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Climate change is one of the major threats to coastal fish biodiversity, and optimization of no-take marine protected areas (MPAs) is imminent. We predicted fish redistribution under climate change in coastal China Seas with joint species distribution modeling and prioritized areas for conservation with Zonation, for which we used core area zonation (CAZ) and additive benefit function (ABF). Based on our results, we devised an expansion plan of no-take MPAs. Under climate change, fish were redistributed northward along the coast. These redistributions were segmented by the Yangtze River estuary and its adjacent waters, indicating a possible biogeographical barrier. Under CAZ and ABF, significantly more fish habitat was conserved than under random prioritization (p < 0.001, Cohen's d = -0.36 and -0.62, respectively). The ABF better represented areas with higher species richness, whereas CAZ better represented core habitats for species with narrow distributions. Without accounting for species redistribution, the expanded MPAs were mainly distributed in the northwest of the South China Sea, the East China Sea, the north of the Yellow Sea, and the west of the Bohai Sea. When accounting for species redistribution, the proposed MPAs were mainly distributed in the north of the Bohai Sea and southwest of the Yellow Sea, corresponding to the northern species redistributions. These MPAs conserved less habitat for fishes at present but protected more and better quality habitat for fishes in 2050 and 2100 than those MPAs that did not account for species redistribution, indicating improved fish conservation under climate change. Incorporating species redistribution and trade-offs between areas with high species richness and areas that contain habitats for rare species are suggested to address coastal fish conservation under climate change. This work provides valuable information for fish conservation and is a precursor to systematic conservation planning along the coastlines of China Seas., (© 2023 Society for Conservation Biology.)

China has always tried to maintain multilateralism and advocated working together to deal with global climate change through multilateral mechanisms. Although China’s announcement to peak its carbon emissions by 2030 comes as no surprise, its commitment to carbon neutrality does. As the period between its carbon peaking and carbon neutrality is far shorter than that in the developed countries, China’s economic and energy structures need to be adjusted toward the low-carbon and carbon-free end with unprecedented efforts. To that end, China should define the responsibilities of local authorities and industrial entities to promote the orderly accomplishment of carbon peaking in all regions and industries. To supply the huge investments needed to achieve the goals of carbon peaking and carbon neutrality, China has an urgent need to accelerate the development of green finance and a national carbon emissions trading market, guide the rational allocation of resources, and channel resources to eco-friendly projects for green and low-carbon development. At the same time, China and the international community should strengthen dialogue and coordination, promote international cooperation on the way to carbon neutrality, formulate widely acceptable policy guidelines as soon as possible, and avoid unilateral measures that may cause conflicts. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

Carbon emissions are critical to climate change, and land-use change is an essential source of growth in carbon emissions. Research on land-use carbon emissions has become one of the hotspots in academic research. To explore the research hotspots and development trends of land-use carbon emissions in the last 20 years, CiteSpace software was used to conduct a quantitative analysis of relevant literature. This paper was based on the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) database literature on land-use carbon emissions from 2001 to 2020. The scientific research cooperation network CiteSpace software, with keyword co-occurrence, clustering, and burst word detection, was used to systematically analyze the main research strengths, hotspots and frontiers and clarify the research progress. The research results are as follows: (1) the amount of literature and the depth of research on land-use carbon emissions have increased yearly. However, there is little cooperation between research institutions and scholars, and there is still a lack of large-scale and stable research teams. (2) At the research hotspot level, the English literature focuses on building models and theoretical frameworks to study the internal mechanisms and driving factors of carbon emissions and climate change. The Chinese literature focuses on achieving regional carbon emissions reductions and carbon cycle goals and optimizing a low-carbon economy, transportation and land-use structure. (3) Research frontiers and trends show that the English literature first explored carbon sequestration, organic carbon, and carbon accounting. In China, the research frontiers are gradually becoming focused on influencing factors, decoupling analysis, and the built environment. The study will strengthen the intensity and depth of global carbon emission research and provide a reference for improving global climate change, protecting ecology and balancing economic development. [ABSTRACT FROM AUTHOR]

Blue Carbon is increasingly popular worldwide, and it also belongs to circular economy field which would last a long period in academy. To further understand the development and characteristics of Blue Carbon, this study uses CiteSpace software to perform quantitative analysis on literature published on Web of Science and Chinese CNKI database with the main topic of "Blue Carbon." The results show that: (1) Since 2009, increasing attention has been paid to Blue Carbon research, among which the United States, Australia and China are the leading countries. (2) Keywords such as "Blue Carbon," "mangrove," "carbon sequestration" and "carbon neutrality" are the high-frequency keywords appearing both in China and the World in recent years. (3) Spartina alterniflora, soil organic carbon, livestock, trophic cascade, biodiversity and seagrass ecosystem clustering are hot topics related to international Blue Carbon research, while organic carbon, seagrass-conservation, methodology, sustainable development, climate change, carbon neutralization, coastal zone and carbon storage are hot topics related to Chinese Blue Carbon research. In addition, based on the research trends of Blue Carbon, this paper attempts to sort out the research framework from three levels: core characteristics, theoretical basis and research methods, respectively. Facing a series of challenges brought by climate change, Blue Carbon research should strengthen the accurate estimations of Blue Carbon sink and its market potential, and explore the reasonable market mechanism and protection mechanism, to respond to realistic demands, solve major concerns and promote new progress in Blue Carbon theory and practice. [ABSTRACT FROM AUTHOR]

Climate change has become a critical global issue and challenge, with significant implications for financial enterprises as an integral part of economic activities. A thorough analysis of the impact of climate change on the high-quality development of financial enterprises is of great importance for financial sustainability. This paper first conducts an indepth mathematical analysis of the intrinsic mechanisms through which climate change affects the high-quality development of financial enterprises by establishing a game theory model. Secondly, using data from listed companies for the years 2000-2020, an econometric model is constructed to empirically examine the relationship between climate change and the high-quality development of financial enterprises. The research findings demonstrate that climate change significantly inhibits the highquality development of financial enterprises, as evidenced by robust results obtained through various methods such as data truncation, variable substitution, and changes in sample periods. Furthermore, this study addresses the endogeneity of the regression model using propensity score matching (PSM), instrumental variable methods, and system generalized method of moments (GMM). Additionally, climate change impacts the high-quality development of financial enterprises through technological innovation. Given the backdrop of climate change, understanding the relationship and logic between climate change and the high-quality development of financial enterprises and discerning the channels and mechanisms through which climate change affects their development are crucial. This research provides a new perspective and expands the research frontier on the high-quality development of financial enterprises, enriching the theoretical foundations in this field. [ABSTRACT FROM AUTHOR]

With the increase in global temperature, the global change situation dominated by climate warming is becoming more and more serious. Climate change will cause differences in the suitable areas of species in different periods. Ginkgo biloba L., a rare and endangered wild plant protected at the national level in China, is the oldest relict plant in the world. Because of severe climate change, only China's wild Ginkgo biloba has been preserved, yet China's wild Ginkgo biloba population is facing extinction risk. Ginkgo biloba has rich ornamental value, application value, economic value, medicinal value and ecological value. Not only can it produce economic and ecological benefits, but it can also produce huge social benefits. Based on the data of Ginkgo biloba sample distribution, bioclimatic variables and soil variables, this paper uses the MaxEnt model to simulate Ginkgo biloba suitable area under current and future different climate scenarios, and analyzes the changes in the potential suitable area of Ginkgo biloba in the future through ArcGIS 10.6. The results are as follows: (1) the results simulated by the MaxEnt model are AUC > 0.9, showing that the simulation results have a high accuracy; (2) the min temperature of the coldest month, precipitation of the wettest month, elevation, and temperature seasonality are the main environmental variables affecting the change in the Ginkgo biloba suitable area; (3) under future climate scenarios, the suitable area of Ginkgo biloba is predicted to expand in the future, covering most of the south and some northeast regions, and moderate temperature and precipitation changes under climate change are conducive for the growth of Ginkgo biloba; and (4) in the future, the distribution center of the suitable area will move to the northeast. According to the conclusions in this paper, it is expected to provide theoretical reference for cultivation and management, sustainable utilization and solution of ecological environment problems of Ginkgo biloba. [ABSTRACT FROM AUTHOR]

Cities, contributing over 70% of global emissions, are key areas for climate change mitigation. Heterogeneity within cities determines the need for spatialized urban emissions reduction policies. However, few studies have attempted to characterize the spatial distribution of carbon emissions at the urban scale. To address this issue, a novel mapping method was proposed, using Xi'an as an example to explore the spatial distribution of carbon emissions at the city scale. Firstly, multiple geospatial open-source data, such as point of interest (POI), road networks, and land use, were utilized to identify the locations of emission sources. High-resolution carbon emission distributions were then mapped by allocating emissions based on the Intergovernmental Panel on Climate Change (IPCC) methodology. The study employed Global Moran's I to analyze the changes in spatial heterogeneity at different resolutions. Additionally, the Local Indicators of Spatial Association index (LISA) and Standard Deviation Ellipses (SDE) were adopted to examine the spatiotemporal characteristics of carbon emissions in Xi'an. The results show that carbon emissions at Xi'an City rises from 45.112 million tons to 72.701 million tons between 2010 and 2021. The construction of multi-scale carbon emissions spatial distributions, with a resolution of up to 30 m, allowed for a more detailed characterization of carbon emissions, especially in urban fringe areas. In addition, the results indicate that urban carbon emissions exhibit the strongest spatial autocorrelation at a resolution of 350 m. The study can provide a reference for the development of regional carbon emission reduction policies and spatial planning. In addition, the proposed spatialized method of city carbon emissions depends on open-source data, which allows it to have the potential for application in other cities., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ling Han reports financial support was provided by Shaanxi University of Technology. Ziyan Liu reports financial support was provided by Chang'an University. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Climate change is increasingly contributing to climatic mismatches, in which habitat suitability changes outpace the dispersal abilities of species. Climate niche models (CNM) have been widely used to assess such impacts on tree species. However, most studies have focused on either a single or a limited number of species, or have employed a fixed set of climate variables for multiple species. These limitations are largely due to the constraints of data availability, the complexity of the modeling algorithms, and integration approaches for the projections of diverse species. Therefore, whether specific climatic drivers determine the climatic niches of multiple tree species remains unclear. In this study, CNMs were developed for 100 economically and ecologically important tree species in China and were used to project their future distribution individually and collectively. Continentality was the predominant climate variable, affecting 71 species, followed by seasonal precipitation, which also significantly influenced over 50 species. Of the 100 tree species, the climate niche extent was projected to expand for 29 ("winners"), contract for 36 ("losers"), be stable for 27, and fluctuate for the remaining eight species. Principal component analysis showed that winners and losers were differentiated by geographic variables and the top five climatic variables, however, not by species type (deciduous vs. evergreen or conifer vs. broadleaf). The regions with the highest species richness were mainly distributed in the Hengduan Mountains, a global biodiversity hotspot, and were predicted to increase from 5.2% to 7.5% of the total area. Areas with low species richness were projected to increase from 33.0% to 42.4%. Significant shifts in species composition were anticipated in these biodiversity-rich areas, suggesting potential disruption owing to species reshuffling. This study highlights the urgent need for proactive forest management and conservation strategies to address the impacts of climate change on tree species and preserve ecological functions by mitigating climatic mismatches. In addition, this study establishes a framework to identify the common environmental drivers affecting niche distribution and evaluates the collective patterns of multiple tree species, thereby providing a scientific reference for enhanced forestry management and climate change mitigation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

With increasing temperatures, changing weather patterns and ongoing development, it is becoming increasingly important to clarify the evolution mechanism of future regional streamflow processes and their controlling factors. In this study, an integrated framework for watershed streamflow prediction based on a Global Climate Model (GCM), the Patch-generating Land Use Simulation model (PLUS), and the Soil and Water Assessment Tool (SWAT) was proposed in the middle Yellow River. The results indicate that, compared with the baseline period (1989-2018), levels of precipitation and maximum and minimum temperatures are expected to increase in the next 30 years, resulting in a warmer and wetter regional climate. Under various climate scenarios, the annual streamflow is projected to increase by 49.2-115.1%. The acreage of various land types may have tended to be saturated, and the main land types such as cropland, forest and grassland have little change (-6.6%-0.6%), so the impact on streamflow will be correspondingly reduced. Under various land use scenarios, the annual streamflow is projected to increase by 5.0%-7.3%. The annual average streamflow trends under the combined climate and land use scenarios are consistent with the climate change scenarios, while the mean values corresponding to the combined scenarios are higher than those of the single scenario. Findings show that climate change is the main driver influencing streamflow, with a contribution of 86.3%-95.1%. This study deepens understanding of the change pattern and influence mechanism of the streamflow process, which can provide a scientific basis for the development and refinement of regional ecological construction plans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030-2039), 2060 s (2060-2069), and 2090 s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Accurately quantifying the impact of climatic and anthropogenic factors on vegetation change is critical for developing and evaluating ecological management strategies. However, most presented studies typically ignore the climate temporal effects and assume that all pixels are affected by both climate change (CC) and human activities (HA), which often introduce uncertainties. In this study, Leaf area index (LAI), temperature, precipitation, solar radiation, and land cover data from 1982 to 2020 were used to detect and attribute vegetation dynamics in China. We used partial correlation analysis, generalize linear model, trend analysis, and improved RESTREND to analyze the spatiotemporal variation characteristics of vegetation LAI from 1982 to 2020 and to quantify the effects of CC and HA on vegetation dynamics since the implementation of the Grain for Green Project (GGP). The results indicate that significant vegetation greening appeared in most areas (66.2%) between 2000 and 2020. Both CC and HA have positive effects on vegetation greening. In arid and semi-arid regions, precipitation was the primary driver of vegetation change, while in high-latitude areas of southern and southwestern China, temperature was the primary determinant. After considering the temporal effects, the explanatory power of climate variables for vegetation dynamics increased by 4.0% compared to ignoring the temporal effects, accounting for 72.81%. After dividing the pixels into those affected by CC and those affected by both CC and HA, the contribution of HA was decreased from 31.19% to 25.96%. Although the contribution of HA is lower than that of CC, ecological engineering has effectively promoted vegetation greening. These research findings provide scientific data and theoretical basis for ecological environment protection and natural resource management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The main stream of the Tarim River is a crucial part of China's ecological security strategy within the "two screens and three belts" framework, serving the "northern sand control belt" and the ecological civilization corridor. Evaluating and understanding desertification dynamics and driving factors is essential for achieving the United Nations Sustainable Development Goals and promoting ecological civilization. This study, based on the United Nations Convention to Combat Desertification, quantified the desertification process of the Tarim River's main stream from 1990 to 2020 using Landsat series satellite imagery from Google Earth Engine. Additionally, we employed panel data models to analyze the driving roles of climate change, socio-economic factors, and policies in desertification.Results indicate that between 1990 and 2020, desertification in the main stream of the Tarim River initially intensified, with 15% of the area experiencing desertification between 1990 and 2000. However, this trend was subsequently reversed, with only 0.6% of the area undergoing desertification over the 30-year period. Extensive economic development (-37.2%) and population growth (-48.7%) were the predominant factors exacerbating desertification in the initial period (1990-2000), whereas positive policies (55.3%) were the key to reversing desertification in the main stream of the Tarim River over the past 30 years.We also explored whether policies necessarily play a positive role in combating and preventing desertification. Based on this, we suggest actively engaging in interdisciplinary research and linking research outcomes with practical situations to formulate scientifically sound policies and measures for desertification prevention and control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Water colour has been recognized as one of the most important Essential Climate Variables of the lake ecosystem, as it is directly related to changes in water constituents and almost all of the lake's ecological changes could alter water colour. Given the high retrieval accuracy from existing Earth observation satellite data, water colour, in terms of Forel Ule Index (FUI), can be a realistic indicator to track the long-term changes in the lake ecosystem and further explore the lake response to environmental changes. This paper aims to comprehensively investigate the spatiotemporal variation patterns of FUI in 159 large lakes (≥25 km 2 ) across China during 2000-2022 based on the MODIS data and detect the climatic and anthropogenic driving forces of these changes. The 23 years of MODIS records revealed an overall downward trend of lake FUI across China, indicating the lakes in China shifted to bluer colour during the past two decades. Through driving factor analyses, the complicated interplay among lake colour, lake morphology, regional climate shifts and human interference dynamics was uncovered. In the long term, it was found the pronounced change in lake colour in the western lake zones was primarily attributed to climate warming and humidification, whereas that in the eastern lake zones was mainly related to the alterations in regional land cover during the past two decades. Seasonally, lake basin's air temperature was identified as the main factor impacting the seasonal patterns of lake colour, followed by wind speed and runoff. Spatially, there was high spatial variability in lake colour across China, which was mainly associated with lake elevation and lake basin's precipitation rate, although the factors exhibited considerable divergence across different zones. Based upon the above findings, the implications for lake environment protection and management in different regions of China were further discussed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In exploring strategies to address global climate change and achieve carbon neutrality goals, climate policy uncertainty (CPU) has become a significant challenge that cannot be ignored. It is crucial to understand how regions can effectively respond to climate risks and achieve energy transition. In this context, we utilized panel data from 277 Chinese cities and employed fixed effects models to analyze the relationship and mechanism between Chinese climate policy uncertainty (CCPU) and energy transition (ET). Our study found that CCPU significantly hinders the progress of ET, and this impact exhibits asymmetric characteristics. Compared to regions with strong environmental regulations, limited fiscal decentralization, and higher administrative levels, CCPU has a more pronounced inhibitory effect on ET in regions with weak environmental regulations, significant fiscal decentralization, and lower administrative levels. Green finance and energy structure are identified as important channels through which CCPU reduces ET. Additionally, further analysis indicates that CCPU significantly suppresses regional high-quality economic development and innovation, and this impact is achieved through inhibiting ET. Therefore, in the face of external uncertainties, this research can provide insights for local climate policy formulation. Focusing on and striving to reduce CCPU will contribute to the development of ET in regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The carbon emission trading scheme (ETS), a market-based environmental regulation, is critical for in combating climate change in China. According to the Porter effect, ETS can promote green innovation, while the specific impact of carbon price on a company's green innovation, and the role of price signals, remain unclear. This study examines the impact of carbon price on green innovation, utilizing a dataset of A-share listed companies spanning from 2010 to 2020. The difference-in-differences estimation results demonstrate that carbon price significantly increases green innovation, promoting both invention patents and utility model patents. Our findings further indicate that moderating variables such as ESG disclosure, larger institutional investor shareholding, local environmental penalties, price stabilization mechanisms, and free quotas allocation can all amplify the constructive influence of carbon pricing on sustainable innovation. Moreover, heterogeneity analysis suggests that state-owned and large-scale companies, particularly those in the power sector and polluting sector, are more sensitive to price signals impacting green innovation. Additionally, we discovered a spatial externality of carbon pricing on green innovation in a radius ranging from 150 km to 300 km. This paper provides specific policy recommendations to stabilize the carbon price signal., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The vegetation-runoff relationship remains unclear in karstic regions. The karst landform in southwest China is a focal area where significant changes in vegetation have occurred in the past few decades, which may substantially impact water resources. To date, the effects of these changes on runoff remain uncertain. This study employed statistical analysis, numerical simulation, and scenario analysis to investigate the temporal and spatial patterns of runoff, climate, and vegetation in 20 typical catchments. The study also evaluated the response of runoff to vegetation and climate changes and the underlying factors. The findings revealed precipitation changes dominated changes in runoff in these catchments (mean contribution of 53.03%), whereas the contributions of vegetation and potential evapotranspiration changes were 23.16% and 23.82%, respectively. The study also revealed that the impacts of vegetation changes on runoff were significantly dependent on vegetation and climate factors (R 2  = 0.60, P < 0.01). Furthermore, under the same climate change conditions, a higher distribution of natural vegetation (such as forest) in the catchment resulted in a larger decreasing trend in runoff. The results provide guidelines for the prediction of runoff variation in southwest China, and benefits to decision-making on ecological restoration and water resources development., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Achieving natural resource utilization efficiency (NRUE) is a critical objective in addressing the pressing challenges of climate change and the risks associated with the finite availability of mineral resources. Enhancing NRUE can mitigate environmental impacts and support sustainable development for future generations. In this context, green innovation emerges as a pivotal driver of environmental sustainability and resource conservation. However, its potential role in advancing the NRUE has not been fully explored. To fill this gap, this study conducts an empirical analysis of 268 Chinese cities from 2010 to 2022, examining the impact of green innovation on NRUE. This study also incorporates the mediating role of environmental regulations in shaping this impact. The findings demonstrate that green innovation significantly enhances NRUE, primarily by facilitating industrial structural upgrading and reducing resource dependence. Additionally, environmental regulations strengthen the positive effects of green innovation, further amplifying its contribution to NRUE. Moreover, geographical location and differences in resource endowments among cities lead to variations in the effectiveness of green innovation on NRUE. These findings underscore the complex interplay between green technological progress, proactive government policies, and NRUE, offering valuable insights for policymakers and researchers alike., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Carbon storage and the aboveground biomass of farmland provide practical significance for understanding global changes and ensuring food production and quality. Based on soil carbon storage, aboveground biomass, climate, geochemistry, and other data from 19 farmland ecological stations in China, we analysed the distribution characteristics of farmland carbon storage in topsoil and aboveground biomass. We notably revealed the response direction and degree of climate and geochemical factors to farmland carbon storage in topsoil and aboveground biomass. The results indicated that the average carbon stocks of farmland in different regions ranged from 0.28 to 7.91 kg m -2 , the average fresh weight of the aboveground biomass (FAB) ranged from 1370.64 to 5997.28 g m -2 , and the average dry weight of the aboveground biomass (DAB) ranged from 119.95 to 852.35 g m -2 . The least angle regression (LARS) and the best subsection selection regression (BSS) showed that evapotranspiration and extreme low temperatures were significant climatic factors affecting carbon sequestration and aboveground biomass on long-time scales. The linear mixed-effects model (LMM) further showed that AN and AP had significant long-term effects on carbon sequestration and aboveground biomass (p < 0.05), with AN having the highest contribution to SOC %, FAB, and DAB. The structural equation model (SEM) showed that carbon sequestration and aboveground biomass in agricultural fields were significantly positively correlated (p < 0.05). Moreover, the climate had a less direct contribution to carbon sequestration and above-ground biomass compared to geochemistry (PC c  < 0.1G ), and its effect was more indirect. When the geochemical variables were removed, the correlation between climate and carbon and aboveground biomass variables decreased significantly. We conclude that it is possible that extremes climate and geochemistry control carbon sequestration and above-ground biomass in long-term cropland through interactions in the context of global change, which provides new insights into the evolution of soil organic carbon in long-term cropland and the scientific formulation of policies to increase food production and preserve quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

China is the largest global orchard distribution area, where high fertilization rates, complex terrain, and uncertainties associated with future climate change present challenges in managing non-point source pollution (NPSP) in orchard-dominant growing areas (ODGA). Given the complex processes of climate, hydrology, and soil nutrient loss, this study utilized an enhanced Soil and Water Assessment Tool model (SWAT-CO 2 ) to investigate the impact of future climate on NPSP in ODGA in a coastal basin of North China. Our investigation focused on climate-induced variations in hydrology, nitrogen (N), and phosphorus (P) losses in soil, considering three Coupled Model Intercomparison Project phase 6 (CMIP6) climate scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Research results indicated that continuous changes in CO 2 levels significantly influenced evapotranspiration (ET) and water yield in ODGA. Influenced by sandy soils, nitrate leaching through percolation was the principal pathway for N loss in the ODGA. Surface runoff was identified as the primary pathway for P loss. Compared to the reference period (1971-2000), under three future climate scenarios, the increase in precipitation of ODGA ranged from 15% to 28%, while the growth rates of P loss and surface runoff were the most significant, both exceeding 120%. Orchards in the northwest basin proved susceptible to nitrate leaching, while others were more sensitive to N and P losses via surface runoff. Implementing targeted strategies, such as augmenting organic fertilizer usage and constructing terraced fields, based on ODGA's response characteristics to future climate, could effectively improve the basin's environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Xinjiang is one of the most sensitive regions in China in terms of its response to climate change. Against the background of global warming, analyses and predictions using different scenarios for Xinjiang should be conducted. The spatial and temporal distribution characteristics and trends of future temperature and precipitation trends should be considered to provide a scientific basis for the government to respond to future climate change. In this paper, using the CN05.1 dataset and seven models from the sixth phase of the Coupled Model Intercomparison Project, the delta downscaling method is used to predict the temperature and precipitation changes in Xinjiang Province from 2021 to 2050 under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios. The results show that (1) most models of CMIP6 have a good effect on temperature simulation in Xinjiang, and the mean values as well as the trends of the temperatures expressed by the multi-model ensemble averaging are in good agreement with the observed data and have a high degree of confidence. The observed precipitation increase rate is significantly higher than that predicted by the model, and the simulation results of each model overestimate the precipitation. (2) The mean annual temperatures in the Xinjiang region increase at rates of 0.32°C/10 a, 0.46°C/10 a, 0.47°C/10 a and 0.67°C/10 a, respectively, under the four scenarios. The rates of temperature increase in the four seasons exhibit the following pattern: autumn > summer > spring > winter. (3) From 2021 to 2050, the average annual precipitation in Xinjiang will change at rates of 3.95 mm/10 a, 1.90 mm/10 a, 2.50 mm/10 a, and 8.67 mm/10 a, respectively, under the four scenarios. The precipitation amounts predicted under the different scenarios increase at the slowest rates in winter and at faster rates in spring. Spatially, the precipitation in the whole Xinjiang region under the four scenarios shows an increasing trend. Overall, except for the SSP1-2.6 scenario, the rates of increase in precipitation increase gradually in all seasons during the future period as the emission scenarios increase. Overall, the climate of the Xinjiang region will be characterized by warming and humidification from 2021 to 2050., Competing Interests: The authors declare no conflicts of interest., (Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Influence of climate change on the geospatial heterogeneity in agricultural production remains poorly understood. In this study, heterogeneity in climate's impacts on wheat production across the North China Plain (NCP) was explored by integrating APSIM model, process-based factor-control quantitative approach, and geostatistical analyses. The results indicated that increased precipitation and minimum temperature boosted yields, while elevated maximum temperature and reduced radiation exerted adverse effects. The most pronounced negative impact arose from the coupling variation between maximum temperature and radiation, contributing to yields' variations of -5.84% from 2000 to 2010 and -5.22% from 2010 to 2020. In last two decades, climate change has augmented the overall geospatial heterogeneity degree in wheat yields. The chief factor contributing to yields' heterogeneity was the maximum temperature during anthesis-maturation stage, explaining an average of 37.6% of yields' heterogeneity, followed by precipitation throughout the whole growth period and the anthesis-maturation stage, explaining 36.1% and 34.5% respectively. A reciprocal enhancement mechanism exists between factors in driving yields' heterogeneity. Wheat yields in the southwestern NCP benefited more from increased precipitation and minimum temperature. Between 2000 and 2010, yields in the central NCP (junctions of Henan, Hebei, and Shandong) experienced the most pronounced adverse impact from increased maximum temperature. However, by 2010-2020, significant adverse impact shifted to western NCP, expanding spatially. During 2010-2020, the geospatial scope of radiation's significant negative impact expanded compared to the preceding decade, particularly affecting the yields in central and eastern NCP. The identified geospatial heterogeneity pattern of climate's impacts can guide spatially-matched climate-adaptive management adjustments. For instance, intensifying the defense against high-temperature's impacts in northwestern Henan, southern Hebei, and western Shandong, while improving the adaptation to radiation reduction in the central and eastern NCP. The findings are expected to advance regional-scale climate-smart agricultural development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Climate change has profoundly affected human production and development, and also brought new challenges to China's goal of achieving inclusive economic growth. Using the data of 273 cities in China from 2001 to 2019, this research evaluates the impact of climate change on urban inclusive economic growth by constructing a temperature bin variable according to the daily average temperature. It is found that with the temperature bin [18 °C, 21 °C) as the benchmark group, both temperature rise and fall have a negative influence on inclusive economic growth. Notably, the adverse effects of high temperatures (above 27 °C) are statistically and economically significant, exhibiting a trend of increasing magnitude. The mechanism test shows that high temperature affects the inclusive growth level of the urban economy mainly by exacerbating the urban‒rural income gap. The heterogeneity analysis found that cities located in hot regions, southern regions or coastal areas are more sensitive to high temperatures and experience more prominent effects. This research holds significant practical implications for China to achieve a win‒win situation of balanced economic development and climate governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The Beijing-Tianjin-Hebei (BTH) is one of the key areas with PM 2.5 air pollution in China. Driven by the PM 2.5 target accessibility of the Interim Target-1 (IT-1) by World Health Organization (WHO) and China's carbon neutrality, this study explored and quantified the contribution of climate change and anthropogenic emission to future PM 2.5 in the region. The experiments considered future climate change scenarios RCP8.5, RCP4.5, and RCP2.6 with the baseline (Base) and reduced emission (EIT1) inventories in 2030, and RCP4.5 climate scenario with 3 emission inventories in 2050, the additional strong control emission scenario called Best-Health-Effect (BHE). Under various climate scenarios, the future air quality research modelling system projected annual PM 2.5 concentrations nearing 35 μg/m 3 in 2030. However, considering only the effect of emission reduction, the annual PM 2.5 concentrations under EIT1 emission scenario is about 35% less than under Base scenario in different key years. The future PM 2.5 concentrations are highly related to anthropogenic emission from human activities, while climate change by 2030 or 2050 has little impact on future air quality over the BTH region. The BHE emission reduction is significantly required for China to meet the new PM 2.5 guideline value of WHO in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

As an important part of terrestrial carbon cycle research, net primary productivity is an important parameter to evaluate the quality of terrestrial ecosystem and plays an important role in the analysis of global climate change and carbon balance. Anhui Province is in the Yangtze River Delta region in eastern China. Based on the theoretical basis of CASA model, this paper uses MODIS NDVI, vegetation type data, meteorological data, and LUCC to estimate the NPP of Anhui Province during 2001-2020 and analyzes its spatial-temporal pattern. The results showed that the average NPP in Anhui province was 508.95 gC· (m2 ·a) -1, and the spatial heterogeneity of NPP was strong, and the high value areas were mainly distributed in the Jiangnan Mountains and Dabie Mountains. NPP increased in most areas of Anhui Province, but decreased significantly in 17.60% of the area, mainly in the central area affected by urban and rural expansion and the transformation of the Yangtze River. The dynamic change of NPP in Anhui province is the result of climate change and land use change. Meteorological data are positively correlated with NPP. Among them, the correlation between temperature and solar radiation is higher, and the correlation between NPP and precipitation is the lowest among the three. The NPP of all land cover types was more affected by temperature than precipitation, especially forest land and grassland. The decrease of cultivated land and the increase of Artificial Surfaces (AS) may have contributed to the decrease of NPP in Anhui Province. Human activities have weakened the increase in NPP caused by climate change. In conclusion, this study refined the drivers of spatial heterogeneity of NPP changes in Anhui province, which is conducive to rational planning of terrestrial ecosystems and carbon balance measures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Regional budget assessments of methane (CH 4 ) are critical for future climate and environmental management. CH 4 emissions from rice cultivation (CH 4-rice ) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH 4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH 4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH 4-rice emissions in China ranged between 6.21 and 6.57 Tg yr -1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH 4 emissions per unit rice production (CH 4-urp ), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH 4-urp . Scenario analysis indicates that under policies focusing on production or demand, CH 4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH 4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH 4-rice in China, while optimizing industrial layouts contributes to regional development and CH 4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply-demand balance can effectively reduce CH 4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %-12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH 4-rice ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Carbon sequestration is vital to maintaining carbon neutrality and mitigating climate change's impact on humans and the environment. As the government's role in eco-advocacy is primarily designed to safeguard the environment, this paper discusses the impact of government environmental regulations on carbon sequestration. By analyzing 286 cities from 2000 to 2019 in China, we propose that government environmental regulation can lead to a 0.77% increase in carbon sequestration. Additionally, industrial agglomeration and industrial structure advancement are regarded as viable channels. As a result of the differences in city types, government intervention, and public concern across different cities, the impact is likely to vary as well., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Dual control policies aim to effectively reduce energy consumption and carbon emission by setting targets for total volume and intensity control. With global climate change becoming increasingly serious. China, as a large energy-consuming and carbon-emitting country, faces a huge challenge to reduce carbon emissions. The transition from the "dual control of energy consumption" to the "dual control of carbon emissions" in China is necessary to optimize energy structures, promote energy conservation, reduce carbon emissions, and reach carbon neutrality. This study utilizes multi-regional input-output models to evaluate the results toward both goals from production-based, consumption-based, and income-based perspectives. The findings indicate that "dual control of carbon emissions" is a more precise approach than "dual control of energy consumption". Some provinces have met the latter goal while still falling short of the former. Provinces having met their production-based energy intensity and carbon emission intensity targets, but having failed their consumption-based and income-based targets, are identified to develop a comprehensive and accurate assessment of these targets. A net outflow of embodied energy and carbon emissions is observed among provinces in less-developed central and southern regions to more-developed eastern and northern regions. Suggestions and policy implications based on these findings include establishing a comprehensive evaluation of energy and carbon intensity, considering both consumption-based and income-based perspectives, as well as facilitating enhanced cooperation among developed and developing provinces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Terrestrial Water Storage (TWS) plays a pivotal role in water resource management by providing a comprehensive measure of both surface water and groundwater availability. This study investigates changes in TWS driven by human activities from 2003 to 2023, and forecasts future TWS trends under various climate change and development scenarios. Our findings reveal a continuous decline in China's TWS since 2003, with an average annual decrease of approximately 1.36 mm. This reduction is primarily attributed to the combined effects of climate change and human activities, including irrigation, industrial water use, and domestic water consumption. Notably, TWS exhibits significant seasonal and annual fluctuations, with variations ranging ±10 mm. For the future period (2024-2030), we project greater disparities between water resource supply and demand in specific years for the Songliao, Southwest, and Yangtze basins. Consequently, future water resource management must prioritize water conservation during wet seasons, particularly in years when supply-demand conflicts for limited water resources intensify. This study is valuable for effective planning and sustainable utilization of water resources., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chunmiao Zheng reports financial support was provided by the Ministry of Education of China and the National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The development of renewable energy has become an important means for the world to cope with climate change, ensure energy security, and protect the ecological environment. Using the panel data of 30 provinces in China from 2013 to 2021, this study used the mediating effect model and the spatial Durbin model (SDM) to explore the mechanism and spatial effects of renewable energy development on China's regional carbon emission reduction. The results show that: (1) Renewable energy development can help to reduce carbon emission intensity. (2) The results of mechanism analysis show that renewable energy development reduces carbon intensity by improving energy structure, promoting industrial structure optimization, and industrial structure upgrading. (3) The development of renewable energy can not only reduce the local carbon intensity but also have a positive spillover effect on the carbon intensity of neighboring regions. (4) Further analysis shows that the long-term effect of renewable energy development on carbon emissions is greater than the short-term effect. At the same time, the heterogeneity analysis shows that compared with the Yellow River basin, the development of renewable energy has a significant carbon emission reduction effect in the Yangtze River Economic Belt region. Energy-rich areas fall into the "resource curse", which makes the carbon emission reduction effect of renewable energy development not significant. This paper has certain reference significance for promoting reasonable decomposition between regions and formulating renewable energy development policies., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Natural wetlands are among the most important sources of methane; thus, these areas are important for better understanding long-term temporal variations in atmospheric methane concentration. During the last 60 years, wetlands have experienced extensive conversion and global impacts from climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we present a modeling framework, integrating CH4MODWETLAND, TOPMODEL and TEM models, to analyze the temporal and spatial variations in CH4 emissions from natural wetlands (including inland wetlands, coastal wetlands, lakes and rivers) in China. Our analysis revealed an increase of 25.5 %, averaging 0.52g m-2 per decade, in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Higher rates of increasing CH4 fluxes occurred in northeastern, northern and northwestern China, associated with large temperature increases. However, decreases in precipitation due to climate warming o_set the increase in CH4 fluxes in these regions. The CH4 fluxes from the wetland on the Qinghai Tibetan Plateau exhibited a lower rate of increase, which was approximately 25% of that simulated in northeastern China. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91-2.81 Tg), i.e., from 4.50 Tg in the early 1950s to 2.15 Tg in the late 2000s, due to a large wetland loss of 17.0 million ha. Of this reduction, 0.26 Tg 0.24-0.28 Tg) was derived from lakes and rivers, 0.16 Tg (0.13-0.20 Tg) from coastal wetlands, and 1.92 Tg (1.54-2.33 Tg) from inland wetlands. Northeastern China had the largest contribution to this reduction, with a loss of 1.68 Tg. The CH4 emissions were reduced by more than half in most regions in China except for the Qinghai Tibetan Plateau, where only a 23.3% decrease in CH4 was observed. [ABSTRACT FROM AUTHOR]

Based upon seven field surveys conducted between May 2011 and January 2012, we investigated pH, carbonate saturation state of aragonite (Ωarag), and ancillary parameters on the Chinese side of the North Yellow Sea, a western North Pacific continental margin of major economic importance. Subsurface waters were nearly in equilibrium with air in May and June. From July to October, the fugacity of CO2 (fCO2) of bottom water gradually increased to 697±103 µatm and pH decreased to 7.83±0.07 due to respiration/remineralization processes of primary production induced biogenic particles. In November and January, bottom water fCO2 decreased and pH gradually returned to an air-equilibrated level due to cooling enhanced vertical mixing. The corresponding bottom water Ωarag was 1.74±0.17 (May), 1.77±0.26 (June), 1.70±0.26 (July), 1.72±0.33 (August), 1.32±0.31 (October), 1.50±0.28 (November), and 1.41±0.12 (January). Critically low Ωarag values of 1.0 to 1.2 were mainly observed in subsurface waters in a salinity range of 31.5-32.5 psu in October and November, accounting for ~10% of the North Yellow Sea area. Water mass derived from the adjacent Bohai Sea had a typical water salinity of 30.5-31.5 psu, and bottom water Ωarag values ranged mostly between 1.6 and 2.4. This study showed that the carbonate system in the North Yellow Sea was substantially influenced by global atmospheric CO2 increase. The community respiration/remineralization rates in typical North Yellow Sea bottom water mass were estimated at 0.55-1.0 µmol O2 kg-1 d-1 in warm seasons, leading to seasonal drops in subsurface pH and Ωarag. Outflow of the Bohai Sea water mass counteracted the subsurface Ωarag reduction in the North Yellow Sea. [ABSTRACT FROM AUTHOR]

In the era of climate change and carbon neutrality, China is actively coping with its carbon lock-in dilemma. In this context, the development of the digital economy is considered a possible path to carbon unlocking. This study contributes to the literature by providing a comprehensive analysis of how the digital economy can be leveraged to address carbon lock-in, highlighting the importance of formal environmental regulation and informal environmental regulation in enhancing this effect. Accordingly, following findings are highlighted. (1) Our primary findings provide strong evidence on the negative effect of the digital economy on carbon lock-in; by implication, improving the digital economy is an efficient measure for eradicating carbon lock-in. (2) The digital economy shows the greatest marginal impact on industrial lock-in, while its inhibiting effect on behavior lock-in is the least pronounced. Moreover, the digital economy plays a prominent role in curbing carbon lock-in in provinces with a higher level of physical, human, and social capital. And the asymmetric impacts of the digital economy on carbon lock-in are significant at most quantiles. (3) Environmental regulation is a significant moderator. Put differently, the synergy of formal environmental regulation and the digital economy, as well as informal environmental regulation and the digital economy, are important means to break carbon lock-in. (4) The carbon lock-in mitigation effect of the digital economy is caused mainly by increasing technical market turnover and the efficiency of energy consumption., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Increased ecological land (IEL) such as forests and grasslands can greatly enhance ecosystem carbon sinks. Understanding the mechanisms for the magnitude of IEL-induced ecosystem carbon sinks is crucial for achieving carbon neutrality. We estimated the impact of IEL, specifically the increase in forests and grasslands, as well as global changes including atmospheric CO 2 concentration, nitrogen deposition, and climate change on net ecosystem productivity (NEP) in National Key Ecological Function Zones (NKEFZs) in China using a calibrated ecological process model. The NEP in NKEFZs in China was calculated to be 119.4 Tg C yr -1 , showing an increase of 42.6 Tg C yr -1 from 2001 to 2021. Compared to the slight contributions of climate change (-8.0%), nitrogen deposition (11.5%), and reduction in ecological land (-3.5%), the increase in NEP was primarily attributed to CO 2 (66.5%) and IEL (33.5%). Moreover, the effect of IEL (14.8 Tg C yr -1 ) surpassed that of global change (13.1 Tg C yr -1 ) in the land use change zone. The IEL-induced NEP is significantly associated with CO 2 fertilization, regulated by precipitation and nitrogen deposition. The high values of IEL-induced NEP occurred in areas with precipitation exceeding 800 mm and nitrogen deposition exceeding 25 kg N ha -1 yr -1 . We recommend prioritizing the expansion of ecological land in areas with sufficient water and nutrients to enhance CO 2 fertilization, while avoiding increasing ecological land in regions facing unfavorable climate change conditions. This study serves as a foundation for comprehending the NEP response to ecological restoration and global change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Many studies have confirmed that climate change leads to frequent urban flooding, which can lead to significant socioeconomic repercussions. However, most existing studies have not evaluated the impacts of climate change on urban flood from both event-scale and annual-scale dimensions. In addition, there are only few studies that simultaneously consider scenario and model uncertainties of climate change, and combine flood risk assessment and uncertainty analysis results to provide practical suggestions for urban drainage system management. This study uses the statistical downscaling method to calculate the design rainfall under ten rainfall return periods of four climate models and three climate change scenarios in 2040s, 2060s, and 2080s in various prefecture-level cities in China. The four climate models are HadGEM2- ES, MPI-ESM-MR, NorESM1-M and FGOALS-g2 models and the three climate change scenarios are constructed by different representative concentration pathways (RCP), namely RCP2.6, RCP4.5 and RCP8.5. On this basis, relying on the generated drainage systems using geographical information and other data, event-scale and annual-scale precipitation are combined to calculate the change ratio of annual flood volume expectation in prefecture-level cities in each future year compared with the current situation. Furthermore, the study evaluates scenario and model uncertainties of climate change, and then comprehensively integrates the flood risk and its uncertainties to provides suggestions for urban drainage system management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Accelerating the attainment of carbon balance in Chinese cities has become pivotal in addressing global climate change and promoting green, low-carbon development. This study, encompassing 277 prefecture-level and above cities from 2007 to 2020, reveals a positive overall trend in China's urban carbon balance index. The evolution unfolds in two stages, demonstrating a distinct "tiered development" pattern across the eastern, central and western regions. Moreover, significant spatial agglomeration characteristics characterize China's carbon balance hot and cold spots throughout the study period, with their spatial agglomeration degree remaining stable. The standard deviation ellipse analysis confirms these hot and cold spots' alignment with China's economic development level and population distribution. The GTWR test results highlight the pronounced non-stationary characteristics of different driving factors in space and time, exhibiting variations in strength and direction among regions. Consequently, enhancing China's urban carbon balance requires tailored measures based on different areas' unique conditions and development characteristics, emphasizing a hierarchical and classified approach to leverage distinct driving factors and foster a green development system in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Climate change is considered one of the major systemic risks facing the world in the 21st century. To address climate change, China has adopted a series of climate policies, but the uncertainty brought about by frequent climate policy issuance has increased pressure on enterprises, which may not be conducive to enterprises reducing emissions. This paper uses data on 1211 listed companies on the A-share market in China from 2012 to 2022 to study the impact of climate policy uncertainty on enterprise pollutant emissions. The research findings show that climate policy uncertainty increases corporate pollution emissions; climate policy uncertainty mainly generates negative impacts on enterprise environmental regulation, social responsibility, and R&D investment, thereby negatively affecting enterprise emissions reduction. Further heterogeneity analysis shows that climate policy uncertainty in China has a more significant impact on non-state-owned enterprises, technology-intensive enterprises, lightly polluting enterprises, and enterprises in western regions. These findings emphasize the importance of enterprise social responsibility, environmental regulation, and R&D investment in enterprise emissions reduction and provide policy implications for Chinese enterprises to optimize their energy-saving and emission reduction strategies in the face of climate policy uncertainty., Competing Interests: Declaration of competing interest All authors disclosed no relevant relationships., (Copyright © 2024. Published by Elsevier Ltd.)

Rising temperatures can increase the risk of mental disorders. As climate change intensifies, the future disease burden due to mental disorders may be underestimated. Using data on the number of daily emergency department visits for mental disorders at 30 hospitals in Beijing, China during 2016-2018, the relationship between daily mean temperature and such visits was assessed using a quasi-Poisson model integrated with a distributed lag nonlinear model. Emergency department visits for mental disorders attributed to temperature changes were projected using 26 general circulation models under four climate change scenarios. Stratification analyses were then conducted by disease subtype, sex, and age. The results indicate that the temperature-related health burden from mental disorders was projected to increase consistently throughout the 21st century, mainly driven by high temperatures. The future temperature-related health burden was higher for patients with mental disorders due to the use of psychoactive substances and schizophrenia as well as for women and those aged <65 years. These findings enhance our knowledge of how climate change could affect mental well-being and can be used to advance and refine targeted approaches to mitigating and adapting to climate change with a view on addressing mental disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Effectively tackling extreme climate change requires sound knowledge about carbon emissions and their driving forces. Currently, agricultural carbon emission assessment often deals with its inventory, efficiency, determinants, and response independently, which will leave out the complex interactions among its various components, thus there is a lack of comprehensive, scalable, comparable explanations for agricultural carbon emissions. Herein, we introduce an integrated agricultural carbon emission assessment framework (IEDR): Inventory (I) × Efficiency (E) × Determinants (D) × Response (R), which was then applied to an illustration for the county-level agricultural carbon emissions in Hunan Province, China. Results show that: (1) Agricultural carbon emission inventory (ACEI) increased from 20.06 × 10 6 tC in 2006 to 21.99 × 10 6 tC in 2014 and decreased to 19.07 × 10 6 tC by 2020, depicting a fluctuating trend. Meanwhile, there was remarkable spatial heterogeneity, with higher ACEI in the North and South than in the East and West. (2) Agricultural carbon emission efficiency (ACEE) increased from 0.8520 in 2006 to 0.8992 in 2020, depicting a growing trend driven by technological progress. Spatially distributed in contrast to ACEI, regions with higher ACEE were located in the eastern and western areas. (3) ACEI was negatively correlated with ACEE (-0.657), indicating that increasing ACEE is a key strategy for reducing emissions. (4) The natural environment, rural development level, and policy support had critical impacts on ACEE and ACEI. In particular, the cultivated area and rural water affairs development were significant influences on ACEE and ACEI. Given the externalities of carbon emissions and its important public goods characteristics of the atmosphere, local carbon issues are also global concerns. Therefore, the case study of the IEDR model not only validates this theoretical paradigm and realizes regional responsibility for global carbon reduction but also supports and expands the theoretical and empirical corpus in the field of agricultural carbon emissions and efficiency, providing insights and references for other global regions facing similar challenges., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Climate change is a common challenge faced by all humanity. Promoting emission and carbon reduction in agricultural land is the most important priority for addressing climate change and realizing sustainable development. Based on data from 296 prefecture-level cities in China from 2011 to 2021, this study utilizes machine-learning and text-analysis methods to construct an indicator of government climate-risk attention (GCRA). It combines a two-way fixed-effects model to investigate how GCRA affects agricultural-land carbon emissions (ALCE) and carbon intensity (ALCI) and the mechanism of the impact. The results indicate that (1) GCRA substantially reduces ALCE and ALCI, and the conclusions are robust to a battery of tests. Furthermore, (2) mechanism analysis reveals that GCRA primarily uses three mechanisms-strengthening environmental regulation, promoting agricultural green-technology innovation, and upgrading agricultural-land mechanization-to reduce ALCE and lower ALCI. Additionally, (3) heterogeneity analysis suggests that the carbon-emission reduction effect of GCRA is more significant in the east, in arid and humid climate zones, and in non-grain-producing regions. Finally, (4) spatial-spillover effect analysis and quantile regression results demonstrate that GCRA also significantly inhibits carbon emissions and the carbon intensity of nearby agricultural land, with the inhibition effect becoming more pronounced at higher levels of government attention. This study's discoveries are helpful in promoting the emission reduction and carbon sequestration of agricultural land and provide references for developing countries to cope with climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In the context of global climate change threatening human survival, and in a post-pandemic era that advocates for a global green and low-carbon economic recovery, conducting an in-depth analysis to assess whether green finance can effectively support low-carbon economic development from a dynamic perspective is crucial. Unlike existing research, which focuses solely on the average effects of green credit (GC) on carbon productivity (CP), we introduce a non-parametric panel data model to investigate GC's impact on CP across 30 provinces in China from 2003 to 2021, verifying a significant time-varying effect. Specifically, during the first phase (2003-2008), GC negatively impacted CP. In the second phase (2009-2014), this negative influence gradually diminished and transformed into a positive effect. In the third phase (2015-2021), GC continued to positively influence CP, although this effect became insignificant during the pandemic. Further subgroup analysis reveals that in the regions with low environmental regulations, GC did not significantly boost CP throughout the sample period. In contrast, in the regions with high environmental regulations, GC's positive effect persisted in the mid to late stages of the sample period. Additionally, compared to the regions with low levels of marketization, the impact of GC on CP was more pronounced in highly marketized regions. This indicates that the promoting effect of GC on CP depends on strong support from environmental regulations and well-functioning market mechanisms. By adopting a non-parametric approach, this study reveals variations in the impact of GC on CP across different stages and under the influence of the pandemic shock, offering new insights into the relationship between GC and China's CP., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The long-standing development pattern dominated by international circulation makes China face the risk of "low-end lock-in" and "being decoupling". In addition, the current global climate change and environmental crisis are becoming increasingly severe, coupled with the COVID-19 impact. Chinese enterprises must actively build a green development system for domestic industries in a mutually reinforcing manner in the context of the domestic general circulation, in order to adapt to the new dual circulation environment as soon as possible. This paper analyzes the specific coupling and coordination relationship between the two systems based on the relevant data of China's three major industries from 2008–2014 using Index DEA, entropy value method, gray correlation analysis and coupling coordination model. The results of the study show that: the two systems of dual circulation pattern and industrial green development have a strong correlation and basically present a coupling relationship, but within the industry, there is a problem of the collapse of the tertiary industry. In terms of the type of coupling, the domestic and international circulation in general gradually present the green development leading state, except for the primary industrial segment of the international circulation. On the whole, the coupling quality of the two systems needs to be further improved. Based on this, this paper puts forward the following suggestions: (1) coordinate the internal and external development of the industry; (2) take innovation as the driving force to promote the green transformation of industries; (3) take green sharing as the goal to strengthen the policy orientation of green development; (4) take the opportunity of mutual promotion of dual circulation to stabilize the steady state of green development coupling. [ABSTRACT FROM AUTHOR]

To effectively shift from economic growth based on high levels of energy expenditure and pollution and to actively address global climate change, the purpose of this paper is to explore whether environmental regulation in developing countries helps promote TFP from a credit resource allocation perspective. This paper examines the impact of environmental regulation on firm TFP and the underlying mechanism of TFP using data on Chinese listed A-share companies from 2011 to 2018. The relationship between ERS and enterprise TFP is found to exhibit a clear U shape, that is, it shows the characteristics of inhibition followed by promotion. The mechanism analysis indicates that credit allocation is a significant mediator between environmental regulation and its effect on firm TFP through such allocation, while the heterogeneity analysis shows that in the central and western regions and in highly competitive industries, environmental regulation significantly affects firm TFP through credit allocation. The empirical results, which indicate that ERS in China is still at the left-hand side of the U-shaped curve inhibition area, suggest that government regulation should be strengthened, differentiated regional environmental regulation should be implemented, the bank credit system should be improved, and the U-shaped inflection point must be crossed if high-quality economic development is to be achieved in China. [ABSTRACT FROM AUTHOR]

The Chinese Communist Party and its supporters are increasingly using social media platforms to shape China's public image. This online image is a means of strengthening domestic nationalism and of projecting "soft power" abroad. This paper examines various forms of anti-Westernism that are central to this image-making. It analyzes several recent topics—the Belt and Road Initiative, climate change, the COVID-19 vaccine, the Beijing Olympics, and the conflict in Ukraine—on the r/Sino subreddit page of Reddit and compares them with two online news outlets, the South China Morning Post and China Daily. The paper focuses on how these media frame the contest between a rising China and a failing West, so creating a discourse that competes with the negative portrayals of China outside the country. The paper contrasts the aggressive strengthening of China's image against the West on social media with more sober accounts of the same topics in China's official media and in commercial news outlets. The contribution of the paper is to document an emerging online anti-Westernism that is playing an increasing role in the changing geopolitical landscape. [ABSTRACT FROM AUTHOR]

To depict the wet (April with a soil water content, SWC, of 37 %) and dry (October with a SWC of 24.8 %) seasonal changes in the water use and physiological response of a Eucalyptus urophylla plantation in subtropical South China characterized by monsoon climate, the whole-year (June 2012 to May 2013) transpiration of E. urophylla was monitored using the TDP method. Daily transpiration (ET) in October averaged 5.7 ± 2.9 kg d-1 and was 58.0 % higher than that in April (3.6 ± 2.3 kg d-1). The difference is consistent with that of the radiation and evaporative demand of the two months, while the nocturnal transpiration (ET-NOC) in the wet season (0.18 ± 0.021 kg d-1) was almost twice that in the dry season (0.11 ± 0.01 kg d-1). Trees displayed a higher stomatal conductance (GS) (53.4-144.5 mmol m-2 s-1) in the wet season and a lower GS (45.7-89.5 mmol m-2 s-1) in the dry season. The leaf-soil water potentials (ΨL) of the two months (April and October) were -0.62 ± 0.66 and -1.22 ± 0.10 MPa, respectively. A boundary line analysis demonstrated that the slight improvement in the GS by SWC in wet season was offset by a significant decrease in D, and the slope of GS sensitivity to D (dGS/dlnD) in response to GSref (references GS at D = 1 kPa) was affected by the variance of radiation instead of SWC. Specific hydraulic conductivity (ks) of trees of different sizes decreased by 45.3-65.6 % from the wet to the dry season. Combining the decreased maximum reference GS at D = 1 kPa (GSref-max) by 22.4 % with the constant max GS (GSmax) when ΨL < -1.2 MPa, we shed some light on the mechanism underlying the high water-use efficiency (WUE) of this Eucalyptus specie. With a slight change in GSref-max and high sensitivity of ks to decreasing ΨL, large trees used water more efficiently than small ones did. In addition, the -m in the dry season (0.53 ± 0.007) was lower than that in the wet season (0.58 ± 0.01) due to the difference in the ratio of GS to the boundary layer conductance (gb) in the two months. The negative relationship between -m (except when light is limited) and Q proved to be a plastic response to environmental changes for E. urophylla but did not change with decreased ks as expected. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

The bioeconomy model provides an alternative view of global economic systems by putting sustainable practices combined with digital approaches at the forefront to tackle issues such as climate change. To address this new business trends, financial institutions began to set up the environmental, social, and governance (ESG) business units to evaluate their business strategies. This paper is aimed at examining the nonfinancial effect created by the digital transformation (DT) activities, highlighting the role of enterprise heterogeneity after the implementation of Environmental Protection Law (EPL) in China. We employ the panel data of A-share listed companies from 2010 to 2020, selecting DT and ESG indicators as the important representations of "Industry 5.0." Our empirical results demonstrate a positive impact of EPL on the ESG performance in sight of resource enterprises (REs), environmental enterprises (EEs), and polluting enterprises (PEs), but a negative impact of EPL on the DT indicators among those environmental related industries. Additional causal relationship regression reveals that enterprise DT has an intrinsic promoting effect on the ESG performance, emphasizing on the high risk of digitization process being the shock transmitters to enterprise nonfinancial indices. Notably, the connectedness of environmental policy illustrates dynamic patterns by parallel trend test and propensity score matching (PSM) DID regression. This paper is prone to benefit lawmakers, regulators, and firm executives responsible for analyzing and assessing enterprise digitization behavior by exploring the influence of macrolevel environmental policy. [ABSTRACT FROM AUTHOR]

Affected by global warming, the frequency of crop pests and diseases have increased, causing huge losses to agricultural production. To better grasp the development and trends of research on the effects of climate change on crop pests and diseases, the literature on the impact of climate change on crop pests and diseases published from 1990 to 2021 in the Web of Science (WOS) core collection database was used. This study explores the literature characteristics and hotspot evolution through the bibliometric visualization analysis software COOC, VOSviewer, and CiteSpace, with a view to identifying the changing characteristics and trends of research changes in this field. The results showed that the number of literature on the impact of climate change on crop pests and diseases increased rapidly. The main fields involved include environmental sciences, ecology, and agronomy. Papers in these fields mainly published in journals, such as PLos One, Forest Ecology and Management, and Frontiers in Plant Science. The country with the highest number of publications was the United States, followed by China and Australia. The most prolific authors in the top 20 are research scholars from China. The first author of the top 20 highly cited papers was from the United States. It was found that that current research on the impact of climate change on crop pests and diseases mainly focuses on agricultural production and food safety. Modelling and crop growth has maintained steady development. At present, research in this field mainly focuses on pest management strategies under the impact of climate change, the response of single species, and the complex ecological mechanisms behind the response. This study provides unique insights into the research field of the impact of climate change on crop pests and diseases and provides a reference direction for future research development in this field. [ABSTRACT FROM AUTHOR]

The impact of drought on terrestrial ecosystems is increasing, and the spatiotemporal heterogeneity of drought changes exacerbates the difficulty of determining ecosystem responses, especially in arid regions far from oceans. Tree rings have been widely used to understand how forest ecosystems respond to drought. However, the link between local hydroclimate variations related to tree rings and large-scale climate changes is not clear in the Qilian Mountains. Here, we used the tree ring width index to analyze the trend of Picea crassifolia growth and its relationship with climate in the middle Qilian Mountains. The results showed that the radial growth trend of Picea crassifolia is synchronized in the middle Qilian Mountains by calculating the Gleichläufigkeit index (GLK). Our analyses indicated that tree radial growth is positively correlated with drought during the growing season. Tree growth responds stably to drought (scPDSI and SPEI) and precipitation but unstably to temperature during 1950-2019. We further traced the meteorological factors that cause regional drought changes associated with radial growth. An increased total precipitation and decreased evaporation contribute to drought alleviation, favoring an increased tree radial growth. The increased total precipitation is mainly due to increased large-scale precipitation, which is related to water vapor transport changes. This study attempts to explore the influence of large-scale meteorology on regional drought change and its related tree radial growth response, which helps us to better understand the changes in forest ecosystems under climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Afforestation is a promising nature-based climate solution for mitigating climate change, but it is subject to a complex web of biophysical, cost-benefit, market, and policy processes. Although its biophysical feasibility has been established, the cost, market, and policy constraints that affect climate change mitigation through afforestation are still unclear. Here, we estimate such cost, market, and policy constraints on the basis of biophysical feasibility. Our findings reveal that implementation costs are a more relevant constraint than opportunity costs on mitigating climate change through afforestation. The China Certified Emission Reduction market currently provides only a 0.308 % incentive for climate change mitigation through afforestation, due to market access constraints. The current market prices of China Certified Emission Reduction, China Carbon Emissions Trading Exchange, and Nature Based Carbon Offset in Voluntary Carbon Market constrain 88.15 %, 87.95 %, and 85.75 % of CO 2 removal actions through afforestation, compared to the carbon price scenario (US$62.97 tCO 2 ) of the EU Emissions Trading System. Moreover, land policy under the scenarios of prohibiting conversion of cultivated land to forest and forest restoration in degraded areas exhibit 8.87-29.59 % and 65.16-74.10 % constraints, respectively, on mitigating climate change through afforestation compared to land-use freedom conversion scenarios from 2020 to 2060. Thus, enhancing the incentive price of CO -1 ) of the EU Emissions Trading System. Moreover, land policy under the scenarios of prohibiting conversion of cultivated land to forest and forest restoration in degraded areas exhibit 8.87-29.59 % and 65.16-74.10 % constraints, respectively, on mitigating climate change through afforestation compared to land-use freedom conversion scenarios from 2020 to 2060. Thus, enhancing the incentive price of CO 2 removal, addressing the market access barrier, strengthening cooperation between global carbon markets, and exploring carbon-neutral and food multi-oriented land policies can be valuable sources of mitigation efforts over the next 40 years., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)