coming mainly from cropland. (2) There was an increasing trend in the overall net CE, from 3.17 × 107 t in 2000 to 3.89 × 107 t in 2010 and 6.38 × 107 t in 2020. The land use CE had a spatial distribution characteristic of being high in the west and south and low in the east and north. The total CE was the largest in 2030 in business-as-usual scenario (BAUs), and the CE class of the cities in the study area was mainly high CE, while the ecological and economic balance scenario (EEBs) was higher CE. In 2030, the BAUs will have the largest total CE, and the CE levels of the cities will mainly high CE. (3) The decoupling state between the land use mix degree (LUM) and CE in the study area was mainly an expansionary negative decoupling over the past 20 years and changed from long negative decoupling to weak decoupling in the economic development priority scenario (EDPs) and strong decoupling in EEBs, which might be better suited to the future development of Shanxi Province. This study makes it easier to comprehend how different land use patterns affect the number of CE in CRBRs. Additionally, it provides other CRBRs with a theoretical framework and instances needed to research CE. [Display omitted] • Using MOP-PLUS model and Tapio decoupling analysis method. • Carbon emissions are higher in the south and west, and lower in the north and east. • The transition of decoupling states vary in different scenarios. • The ecological and economic balance scenario (EEBs) is the most suitable model. • A reference for other coal resource-based regions. [ABSTRACT FROM AUTHOR]

Under the dual impacts of global environmental degradation and human activities, ecosystem service functions have steadily declined. Ecological compensation has emerged as an important direct and efficient motivator for countries to implement ecosystem protection and restoration. At present, few studies have considered ways in which to establish ecological compensation mechanisms or have analyze the related influencing factors. The ecological compensation threshold is in the conceptual analysis stage; thus, quantitative simulation studies are lacking. In this study, the relationship between water conservation and ecological compensation was analyzed. Scenario simulation and the minimum data method were combined to establish an ecological compensation mechanism for the upper Yangtze River (UYR) basin, and the ecological compensation thresholds were quantitatively assessed. Finally, the factors influencing ecological compensation and the interactions among the factors were analyzed using an optimal parameters-based geographical detector. The results showed that (1) the different land use scenarios for the UYR resulted in notable water conservation differences, with greater differences under the fallow-to-forest scenario than under the fallow-to-grass scenario and existing scenario. (2) Furthermore, 27 subbasins were suitable for the implementation of the fallow-to-forest scenario, with an average ecological compensation threshold of 46.48 yuan/m3 and an average new water conservation amount of 22.02 × 108 m3; and 21 subbasins were suitable for the implementation of the fallow-to-grass scenario, with an average ecological compensation threshold of 107.87 yuan/m3 and an average new water conservation amount of 3.72 × 108 m3. (3) The drivers with the highest and lowest impacts on the ecological compensation thresholds were the grain yield and NDVI, respectively, while their impacts on ecological compensation were significantly enhanced by interactions among the influencing factors. In this study, the differences in ecological compensation standards were compared at the basin scale and administrative scale in different regions worldwide. Moreover, the need to establish a basin-scale ecological compensation mechanism as an effective reference for promoting the implementation and development of ecological compensation policies was explored. [Display omitted] • Coupling of land use conversion scenarios with water conservation was explored. • Thresholds for ecological compensation at the basin scale were identified. • Mechanisms affecting ecological compensation at the basin scale were constructed. • Implementation of ecological compensation measures at the basin scale is essential. [ABSTRACT FROM AUTHOR]

Urban areas are undergoing rapid expansion, resulting in diminished vegetation cover and an escalating urban flood problem, and posing substantial threats to aquatic ecosystems, human safety, and socioeconomic structures. However, research on urban flood risk using methods like the Analytic Hierarchy Process (AHP), further exploration of spatiotemporal variations is needed, especially within the context of karst mountainous urban clusters. This study focuses on Guiyang city within a karst mountainous urban cluster, investigating fractional vegetation cover (FVC), infiltration capacity, and urban flood risk. Methodologies encompass slope trend analysis, the utilization of the Google Earth Engine, and geographic detectors to assess the dynamics of FVC and infiltration capacity. AHP is employed to assign weights to infiltration capacity, land use and land cover (LULC), FVC, and elevation, culminating in the generation of flood risk maps through linear weighted overlay. The results showed that: (1) The average FVC in Guiyang City was 0.7440 in 21 years, with relatively low levels in the central and southern regions. The FVC increased by 0.21% per year from 2000 to 2020, driven mainly by land use change and human activities. (2) The infiltration capacity of the city of Guiyang has increased as a whole, mainly due to reforestation efforts in specific areas, while the infiltration capacity of impervious areas tends to decrease. (3) The central urban areas exhibit greater vulnerability, with an estimated ten-year average growth rate of 73.36% in very high flood risk areas by 2030, affecting 7.38% of Guiyang's total area. These urban flood risk maps serve as valuable tools for local governments to enhance urban management practices. • Urban growth and a notable decrease in vegetation cover, particularly in high-density areas. • Afforestation efforts have led to improved infiltration capacity in certain areas. • Central urban regions as more vulnerable to urban flooding, projecting a significant growth in high-risk zones. [ABSTRACT FROM AUTHOR]

The changing land use is one of the primary factors influencing the pattern of carbon sources/sinks, while climate change is a major driver for land use change. With global warming increasing, assessing the impact of climate extremes on land use carbon emissions remains a great challenge. Here, we explored the changes in climate extremes from 1961 to 2020 using the CN05.1 gridded observation dataset. The impact of climate extremes on land use carbon emissions was analyzed by Pearson correlation methodology. The results demonstrated that (1) extreme temperatures were trending upwards, and dry periods were long, but short periods of heavy precipitation were possible from 1961 to 2020. (2) In terms of the extreme temperature indices, the high temperatures indices were positively correlated with land use carbon emissions. For the extreme precipitation indices, the other seven indices except CDD were also positively correlated with land use carbon emissions. (3) Furthermore, the extreme heat indices were positively correlated with land use carbon emissions mainly on construction land. The wetness indices showed a positive correlation with land use carbon emissions in the middle of Shandong Province. (4) Additionally, the influence of extreme temperatures on land use carbon emissions in Shandong Province was larger than of extreme precipitation. Among all the extreme climate indices, TN10p had the largest effect on land use carbon emissions and was significantly negatively correlated. These findings will provide scientific references for regional responses to climate change and the promotion of carbon emission reduction. • The impact of extreme temperatures on LUCE is larger than of extreme precipitation. • TN10p has the largest effect on LUCE and was significantly negatively correlated. • The extreme heat indices are positively correlated with land use carbon emissions mainly on construction land. • The wetness indices show a positive correlation with land use carbon emissions in the middle of Shandong Province. [ABSTRACT FROM AUTHOR]

The rapid urbanization and frequent occurrence of extreme weather have made flooding more frequent; tide-sensitive areas are more prone to flooding due to tide level. However, the extent of their respective impacts on flood variability in the context of the combined effects remains to be explored. Therefore, analysis of the driveability of the water level is important for regional flood control. Land use data from 1985 to 2015 was used in this study to analyze the characteristics of the changes. General trends, abrupt variability, and persistence of rainfall, tide, and water level data from 1957 to 2018 were analyzed. The influence of rainfall, tide level factors and underlying surface on water level variation was analyzed qualitatively and the contribution of the three factors to water level variation was quantified. The results indicate that the most important directions of land-type transformation were the construction land and arable land. Within the rainfall sequence, only the 3d rainfall sequence exhibited a significant increasing trend, while both tide level and water levels showed significant increasing trends. The 3d rainfall sequence and tide level sequence are significantly positively correlated with water level sequences, whereas among the underlying surface factors, only construction land and unused land are significantly positively correlated with water levels. Furthermore, the contribution rates of driving factors vary across different regions. In the Changzhou region, the underlying surface factors dominated with a relative influence of 62%., whereas for other regions, the combined relative influences of rainfall and tide level are 57.2%, 52.8%, 60.4%, and 66.9%, The methods and results of this study contribute to regional flood regulation. • The main directions of conversion of land type are construction land and arable land. • Rainfall and tide level are positively correlated with water level in an upward trend. • The rainfall and tide level factors are the dominant factors influencing the rise in water level. • The net effect of human activities on changes in water level is actually not very strong. [ABSTRACT FROM AUTHOR]

Clarifying the marginal effects of dominant factors influencing ecosystem services in different land use policy zones and the resulting changes in trade-offs and synergies within ecosystem services is an essential prerequisite for the sophisticated management of ecosystem services. Moreover, it is a crucial requirement for achieving the sustained provision of ecosystem services and sustainable human development. This study quantified spatial and temporal changes of ecosystem services in different land use policy zones of Shaanxi, assessed the marginal effects of drivers using the random forest, and explained the relationships within ecosystem services by the geographically weighted regression model. The results showed that water yield (WY) increased in the Economic Development Zone, food Production (FP), water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ) improved in the Ecological Enhancement Zone and Ecological Restoration Zone. In contrast, water yield (WY) and soil conservation (SC) in the Ecological Conservation Zone decreased from 2000 to 2020. Changes in the dominant factors in different policy zones affected ecosystem services in a non-stationary manner. For example, the initial increase in construction land ratio would lead to complex and dramatic effects on multiple ecosystem services. Differences in the most significant factors and their respective marginal effects led to disparities in transformations of trade-offs and synergies between ecosystem services in different land use policy zones. The area of trade-offs between water yield (WY) and carbon storage (CS) decreased by 1.67% in the Ecological Conservation Zone, while it increased by 1.53% in the Ecological Restoration Zone. This study could provide theoretical guidance for different policy zones to optimize ecological management policies, coordinate human-earth relations, and achieve sustainable development. [Display omitted] • The random forest can effectively assesses the marginal effects of drivers. • Trends in ecosystem services (ES) differently in different land-use policy zones. • Dominant factors affecting ES showed variability in different land use policy zones. • Socio-economic factors mostly have a negative impact on ES. • The trade-offs and synergies between ES do not improve with continued ecological restoration projects. [ABSTRACT FROM AUTHOR]

The prediction of future land use and land cover (LULC) change is essential for natural resource management and the development of environmental monitoring strategies, especially for a non-resilient system. Thus, a novel LULC prediction model was proposed by coupling a hybrid predictor screening approach with the Cellular Automata coupled Artificial Neural Network (CA-ANN) approach. The hybrid predictor screener was formed by integrating the outcomes of Correlation Coefficient (CC), Mutual Information (MI), and Decision Tree (DT) methods and termed as the CMD technique. The CA-ANN model was trained by LULC maps of 1995 and 2005 and tested by the map of 2020 for these four sets of variables (i.e., CC, MI, DT, and CMD). The results revealed that the CMD predictors were the most influential variables for LULC prediction, followed by the DT-based variables. In contrast, the CC-based predictors were found to be the least effective, followed by the MI variables. Thus, the CMD-CA-ANN model was established as the benchmark model in this study. The study showed that elevation and distance from roads were more critical variables for LULC prediction compared to slope and aspect parameters. The proposed model demonstrated that by 2080, there would be an increase in the area of built-up land (5.79%), cropland (4.35%), shrubland (1.62%), and water bodies (0.3%) and a decrease in the area of forested land (1.34%) and barren land (10%) in the study area. The research has the potential to significantly contribute to the identification and management of significant environmental changes. [Display omitted] [ABSTRACT FROM AUTHOR]

The rapid expansion of built-up land in China contributes to the great differences in regional development, which has impacted balanced regional development. Analysis on teleconnections of built-up land can better understand the mechanism of spatial imbalance, thus promoting the achievement of overall carbon neutrality. We attempt to quantify the degree of unbalanced regional development based on teleconnections of built-up land in China. Results reveal an increase in external dependence in developed regions, with the economic growth in these regions driving the expansion of built-up land in undeveloped regions. Undeveloped regions primarily serve as suppliers of land for the mining and manufacturing industry, while developed regions export substantial land for the service industry. There is considerable variation in the environmental-economic benefits among regions: While each province experiences economic gains from built-up land expansion, differences in land utilization efficiency contribute to a significant development gap among regions. This divergence in development levels exacerbates the unbalanced regional development in China, a trend that is currently widening. It is imperative for developed regions to assume greater responsibility in achieving carbon neutrality. This involves providing economic and technological support to undeveloped regions, fostering a more equitable and sustainable development path. [Display omitted] [ABSTRACT FROM AUTHOR]

Surface mining has been subject to increased criticism and pressure due to its potential to cause environmental damage. China accounts for more than half of world coal consumption, and this continued demand for coal, combined with low costs, has accelerated surface coal mining worldwide. However, it isn't easy to understand the impact of surface mining in China. Therefore, combined with POI, the Exposed Coal Frequency Index (ECFI) was constructed without any mining information in China. A LandTrendr algorithm was used to identify past mining disturbances and reclamation events (1986–2021). While examining these events, surface destruction due to coal mining in China was revealed. Based on the results, (1) the detection accuracy of statistical surface mining sites by province reaches 91.8%, while the detection accuracy of disturbance and reclamation events exceeds 72.59 %. Also, by comparing the mine data, our results provide more accurate information regarding both time and spatial consistency. (2) 253.61 km2 of surface mining sites were identified in 14 provinces or autonomous regions during 1986–2021. Of these, Inner Mongolia, Ningxia, Shanxi and Xinjiang ranked in the top four occupying 89.0% of the total mining site. (3) China has cumulatively disturbed 545.84 km2 and reclaimed 169.41 km2 including more comprehensive human activities. In the last 12 years, large-scale mining and reclamation have accounted for 51.63% and 75.17% of the cumulative area, respectively. (4) Generally, reclamation in China can be completed within four years. In contrast, reclamation time intervals and the proportion of reclamation varied widely between mining areas. Clearly, this study provides the most accurate data on surface coal mining disturbances in China, which will be beneficial for future studies in spatial geography related to mining. It also includes more policies and management creation for mines. [Display omitted] [ABSTRACT FROM AUTHOR]

Efficient utilization of land resources is fundamental for achieving sustainable urban development. Utilizing the urban land use efficiency (ULUE) framework for production-living-ecological (PLE) functions, this study establishes three key indicators to evaluate the sustainable development status of each dimension. The indicator system was applied to 433 Chinese cities to analyze the temporal and spatial changes in urban sustainable development from 2000 to 2020. Research findings reveal significant disparities in sustainable urban development levels across Chinese regions from 2000 to 2020, following a consistent trend: Eastern > Western > Central > Northeast. The ULUE for living and production functions in Chinese cities experienced an obvious decline from 2015 to 2020. This indicates that urban land expansion in most Chinese cities surpassed population growth, accompanied by a noticeable reduction in economic growth rates. Since 2010, the ULUE for ecological function has improved significantly in Eastern region, reflecting a shift in development priorities towards a green approach rooted in ecological conservation principles. However, the ULUE in Northeastern cities has declined, placing this region at a competitive disadvantage due to the dual challenges of declining population and economic recession. Since 2015, urban land expansion in Central Chinese cities has significantly outpaced other regions, resulting in extensive land use, posing challenges to resource planning and management. Smaller cities, in contrast to their larger counterparts, face a lower overall sustainability level and encounter more acute challenges related to population migration and economic transition. The analysis offers valuable insights and policy recommendations to enhance sustainability in developing regions. • Efficient urban land use contributes to sustainable urban development. • Introduce an assessment indicator system for Urban Land Use Efficiency (ULUE). • Uncover spatial and temporal disparities in sustainable urban development. • Examine regional disparities in sustainable development among various Chinese cities. [ABSTRACT FROM AUTHOR]

Balancing intensive development with biodiversity conservation is critical for ecological sustainability. In the Loess Hilly-Gully region, which has experienced significant environmental changes from 1980 to 2020, land use changes are vital for ecosystem service maintenance. However, these processes are susceptible to environmental stressors such as climate change, land degradation, and inadequate land management. Despite recognizing these stressors, their combined impact on land use and ecosystem services is not well understood. This study addresses this gap by utilizing multi-model land use simulations combined with artificial intelligence to analyze changes over the four-decade period. We focused on identifying ecological nodes essential for landscape connectivity, finding that these nodes significantly enhance regional ecosystem services. We also examined the relationship between land use changes and ecosystem services under various environmental stressors within the specified timeframe. Our analysis indicates that land use changes are a strong indicator of ecosystem evolution in these areas. We observed that under natural conditions, land use and ecosystem services interactions are governed by both stochastic and deterministic factors. Interestingly, multiple stressors intensified the stochastic nature of land use changes and the deterministic aspects of ecosystem services. Specifically, climate change, coupled with suboptimal land management, significantly affects this relationship, with climate change being the most influential factor on land use patterns during the studied period. This research offers important insights for improved environmental management and reducing impacts on aquatic ecosystems amid escalating climate change threats. [Display omitted] • AI-enhanced simulations analyze Loess Hilly-Gully region's land use and ecosystem. • Key ecological nodes identified, vital for sustaining regional ecosystems. • Loess Plateau land use changes driven by stochastic and deterministic factors. • Climate and land management impact land use patterns and ecosystem interactions. • Insights on ecological sustainability link land use changes to ecosystem evolution. [ABSTRACT FROM AUTHOR]

Swamp wetlands play a pivotal role in conserving water sources, regulating river runoff, and maintaining water safety and balance. The study pioneers a new research framework in the field of pollution ecology of swamp wetlands, with a focus on the complex "source-transfer-sink" processes affecting water quality in micro swamp wetlands, an area previously under-researched. Taking the Momoge Wetland in the Songnen Plain as an example, we innovatively combined the "source-transfer-sink" theory with landscape patterns, topographic factors, and their impacts on wetland water quality. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), our research quantifies and models the relationships among various environmental factors. This approach reveals how landscape patterns influence pollutant migration and water quality at a micro-scale. Our findings suggest that a 700-m buffer zone is most effective in capturing the fluctuations in water quality in arid wetlands, which is crucial for wetland management practices. We identified the main pollution sources in the Momoge Wetland, including sediment (21.60%), vegetation (24.94%), livestock and crop-related non-point sources (41.21%), and hydrodynamic factors such as water diversion (12.25%). In pollutant migration, land use emerged as the most significant factor affecting water quality (56.64%), followed by landscape patterns (25.54%). Notably, our study finds that grasslands are essential for water purification, and a uniform distribution of landscape patches significantly improves water quality. This research marks a significant stride in understanding and optimizing landscape patterns to enhance water quality in micro swamp wetlands. The insights gained are invaluable for the protection of these ecosystems and promoting their ecological value functions, providing a reference point for future wetland conservation and management strategies. [Display omitted] • "Source-Transfer-Sink" theory explains the decline in water quality in small micro wetlands. • Revealing water quality fluctuations by combining source apportionment and landscape patterns during migration. • 700m buffer zone is optimal for controlling water quality in small micro wetlands. • Increased grassland area improves water quality in small micro wetlands. • Uniform distribution among different patches enhances water quality. [ABSTRACT FROM AUTHOR]

Green roof installations and photovoltaic (PV) systems are widely employed roof retrofits that aid cities in mitigating climate change impacts, while avoiding the need for increased land utilization. By integrating PV systems with vegetation on urban roofs, a photovoltaic-green (PV-Green) system can be achieved for multifunctional use of the roof space, thereby simultaneously achieving PV and greening benefits. However, current research solely based on one retrofit type cannot meet the requirement for assessing the multifunctional retrofit potential of urban roofs. In this study, an assessment method is proposed to identify and quantify the multiple retrofit potential of urban roofs by integrating roof attributes (slope, orientation, and area), roof type (gable or flat), solar attributes (radiation and irradiation duration), and biogeochemical simulation. Moreover, three roof retrofit scenarios, Scenario 1 (S1): maximization of PV-Green roofs, Scenario 2 (S2): maximization of PV economic benefits, and Scenario 3 (S3): maximization of public subjective well-being through roof greening, were designed to allocate the use of urban roof spaces and evaluate their respective potential power and carbon benefits at the city scale. Using Shanghai's downtown as an example, the results showed that 85,722 roofs (or 7310.86 ha) were available for multifunctional use. S1 revealed that applying PV-Green roofs can increase the additional green biomass by 0.74 × 107 kg C/yr compared to only installing PV roofs. Moreover, S1 produced the highest power output of 2.31 × 1010 kWh/yr to meet 15.4% of Shanghai's electricity demand. S2 identified 609 flat roofs and 70,527 gable roofs that were uneconomical for PV system installation. This indicated that the solar radiation received by most gable roofs was insufficient to cover the installation cost. S3 offered a biomass production of 1.48 × 107 kg C/yr and increased carbon stocks in Shanghai by 0.87%. This assessment method provides urban planners and policymakers with an analytical tool to optimize the use of urban roof spaces, thereby enhancing urban livability and sustainability. • A new assessment method to identify the multiple retrofit potential of urban roofs. • Evaluate the power and carbon benefits of roofs' retrofit scenarios in Shanghai. • PV-Green roofs can increase green biomass compared to installing PV systems only. • Most gable roofs are uneconomical for PV use due to insufficient solar radiation. • Green roofs enhance biomass production and urban carbon stocks. [ABSTRACT FROM AUTHOR]

The supply-demand balance of ecosystem services (ESs balance) is a research hotspot. Previous studies have explored spatio-temporal patterns of ESs supply, demand, and balance, but have neglected the inherent relationship between ESs balance and land use structure, which impedes the development of direct and effective land use regulatory strategies. This study assessed the balance of six ESs (i.e., timber production (TP), food production (FP), water retention (WR), carbon sequestration (CS), soil retention (SR), and habitat quality (HQ)) by the index of ecological relative surplus ratio (ERSR) at 30 m × 30 m pixel scale, and identified ESs balance bundles (ESBBs) in Lancang County, a typical mountainous region in China. It also defined the land use proportion thresholds for achieving different objectives of ESs balance, and proposed land use regulatory strategies accordingly. The results showed that: (1) From 2010 to 2020, the supply of six ESs exceeded the demand in Lancang County, and the surplus of different ESs changed over time. ESs balance also exhibited spatial heterogeneity, and ESs imbalance aggravated in some areas. Three ESBBs were divided as FP-WR-SR integrated bundle, TP–CS–HQ integrated bundle, and Integrated promotion bundle at the township scale. (2) Cropland, built-up land, and forest were the key land use types that affected the balance of the six ESs. Moreover, the land use proportion thresholds under the objectives of "ERSR ≥0″ and "ERSR ≥1″ were determined, and they differed by ES type and objective. (3) For each ESBB, ESs comprehensive management zones were delineated at the multi-scales of the township and 1 km × 1 km grid. Regulatory strategies oriented by "reducing/increasing/maintaining the proportion of certain land use types" were suggested under different objectives. This study developed a framework for "multi-level zoning management of 'county – ESs balance bundle – township – grid' for promoting ESs balance by land use structure regulation" that aligned with China's territorial spatial planning hierarchy at the county and township levels. It could inform the design of a scientific and orderly territorial spatial pattern with a high-level ESs balance at various scales (e.g., counties, agglomerations, provinces, and cities) and regions. However, this framework could not be directly applied to land use spatial optimization at pixel scale. Further research is needed to integrate land use simulation models, such as the mixed-cell cellular automata (MCCA) model, to achieve ESs balance objectives at finer scales. [Display omitted] • Ecological relative surplus ratio (ERSR) was originally constructed to spatially explicate ESs supply-demand balance. • Spatio-temporal variations in supply, demand, and balance of six ESs were analyzed from 2010 to 2020. • Three ESs balance bundles (ESBBs) were divided, and the regulated ES types and their objectives were identified. • Different land use types have varying effects on specific ESs, from significant to negligible. • Thresholds of land use proportions that can achieve two ESs balance objectives were defined, respectively. [ABSTRACT FROM AUTHOR]

The continuous change of global land use and intense human activities lead to the constant change of landscape ecological risk (LER). The increase of LER will pose a serious threat to human welfare and sustainable development. In previous studies, there were few studies on coupling coordination between land use intensity (LUI) and LER in multi-scenario simulation. Therefore, it is of a certain significance to study the coupling and coordination relationship between LUI and LER in a long-term multi-scenario simulation in the future for the sustainable use of land resources and the management of ecological risk. Based on the multi-scenario land use simulation data of China in 2010, 2050, and 2100, this study selects the comprehensive index of land use intensity, landscape pattern index, spatial autocorrelation, and coupling coordination methods to analyze the spatio-temporal characteristics of LUI and LER from 2010 to 2100, as well as the coupling coordination relationship between them. The results show that the overall LUI of China remains stable at around 200 from 2010 to 2100, with a spatial distribution that is "low in the northwest and high in the southeast." The LUI of China decreases under the balanced resources scenario and global environmental protection scenario, while the regional economic development scenario and regional environmental protection scenario exhibit an increasing trend. The overall LER in China is approximately 0.150, with a spatial distribution that is "high in the north and low in the south." The four scenarios exhibit a downward trend from 2010 to 2100. There is significant spatial dependence between LUI and LER in China, with the largest number of counties exhibiting reluctant coordination between the two (accounting for nearly 45%), while their interaction and mutual influence remain strong. Thus, this study may contribute to understanding this relationship and to creating effective landscape ecological risk management policies. [Display omitted] • There was significant spatial dependence between LUI and LER in China. • The coupling coordination degree between the LUI and LER were explored under different scenarios. • Reluctant coordinated counties occupied the dominant position. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have resulted in an excessive intensity of land use, structural imbalances, and regional ecological deterioration. To achieve sustainable development, it is essential to optimize different land use types and enhance the ecosystem service value (ESV). However, previous studies rarely combined the optimization of land use quantitative structure with the simulation of land use spatial layout under the background of maximizing economic and ecological benefits at the same time, and this kind of research was rarely applied to state-level new areas. On the premise of maximizing economic and ecological benefits, this study develops an improved optimization method that integrates the non-dominated sorting genetic algorithm II (NSGA-II) with the patch generating land use simulation (PLUS) model. The approach optimizes land use while predicting ESV for a state-level new area-Liangjiang New Area (LJNA). The model operation takes into full account ecological spatial constraints, including ecological protection red line, prime farmland, and urban development land use suitability. Results show that LJNA encountered the most substantial increase in built-up land (392.31 km2) due to farmland occupation, leading to a continuous decrease in ESV (443.6 million yuan) from 2000 to 2020. Optimization results for 2030 indicate that the main difference between different scenarios is the area of forest and built-up land. Under ecological protection priority scenario, ESV will increase in 2030 but built-up land should be confined within 620 km2. We present multiple land use scenarios based on decision makers' preferences, offering important implications for the balance and optimization of land resources under different policy priorities using coupled spatiotemporal simulation-quantitative allocation model. This study provides valuable references for future land use optimization research. • An improved multi-objective land use optimization method is developed. • The method integrates the non-dominated sorting genetic algorithm II with the patch generating land use simulation model. • The method optimizes land use while predicting ESV for the Liangjiang New Area, China. • The ecological spatial constraints are developed based on ecological protection red line, prime farmland, and urban development land use suitability. • Taking into account both ecological and economic benefit, four development scenarios are set up. [ABSTRACT FROM AUTHOR]

The traditional carbon accounting method, with a lag of over 2 years due to the release time of statistical yearbooks, impedes timely policy adjustments in urban planning and management. Hence, there is an urgent need to establish a real-time carbon emissions characterization model. Xi'an which has a complex land-use structure was chosen as the study site and its carbon emissions were calculated using the Emission Factor Method. The GIS-Kernel Density (KD) model was constructed, and land use was subdivided based on Point of Interest (POI) and road network data. Based on the results of carbon emissions accounting and land-use subdivision, a Multilayer perceptron (MLP) model was established. The remote sensing (RS) images of Xi'an underwent supervised classification, and the carbon emissions of Xi'an were characterized based on the subdivision results and MLP model. The results show that: (1) The accuracy of the characterization model is more than 90%, and with the improvement of RS technology, the accuracy will be further improved; (2) Compared with the existing model, this model can real time reflect the spatial distribution of carbon emissions; (3) Atmospheric emission of Xi'an will be 41.92 million tons at the end of 2022, a decrease of 2.80 million tons compared with that of 2020, but an increase of 0.33 million tons from 2021. The north of Xi'an and periphery of the central urban area are the main carbon sink loss areas, while the east of Xi'an and north foot of the Qinling Mountains are carbon sink growth areas. • A model that can characterize carbon emissions in real time is proposed. • Land use subdivision was considered and the accuracy of the model reached 90%. • The model can realize the spatial characterization of carbon emissions. • Xi'an, China was selected as a case to demonstrate the advantages of the model. [ABSTRACT FROM AUTHOR]

Regional carbon storage disparity between demand side and supply side is a noteworthy issue for achieving carbon neutrality. For better effective carbon budget management and ecological protection, it is imperative to clarify the mismatch patterns of carbon storage demand and supply as well as the underlying key drivers. From the perspective of ecosystem services, this study conducted in-depth analysis on the spatial mismatch and drivers of carbon storage demand and supply in the Yangtze River Economic Belt. The hot spot analysis results visually showed a distinct spatial mismatch characteristic between carbon storage service demand and supply both in 2000 and 2017. This characteristic was further quantified by a spatial mismatch index, suggesting an increasing spatial heterogeneity in the mismatch patterns. Additionally, the factor detection result from Geodetector model indicated that land use and socio-economic factors were the dominant drivers affecting the spatial mismatch patterns of carbon storage demand and supply. To determine the specific contribution of the drivers, K-means++ algorithm was used for zoning and a spatial decomposition analysis was further applied. The results suggested the county-level differences of spatial mismatch were mostly due to the between-group differences, which were primarily promoted by urban expansion and partly restrained by population agglomeration. As for the attribution analysis for the within-group differences, the drivers basically performed differently in each group. Based on these results, this study proposed to break down administrative divisions and implement hierarchical carbon budget control strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Optimizing the green use efficiency of cultivated land in the karst region of southwest China is crucial for promoting sustainable development of land resources and achieving harmony between humans and nature. Based on the epsilon-based measure model and geographically and temporally weighted regression methods, this paper investigated the spatio-temporal variation and influencing factors of cultivated land green utilization efficiency. The results indicated that: i) Cultivated land green utilization efficiency had slightly increased from 0.842 in 2000 to 0.866 in 2020. ii) The spatial pattern of cultivated land green utilization efficiency showed a significant positive correlation, with a "hotspot-not significant-coldspot" from north to south. iii) Its spatial heterogeneity had increased during the observation period, with high-efficiency areas shifting from northeast to north. iv) The proportion of agricultural economy, general public budget revenue, per unit cultivated land value had a positive impact on the cultivated land green utilization efficiency, while urbanization rate, per capita cultivated land area, land replanting index, average altitude had a negative impact. Moreover, the driving factors exhibited significant spatiotemporal heterogeneity. Therefore, it is necessary to promote technological progress and scientific research, implement funds and policies, leverage the leading role of high-efficiency areas, formulate differentiated development strategies, and thereby improve the green use efficiency of cultivated land. • Cultivated land green utilization efficiency had slightly increased. • The high-efficiency area distribution changed from northeast to due north. • The driving factors exhibited significant spatiotemporal heterogeneity. • The differentiated policies promote the effective use of cultivated land. [ABSTRACT FROM AUTHOR]

Forests and solar energy are both critical to achieving the climate goals proposed by the Paris Agreement. However, large-scale deployment of solar farms requires vast land areas, potentially posing conflicts with other land uses. For example, solar farms have been built in forested regions or with a direct cost to forests (through deforestation). Here, we evaluated land-use conflicts between forests and established solar farms worldwide, and further assessed the energy efficiency effect of placing solar farms over forests using simulation results from seven state-of-the-art Earth system models. Our results, based on remote sensing analysis, showed that 6320 solar farms (9.14%) exhibit land-use conflicts with forests, accounting for 4.9% of the total solar farm area. The capacity factor (CF) of solar farms was found to decrease with increasing forest coverage because of enhanced cloud formation and reduced solar radiation. Even though deforestation was shown to be able to increase the local CF, in deforestation areas CF was still found to be lower than over open land (cropland or grassland). Moreover, the effect of a significantly increased CF following deforestation was found to take about 36 years to emerge, potentially exceeding the service lifetime of a solar farm (25–30 years). Our results highlight the fact that building solar farms over forests or through deforestation leads to no gain in energy efficiency compared to open land, and hence should only be carried out with great caution or completely discouraged. • Solar farms expansion showed small but widespread land-use conflicts with forests. • Forests can reduce solar energy efficiency through reducing solar radiation. • Solar energy efficiency is lower over forests compared to cropland or grassland. • Energy efficiency over deforested regions is lower than cropland or grassland. • Placing solar farms over forests or through deforestation should be discouraged. [ABSTRACT FROM AUTHOR]

Human-environment interactions are often directly reflected in land use changes. Subsequently, researching the impact of land use change on the uncertainty in ecosystem services under different scenarios can help convey how human-environment interactions create uncertainty in such services, thereby promoting the rational development of territorial spatial planning. Taking the Zhangjiakou-Chengde (abbreviated as "Zhang-Cheng") area in China as a case study, this research used the CA-Markov model to predict future spatial distribution of land use types under three scenarios in 2030, 2040, and 2050: business as usual, cropland protection, and ecological security. It employed the InVEST model to evaluate three major ecosystem services of the study area, including carbon storage, habitat quality, and soil conservation. Next, the uncertainty in ecosystem services under different policy scenarios was measured using the coefficients of variation. The results demonstrated that built-up land would continue to expand significantly under the business-as-usual scenario, with substantial increases in cropland under the cropland protection scenario and forestland under the ecological security scenario. In 2050, carbon storage, habitat quality, and soil conservation under the ecological security scenario will be the highest at 901.39 × 105 Mg, 0.7240, and 458226.94 t, which are 1.10, 1.03 and 1.26 times higher than that of 2020, respectively. In each simulation scenario, the uncertainty in habitat quality will be higher than that in carbon storage and soil conservation. Under the ecological security scenario, uncertainty in both carbon storage and habitat quality will be the lowest compared to the other two scenarios. The greater the change in land use area, the higher the uncertainty in ecosystem services. In addition, uncertainty in ecosystem services is associated with changes in land types. Specifically, increases or decreases in water lead to high uncertainty in carbon storage, changes in built-up land result in high uncertainty in habitat quality, while changes in land types have small effects on uncertainty in soil conservation. Simulating future land use change dynamics and exploring ecosystem services and their uncertainties under different scenarios are conducive to constructing reasonable land use patterns and providing decision-making references for regional sustainable development. [ABSTRACT FROM AUTHOR]

Understanding the process of land use/cover changes (LUCC) can provide experience on the enhancement of soil organic carbon (SOC) stocks and carbon sequestration potential for different areas. This study is uniquely to divide different ecological functional areas, and originally combine the machine learning method and soil carbon pool dataset for regional comparative analysis, to compare and quantitatively analyze the drivers of LUCC and the changes in SOC stocks effected by LUCC over 30 years. The results show that topography and climate changes are the main drivers affecting LUCC in four natural areas, while soil factors and population changes do not cause significant effects. The total SOC stocks in Qinghai was increased by 71.18 Tg C and 107.19 Tg C in 0–30 cm and 0–300 cm layers, respectively, and the highest SOC stocks within 0–300 cm were in Pastoral area. Desert and Gobi area had the lowest SOC stocks in both 0–30 cm and 0–300 cm layers. SOC stocks increased in both 0–30 cm and 0–300 cm layers only in Sanjiangyuan Natural Reserve, while the Desert and Gobi area showed a decrease in both over 30 years. This study emphasizes the significant impact of grassland changes on SOC stocks, indicating the importance of considering these changes in land management and ecological protection policies. The initial and original SOC stocks of pre-LUCC may influence the SOC stocks in post-LUCC. The response of SOC stocks changes to LUCC was varies in different areas. The heterogeneity of different ecological functional areas is affected by multiple factors and SOC stocks will become more complex among these areas in the future. These findings contribute to the development of ecological protection policies and the enhancement of regional land management strategies. [Display omitted] • We delineated four functional regions and compared differences in LUCC and SOC stock changes on a 30-year scale. • A machine learning approach was used to quantify the differences in the drivers of LUCC within the different functional regions. • Climate change and topographic factors are the main drivers of LUCC, and population change is constrained by natural factors within different functional zones to produce different driver strengths. • All four functional zones have a decrease in SOC reserves due to a decrease in grassland and large areas of bare ground. • SOC stocks increased only in the 0–30 cm and 0–300 cm layers in Sanjiangyuan Nature Reserve, but decreased in other functional areas. [ABSTRACT FROM AUTHOR]

Cereal grains are widely used as staple foods, therefore ensuring a steady supply of food globally requires cereal production, and South Asia contributes significantly to this endeavor. However, the global food system is thought to be responsible for around one-fourth of all greenhouse gas (GHG) emissions, with grain production being a major contributor to this system. With the increasing need for food, especially cereal grains, it is difficult to reduce GHG emissions from food production on limited land. However, the cereal production - land use - agricultural GHG emissions nexus has been disregarded in earlier studies which needs to be identified for the sustainable food production system. Therefore, this research aims to assess the interactions between agricultural GHG emissions, food production index, and land usage on cereal production in South Asia. This study employs the Fully Modified Ordinary Least Square (FMOLS) model as a baseline model for a panel data set of 1990–2020 and further checks the validity via Dynamic Ordinary Least Square (DOLS) and robust least square procedure to tackle the endogeneity, serial correlation, and outlier issues. Findings confirm that growing the food production index and land usage boosts cereal grain production in South Asia, whereas rising agricultural CO 2 emissions lessen output in the long run. In this paper, we also deploy Dumitrescu and Hurlin's (2012) panel causality test to prove a dual causal connection between the food production index, land use, and cereal food production. From a policy perspective, the findings indicate the necessity of integrating green agro-technology into land cultivation practices in order to achieve increased grain production and mitigate GHG emissions originating from the agricultural sector. [ABSTRACT FROM AUTHOR]

With the serious challenge of persistently high carbon emissions in China, the construction of low-carbon cities is poised to become a trend in future development. However, there has been limited research quantitatively exploring carbon emission spatial targets and efficient algorithmic optimization in a systematic manner. To investigate regional carbon emission compliance and systematic optimization methods, this study takes Shanghai Pudong New Area in China as a case study. It integrates an improved Kaya identity model for forecasting, carbon emission intensity analysis, and an enhanced multi-objective genetic algorithm for land-use optimization. The study aims to predict and account for carbon emissions, compare them against carbon emission targets, analyze spatial influencing factors, and consider relevant policy constraints to simulate low-carbon land-use layouts. The findings reveal the following: (1) Through scenario forecasting and carbon emission accounting analysis, it is evident that Pudong New Area's carbon emissions do not meet the target requirements. There is potential for optimization in terms of the balance between residential and workplace spaces, land use mix, and ecological areas. (2) After applying the genetic algorithm optimization, the carbon emissions in the land-use layout plan are reduced by 11.2%–27.88 million tC compared to the original planning scheme. (3) In simulated scenarios, there are significant changes compared to planned land-use layouts, including a 49% increase in the balance between residential and workplace areas, a 20% increase in land use mix, and a 33.9% increase in per capita park green space.This systematic optimization approach effectively predicts carbon emissions, adjusts land-use layout, and achieves a reduction in carbon emissions. The conclusions provide valuable technical support for low-carbon land-use planning and offer insights for the low-carbon development of other cities." [Display omitted] • Simulate land use layout by policy and factors. • Put methodology of co 2 accounting-peak scenario-target optimization-land use simulation. [ABSTRACT FROM AUTHOR]

The imbalance and mismatch between land use structures and resource elements lead to the intensified competition for land use cover, and the resulting land use conflicts (LUCs) have attracted much attention. However, there are few studies on multi-spatial scale determinants of LUCs, due to relatively discrete scales or single determinant used in previous studies. It is a great challenge to explore the method of prioritizing research multi-scales in view of the determinants of LUCs. This study took the Shenyang Economic Zone, a developed urban agglomeration at high latitudes in China, and used cross-wavelet analysis to clarify the determinants of LUCs between natural resources and human activities in typical years (1980, 1993, 2006, and 2019). The cross-wavelet coefficients were used to extract the determinants of LUCs, and the cross-wavelet phase angles were applied to reveal the acting direction and spatial multi-scale correlation of LUCs with the determinants in the Shenyang Economic Zone. The results showed that: (1) the determinants of LUCs in the study area were distance to industrial and mining storage, intensity, soil types, digital elevation model (DEM), and landforms in 1980, were DEM and distance to industrial and mining storage in 1993, were distance to industrial and mining storage, intensity, and diversity in 2006, and were energy consumption of industrial enterprises, gross domestic product (GDP), and intensity in 2019. From 1980 to 2019, the dominant determinants influencing LUCs in the SEZ shifted from a joint influence of natural resources and human activities to dominance of human activities. (2) The action direction of LUCs with determinants had both positive and negative effects in different spatial positions. (3) The multi-scale correlations between LUCs and their determinants were obvious, and the spatial scale correlations varied significantly. The spatial scale between 94,629 and 118950 m was the most suitable spatial scale to explain the association between LUCs and determinants. The results indicated that the competition between natural resources would aggravate LUCs, however, human activities were the main cause of LUCs. Therefore, we believed that territorial spatial planning should not only consider the land distribution pattern, but also took the determinants as control variables to participate in territorial spatial planning. Our findings could provide a scientific basis for alleviating regional land contradictions and effectively allocating resource elements. [ABSTRACT FROM AUTHOR]

The integration of a model combining multi-layer dimensions of Life cycle assessment (LCA), external Supply Chain (SC) risk factors and Geographical Information System (GIS) is lacking; in order to fulfil this research gap this article proposes an integrated model combining LCA, SC-risk factors and GIS. This research assesses the sustainability of various supply chains representing bio-derived levulinic acid production. The feedstock supplies are corn stover from US, and rice straw from Thailand, China and India. A combined life cycle assessment (LCA) and supply chain (SC) approach, from farm to final bio-derived product distribution and sales are investigated. GIS is applied to provide resolution of spatial and location datasets for the supply chain. The proposed framework is tested on 8 scenarios for the supply and distribution of 100 kilo-ton levulinic acid delivered to China (35%), US (30%), Germany (20%), Japan (10%) and Singapore (5%). The results showed that scenarios 5 and 6 are observed to have the highest overall (external, macro) risks. An overall quantitative (scaled) assessment highlighted that scenarios 1 and 2 are observed to both have the least impacts. With revenue as the main SC priority, scenario 7 gained the advantage of displaying an overall reasonable (moderate) sustainability performance. Based on the limitations of the present integrated model, a future research framework was suggested to include i) multi-criteria optimization methods; ii) land use change (LUC); iii) Water Footprint; iv) dynamic modelling. Image 1 • Combined LCA and supply chain (SC) is modelled for bio-derived levulinic acid. • GIS used to identify locations of feedback supply to proposed biorefineries. • Biomass feedstock include US stover; and rice straw from Thailand, China and India. • Land footprint, costs and revenues, external SC risks and impacts of 8 scenarios. • Future framework/research is suggested to include LUC, WF and dynamic optimization. [ABSTRACT FROM AUTHOR]

Due to its low global share of direct energy consumption and greenhouse gas emissions (1–2%), the implications of technological transitions in the agricultural and forestry sector on the energy system have been overlooked. This paper introduces the Agriculture and Land Use Sector module part of the ModUlar energy System Environment (MUSE), a novel energy system simulation model. The study presents a generalisable method that enables energy modellers to characterise agricultural technologies within an energy system modelling framework. Different mechanisation processes were characterised to simulate intensification/extensification transitions in the sector and its wider implications in the energy and land use system aiming at providing reliable non-energy outputs similarly to those found in dedicated land use models. Additionally, a forest growth model has been integrated to explore the role of reforestation alongside decarbonisation measures in the energy system in achieving carbon mitigation pathways. To illustrate the model's capabilities, Brazil is used as case study. Outputs suggest that by 2030 under a 2 °C mitigation scenario, most of Brazil agricultural production would move from 'transitional' to 'modern' practices, improving productivity and reducing deforestation rates, at the expense of higher energy and fertiliser demand. By mid-century Brazil has the potential to liberate around 24.4 Mha of agricultural land, where large-scale reforestation could have the capacity to sequester around 5.6 GtCO 2 , alleviating mitigation efforts in the energy system, especially reducing carbon capture and storage technology investments in the industry and power sector. • A novel energy-oriented agriculture and land use systems model has been developed. • Mechanisation levels are characterised using cluster analysis and linear optimisation. • Role of reforestation alongside measures in the energy sector in Brazil are studied. • By 2050, modern mechanisation could represent 54–63% of agricultural production. • Brazil has the potential to sequester around 5.6 GtCO 2 through reforestation. [ABSTRACT FROM AUTHOR]

We present a comparative socio-ecological modeling approach to identify possible improvement opportunities for Climate Action Plans (CAPs), focusing on two cities, Chicago and Stockholm. The aim is to provide a tool for capturing and addressing deep-rooted behavioral and institutional preferences that may aggravate greenhouse gas (GHG) emissions in cities. Socio-economic activities, land use change, and future urban forms are considered and forecast to the year 2040 on 30m × 30m spatial grids. GHG emissions associated with these urban development aspects are calculated and compared between the cities. Innovative policy instruments for growth control and zoning (GCZ) are simulated and tested through the socio-ecological model, to determine their effectiveness when added to other interventions included in the CAPs. Our findings show that behavioral/institutional preference for sprawl, its low-density form, and resultant carbon sink losses are main factors driving current and future residential and transportation GHG emissions in Chicago. GCZ policies are shown to counteract and mitigate around 20% of these factors in the form of future GHG emissions. • Comparative socio-ecological models to forecast urban GHG emissions developed. • Urban development factors omitted in existing CAPs are accounted. • Behavioral preference for sprawl and low-density form are drivers of GHG emissions. • Growth control and zoning can counteract and mitigate around 20% of these factors. [ABSTRACT FROM AUTHOR]

The dependence of county industry on high CO 2 emission industries makes it difficult to balance the development of county economy and CO 2 emission reduction. Therefore, this article attempts to study on the spatial-temporal evolution and influencing factor on land use-related CO 2 emissions at region-county level to promote county economy from CO 2 source to CO 2 sink. 9 regions and 38 counties in Chongqing of China were thus selected as study objects. Based on land use data, land use-related CO 2 emissions were estimated using direct and indirect CO 2 emission models for the period 1997–2015. On this basis, the space-time patterns were revealed from two scales of region and county. And the main factors influencing CO 2 emissions according to land use were revealed based on Logarithmic Mean Divisia Index (LMDI) and geographic detector analysis (GDA), respectively. The results show that: 1) at regional scale, CO 2 emissions of different regions all greatly improve in which southeastern ecological protection and development area showed the largest increase. Increases in per capita CO 2 emissions in two-wing (suburban) areas are higher than those in downtown and surrounding-downtown areas. 2) at regional scale, the influences of various decomposed factors on the change of CO 2 emissions fluctuate. The effect of population shows an insignificant influence on CO 2 emissions. Economic development greatly influences CO 2 emissions. Additionally, energy consumption shows a significant inhibitory effect on CO 2 emissions while energy mix exhibits significant hysteresis. 3) at county scale, heavy CO 2 emissions are concentrated in core urban areas; moderate and mild emissions occur mainly in the main urban expansion area, the region around the main urban areas, and in regional hub cities; low emissions are mainly concentrated in the Wuling mountainous area in southeast Chongqing and the Three Gorges Reservoir area in northeast Chongqing. 4) at county scale, the main influences on land use-related CO 2 emissions are total energy consumption, per capita GDP, and urbanization rate. Minor influences include population size, proportion of secondary and tertiary industries, and proportion of land used for construction. [ABSTRACT FROM AUTHOR]

In order to produce goods and services that are consumed in Sweden, natural resources are extracted and pollutants are emitted in many other countries. This paper presents an analysis of the goods and services consumed in Sweden that cause the largest environmental pressures in terms of resource use and emissions, identifying in which countries or regions these pressures occur. The results have been calculated using a hybrid model developed in the PRINCE project combining the multi-regional input-output database EXIOBASE with data from the Swedish economic and environmental accounts. The following environmental pressures are analysed: Use of Land, Water and Material resources, Emissions of Greenhouse gases (GHG), Sulphur dioxides (SO2), Nitrogen oxides (NOx), and Particulate Matters (PM 2.5 and 10). The product groups are those goods and services bought for private or public consumption and capital investments, as listed in the Swedish economic accounts. The results show that Sweden is a net importer of all embodied environmental pressures, except for land use and material use. The most important product groups across environmental pressures are construction, food products and direct emissions from households (except for sulphur dioxide emissions and material use for the latter). Other product groups that are found to have environmental pressures across several indicators are wholesale and retail services, architecture and engineering, dwellings, motor vehicles and machinery and equipment. However, for the three natural resource pressures Use of Water, Land and Material resources, agricultural products are a relatively important product group along with products from forestry for the last two indicators. A considerable proportion of the environmental pressure occurs in Sweden, but when comparing those of domestic origin and that occurring internationally, the majority of all pressures for Swedish consumption occur abroad (except for land use). Other countries stand out as particularly important as origins of pressure for Swedish consumption, most notably China, which is among the top five countries for emissions to air, as well as blue water and material use. Other highly relevant countries or regions are Rest of Asia and Pacific (i.e. Asia and Pacific except Indonesia, Taiwan, Australia, India, South Korea, China and Japan), Russia, Germany as well as Denmark and Spain for certain product groups and environmental pressure combinations. This pattern of geographically spread pressures caused by Swedish consumption indicates the need for addressing the pressures at various levels of collaboration: national, within the European Union, bilateral and international. [ABSTRACT FROM AUTHOR]

The objective of sustainable development in the globe is to eradicate all types of poverty. Land resources are important production factors and income sources for farmers who are in poverty or have been lifted out of poverty. In recent years, it has been a significant instrument to transfer land use rights, in order to improve the well-being of farmers and the productivity of rural land. This paper elucidates the well-being of land transferring farmers, and investigates the influence mechanism of livelihood capital and initiatives to alleviate poverty on the well-being. This is of great significance to improve the well-being and livelihood capacity of land-transfer farmers. The findings reveal that poverty alleviation measures have improved the well-being of land transfer farmers to some extent. Among them, the total effect of e-commerce poverty alleviation on farmers' well-being is considered to be the largest. The study findings also indicate that physical capital and social capital play an imperative mediating role in the path of livelihood capital to influence the well-being of farmers. In particular, certain types of livelihood capital play a complete mediating role in alleviating industrial poverty, alleviating ecological poverty, and alleviating tourism poverty, respectively. Based on the research findings, this study proposes related policy recommendations to improve the well-being of farmers. [ABSTRACT FROM AUTHOR]

Exploring multi-goal sustainable development paths is a global concern. To date, little is known about the characteristics of and logic behind the evolution of China's land use policies (LUPs), especially when they are linked to China's governance philosophy of an ecological civilization (EC). An EC is a unique development concept in China that emphasizes human-nature coexistence alongside economic progress. Therefore, we examine the evolutionary process of China's LUPs in the context of an EC. We identify meaningful shifts that have occurred in those policies, as well as reveal the logic behind the changes. Based on staged text mining of 220 national LUPs initiated in China between 1986 and 2021, by disclosing the changes in the number, foci, goals, concepts, measures, and reform methods of LUPs, this paper provides an overview and four-dimensional deconstruction of the country's LUP evolution in the context of an EC. Three major findings emerge from text mining. First, China's LUP has evolved through three stages, with modifications in the number, dominant foci, and themes of the policies across each stage. Second, comprehensive and significant alterations have transpired in the orientation, goals, concepts, measures, and reform approaches of the policies. Third, the transformation in LUP has transpired centering on four dimensions: improving economic efficiency; balancing production, living, and ecology; promoting social equity; and conserving ecology. These four aspects accord with four governance concepts of an EC—efficient development, symbiosis of humans and nature, social harmony, and green development. We also discuss how China's LUP evolution offers a valuable case for exploring sustainable development at a global level. [Display omitted] • Ecological civilization (EC) and land use policies (LUPs) are interactive in China. • Key changes of China's LUP are tracked by text mining. • An overview and deconstruction of China's LUP evolution are provided under an EC. • Four concepts of an EC are matched with four evolutionary benchmarks of LUP. • China's LUP provides a case for exploring multigoal sustainable development. [ABSTRACT FROM AUTHOR]

The conflict between socio-economic development and ecological protection results in large areas of illegal land use within ecological spaces. Determining the spatial patterns and influencing mechanisms of illegal land use is important because it is harmful to the natural environment. Previous studies mainly considered macro-scale influencing factors, but rarely analyzed the influencing mechanisms behind different types of illegal land use (e.g., residential areas, industrial areas). Therefore, we assessed the spatial distribution of suspected illegal land use and then investigated the influencing factors of various illegal land use types by combining remote sensing and the maximum entropy algorithm. The accuracies of the models for almost all types of illegal land use were much higher than 0.8. The results indicated that 36.14% of the subdistricts exhibited illegal land use issues in terms of the first-level ecological red lines, and 56.63% of subdistricts had this problem within the second-level ecological red lines. Rural residential areas, residential areas, and industrial areas were the major types of illegal land use. In addition, population, elevation, and transportation had a great impact on the occurrence probability of illegal land use. Particularly, transportation-related factors, such as distance from roads, distance from trunk lines, and distance from highways, had a large impact on illegal residential and industrial areas. Proximity to public transportation facilities was associated with a greater risk of illegal commercial areas. Therefore, local governments should strengthen the management of high-risk areas and monitor them closely to prevent conflicts between urban development and ecological protection plans. They must pay sufficient attention to areas with higher population density, lower elevation, and closer proximity to public transportation facilities. Overall, these conclusions can facilitate the fine-scale protection of ecological spaces and provide a theoretical basis for sustainable ecological planning. [Display omitted] • This study revealed spatial patterns and factors of various illegal land use types. • A maximum entropy-based framework was developed to fulfill this purpose. • Illegal land use varied greatly among different levels of ecological red lines. • Population, elevation, and transportation conditions played most important roles. • These findings could support the fine-scale management of ecological spaces. [ABSTRACT FROM AUTHOR]

The consumption of meat and dairy products raise enormous environmental concerns. Circa 80% of global greenhouse gas emissions (GHG) from the livestock industry originate from beef, milk and pork production. Changing the production and consumption of meat and dairy products is considered to offer an important contribution to achieving the Paris Agreement climate targets (UNFCCC, 2015), and could reduce the import of soybean meal to Europe from countries where it is linked with deforestation. However, individual diet substitutions may have indirect and unintended environmental consequences across interlinked livestock systems – hence a wider assessment of impacts of consumption changes is required using consequential life cycle assessment (LCA). In this study, we investigated the environmental consequences of two independent yet interconnected diet choices in a German context: (i) replacing dairy milk with soy milk, and; (ii) replacing beef meatballs with pea protein balls. We related commodity demand to detailed agricultural rotations and land use changes via farm scale economic modelling coupled with consequential LCA. The substitution of beef meatballs with pea-derived protein balls can result in GHG savings of 2.4 kg CO 2 e per 100 g serving, and up to 7.3 kg CO 2 e per 100 g serving if spared land is afforested. Environmental problems related to nutrient leakage such as acidification and eutrophication are also mitigated. Meanwhile, unless accompanied by dramatic reductions in beef consumption, the substitution of cow milk with soy-based milk does not lead to significant GHG mitigation owing to the displacement of dairy-beef production to less efficient suckler-beef systems. Nonetheless, land sparing by cow milk substitution could support overall GHG mitigation if combined with afforestation. This study confirms that legumes can play an important role in diet transitions towards climate neutrality, especially via substitution of meat (as opposed to dairy) products. • Substituting beef meatballs with pea proteinballs scan save 2.42 kg CO 2 e per 100 g serving. • Afforestation of spared land could deliver a total mitigation of 7.3 kg CO 2e per 100 g serving. • Displaced calf production negates CO 2 e mitigation by soy milk substitution of cow milk. • But carbon dioxide removal (CDR) on spared land could generate net CO 2 e mitigation. • Plant protein diet transitions coupled with CDR support climate neutrality. [ABSTRACT FROM AUTHOR]

Promoting the level of intensive use of cultivated land (IUCL) and achieving zero or negative growth of non-grain production of cultivated land (NGPCL) is essential to fully utilize cultivated land resources and ensure world food security. China is an active contributor to global food security, but its current research on the interrelationships between NGPCL and IUCL is not deep enough. Therefore, on the basis of establishing the mechanism of NGPCL and IUCL, we constructed an evaluation index system for each, and investigated the decoupling characteristics of NGPCL and IUCL in China and its 31 provinces using the Tapio decoupling model. The findings indicated that: (1) From 1990 to 2019, China's NGPCL fluctuated and decreased but showed an increasing trend after 2017, while the overall IUCL fluctuated and increased, and the level of NGPCL and IUCL in each province had evident spatial distribution. (2) The decoupling characteristics of China's NGPCL and IUCL showed a spiral change of "expansive negative decoupling–weak decoupling–strong negative decoupling–strong decoupling–expansive connection," and the evolution of cultivated land utilization involved the "pursuit of horticulture–more rationalization–pursuit of ecology–rationalization–transition". (3) The decoupling statuses of 31 provinces were mainly weak and strong decoupling, among which strong decoupling provinces were concentrated in the main grain-production areas in the northeast and east, and more provinces in the western production and marketing balance and main grain-marketing areas showed expansive negative and strong negative decoupling. Based on the research results, we propose specific measures to strengthen the protection and utilization of cultivated land resources. [ABSTRACT FROM AUTHOR]

Aquaculture has emerged as an alternative food production system, but it comes with both benefits and costs that need to be balanced. To evaluate the sustainable status of Chinese aquaculture, we quantify the benefits and costs of aquaculture in each province in China. We obtained the data on aquaculture production from the China Fisheries Statistical Yearbooks (2021) and used nine indicators to represent aquaculture benefits (nutrient, economy, and employment) and aquaculture costs (freshwater, energy, and land use, greenhouse gas, nitrogen, and phosphorus emissions). We found that the nine indicators varied among the 30 provinces in this study. The Southwest and South regions showed the highest benefits (SBS = 30.65) and costs (EPS = 38.55) at the regional level in composite aquaculture (freshwater and mariculture) respectively. At the provincial level, Tibet and Hainan had the largest score for aquaculture benefits (SBS = 82.90) and costs (EPS = 61.37) in composite aquaculture, respectively. Tibet province performed the best in freshwater and composite aquaculture (6.09 and 4.86 respectively), while Jiangsu province performed the best in mariculture according to benefits-to-costs ratio (2.71). More sustainable species production and use cleaner energy (such as hydro energy and nuclear energy etc) and reduce the feed conversion ratio are the direction of more sustainable aquaculture. This study provides the first analysis of Chinese aquaculture sustainability by benefits and costs, and more accurate data and more indicators through weighting could be included in this framework to achieve greater aquaculture assessment in the future. • This study provided the most indicators analysis for the Chinese aquaculture as far. • This study constructed a framework for calculating the benefits and costs of aquaculture. • This study provided the first Chinese aquaculture sustainability assessment by benefits and costs. • The sustainability of aquaculture varies greatly between provinces based on benefits and costs. [ABSTRACT FROM AUTHOR]

Future projections indicate an expansion for both food and energy demands, which can increase pressure on land use, while there is an urgent global need for climate change mitigation. Bioenergy is foreseen as key option to meet future energy demands and reduce greenhouse gas (GHG) emissions, however its sustainability depends on locations and regional characteristics. Simultaneously, agricultural production models that co-produce food, feed, and energy offer sustainability synergies and co-benefits, but site-specific sustainability assessments of their large-scale implementation are missing. This study presents a bottom-up approach to assess spatially explicit sustainability aspects of bioenergy-livestock integrated systems (BLI) in Brazil and shed light on their contribution to future energy demands, to climate change mitigation targets, and their impacts on selected ecosystem services, including bioenergy production, climate change mitigation, reduction of food competition, biodiversity conservation, and avoided deforestation. The proposed integration considers livestock intensification and use of biofuels by-products as animal feed supplement, taking advantage of synergies between these two value chains. The expansion of the BLI system in the Center-South region of Brazil produce up to 89 billion liters of ethanol, enough to meet future domestic ethanol demands from multiple shared socioeconomic pathways and generating surpluses for export. This production takes place on 16 million hectares of pastureland within the Sugarcane Agroecological Zoning, excluding the Amazon and Pantanal biomes, and biodiversity hotspots. BLI expansion mitigate up to 250 million tonnes of CO 2 eq and generate 15 billion dollars of profits. The best locations to maximize the selected ecosystem services are west of São Paulo, east of Mato Grosso do Sul, and the south-central region of the states of Goiás. This study may encourage the formulation of enhanced public policies for the integration of bioenergy and livestock value chains and guide a sustainable large-scale deployment of BLI systems. • Bioenergy and livestock integration (BLI): co-production of food, feed and energy. • BLI systems: 89 billion liters of ethanol and 250 million tonnes of CO 2 eq mitigated. • Enough ethanol to meet future Brazilian demands and surplus to be exported. • Biomass expansion only on pastureland inside Sugarcane Agroecological Zoning. • Without land displacement and deforestation of native vegetation. [ABSTRACT FROM AUTHOR]

The stability of the arable ecosystem plays a crucial role in the sustainable utilization of land resources and the efficiency of agricultural production. However, irrigated agriculture has led to severe desertification and salinization in arid and semi-arid areas, resulting in long-term low ecological stability of arable land. This study focuses on the arable ecosystem stability (AES) in the Hexi Corridor and constructs an AES evaluation model based on the pressure-buffer-response process. Using methods such as the revised wind erosion equation, remote sensing ecological index and path analysis to explore the spatiotemporal dynamics and driving mechanism of AES during the growing season (April–October). The results showed that the AES in the area was transitioning from a critical to stable state, with vulnerable arable land gradually decreasing while stable land increased. Stable arable land was concentrated in the middle reaches of the Heihe River basin, while arable land in the Shule River Basin was basically at critical level, a crucial area for wind erosion prevention. In the lower reaches of the Shiyang River Basin, much arable land was vulnerable to salinization, requiring urgent treatment. Complex climatic conditions and irrational irrigation patterns are the main causes of AES fluctuations. Agricultural engineering construction and favorable policy implementation can significantly improve AES. In addition, seasonal variability in wind erosion, salinization and AES was significant, with the worst in spring and the best in summer. Climate and vegetation factors have become the main factors affecting wind erosion and salinization. The fallow period before spring is a critical time for wind erosion control and salinity soil improvement. This study aims to provide theoretical guidance for the construction of agricultural production and ecological management in arid and semi-arid areas. [Display omitted] [ABSTRACT FROM AUTHOR]

Landscape pattern can affect the export of non-point source nitrogen (N) in watersheds by regulating hydrological and biogeochemical processes. However, due to the inherent spatiotemporal variability of N exports under different land uses and hydrological regimes, it is essential to quantitatively evaluate the impact of landscape pattern on total N export coefficients (TNECs) and identify the threshold effect of TNECs between key landscape metrics. Based on river monitoring data for eight years in nine catchments of a typical agricultural watershed in the central subtropical region of China, we estimated the spatiotemporal variability and uncertainty of typical land-use TNECs (cropland, forest, and tea gardens) by combining an improved pollutant export coefficient model and Bayesian statistics. Subsequently, the contribution of landscape pattern to the variability in land use TNECs under different hydrological regimes was quantified, and the abrupt change points of TNECs along with the gradient of key landscape metrics were further determined. The results revealed that landscape pattern only had a significant effect on TNECs under medium-flow (representing discharge values within the 30–70th percentile range) and low-flow hydrological regimes (70–100th percentile range), explaining 48.1–54.7% and 55.2–69.3% of the variability, respectively. Threshold effects were observed between key landscape metrics representing different landscape categories (area edge, shape, and aggregation) and TNECs for each land use, and the threshold intervals corresponding to the TNEC abrupt change points were relatively consistent under medium- and low-flow regimes. These results serve as a critical reference for land-use planning and management to improve water quality, the approaches developed can be broadly extended to other regions with diverse land-use types and pollutant sources. [Display omitted] • Spatiotemporal variability of land use TNECs are addressed using Bayesian statistics. • Landscape pattern significantly affect TNECs under medium- and low-flow regimes. • The Landscape-TNEC relationship exhibits threshold-driven change. • The abrupt change analysis in landscape-TNECs is vital to landscape planning. [ABSTRACT FROM AUTHOR]

Phytoplankton is a crucial primary producer in wetland ecosystems and is highly sensitive to changes in water quality. It has long been considered one of the most important biological indicators for monitoring water pollution. However, our understanding of the various aspects of phytoplankton communities assembly and the factors driving them remains limited. In this study, we conducted collection and analysis of phytoplankton samples from a temperate wetland cluster encompassing both lake and marsh types under the backdrop of industrial pollution from the petroleum industry. Our aim was to investigate the influence of spatial factors, land use patterns, and local environmental variables on the taxonomic and functional structure of the phytoplankton community, utilizing structural equation modeling (SEM) and variation partitioning. Our results revealed that environmental filtering exerts a greater relative impact on shaping the taxonomic composition of phytoplankton compared to mass effects. Human activities, such as industrial and agricultural production, can lead to landscape modifications that increase water nutrient levels and consequently influence the community composition. Taxonomic beta diversity is determined by both mass effects and environmental filtering. In contrast, functional beta diversity responds more to local environmental gradients, while the land use pattern was not important for facets of beta diversity in the wetland cluster. These results validate the concordance and complementarity between functional and taxonomy-based biome structures, highlighting the significance of integrating multiple ecological drivers. The results of this study contribute to a deeper understanding of wetland community assembly and the processes of biogeography, and are of crucial significance for the biological monitoring and management of freshwater ecosystem environmental pollution. [Display omitted] • Environmental filtering dominated in controlling community assembly in wetlands. • Different types of land use increase community heterogeneity among-wetland. • Wetland connectivity can exert controls on high dispersal rate community dynamics. • Taxonomic species replacements are less associated with turnover in functional traits. [ABSTRACT FROM AUTHOR]

Land use activities play an essential role in habitat degradation and restoration. As priority zones for global habitat conservation, studying the impact of land use activities on habitat quality (HQ) in the World Protected Areas (WDPA) has great importance. However, insights into land use activities and HQ in the WDPA remain scarce and their relationship is still unclear. Here, we assessed land use activities and HQ in the WDPA over the past 20 years and analyzed the impact of land use activities on HQ. The results showed that forestland was the dominant land use type in the WDPA and that the area of forestland, bare land, and water area decreased while the area of other land use types increased during the study period. Land use change in protected areas in different continents shows great differences. Land use intensity (LUI) in the WDPA increased over the 20 years, but HQ remained largely unchanged. LUI increased but HQ decreased was the main change type of grid cells in the WDPA. The bivariate spatial autocorrelation results showed that High-Low (high HQ and low LUI) clusters were the dominant clustering type in the WDPA, while Low-High (low HQ and high LUI) clusters were the least represented clustering type. The regression results showed that LUI tended to have a negative effect on HQ in forested areas and a positive effect on HQ in desert, permafrost areas. These findings can provide a reference for effective land use differentiation control measures and biodiversity conservation measures in the WDPA. [Display omitted] [ABSTRACT FROM AUTHOR]

Urban fragmentation is generally regarded as a strong urban structural polarisation that is closely related to sustainability, yet a comprehensive understanding of the management of different fragmentation scenarios and their causes is still lacking. The Wuhan metropolitan area, as a rapidly urbanising region, shows clear evidence of different forms of urban fragmentation due to rapid urbanisation and spatial differentiation in pedestrian network structure, neighbourhood residential pattern and land use structure. In this study, an integrated framework for examining the fragmentation of dynamic and complex metropolitan areas, is proposed. The results indicate that the 49 highly fragmented sub-districts are distributed with large gated communities, industrial parks, green spaces and rivers/lakes. The fragmentation forms of the Wuhan metropolitan area include morphological, connectional and functional (variety and conflict) fragmentation, which constitute six scenarios. The geographical detector model manifests that urban fragmentation is the result of natural, socio–economic and construction factors. The increase in spatial debris driven by housing prices (q = 0.334), gross domestic product (q = 0.282), population density (q = 0.359), constructive index (q = 0.292) and road density (q = 0.314) has dramatically affected spatial organisation co–evolution. Additionally, there are synergistic enhancement effects between each pair of driving factors, i.e., bivariate or nonlinear interaction strengthens the impact of each other factor on the index of urban fragmentation. The strongest bivariate interaction is between housing prices and constructive index, with a value of 0.503. The largest nonlinear interaction is between constructive index and industrial index, with a value of 0.487. These interactions all further exacerbate urban fragmentation. These findings not only contribute to an integrated methodological framework, but also provide scientific implications for the purpose of sustainable urban development and cleaner production planning. • Using fine–scale land use information to examine fragmentation in a metropolitan. • Fragmentation is quantified and characterised by morphology, connection and function. • Population density is found to have the greatest impact on urban fragmentation. • Bivariate/nonlinear interactions among drivers enhance the impact on fragmentation. • This empirical research highlights the sustainable urban form and anti–fragmentation. [ABSTRACT FROM AUTHOR]

Farmland landscape fragmentation has become one of the main manifestations of global land use changes during the last century. Since the reform and opening-up in China, the Beijing-Tianjin-Hebei region, as the representative region in China, has exhibited a continuous process of farmland landscape fragmentation. Scientifically revealing the spatiotemporal dynamics of farmland landscape fragmentation is of great significance for sustainable land management. Although the characteristics of farmland landscape fragmentation have been widely studied, measuring the dynamics of farmland landscape fragmentation from the perspectives of landforms and urban-rural variations remains poorly understood. This study relies on the comprehensively theoretical models to spatiotemporally identify farmland landscape fragmentation and applies a comprehensive index method that includes ArcGIS, FRAGSTATS landscape pattern analysis and the multiscale geographically weighted regression model to empirically analyse the spatial-temporal characteristics of farmland landscape fragmentation in China from 1980 to 2020. The results indicate that the value of the farmland landscape fragmentation index in the Beijing-Tianjin-Hebei region is characterised by process of 'slight increase-rapid decrease-continuous increase'. High farmland landscape fragmentation index values were observed in the northern and western Beijing-Tianjin-Hebei regions. Moreover, significant differences in farmland landscape fragmentation were observed under different macro landforms. The farmland landscape fragmentation index in the mountainous regions is much higher than in the plains. Furthermore, as the distance to Beijing's centre increases, the farmland landscape fragmentation index decreases in suburban and peri-urban areas. Finally, the results also reveal the driving factors of farmland landscape fragmentation. The results showed that the natural environment is always the crucial driver of farmland landscape fragmentation. Besides, social activities play an important role in the past, but economic development has a more significant coefficient these days. The findings of this study not only verify that the proposed theoretical framework is valid and provides a reference for future policy measures to protect farmland but also provide a basis for farmland landscape fragmentation from a multiscale perspective by, more precisely, identifying the heterogeneity of drivers. [Display omitted] • Theoretical temporal and spatial models of farmland fragmentation were constructed. • Farmland fragmentation index system (patch scale, shape regularity, spatial distribution) was created. • Farmland fragmentation index in the mountainous regions was much higher than that in plains. • Farmland fragmentation index shows a decreasing trend with the urban-to-rural gradient. • Natural environment is always the crucial driver of farmland fragmentation. [ABSTRACT FROM AUTHOR]

Ecosystem service value (ESV) is increasingly influenced by land use/land cover (LULC). At the same time, China's extensive urbanization over the past 40 years has reduced ESV, highlighting a pressing need for spatial studies. However, few studies on the spatial relationship between LULC, urbanization, and ESV, especially at the national level, represent a significant gap in this field. In this research aims, we aim to fill this gap by examining their spatial relationships by studying 279 prefecture-level cities in China. Furthermore, to understand the changing dynamics, we studied the temporal and spatial heterogeneity of the effects of LULC and urbanization on ESV in 2005, 2010, 2015, and 2020 using a multiscale geographically weighted regression model. Regarding LULC, the results show that the impact of land use intensity on ESV is significantly negative nationwide, and the trend continued to strengthen from 2005 to 2020. There was significant spatial and temporal heterogeneity in the effects of land use diversity on ESV, with negative effects in the north and a positive impact in the Beijing-Tianjin-Hebei region. Concerning urbanization, the association between ESV and different types of urbanization varied greatly over space and time. Our findings suggest that policymakers should pay attention to compact land development, optimize land use structure, and promote the mixed use of land on the basis of rational planning in urban layouts, to mitigate the negative impacts of urbanization and LULC changes on ESV. [Display omitted] • Complex temporal and spatial relationships between Urbanization, Land Use/Cover, and ESV in China. • The association between ESV and different types of urbanization varied greatly over space and time. • Land use intensity negatively impacts ESV nationwide, trend strengthens 2005-2020. • Land use diversity effects on ESV show spatio-temporal heterogeneity. [ABSTRACT FROM AUTHOR]

Industrial transfers are conducive to reducing regional development disparities, but they may cause pollution transfers through pollution-intensive industries (PIIs). This study tries to characterize transfers of PIIs in China from 2007 to 2016 with newly expanded industrial land use data. The industry transfer relative intensity index is calculated to measure interregional transfers of PIIs, and hot spot analysis is used to illustrate the spatial clustering pattern of PII transfers. The results are as follows. 1) PIIs are transferred from the east to the west and from the eastern coastal region to the northwest and the middle reaches of the Yellow River economic zone. Land use by PIIs in Western China as a proportion of the national total has gradually increased, from third to first rank. 2) Over time, the significant cold spots (i.e., clusters of transfer-out regions) have spread from the eastern coastal provinces to the central provinces, and the hot spots (i.e., clusters of transfer-in regions) have become more significant in the northwestern provinces. 3) PII transfers in urban agglomerations are strongly consistent. 4) Transfers of PIIs are influenced by regional resource endowments, environmental regulations, and other policies. These findings provide vital information to aid environmental protection and policymaking. • Transfers of pollution-intensive industries are measured with newly-increased industrial land. • Land use by pollution-intensive industries in Western China as a proportion of the national total has gradually increased. • Transfers of pollution-intensive industries in urban agglomerations are strongly consistent. • Transfers of pollution-intensive industries are influenced by regional resource endowments and environmental regulations. [ABSTRACT FROM AUTHOR]

International trade of soybeans has increased substantially over recent decades. Its environmental toll is routinely linked to deforestation and biodiversity loss. However, soybean trade also imposes a huge demand on water and land resources, in individual countries and globally. Such a burden, and its underlying sectoral drivers, is frequently overlooked within the current research and policy agenda around sustainable soybean supply chains. This study evaluates the Virtual Water Trade (VWT) and Virtual Land Trade (VLT) of global soybean trade and reveals which countries and sectors are responsible. Soybean-related VWT and VLT are estimated by combining physical import and export data and associated resource use information from 166 countries during the period 2000–2016. Over this period global virtual soybean-related virtual water and land trade grew by 298% and 250% respectively. In 2016, 812 Gm3 of water use and 41 Mha of land use was directly embodied in international soybean trade. This corresponds to one-third of water and land used to grow soybean globally. Soybean-related VWT and VLT was mainly driven by demand in China, the Netherlands and Mexico, for soybean grown in the US, Brazil and Argentina. Animal feed is responsible for around three-quarters of this resource use. A reduction in the consumption of animal products or switching to direct human consumption of soybeans would reduce the overall demand for soybean production and associated resource use. Although welcome, calls for deforestation-free soybean supply chains do not go far enough to reduce the large, global water and land demand of soybean trade. The research and policy agenda around soybean trade warrants a broader focus on water and land use and whether this represents an efficient, and logical, allocation of resources within the context of food provision and national resource security. [ABSTRACT FROM AUTHOR]

Abstract Sweden's environmental policy aims to solve domestic environmental problems without increasing environmental and health impacts overseas. Realizing this aim requires an indicator system with a consumption-based (or "footprint") perspective that captures both local and global impacts and their development over time. In this paper, we present a set of novel footprint indicators to measure environmental pressures from Swedish food consumption. The indicators are calculated by combining data and statistics on agrochemicals and deforestation emissions with EXIOBASE3, a global Multi-Regional Input Output (MRIO) database with a unique and high level of product detail across countries. We estimate the use of pesticides and antimicrobial veterinary medicines associated with current Swedish food consumption and compare those footprint indicators with the EU-28. Carbon emissions from deforestation are calculated with a land balance model and included in the overall carbon footprint of food. We find that Sweden, with its large reliance of food imports, exert a significant agro-chemical and climate footprint overseas, mainly in the EU and Latin America. We point to a need for better data and statistics on the use of pesticides, veterinary medicines and agrochemicals residuals (especially in developing countries) as well as improved spatial data on agricultural activity to further reduce uncertainty in the environmental footprint of Swedish food consumption. Highlights • We present footprints for agrochemicals and climate from Swedish food consumption. • Due to large food imports, a significant share of Sweden's impact occur overseas. • Emissions from tropical deforestation represent roughly 10% of carbon footprint. • More than three quarters of Sweden's pesticide footprint is embedded in imports. • Data gaps on use of agrochemicals are significant, especially in developing countries. [ABSTRACT FROM AUTHOR]