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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]

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]

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]

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

Henan Province is the birthplace of Chinese civilization and one of the earliest human settlements, which means that the area has an important national cultural heritage. Traditional villages are an important facet of this cultural heritage, and studying their spatiotemporal characteristics in different periods has important theoretical and practical significance for the sustainable development and protection of cultural heritage in the region. This paper takes the traditional villages of the Yellow River basin in Henan Province that were formed before 1919 as the research object. Information on the ancient river was obtained through a literature search as well as via field research, and the important tributaries of the Yellow River in different periods were mapped using ArcGIS 10.0 software. The nearest neighbor index, kernel density estimation, standard deviation ellipse and other methods were adopted to analyze the spatiotemporal characteristics of the traditional villages. The factors that influenced the evolution of traditional villages were explored in depth by combining changes in the course of the river and water conservancy projects. The results show that the formation of traditional villages along the Yellow River in Henan Province has experienced a historical track of growth, contraction, growth and prosperity and stability. The traditional villages along the Yellow River in Henan Province generally show a clustered pattern, forming a dense concentration of traditional villages in the middle reaches of the Yellow River. The center of gravity shows a migration trend from southeast to northwest. In terms of influencing factors, the spatiotemporal evolution of the relationship between villages and their distance to water is closely related to climatic fluctuations, changes in channel, water conservancy projects and social and cultural factors. This paper deepens our understanding of the relationship between traditional village evolution and watersheds by improving the consistency between village spatial distribution and historical geography and provides a useful theoretical reference for the sustainable development of China's traditional villages. [ABSTRACT FROM AUTHOR]

Steel sheeting is usually provided at the upper flange of purlin in steel roof with screw connections. The resulting diaphragm effect provided by the sheeting enhances the buckling resistance of the purlin. However, this diaphragm effect will be reduced due to any abnormality in the screw connection caused by wind-induced fatigue particularly from typhoon. This would reduce the buckling resistance of the purlin with sheeting (the purlin-sheeting system), and it would affect subsequent condition evaluation during their service life. This problem is addressed in this paper with a framework of time-dependent reliability evaluation of the buckling limit state of the purlin-sheeting system. The buckling resistance reduction due to the degradation of the diaphragm effect from typhoon is taken into account in the resistance model. The randomness of wind intensity and landfall occurrence of typhoon during the service life of purlin are also accounted for in the wind load effect model. The time-dependent reliability of the purlin at different positions of a roof is studied. Then the variation of reliability of the system due to the effect of climatic changes in the design service life is discussed. The proposed strategy is then applied to the evaluation of a purlin-sheeting system in eleven cities in China with typhoon occurrences with some useful results for future studies in the provisions of the design code. [ABSTRACT FROM AUTHOR]

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

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

Climate change is directly linked to a broad array of changes because of disorganized activities within the economic system and human intervention. Climate change affects the well-being status of both non-living and living things. Relevant policies to mitigate and adapt to climate change conditions concentrate on solutions that intend to use renewable energy instead of fossil fuels or other conventional energy sources. This study aims to process a review focused on how renewables advance environmental quality and create relevant benefits within severe economic activities. This study elaborates on the case of China for two main reasons. First, China has a pivotal role in the economic system worldwide. Second, China is making serious attempts to transition into a low-carbon economy. An integrative review was processed to receive selected publications. The advantage of this process is that it considers empirical and non-empirical studies, policy papers, and conceptual frameworks. Inclusion and exclusion criteria were applied to retrieve the final number of publications. Review results from 39 well-acknowledged Journals provided 180 selected publications categorized into seven study groups: data analyses, model optimization studies, market issues, renewable energy technology publications, nuclear energy publications, ocean energy publications, and policy-related studies. Policy implications concern China's efforts to accelerate the integration of renewables in the energy mix. Hence, the country should increase energy efficiency in consumption and process investment plans based on robust research and development efforts. [ABSTRACT FROM AUTHOR]

The Chinese government's use of fiscal policy, which includes fiscal income and spending, is crucial in its fight against environmental pollution and climate change. Innovation‐driven has arisen as a new alternative to reconcile economic success with environmental conservation in light of tighter resource restrictions and the suggestion of the Chinese High‐quality Development policy. The paper uses an econometric model to examine the connection between institutional resource consumption efficiency and carbon neutrality, using a data set consisting of Chinese inter‐provincial panel data from 2007 to 2020 as a research sample; fiscal decentralization is also discussed as a potential moderating factor. Collaborative innovation positively boosts ecological efficiency and produces geographical spillovers, and the findings suggest so long as the economic distance is considered. When it comes to increasing ecological efficiency, collaborative innovation plays a more important role than financial decentralization alone. Among these is the improvement of carbon neutrality, which is best achieved via the joint promotion of ecological efficiency and industrial organizations. By reducing the intensity of the positive effect of innovative cooperation on ecological efficiency, the moderating effect suggests that fiscal decentralization is a critical factor in this relationship. Promoting China's ecological efficiency necessitates a fair distribution of local budgetary spending. China should also actively encourage the degree of synergy between institutional resource consumption efficiency and associated institutions to improve eco‐efficiency. [ABSTRACT FROM AUTHOR]

Seamless prediction is a weather–climate integrated prediction covering multiple time scales that include days, weeks, months, seasons, years, and decades. Seamless prediction can provide different industries with information such as weather conditions and climate variations from the next few days to years, which have important impacts on economic and social development and important reference value for short-, medium- and long-term decision-making and planning of the country. Therefore, seamless prediction has received widespread attention from the international scientific community recently. As Chinese scientists have also carried out relevant research, this paper reviews the research in China on developments and applications of seamless prediction methods and prediction systems in recent years. Among them, the main progress of seamless prediction methods studies is reviewed from four aspects: short- and medium-range weather forecasting, subseasonal-to-seasonal, seasonal-to-interannual, and decadal climate prediction. In terms of development and application of seamless prediction systems, the main achievements made by meteorological operational departments, scientific institutes, and universities in China in recent years are reviewed. Finally, some of the issues in seamless prediction that need further study are discussed. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

The rainfall distribution in southwest China is uneven, and the rainstorm threshold cannot use in a unified standard. This paper synthesizes a calculation method for the extremely heavy precipitation threshold and the provision of the rainstorm threshold in meteorological operation. It calculates the daily precipitation rainstorm threshold at 400 national ground stations in southwest China. The rainstorm events from 1961 to 2021 were statistically analyzed using the rainstorm threshold and analyzing the spatial-temporal variation characteristics. The results show that the number of single-station rainstorm events and the average precipitation of single-station rainstorm events in southwest China decreased from east to west. The number and frequency of single-station rainstorm events in Guizhou, Sichuan, Tibet, and Chongqing are increasing, while the number of single-station rainstorm events in Yunnan is decreasing. There is no apparent spatial distribution pattern for the continuous rainstorm events in the southwest region. From 1961 to 2021, the number and frequency of rainstorm events at a single station in southwest China followed an upward trend. The number of rainstorm events at a single station increased by 16.7 times · (10a)−1, and the frequency of rainstorms increased by 9.9% · (10a)−1. The continuous rainstorm events show an increasing trend, with an increase of 0.1 times · (10a)−1. Using the rainstorm threshold in southwest China, the early warning threshold for rainstorm disasters can be adjusted. The temporal and spatial characteristics of rainstorm events since 1961 can analyze the changes occurring in rainstorm events under global warming and provide data to support the response of southwest China to climate change. [ABSTRACT FROM AUTHOR]

Tea (Camellia sinensis L.), as one of the most important cash crops in China, plays an important role in increasing farmers' incomes and guaranteeing a high quality of life. Tea production has been greatly influenced by both climate change and economic development in China. However, without a scientific understanding of the interaction mechanism of climate change and the impetus from rapid economic development on tea production practices in China, it is difficult to take adaptive actions to meet the climate change challenges for the tea industry. In this paper, we firstly assessed the potential impacts of climate change on tea climate suitability by empirical formula calculation using meteorological data; then, the effects from the additional climatic stress due to warming on tea production were detected with the annual statistical tea yield record on a municipal level. The contribution of socioeconomic development to the tea industry was evaluated with the comparison of the movement of China's national economy's and tea industry's gravity center during the period of 1987–2017. Finally, a conceptual adaptation framework was built to demonstrate the interaction mechanisms between climate change, tea production, and the economic development. The results showed that there was a negative impact of climate change on tea production in mainland China, with the percentage of high tea climate suitability (>0.9) areas dropping by 45% to 32%, while opportunities of enlarging the tea cultivating area emerged in the north tea production region where the tea climate suitability increased. We found that the tea planting area expanded northwards from 33° N in 1987 to 35° N in 2017 to take advantage of the favorable climatic resources due to warming, and tea planting decreased at an altitude of 100–400 m while increasing to higher altitude of 400–2000 m to avoid hot temperature damage and seek the optimum environment in high mountainous areas for tea production. In addition, the tea production moved westward along the longitude, decreasing obviously at 117–121° E while increasing significantly at 98–104° E and 107–110° E. Meanwhile, the tea production gravity center showed a westward movement consistent with the national economic gravity center moving trend, which means that tea industry development was driven by multiple socioeconomic factors and climatic forcings. A conceptual framework was built in this paper, aiming to show a robust adaptation mechanism for the tea system to maximize the benefits and minimize the damages from the altered climatic resources under rapid economic development in mainland China. The results in this study would help deepen the understanding of the adaptation process and practices for tea production in mainland China. [ABSTRACT FROM AUTHOR]

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

This paper examines the life-cycle wind resistant performance of a constructed long-span suspension bridge in the coastal region of China, aiming to quantify the multisource time-variant effects and uncertainties and offering a reference for designs of long-span bridges in the future. Randomness from modal frequencies, damping ratios, and identification uncertainty of flutter derivatives (FDs) was considered; then, their effects on probability of flutter failure and probability of exceeding the predefined buffeting response root-mean square (RMS) are discussed. Firstly, results of full-track tropical cyclone (TC) simulation under various climate warming scenarios are reviewed; then, the time-variant probability density function (PDF) of annual extreme wind speed is discussed. Secondly, 6-year modal frequencies and damping ratios of a long-span suspension bridge with a center-slotted section were extracted by fast Bayesian FFT method with structural health monitoring (SHM) data, which were utilized to explore the deterioration rules of structural properties. Thirdly, FDs were modeled from a probabilistic perspective based on complex Wishart distribution, which were identified in the turbulent flow and the frequency domain by Bayesian inference. The posterior distributions of FDs, namely identification uncertainty, were quantified by Markov chain Monte Carlo (MCMC) sampling. This paper finds that for flutter resistant performance, the time-variant effects (i.e., modal frequencies and PDFs of extreme wind speed) will make the flutter failure probability seven times larger than the initial value; for the probability of exceeding the predefined buffeting response RMS, however, the time-variant effects will make a negligible difference. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper analyzed the different relationships between earlywood and latewood as well as total tree-ring growth and the climate factors and reconstructed 106 years of May–June mean temperature (TMJ) in the Tongbai Mountains based on the earlywood width chronology of Pinus taiwanensis Hayata. It also analyzed the linkages to the Indian and Pacific Oceans. This paper found that earlywood width chronology has better response to the climate factors than latewood width and total tree-ring width. This study also found that the main limiting factors that restrained radial growth of Pinus taiwanensis Hayata in the Tongbai Mountains were May–June mean temperature and mean maximum temperature. The reconstructed TMJ series have a better reliability and are significantly negatively correlated with sea surface temperature (SST) over the tropical Western Pacific Ocean and Indian Ocean and are significantly positively correlated with SST over the subtropical Pacific Ocean. Finally, the periodic fluctuations of TMJ in the Tongbai Mountains might be related to the quasi-biennial interannual oscillation of SST over the Indo-Pacific equatorial region (QBO). The results of this study are significant for further understanding and exploring forest growth and climate change in the climatic transition zone. The Tongbai Mountains are an ecologically sensitive region to climate change, where there lies a climatic transitional zone from a subtropical to a warm–temperate monsoon climate. The northern boundary of Pinus taiwanensis Hayata is here; thus, climate information is well recorded in its tree rings. Based on developed earlywood width (EWW), latewood width (LWW) and total ring width (RW) chronologies (time period: 1887–2014 year) of Pinus taiwanensis Hayata in the Tongbai Mountains in central China, this paper analyzed characteristics of these chronologies and correlations between these chronologies and climate factors. The correlation results showed that earlywood width chronology contains more climate information than latewood width chronology and total ring width chronology, and mean temperature and mean maximum temperature in May–June were the main limiting factors for radial growth of Pinus taiwanensis Hayata. The highest significant value in all correlation analyses is −0.669 (p < 0.05) between earlywood width chronology and May–June mean temperature (TMJ) in the pre-mutation period (1958–2005) based on mutating in 2006. Thus, this paper reconstructed May–June mean temperature using earlywood width chronology from 1901 to 2005 (reliable period of earlywood width chronology is 1901–2014). The reconstructed May–June mean temperature experienced eight warmer periods and eight colder periods and also showed 2–3a cycle change over the past 105 years. The spatial correlation showed that the reconstructed series was representative of the May–June mean temperature variation in central and eastern China and significant positive/negative correlation with the sea surface temperature (SST) of the subtropical Pacific Ocean and the tropical Western Pacific Ocean and Indian Ocean from the previous October to the current June. This also indicated that May–June mean temperature periodic fluctuations might be related to the quasi-biennial oscillation (QBO) in the tropical Western Pacific Ocean and Indian Ocean. The results of this study have extended and supplemented the meteorological records of the Tongbai Mountains and have a guiding significance for forest tending and management in this area. [ABSTRACT FROM AUTHOR]

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area's precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen's Slope in the baseline and future periods with all RCPs. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Petrocodon Hance is one of the famous ornamental flowers, but most of them are assessed as extremely dangerous (CR), or at least above vulnerable (VU) due to climate turbulence and strong interference of human activities. To reconstruct the temporal and spatial changes of the potential suitable areas of Petrocodon since the last interglacial period, and explore the response of the suitable areas to environmental changes, which provided theoretical guidance for the origin of Petrocodon, the study of geographical differentiation, the conservation of unique germplasm resources in China, and the development and utilization of gardens. In this paper, combined with 120 distribution records and 17 environmental variables, the optimal MaxEnt model and geographic information technology (ArcGIS) were used to simulate the suitable areas and distribution pattern of Petrocodon in China and Indo-China Peninsula. Based on stepwise multiple linear regression analysis, redundancy analysis and Monte-Carlo test, the dominant variables affecting the current geographical distribution of Petrocodon were evaluated. The results were as follows: (1) The prediction accuracy of the optimized MaxEnt model was high, and the AUC value was greater than 0.96. The potential suitable areas of Petrocodon for the present distribution are continuous from Southwest China to North Vietnam, scattered in central and southern China and blocky in North Myanmar, of which the South Yunnan-Guizhou Plateau in China was the most suitable. (2) The environmental variables which restrict the geographical distribution of Petrocodon included precipitation of the driest month (bio14), precipitation of the warmest quarter (bio18), precipitation of the wettest quarter (bio16), SD of the temperature seasonality (bio4), min temperature of the coldest month (bio6) and altitude (alt). (3) Under the climate change scenario, the expansion and contraction areas of the suitable habitat of Petrocodon were located in the north and northeast of the current potential distribution area, which were sensitive areas susceptible to climate change. During the last interglacial period, the suitable area of Petrocodon expanded on a large scale, but there was almost no suitable distribution area of Petrocodon in the dry and cold environment during the last glacial maximum. After that, with the aggravation of climate warming, the suitable habitats of Petrocodon increased rapidly to high latitudes, while the suitable habitat in low latitudes decreased. (4) The centroid position of the suitable area for Petrocodon migrated northwards from Yongfu County, Guangxi (110.10° E, 24.69° N) to Chengbu County, Hunan (110.29° E, 26.05° N). To sum up, global warming has a positive impact on the potential distribution area of Petrocodon, but extreme warming will cause the suitable habitat of Petrocodon to shrink, and the niche of Petrocodon will narrow. Southwest China to North Vietnam, which has the advantage of mature karst landform, may be its main refuge. [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important policy in the current global response to climate change and has been widely recognized by various industries. In the process of promoting carbon neutrality, new energy plays a pivotal role. In this study, the definition and connotation of new energy and its role and specific operation in the energy transition of carbon neutrality are firstly explained. Promoting new energy development requires significant green and low-carbon investments. Taking China as an example, this paper analyzes the opportunities brought by the carbon neutral process to the field of green finance and analyzes the main features and development trends of green finance in China at present. Then this paper proposes policy recommendations to strengthen the development of green finance in China in terms of improving the green financial policy system, enhancing the supply capacity of green financial services, and optimizing the supporting environment for green financial development. Finally, this paper analyzes the measures and experiences of the United States in promoting low-carbon development and proposes countermeasures for China's low-carbon development on the basis of the five major relationships that need attention in China's carbon-neutral process. That is, strengthen the top-level design and improve the regulatory policy system; optimize the energy structure and increase the proportion of clean energy; optimize the industrial structure and reduce energy consumption in key industries; build a complete low-carbon technology system and promote low-carbon technology research and development and demonstration applications, and encourage local conditions to explore low-carbon development paths. The development of green finance can contribute to the advancement of new energy technologies, thus contributing to the achievement of carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top- 1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers. [ABSTRACT FROM AUTHOR]

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model. [ABSTRACT FROM AUTHOR]

The alpine grassland ecosystem accounts for 53 % of the Qinghai–Tibet Plateau (QTP) area and is an important ecological protection barrier, but it is fragile and vulnerable to climate change. Therefore, continuous monitoring of grassland aboveground biomass (AGB) is necessary. Although many studies have mapped the spatial distribution of AGB for the QTP, the results vary widely due to the limited ground samples and mismatches with satellite pixel scales. This paper proposed a new algorithm using unmanned aerial vehicles (UAVs) as a bridge to estimate the grassland AGB on the QTP from 2000 to 2019. The innovations were as follows: (1) in terms of ground data acquisition, spatial-scale matching among the traditional ground samples, UAV photos, and MODIS pixels was considered. A total of 906 pairs between field-harvested AGB and UAV sub-photos and 2602 sets of MODIS pixel-scale UAV data (over 37 000 UAV photos) were collected during 2015–2019. Therefore, the ground validation samples were sufficient and scale-matched. (2) In terms of model construction, the traditional quadrat scale (0.25 m 2) was successfully upscaled to the MODIS pixel scale (62 500 m 2) based on the random forest and stepwise upscaling methods. Compared with previous studies, the scale matching of independent and dependent variables was achieved, effectively reducing the impact of spatial-scale mismatch. The results showed that the correlation between the AGB values estimated by UAV and MODIS vegetation indices was higher than that between field-measured AGB and MODIS vegetation indices at the MODIS pixel scale. The multi-year validation results showed that the constructed MODIS pixel-scale AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m -2. Our dataset provides an important input parameter for a comprehensive understanding of the role of the QTP under global climate change. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (10.11888/Terre.tpdc.272587; H. Zhang et al., 2022). [ABSTRACT FROM AUTHOR]

Clues of climate change on the Alashan Plateau since the last glacial period (40 ka) are important for revealing the mechanism of desertification of middle-latitude deserts in the Northern Hemisphere (NH). Studies are still rare for the understanding of the specific relationship of climate changes between the Alashan Plateau and the global. Based on a systematic and comparative analysis of the existing research in China and the international academic community, this paper reviews the environmental evolution history of the Alashan Plateau since the last glacial period from the records of paleo-environment and geomorphological characteristics in different deserts of the plateau (e.g., Badanjilin, Tenggeli, and Wulanbuhe). From about 40 ka to the end of the last glacial maximum, the climate on the plateau was wetter than it is today, and to the end of the Pleistocene, the climate was generally dry and the aeolian activities were enhanced. However, the climate was arid during the whole last glacial period in the Wulanbuhe Desert, evidently different from the overall pattern of the plateau. The Tenggeli Desert was characterized by an arid climate in the early Holocene. The most controversial events for the Alashan Plateau are the drought events in the middle Holocene in the Badanjilin Desert. The role and impact of the westerlies and the East Asian Summer Monsoon (EASM) systems on the climate change of the desert and even the whole plateau is a vexed question that brings different views in different periods. There is still a lack of definite evidence representing the events of global environmental change that occurred on the plateau during the discussed period. The distinctive morphology of dune mountains and the distribution of sand dunes are mutually indicative of the direction and energy of wind systems on the plateau. It is suggested that appropriate wind energy is the significant key to the desertification in these middle-latitude deserts on the plateau. From a global-scale review of climate change, the desertification of the modern-scale sandy desert landscapes on the Alashan Plateau is generally related to the global glacial period and the cold and dry climate during the past 40 ka. [ABSTRACT FROM AUTHOR]

• A dengue model is proposed with parameters linked to climate and human factors. • Both local and global stability of the disease-free equilibrium are analyzed. • Sensitive analysis reveals a decisive role of temperature in dengue spread. • Sensitive analysis discloses a local role of precipitation and human population. • Climate changes aggregate dengue burden more than human population. Dengue fever (DF) is a re-emerging disease spread by mosquitoes. It is primarily found in the tropics and subtropics, and its prevalence is heavily influenced by global warming. A comprehensive understanding of how the changes in climate and human population affect future dengue epidemics is crucial for effective prevention and control. In this paper we extend a mechanistic compartmental model for mosquito dynamics of immature and mature stages, coupled with human population dynamics. Stability analysis of the disease-free equilibrium is carried out analytically, and the basic reproduction number is derived. Model parameters are explicitly linked to climatic variables and human population density. Model validation suggests that the basic reproduction number acts as a reliable measure of the spread ability of DF in response to future scenarios of climate and human population change. Our model predicts that the risk area of DF will expand considerably in mainland China, and the expansion fronts are mainly extended in the center and east. Most importantly, sensitivity analysis and model prediction both show that while temperature is critical in determining the threshold suitability for DF transmission, precipitation and human population density act locally to regulate the spreading DF patterns, where high values of these two factors may significantly accelerate the spreading process. Our results indicate a strong call for increased attention in the areas that are currently safe from DF, but climatically suitable for DF spread as consequence of the fast-economic growth and rapid urbanization. [ABSTRACT FROM AUTHOR]

The North Yellow Sea, located at the intersection of the Eurasian continent and North Pacific Ocean at mid-latitudes, is a sensitive area subjected to the joint actions of the ocean, land, and monsoons. On its southern shore, loess and paleosol sedimentary sequences were widely developed during the last interglacial period, which is of great significance for revealing patterns of climate change and dynamic conditions. In this paper, we focus on the Zhifu section (ZFS) on Zhifu Island within the Shandong Province of China. The optically stimulated luminescence (OSL) dating method was used to construct our chronological framework. Grain size and its endmember (EM) components were then analyzed; EM1 is a clay component EM, which represents a weak dynamic environment and strong weathering pedogenesis, while EM2 and EM3 are silt and very fine sand component EMs, respectively, representing a strong dynamic environment and weak weathering pedogenesis. Maximum EM1, mean grain size, clay content, and pH values occur in the paleosol layers (ZF4, ZF6, and ZF8), with minimum values in the loess layers (ZF5 and ZF7); EM3 values show the opposite pattern. This indicates that the ZF4, ZF6, and ZF8 layers represent warm and humid environments with abundant precipitation, where the East Asian summer monsoon (EASM) was enhanced, corresponding to Marine Isotope Stages (MIS) 5a, 5c, and 5e. In contrast, ZF5 and ZF7 represent sub-warm and humid environments with less precipitation, where the EASM was weakened, corresponding to MIS 5b and 5d. Among these stages, MIS5e is the warmest and wettest. These climatic events reveal the pattern of climate fluctuation over a ten-thousand-year timescale; they are synchronous with climate changes recorded in other geological repositories, such as cave stalagmites in southern China and sea-level fluctuations in the Yellow-Bohai Sea, which result from changes in global solar radiation. [ABSTRACT FROM AUTHOR]

Climate change has a significant impact on agriculture so it is necessary to adapt to climate change to promote agricultural transformation and sustainable development. The key to achieving such a goal is to promote the development of climate smart agriculture (CSA) against the background of climate change. The paper first uses official statistical data to evaluate the effect of climate smart agricultural technology project, and then uses the statistical method of questionnaire survey to further investigate and statistically analyze the implementation effect of climate smart agricultural technology project in the pilot area. Further, semi-structured interview method is employed to conduct more in-depth investigation and analysis on some main topics on the basis of preliminary investigation and statistical analysis. The interviews focus on the environmental and economic effects of project practice, the difficulties of smallholder farmers' technology extension, and the farmers' willingness to participate. The study indicates that to promote climate smart agriculture technologies is an effective way to solve agricultural problem in practice under the background of climate change, and can achieve at least three benefits. The first is to reduce production costs, which can be reduced by 10% to 15% in terms of fertilizers and pesticides alone. The second is to improve productivity, and preliminary results show that food production can be increased by more than 5%. Finally, it has carbon sequestration capabilities and can significantly reduce greenhouse gas (GHG) emissions. Therefore, the promotion of climate smart agriculture (CSA) technologies helps to solve the problem of agricultural transformation and sustainable development. To this end, it is necessary to drive the transformation and optimization of regional agricultural ecological environment and production system, and promote the innovation and extension of CSA technology. In addition, some soft conditions (e.g., talent, system and technology, etc.) and hard conditions (e.g., modern agricultural supply chain, agricultural big data and the Internet of Things, etc.), must be created, too. [ABSTRACT FROM AUTHOR]

Sanjiang Plain is the largest marsh distribution area of China, and marshes in this region significantly affect regional carbon cycle and biodiversity protection. The vegetation phenology of marsh significantly affects the energy exchange and carbon cycle in that region. Under the influence of global climatic change, identifying the changes in phenology and their responses to climatic variation in marshes of Sanjiang Plain is essential for predicting the carbon stocks of marsh ecosystem in that region. Using climate and NDVI data, this paper analyzed the spatiotemporal variations in the start (SOS), end (EOS), and length (LOS) of vegetation growing season and explored the impacts of climatic variation on vegetation phenology in marshes of Sanjiang Plain. Results showed that the SOS advanced by 0.30 days/a, and EOS delayed by 0.23 days/a, causing LOS to increase significantly (p <.05) by 0.53 days/a over marshes of Sanjiang Plain. Spatially, the large SOS advance and EOS delay resulted in an obvious increasing trend for LOS in northern Sanjiang Plain. The rise of spring and winter temperatures advanced the SOS and increased the LOS, and the rise in temperature in autumn delayed the EOS in marshes of Sanjiang Plain. Our findings highlight the necessity of considering seasonal climatic conditions in simulating marsh vegetation phenology and indicate that the different influences of climatic variation on marsh vegetation phenology in different regions should be fully considered to assess the marsh ecosystem response to climatic change in Sanjiang Plain. [ABSTRACT FROM AUTHOR]

Background: Desertification is one of the main obstacles to global sustainable development. Monitoring, evaluating and mastering its driving factors are very important for the prevention and control of desertification. As one of the largest deserts in China, the development of desertification in Otindag Sandy Land (OSL) resulted in the reduction in land productivity and serious ecological/environmental consequences. Although many ecological restoration projects have been carried out, the vegetation restoration of OSL and the impact mechanism of climate and human activities on desertification remain unclear. Methods: Taking OSL as the research area, this paper constructs the desertification index by using the remote sensing images and meteorological and socio-economic data, between 1986 and 2016, and analyzes the spatio-temporal evolution process and driving factors of desertification by using trend analysis and spearman rank correlation. Results: The results showed that: (1) Desertification in the OSL has fluctuated greatly during the past 30 years. Desertification recovered between 1986 and 1990, expanded and increased between 1990 and 2000, reduced between 2000 and 2004, developed rapidly between 2004 and 2007, and recovered again between 2007 and 2016; (2) The desertification of OSL is dominated by a non-significant change trend, accounting for 73.27%. In the significant change trend, the area of desertification rising trend is 20.32%, which is mainly located in the north and east, and the area of declining trend is 6.41%, which is mainly located in the southwest; (3) Desertification is the result of the superposition of climate and human activities. Climate change is the main influencing factor, followed by human activities, and the superposition effects of the two are spatio-temporal differences. Conclusions: These results shed light on the development of desertification in OSL and the relative importance and complex interrelationship between human activities and climate in regulating the process of desertification. Based on this, we suggest continuing to implement the ecological restoration policy and avoid the destruction of vegetation by large-scale animal husbandry in order to improve the situation of desertification. [ABSTRACT FROM AUTHOR]

In line with the United Nations Sustainable Development Goal (SDG) 6, the main goal of the Special Issue on "Remote sensing for water resources and environmental management" was to solicit papers from a diverse range of scientists around the world on the use of cutting-edge remote sensing technologies to assess and monitor freshwater quality, quantity, availability, and management to ensure water security. Special consideration was given to scientific manuscripts that covered, but were not limited to, the development of geospatial techniques and remote sensing applications for detecting, quantifying, and monitoring freshwater water resources, identifying potential threats to water resources and agriculture, as well as other themes related to water resources and environmental management at various spatial scales. The Special Issue attracted over thirteen peer-reviewed scientific articles, with the majority of manuscripts originating from China. Most of the studies made use of satellite datasets, ranging from coarse spatial resolution data, such as the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), to medium spatial resolution data, such as the Landsat series, ERA5, Modern-Era Retrospective Analysis for Research and Application Land version 2 reanalysis product (MERRA2), CLSM and NOAH ET, and MODIS (Moderate Resolution Imaging Spectroradiometer). Google Earth Engine (GEE) data, together with big data processing techniques, such as the remote sensing-based energy balance model (ALEXI/DisALEXI approach) and the STARFM data fusion technique, were used for analyzing geospatial datasets. Overall, this Special Issue demonstrated significant knowledge gaps in various big data image processing techniques and improved computing processes in assessing and monitoring water resources and the environment at various spatial and temporal scales. [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]

Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem. [ABSTRACT FROM AUTHOR]

China's economy has made significant strides in the past three decades. As a direct result of China's "one belt, one road" (OBOR) initiative, the country's rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely dependent on the enormous amounts of energy currently being consumed and forms the foundation of the world's high levels of carbon emissions. It is generally agreed that the production of greenhouse gases, particularly carbon dioxide, is the primary contributor to the current state of climate change. In this paper, a CO2 emission prediction model based on Bi-LSTM is constructed. In order to conduct empirical tests on the model, this study uses data from South Asian countries and China from 2001 to 2020. China's CO2 emissions from 2022 to 2030 were predicted along with those of other countries in order to study the combined effects of the scientific and technological progress, industrial structures, and energy structure factors affecting CO2 emissions. When compared with the LSTM and GRU methods, the Bi-LSTM model's results produced lower MAE, MSE, and MAPE values, indicating that it performs better. According to the findings, carbon emissions represent a significant problem that will become much worse in the future due to China and India's high emissions, particularly in the next 10 years, if the government does not implement policies that help reduce those emissions. [ABSTRACT FROM AUTHOR]

Vegetation degeneration has become a serious ecological problem for karst regions in the Anthropocene. According to the deficiency of long serial and high-resolution analysis of karst vegetation, this paper reconstructed the variation of vegetation landscape changes from 1987 to 2020 in a typical karst region of China. Using Landsat time series data, the dynamic changes and driving factors of natural karst vegetation were identified at the landscape scale. On the premise of considering the time-lag effect, the main climatic factors that influence vegetation growth were presented at the interannual timescale. Then, the approach of residual analysis was adopted to distinguish the dominant factors affecting vegetation growth. Results of trend analysis revealed that 21.5% of the forestland showed an overall significant decline in vegetation growth, while only 1.5% showed an increase in vegetation growth during the study period. Precipitation and radiation were the dominant meteorological factors influencing vegetation at the interannual timescale, as opposed to temperature. More than 70% of the natural vegetation growth was dominated by climatic factors. The area percentage of negative human impact has increased gradually since 2009 and reached 18.5% in 2020, indicating the currently serious situation of vegetation protection; fortunately, in recent years, human disturbances on vegetation have been mitigated in karst areas with the promotion of ecological conservation and restoration projects. [ABSTRACT FROM AUTHOR]

In recent years, extreme weather events caused by global climate change have occurred frequently, intensifying the frequency of flood disasters. For flood hazard analysis, high-quality data and a reasonable weight assignment of the relevant factors are critical. This study conducts four rainfall fusion methods, to fuse the Tropical Rainfall Measuring Mission (TRMM) 3B42 and the observations in Dazhou City, China. Then, the random forest was applied to obtain the weights of various factors to facilitate a comprehensive flood hazard analysis under four rainfall durations. The results show that (1) the linear regression performs best out of the four fusion methods, with a correlation coefficient of 0.56; (2) the Digital Elevation Model (DEM) is the most impact factor with a weight of more than 0.2; and (3) the proposed flood analysis system performs well, as 70% of historical flood points are distributed in high and sub-high hazard areas and more than 93% of historical flood points are distributed in medium hazard areas. This study identified the flood hazard grade and distribution in Dazhou City, which could provide a valuable methodology to contribute to flood hazard analysis and disaster management with satellite rainfall. Furthermore, the results of this paper are profound for future work on the high-resolution flood risk assessment and management in Dazhou City. [ABSTRACT FROM AUTHOR]

China's declaration to the international community to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 is of great significance in advancing the objectives of the Paris Agreement, and has a positive and far-reaching impact on China's high-quality development. This paper expounds on responsibilities and ambitions in tackling climate change, analyzes the high-quality development opportunities brought about by CO2 emissions peak and carbon neutrality, and discusses the net zero carbon emissions transformation in the new era of ecological civilization. This paper is of the view that development towards net zero carbon emissions provides a new impetus for building a Beautiful China, and promoting ecological civilization and green development. The essence of carbon neutrality should be correctly understood so that the world will work together to improve climate resilience. China should also deepen the understanding of the principles and methodologies of climate change economics. [ABSTRACT FROM AUTHOR]

This paper explores the non-technological innovation system for building low-carbon cities in China. It establishes a comprehensive evaluation index system and grading standards for low-carbon cities, concerning both technological innovation and non-technological innovation factors. Defining non-technological innovation factors as independent variables, GDP per capita as the main control variable, and low-carbon development and carbon productivity as dependent variables, this paper examines the contribution of non-technological innovation to the building of low-carbon cities. The result shows that non-technological innovation manifested a significant trajectory of progress. It demonstrates that the continuous improvement to non-technological innovation system should effectively promote the further development of low-carbon cities. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [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]

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]

With the aggravation of global warming and the increasing demand for energy, the development of renewable energy is imminent. Floating photovoltaic (FPV) is a new form of renewable energy generation. However, the impact of FPV on the aquatic environment is still unclear. By long-term empirical monitoring and data analysis, this paper reveals the shading effect of large-scale FPV power station on aquatic environment for the first time. The results show that: (1) Compared with the non-photovoltaic (NP) zone, FPV only significantly reduces the concentration of dissolved oxygen in the photovoltaic (P) zone. (2) The concentration of chlorophyll a , nitrate nitrogen and total phosphorus increase, while pH and ammonia nitrogen decrease. FPV only causes an effect of the same order of magnitude as the initial concentration, and has no significant adverse effects on the nutritional status of the water body at a coverage ratio less than 50%. (3) FPV has a cooling effect on the water body during the daytime and a thermal insulation effect at night, with the most pronounced impact on peak water temperature (T w). The heating and cooling process of T w in P zone usually lags behind the NP zone by 1–3 h. The diurnal fluctuation and vertical difference of T w as well as the stability of water body are reduced under the shading of FPV, alleviating the influence of climate change on T w and water body stratification. (4) If 10% of the water area larger than 1 km2 in China are used to develop FPV, more than 900 million tons of CO 2 emissions can be reduced, and about 5 billion m3 water can be saved, which is significant in the context of climate change. In general, this paper provides a reference for the future aquatic environmental impact assessment of FPV and the formulation of related policies. • The impact of FPV on aquatic environment has been assessed. • The scale effect of FPV and impact of "fish-photovoltaic integration" are revealed. • Spatial-temporal and object specificity of impact on aquatic environment is reviewed. • The responds of FPV to the challenges of global climate change are further discussed. [ABSTRACT FROM AUTHOR]