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Effluents from paper mills are highly toxic and are a major source of aquatic pollution. In this study, we collected water and sediment samples to examine the microbial communities using denaturing gradient gel electrophoresis and identified bacterial taxa greatly affected by paper mill pollution using next-generation sequencing data. Our results indicated that bacterial communities in downstream sediments were similar to those in paper mill discharge sites, indicating obvious effects of pollution, while bacterial communities in downstream water samples showed similar profiles to those in upstream sites, both being quite different from the bacterial communities in paper mill discharge sites. This was possibly because of the short contact period. In addition, bacterial communities in the estuary were quite different from those in other water and sediment samples, which was owing to the special habitat type. Considering the storage of paper mill pollutants in sediment and the significant effect on shifts in bacterial communities, we selected Clostridia and Epsilonproteobacteria at the class level and Fusibacter and Desulfobulbus at the genus level as bacterial indicators of paper mill pollution. To monitor the remediation of polluted aquatic environments, we propose Sphingobacteria , Alphaproteobacteria , Actinobacteria , Subdivision3 , Planctomycetacia and Verrucomicrobiae at the class level and Bacillus , Steroidobacter , Nocardioides , Terrimonas , Pirellula and Methylibium at the genus level. [ABSTRACT FROM AUTHOR]

Abstract: We studied ecotoxicological responses of aquatic insects to evaluate the recovery of a watercourse with a history of over 100 years as a recipient of pulp and paper mill effluents. The recovery of the water quality began in 1985 due to the improved technology, but ecotoxicological effects on biota have still been evident two decades later, as indicated by morphological abnormalities in tracheal gills of caddis larvae. We hypothesized that these abnormalities are related to organic contaminants, such as resin acids, alkylated PAHs and chlorinated organic compounds, released historically from the mills, and more recently via resuspension from the sediment. Samples were collected between 1999 and 2008, and the species composition and morphological abnormalities in the gill tufts were analysed. We tested a Hydropsychidae index (HA) based on species sensitivity scoring as an indicator of improved overall water quality, especially oxygen concentrations. Gill abnormalities were used as morphological biomarkers indicating potential ecotoxicity. The increased HA values revealed improved oxygen levels and associated recovery of benthic macroinvertebrate community structure. However, the incidence of gill abnormalities remained elevated until the year 2008 indicating slow recovery, as 20-year impacts on population health and ecotoxicity was detected in the watercourse polluted by pulp and paper industry. [Copyright &y& Elsevier]

Monogenea is a Class of ecologically and economically significant platyhelminth parasites of freshwater and marine hosts. Contamination of the environment has been shown to variably affect parasites resulting in alterations at the population and organismal levels. The aim of this study was to perform a meta-analysis of published data to assess similarities among responses of monogeneans to pollution and estimate effect sizes of contaminant exposure on these parasites. Effect size was calculated according to Cohen’s d based on reported mean abundance for monogeneans from individual studies. A total of 57 studies were used in the present study. Each Monogenea–contaminant record represented a single data point in the meta-analysis, and this accounted for a total of 217 useable records. Most studies were concerned with species belong to Gyrodactylidae, Diplozoidae, Ancyrocephalidae and Dactylogyridae. Assessment of the effects of specific pollutants on monogeneans have mostly been restricted to exposure to eutrophication, pulp-mill effluent and metals. Comparison of effect sizes showed strong negative effects for metals and strong positive effects for eutrophication on monogeneans. Other contaminant types had weak effect sizes on monogeneans. Comparison of effect sizes among monogenean families showed that none of the effect sizes calculated were significant but metals and disturbance contaminants showed strong negative and positive effects respectively for Gyrodactylidae. The current comparisons were based on changes in the population structure and infections of monogeneans, however, organ level effects associated with exposure to poor water quality have also been noted. In this instance, exposure has been suggested to result in asymmetry of the attachment organs of some monogeneans. Despite numerous records of impacts of pollution exposure at the population level, understanding of the physiological effects and mechanisms employed by Monogenea to survive and adapt to changes in the environment are yet to be explored. Study of these aspects would enable better understanding of the variation in the trends observed at a population level for monogeneans in relation to the quality of the macroenvironment.

Spatial and temporal variations in raw sewage input via river discharge to a tropical bay (Guanabara Bay, Rio de Janeiro, Brazil) were characterized by considering chemical (sterols, δ 13 C) and biological ( E. coli ) indicators in suspended particles collected during three periods in eight representative rivers that contribute to the bay. Coprostanol concentrations ranged from 0.03 to 206 μg L −1 , averaging 21.9 ± 43.4 μg L −1 , whereas thermotolerant coliforms counts ranged between 0.4 × 10 3 and 1.1 × 10 12  MPN/100 mL. A close relationship between the most contaminated rivers and human density occupation was determined, revealing the extreme lack of basic sanitation networks in the largest metropolitan region on the coast of Brazil. Coprostanol concentrations of 0.060 μg L −1 correspond to the limit established in the national legislation for primary contact water according to microbiological standards (thermotolerant coliforms). Therefore, this criterion based on coprostanol can be used as an additional tool to monitor the quality of the water used for recreation in the region. [ABSTRACT FROM AUTHOR]

Highlights • Forest resource Metabolism Network model isdeveloped for ecological and economic analysis. • Exploitation index is developed to reveal the weaker sectors in the ecological relations. • A case study of Guangdong province, China isconducted to illustrate the potential benefits. • Scientific Basis are provided to allocate forestresources and stabilize industrial structure. Abstract Integrating forest resources into the socio-economic system correctly and reasonably is of vital importance to tackle the increasingly scarce forest resources. In this paper, forest resource input-output model and forest resource metabolism network model are established to provide new insights into the relationships among the systems, industries and sectors related to forest resources. A promising indicator named exploitation index is developed to reveal the weaker sectors in the ecological relations, which will further help to provide better corrective actions and integrated strategic measures. Guangdong is taken as an example to verify the availability of the model and solve the problem. The results show that the primary manufacturing consumes more direct timber, while advanced manufacturing and the service sector utilize timber indirectly. In addition, Guangdong forest metabolism system shows a negative correlation and the whole network does not achieve the mutualism state, leading to competition relationships between pairwise sectors that should not appear, such as Forestry sector and Papermaking and Paper Products sector. These results provide the corresponding reference for helping the decision makers to allocate forest resources and coordinate ecological and economic development. [ABSTRACT FROM AUTHOR]

Cities constitute a critical component of the “dual carbon” strategy, highlighting the importance of examining the carbon emission trends within various city categories to formulate a low-carbon development path. In this paper, 21 cities (prefectures) in Sichuan province were divided into 4 categories (service-based cities, resource-based cities, industry-based cities, and other cities) through K-means clustering, and the differences in driving factors of carbon emissions in different types of cities were explored. At the same time, baseline scenarios, technological innovation scenarios, controlled development scenarios, and mandatory emission reduction scenarios were set up to dynamically simulate the evolution path of urban carbon emissions in the next 30 years from the bottom-up. The results show that: (1) Input scale is the main driving factor for carbon emission growth in Sichuan province, while input carbon intensity is the leading factor for carbon emission reduction. Environmental input and population scale have opposite effects on carbon emission of different urban types. (2) Resource-based cities face challenges in completing the phased goal of “carbon peaking” under both baseline scenarios and controlled development scenarios. These cities have gradually become the predominant city type of emission source in Sichuan province, surpassing service-based cities. (3) Except for the normal scenario, Sichuan province can achieve the target of “carbon peaking” in other scenarios, and is expected to achieve the target of 90 % greenhouse gas reduction by 2050. (4) Among the 81 development paths derived from the urban scenario combinations, the path labeled M−B−C−M exhibits the lowest economic-ecological comprehensive impact coefficient. The bottom-up carbon emission scenario analysis framework established in this paper offers a novel perspective for the study of “carbon peaking” and can provide theoretical support for policymakers in devising regional low-carbon development strategies.

The rapid expansion of cities has brought new challenges to sustainable development (SD). Therefore, how to balance between SD and the economic growth has become the key to regional development. With the aim of enhancing the research system of SD level, founded on the deep research of SD level from a new perspective of “input-output” and the dynamic evolution law of SD level, this paper has explored the path for cities to improve their level of SD to achieve regional coordinated development. By virtue of the Super-efficiency Slack-Based Measure model based on unexpected output (unexpected super efficiency SBM model), it has measured the SD level of 21 cities in Sichuan from 2010 to 2019. Using methods such as equilibrium coefficient, obstacle analysis and gravitational model, this paper has studied the spatiotemporal evolution law of SD level and constructed six scenarios to simulate the future trend of SD level. The results have indicated that the level of SD in Sichuan is showing a gradual decline with significant constraints. The focus of SD in Sichuan is gradually shifting from Chengdu to a city cluster centered around Chengdu, Ziyang, and Meishan. In an ideal development scenario, the level of SD has significantly improved. This study has revealed the current status and potential of SD in Sichuan. In the future, with more concentration on the role of core urban agglomerations, Sichuan should adjust policies to address input–output barriers to promote SD throughout the province.

As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city’s overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches.

Understanding the spatiotemporal changes in ecosystem service value (ESV) under urbanization, as well as the supply–demand relationship between different regions, can provide a consultation for ecological compensation (EC) standards. Taking Suzhou, a typical city experiencing rapid urbanization in the Yangtze River Delta, as a case study, this paper analyzes the spatiotemporal changes in land use and ESV from 2000 to 2020. To quantify the ecosystem service flow (ESF), we apply the breakpoint formula and field strength model. Additionally, an EC standard is established, taking population, area and GDP into account while specifying compensation. The findings reveal that urbanization has led to a substantial increase in built-up land in Suzhou, accompanied by continuous reductions in farmland and water bodies. As a result, ESV decreased from 153.07 billion CNY to 138.81 billion CNY. Furthermore, the research identifies a spatial pattern where ESV increases with distance from the city center but decreases with distance from the lake center. This pattern suggests a directional flow of ESV from lakes to cities. Notably, ESF mainly occurs in the southwestern and central areas of Suzhou, with areas closer to Taihu Lake experiencing greater ESV transfer. The transfer value ranges from 5.11 and 32.57 billion CNY. There is an imbalance between the supply and demand of ecosystem services. Therefore, specific county-level cities in Suzhou, namely, the Kunshan District and Industrial Park, emerge as contributors of EC and should contribute 71.94 and 80.74 billion CNY, respectively, to other cities. By formulating a novel EC policy for Suzhou, this paper provides a scientifically informed reference for promoting sustainable development.

Promoting the high-quality development of urbanization is a crucial way to achieve sustainable development goals. Water resources are a rigid constraint for such development. However, There is still room for improvement in the research on the spatio-temporal pattern and key driving factors of high-quality urbanization development under the constraint of water resources. Aiming at the problem that the high-quality development of urbanization in the Yellow River Basin (YRB) is facing water resources constraints, this paper discussed the spatial–temporal pattern and key drivers of the high-quality development of urbanization in the YRB under water resource constraints by using the Analytic Hierarchy Process model reformed by entropy technology, multi-objective fuzzy membership function, spatial autocorrelation analysis and obstacle model. The results revealed that, first, we found the High-Quality Urbanization Development Index (UQDI) exhibited steady growth, while both the Water Resources Index (WRI) and the Water Resources Constraint Intensity (WRCI) initially increased and then decreased during the study period. Second, the UQDI displayed a dual-core pattern, with the Shandong Peninsula urban agglomeration and the Central Plains urban agglomeration serving as the cores. WRI exhibited relatively stable spatial distribution, with the southeast region outperforming the northwest. WRCI also demonstrated a relatively stable spatial distribution, resulting in two weak-constraint areas, represented by Shandong and Henan, and a strong-constraint area centered around Ningxia. Third, the UQDI, WRI, and WRCI exhibited spatial interdependence. The spatial interdependence of UQDI and WRI increased, while that of WRCI decreased during the study period. The three indexes also displayed a clear pattern of local clustering in space. Two low-value aggregation areas, namely Shandong and Henan, and a high-value aggregation area located in Ningxia, emerged during the study period. Last, the WRCI was primarily influenced by the fundamental conditions of water resources. The main influencing factors included per capita water resources, mean annual precipitation, total water resources, water resources modulus, and the total amount of foreign investment utilization. In light of the research findings, the paper proposes policy recommendations for promoting high-quality urbanization development in the YRB. This study provides decision-making guidance for countries and regions in arid areas to solve the water resources constraints on the high-quality development of urbanization.

China has abundant straw resources, but challenges in utilization persist. Utilization rates need improvement, and environmental pollution from straw burning remains a significant issue. Accurate and intelligent remote sensing classification of straw types is crucial for enhancing straw utilization and preventing straw burning. This paper proposed a new approach for the intelligent classification of maize straw types, using the DenseNet201 deep transfer learning algorithm based on RGB images captured by Unmanned Aerial Vehicle (UAV). The sample labels dataset was established for maize straw types, utilizing DenseNet201 deep transfer learning algorithm to pre-train the sample set. This pre-training facilitated model transfer and parameter initialization. Subsequently, the second round of deep transfer learning was performed to construct the final maize straw type remote sensing classification models using DenseNet201 deep transfer learning algorithm. This model and results were subsequently compared with maize straw type classification by the ResNet50 and GoogLeNet deep transfer learning algorithms, as well as maize straw type classification using DenseNet201, ResNet50, and GoogLeNet deep learning algorithms. The results showed that the accuracy of the pre-trained maize straw type deep transfer learning remote sensing classification model surpassed that of the untrained maize straw type deep learning remote sensing classification model, resulting in an enhancement of accuracy by 8.59%, 7.38%, and 1.28%, respectively. The DenseNet201 deep transfer learning model for maize straw types exhibited the highest accuracy with the overall accuracy of 95.57%, and the kappa coefficient of 0.9410. Hence, the DenseNet201 deep transfer learning classification of maize straw types enabled the attainment of intelligent remote sensing recognition of maize straw types. The classification methodology, model, and results presented in this paper can serve as valuable technical references, offering essential information support for agricultural and environmental protection departments actively involved in the comprehensive utilization of straw resources and atmospheric environmental protection efforts.

The phenomenon of inner peripherality is on the rise in Europe. Inner peripheries can be defined as peripheral rural areas experiencing territorial disconnection and progressive marginalization given their distance to urban centres, where the supply of services is concentrated. Assessing and comparing the sustainable development of these areas according to nuanced and integrated social-biophysical perspectives is crucial to highlight their genuine long-term sustainability potential and critical aspects. Moreover, it is essential to monitor that the socio-economic development of the latter goes hand in hand with territorial stewardship and an appropriate management of their extensive natural endowments. To achieve these objectives, this paper illustrates an innovative methodology to design a multi-criteria evaluation framework named PAISDA (Peripheral Areas Integrated Sustainable Development Assessment). The framework, based on the theoretical background of ecological economics, makes it possible to monitor the sustainable development of inner and marginalized areas according to a “post-growth” approach. It also allows a shift towards a strong sustainability perspective by assessing the phenomenon in an integrated way, which combines social and biophysical dimensions. This can help to design more robust and better targeted policies for these areas, thereby improving local strategic planning. The assessment process is as follows: first, the values of lower order components are computed through a reflective measurement model, then aggregated to form the values of higher order components, which are used as criteria in the last phase of multi-criteria decision analysis (MCDA). The choice of normalization and aggregation methods responds to methodological coherence. The paper describes a step-by-step procedure for applying the PAISDA framework in any European country, providing an illustrative example of its implementation in relation to Italian inner areas.

Ecosystem services (ES) assessment is crucial in ecology, with numerous studies seeking to evaluate them. Despite the abundance of methods and indicators, standardization is lacking, hindering comparability and progress in ES understanding and monitoring. This paper reviews indicators used in scientific literature to evaluate mountain ES and then examined whether the most used indicators are also the best. Using ISI Web of Knowledge we searched papers published between 2015 and 2020 containing “ecosystem services” AND “mountains” and we selected 400 papers effectively applying at least one indicator to evaluate ES. For each article, we extracted the following information: type of ES evaluated; indicator(s) used; input data used; type of value-domain (ecological, economic or social); scale of analysis; country; mapping; and management suggestions. From the literature, we extracted a list of 130 most frequently used indicators. The results indicated that regulating services were the most frequently assessed ES, followed by provisioning, cultural, and lastly supporting. The scale of analysis was mainly regional (51%) and local (40%), while studies at national scale were less frequent (9%) and only 2 studies were at global scale. Mountain areas most studied were in Europe (50%) and Asia (31%). Ecological value-domain was the most frequent used (55%), followed by social (26%) and economic (18%). 84% of studies considered only one dimension of the value and few studies combined multiple value-domains (15%). Almost half of studies mapped ES and around one third provided management suggestions. We examined the quality of indicators based on six criteria evaluated by experts in the field: significance, simplicity, cost, replicability, ease of interpretation and policy relevance. Indicators used exhibit significant diversity, and there is no clarity in nomenclature. There are cases where the indicators used represent inadequately the ecological parameters to be measured. Although many indicators score high in some of the properties evaluated, only 13 indicators perform well in all properties. These indicators have a universal value both in terms of semantics, but also in terms of properties and should be promoted for standardization among ES assessments. We envisage the necessity to condense the array of indicators commonly used down to a small set of standardized high-quality metrics.

Jianghan Plain is an important grain-producing area in China, and the transformation of the natural environment by the long-term polder activities of the people in this area has created a characteristic polder landscape. After 2000, urbanization has led to the destruction of ecosystems in these polder landscapes, especially in sensitive areas at the urban–rural interface. ESP can help mitigate this threat by systematically identifying and connecting ecologically significant areas to enhance ecosystem stability and sustainability. In this paper, taking Dongxihu Polder as an example, we apply multi-source remote sensing data to develop LER and LUC models. Combining these with MCR model, we construct an ESP for Dongxihu Polder. The study shows that (1) the growth of LER and LUC in Dongxihu Polder is characterized by “strong dynamics, high complexity and weak protection”, which is closely related to the urban expansion of the urban–rural boundary area; (2) Watersheds, woodlands, and farmlands play an important role in controlling LERs and LUCs, so we identified 33 ecologically important source areas that are mainly concentrated in these regions; (3) In this paper, 46 ecological strategic nodes and 16 ecological corridors were extracted to construct the Dongxihu Polder ESP of “one ring, five axes, multiple points and multiple chains”, and suggested specific optimization strategies. The study provides feasible ecological management policy recommendations for the protection as well as sustainable development of Dongxihu Polder.

The adoption of the 2030 Agenda for Sustainable Development by the United Nations General Assembly, encompassing 17 Sustainable Development Goals (SDGs), established a universal framework for addressing global challenges. Within the European Union (EU), the commitment to these goals has prompted the integration of the SDGs into a strategic framework for sustainable and inclusive growth. Recognizing the need for localized and detailed monitoring to capture the nuanced progress and challenges across Europe’s diverse regions, this paper proposes a comprehensive set of regional indicators specifically designed for the European context. Through a systematic review of existing SDG monitoring frameworks at different territorial levels and an extensive methodological process, the paper identifies 116 indicators that address 75 SDG targets. This tailored set is derived from a combination of national, regional, and supranational sources. The paper discusses the critical balance between standardization for comparability and customization to accommodate unique regional characteristics. The proposed indicator set is evaluated for its capacity to reflect the holistic vision of the SDGs while allowing for effective regional benchmarking. The research emphasizes the need for robust regional data infrastructure, the importance of aligning policies with broader sustainability objectives, and the dynamic nature of indicators that can adapt to societal changes such as demographic shifts. Finally, the paper highlights the significance of a pragmatic and adaptive regional approach to SDG monitoring. The proposed indicator set is a strategic tool for policymakers, stakeholders, and practitioners, guiding Europe’s regions towards a sustainable future and contributing to the global effort to achieve the SDGs by 2030.

Yang and Meng (2020) used sub-optimal search keywords and methods to publish a bibliometric paper in Ecological Indicators. There are two questionable parts to the original paper: a filter could be used to retrieve a more accurate set of data and the use of sub-optimal search keywords. There is a big difference between the two results that were searched using search keywords ("carbon footprint", "carbon footprints", and "carbon footprinting") which we suggested and ("carbon footprint") which authors used. Finally, an appropriate method and search keywords were presented. [ABSTRACT FROM AUTHOR]

In Northeast (NE) China, the largest commodity grain base and natural forest area in China, both agricultural production and ecological protection require attention. In recent years, land degradation in NE China has increased, seriously affecting the production-ecology synergy. In this paper, four key ecosystem services (ESs) in NE China are quantified: provisioning, water conservation (WC), soil conservation (SC) and sand fixation (SF), and the spatiotemporal evolution characteristics and trade-offs and synergies (T&S) of ESs are analyzed. The driving factors of provisioning services and the characteristics of T&S are considered, and the county zoning scheme and the corresponding production-ecological function synergistic optimization paths are proposed. The results show that (1) the provisioning, WC and SF services in NE China have slightly increased in the past 20 years, and the provisioning in the Greater-Khingan-Mountains-Region (GKMR) and Lesser-Khingan-Mountains-Region (LKMR), the WC in the LKMR, and the SF in the Liao-River-Plain (LRP) have more obviously increased. The SC service has slightly decreased, especially in the Changbai-Mountains-Region (CBMR). (2) The provisioning service in NE China mainly shows a synergistic relationship with WC and SF, accounting for 79.1 % and 62.9 % of the area, respectively, and a trade-off relationship with SC, accounting for 52.54 % of the area. (3) Human activities (HA) are the dominant driving factor of the provisioning service change in NE China, with an impact degree of 62.65 %. The LKMR is an exception, as climate change (CC) dominates. The LRP, Songnen-Plain (SNP) and GKMR have high degrees of HA. (4) The number of synergistic optimized (SO), light optimized (LO) and trade-off limited (TL) counties accounted for 19.0 %, 61.7 % and 19.3 %, respectively. Among them, the SO type counties should prioritize improving provision and grain production capacity, the LO type counties should protect basic farmland and decrease trade-offs between ESs, and the TL type counties should improve ecological functions and strengthen ecological protection and restoration. This paper clarifies the main contradictions of ESs in NE China and provides an important scientific basis for ecological protection and restoration, which is important for ensuring food and ecological security and realizing the ecological and efficient sustainable utilization of black soil.

Maintaining and restoring ecological connectivity (EC) are important measures of mitigating habitat isolation caused by urbanization. Considering the prominent contradiction of land use in highly urbanized areas, the EC protection measures proposed in the previous studies, such as expanding the ecological sources and widening the ecological corridors, are unrealistic. By using the stepping-stone and complex network theories, this paper simulated the ecological network (EN), evaluated the centrality of each ecological source and stepping-stone, and analysed the network robustness under different damage scenarios, then identified the optimal strategy and key patches for EC maintaining. Meanwhile, this paper evaluated whether the key patches are protected by China’s new policies, which are, Ecological Protection Red Line (EPRL) and the Three Lines One Permit (TLOP). The results were as follows: (1) The EN is composed of 53 ecological sources and 291 stepping-stones, with 591 links between them. (2) The network stability can be optimally maintained by prioritizing the protection of stepping-stones with high centrality. (3) The 53 ecological sources and 51 stepping-stones with the highest centrality can ensure the stable operation of the EN, that is, they are key patches for EC maintaining. (4) Compared with EPRL, the protection rate for ecological sources and stepping-stones are significantly improved by TLOP; however, stepping-stones with high centrality require stronger protection. This study enriched the research cases of complex network theory applied in landscape ecology, and provided references for the improvement of policies in the future.

Rivers originating from the Himalayas play a crucial role as primary water sources for a significant proportion of the population in Asia downstream. This paper presents a comprehensive synthesis of hydrogeochemical data, incorporating major ions and trace elements from 153 papers spanning 2000 to 2023, with a detailed analysis of 20 papers specific to Nepal Himalayan rivers. To bridge the research gap due to sparse data, we aimed to enhance inclusivity by amalgamating both seasonal and one-time datasets, computing mean values for singular instances, and employing grand means for multiple seasonal data points. Our findings highlight varied research attention across different river basins, with the eastern Koshi Basin receiving extensive attention, while the middle Gandaki and Bagmati Basins garner moderate attention, and data scarcity observed in the western Karnali Basin. Predominant ionic composition, notably Ca2+ and HCO3–, reflect lithological influences, primarily driven by rock weathering. Although anthropogenic impacts remain minimal in most basins, certain lowland areas with higher population densities exhibit increasing significance. Trace element contamination, notably Cd, Cu, Sr, and Zn, poses ongoing threats, both from natural and anthropogenic sources. Water quality assessments conducted for agricultural and drinking suitability indicated good status, except in the densely polluted urban Bagmati stem. Health and ecological risks are low, as determined by pollution indices such as Pi, NPI, HI, and CI. The Bagmati River's middle segment, with high population density and moderate agricultural activity, shows pronounced anthropogenic footprints, while downstream areas exhibited greater impacts. Additionally, this article proposes the potential use of a Water Quality Index tool to comprehensively assess water quality across all parameters in Himalayan water bodies, providing a roadmap for future environmental conservation in the Himalayas. This pioneering review represents a significant effort to understand Himalayan rivers geochemistry on a large geographical scale and emphasizes the need for integrated observation and consideration of river water quality across the entire Himalayan region, from high mountains to lowlands.

• Analyze SD level from the perspective of "input-output". • Analyze the factors that constrain SD level using obstacle factor results. • Using gravity models to analyze the spatial impact strength of SD level. • Using scenario simulation methods to determine the path of SD level. The rapid expansion of cities has brought new challenges to sustainable development (SD). Therefore, how to balance between SD and the economic growth has become the key to regional development. With the aim of enhancing the research system of SD level, founded on the deep research of SD level from a new perspective of "input-output" and the dynamic evolution law of SD level, this paper has explored the path for cities to improve their level of SD to achieve regional coordinated development. By virtue of the Super-efficiency Slack-Based Measure model based on unexpected output (unexpected super efficiency SBM model), it has measured the SD level of 21 cities in Sichuan from 2010 to 2019. Using methods such as equilibrium coefficient, obstacle analysis and gravitational model, this paper has studied the spatiotemporal evolution law of SD level and constructed six scenarios to simulate the future trend of SD level. The results have indicated that the level of SD in Sichuan is showing a gradual decline with significant constraints. The focus of SD in Sichuan is gradually shifting from Chengdu to a city cluster centered around Chengdu, Ziyang, and Meishan. In an ideal development scenario, the level of SD has significantly improved. This study has revealed the current status and potential of SD in Sichuan. In the future, with more concentration on the role of core urban agglomerations, Sichuan should adjust policies to address input–output barriers to promote SD throughout the province. [ABSTRACT FROM AUTHOR]

• This paper measures the CUEE with the Super-SBM with undesired outputs. • This paper explores the evolution of CUEE from a micro perspective with the CNA. • With the link prediction, the development trend of the CUEE is analyzed. • The Geodetector and GWR are used to excavate the influencing factors of CUEE. • This paper innovatively considers the impact of network attributes on the CUEE. Urban eco-efficiency (EE) refers to the ability of a city to balance economic growth with environmental protection through the optimal use of resources and environmental management, reflecting the city's performance in sustainable development. Quantitative EE analysis is a crucial evaluation criterion for measuring the process of sustainable development (SD). To assess the current state of sustainable development in China, this study employs the slacks-based super efficiency model (Super-SBM) to measure the the urban eco-efficiency in China (CUEE) of 284 cities. The study utilizes Kernel Density Estimation (KDE) and Spatial Autocorrelation Analysis (SAA) to investigate the fundamental patterns of CUEE in terms of inter-city differences and relationships. Complex Network Analysis (CNA) and Link Prediction methods are applied to examine the characteristics and future trends of the CUEE network. Additionally, Geodetector and Geographically Weighted Regression (GWR) are used to analyze the influencing factors of CUEE. The findings are as follows: Overall CUEE is relatively low but shows a steady increase. The spatial association network of CUEE is becoming more complex, with increasing association strengths. The Chengdu-Chongqing Economic Circle (CCEC) is expected to further enhance its spatial association strength and may emerge as a new core area. The effectiveness of the interactions among selected factors is greater than that of individual factors. Degree centrality (X1) is identified as a core explanatory factor influencing CUEE, showing a positive correlation with CUEE. Scientific expenditure (X5) is also positively correlated with CUEE. Local fiscal budget expenditure (X3), industrial output value of foreign-invested enterprises (X7), and total cargo transportation volume (X9) are negatively correlated with CUEE. The analytical framework and research conclusions of this study offer valuable insights into the development of urban ecological efficiency in China and provide constructive recommendations for promoting sustainable urban development. [ABSTRACT FROM AUTHOR]

• 21 cities (prefectures) in Sichuan Province were divided into 4 categories. • Considering the factors of government intervention, four scenarios are set. • The bottom-up carbon emission scenario analysis framework was established. • Explore low-carbon development path from the perspective of urban differentiation. Cities constitute a critical component of the "dual carbon" strategy, highlighting the importance of examining the carbon emission trends within various city categories to formulate a low-carbon development path. In this paper, 21 cities (prefectures) in Sichuan province were divided into 4 categories (service-based cities, resource-based cities, industry-based cities, and other cities) through K-means clustering, and the differences in driving factors of carbon emissions in different types of cities were explored. At the same time, baseline scenarios, technological innovation scenarios, controlled development scenarios, and mandatory emission reduction scenarios were set up to dynamically simulate the evolution path of urban carbon emissions in the next 30 years from the bottom-up. The results show that: (1) Input scale is the main driving factor for carbon emission growth in Sichuan province, while input carbon intensity is the leading factor for carbon emission reduction. Environmental input and population scale have opposite effects on carbon emission of different urban types. (2) Resource-based cities face challenges in completing the phased goal of "carbon peaking" under both baseline scenarios and controlled development scenarios. These cities have gradually become the predominant city type of emission source in Sichuan province, surpassing service-based cities. (3) Except for the normal scenario, Sichuan province can achieve the target of "carbon peaking" in other scenarios, and is expected to achieve the target of 90 % greenhouse gas reduction by 2050. (4) Among the 81 development paths derived from the urban scenario combinations, the path labeled M−B−C−M exhibits the lowest economic-ecological comprehensive impact coefficient. The bottom-up carbon emission scenario analysis framework established in this paper offers a novel perspective for the study of "carbon peaking" and can provide theoretical support for policymakers in devising regional low-carbon development strategies. [ABSTRACT FROM AUTHOR]

• We incorporate spatial factors affecting carbon emissions as drivers into the RF-CA model. • We change the constraints in the CA model for land use change prediction. • We predicted the land use change of Shanghai in 2025 under a low-carbon scenario. As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city's overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches. [ABSTRACT FROM AUTHOR]

• Mismatch between supply and demand for ecosystem services in Suzhou. • Ecosystem service flows are mainly directed from lakes to cities. • An ecological compensation model based on ecosystem services was established. • Provided compensation standards for developed areas. Understanding the spatiotemporal changes in ecosystem service value (ESV) under urbanization, as well as the supply–demand relationship between different regions, can provide a consultation for ecological compensation (EC) standards. Taking Suzhou, a typical city experiencing rapid urbanization in the Yangtze River Delta, as a case study, this paper analyzes the spatiotemporal changes in land use and ESV from 2000 to 2020. To quantify the ecosystem service flow (ESF), we apply the breakpoint formula and field strength model. Additionally, an EC standard is established, taking population, area and GDP into account while specifying compensation. The findings reveal that urbanization has led to a substantial increase in built-up land in Suzhou, accompanied by continuous reductions in farmland and water bodies. As a result, ESV decreased from 153.07 billion CNY to 138.81 billion CNY. Furthermore, the research identifies a spatial pattern where ESV increases with distance from the city center but decreases with distance from the lake center. This pattern suggests a directional flow of ESV from lakes to cities. Notably, ESF mainly occurs in the southwestern and central areas of Suzhou, with areas closer to Taihu Lake experiencing greater ESV transfer. The transfer value ranges from 5.11 and 32.57 billion CNY. There is an imbalance between the supply and demand of ecosystem services. Therefore, specific county-level cities in Suzhou, namely, the Kunshan District and Industrial Park, emerge as contributors of EC and should contribute 71.94 and 80.74 billion CNY, respectively, to other cities. By formulating a novel EC policy for Suzhou, this paper provides a scientifically informed reference for promoting sustainable development. [ABSTRACT FROM AUTHOR]

• Evaluating the Water Resources Constraint Intensity(WRCI) from the Perspective of High-quality Development. • An Analytic Hierarchy Process (AHP) model reformed by entropy technology and a multi objective fuzzy membership function were employed for indicator aggregation. • The spatiotemporal changes and correlation of UQDI, WRI, and WRCI in 78 prefecture level cities in the Yellow River Basin during 2011–2020 were analyzed. Promoting the high-quality development of urbanization is a crucial way to achieve sustainable development goals. Water resources are a rigid constraint for such development. However, There is still room for improvement in the research on the spatio-temporal pattern and key driving factors of high-quality urbanization development under the constraint of water resources. Aiming at the problem that the high-quality development of urbanization in the Yellow River Basin (YRB) is facing water resources constraints, this paper discussed the spatial–temporal pattern and key drivers of the high-quality development of urbanization in the YRB under water resource constraints by using the Analytic Hierarchy Process model reformed by entropy technology, multi-objective fuzzy membership function, spatial autocorrelation analysis and obstacle model. The results revealed that, first, we found the High-Quality Urbanization Development Index (UQDI) exhibited steady growth, while both the Water Resources Index (WRI) and the Water Resources Constraint Intensity (WRCI) initially increased and then decreased during the study period. Second, the UQDI displayed a dual-core pattern, with the Shandong Peninsula urban agglomeration and the Central Plains urban agglomeration serving as the cores. WRI exhibited relatively stable spatial distribution, with the southeast region outperforming the northwest. WRCI also demonstrated a relatively stable spatial distribution, resulting in two weak-constraint areas, represented by Shandong and Henan, and a strong-constraint area centered around Ningxia. Third, the UQDI, WRI, and WRCI exhibited spatial interdependence. The spatial interdependence of UQDI and WRI increased, while that of WRCI decreased during the study period. The three indexes also displayed a clear pattern of local clustering in space. Two low-value aggregation areas, namely Shandong and Henan, and a high-value aggregation area located in Ningxia, emerged during the study period. Last, the WRCI was primarily influenced by the fundamental conditions of water resources. The main influencing factors included per capita water resources, mean annual precipitation, total water resources, water resources modulus, and the total amount of foreign investment utilization. In light of the research findings, the paper proposes policy recommendations for promoting high-quality urbanization development in the YRB. This study provides decision-making guidance for countries and regions in arid areas to solve the water resources constraints on the high-quality development of urbanization. [ABSTRACT FROM AUTHOR]

[Display omitted] • A research framework of "potential supply/demand–pressure/accessibility–actual supply/demand" for urban park green space recreational services was proposed. • The framework quantifies the supply, demand, and flow of services in a theoretically and quantitatively consistent manner. • The framework makes the evaluation results of recreational services in different regions and the evaluation results of the same research area at different periods comparable.The number of characters in Highlights cannot be reduced any further, otherwise the content of the paper cannot be accurately expressed. • The number of characters in Highlights cannot be reduced any further, otherwise the content of the paper cannot be accurately expressed. Regular recreational activities in urban park green spaces are beneficial to the physical and mental health of residents. The supply capacity of, the residents' demand for, and the actual flow of recreational services must be distinguished and evaluated to promote the fair and reasonable layout of urban park green spaces. However, the unit dimensions of the supply, demand, and flow indexes of recreational services are often inconsistent or only in simple semiquantitative forms, which cannot be directly compared and analyzed. Thus, this study constructed a research framework of "potential supply/demand–pressure/accessibility–actual supply/demand" for recreational services, and the framework was tested using the central urban area of Xuchang as the experimental area. Results show the following: (1) A spatial mismatch exists in the supply–demand relationship of recreational services in the study area; this relationship is reflected in the semicircular layer structure from the central and southern areas to the periphery, changing from shortage of supply to oversupply. (2) The actual supply of recreational services is highly correlated with the number of people served, which can explain 50.38% of the change in the actual supply. (3) The potential demand for recreational services is highly correlated with the actual demand. It can explain 78.96% of the change in the actual demand. (4) Accessibility is a non-critical factor affecting the travel rate of residential quarters, while supply pressure is a key factor affecting the utilization rate of park green space. The framework can effectively identify important or low-utilization service-providing areas, unmet service-demanding areas, and important service-connecting areas. It is suitable for the study of the relationship between the supply, demand, and flow of user movement-related services. [ABSTRACT FROM AUTHOR]

China has abundant straw resources, but challenges in utilization persist. Utilization rates need improvement, and environmental pollution from straw burning remains a significant issue. Accurate and intelligent remote sensing classification of straw types is crucial for enhancing straw utilization and preventing straw burning. This paper proposed a new approach for the intelligent classification of maize straw types, using the DenseNet201 deep transfer learning algorithm based on RGB images captured by Unmanned Aerial Vehicle (UAV). The sample labels dataset was established for maize straw types, utilizing DenseNet201 deep transfer learning algorithm to pre-train the sample set. This pre-training facilitated model transfer and parameter initialization. Subsequently, the second round of deep transfer learning was performed to construct the final maize straw type remote sensing classification models using DenseNet201 deep transfer learning algorithm. This model and results were subsequently compared with maize straw type classification by the ResNet50 and GoogLeNet deep transfer learning algorithms, as well as maize straw type classification using DenseNet201, ResNet50, and GoogLeNet deep learning algorithms. The results showed that the accuracy of the pre-trained maize straw type deep transfer learning remote sensing classification model surpassed that of the untrained maize straw type deep learning remote sensing classification model, resulting in an enhancement of accuracy by 8.59%, 7.38%, and 1.28%, respectively. The DenseNet201 deep transfer learning model for maize straw types exhibited the highest accuracy with the overall accuracy of 95.57%, and the kappa coefficient of 0.9410. Hence, the DenseNet201 deep transfer learning classification of maize straw types enabled the attainment of intelligent remote sensing recognition of maize straw types. The classification methodology, model, and results presented in this paper can serve as valuable technical references, offering essential information support for agricultural and environmental protection departments actively involved in the comprehensive utilization of straw resources and atmospheric environmental protection efforts. [ABSTRACT FROM AUTHOR]

• A review of 400 papers resulted in 130 indicators on mountain ecosystem services (ES) • Regulating and provisioning ES were more popular and supporting ES least mentioned. • Regional and local scales and ecological evaluations were the most frequent. • Expert-based analysis identify 13 indicators with high values of usability. • There is a need necessity to standardize high-quality metrics in ES assessment. Ecosystem services (ES) assessment is crucial in ecology, with numerous studies seeking to evaluate them. Despite the abundance of methods and indicators, standardization is lacking, hindering comparability and progress in ES understanding and monitoring. This paper reviews indicators used in scientific literature to evaluate mountain ES and then examined whether the most used indicators are also the best. Using ISI Web of Knowledge we searched papers published between 2015 and 2020 containing "ecosystem services" AND "mountains" and we selected 400 papers effectively applying at least one indicator to evaluate ES. For each article, we extracted the following information: type of ES evaluated; indicator(s) used; input data used; type of value-domain (ecological, economic or social); scale of analysis; country; mapping; and management suggestions. From the literature, we extracted a list of 130 most frequently used indicators. The results indicated that regulating services were the most frequently assessed ES, followed by provisioning, cultural, and lastly supporting. The scale of analysis was mainly regional (51%) and local (40%), while studies at national scale were less frequent (9%) and only 2 studies were at global scale. Mountain areas most studied were in Europe (50%) and Asia (31%). Ecological value-domain was the most frequent used (55%), followed by social (26%) and economic (18%). 84% of studies considered only one dimension of the value and few studies combined multiple value-domains (15%). Almost half of studies mapped ES and around one third provided management suggestions. We examined the quality of indicators based on six criteria evaluated by experts in the field: significance, simplicity, cost, replicability, ease of interpretation and policy relevance. Indicators used exhibit significant diversity, and there is no clarity in nomenclature. There are cases where the indicators used represent inadequately the ecological parameters to be measured. Although many indicators score high in some of the properties evaluated, only 13 indicators perform well in all properties. These indicators have a universal value both in terms of semantics, but also in terms of properties and should be promoted for standardization among ES assessments. We envisage the necessity to condense the array of indicators commonly used down to a small set of standardized high-quality metrics. [ABSTRACT FROM AUTHOR]

• Inner and marginalized areas: an increasingly relevant issue at European level. • Inner areas as socio-ecological systems (SES): an integrated sustainability approach. • An innovative methodology to design a system of indicators of sustainability. • Theoretical background based on Ecological Economics and strong sustainability. • Multi-criteria framework for a standardized social-biophysical evaluation grid. The phenomenon of inner peripherality is on the rise in Europe. Inner peripheries can be defined as peripheral rural areas experiencing territorial disconnection and progressive marginalization given their distance to urban centres, where the supply of services is concentrated. Assessing and comparing the sustainable development of these areas according to nuanced and integrated social-biophysical perspectives is crucial to highlight their genuine long-term sustainability potential and critical aspects. Moreover, it is essential to monitor that the socio-economic development of the latter goes hand in hand with territorial stewardship and an appropriate management of their extensive natural endowments. To achieve these objectives, this paper illustrates an innovative methodology to design a multi-criteria evaluation framework named PAISDA (Peripheral Areas Integrated Sustainable Development Assessment). The framework, based on the theoretical background of ecological economics, makes it possible to monitor the sustainable development of inner and marginalized areas according to a "post-growth" approach. It also allows a shift towards a strong sustainability perspective by assessing the phenomenon in an integrated way, which combines social and biophysical dimensions. This can help to design more robust and better targeted policies for these areas, thereby improving local strategic planning. The assessment process is as follows: first, the values of lower order components are computed through a reflective measurement model, then aggregated to form the values of higher order components, which are used as criteria in the last phase of multi-criteria decision analysis (MCDA). The choice of normalization and aggregation methods responds to methodological coherence. The paper describes a step-by-step procedure for applying the PAISDA framework in any European country, providing an illustrative example of its implementation in relation to Italian inner areas. [ABSTRACT FROM AUTHOR]

• Compared with rural, urban construction lead to higher LER and LUC. • Combining "risk-conflict" evaluation with ESP construction. • Concerned and constructed the ESP of Dongxihu Polder. • Proposed sustainable strategies for polder landscapes adapted to urbanization. Jianghan Plain is an important grain-producing area in China, and the transformation of the natural environment by the long-term polder activities of the people in this area has created a characteristic polder landscape. After 2000, urbanization has led to the destruction of ecosystems in these polder landscapes, especially in sensitive areas at the urban–rural interface. ESP can help mitigate this threat by systematically identifying and connecting ecologically significant areas to enhance ecosystem stability and sustainability. In this paper, taking Dongxihu Polder as an example, we apply multi-source remote sensing data to develop LER and LUC models. Combining these with MCR model, we construct an ESP for Dongxihu Polder. The study shows that (1) the growth of LER and LUC in Dongxihu Polder is characterized by "strong dynamics, high complexity and weak protection", which is closely related to the urban expansion of the urban–rural boundary area; (2) Watersheds, woodlands, and farmlands play an important role in controlling LERs and LUCs, so we identified 33 ecologically important source areas that are mainly concentrated in these regions; (3) In this paper, 46 ecological strategic nodes and 16 ecological corridors were extracted to construct the Dongxihu Polder ESP of "one ring, five axes, multiple points and multiple chains", and suggested specific optimization strategies. The study provides feasible ecological management policy recommendations for the protection as well as sustainable development of Dongxihu Polder. [ABSTRACT FROM AUTHOR]

• Tailored set of 116 regional indicators for monitoring EU's 2030 SDGs. • Harmonized standardization and customization for robust regional sustainability monitoring. • Emphasis on fostering regional data capacities and infrastructure for effective monitoring. • Facilitates strategic policy alignment with significant EU initiatives such as the European Green Deal. • Encourages mutual learning and collective growth among European regions. The adoption of the 2030 Agenda for Sustainable Development by the United Nations General Assembly, encompassing 17 Sustainable Development Goals (SDGs), established a universal framework for addressing global challenges. Within the European Union (EU), the commitment to these goals has prompted the integration of the SDGs into a strategic framework for sustainable and inclusive growth. Recognizing the need for localized and detailed monitoring to capture the nuanced progress and challenges across Europe's diverse regions, this paper proposes a comprehensive set of regional indicators specifically designed for the European context. Through a systematic review of existing SDG monitoring frameworks at different territorial levels and an extensive methodological process, the paper identifies 116 indicators that address 75 SDG targets. This tailored set is derived from a combination of national, regional, and supranational sources. The paper discusses the critical balance between standardization for comparability and customization to accommodate unique regional characteristics. The proposed indicator set is evaluated for its capacity to reflect the holistic vision of the SDGs while allowing for effective regional benchmarking. The research emphasizes the need for robust regional data infrastructure, the importance of aligning policies with broader sustainability objectives, and the dynamic nature of indicators that can adapt to societal changes such as demographic shifts. Finally, the paper highlights the significance of a pragmatic and adaptive regional approach to SDG monitoring. The proposed indicator set is a strategic tool for policymakers, stakeholders, and practitioners, guiding Europe's regions towards a sustainable future and contributing to the global effort to achieve the SDGs by 2030. [ABSTRACT FROM AUTHOR]

Unconventional water serves as a bridge to water sustainability. However, many developing nations still have a long way to go in terms of unconventional water utilization. Different regional characteristics lead to different consumption capacities for unconventional water. Consequently, more unconventional water use (UWU) may not necessarily be positive for alleviating water poverty. However, there is a significant research gap in this field. This paper aims to answer three key questions: “Whether UWU consistently alleviates water poverty?” “Is this effect spatially heterogeneous?” and “What role do economic factors play in addressing water poverty?” For that, this paper focused on 30 provinces in China, with the sample period spanning from 2006 to 2021. To identify the mechanisms through which UWU alleviates water poverty, this paper employed a panel fixed-effects model using the Water Poverty Index (WPI) as the dependent variable and the square of UWU amount as an independent variable. The results indicate a non-linear impact of UWU on WPI, with the significance of impact influenced by GDP per capita (PGDP). Furthermore, threshold regressions were conducted with PGDP as the threshold variable. The results revealed a double-threshold effect of PGDP in the impact of UWU on WPI, displaying “U” or inverted “U” shape as PGDP develops: When PGDP is less than or equal to RMB 13,574, UWU demonstrates a negative effect on WPI; when PGDP ranges from RMB 13,574 to RMB 53,653, the effect turns positive; however, when PGDP exceeds RMB 53,653, the effect turns back to negative. The findings confirm that more UWU is not always better. Sustainable utilization plans of water resources must be tailored to local conditions, especially considering the unique characteristics of the regional economy.

Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China’s Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future.

Land disputes pose significant challenges to social stability and development. In this paper, land dispute intensity (LDI) is measured at the provincial level in China from 2009 to 2018 and its spatiotemporal evolution characteristics and influencing factors are explored. The ordinary least squares(OLS), spatial durbin model (SDM), geodetector model, and panel threshold model are used to explore the spatial spillover effects of LDI and its potential non-linear relationship with socio-economic factors. The results reveal that LDI is spatially distributed in a decentralized form, with local areas showing the structural characteristics of “single core, multiple clusters”. The LDI exhibits a significant positive spatial autocorrelation and follows a “logarithmic” upward trend over time. The urbanization rate (UR), social security expenditures (SSE), and the number of land and resources institutions (NLRI) are important driving forces affecting LDI. The SSE and NLRI have a single threshold effect on the LDI, with a “V” shaped weakening trend, and the UR is an important factor causing nonlinear effects. Interestingly, the effect shifts from inhibition to stimulation when the SSE and NLRI cross the corresponding threshold value. This paper can provide new insights into the governance of land disputes.

An integrated water sustainability assessment is conducive to realizing the optimal allocation and efficient water utilization, and alleviating the water crisis. Existing research mainly appraises water quantity and water quality as unidimensional or in combination, without considering the water benefit, and few studies have assessed the regional water sustainability based on an integrated evaluation multidimensionally. Therefore, this paper innovatively introduces water benefit to construct a three-dimensional quantity-quality-benefit model (QQBM) to evaluate water sustainability in line with the water footprint (WF) theory and water resources balance sheet (WRBS). The impact of the coupled coordination relationship among water quantity, water quality, and water benefit on the water sustainability evaluation is further analyzed by introducing the coupled coordination degree model (CCDM). This paper takes the Yangtze River Economic Belt (YREB) as an example and makes a spatio-temporal analysis of the water sustainability in its 11 provincial capitals during 2010-2021 from a single dimension and a three-dimensional perspective, respectively. The results found that: (1) From a single dimension, the water sustainability in the 11 provincial capitals in the YREB during 2010-2021 is at a medium level, with better water benefit sustainability, moderate water quantity sustainability, and horrendous water quality sustainability. Among them, the water sustainability is the best in Guiyang and Hangzhou, while the worst in Shanghai. (2) From a three-dimensional perspective, the water sustainability in the 11 provincial capitals from 2010 to 2021 is horrific. Among them, the water sustainability is the best in Kunming, Changsha, Nanjing and Shanghai, while the worst in Wuhan and Hefei. (3) The degree of coupling coordination between water quantity, water quality and water benefit significantly influence the water sustainability in the 11 provincial capitals of the YREB. The three-dimensional assessment model QQBM constructed in this study is more comprehensive and objective than the single perspective assessment. The findings in this paper can help other regions to conduct similar water sustainability assessments and inform policy recommendations.

The invasion of exotic ant species in China presents significant challenges to ecosystems, agriculture, and the economy. This paper provides an in-depth analysis of China's ongoing battle with exotic ants, examining the factors contributing to their introduction and establishment. It explores the responses implemented by the decision makers, including capacity building, establishment of research institutions, and legislative measures. Limitations and gaps in the current strategies are identified, highlighting the need for regional collaboration, increased awareness, and strengthened early detection and response systems. Furthermore, the paper emphasizes the importance of conducting research to understand various exotic ant species' ecological and economic impacts, facilitating the development of targeted and effective management approaches. By adopting a comprehensive and coordinated approach, China can mitigate the impacts of ant invasions and safeguard its biodiversity, agriculture, and economy. This analysis underscores the significance of collective efforts in addressing the ongoing battle with exotic ants and preserving the well-being of ecosystems, economies, and the society.

The balance between the supply and demand of ecosystem services (ESSD) is important for sustainable regional development. The hilly regions of south China have rich natural resources and are rapidly being urbanized, which significantly impacts sustainable development in the region. Therefore, how to analyze ESSD from the perspective of social ecology is imperative. Ganzhou region, which is a typical hilly region in southern China, as an example, this paper creatively integrated ESSD into the social-ecological system (SES) framework, analyzed the spatial and temporal changes of ESSD in 2005, 2010, 2015, and 2020, and constructed a system of indicators from the SES, and analyzed the driving factors of ESSD, so as to provide a reference for balancing ESSD. Based on the classical SES framework proposed by Ostrom, this study first analyses the social-ecological system profile of the Ganzhou region at the macro-scale and constructs an SES indicator system. The innovation of combining the SES framework and ecosystem services lies in integrating the social and ecosystem perspectives and merging these two concepts to understand better and manage the relationship between humans and the natural environment. It provides a comprehensive analytical approach and decision support tool for achieving sustainable development. Our results demonstrate that: (1) From 2005 to 2020, ecosystem services in the study area were highly valued, lower areas had homogeneous distribution characteristics, total demand displayed spatial differentiation, there were high-value areas in the midwest, and low-value areas were concentrated in the region’s boundary. (2) There are obvious supply and demand deficits in the southeast and east of the study area, while supply–demand is equal in the north and supply exceeds demand in other regions. From 2005 to 2020, the overall coupling coordination degree of ESSD in the study area was lower than 0.5, indicating a mild to moderate imbalance. (3) The supply of ecosystem services (ESS) was primarily driven by carbon storage, habitat quality, and water yield, while the demand was primarily driven by forest and grassland areas. Factors related to the ecosystem, resource unit, resource system, social system, governance system, and actor all have experienced two-factor interactions, which can explain up to 99% of ESSD. Based on the SES framework, this paper studies the relationship between ESSD in typical areas of the southern hills to provide a reference for research on ESSD in relevant areas and provide a scientific basis for the Chinese government to evaluate ecological protections and improve compensation policies, which is important for ensuring China's ecological security.

• A practical and feasible protection strategy for EC maintaining in highly urbanized areas was proposed. • Key patches for EC maintaining were identified by using stepping stone and complex network theories. • The protection rate for key patches by the new policies were assessed. Maintaining and restoring ecological connectivity (EC) are important measures of mitigating habitat isolation caused by urbanization. Considering the prominent contradiction of land use in highly urbanized areas, the EC protection measures proposed in the previous studies, such as expanding the ecological sources and widening the ecological corridors, are unrealistic. By using the stepping-stone and complex network theories, this paper simulated the ecological network (EN), evaluated the centrality of each ecological source and stepping-stone, and analysed the network robustness under different damage scenarios, then identified the optimal strategy and key patches for EC maintaining. Meanwhile, this paper evaluated whether the key patches are protected by China's new policies, which are, Ecological Protection Red Line (EPRL) and the Three Lines One Permit (TLOP). The results were as follows: (1) The EN is composed of 53 ecological sources and 291 stepping-stones, with 591 links between them. (2) The network stability can be optimally maintained by prioritizing the protection of stepping-stones with high centrality. (3) The 53 ecological sources and 51 stepping-stones with the highest centrality can ensure the stable operation of the EN, that is, they are key patches for EC maintaining. (4) Compared with EPRL, the protection rate for ecological sources and stepping-stones are significantly improved by TLOP; however, stepping-stones with high centrality require stronger protection. This study enriched the research cases of complex network theory applied in landscape ecology, and provided references for the improvement of policies in the future. [ABSTRACT FROM AUTHOR]

• Ecosystem services are quantified at large scales and long time series in NE China. • The trade-offs and synergies among ecosystem services are characterized. • Human activities are the dominant driving factors of provisioning services. • Synergistic optimization paths of production-ecological functions are proposed. In Northeast (NE) China, the largest commodity grain base and natural forest area in China, both agricultural production and ecological protection require attention. In recent years, land degradation in NE China has increased, seriously affecting the production-ecology synergy. In this paper, four key ecosystem services (ESs) in NE China are quantified: provisioning, water conservation (WC), soil conservation (SC) and sand fixation (SF), and the spatiotemporal evolution characteristics and trade-offs and synergies (T&S) of ESs are analyzed. The driving factors of provisioning services and the characteristics of T&S are considered, and the county zoning scheme and the corresponding production-ecological function synergistic optimization paths are proposed. The results show that (1) the provisioning, WC and SF services in NE China have slightly increased in the past 20 years, and the provisioning in the Greater-Khingan-Mountains-Region (GKMR) and Lesser-Khingan-Mountains-Region (LKMR), the WC in the LKMR, and the SF in the Liao-River-Plain (LRP) have more obviously increased. The SC service has slightly decreased, especially in the Changbai-Mountains-Region (CBMR). (2) The provisioning service in NE China mainly shows a synergistic relationship with WC and SF, accounting for 79.1 % and 62.9 % of the area, respectively, and a trade-off relationship with SC, accounting for 52.54 % of the area. (3) Human activities (HA) are the dominant driving factor of the provisioning service change in NE China, with an impact degree of 62.65 %. The LKMR is an exception, as climate change (CC) dominates. The LRP, Songnen-Plain (SNP) and GKMR have high degrees of HA. (4) The number of synergistic optimized (SO), light optimized (LO) and trade-off limited (TL) counties accounted for 19.0 %, 61.7 % and 19.3 %, respectively. Among them, the SO type counties should prioritize improving provision and grain production capacity, the LO type counties should protect basic farmland and decrease trade-offs between ESs, and the TL type counties should improve ecological functions and strengthen ecological protection and restoration. This paper clarifies the main contradictions of ESs in NE China and provides an important scientific basis for ecological protection and restoration, which is important for ensuring food and ecological security and realizing the ecological and efficient sustainable utilization of black soil. [ABSTRACT FROM AUTHOR]

[Display omitted] • Integrated dataset of major ions and trace elements for Nepal Himalayan rivers basin. • Rock weathering is the primary factor controlling ion concentrations. • Anthropogenic impacts become significant in densely populated lowland basins. • Water in most rivers is safe for drinking, except for densely polluted urban Bagmati. • A uniform and comparable Himalayan Water Quality Index is proposed. Rivers originating from the Himalayas play a crucial role as primary water sources for a significant proportion of the population in Asia downstream. This paper presents a comprehensive synthesis of hydrogeochemical data, incorporating major ions and trace elements from 153 papers spanning 2000 to 2023, with a detailed analysis of 20 papers specific to Nepal Himalayan rivers. To bridge the research gap due to sparse data, we aimed to enhance inclusivity by amalgamating both seasonal and one-time datasets, computing mean values for singular instances, and employing grand means for multiple seasonal data points. Our findings highlight varied research attention across different river basins, with the eastern Koshi Basin receiving extensive attention, while the middle Gandaki and Bagmati Basins garner moderate attention, and data scarcity observed in the western Karnali Basin. Predominant ionic composition, notably Ca2+ and HCO 3 –, reflect lithological influences, primarily driven by rock weathering. Although anthropogenic impacts remain minimal in most basins, certain lowland areas with higher population densities exhibit increasing significance. Trace element contamination, notably Cd, Cu, Sr, and Zn, poses ongoing threats, both from natural and anthropogenic sources. Water quality assessments conducted for agricultural and drinking suitability indicated good status, except in the densely polluted urban Bagmati stem. Health and ecological risks are low, as determined by pollution indices such as Pi, NPI, HI, and CI. The Bagmati River's middle segment, with high population density and moderate agricultural activity, shows pronounced anthropogenic footprints, while downstream areas exhibited greater impacts. Additionally, this article proposes the potential use of a Water Quality Index tool to comprehensively assess water quality across all parameters in Himalayan water bodies, providing a roadmap for future environmental conservation in the Himalayas. This pioneering review represents a significant effort to understand Himalayan rivers geochemistry on a large geographical scale and emphasizes the need for integrated observation and consideration of river water quality across the entire Himalayan region, from high mountains to lowlands. [ABSTRACT FROM AUTHOR]

Urban green spaces have long been cherished as the “lungs of the city”, it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops.