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

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

This paper proposes a conceptual and analytical framework of states' legitimacy-seeking to comprehensively investigate the motivation behind China's climate and environment policy. While previous research has largely overlooked political factors that underlie China's climate policy, this paper argues that these factors are crucial in understanding China's policy changes, which are evident at both domestic and international levels. By examining sources such as government documents, leaders' speeches and authoritative literature, this study contends that China's climate change initiatives are part of a broader effort to enhance domestic and international legitimacy. The issue of climate change has become highly politicised in China under the leadership of President Xi Jinping, and it serves as a crucial test of the ruling party and the state's capacity to govern effectively. As such, legitimacy-seeking is the key driver that links China's domestic measures and international commitments. [ABSTRACT FROM AUTHOR]

Droughts are increasing in frequency and intensity as the global climate changes. Risk assessment for agricultural drought disasters is an important approach for disaster prevention and mitigation. Based on the formation mechanism of natural disaster risk, the index system model of agricultural drought risk assessment in North China was constructed, and the robustness of the established risk assessment model was tested by using the internal test method. Then based on the characteristics of agricultural drought risk formation in North China, the paper proposes corresponding risk prevention recommendations. The conclusions were as follows: when adjusting the indices and methods in the risk assessment model, the range of changes in the agricultural drought risk ranking for each city was mostly 1-2.5 places, and the model was relatively robust. With the exception of Beijing and Tianjin, which had the highest disaster prevention and mitigation capacity, central and northern China had the highest agricultural drought risk, which was previously linked to the high risk and vulnerability of these regions. The agricultural drought risk in northern Henan and southern Shandong is low, mainly due to the low risk. The 34 cities in North China can be divided into 6 agricultural drought risk clusters, which are not dispersed in space and cross-city distribution, and have good aggregation. Cluster 4, located in the northernmost mountainous areas, has the highest risk of drought, which is associated with high environmental vulnerability and low capacity for disaster prevention and mitigation, so agricultural areas should be reduced and agricultural input should be increased. Clusters 2, 5 and 6, located in the central and southern regions, have higher grain acreage and yields due to drought, so agricultural drought risk can be further reduced by increasing agricultural input and improving irrigation guarantee rate. [ABSTRACT FROM AUTHOR]

Exploring the complex relationship between population change and surface urban heat island (SUHI) effect has important practical significance for the ecological transformation development of shrinking cities in the context of the prevalence of urban shrinkage and the global climate change. This paper compares the population change and SUHI effect between population shrinking region (Northeast Region, NR) and population growing region (Yangtze River Delta, YRD) in China, and explores their differences in driving mechanisms, using GIS spatial analysis and Geodetector model. Our results indicated that there are significant differences in population changes and SUHI intensity between these two regions. About 72.22% of the cities in the NR were shrinking, while their SUHI intensities increased by an average of 1.69°C. On the contrary, the urban population in the YRD shows a linear growth trend, while their SUHI intensities decreased by 0.11°C on average. The results of bivariate Moran's I index also indicated that the spatial correlation between the urban population changes and the SUHI intensity changes are not significant in the above regions. Furthermore, there are significant differences in the primary drivers of SUHI variations between these two regions. In the NR, underlying surface changes, including the changes of green coverage and built-up areas, are the most important driving factors. However, atmospheric environment changes, such as carbon dioxide emission and sulfur dioxide emission, are the key drivers in the YRD. Northam's theory of three-stage urbanization and environmental Kuznets curve hypothesis are powerful to explain these differences. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are widely recognized as low-carbon transportation that adopts green and clean technology with contributing to mitigating global climate change. However, it appears that the practice in using EVs has not gained widespread popularity despite the promotion of various incentives with the presence of various restricting factors and challenges. In conducting this study in the context of China, we hypothesize that restricting factors have varying impacts on promoting EVs in China, where the adoption of EVs is of great potential. This paper identifies these restricting factors by applying AHP-FCE integrated approach, and these factors are classified into five dimensions, namely, technical, infrastructural, economic, governance and social. The results indicate that the top five restricting factors are security issues, limited driving range, long charging time, improper distribution of charging stations and lack of sharing between charging piles respectively. Our research contributes to a better understanding of EV restricting factors and their significance, which offers the assistance in the formulation of policies and decisions in order to promote effectively EVs in China. • The promotion of EVs is of great potential in China for mitigating global climate change. • Explore the RFPEVs in China using AHP-FCE integrated approach. • The RFPEVs in China can be classified into five dimensions, namely, technical, infrastructural, economic, governance and social. • The technical and infrastructural related are the most important constraints. • The main three important restricting factors are security issues, limited driving range, long charging time. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Reducing food waste is an important initiative to ensure food security and mitigate climate change. Previous studies have largely ignored the influence of reference points on food waste behavior and the role of human-to-human relational interactions, failing to capture their role in guiding residents' food waste behavior (RFWBs). To address this gap, this study proposes a model that examines the role of reference dependence, normative internalization, and symbolic expectations in RFWBs, while introducing network embeddedness as a moderating variable. Using data collected from 981 respondents online, ordinary least squares were used to test the hypotheses. The results showed that reference dependence and normative internalization had a positive effect on reducing RFWBs with regression coefficients of 0.178 and 0.293 respectively, while symbolic expectations also had a positive effect on RFWBs with a regression coefficient of 0.227. Additionally, Network embeddedness played a significant moderating role in reference dependence, normative internalization, and symbolic expectations with RFWBs. This paper is theoretically innovative and the relevant findings fill the current research gap in the field of food waste, providing guidance and reference for government departments to formulate policies and promote residents to implement food waste reduction behaviors. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB) is an important strategic area in China. However, frequent extreme precipitation events have caused great economic losses and human casualties in this region. In this article, we explore the spatial and temporal links between extreme precipitation events and Sunspot Number (SSN), El Niño Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO) in this important economic belt. According to the research findings, all of the extreme precipitation indices (EPIs) except for consecutive dry days (CDD) and consecutive wet days (CWD) showed an upward trend in the YREB over the 59 years. The spatial distributions of very wet days (R95p), extremely wet days (R99p), max 1-day precipitation amount (Rx1day) and max 5-day precipitation amount (Rx5day) had similar distribution patterns, showing decreasing trends from east to west. The EPIs generally had a 2–4-year band, suggesting stronger and more elusive changes. The wavelet coherence (WTC) spectra suggested that SSN, ENSO, AO, and PDO have different effects on extreme precipitation events during different time periods. Before 1985, the SSN, ENSO, AO, PDO and extreme precipitation events shared similar oscillation periods, but after 1985, their oscillation periods were no longer consistent with each other. In addition, solar activity and the AO mainly had negative correlations with extreme precipitation events, while the ENSO and PDO had predominantly positive correlations with the EPIs. This paper provides a reference for national economic strategic planning and natural resource management in the YREB. [ABSTRACT FROM AUTHOR]

There are many types of atmospheric heat engines in land-air systems. The accurate definition, calculation and interpretation of the efficiency of atmospheric heat engines are key to understanding energy transfer and transformation of land-air systems. The atmosphere over the Qinghai-Tibet Plateau (QTP) in summer can be regarded as a positive heat engine. The study of the heat engine efficiency is helpful to better understand land-air interaction and thermal-dynamic processes on the QTP. It also provides a new perspective to explain the impact of the QTP on the climate of China, East Asia and even the world. In this paper, we used MOD08 and ERA5 reanalysis data to calculate the atmospheric heat engine efficiency, surface heat source and atmospheric heat source on the QTP in summer (May to September) from 2000 to 2020. The average atmospheric heat engine efficiency on the QTP in summer from 2000 to 2020 varies between 1.2% and 1.5%, which is less than 1.6%; the heat engine efficiency in summer is higher than that in June, July and August; the Qaidam Basin is the region with the highest atmospheric heat engine efficiency, followed by the western QTP. The mean surface heat source on the QTP in summer from 2000 to 2020 is 96.0 W m−2, the atmospheric heat source is 90.7 W m−2, and the release of precipitation condensation latent heat is the most important component of the atmospheric heat source on the QTP in summer. There is a strong and significant positive correlation between the atmospheric heat engine efficiency and the surface heat source on the QTP in summer. The precipitation con densation latent heat is the most important component of the atmospheric heat source in summer and can reflect the precipitation process. There is a strong and significant negative correlation between the atmospheric heat engine efficiency and the atmo spheric heat source on the QTP in summer. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

Purpose: After almost 10 years, people wonder if green finance has been able to attain its objectives in terms of controlling climate change. Persistent global warming and climate deregulation manifested by melting glaciers, droughts and floods, are all of these determinants that have called into question the efficiency of green finance. Design/methodology/approach: Green finance is a way to support climate action through investments. It has proven that this is a viable financial instrument and that it can be used by governments and private companies to plan for the future of our planet. Findings: Based on an analysis of articles published in top international journals from 2016 to 2022, about the relationship between green technology and financial services in China, this paper aims to present an overview of green finance, its importance for the planet, its objectives and its instruments. Research limitations/implications: This study's contribution is to shed light on the aspects that may have limited its effectiveness, such as the absence of incentives, the absence of climate costs and above all the absence of finance green standards. Originality/value: The results have shown that there is still a significant gap in green finance before inclusive green growth can be achieved. Inclusive green growth. All stakeholders need to increase the level of investment in green finance. The green investment financing gap is the result of inconsistencies in sustainability and policies. Therefore, governments must intervene to impose appropriate policies and regulations to compel the financial sector to engage in sustainable development. All of these factors make the concept of green finance just an illusion. [ABSTRACT FROM AUTHOR]

Climate change leads to the frequent occurrence of natural disasters. It has had a severe impact on agricultural economic growth in China. Based on data in China from 2004 to 2020, this paper uses a fixed-effect model to discuss the effects of natural disasters on agricultural economic growth. The empirical results are as follows. (1) Natural disasters negatively affect agricultural economic growth. The regression coefficient of natural disasters on agricultural economic growth is −0.1183. (2) The inhibition of agricultural economic growth by natural disasters is more prominent in areas with low government attention and average agricultural production conditions. (3) The mechanism analysis shows that natural disasters inhibit agricultural economic growth through channels that cause the spread of diseases and pests. (4) Expanding the scale of agricultural insurance can prevent the impact of natural disasters on agricultural economic growth. This research provides policy recommendations for preventing the negative impacts of natural disasters. Agricultural producers should raise awareness of disaster management and improve the accuracy of disaster warning mechanisms. • This paper measures the level of natural disasters in China. • This paper expands the application field of functional data analysis methods. • This paper examines the mechanism of natural disasters affecting agricultural economic growth. • This paper provides policy suggestions for ensuring agricultural economic growth. [ABSTRACT FROM AUTHOR]

Preventing the impact of natural disasters on urban-rural income inequality helps to achieve shared prosperity. This paper uses the functional entropy weight method to calculate the level of natural disasters from 2004 to 2020. Then, this paper discusses the impact of natural disasters on the urban-rural income gap. The empirical results are as follows. (1) Natural disasters have expanded the urban-rural income gap. The regression coefficient is 0.2663, which is significant at the 1% level. (2) In areas with a high proportion of the rural population, the impact of natural disasters is more prominent. (3) Mechanism analysis indicates that natural disasters have widened the urban-rural income gap by restraining rural investment and agricultural production. Finally, this paper suggests strengthening investment in the agricultural sector to mitigate the negative impact of natural disasters. • This paper uses the functional entropy weight method to calculate the level of natural disasters. • This paper quantitatively measures the impact of natural disasters on the urban-rural income gap. • This paper examines the mechanism of the impact of natural disasters on the urban-rural income gap. • This paper provides policy suggestions for narrowing the urban-rural income gap. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

Offshore aquaculture plays an important role in alleviating the pressure of coastal aquaculture and promoting the sustainable development of fisheries. And changes in ocean conditions caused by climate change will have a huge impact on mariculture. Considering the conditions of climate change, this study took the main mariculture fishes in China as the research object, used a species distribution model (SDM) to predict the potential mariculture areas of each fish under the current and different future (2040–2050) climate scenarios, divided the mariculture areas into three potential levels by natural breaks classification method, and calculated the area of different levels potential areas of each fish through the grid number and grid unit area. Additionally, this paper compares the potential area variation of different fishes under different climate scenarios. The results indicate that: (1)In the current climate, the potential area of Yellowtail kingfish(Seriola lalandi) is the largest among seven fishes, estimated at 1,288,500 km2. And the number of varieties suitable for aquaculture in the East China Sea and the South China Sea is more than that in the Bohai and Yellow Seas. (2)Compared with the high potential area of current and future climate scenarios, Large yellow croaker(Larimichthys crocea) has the largest increase, Yellowtail kingfish(Seriola lalandi) decreases under all four future climate scenarios, and both Cobia(Rachycentron canadum) and Allied Kingfish(Seriola dumerili) has small changes. (3)In the future climate scenarios, the number of species potentially suitable for culturing increases significantly in the Bohai and Yellow Sea area, and in the South China Sea, the suitable areas for cultured Large yellow croaker(Larimichthys crocea), gold pompanos(Trachinotus ovatus), Cobia(Rachycentron canadum) and Allied Kingfish(Seriola dumerili) decrease significantly. Overall, the potential areas of each fish show a northward trend. • We forecasted the potential areas of offshore finfish aquaculture in China • Mapping the distribution of offshore finfish aquaculture in China under current and future climate scenarios • Provides information for the selection of the offshore aquaculture species and the sea area planning in China • Provides information on the development direction for China's offshore aquaculture in response to climate change [ABSTRACT FROM AUTHOR]

The sedimentary sequences of the Yangtze River delta comprise important Quaternary records of tectonics, sea-level oscillation, and climatic change; however, analysis is hampered by a lack of a reliable chronological framework. In this paper, we present an integrated chronology for two sedimentary sequences (core ZKW2 and ZKW4) on the southern side of the Yangtze River delta, based on magnetostratigraphy and absolute methods (OSL, 14C, and ESR dating). The basal ages of the core ZKW2 and ZKW4 are ca. 2.25 Ma and 2.96 Ma, respectively. The integrated chronology indicates significant increases in the sedimentary accumulation rate at ∼0.15 Ma, rather than the Matuyama-Brunhes boundary as indicated by magnetostratigraphy alone. The observed sedimentary transition is possibly controlled by regional subsidence of the Zhe-Min Uplift, and climate evolution during the last interglacial period. • High-quality magnetostratigraphy is obtained for the Quaternary sediments in the YRD. • The SARs of the YRD sediments significantly enhanced since ∼0.15 Ma. • Tectonics and climate factors jointly control the sedimentary evolution in the YRD. [ABSTRACT FROM AUTHOR]

The development of dry ports has reshaped the international freight shipping market, introducing both competition pressure (i.e., the common hinterland) and cooperation opportunities (sea-rail intermodal) for seaports. This is more evident in China with the development of the China Railway Express. Unlike dry ports, seaports are more vulnerable to climate change-related disasters, calling for investment in adaptation measures. This paper examines how co-opetition with the dry port affects seaport adaptation investment using a two-stage game-theoretical economic model. Results indicate that cooperation leads to more seaport adaptation investment, while competition results in reduced investment. When compared to the social optimal level of adaptation investment, the seaport tends to under-invest (over-invest) when the cooperation (competition) market size is larger. We also analyze how government subsidies in the seaport's adaptation help achieve optimal social adaptation and how the Knightian uncertainty of the disaster occurrence affects seaport adaptation investments. The relevant policy implications are also discussed. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

• Transition zones are the hotspots of bioclimatic changes under global warming. • Global warming extends growing season lengths but increases heat and water stresses. • Sustainable grasslands in China shrink and shift northwestward with global warming. Bioclimatic response to global warming is a key linkage between anthropogenic climate change and ecosystem sustainability, particularly for the impact-prone climate transition zones. This paper examines changes in heat-water conditions from 2006 to 2100 across China, using the fifth generation climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) and bias-adjusted climate projections by the Coupled Model Intercomparison Project Phase 5 (CMIP5). We then assess the effects of these changes on habitat suitability for responsive ecosystems using a species distribution model. The results reveal significant changes in bioclimatic environments across dry–wet climate transition zones under the present-day climate and the RCP8.5 scenario. By the end of the 21st century, local growing season length (GSL) could extend by 60 days and 30 % of the GSL could be under heat stress. Water conditions worsen overall in both the air and the soil, despite some improvements in the middle parts of transition zones. With altered heat-water conditions, sustainable grasslands shift northwestward, with a reduction of approximately 131 million km2 (46.6 % relative to 2006–2010) in total area. These changes primarily arise from alterations in winter and spring heat-water conditions. Our findings highlight the climate transition zones as hotspots of ecosystem vulnerability demanding particular attention in impact assessment and adaptation studies. [ABSTRACT FROM AUTHOR]

Low-carbon technology has become the focus of addressing global climate challenges but is facing the supply restriction of critical high-tech metals. Recycling has become a powerful measure to solve this issue. In the paper, a comprehensive recycling potential index (RPI) is constructed to evaluate the recycling potential of high-tech metals for low-carbon energy technologies in China from 2020 to 2050, and development strategies are proposed based on the evaluation results. The results indicate that the future trends of recycling potential show four evolution modes – either reaching or rapidly rising to a high level, increasing to the middle and middle-high level, unsteadily staying at the low and middle-low level, or remaining at a low and continuously decreasing level. According to the evolution trend, different strategies, including key development, reserves, digestion, and transfer, should be adopted in different stages. Co, Li, Dy, Nd, Tb, and Eu should be the focus of technology, funds and policy from both the government and enterprises due to their high recycling potential in the long term. Moreover, measures should be taken to encourage recycling and mitigate the supply risk of high-tech metals for low-carbon energy technologies, including tracking the development of low-carbon energy technologies, adjusting the list of critical high-tech metals, promoting recycling technology, and exploring substitute resources. [Display omitted] • A comprehensive recycling potential index is constructed to evaluate the recycling potential of high-tech metals. • The future trends of recycling potential of high-tech metals show four evolution modes. • Strategies like key development, reserves, digestion, and transfer should be adopted in different stages. [ABSTRACT FROM AUTHOR]

Coastal wetlands provide valuable ecosystem services and understanding their response to past climatic changes may help predict their possible future responses. In this paper, we obtained records of pollen, algae, sediment grain-size, and other environmental proxies, from a late Holocene sediment core (CFD-E) from the Caofeidian area, on the northwest coast of the Bay of Bohai, China. Our results indicate three major stages of environmental change. During Stage I (3500–2800 cal yr BP), arboreal pollen content was high (mostly >60%), especially for Pinus and Quercus , and the PCA sample scores on Axis 1 were negative indicating that regional vegetation was temperate broadleaved forest and the climate was wet. During Stage II (2800–2350 cal yr BP), the arboreal pollen content decreased substantially (mostly <40%), and the PCA Axis 1 sample scores were positive indicating a decrease in forest vegetation, grassland expansion, and a drier climate. During Stage III (2350–1400 cal yr BP), the arboreal pollen content increased again (mostly >40%), although it remained lower than during Stage I, indicating that forests expanded under a relatively humid climate while the wetland area decreased slightly. Our results also record the 2.8 ka and 2.4 ka events of monsoon weakening, which were characterized by increases in herbaceous pollen (indicating grassland expansion) and the drying of the regional climate. There are several differences in the regional expression of these two climatic events. During the 2.4 ka event, Chenopodiaceae pollen increased substantially (average of 42.0%), indicating the expansion of halophytes; whereas during the 2.8 ka event, an increase in Artemisia indicates the occurrence of a dry climate throughout the region. We suggest that the aridity during the 2.8 ka event was triggered by decreased solar activity and the resulting changes in the El Niño-Southern Oscillation, which weakened the East Asian summer monsoon. However, we suggest that the 2.4 ka event was driven by the weakening of the Atlantic Meridional Overturning Circulation. • Significant increase in halophytic vegetation during 3500–1400 cal yr BP • The 2.8 ka and 2.4 ka events were characterized by climate drying lasting ∼150 years. • During these two events the area of forest decreased and grassland expanded. [ABSTRACT FROM AUTHOR]

The Carnian Pluvial Event (CPE) induced an intense carbon-cycle disturbance and biological crisis at a global scale. The eruption of the Wrangellia Large Igneous Province (W-LIP) is considered a possible triggering mechanism; however, this cannot fully explain the significant differences in environmental perturbations across different regions. In this paper, we present detailed records of petrography, mercury geochemistry, carbon and sulfur isotopes, trace elements, and provenance data for the Triassic lacustrine facies of the Ordos Basin in the North China Plate, which provide insights into the important effects of volcanic activities, other than the W-LIP, on palaeoenvironment during the CPE interval. Massive emissions of SO 2 , CO 2 , and pyroclastic deposits resulting from these volcanic activities triggered four humid episodes, each characterized by lake-level rise, negative δ13C org excursion, a transition from mudstones to organic-rich shales facies, as well as algal bloom within a time span of 180 kyrs. The establishment of an age framework in the Ordos Basin enables comparative analyses of environmental evolution during the Carnian age across the North China Plate, the western Tethys domain, and the South China Plate. During the period of global climate perturbation driven by the W-LIP eruption, we conclude that short-term localized volcanic activities may have further induced high frequentcy environmental perturbations, which influenced biological shifts and increase organic carbon burial. These short-term volcanic activities with different occurrence times and frequencies complicate local-scale palaeoenvironmental evolutions, which may be an important reason contributing to significant differences in environmental perturbations during the CPE interval across different regions of the globe. • Four humid episodes and sedimentary changes occurred within 0.18Ma in the Ordos Basin during Carnian age. • Environmental changes in the Ordos Basin was related to the local volcanisms in its nearby Qinling orogenic belts. • Short-term local volcanisms can complicate the environmental evolutions in different parts of globe during the CPE interval. • Local volcanic processes may cause inconsistent environment perturbation in different parts of globe during the CPE interval. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change. • Extreme heat increases the likelihood of residents purchasing health insurance. • Each additional day of extreme heat boosts health insurance purchases by 0.3%. • This effect varies among different populations. • Mechanistic analyses indicate extreme heat impacting physical and mental health. [ABSTRACT FROM AUTHOR]

Southwestern China, a biodiversity hotspot, underwent dramatic climate change following the Last Glacial Maximum and intensive human activity also exerted a major impact since the late Holocene. In this paper, we report a pollen record from Yilong Lake in Yunnan Province, southwestern China, to understand vegetation response to long-term climatic variation and human activities at a regional-level over the last 27,000 years. Findings show that temperate and coniferous taxa were dominant before 18 cal kyr BP reflecting the glacial climate. Between 18 and 14 cal kyr BP, thermophilic taxa increased in response to global deglaciation. A notable shift from deciduous to evergreen forests occurred at approximately 14 cal kyr BP, after which pollen concentration increased but pollen diversity decreased. Pollen assemblages indicated dense forests, primarily composed of evergreen oaks developed under warm and strong summer monsoon conditions from 13 to 8 cal kyr BP. High rates of vegetation change occurred during the middle Holocene before vegetation diversity gradually increased during the Holocene Thermal Optimum, with high variability of precipitation in the Yilong Lake region. Anthropogenic forcing progressively became the main factor affecting vegetation composition and vegetation change rates over the past three millennia. • We reported a pollen record from Yilong Lake in Yunnan province, China. • Cold-tolerant taxa dominated before 18 cal kaBP after which thermal-like taxa increased. • Evergreen forests replaced deciduous forests around 14 cal kaBP. • Vegetation change rates peaked in mid-Holocene with mega-thermal but frequent droughts. • Departure of vegetation and potential climax occurred in late-Holocene due to human activities. [ABSTRACT FROM AUTHOR]

This study explores the impact of political uncertainty on sustainable urban development by examining carbon emission trading systems (ETS) in four major markets in China (Beijing, Shanghai, Guangdong, and Hubei) from 2014 to 2022. As an alternative to carbon taxes, carbon ETS markets have become increasingly popular due to their success in reducing greenhouse gas emissions. However, their effectiveness is often hindered by political instability and uncertainty. Utilising logistic regression and AR(1)-GARCH estimations, we identify a negative relationship between political uncertainty and carbon trading volume. Our study also reveals significant variations in the responses of these markets to political uncertainty. The paper contributes to the understanding of how ETS markets operate in a complex and constantly changing political environment. We suggest that policymakers need to consider the impact of political uncertainty on carbon trading when designing and implementing urban policies that promote sustainable development. Additionally, our research contributes to the development of urban policies that can be effectively implemented in both developed and developing regions. • Local government official turnovers are used as the measurement of political uncertainty. • Daily transaction data from four carbon ETS markets (Beijing, Shanghai, Hubei and Guangdong) in China • Considered the probability and proportion of zero transaction day • Logistic regression and AR(1)-GARCH estimations • A negative relationship between political uncertainty and carbon transaction volume [ABSTRACT FROM AUTHOR]

• Forecasting-test framework for long-term power system planning. • Coal-fired generators can be completely withdrawn from the power system by 2060. • China's power capacity mix will transition to wind and solar generators dominated. • Biomass and gas-fired generators will take on the role of reserved generators. • The timing of achieving China's zero-coal power system may be advanced or delayed. Facing the challenges of climate deterioration, environmental pollution, and energy shortages, China has put forward the goals of "carbon dioxide peaking and carbon neutrality", and the electricity sector will be the key area and the main direction of carbon emissions reduction. To prospect China's power system and explore the potential for establishing China's zero-coal power system in the future, this paper proposes a forecasting-test framework for long-term power system planning. We predict, evaluate, and analyze China's power system from 2025 to 2060 using the proposed forecasting-test framework. During this process, the power capacity mix and the electricity generation mix of China's power system will gradually transition from coal-fired generators dominated to wind and solar generators dominated. Moreover, the roles of different generators and energy storages are illustrated through the seasonal comparison and sensitivity analysis of the installed capacity of generators. The results indicate that coal-fired generators can be completely withdrawn from the power system, confirming the feasibility and possibility of achieving China's zero-coal power system by 2060. Although the timing may be advanced or delayed in different scenarios, achieving China's zero-coal power system will require exercising nationwide planning and making joint efforts of various sectors from now on. [ABSTRACT FROM AUTHOR]

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. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop a framework to estimate future Flood Regulation Service (FRS) dynamics. • The framework considers the joint impacts of both climate change and urbanization. • Future FRS supply–demand imbalance will continue to intensify. • Future impacts of climate change in Baiyangdian Lake Basin cannot be ignored. • Cities should actively adapt to climate change to reduce flood risks in the future. Estimating the supply–demand relationship's future dynamics and trend of Flood Regulation Service (FRS) is important for preventing flood risks and choose an appropriate future development path. Less attention has been given to assessing the future trends in this relationship under the joint influence of climate change and urbanization. This paper aims to quantify future trends in the FRS supply–demand relationship under the joint impacts of climate change and urbanization. To this end, we took the Baiyangdian Lake Basin as an example and developed a "Climate Change-Urbanization-FRS supply and demand" framework by combining future climate scenarios from the ScenarioMIP (Scenario Model Intercomparison Project) dataset and socioeconomic data from the SSPs (Shared Socioeconomic Pathways) to estimate the FRS supply and demand dynamics during the period from 2020 to 2050. The results show that the framework has a reasonable ability to estimate the FRS supply–demand relationship. The correlation coefficients between estimated supply–demand ratios and the historical values exceeded 0.9. The average FRS supply–demand ratio among the four scenarios shows a significantly downward trend between 2020 and 2050. The FRS is expected to decrease by 0.159 (36.6 %), resulting in the imbalanced area increasing from 38.3 km2 (4.1 % of the whole basin) to 11049.7 km2 (36.2 %). We believe that although urbanization is the dominant factor contributing to the intensified imbalance trend (with a contribution of 71.2 %), influences from climate change also cannot be ignored (with a contribution of 28.8 %). Therefore, adaptation actions to climate change should be actively taken to reduce urban flood risks in the future. [ABSTRACT FROM AUTHOR]

Climate change and human migration are the key focus of scientific attention in developing countries to achieve sustainable development. Exploring the interaction between the two is informative about understanding the law of human migration, and grasping the trend of climate change, to achieve environmentally sustainable development. In recent years, a large number of studies and discussions about "climate migration", and "environmental refugees" were launched. However, most researchers focus on the relationship between climate change and human migration, and few researchers have noticed and discussed the impact of human migration on climate change. There is still a lack of interpretation of the relationship between the two. In order to make up for the shortcomings of existing studies, this paper takes Ningxia immigrants of China as an example, uses PEST model analysis, considers the four dimensions of Political, Economic, Social, and Technological as judgment criteria, and explains the impact of the bidirectional force between climate change and human migration on the external environment. Further explore how climate change impacts human migration through spatial analysis, and mapping using ENVI and Geographic Information Systems (GIS) tool. The findings of this are; (i) climate change and human migration interact with each other but do not have a direct effect, and the external environment is an important intermediate factor, (ii) climate change does not directly affect human migration, but forms a push for it through its impact on the external environment of the origin place, and at the same time, combined with the pull effect of the place of destination, and helps in smoothing this process, (iii) human migration does not directly affect climate change, but only creates operational space for capital and technology investment, and (iv) climate change and human migration interact through intermediate factors in the external environment, hence the need to strengthen cross-sectoral cooperation in different regions is of prime concern to promote environmentally sustainable social development. • Climate change and human migration become the key focus of scientific attention. • The concept of 'migration as adaptation' needs revisiting. • PEST model used to explain the impact of bidirectional force on external environment. • Migration, Climate change, and urban landscape are interrelated. [ABSTRACT FROM AUTHOR]

This paper matched the data for all non-financial listed firms in China from 1990 to 2017 with weather data and used temperature and precipitation to represent climate change. Using daily temperature and daily precipitation data, we constructed temperature bins and precipitation bins. This study presents a potential first empirical analysis that applies the risk perception theory to comprehensively examine the impacts of daily temperature and daily precipitation on firms' debt financing costs. Compared to a day with a suitable temperature, a day with temperatures above 30 °C increases firms' debt financing costs by 0.2411%. Compared to a sunny day, a day with torrential rain increases firms' financing costs by 0.2697%. Approximately $122.13 million and $20.49 million in extra costs were incurred across all firms in 2017. We conducted a series of heterogeneity tests. We found that the negative impacts of climate change on debt financing costs are greater for firms that investor considers more vulnerable. Finally, we found two possible mechanisms. First, from the firm's subjective initiative perspective, firms that respond proactively during seasons of high temperatures and heavy rains can reduce the negative impacts. Second, adverse weather caused by climate change may also increase firms' debt financing costs by blocking travel. These results enrich the literature on firms' debt financing costs and contribute to the understanding of climate change's impact on firms. [Display omitted] • An extra high-temperature day increases firms' debt financing cost by 0.2411%. • An extra heavy-rain day increases firms' debt financing costs by 0.2697%. • The negative impacts will be greater for those firms that investor considers more vulnerable. • Firms' response proactively can reduce the negative impacts. • Climate change also may increase firms' debt financing costs by blocking travel. [ABSTRACT FROM AUTHOR]