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This paper investigates the impact of Chinese firms' environmental, social, and governance (ESG) performance on their financial constraint and financing activities. We find a negative association between firms' ESG performance and their financial constraint driven by the Chinese government's commitment to tackling climate change. Compared with state‐owned enterprises (SOEs), non‐SOEs have alleviated their financial constraint through both equity and debt issuance, thanks to the stock price appreciation and green credit. High‐pollution firms benefit from both equity and debt issuance, while low‐pollution firms mainly finance through equity issuance. Our findings demonstrate the leading role of the Chinese government in its domestic capital markets. [ABSTRACT FROM AUTHOR]

Taking China's provincial panel data from 2010 to 2020 as an example, this paper verifies that climate change, especially extreme climate change, can destabilize China's financial stability and explores the transmission path of climate risks with meteorological disaster losses as the channel variable. Our empirical results demonstrate that: (a) only after the extreme climate change breaks through a certain threshold, thus causing a significant impact on the financial system; (b) we cannot ignore the improvement of disaster prevention and reduction ability brought by the improvement of social and economic development level; (c) the impact of extreme climate change will spread to the financial system through the economic losses caused by meteorological disasters; (d) there is obvious regional heterogeneity in the spread of meteorological disaster losses to the financial system. Our results are robust to a wider battery of checks and have important policy implications. • This paper empirically tests the impact of climate change on financial stability. • Extreme climate change will damage China's financial stability. • The economic losses caused by climate disasters will spread to the finance. • The transmission of such losses has obvious regional heterogeneity. • This paper provides policy implication for coping with climate risks. [ABSTRACT FROM AUTHOR]

Net precipitation (NP) is the primary source of soil water essential for the functioning of vegetated ecosystems. By quantifying NP as the difference between gross precipitation and canopy interception evaporation, this study examined the dynamics of NP in China from 2001 to 2020 and the contribution of environmental factors to NP variations was investigated. The findings revealed a multiyear mean NP of 674.62 mm, showcasing a 2.93 mm/yr increase. The spatiotemporal variations in NP were mainly attributed to a remarkable increase in precipitation rather than canopy interception. Notably, climate (temperature, wind speed, surface solar radiation downward and vapor pressure deficit) and vegetation factors (leaf area index and net primary productivity) played a dominant role in NP in 61.53% and 15.39% of China, respectively. The dominant factors contributing to NP changes were vapor pressure deficit (mean contribution rate: −43.68%), temperature (mean contribution rate: 11.69%), and leaf area index (mean contribution rate: 2.13%). The vapor pressure deficit negatively exerts a negative influence on the southern and eastern regions. Temperature and leaf area index have the greatest effect on the northeastern and southwestern regions, respectively. The results provide valuable insights into the pivotal role of climatic and vegetation factors in ecohydrological cycles. [ABSTRACT FROM AUTHOR]

Recent research shows that China is experiencing significant greening, with afforestation initiatives being the main cause. Quantitative calculation of vegetation change influencing factors and evaluation of the contribution of afforestation to vegetation greening in China are critical to coping with climate change and improving the implementation and efficacy of forestry projects. We investigated the temporal and spatial dynamics of the Normalized Difference Vegetation Index (NDVI) from 1982 to 2020, and quantified the contribution of afforestation initiatives, a typical human activity, to the dynamic changes of vegetation. The results showed that NDVI in China has primarily increased in the last 39 years. 57% of the pixels increased, 27% were stable and unchanged, and 16% decreased. Climate change was responsible for 72.34% of vegetation restoration, while human activities were responsible for 27.36% of vegetation restoration, according to residual analysis. In the future, only 14% of the regions showed continuous growth of the NDVI, while the remaining regions showed obvious antipersistence (59% will go from increasing to decreasing, and 22% will go from decreasing to increasing). The contribution of climate factors to vegetation change will decrease in the future, and human activities will become more complex. Except for Huaihe River and Taihu Lake (SPHRTL), other forestry projects showed an increasing trend of NDVI after the implementation of ecological engineering. However, due to differences in climate conditions and ecological engineering implementation, there are differences in the benefits of forestry projects. Some forestry project areas still have obvious vegetation degradation, and appropriate forestry management is necessary. This work provides a quantitative analysis of vegetation change and its driving factors in China, which will help to cope with future climate change and provide a reference for the implementation and management of ecological projects. [ABSTRACT FROM AUTHOR]

This study modeled the habitat distribution of Pterocarpus santalinus, a valuable rosewood species, across China under current and future climate scenarios (SSPs126, SSPs245, and SSPs585) using MaxEnt. Our findings reveal that the current suitable habitat, spanning approximately 409,600 km2, is primarily located in the central and southern parts of Guangdong, Guangxi, Fujian, and Yunnan, as well as in the Hainan provinces, along with the coastal regions of Taiwan, and the Sichuan–Chongqing border. The habitat's distribution is significantly influenced by climatic factors such as temperature seasonality (bio4), mean temperature of the wettest quarter (bio8), annual mean temperature (bio1), and annual precipitation (bio12), while terrain and soil factors play a lesser role. Under future climate scenarios, the suitable habitat for P. santalinus is projected to expand, with a northeastward shift in its distribution center. This research not only sheds light on the geoecological characteristics and geographical distribution of P. santalinus in China but also offers a scientific basis for planning its cultivation areas and enhancing cultivation efficiency under changing climate conditions. [ABSTRACT FROM AUTHOR]

Global climate change has intensified the water cycle, leading to frequent extreme precipitation events, posing a significant threat to railway infrastructure and safety operations. Based on the analysis of past and future precipitation changes in China, this study investigates the impact of climate change on railway safety operations. The study reveals the following findings: (1) Under the influence of the intensified East Asian summer monsoon and the northward shift of the subtropical high during the 2017-2021 compared to the 2012-2016, precipitation has significantly decreased (120 mm) in the regions south of the Yangtze River and South China, while it has increased (60 mm) in the regions from the eastern of Northwest China to the middle and lower reaches of Yangtze River; The operational precipitation risk has decreased for Urumqi, Lanzhou, Qinghai-Tibet Group, Xi'an, and Wuhan railway bureaus (abbreviated as Bureau), while it has increased for Nanchang, Chengdu, Zhengzhou, Shanghai, and Shenyang Bureaus. Particularly noteworthy is that despite a decrease in total annual precipitation for Nanchang bureau (15.3 mm/a), the frequency of intense precipitation events has increased, leading to an increased operational precipitation risk. (2) During the 21[sup st] century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that most of the China will experience an increasing trend in precipitation, with significant increases in precipitation observed in the regions south of the Yangtze Rive, South and Southwest China. The higher the greenhouse gas emissions, the more pronounced the increasing trend in precipitation. (3) Compared to the 20[sup th] century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that the total annual precipitation hours, railway inspection, speed limit, and closure risk hours have all increased on a national scale during the 21[sup st] century. The operational precipitation risk for railways has also increased. The higher the alert level for railway precipitation (precipitation < inspection < speed limit < closure), the higher the proportion of risk hours compared to the 20th century. By the late 21[sup st] century, the railway inspection, speed limit, and closure risk hours have increased by 175%, 463%, and 647%, respectively, compared to the 20[sup th] century. [ABSTRACT FROM AUTHOR]

This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India. [ABSTRACT FROM AUTHOR]

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Faced with the impact of climate risks, what responses do local governments make, particularly in the domain of social public policy? This study uses provincial panel data from China from 2009 to 2020 to investigate how climate risks affect local government education expenditure and its mechanisms. Analysis using spatial econometric models reveals the following. First, local climate risks significantly increase government education expenditure. This conclusion remains consistent across different proxy variables, model specifications, and estimation methods. Additionally, there is a spatial dependency on local government education expenditure, meaning that educational spending in neighboring areas positively influences the education expenditure of a specific location. Second, further mechanism analysis shows that climate risks lead to credit easing and drive the digital economic transformation of a location, thereby increasing its education expenditure. Third, considering the heterogeneity in the spatial dimension, it is found that this positive impetus exists only in the economically more developed eastern region. This study provides insights into understanding how the Chinese government responds to the impact of climate risks and its fiscal policy choices. [ABSTRACT FROM AUTHOR]

In recent years, global climate change and human alterations to land use have led to a decrease in ecosystem services, making ecosystems more vulnerable. However, unlike the well-established risk assessment frameworks used in natural disaster research, the concept of ecological risks arising from changes in land use is still in its early stages, with its nuances and assessment methodologies yet to be clearly defined. This study proposes a new framework for assessing ecological risks resulting from changes in land use in the Tarim River Basin. The framework employs a coupled PLUS and Invest model to evaluate the ecological risks of land use change under three development scenarios projected for the Tarim River Basin in Xinjiang by 2035. The findings indicate that: (1) Between 2000 and 2020, the predominant land use types in the Tarim River Basin in Xinjiang were primarily unused land, followed by grassland and cropland. Conversely, grassland, water, and construction land were relatively less prevalent. During this period, the area of unused land and cultivated land increased, while grassland, forest land, and water exhibited a declining trend. Moving forward, under the three scenarios from 2020 to 2035, land use changes in the study area are characterized by the expansion of cropland and unused land, coupled with a significant decrease in grassland area, while other land categories demonstrate minor fluctuations. (2) From 2020 to 2035, across various scenarios, the total ecosystem service within the study area demonstrates an overall increasing trend in both the northern and southern marginal zones. Specifically, under the baseline scenario, the total amount of ecosystem services in the study area decreased by 15.247% compared to 2020. Similarly, under the economic development scenario, this decrease amounted to 13.358% compared to 2020. Conversely, under the ecological protection scenario, the decrease reached 19.852% compared to 2020. (3) The structure of ecological risk levels from 2020 to 2035, across multiple scenarios, demonstrates a consistent pattern, characterized by a predominant proportion of moderate risk. Conversely, other risk levels occupy relatively smaller proportions of the area. [ABSTRACT FROM AUTHOR]

As the largest terrestrial organic carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle, but it is easily affected by land use and climate change. The Huang-Huai-Hai Plain (HHHP) in China, which is dominated by dry farming, is experiencing rapid farmland loss and gain (farmland use transition), which may cause drastic changes in SOC storage. To clarify the effects of farmland use transition on SOC in dry farming areas, this study adopted a land use transition matrix and spatial analyst tool to explore the characteristics of farmland use transition and its effects on SOC content and stocks in the 200 cm soil layer in the HHHP from 2000 to 2020. The results showed that the farmland use transition in this area during that time period resulted in a net decrease of 16.06 × 103 km2 of farmland, of which urban built-up land and rural settlements led to a net reduction of farmland by 9.74 × 103 km2 and 6.43 × 103 km2, respectively, which was mainly affected by climate, topography, and economic factors. In addition, the farmland use transition resulted in a net increase in SOC storage of 6.13 Tg C, contributing 44.32% of the net increase. This is likely because the change in land use type led to a change in soil bulk density and soil gravel content while altering the SOC content, which in turn affected the SOC stock. This study has important implications for addressing global climate change and maintaining sustainable agricultural resources. [ABSTRACT FROM AUTHOR]

Study region: China. Study focus: In the context of global warming, droughts occur more frequently and have caused great losses to human society. Therefore, understanding the potential changes in future droughts under climate change is of great scientific significance for disaster prevention and mitigation. In this paper, combining with climate models from CMIP6, the emergent constraint and the skill scoring methods are used to analyze the characteristics of meteorological, agricultural and hydrological droughts in China under four socioeconomic scenarios in the mid and late 21st century. New hydrological insights for the region: In the mid-21st century, there are more frequent meteorological, agricultural and hydrological droughts in northern China. In the late 21st century, sustained and more intense droughts are more likely to occur in China than in the mid-21st century. Additionally, the relationship between meteorological drought and agricultural/hydrological drought is strengthened to varying degrees in the future. From the perspective of extreme drought events, the probabilities of extreme drought events with long duration and high severity increase significantly in Northwest and Central China under each scenarios. In a higher socioeconomic scenario, drought is suppressed in the mid 21st century, but is intensified in the late 21st century. These findings are of great significance for drought monitoring under climate change and can provide a basis for developing measures to respond to drought.

To mitigate climate change and achieve sustainable development, Chinese governments have introduced "1+N" "dual-carbon" policy system aimed at reducing CO 2 emissions, transforming energy structures and controlling pollution. An effective policy mix and synergy is crucial for achieving the emission reduction targets and for ensuring the effectiveness of the policies, and it is therefore of great practical importance to provide a pathway for policy synergy based on assessing policy effectiveness. This paper selects three policies, namely the carbon Emission Trading System (ETS), Coal Control and Clean Utilization (CCCU), and Green Financial Reform and Innovation Pilot Zone (GFPZ), sets up ten scenarios, adopts difference-in-differences (DID) models to evaluate the impact, and give a pathway for policy synergy. The results show that ETS, CCCU, and GFPZ policies have significant positive effects on carbon emission reduction, energy structure transformation, and industrial environmental pollution control, respectively; CCCU has synergistic effects with ETS and GFPZ policies in controlling coal consumption and increasing the completion of industrial pollution control investments, respectively; while GFPZ policies have conflicting effects with CCCU and ETS in reducing carbon emissions and coal consumption, the GFPZ policy has conflicting effects with CCCU and ETS in reducing carbon emissions and controlling coal consumption. Finally, the study proposes a phased policy support system around carbon emission reduction in the power generation industry, energy structure transformation, and industrial environmental pollution control before 2030 and from 2030 to 2060. [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]

The intensification of the regional water cycle resulting from climate change, coupled with the influence of human activities, has brought about alterations in the frequency, scale, and intensity of droughts. In this study, based on hydrological big data and the standardized runoff drought index (SRI), the multi-scale spatiotemporal evolution of hydrological drought in China from 1948 to 2014 was analyzed using the run-length theory and gravity center model. Meanwhile, the hydrological drought hazard index was constructed to analyze the distribution of the hazard levels of drought in China. The results showed that, during 1948~2014, there was an opposite spatial distribution between the average intensity and the average coverage–duration–frequency of drought in the Yellow River Basin, Haihe River Basin and southeastern river basins. The drought situation in most river basins in China has shown an aggravating trend, among which the southeastern river basins, Haihe River Basin, Songliao River Basin and Pearl River Basin have generally shown an aggravating trend. The drought situation in China was severe in the 1950s and 1960s, gradually reduced in the 1970s, 1980s, and 1990s, and the drought situation was the mildest in the 1990s. After entering the 21st century, the drought situation began to worsen sharply. Meanwhile, from 1948 to 2014, the hazard level of drought generally presented a pattern of high in the west and north, and low in the east and south. The hazard levels of drought in the northwest and northeast were generally higher, and those in the southwest and southeast regions were generally lower. In general, the hazard levels of drought were relatively high in most areas of China. [ABSTRACT FROM AUTHOR]