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The Tibetan Plateau works as an important environmental and ecological barrier for the Asian continent. The researches on Tibetan environment and ecology are becoming extensive, but there is no systematic summary of research hotspots and trends in this field. Here, we analyzed 9180 publications retrieved from the WOS and CNKI during 2000 ~ 2020. The characteristics of publication, keywords with a 5-year interval and co-occurrence analysis were carried out so as to reveal the evolution and development trends of topics. The results show that articles increase dramatically since 2012. Except for common concerns like evolution, climate change, and precipitation, diversity was been studied more by Chinese scholars, while the USA, Germany, UK, and Australia researchers focused more on adaptability, basin western Tibet, lake, barley, and ore-related themes, respectively. Besides, China closely collaborated with the USA, Australia, and Germany in topics of evolution, climate change and degradation, precipitation, and diversity. The institutions located in Chinese different economic regions focused on different research keywords, such as vegetation, growth, trace elements, and geochemistry. The CAS contributed the most articles with 4254, showed advantages both in quantity and quality. Few articles were published by researchers affiliated to Free University of Berlin but with higher citations. It is the only one institute outside of China in the top 20. Main research hotspots include climate change, geology, and diversity. In future researches, ecological management and rehabilitation of mining area and tailings ponds, waste disposal, and changes of soil and water quality are worthy of attention and funding., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon mitigation in the building sector is crucial for China to fulfill its commitments towards achieving a carbon peak and carbon neutrality. However, the impact of societal development and ecological indicators on building carbon emissions remains unclear. This study employs the panel smooth transition regression model to investigate the complex implications of societal development comprehensive indicators, characterized by harmonious development, decoupling, and technological advances, on buildings' total carbon emissions, based on the evidence from China's 30 provinces for the period between 2007 and 2020. Additionally, the robustness of the model confirms that the conclusion is still valid. The empirical results indicate a strongly non-linear relationship between societal development comprehensive indicators and building carbon emissions. Both the harmonious development and technological advances exhibit two transition functions, and decoupling features a single transition function. Harmonious development is more sensitive to the impact of building carbon emissions, while technological advances have tremendous emission reduction potential. From the time dimension, fluctuation trends and ranges are different. From the spatial dimension, the inhibiting and promoting effects on each province have regional heterogeneity. Our results entail suggestions for reduced building total carbon emissions and practical strategies for regional climate resilience and efficiency in mitigating climate change., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In the context of the dual carbon targets, digital trade brings new impetus to China's economic development to achieve low-carbon emission reduction. This article uses panel data from 30 provinces in China from 2011 to 2020, and uses a two-way fixed effect model to empirically investigate the impact of digital trade development on regional carbon emissions and its heterogeneity. The results show that the development of digital trade significantly reduces regional carbon emissions, and the conclusion is still valid after conducting the robustness tests. Digital trade can reduce regional carbon emissions by exploiting its effects of expanding economic scale, upgrading industrial structure, and promoting green technology innovation. In addition, the carbon reduction effect of digital trade varies due to differences in regions, trade openness, and carbon emission intensity. The carbon reduction effect of digital trade in central and western regions is larger than that in eastern regions, and the effect in inland regions is greater than that in coastal regions. As the degree of trade liberalization increases and carbon intensity decreases, the carbon reduction effect of digital trade will also weaken. The research conclusions have profound practical significance for achieving the carbon neutrality target, effectively addressing climate change, and promoting high-quality economic development., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Narrowing the income gap between urban and rural areas is the key to achieving common prosperity in China. On the basis of analyzing the mechanism of climate change's impact on urban-rural income gap, this article empirically analyzes the impact of climate change on urban-rural income gap using provincial-level panel data of 30 provinces in China from 2011 to 2020. Research indicates that climate change significantly impacts the urban-rural income gap at the 1% significance level, implying that climate change exacerbates the urban-rural income gap. This widening effect varies significantly across different regions, particularly in the western regions and areas with lower fiscal support for agriculture. Further analysis reveals that there is a mediating role between the total agricultural output value and resource mismatch in the impact of climate change on urban-rural income inequality; the digital rural construction plays a regulatory role in the impact of climate change on the urban-rural income gap. On this basis, policy recommendations are proposed to promote the development of climate-resilient agriculture, improve the meteorological forecast and early warning system, increase financial support, and optimize the allocation of agricultural resources., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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.)

One of the greatest challenges facing humanity in the current millennium is the need to mitigate climate change, and one of the most viable options to overcome this challenge is to invest in renewable energy. The study dynamically examines the links between renewable energy consumption, non-renewable energy consumption, climate change, and economic growth in five emerging Asian countries during the period 1975-2020. Variables selected in the model have long-term cointegration, as explored by the Pedroni cointegration test and the Westerlund cointegration test. The long-term estimated parameters of the augmented mean group (AMG) method show that renewable energy consumption significantly reduces climate change, while non-renewable energy consumption significantly promotes climate change. The results also show that GDP, investment in transport infrastructure, and urbanization can significantly contribute to climate change in selected emerging Asian countries. Moreover, the results validate the inverted U-shaped EKC hypothesis for emerging Asian economies. Country-specific analysis results using AMG estimates shows that renewable energy consumption reduces climate change in selected emerging Asian countries. Non-renewable energy consumption and investment in transport infrastructure have had significant progressive impacts on climate change in all countries. Urbanization contributes significantly to climate change, with the exception of Japan, which does not have any significant impact on climate change. GDP contributes significantly to climate change in all countries; however, GDP2 has significant adverse effects on climate change in India, China, Japan, and Korea, validating the inverted U-shaped EKC assumption for all countries except Bangladesh. Moreover, the Dumitrescu and Hurlin causality test confirmed a pairwise causal relationship between non-renewable energy consumption and GDP, supporting the feedback hypothesis. The results suggest that the best option for climate change mitigation in selected emerging Asian countries is to transition from non-renewable to renewable energy sources., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Under the background of global warming, the intensity and frequency of extreme meteorological events in the maize growing season in northeast China are increasing. In order to clarify the occurrence characteristics of extreme meteorological events in northeast China, this study focused on three extreme agrometeorological events, i.e., high temperatures, drought, and the compound events of high-temperature and drought during the maize growing season (May-September), impacting maize production., Results: Based on historical (1981-2017) and future (2021-2060) climate data, we analyzed the spatial-temporal patterns of these three events with different intensities in northeast China. The results indicated that slight high-temperatures and moderate and severe droughts occurred more frequently in the study area during the historical period. The frequency of the different grades of the compound events of high-temperature and drought will exhibit an increasing trend in the future, as will the frequency of the compound events of high-temperature and drought. This is particularly evident in the northwest of the study area., Conclusion: The compound events of high-temperature and drought mainly occurred in late July and early August, encompassing the flowering stage of maize varieties. It is important to identify the area and time of major extreme weather events to implement the necessary preventive measures. © 2023 Society of Chemical Industry., (© 2023 Society of Chemical Industry.)

Clarifying the spatiotemporal variation of crop irrigation water requirement (IWR) under the background of climate change is an essential basis for water resource management, determining the irrigation quota and adjusting the planting structure. Using 61 years of climate data from 205 stations in Northwest China, this study investigated the spatiotemporal variations of climatic factors and IWR during the growth period of five main grain crops (spring wheat, winter wheat, spring maize, summer maize, and rice) and explored the dominant climatic driving factors of IWR variation. Results showed that (1) the IWR of grain crops showed distinct differences. Rice was the highest water consumption crop (mean of 753.78 mm), and summer maize was the lowest (mean of 452.90 mm). (2) The variation trends and average values of IWR of different grain crops have spatial heterogeneity across Northwest China. For most crops, high values and increasing trends of IWR were mainly located in eastern Xinjiang, western Gansu, and western Inner Mongolia. (3) T max (maximum temperature), T min (minimum temperature), and P eff (effective precipitation) showed an increasing trend during the growth period of each grain crop, while U 10 (wind speed at 10 m height), SD (solar radiation), and RH (relative humidity) presented decreasing trends. (4) SD, T max , and U 10 promoted the increase of grain crops' IWR, while P eff and RH inhibited it. The impacts of climatic factors on the grain crop IWR differed among different regions. P eff was the most influential factor to the IWR of all grain crops in most areas. Therefore, under the premise of a significant increase in T and uncertain precipitation mode in the future, it is urgent to take effective water-saving measures according to the irrigation needs of the region. To cope with the adverse impact of climate change on the sustainable development of agriculture in the northwest dry area, to ensure regional and national food security., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Vegetation dynamics is an important aspect for determining climate change trends. The present study delineates to examine spatiotemporal changes of vegetation cover in Pindari valley (Kumaun Himalaya) from the 1972 to 2018 timeline. The study includes the calculation of vegetation spectral indices of normalized vegetation index (NDVI), extraction of different vegetation classes, and statistical analysis of the Mann-Kendall (MK) test on historical metrological data (especially precipitation and temperature) of the study site. For the statistical analysis of metrological data, the power data access viewer datasets have been used. The central feature classes of the study are grassland, scrubland, and forest cover. The results revealed that the region's forest cover significantly decreased by 24.74 sq. km from 1972 to 2018, increased in grassland cover by 17.84 sq. km, respectively, and a slight increase in scrubland class by 3.13 sq. km for the study period. The calculated NDVI shows significant changes over the study location; it has been noticed that the maximum values of the NDVI decreased by 0.24, and the minimum values show growth of about 0.047. The analysis indicates that climatic parameters such as precipitation and temperature are the main limiting factors affecting vegetation growth. The annual mean maximum temperature showed a decreasing trend. The estimated results show an increase in annual rainfall and annual minimum temperature, while the decreasing trend is observed in the case of maximum annual temperature. Objectives of the study are (1) spatiotemporal analysis of the vegetation cover, (2) identification of the main causes of change in the vegetation cover, and (3) statistical trend analysis of long-term metrological data. The outcome of the presented research work would be beneficial for the proper management and monitoring of the forest ecosystem., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The past few decades of extreme drought and flooding caused by changing climate conditions have significantly affected agricultural production globally. This study focuses on two vital crops in China-maize and rice-and provides a comprehensive analysis of how these crops are affected by climate change-induced factors over the periods 1978Q1-2015Q4. Four key findings were obtained. First, using a nonparametric approach to estimate actual and observed trends of climatic variables, the results show a significant positive trend in average temperature from February to October. On the other hand, seasonal temperature increases during spring, summer, and autumn. Second, the results show no significant change in the monthly, seasonal, and annual rainfall patterns when examined over the study period. Third, using an autoregressive distributed lag (ARDL) model, we find that while temperature and rainfall do not significantly support rice production in the long and short run, they play a substantial role in maize production in China. Finally, we find no significant difference in the results for rice when the quantile regression (QR) technique that controls for distributional asymmetry effects is employed. However, the impact of temperature on maize decreases at higher quantiles. Given the outcomes of our study, we argue that an advanced irrigation system is crucial and must be encouraged to minimize the effects of climate change on crop production., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study sought to investigate the impacts of climate change on cereal production in China over the period 1990Q1-2013Q4. Using the Autoregressive Distributed Lag (ARDL) approach, the results showed that CO 2 emissions, average temperature, and temperature variability have a significant negative impact on cereal production in the long run. However, energy consumption, average rainfall, labor force, and cultivated area significantly and positively influenced the production of cereal crops in the long run. Meanwhile, the study observed that rainfall variability has no significant effect on cereal production in the long run. The study again found that in the short run, CO 2 emissions, average temperature, and temperature variability have a significant negative relationship with cereal production. Besides, energy consumption, average rainfall, rainfall variability, labor force, and the cultivated area had a significant positive association with cereal production in the short run. The results of the Granger causality test showed that there exists a unidirectional causality running from CO 2 emissions, energy consumption, and labor force to the production of cereal crops in China. On the contrary, the study found no causality between cultivated area and cereal production. The study suggests that improved cereal crop varieties ought to be developed and introduced to cope with the adverse impacts of climate change in China. This will help to circumvent Huang et al.'s (2017) prediction of a decline in the total food self-sufficiency of China from 94.5% in 2015 to about 91% by 2025.

China has been the world's largest emitter of carbon dioxide since 2006. To achieve the goal of carbon neutrality by 2060, social scientists must become involved in China's deep decarbonization process. However, Chinese social scientists have given little attention to climate change in their bibliometric research. Based on the Chinese Social Sciences Citation Index journal catalog of the four essential social sciences, namely, management, economics, politics, and sociology, we used the China National Knowledge Infrastructure database to quantify the extent to which Chinese social scientists are concerned about climate change. The results showed that from 1978 to 2020, 1179 articles on climate change were published in management, economics, politics, and sociology journals, which represented only 26.8% of the 4397 articles published on pollution in the same journals. Politics journals published the most articles (38.76%), while sociology journals published the fewest (2.37%). Thus, Chinese social scientists rarely considered climate change, mainly because this topic remains controversial in some fields and because of the influence of international politics in addition to the promotion and incentive mechanisms for researchers. We analyzed the keywords and evolution of climate change research in the four social sciences and our results show that social scientists should give greater emphasis to climate change in their research., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Climate change can significantly alter phytoplankton growth and proliferation, which would counteract restoration efforts to control algal blooms. However, the knowledge is limited about the quantitative evaluation of the causal effect of algal biomass resurgence in large shallow lakes where there is no significant improvement after long term lake restoration. Here, a bucket process-based phytoplankton dynamic model is developed to quantify the contributions of climate change and nutrients concentration changes to phytoplankton biomass resurgence after 2014 in hypereutrophic Lake Taihu, China. Compared to 2008-2014, the mean water temperature (WT) and the mean phosphate are higher, the mean photosynthetically active radiation (PAR), the mean total suspended solids (TSS), and the mean dissolved inorganic nitrogen (DIN) are lower, during 2015-2020. Their contribution to algal biomass resurgence during 2015-2020 is WT (+58.7 %), PAR (-2.6 %), TSS (+23.2 %), DIN (-22.1 %) and phosphate (+42.7 %), respectively. Climate change (WT, PAR, and TSS), which contributed +64.9 % to the phytoplankton biomass resurgence, underscores the urgent need to continuously take more effective measures to reduce nutrient emissions to offset the effects of climate change in Lake Taihu and in other eutrophic lakes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationship that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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.)

Adapting to climate change is critical to building sustainable and resilient agricultural systems. Understanding farmers' perceptions of climate change has become the key to the effective implementation of climate change adaptation policies. This research draws multidisciplinary attention to how farmers participate in decision-making on adaptation behaviors and provides useful insights for realizing synergies between environmental change and agricultural production. In this work, we conducted a meta-analysis of 63 quantitative studies on Chinese farmers' adaptation to climate change to assess the relationship between motivational factors and adaptation behavior. Our analysis highlights that farmers' perceptions of precipitation changes are often inaccurate; however, other psychological factors, such as perception, experience, and risk attitude, significantly positively impact their adaptation behavior. In addition, different climate regions are the main source of high heterogeneity in inter-study comparisons of climate change perception, and the effect of climate regions may therefore constitute a moderating factor that weakens the positive relationship between climate change perception and adaptive behavior. Furthermore, this study highlights the need to intervene at the household level to enhance farmers' adaptability to climate change, which includes providing support through income diversification, early warning information services, training, assistance, credit, subsidies, and other resources. In the future, research on how perception, experience, and risk interact to affect adaptive behavior should be strengthened., 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.)

China's commitment to attaining carbon neutrality by 2060 has galvanized research into carbon sequestration, a critical approach for mitigating climate change. Despite the rapid urbanization observed since the turn of the millennium, a comprehensive analysis of how urbanization influences urban carbon storage throughout China remains elusive. Our investigation delves into the nuanced effects of urbanization on carbon storage, dissecting both the direct and indirect influences by considering urban-suburban gradients and varying degrees of urban intensity. We particularly scrutinize the roles of climatic and anthropogenic factors in mediating the indirect effects of urbanization on carbon storage. Our findings reveal that urbanization in China has precipitated a direct reduction in carbon storage by approximately 13.89 Tg of carbon (Tg C). Remarkably, urban sprawl has led to a diminution of vegetation carbon storage by 8.65 Tg C and a decrease in soil carbon storage by 5.24 Tg C, the latter resulting from the sequestration of impervious surfaces and the elimination of organic matter inputs following vegetation removal. Meanwhile, carbon storage in urban greenspaces has exhibited an increase of 6.90 Tg C and offsetting 49.70% of the carbon loss induced by direct urbanization effects. However, the indirect effects of urbanization predominantly diminish carbon storage in urban greenspaces by an average of 5.40%. The degree of urban vegetation management emerges as a pivotal factor influencing the indirect effects of urbanization on carbon storage. To bolster urban carbon storage, curbing urban sprawl and augmenting urban green spaces are imperative strategies. Insights from this study are instrumental in steering sustainable urban planning and advancing towards the goal of carbon neutrality., 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.)

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.)

Enterprise digital transformation (EDT) is a strategic initiative that provides robust support for optimising resource allocation, fosters business innovation, and significantly impacts ecological environment to increase financial performance. This study re-examines the substantial contributions of EDT to climate change mitigation. Drawing on data from Chinese A-share listed companies from 2010 to 2021, we investigated the changes and mechanisms influencing carbon emissions reduction performance (CERP) of enterprises undergoing digital transformation. The empirical results indicate that EDT actively contributes to enhancing the CERP of enterprises, with a more pronounced effect observed in non-polluting industries, state-owned enterprises, and manufacturing companies. Furthermore, empirical findings from mechanism tests reveal that EDT effectively improves the CERP by driving green technological innovation, strengthening industry chain connections, and enhancing capacity utilisation. Finally, within external oversight groups, particularly in government and investor supervision, the enhancement of enterprise CERP is more significant, highlighting the crucial role of external oversight in the EDT process., 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.)

Fractional vegetation cover (FVC) has changed significantly under various disturbances over northern China in recent decades. This research examines the dynamics of FVC and how it is affected by climate and human activity during the period of 1990-2018 in northern China. The effects of climate change (i.e., temperature, precipitation, solar radiation, and soil moisture) and human activity (socioeconomic data and land use) on vegetation coverage change in northern China from 1990 to 2018 were quantified using the Sen + Mann-Kendall test, partial correlation analysis, and structural equation modelling (SEM) methods. The findings of this research indicate the following: (1) From 1990 to 2018, the overall trend in FVC in northern China was increased. The areas with obvious increases were mainly situated on the northern slope of Tianshan Mountains, Xinjiang, the Loess Plateau, the Northeast China Plain, and the Sanjiang Plain, while the areas with distinct degradation were located in the Inner Mongolia Plateau, the Changbai Mountain and the eastern part of north China. (2) In the past 29 years, the FVC in northern China has been mainly affected by precipitation and soil moisture. (3) Based on structural equation modelling, we discovered that certain variables impacted the main factors influencing the amount of FVC in northern China. Human activity has had a larger impact on FVC than climate change. Our findings can accelerate the comprehension of vegetation dynamics and their underlying mechanisms and provide a theoretical basis for regional ecological environmental protection., 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.)

The increasing frequency of heat waves under the global urbanization and climate change background poses elevating risks of chronic kidney disease (CKD). Nevertheless, there has been no evidence on associations between long-term exposures to heat waves and CKD as well as the modifying effects of land cover patterns. Based on a national representative population-based survey on CKD covering 47,086 adults and high spatial resolution datasets on temperature and land cover data, we found that annual days of exposure to heat waves were associated with increased odds of CKD prevalence. For one day/year increases in HW&#95;975&#95;4d (above 97.5 % of annual maximum temperature and lasting for at least 4 consecutive days), the odds ratio (OR) of CKD was 1.14 (95 %CI: 1.12, 1.15). Meanwhile, stronger associations were observed in regions with lower urbanicity [rural: 1.14 (95 %CI: 1.12, 1.16) vs urban: 1.07 (95 %CI: 1.03, 1.11), Pinteraction < 0.001], lower water body coverage [lower: 1.14 (95 %CI: 1.12, 1.16) vs higher: 1.02 (95 %CI: 0.98, 1.05), Pinteraction < 0.001], and lower impervious area coverage [lower: 1.16 (95 %CI: 1.14, 1.18) vs higher: 1.06 (95 %CI: 1.03, 1.10), Pinteraction = 0.008]. In addition, this study found disparities in modifying effects of water bodies and impervious areas in rural and urban settings. In rural regions, the associations between heat waves and CKD prevalence showed a consistent decreasing trend with increases in both proportions of water bodies and impervious areas (Pinteraction < 0.05). Nevertheless, in urban regions, we observed significant effect modification by water bodies, but not by impervious areas. Our study indicates the need for targeted land planning as part of adapting to the kidney impacts of heat waves, with a focus on urbanization in rural regions, as well as water body construction and utilization in both rural and urban 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 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In the context of increasingly severe global climate change, finding effective carbon emission reduction strategies has become key to mitigating climate change. Environmental Protection Tax (EPT), as a widely recognized method, effectively promotes climate change mitigation by encouraging emission reduction behaviors and promoting the application of clean technologies. Based on data from 282 cities in China, this paper takes the official implementation of the EPT in 2018 as the policy impact and the cities with increased tax rates for air taxable pollutants as the treatment group and uses DID model to systematically demonstrate the relationship between the implementation of the EPT and carbon intensity (CI) and further explores the possible pollutant emissions and green innovation mediating effects. The findings show that (1) the implementation of EPT can effectively reduce CI by about 4.75%, and this conclusion still holds after considering the robustness of variable selection bias, elimination of other normal effects, policy setting time bias, and self-selection bias. (2) The implementation of EPT can reduce CI by reducing pollutant emissions and improving the level of green innovation. (3) There is obvious regional heterogeneity in the carbon reduction effect of EPT, and the implementation of EPT has a more significant effect on CI in medium-tax areas, low environmental concern areas, general cities, and eastern regions. This paper not only provides a new analytical perspective for systematically understanding the carbon emission reduction effect of EPT but also provides policy insights for promoting regional green transformation and advancing carbon peak carbon neutralization., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Ecological restoration projects (ERPs) are implemented worldwide to restore degraded ecosystems and promote ecosystem sustainability. In recent years, a series of ERPs have been implemented to enhance vegetation cover in the unique alpine ecosystems of the Qinghai-Tibet Plateau (QTP). However, the current assessment of the ecological benefits of ERPs is relatively single, and the scale and extent of future ecological restoration project implementation cannot be determined. We quantified trends in normalized vegetation index (NDVI) since the implementation of ERPs. Changes in four major ecosystem services were assessed before and after ERPs implementation, including wind erosion protection, soil retention, water yield, and net primary productivity (NPP). The relationship between NDVI and ecosystem services was further explored using a constraint line approach to identify NDVI as a threshold reference for ERPs implementation. The results showed that: (1) since the implementation of ERPs, 21.80% of the regional NDVI of the QTP has increased significantly. (2) After the implementation of ERPs, the average total ecosystem services index (TES) increased from 0.269 in 2000 to 0.285 in 2020. The average soil retention and water yield increased but the NPP and sandstorm prevention decreased slightly. (3) NDVI had no significant constraint effect on soil retention and NPP, but there was a significant constraint effect on wind erosion prevention and water yield. (4) The constraint line of NDVI on TES was S-shaped. After the implementation of ERPs, the TES gradually reached a threshold value when NDVI was 0.65-0.75. Our findings identify significant contributions of ERPs and thresholds for the constraining effects of vegetation cover on ecosystem services, which can inform sustainable ERPs for governments., 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.)

Heatwaves have been intensified worldwide due to climate change, posing great health risks, especially to elderly populations. However, in China, limited studies have employed the heat index to decipher the spatiotemporal trends of heatwaves and their impacts on the elderly population. By comparing the three heatwave definitions, this study aimed to evaluate the long-term spatiotemporal variations in heatwaves from 1964 to 2022 across China using the Excess Heat Factor (EHF). We took advantage of high-resolution reanalysis temperature data on the Google Earth Engine (GEE) platform to efficiently calculate the heatwaves. Our results revealed that the frequency and duration of heatwaves increased significantly in approximately 77 % of China's total area, with South China experiencing the most frequent and prolonged heatwaves. Conversely, in most areas, no significant trend was discerned in the growth of the maximum and average heatwave intensities. The total number of elderly people affected by heatwaves surged from approximately 11.96 million in 2001 to over 30.31 million in 2020, with an estimated additional 1.12 million older adults exposed to heatwaves annually across the nation (R 2  = 0.60, p < 0.05). The population factor exhibited largest effect on the exposure of heatwaves, followed by climate effects and combined factors, with the corresponding explanatory power about 42.84 %, 34.85 % and 22.31 %, respectively. These individuals predominantly resided in the Northeast China, Southwest China, and South China. We also found geographical variations in heatwave exposure along elevations and land use types. These insights underscore the pressing necessity for formulating strategic interventions to mitigate the health threats presented by mounting heatwave exposure, especially for susceptible groups like the elderly 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. Published by Elsevier B.V.)

Altay Prefecture, a typical arid region in northwestern China, has experienced the climate transition from warming-drying to warming-wetting since 1980s and has attracted widespread attention. Nonetheless, it is still unclear how climate change has influenced the distribution of vegetation in this region. In this paper, a reaction-diffusion model of the climate-vegetation system is proposed to study the impact of climate change (precipitation, temperature and carbon dioxide concentration) on vegetation patterns in Altay Prefecture. Our results indicate that the tendency of vegetation growth in Altay Prefecture improved gradually from 1985 to 2010. Under the current climate conditions, the increase of precipitation results in the change of vegetation pattern structures, and eventually vegetation coverage tends to be uniform. Moreover, we found that there exists an optimal temperature where the spot vegetation pattern structure remains stable. Furthermore, the increase in carbon dioxide concentration induces vegetation pattern transition. Based on four climate change scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6), we used the power law range (PLR) to predict the optimal scenario for the sustainable development of the vegetation ecosystem in Altay Prefecture., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.)

By utilizing the mediation effect model and the spatial Durbin model, this research investigates the influence that environmental restrictions have had on marine pollution in 38 coastal prefecture-level cities from the years 2000-2018. In order to gain a comprehensive understanding of the effect that environmental legislation has on contamination in offshore regions as well as its primary goal, the research takes a variety of different approaches into consideration. Following are the findings from the study; Firstly, pollution levels in coastal marine areas tend to rise at first and then fall when environmental laws are enacted, illustrating a non-linear pattern known as an inverted "U" shape. In order to improve the maritime environment through environmental legislation, it is crucial to support new green technologies. There is a "U" shaped linkage amongst environmental legislation and development of environmentally friendly technologies. Spatial spillover effects may allow for the regulation of coastal city environments to affect marine pollution in neighboring areas. Secondly, there is also an inverted "U" pattern visible in the impact trajectory of this effect. According to the results of this research, it is crucial to set up a strict and factually sound regulatory framework in the field of marine environmental governance. It is also suggested that local context be taken into account while crafting environmental regulating regulations. Also, it's crucial to promote development, dissemination, and use of green technology by completely capitalizing on the innovation's conduction effect. Thirdly, promoting cooperation efforts among areas to avoid and control such pollution is essential, and the transfer and management of offshore pollution between regions must be a top priority., 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 © 2023. Published by Elsevier Inc.)

Flash droughts characterized by rapid onset and intensification are expected to be a new normal under climate change and potentially affect vegetation photosynthesis and terrestrial carbon sink. However, the effects of flash drought on vegetation photosynthesis and their potential dominant driving factors remain uncertain. Here, we quantify the susceptibility and response magnitude of vegetation photosynthesis to flash drought across different ecosystems (i.e., forest, shrubland, grassland, and cropland) in China based on reanalysis and satellite observations. By employing the extreme gradient boosting model, we also identify the dominant factors that influence these flash drought-photosynthesis relationships. We show that over 51.46 % of ecosystems across China are susceptible to flash drought, and grasslands are substantially suppressed, as reflected in both sensitivity and response magnitude (with median gross primary productivity anomalies of -0.13). We further demonstrate that background climate differences (e.g., mean annual temperature and aridity) predominantly regulate the response variation in forest and shrubland, with hotter/colder or drier ecosystems being more severely suppressed by flash drought. However, in grasslands and croplands, the differential vegetation responses are attributed to the intensity of abnormal hydro-meteorological conditions during flash drought (e.g., vapor pressure deficit (VPD) and temperature anomalies). The effects of flash droughts intensify with increasing VPD and nonmonotonically relate to temperature, with colder or hotter temperatures leading to more severe vegetation loss. Our results identify the vulnerable ecological regions under flash drought and enable a better understanding of vegetation photosynthesis response to climate extremes, which may be useful for developing effective management strategies., 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 B.V. All rights reserved.)

Diatoms and dinoflagellates are two typical functional groups of phytoplankton, playing important roles in ecosystem processes and biogeochemical cycles. Changes in diatoms and dinoflagellates are thought to be one of the possible mechanisms for the increase in harmful algal blooms (HABs), due to changing hydrological conditions associated with climate change and human activities. However, little is known about their ability to adapt to changing ocean environments, thus making it difficult to know whether and how they are adapting. By analyzing a 44-year monitoring dataset in the central Bohai Sea during 1978-2021, we found that the abundance ratio of diatoms to dinoflagellates showed a decreasing trend seasonally and ecologically, indicating that the phytoplankton community underwent distinct successional processes from diatom dominance to diatom-dinoflagellate co-dominance. These processes exhibited varying responses to temperature, nutrient concentrations and ratios, and their interactions, of which temperature primarily drove the seasonal succession whereas nutrients were responsible for the ecological succession. Specifically, diatoms showed a preference for lower temperatures and higher DIP concentrations, and were able to tolerate lower DIN at lower temperatures. In contrast, dinoflagellates tended to prevail at conditions of warming and high N/P ratios. These different traits of diatoms and dinoflagellates reflected the fact that warming as a result of rising temperature and eutrophication as a consequence of nutrient input would favor dinoflagellates over diatoms. Moreover, the increasing dominance of dinoflagellates indicated that dinoflagellate blooms were likely to become more frequent and intense in the central Bohai Sea., 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 B.V. All rights reserved.)

Corn is the third most cultivated food crop in the world, and climate change has important effects on corn production and food security. China is the top user of chemical fertilizer in the world, and analyzing how to effectively manage fertilizer application in such a developing country with resource constraints is crucial. We present empirical evidence from China to demonstrate the nonlinear impact of temperature on fertilizer usage in corn production based on a panel dataset that shows 2297 corn-growing counties during 1998-2016. Our findings indicate that fertilizer usage barely changes with increasing temperatures that are below 28 °C; however, exposure to temperatures above 28 °C leads to a sharp increase in fertilizer use. The increase in temperatures in the sample period implies that fertilizer usage per hectare for corn increased by 1.5 kg. Summer corn fertilizer application in the Yellow-Huai River Valley is more sensitive to warming than in the North region. Moreover, nitrogen, phosphorus, and potassium fertilizers have different temperature thresholds of 32 °C, 20 °C, and 20 °C, respectively, that cause significant changes., 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 B.V. All rights reserved.)

Drought and floods seriously affect agriculture across the world. It is of great importance to lower down the agricultural vulnerability to disasters to build climate-resilient agriculture. The paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought and floods in the world in the period 2003-2019. Research results show that (1) the agricultural vulnerability to drought and floods is at a low level across the globe owning to the dual effects of decreasing exposure and increasing adaptability; (2) the northern parts of United States, northeastern parts of China, and the border between Russia and Kazakhstan are identified as most vulnerable areas to drought and floods; and (3) spatio-temporal mismatch of precipitation is the main factor to cause floods and drought while better adaption is beneficial to minimize the adverse effects of disasters. Based on analysis on the drivers and spatial patterns of drought and floods risk in all dimensions, tailored measures and policies are put forwards to make adaptive strategies of agriculture to 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. Published by Elsevier B.V.)

Both cyanobacterial blooms and antibiotic resistance have aggravated worldwide and posed a great threat to public health in recent years. As a significant source and reservoir of water environmental resistome, cyanobacteria exhibit confusing discrepancy between their reduced susceptibility and their chronic exposure to antibiotic mixtures at sub-inhibitory concentrations. How the increasing temperature affects the adaptive evolution of cyanobacteria-associated antibiotic resistance in response to low-level antibiotic combinations under climate change remains unclear. Here we profiled the antibiotic interaction and collateral susceptibility networks among 33 commonly detected antibiotics in 600 cyanobacterial strains isolated from 50 sites across four eutrophicated lakes in China. Cyanobacteria-associated antibiotic resistance level was found positively correlated to antibiotic heterogeneity across all sites. Among 528 antibiotic combinations, antagonism was observed for 62 % interactions and highly conserved within cyanobacterial species. Collateral resistance was detected in 78.5 % of pairwise antibiotic interaction, leading to a widened or shifted upwards mutant selection window for increased opportunity of acquiring second-step mutations. We quantified the interactive promoting effect of collateral resistance and increasing temperature on the evolution of both phenotypic and genotypic cyanobacteria-associated resistance under chronic exposure to environmental level of antibiotic combinations. With temperature increasing from 16 °C to 36 °C, the evolvability index and genotypic resistance level increased by 1.25 - 2.5 folds and 3 - 295 folds in the collateral-resistance-informed lineages, respectively. Emergence of resistance mutation pioneered by tolerance, which was jointly driven by mutation rate and persister fraction, was found to be accelerated by increased temperature and antibiotic switching rate. Our findings provided mechanic insights into the boosting effect of climate warming on the emergence and development of cyanobacteria-associated resistance against collateral antibiotic phenotypes., 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.)

This study investigates the impact of China's Low-Carbon Pilot Policy on analyst forecast behaviors. Using a staggered difference-in-difference approach, we find that the program reduced analyst forecast errors and divergence, as mandatory sustainability disclosures enable analysts to incorporate new information to improve forecast quality. The effect is concentrated in state-owned firms and manufacturing-oriented cities. Additional tests explore accounting information quality and investor attention as plausible channels. Overall, exploiting a major Chinese environmental regulation, we provide novel evidence that green policies can enhance transparency and capital market efficiency. The findings offer implications for regulators, investors, and managers as countries pursue climate change mitigation strategies., 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.)

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003-0.0319 year -1 . The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO 2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration., 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 © 2023 Elsevier B.V. All rights reserved.)

The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0-7 cm], shallow [7-28 cm], and middle [28-100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0-28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %-71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under 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 © 2023 Elsevier B.V. All rights reserved.)

With global warming, cities are vulnerable to extreme weather, increasing the climate risk to cities worldwide. Although existing literature has examined the ex-post impacts of extreme weather, it is less clear how climate risk affects cites before extreme weather occur. To lower the risk of urban waterlogging, which is caused by extreme weather, and improve the ability of cities to adapt to extreme weather, China launched the Sponge City Project (SCP) in 2013 to manage the urban stormwater and waterlogging. Adopting the SCP pilot in China as a quasi-natural experiment, we examine the impact of the climate risk caused by urban stormwater and waterlogging on the house price with the difference-in-differences (DID) method. We find that after implementing the SCP pilot program, the house price in pilot cities increased significantly because of the improvement in cities' resilience to climate risk. Additionally, this effect was only demonstrated in cities with a high waterlogging risk. For SCP pilot cities with lower waterlogging risk, the house price is not significantly affected by SCP implementation. This indicates that the house price in China is sensitive to the climate risk caused by the urban stormwater and waterlogging. Our findings also contribute to the understanding of the significance of the climate risk management, and provided theoretical evidence for urban 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 © 2023 Elsevier Ltd. All rights reserved.)

Climate change has resulted in great influence on the geographical distribution of species. Mangrove forests are one of the most precious ecosystems on the planet, yet they are being threatened by the habitat destruction and degradation under the situation of global warming. Seeking suitable areas for planting mangroves to tackle climate change has been gradually popular in ecological restoration. In this study, we applied the Maximum Entropy algorithm to assess the contribution of environmental factors on mangrove distribution, simulated mangrove suitable habitat for present and future (scenario of SSP245-2070s), and used kernel density analysis for identifying priority of mangrove reserve construction. Results indicate that mean diurnal range and elevation made the highest contribution on mangrove distribution. At present, the mangrove habitat suitability along the western coast of the Guangdong-Hong Kong-Macao Area (GHMA) was the highest while that along the eastern coast was the lowest. By 2070s, mangrove suitable areas would show a decreasing trend under SSP245 scenario. High suitable areas (HSAs) would change fastest and shift to northeast in the same direction as dominant environmental factors. For further mangrove restoration, it is advisable to select sites with high suitability density in the future but low reclamation density at present as prior mangrove reserves, and these sites distribute along the northeastern and northwestern coast of Zhanjiang, Yangjiang and Jiangmen, the Pearl River Estuary and Honghai Bay of Shanwei. Meanwhile, regions with lower suitability density but higher reclamation density could be listed as secondary mangrove reserves., 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 © 2023 Elsevier Ltd. All rights reserved.)

Cities generate substantial carbon emissions while facing serious climate challenges. The construction of low-carbon cities is a vital measure to cope with climate change. China has implemented three batches of low-carbon city pilots since 2010, with advocating low-carbon lifestyles and consumption patterns for residents as an indispensable component. However, there is limited research on the impact of pilot cities on carbon emissions of residents, as well as a lack of theoretical guidance and accurate data. Based on 281 prefectural-level cities in China, this study established the difference-in-differences model to evaluate the impact of low-carbon city pilots on residents' carbon emissions. By introducing the Attitudes, Behaviours, and Circumstances theory as the analytical framework and compiling a direct carbon emission inventory of residents, this study attempts to fill the research gap. The results indicate that low-carbon city pilots could lower residents' carbon emissions by 7.3% annually, with a gradual strengthening trend over time. This study presents and validates three influencing mechanisms of the pilot policy, including improving green attitudes, advocating low-carbon behaviours, and optimizing living circumstances. The heterogeneity analysis demonstrates that the eastern and central regions with higher levels of economic development have generated significant policy effects. Although both the northern and southern pilot cities have lowered residents' carbon emissions, the former has exhibited a stronger policy effect. Based on these findings, this study proposes several policy recommendations: innovate attitudinal guidance, nudge behavioural choices, shape external circumstances, and combine local characteristics., 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 © 2023 Elsevier Ltd. All rights reserved.)

Climate change is considered to increase economic costs by worsening heat-related labor productivity loss. While extensive global and national research has been conducted on this topic, few studies have analyzed subnational and individual economic impacts, potentially weakening local governments' motivation to tackle climate change. Figuring out the most affected regions and labors could help climate policymakers to identify priority regions and sectors to allocate adaptation resources efficiently, and enhance stakeholder engagement. This study adopted a provincial Computable General Equilibrium model by distinguishing different labors and regions in modelling work to address the aforementioned gap. The study estimated economic costs at different level under three climate change scenarios (lower (SSP126), middle (SSP245), and higher (SSP585) warming scenario). Low-income regions located in southwest part of China (such as Guangxi and Guizhou), would experience the largest economic loss, 3.4-7.1 times higher than high-income in China by 2100 under SSP245 scenario. Additionally, wages for labors highly sensitive to heat in these regions are expected to rise, for example, by an 8.3% rise in Guangxi, driven by the rising demand for these labors. Conversely, others would experience a significant wage decrease, especially those with less sensitivity (e.g., managers). Therefore, we recommended that national financial supports be allocated more to these most affected regions and that government encourage managers provide assistance to workers vulnerable to heat., 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 © 2023. Published by Elsevier Ltd.)

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide., 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 © 2023 Elsevier Ltd. All rights reserved.)

Climate change has increasingly become a significant challenge to sustainable socio-economic development, and climate adaptation is a key issue that relevant research focuses on regional sustainable development models. By employing panel data between 2007 and 2020 from 284 Chinese prefecture-level cities, this study adopts quasi-experimental methods, including a difference-in-differences design and double dual machine learning model, to study the impact of climate adaptability on green regional sustainable development. Empirical results confirm that the pilot policy of building climate-resilient cities significantly improves urban green total-factor productivity. Difference-in-difference models (derived from entropy-weight and propensity score matching) and double dual learning models also support the improving effect of regional green total-factor productivity after policy intervention. The digital economy has strengthened the green development effect of pilot policies for building climate-adaptive cities. In addition, policy interventions to build climate-adaptive cities promote green urban development by optimizing industrial development structures and enhancing economic growth resilience. In addition, climate adaptability can also attract highly skilled talent and high-quality enterprises, facilitate science and technological progress in urban areas, and thus promoting the green development of cities in China. This study objectively evaluates the effects of climate policies and provides insights for global adaptation to climate change and optimization of public policies., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The economic impacts of climate-induced heat stress on pig farming have not been sufficiently investigated, despite the significant threat it poses to the industry. In this study, we coupled consecutive years of county-scale meteorological data with operational-level economic data to estimate the impact of climate-induced heat stress on the productivity of the Chinese pig industry using a stochastic frontier production function model. Based on model results, we projected the impact of heat stress on pig production in 2030 and 2050 with and without technological advances. Results showed that heat stress has a significant negative impact on pig production, with southern regions being more affected. However, considering technological advances, losses will decrease by 21 % and 52 %, respectively, compared with the scenario without technological advances. Simultaneously, we calculated the costs of climate change mitigation and adaptation and found that increasing production inputs to reduce production losses from heat stress costs one-fifth of forgoing production losses. Therefore, we recommend a positive climate change response strategy., 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 © 2023. Published by Elsevier B.V.)

Comprehending endangered species' spatial distribution in response to global climate change (GCC) is of great importance for formulating adaptive management, conservation, and restoration plans. However, it is regrettable that previous studies mainly focused on geoclimatic species, while neglected climate-sensitive subterranean taxa to a large extent, which clearly hampered the discovery of universal principles. In view of this, taking the endemic troglophile riverine fish Onychostoma macrolepis (Bleeker, 1871) as an example, we constructed a MaxEnt (maximum-entropy) model to predict how the spatial distribution of this endangered fish would respond to future climate changes (three Global Climate Models × two Shared Socio-economic Pathways × three future time nodes) based on painstakingly collected species occurrence data and a set of bioclimatic variables, including WorldClim and ENVIREM. Model results showed that variables related to temperature rather than precipitation were more important in determining the geographic distribution of this rare and endemic fish. In addition, the suitable areas and their distribution centroids of O. macrolepis would shrink (average: 20,901.75 km 2 ) and move toward the northeast or northwest within the study area (i.e. China). Linking our results with this species' limited dispersion potential and unique habitat requirements (i.e. karst landform is essential), we thus recommended in situ conservation to protect this relict., 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 © 2023 Elsevier Ltd. All rights reserved.)

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m -2 ·a -1 ), with a multi-year average of 438.72 gC·m -2 ·a -1 , showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m -2 ·a -1 and 1.97gC·m -2 ·a -1 , respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon Intensity Constraint Policies (CICPs) are vital for addressing climate change challenges and advancing sustainable development. Since 2010, China has rolled out three five-year CICPs. However, there is limited understanding of their impact on carbon emission performance (CEP). Addressing this, this study pioneers the exploration of the CICP's impact on China's CEP. Drawing from government intervention and green paradox theories, this study highlights a concerning scenario: local governments achieve emission targets via excessive intervention. For deeper insights, this study melds the overall technology frontier concept with a non-radial, non-angle directional distance function, introducing a novel efficiency model rooted in the Data Envelopment Analysis (DEA) method. This offers a CEP measure across 30 Chinese provincial regions from 2002 to 2019. Using the quasi-difference-in-differences (quasi-DID) and moderated mediation models, this study ascertains the presence of the green paradox, uncovers its reasons, and suggests mitigation strategies. The results indicate that high government intervention diminishes CEP. This negative effect intensifies under greater regional fiscal pressure. Alarmingly, local authorities' eagerness to meet targets shows a counterproductive, inverted N-shaped trend regarding CICPs' time-based influence on regional CEP. Moreover, the impact varies based on regional economic development levels and stages. This study has ensured the robustness of the findings via parallel trend tests, parallel exclusion policies, a strengthened quasi-DID framework, and diverse control variable configurations. This study underscores the need for more balanced government intervention. It offers valuable policy insights, guiding China's upcoming CICP phase to realize the ambition of peaking carbon by 2030 and achieving carbon neutrality by 2060., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financialinterestsor personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Climate change is altering urban rainfall characteristics, leading to extreme urban stormwater and, particularly, more frequent flooding. Due to the uncertainty of climate change, the responses of urban drainage systems to climate change are becoming more complicated. This complexity makes it difficult for decision makers to assess whether urban infrastructure is sufficiently resilient to cope with flood risks. In this study, the Xiao Zhai area, a high-density urban area of China, was used as an example. A quantitative method for assessing these risks and the resilience of urban drainage systems to future urban stormwater was developed. First, based on the Coupled Model Intercomparison Project Phase 6 (CMIP6), the variation and uncertainty of future rainfall in the study area were analysed. A high-fidelity hydro-hydraulic model was developed to analyse the influence of climate change on future urban stormwater. Finally, the relationship between urban flood risk and the resilience of urban drainage systems was evaluated. The results show that the temporal distribution of future rainfall from 2023 to 2100 is relatively uniform. However, the number of heavy rainfall events increases significantly during this period. The flood risk caused by future rainfall was one level higher than the historical flood risk. For example, the flood risk caused by future 5a rainfall is equal to the flood risk from historical 10a rainfall. The correlations between the spatial distributions of flood risk and resilience are 0.49-0.63. Urban drainage systems urgently need to be improved and refined in areas with flood risk and low resilience to become more resilient to climate change. Rational planning of grey-green rainwater facilities in flood risk and low resilience areas can improve the rainwater system's resilience to 0.67-0.95 for 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 © 2023 Elsevier Ltd. All rights reserved.)

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.

Over-exploitation of groundwater due to intensive irrigation and anticipated climate change pose severe threats to the water and food security worldwide, particularly in the North China Plain (NCP). Limited irrigation has been recognized as an effective way to improve crop water productivity and slow the rapid decline of groundwater levels. Whether optimized limited irrigation strategies could achieve a balance between groundwater pumping and grain production in the NCP under future climate change deserves further study. In this study, an improved Soil and Water Assessment Tool (SWAT) model was used to simulate climate change impacts on shallow groundwater levels and crop production under limited irrigation strategies to suggest optimal irrigation management practices under future climate conditions in the NCP. The simulations of eleven limited irrigation strategies for winter wheat with targeted irrigations at different growth stages and with irrigated or rainfed summer maize were compared with future business-as-usual management. Climate change impacts showed that mean wheat (maize) yield under adequate irrigation was expected to increase by 13.2% (4.9%) during the middle time period (2041-2070) and by 11.2% (4.6%) during the late time period (2071-2100) under three SSPs compared to the historical period (1971-2000). Mean decline rate of shallow groundwater level slowed by approximately 1 m a -1 during the entire future period (2041-2100) under three SSPs with a greater reduction for SSP5-8.5. The average contribution rate of future climate toward the balance of shallow groundwater pumping and replenishment was 62.9%. Based on the simulated crop yields and decline rate of shallow groundwater level under the future climate, the most appropriate limited irrigation was achieved by applying irrigation during the jointing stage of wheat with rainfed maize, which could achieve the groundwater recovery and sustainable food production., 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 © 2023 Elsevier B.V. All rights reserved.)

Industrial structure adjustment is an effective way to reduce carbon emissions. When adjusting the industrial structure, changes in the input and output of industrial sectors in one region may cause changes in industrial sectors of other regions, resulting in inter-regional industrial linkages. What is the impact of industrial structure adjustment on the linkages, and how does it impact climate change? The modified gravity model combines the influence and inductive coefficients to build the carbon emission industrial spatial linkage network (ISL) using social network analysis (SNA) in this work with the data of China's 2008-2019 provincial carbon emissions. The impact of industrial structure adjustment on carbon emission industrial spatial linkage network and its effect on climate change mitigation are explored with the help of the STIRPAT model and quality assurance procedure (QAP). The results of this study are as follows: (1) The provincial carbon emissions under industrial spatial linkages show significant network characteristics, the network density increased from 0.1437 in 2008 to 0.323 in 2019. (2) There is a significant spatial spillover effect in the industrial spatial linkage network (2019) centered on Shandong and Jiangsu. The provinces can be divided into 4 blocks, which play different roles in the network. (3) The industrial structure upgrading can significantly promote the carbon emission industrial linkage network and mitigate climate change. (4) The industrial structure rationalization can promote the development of the network and mitigate climate change in the early and late development stages of carbon emissions industrial linkage. In addition, it is necessary for the government to pay more attention to the development level of the carbon emission spatial industrial linkage network when implementing industrial structure adjustment in response to 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 © 2023. Published by Elsevier Ltd.)

Climate change has impacted the distribution and abundance of numerous plant and animal species during the last century. Orchidaceae is one of the largest yet most threatened families of flowering plants. However, how the geographical distribution of orchids will respond to climate change is largely unknown. Habenaria and Calanthe are among the largest terrestrial orchid genera in China and around the world. In this paper, we modeled the potential distribution of eight Habenaria species and ten Calanthe species in China under the near-current period (1970-2000) and the future period (2081-2100) to test the following two hypotheses: 1) narrow-ranged species are more vulnerable to climate change than wide-ranged species; 2) niche overlap between species is positively correlated with their phylogenetic relatedness. Our results showed that most Habenaria species will expand their ranges, although the climatic space at the southern edge will be lost for most Habenaria species. In contrast, most Calanthe species will shrink their ranges dramatically. Contrasting range changes between Habenaria and Calanthe species may be explained by their differences in climate-adaptive traits such as underground storage organs and evergreen/deciduous habits. Habenaria species are predicted to generally shift northwards and to higher elevations in the future, while Calanthe species are predicted to shift westwards and to higher elevations. The mean niche overlap among Calanthe species was higher than that of Habenaria species. No significant relationship between niche overlap and phylogenetic distance was detected for both Habenaria and Calanthe species. Species range changes in the future was also not correlated with their near current range sizes for both Habenaria and Calanthe. The results of this study suggest that the current conservation status of both Habenaria and Calanthe species should be adjusted. Our study highlights the importance of considering climate-adaptive traits in understanding the responses of orchid taxa to future 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 © 2023 Elsevier B.V. All rights reserved.)

To detect potential impacts of climate change on the distribution of common echinoderm species in the Yellow Sea (YS) and East China Sea (ECS), species distribution models (SDMs) were applied. Ensemble SDMs were constructed and were in good model performance for six of the eight selected common echinoderm species. Under future climate scenarios, the brittle stars Ophiopholis mirabilis, Amphioplus depressus and the sea cucumber Protankyra bidentata were projected to expand in the southwestern areas of the YS, the ECS, and the coastal areas of the YS and ECS, respectively; the brittle stars Stegophiura sladeni, Amphiura digitula and Amphiura vadicola will likely contract their ranges in the south distribution areas and expand in the north, showing a northward movement trend. Temperature was the most important environmental variable influencing the distribution of the latter three echinoderms. Our findings will improve our understanding of the impacts of climate change on marine species distributions., 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 © 2023 Elsevier Ltd. All rights reserved.)

Combining the comprehensive effects of temperature and humidity, this study applies a heat stress index to project future population exposure to high temperature and related health-risks over China under different climate change scenarios. Results show that the number of high temperature days, population exposure and their related health-risks will increase significantly in the future compared to the reference period (1985-2014), which is mainly caused by the change of >T99p (the wet bulb globe temperature >99th percentile derived from the reference period). The population effect is absolutely dominant in influencing the decrease in exposure to T90-95p (the wet bulb globe temperature is in the range of (90th, 95th]) and T95-99p (the wet bulb globe temperature is in the range of (95th, 99th]), and the climate effect is the most prominent contributor to the upsurge in exposure to > T99p in most areas. An additional 0.1 billion person-days increase in population exposure to T90-95p, T95-99p and >T99p in a given year is associated with the number of deaths by 1002 (95% CI: 570-1434), 2926 (95% CI: 1783-4069) and 2635 (95% CI: 1345-3925), respectively. Compared with the reference period, total exposure to high temperature under the SSP2-4.5 (SSP5-8.5) scenario will increase to 1.92 (2.01) times in the near-term (2021-2050) and 2.16 (2.35) times in the long-term (2071-2100), which will increase the number of people at heat risk by 1.2266 (95% CI: 0.6341-1.8192) [1.3575 (95% CI: 0.6926-2.0223)] and 1.5885 (95% CI: 0.7869-2.3902) [1.8901 (95% CI:0.9230-2.8572)] million, respectively. Significant geographic variations exist in the changes of exposure and related health-risks. The change is greatest in the southwest and south, whereas it is relatively small in the northeast and north. The findings provide several theoretical references for climate change adaptation., 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 © 2023 Elsevier Inc. All rights reserved.)