Ecosystem vulnerability is a central issue in research into a globally changing climate and the sustainability of development, and vulnerability measurement and evaluation is essential for understanding the structure and function of ecosystems. Due to the saturation of EVI and GPP in areas with high vegetation cover. To address this issue, this study proposes a more comprehensive perspective than single indicators or weighted multi-indicator approaches. By coupling the 2000-2020 long-term NDVI and NPP indicators to calculate the Ecological Vulnerability Index, and combining it with the Geographic Detector to systematically assess the spatial pattern of ecological vulnerability and its driving mechanisms. Overall EV was high, with the area of moderate and above-grade vulnerable areas accounting for about 66%, and the vulnerability decreasing from north to south. The overall vulnerability of woodlands is low, with No, Slight and Light being the most vulnerable areas, accounting for over 95% of the area. The overall vulnerability of grassland is high, dominated by Slight, Light and Medium vulnerability, with an area share of more than 85%. Vegetation cover and precipitation are the main controlling factors affecting EV, with an explanatory power of 0.59 (0.62) and 0.48 (0.51) respectively, other factors have less influence on EV overall (<0.21).

In the aspect of coordinating land use and ecological security in the urbanizing areas, conventional methods are not applicable because of the weakness in addressing landscape ecological risks resulted from drastic land use changes. Attempting to align land use management with landscape ecological risk control in the five state-level urban agglomerations in Yellow River Basin, we analyzed the spatiotemporal changes in land use, identified landscape ecological risks from 1995 to 2020, and investigated the spatiotemporal heterogeneity and interactions of the revealed risk drivers. The results showed, the highest-risk area in the Jiziwan Metropolitan Area increased by 6.1 % in the study period, representing an increase of ten times that in the other agglomerations. Construction land proportion exhibited a stronger positive impact on the ERI in certain local areas. GDP per capita exhibited a broader spatial influence in positively affecting the ERI. Population density indirectly affects ERI mainly through NDVI, construction land, and GDP. Regarding the spatial characteristics and driver interactions of ecological risks, tailored land use measures were proposed for each urban agglomeration by concentrating on the highest-risk areas, areas with rapid risk variation, and ecologically vulnerable areas. This study demonstrates that a clearly defined landscape ecological risk assessment can support improved land use planning and more targeted zoning strategies for ecological security. It offers a methodological reference for identifying ecological risk drivers in large-scale urbanized regions and provides a foundation for implementing differentiated land use and risk management strategies in major river basins.

Carbon emissions are a key driver of climate change, with substantial implications for human well-being. A central question is the role of technological progress in achieving carbon peaking and modeling future scenarios. Therefore, we aimed to verify that technological progress accelerates CO2 emissions peaking in the megacity of Shanghai. To this end, we combined a genetic algorithm and a back-propagation neural network (GA-BPNN) to predict CO2 emissions from 2023 to 2045 under three scenarios: business as usual, technological progress, and technological progress with energy substitution. Scenario parameters were quantitatively determined using the quartile method, based on historical rates of change for key influencing factors. The results showed that technological progress had a limited impact on reducing CO2 emissions. Technological progress accelerated the peaking of CO2 emissions in Shanghai. Technological progress brought the emissions peak forward by four years (2030 to 2026), reducing emissions by 0.9 %. Energy substitution further advanced the peak to 2023, cutting emissions by 3.71 %. The relationship between technological progress and CO2 emissions exhibited a rebounding effect, indicating an inverted U-shaped pattern. Our findings indicate that long-term investments in technological progress and energy substitution are crucial for reducing carbon emissions.

Exploring the trend of long time-series ecological quality evolution and spatial differentiation of influencing factors in Guiyang is of great significance for realizing regional ecological protection and high-quality development strategies. Based on the 7-period Landsat remote sensing images from 1991 to 2020, the remote sensing ecological index （RSEI） of Guiyang from 1991 to 2020 was calculated using the GEE remote sensing big data platform, and a geodetector, Hurst index, and coefficient of variation with different random sampling quantities and classification strategies were used to analyze the evolutionary pattern of ecological quality, change trends, and spatial differentiation influencing factors. The results showed that ① The ecological quality of Guiyang in the past 30 years was mainly medium and good, showing a wave-like pattern of change, with the highest and lowest values occurring in 2020 （mean value 0.58） and 2010 （mean value 0.47）, respectively, and the overall trend of the RSEI in the past ten years was good, with a spatial trend of decreasing distribution from the northeast to the southwest. ② The domain of values of the coefficient of variation for the RSEI in Guiyang was in the range of （0-2）, of which 46.61% of the area was in high fluctuation change, and the overall volatility of the RSEI was large； the mean value of the Hurst index was 0.59, and the area greater than 0.5 accounted for 73.98%, most of which showed weak persistence, and the future trend of change was the same as that of the past 30 years. ③ Different classification methods and random samples affect the q-value results of the geodetector, but the trend of the size ordering of the explanatory power of different factors was generally consistent. Land use, nighttime lighting index, slope, and population density indicators had stronger explanatory power for RSEI spatial differentiation； factor interaction detection was two-factor enhancement and nonlinear enhancement； and the interaction between land use and other factors was most favorable for explaining RSEI spatial differentiation.

Water scarcity constrains agricultural production and leads to significant economic losses. However, existing water scarcity risk (WSR) assessments often overlook the combined effects of water availability, quality, and efficiency, as well as potential mitigation benefits. This study develops an integrated assessment framework that incorporates these factors to evaluate agricultural WSR in the Yellow River Basin, a critical grain-producing region in China. The framework quantifies both direct economic losses in agriculture and indirect impacts on non-agricultural sectors through intercity trade, while also estimating mitigation benefits. Results show that insufficient water quality significantly amplifies economic losses, reaching 1189.9 billion CNY, compared to 391.0 billion CNY when only water quantity is considered. Key supply chain sectors, including food and tobacco processing, chemicals, and textiles, account for 56.6 % of total indirect agricultural WSR exports. Among mitigation measures, improving water quality and water-use efficiency reduces economic losses by 72.5 billion CNY and 53.2 billion CNY, respectively. Meanwhile, utilizing mine water in coal-rich regions and reclaimed water in urban centers can significantly reduce economic losses, with Ordos and Qingdao experiencing reductions of 75.4 % and 39.1 %, respectively. This framework provides a comprehensive approach to agricultural water management, integrating economic loss estimation with mitigation benefits to support sustainable water resource management.

There has been debates on whether China's environmental governance is authoritarian, which has raised doubts about whether China's environmental governance can achieve a holistic governance model. To resolve the dispute, a thorough analysis was conducted using content analysis and manual coding of the Hunan Province River Chief System case. Field investigations were conducted from 2019 to 2022, during which 46 in-depth interviews were conducted with government officials involved in RCS. By analysing data from two rural counties and two urban areas, three key mechanisms for achieving holistic governance have been identified:1) cross departmental and cross jurisdictional integration; 2) Extensive information sharing and public participation; 3) two-way collaborative governance driven by goal alignment and accountability measures. This study also identified factors that promote holistic governance: 1) The strength of the CPC plays a key leading role; 2) Coordination and interaction of maintaining political party power, public participation, and bureaucratic accountability; 3)The accountability system embedded in the target system and performance evaluation is a key success factor; 4) Combination of voluntary and coercive tools to achieve governance goals. Research has shown that China adopts a state led environmental governance model. This study enriches the literature on authoritarian environmentalism and holistic governance.

The coordination between poverty alleviation and ecological protection is both a crucial requirement and a long-standing challenge for sustainable development. China’s implementation of a targeted poverty alleviation strategy has completed the task of eliminating extreme poverty. However, the evaluation of the corresponding ecosystem changes in the entire poverty-alleviated areas is still insufficient. This study investigated the spatiotemporal changes in ecosystem vulnerability across China’s 832 national poverty-stricken counties from 2005 to 2020. A habitat–structure–function framework was applied to develop an evaluation index, along with a factor analysis of environmental and socio-economic indicators conducted through the Geodetector model. Finally, the implications of China’s practices to balance poverty alleviation and ecological protection were explored. The results show that ecosystem vulnerability decreased from 2005 to 2020, with an even greater decrease observed after 2013, which was twice the amount of the decrease seen before 2013. The post-2013 changes were mainly brought about by the enhancement of the ecosystem function in critical zones such as the Qinghai–Tibet Plateau Ecoregion, Yangtze River and Sichuan–Yunnan Key Ecoregion, and Yellow River Key Ecoregion. From 2013 to 2020, the influence of the gross domestic product (GDP) surpassed that of other factors, playing a significant positive role in diminishing ecosystem vulnerability in the three regions mentioned. The results suggest that China’s poverty-alleviated areas have found a “win–win” solution for poverty alleviation and ecological protection, that is, they have built a synergistic mechanism that combines government financial support with strict protection policies (e.g., more ecological compensation, eco-jobs, and ecological public welfare positions for poor areas or the poor). These findings elucidate the mechanisms behind China’s targeted poverty alleviation outcomes and their ecological implications, establishing a practical framework for coordinated development and environmental stewardship in comparable regions.

The Lijiang River Basin (LRB) is a karst ecosystem that presents unique challenges for agricultural land planning. Evaluating cultivated land suitability based on natural factors is critical for ensuring food security in this region. This study was based on the cultivated land distribution data of the LRB in the China Land-Use and Land-Cover Chang dataset, selecting 22 restriction factors across five dimensions: climate, topography, soil, hydrology, and social conditions, and the suitability of cultivated land (paddy fields and drylands) in the LRB was evaluated using the MaxEnt model to further identify the main restricting factors affecting the spatial distribution. The research showed that (1) For paddy fields, high-suitability areas covered 2875.05 km2, medium-suitability 1670.58 km2, low-suitability 3187.25 km2, and non-suitable 9368.46 km2. The main restriction factors were distance to villages, slope, surface gravel content, soil thickness, soil pH, and total phosphorus content. (2) For drylands, high-suitability areas covered 3282.3 km2, medium-suitability 2260.93 km2, low-suitability 4536.27 km2, and non-suitable 6836.85 km2. The main restriction factors were soil thickness, distance to roads, surface gravel content, elevation, soil pH, and soil texture. This research can provide a scientific basis for the layout of food security and planning agricultural land use in the LRB.

China is one of the world’s largest producers and consumers of cement, making carbon emissions in the cement industry a focal point of current research and practice. This study explores the prediction of cement consumption and its influencing factors across 31 provinces in China using the RF-MLP-LR model. The results show that the RF-MLP-LR model performs exceptionally well in predicting cement consumption, with the Mean Absolute Percentage Error (MAPE) below 10% in most provinces, indicating high prediction accuracy. Specifically, the model outperforms traditional models such as Random Forest (RF), Multi-Layer Perceptron (MLP), and Logistic Regression (LR), especially in handling complex scenarios or specific regions. The study also conducts an in-depth analysis of key factors influencing cement consumption, highlighting the significant impact of factors such as per capita GDP, per capita housing construction area, and urbanization rate. These findings provide important insights for policy formulation, aiding the transition of China’s cement industry towards low-carbon, sustainable development, and contributing positively to achieving carbon neutrality goals.

Anthropogenic activities have substantially elevated nitrogen (N) deposition globally and affect ecosystem processes, including soil carbon (C) storage potential. Phosphorus (P) can become a limiting factor for plant production in instances of N deposition, yet the responses of ecosystem C cycles to P enrichment are poorly understood, particularly in sensitive alpine ecosystems. We conducted a short-term field study to appraise the effects of N and P addition on ecosystem CO2 emissions and CH4 uptake in three typical alpine grasslands, alpine meadow, alpine steppe, and cultivated grassland on the Qinghai-Tibet Plateau (QTP). The closed chamber technique was employed to monitor the fluxes of CO2 and CH4. Environmental factors, including plant biomass and diversity and soil nutrients, and the abundance of C-cycling genes were analyzed to investigate the factors regulating CO2 and CH4 fluxes. The results showed that: (i) N and P addition tended to increase CO2 emissions and CH4 uptake. Furthermore, P addition weakened the positive effects of N on CH4 uptake across the three grasslands, but the interaction of N and P addition on CO2 emissions varied across the three grasslands. (ii) N and P addition affected the fluxes of CO2 and CH4 both directly and indirectly through their impacts on soil and plant factors rather than C-cycling functional genes. These results indicate that in the context of increasing N deposition in the QTP, short-term P addition is not an effective method for mitigating global warming potential and improving soil C sequestration in alpine grassland ecosystems.

Due to the Sustainable Development Goals (SDGs) being designed at both national and globally applicable level, it is challenging to adequately reflect the local context and characteristics in different urban regions without fully utilizing big earth data. To effectively address this issue, this study localized 73 urban indicators for 13 SDGs and both assessed and forecasted urban sustainability across 18 cities in Hainan (2010-2030) using big earth data. Our analysis specifically focused on indicator score, goal score, SDG index, SDG spatial spillover effect, and trade-offs and synergies. The results indicated an overall upward trend in sustainable development in Hainan province, predicting achievement of the SDGs by 2030. The SDG index and spatial spillover showed a pattern of 'high in the north and south, low in the middle'. While synergies outweighed trade-offs, trade-offs increased at a faster pace. More specifically, the average SDG index increased from 29.85 in 2010-60.09 in 2018, with a projected score of 89.76 by 2030. During 2010-2018, the synergy-to-trade-off ratio declined from 3.91-1.84, driven by a trade-off growth rate 2.03 times higher than synergy. Our work provides a valuable localized case method, and data support for monitoring sustainable development at the global urban level.

The identification and restoration of damaged ecosystems are key to achieving ecological conservation and sustainable. Hainan Island is experiencing a serious crisis of biodiversity and habitat degradation. Therefore, its ecological conservation has become a priority and challenge for China. This study aimed to construct a multi-level ecological security pattern (ESP) based on the synergy of multiple ecosystem service functions and identify important ecological elements and ecological restoration areas. Based on the InVEST model, the circuit theory model, and a series of GIS spatial analysis methods, the importance of ecosystem functions (biodiversity maintenance, water conservation, carbon sequestration, and soil conservation) was evaluated, and ecological sources, ecological corridors, ecological pinch points, and ecological barrier points were identified. The results are as follows: 1) The best habitats in Hainan Island were distributed in the central mountainous area with diverse ecosystems, with an area of 10982.5 km2, accounting for 34.25% of the total suitable habitats. Low-level habitats are mainly distributed on tableland and coastal zones. Human disturbance is the direct cause of landscape patch fragmentation in low-level habitat areas. 2) A total of 65 large ecological sources with a total area of 8238.23 km2 were identified, which were concentrated in the biodiversity and water conservation areas in the central part of the island. 3) Crucial areas in Hainan Island mainly comprised forests and water bodies. Ecological corridors radiated across the entire area in the form of a spider web and connected all important ecological patches, including 138 ecological corridors (73 primary ecological corridors and 65 secondary ecological corridors), 222 ecological pinch points, and 198 ecological barrier points. In addition, the identified areas for restoration are primary areas in urgent need of protection and restoration. In general, the ecological pinch points are natural conservation areas supplemented by anthropogenic restoration, and the ecological barrier points demand equal attention for anthropogenic restoration and nature conservation. The ecosystem protection plan developed in this study will enrich the theoretical achievements of territorial spatial ecological planning in Hainan Island, and provides clear guidance for alleviating the contradiction between land use and economic development in Hainan Island.

To explore the spatio-temporal variation and transfer of ecosystem service value (ESV) in Jiuquan City from 2005 to 2020 to help ecological development. Based on the equivalent factor method and grid analysis to analyze the spatial and temporal changes in the value of ecosystem services in Jiuquan City, the fracture point model and field strength model were applied to calculate the transfer of ecological service value in seven districts and counties of Jiuquan City.From 2005 to 2020, the ESV of Jiuquan City showed an overall increasing trend, and all individual ESVs showed an increasing trend, with the ESV of regulating services showing the most significant growth. The top three secondary ESVs are: hydrological regulation, climate regulation, and environmental purification. The value of regulating services accounts for the largest share, followed by support services, supply services and cultural services. From 2005 to 2020, the distribution of high and low ESV zones in Jiuquan City does not change significantly, with the high value zones mainly located in Sujhou District, south of Suebei County and Yumen City, and the low value zones are concentrated in Dunhuang City, Guazhou County, north of Suebei County and Jinta County. The ESVs shifted outward from each district in the study area were, in descending order, Guazhou County, Subei County, Yumen City, Dunhuang City, Akse County, Jinta County, and Suzhou District. Guazhou and Subei counties were the main ESV exporters. Areas with high ESV exports tended to have high ESV values. Hydrologic regulation is the service type with the largest transfer volume, accounting for 19.00% of the total ESV transfer in Jiuquan City. The ecological condition of Jiuquan City is good.

In terms of achieving the dual goal of nature-positive and climate-neutral, there are more or less weaknesses in linking ecological networks (ENs) and carbon-related factors in both research and practice. Considering the widely recognized multifunctionality of ENs across ecological, economic, social, and aesthetic aspects, we propose to integrate spatial carbon emission as a proxy of human activity intensity into the ecological resistance system, and further to improve the design of the ecological nodes and corridors. Here, the spatial pattern of carbon emissions was studied in the Hohhot–Baotou–Ordos–Yulin (HBOY) city cluster, a large energy-intensive area in northern China. And then, by overlying with the primary landscape patterns, 23 ecological nodes and 67 artificial corridors were added to the primary EN, improving network closure, line point rate, and network connectivity by 92%, 30.48%, and 27.45%, respectively. Importantly, the potential capacity of carbon sink would be increased by 28.61%. It is found, the improved EN may help deal with the challenge of carbon reduction and ecological degradation in a manner of multi-objective synergy.

Aims Anthropogenic activities have substantially elevated nitrogen (N) deposition globally and affect ecosystem processes, including soil carbon (C) storage potential. Phosphorus (P) can become a limiting factor for plant production in instances of N deposition, yet the responses of ecosystem C cycles to P enrichment are poorly understood, particularly in sensitive alpine ecosystems. Methods We conducted a short-term field study to appraise the effects of N and P addition on ecosystem CO2 emissions and CH4 uptake in three typical alpine grasslands, alpine meadow, alpine steppe, and cultivated grassland on the Qinghai-Tibet Plateau (QTP). The closed chamber technique was employed to monitor the fluxes of CO2 and CH4. Environmental factors, including plant biomass and diversity and soil nutrients, and the abundance of C-cycling genes were analyzed to investigate the factors regulating CO2 and CH4 fluxes. Results The results showed that: (i) N and P addition tended to increase CO2 emissions and CH4 uptake. Furthermore, P addition weakened the positive effects of N on CH4 uptake across the three grasslands, but the interaction of N and P addition on CO2 emissions varied across the three grasslands. (ii) N and P addition affected the fluxes of CO2 and CH4 both directly and indirectly through their impacts on soil and plant factors rather than C-cycling functional genes. Conclusions These results indicate that in the context of increasing N deposition in the QTP, short-term P addition is not an effective method for mitigating global warming potential and improving soil C sequestration in alpine grassland ecosystems.

As a precautionary tool for decision-makings towards sustainable development, strategic environmental assessment (SEA) is quite promising in coping with climate change by taking the advantage of alternatives evaluation as early intervention and planning optimization. Despite of the acknowledged merits, the current alternatives evaluation has presented a weakness when tackling with the climate factors in practice due to an evident lack of carbon-related indicators. The challenge is even more pronounced in hydropower planning for the most sensitive response to climate, the most complicated impacts to evaluate and the recent doubts about the nature as a clean energy. Considering the assignable carbon emissions from the hydropower engineering including pre-treatment, construction, operation and decommission, six indicators of carbon footprint were selected and integrated with the conventional eco-environment and socio-economic considerations for evaluating four alternatives in the SEA of Upper Yellow River hydropower planning in China. The total 24 indicators were marked by the invited experts, and weighted by employing the BP neural network. The ranked marks from invited experts and improved by BP neural network weighting showed that the alternative II is the best among the four, indicating the slightest environmental impacts, the minimal carbon emissions, and the highest socio-economic benefits. This study delivered an improved framework based on the conventional rapid impact assessment method (RIAM) and carbon footprint assessment, and provided a practical technical solution for evaluating planning alternatives in the context of green hydropower development.

This study explores the connection between environmental, social, and governance (ESG) performance, financing constraints, and corporate investment efficiency. The hypotheses in this study are formulated based on the principles of stakeholder and agency theories. We used secondary data from Chinese A-share listed companies from 2010 to 2021 to conduct an empirical analysis using the Ordinary Least Squares (OLS) and Fixed Effect (FE) estimators. The results indicate that good ESG performance can enhance corporate investment efficiency. Compared to over-investment, ESG performance has a more pronounced effect on mitigating under-investment. Using a mediating analysis model, we also find that ESG performance exerts an inhibitory influence on both under- and over-investments by mitigating corporate financing constraints. Heterogeneity analysis indicates that the enhancing effect of ESG performance on corporate investment efficiency is more significant in non-state-owned corporations, low-pollution corporations, and corporations with a higher proportion of institutional investors. This study provides insights for listed companies to improve ESG performance to enhance capital allocation efficiency and promote sustainable development.

Ensuring ecological sustainability in urbanizing mega-regions like the Yangtze River Middle Reaches (YRMR) city cluster is crucial. Distinct dynamics in ecosystem service supply and demand (ESSD) have emerged due to land use changes, climate shifts, and policy drivers. Addressing potential imbalances and mismatches necessitates strategic ESSD regulation. However, it remains unclear how the future ESSD relationship will evolve under the combined impact of climate change and rapid urbanization. To improve demand simulation, this study examined causal links between socio-economic factors, land use, and ES demands from 2000 to 2018 using a system dynamics model. Six ES supplies and demands were simulated under the SSP-RCP scenarios in 2018–2050. Imbalances and mismatches in ESSD were assessed at grid, city, and sub-city cluster scales. The results showed sizable deficits in crop production (CP) and nature access (NA) services at three scales. A synergistic relationship between CP supply and water yield (WY) demand suggested that increased agricultural production could strain water resources. Growing demand for carbon storage (CS) and WY would worsen ESSD imbalance. To maintain long-term ESSD balance, strict carbon policies, land-use restrictions, cross-scale collaboration are needed. A tiered zoning approach based on supply-demand bundles can enhance ecosystem management in a socio-ecological context.