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Understanding ancient climate changes is hampered by the inability to disentangle trends in continental ice volume from records of relative sea-level change. As a unique coastal deposit in tropical and subtropical regions, beachrock has been proved to be reliable for constraining the glacial meltwater signal and thus the total volume of land-based ice in Quaternary. However, beachrock is rarely recognized in the fossil record due to (a) the two-dimensional distribution of beach deposits, as opposed, for example, to extended platform sediments, and (b) the fact that specific environmental conditions are required in order to lithify sediments directly on the beach. By combining the stratigraphic architecture with petrography of characteristic carbonate cements, we demonstrate the first known occurrence of Ordovician beachrock in the Tarim Block, northwestern China. According to biostratigraphic data, a middle Katian (Upper Ordovician) palaeokarst surface is capped by carbonate conglomerate beachrock and this is suggesting a significant relative sea-level rise in late Katian. The beachrock can be correlated with widespread subaerial exposure surfaces and a pronounced stratigraphic gap within the Katian in northwestern Tarim. We suggest that the beachrock ‘fingerprinted’ a strong melt-water pulse in high latitudes after a short-lived Katian glaciation, which has not received much attention in scientific papers so far. [ABSTRACT FROM AUTHOR]

[Display omitted] • A method for spatiotemporal coordination of multienergy systems is proposed. • Virtual energy storage gain is calculated based on spectral analysis. • The hydropower regulation ability affects the virtual energy storage gain. • The optimal coordination range between multiple energy sources is obtained. Utilizing the spatial heterogeneity and climate periodicity of various available renewable energy sources can enhance the multienergy complementarity, which will further reduce the energy storage demand and contributes to the "virtual energy storage gain." In this paper, we propose a spatiotemporal coordination method based on spectral analysis for a wind-PV-hydropower system that targets the maximum virtual energy storage gain. The complementary effect of hydropower on wind and PV power can be seen as changes in the regulation ability resulting from the hydropower construction development as well as a decreased variance in the total system production output. This method is used to determine the optimal coordination distance of multiple energy sources that are matched over different periods representing typical climate variation. A case study in the Yalong River basin in China obtains the best range of hydropower bundling surrounding wind power and PV power stations under different hydropower construction planning scenarios, and it reveals that increased regulation capacity of hydropower will reduce the optimal coordination distance but can achieve more energy balance if both actual storage and virtual storage is accounted for. This approach can realize energy delivery with the optimal coordination distance to meet intensive and efficient development needs, which can provide guidance and support for the planning and construction of wind-PV-hydropower storage systems. [ABSTRACT FROM AUTHOR]

• The composition structure of the disaster economic resilience theory has been further developed and quantitatively verified. • The correction effect of the resilience on the economic fluctuations (secondary shock) that occurred during the recovery process has been quantitatively evaluated. • The sustainable improvement of the economic system's performance by the resilience at the end of the post-disaster recovery process has been quantitatively evaluated. • Results can provide a multi-dimensional optimization plan for improving the efficiency of post-disaster recovery and reconstruction management. Quantitative measuring disaster resilience especially dynamic economic resilience (DER) belongs to a frontier research in the past decades, which can effectively improve post-disaster economic recovery effects, reducing post-disaster loss. However, DER focuses more on the overall shape changes of recovery path, two features that commonly appear in the dynamic change process of recovery curve are also worth evaluating separately: the "secondary shock" caused by adverse factors during the recovery process and sustainable improvement of economic output at the end of recovery. Therefore, we adopt a dynamic input–output model that integrates capital damage and affected people and apply it to an extreme flood in 2016, Wuhan City, China, building the relationship between 7 recovery actions (rescue funds) and changes of two features, analyzing the impact of resilience on the dynamic recovery path features through 6 characteristic variables constructed in this paper. Results show that (1) economic resilience increases from no to actual action, the dropping rate caused by "secondary shock" decreases 30.4%, and Wuhan's economic output has achieved an improvement in sustainability of 0.088% compared to the pre-disaster level, which contributes permanently to reducing vulnerability to future disasters. (2) only 21.81% (compared to the actual scenario) of the rescue funds is needed to support 30% reduction action plus 0.02% sustainable improvement. But to support the 50% recovery action, 78.92% of the rescue funds is needed. This paper aims to provide a new perspective for the refined dynamic assessment of resilience and to prove the role of resilience in promoting short-term post-disaster recovery and long-term sustainable development. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative was proposed by China in 2013 to promote the interconnected development and prosperity of all participating countries. In the context of global response to climate change, understanding the embodied carbon transfer change along economic trade before and after the Belt and Road Initiative is essential to reduce carbon overall emission. In this paper, we used a multi-regional input-output model to study the embodied carbon transfer in trade between the Belt and Road countries that have signed cooperation documents with China from 2004 to 2017. The results showed that from 2004 to 2017, the growth rate that China's carbon emissions imported from other Belt and Road Initiative countries was about 1.9 times that of its exports. From 2004 to 2017, the proportion of China's carbon imports from other Belt and Road countries in China's total carbon imports increased from 3.41% to 3.73%, and exports decreased from 6.52% to 6.03%. In both 2004 and 2017, Electricity, Gas and Water sector, Heavy Industry sector, Transport sector were the three largest carbon transfer sectors in China's multilateral trade. In 2017, the embodied carbon transfer by multilateral trade among other Belt and Road countries except China increased by 15.53% compared with 2004. By comparing the characteristics of carbon transfer between China and the Belt and Road countries from 2004 to 2017, this study will provide insights for carbon emission reduction policy setting of Belt and Road Initiative countries. • We took countries that have signed documents with China as research objects. • MRIO model was used to analyze the carbon transfer change from 2004 to 2017. • The embodied carbon transfer in 2017 of BRI increased by 15.53% compared with 2004. • The growth rate of China's carbon imports from BRI was 1.9 times that of exports. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds. • A SWAT-based model was established for a multi-level simulation. • Response of hydrological process to a climate-driven vegetation change was explored. • Effect of climate and vegetation changes on hydrological process was quantified. [ABSTRACT FROM AUTHOR]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction. • This paper investigates the impact of carbon emission trading market on the carbon reduction. • China provides an excellent "Quasi-natural Experiment" for assessing the role of carbon emission trading market in environmental management. • It is found that policy implementation has significantly reduced various types of carbon emissions, and this reduction effect is long-term. • Stimulating the vitality of the carbon market and expanding the supply and demand of carbon quotas are the main ways to achieve carbon emission reduction. [ABSTRACT FROM AUTHOR]

Due to the national nutrition crisis and the adjustment of planting structure, millet has once again become a widely planted cash crop in Northern China. However, as the climate warms in recent years, drought has occurred frequently and repeatedly in Northern China, which has seriously threatened millet production safety in this area. Therefore, it is urgent to clarify the hazard of millet drought disaster and provide reference for the formulation of millet disaster prevention and reduction measures. In this paper, combined with the water demand of millet in each growth period, Standardized Precipitation Requirement Index (SPRI) was selected to identify and quantify the drought disaster of millet. Considering the impact of different degrees of drought in different growth periods, a hazard assessment model is constructed to evaluate the hazard of millet drought disaster in Northern China under the background of climate change. The results show that: (1) SPRI can well characterize the drought of millet in Northern China. (2) In the context of climate change, millet drought in Northern China shows a trend of increasing intensity and decreasing frequency, and it is possible that millet drought will be even more severe in the future. (3) Combined with the hazard assessment model, millet drought in Northern China will still be dominated by middle hazard in the future, but the areas with high hazard will gradually increase, mainly distributed in northeast China, central and western Inner Mongolia and northern Gansu. The research results can be of great practical significance for the adjustment of agricultural production structure in the future, especially for the sustainable development of agriculture and the formulation of measures to prevent and resist agricultural disasters. [Display omitted] • We apply SPRI to identify millet drought by considering actual water demand. • Future changes of millet drought evaluated by CMIP6-GCM models. • Hazard assessment model was presented combined with disaster loss coefficient. • The areas with high hazard of millet drought will gradually increase in future. [ABSTRACT FROM AUTHOR]

Understanding coastal flooding processes in response to centennial-scale sea-level rise is essential in preparing for the challenge of present-day global warming. Mid-Holocene sea-level rise induced widespread coastal flooding along the East China coast and precipitated the collapse of the Neolithic Liangzhu Culture, the earliest known prehistoric state in East Asia. This paper presents multi-proxy analyses of sedimentology, grain size, total organic carbon (TOC), and alkaline-earth metals extracted by acetic acid (HAc) of a dated sediment core, ZK07, collected from Liangzhu City, with the aim of revealing the detailed progression of coastal flooding phases and the response of prehistoric people at the end of the associated Liangzhu Culture. A three-step succession of coastal flooding processes between ca. 4.6–4.3 cal kyr BP, brought about by relative sea-level rise, is evident in core ZK07. Initially, an increase in the local water level in response to the first phase of sea-level rise is indicated by a gradual increase in TOC at ca. 4630 cal yr BP. Subsequently, at ca. 4520 cal yr BP, a second phase of increased local water-level, consistent with further sea-level rise and salinity intrusion, is suggested by higher Sr concentrations accompanied by a sharp increase in TOC. Thirdly, at ca. 4480–4315 cal yr BP, low TOC content, high - but strongly fluctuating - Sr and Ba concentrations and coarser sediment grain size are all indicative of coastal inundation caused by both storm surges and river flooding associated with typhoon events that correspond with a concurrent phase of accelerated sea-level rise. Considering the evidence of cultural deposits preserved at Liangzhu City, it appears that the Liangzhu people were forced to respond rapidly to the inundation by abandoning the city at ca. 4480 cal yr BP. We suggest that relative sea-level rise and coastal flooding at the terminal stage of the Liangzhu Culture was the regional response to global climate warming and eustatic sea-level rise at that time. Given evidence that a contemporaneous cultural transition took place in the lower Yellow River basin, we further propose that global climate change around 4.5 cal kyr BP had a widespread impact on Neolithic cultural evolution in East China. Furthermore, the rise in local water levels and associated salinity intrusions may be considered as an early warning signal in monitoring future coastal flooding risk. • A three-step succession of coastal flooding was recognized at the end of Liangzhu Culture. • Rise in local water level and salinity intrusion could be early warning of coastal flooding. • Global climate warming and eustatic sea-level rise at ca. 4.5 ka was the major mechanism. • Contrasting Neolithic cultural evolution occurred in the lower reaches of two large rivers in East China. [ABSTRACT FROM AUTHOR]

Simple Summary: The Colorado potato beetle is a pest of Solanaceae in China, more than 30 species of Solanaceae as host plants of the Colorado potato beetle, and this beetle can cause yield losses to potato farms. Temperature is one of the main factors that affect the growth and survival of insects. In recent years, due to global climate change, sudden drops in short-term temperatures are also frequent, which will affect insects. This paper studies the influence of short-term low temperature on the Colorado potato beetle. In laboratory experiments, we evaluated the effect of short-term low temperature on the Colorado potato beetle eggs, and the emerged date, the number of Colorado potato beetles, were analyzed in combination with the low temperature conditions. Our results show that low temperature had adverse effects on the development of Colorado potato beetle eggs and the emerged of adults Colorado potato beetles, and the longer the low temperature treatment time, the greater the impact. The Colorado potato beetle is a serious pest of Solanaceae in China. In early summer, cold spells in later spring may occur for brief periods in the field environmental conditions, and temperatures often deviate far below the normal temperature for short periods, such as sudden short-term low temperature, may affect the development of Colorado potato beetle eggs. This paper studies the effects of low temperature stress at 8 °C for 0 d, 1 d, 3 d, 5 d, 7 d, and 10 d on the development of Colorado potato beetle eggs. Our results show that egg survival is significantly affected by short-term low temperature exposure. The percentage of eggs hatched is significantly affected by different treatment times (p = 0.000)—the percentage of eggs hatched decreases with increased treatment time, and Colorado potato beetles will extend the wintering time of their soil to resist the effects of lower temperatures. Thus, exposure of Colorado potato beetles to a short-term low temperature affects their emergence and population growth; this study could provide information for the occurrence, monitoring, and early warning of Colorado potato beetle during short-term temperature. [ABSTRACT FROM AUTHOR]

The paper investigates how climate changes and socioeconomic transformations affected grassland productivity from 2000 to 2017 in counties in Inner Mongolia of China. The grassland productivity and climatic change variables included 162 readings (9 periods in the growing season × 18 years), while ten socioeconomic variables contained 18 yearly readings. The mismatch between the environmental observations and socioeconomic data compounds quantitative analysis of causal relations between them. We applied several time-series processing methods to generate five datasets. We fit them with conventional, dependent-lagged, and dynamic-lagged panel regression models to investigate which combinations augment causal relationships between grassland productivity, climate, and socioeconomic changes. The results confirmed that the conventional model with the original data failed to reveal causal relationships between these factors. The panel regression models with the original data tended to intensify the causal effects of climate factors on grassland productivity. The models with the transformed datasets disclosed more socioeconomic variables showing causal relationships with grassland productivity. The dependent-lagged model with the empirical mode decomposition transformed data produced the highest R-squared value and lowest prediction error. GDP, state fixed asset investment, highway construction, grain plantation, and livestock density were primary factors affecting grassland productivity. In brief, the integration of time-series data mining and time-lagged panel analysis effectively unveiled the causes of grassland deterioration under climate and socioeconomic changes. [Display omitted] • Augment causality hidden in env-socio-economic systems with data assimilation. • Assimilate temporal environmental and socioeconomic data into compatible time-series. • Experiment with four groups of computational data mining methods on data assimilation. • Compare combinations of data assimilation methods and lagged panel regression models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Past LULC changes can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). • Carbon storage presented a high-low-high distribution pattern from north to south. • Areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. • Rapid LULC dynamics have reduced the carbon sequestration capacity of the ecosystem. • The implementation of ecological conservation could increase the carbon fixation in ecosystems. Land use/land cover (LULC) change has greatly altered ecosystem carbon storage capacity and can eventually profoundly impact global climate change. Characterizing the LULC change and its impact on ecosystem carbon storage in coastal areas is greatly significant to comprehensively understanding the influences of human activities on ecosystems. Based on LULC data, this paper combined CA-Markov and InVEST models to evaluate the past, present, and future LULC change and its impact on ecosystem carbon storage in coastal areas of China. The results showed that past LULC change in coastal areas can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). Changes in LULC types have led to a downward trend in ecosystem carbon storage, with a cumulative loss of 0.39 Pg and 0.15 Pg during the two stages, respectively. Spatially, carbon storage presented a high-low-high spatial distribution pattern from north to south. Temporally, areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. Compared with the natural change scenario, the areas with LULC types conversion under the ecological conservation scenario in 2050 will be lower due to the limitation of ecological protection, and it caused carbon storage reduction will slow down. Rapid LULC dynamics, that a large area of farmland, unused land and, water have been converted into construction land, reduced the carbon sequestration capacity of the ecosystem. This study will provide reliable references and precise data support for coastal management and decision-making. [ABSTRACT FROM AUTHOR]

The southeastern coastal region of China has coastal sand dunes, which are usually called paleo-sand dunes or "Old Red Sandstone". The ages and geological implications of these coastal dunes have been studied for tens of years but are still controversial. In this paper, we used optically stimulated luminescence (OSL) dating to establish the chronology of the paleo-aeolian reddish sand dunes from two representative sites in the coastal region of SE China. Our results indicate that the sand dunes were mainly accumulated in three periods, including 9–6 ka (broadly corresponding to marine isotope stage (MIS) 1), 50–26 ka (MIS 3), and 110–74 ka (MIS 5). Based on the comparison between the regional aeolian dune records and the global sea-level fluctuations, we concluded that the reddish sand dunes were associated with the aeolian processes during interglacials and interstadials when sea-level were relatively higher compared with glacial maxima. We proposed a conceptual model to interpret the formation of the coastal sand dunes. We suggest that coastal dunes that formed during the glacial maxima could not be preserved in highstands above the present sea-level due to the lower altitude of sand dunes and the erosion by water waves during the subsequent marine transgression. Therefore, only aeolian sand dunes accumulated in higher altitudes during sea-level rise were preserved as in the coastal region of SE China. • Luminescence dating of coastal dunes in SE China • Dune sands were mainly accumulated in MIS 1, MIS 3, and MIS 5. • Interplay between exposure of continental shelf and aeolian processes [ABSTRACT FROM AUTHOR]

• The relationship between the groundwater depth and grassland ecology was analysed; • Groundwater depth affected the composition and diversity of vegetation species; • A reasonable groundwater depth can buffer the impact of climate change on the vegetation to maintain grassland ecological stability; • The control of grassland degradation should include the potential exploitation of groundwater. Grassland degradation in the semiarid area of China is often attributed to overgrazing and expansion of irrigated agriculture without the consideration of groundwater. However, falling groundwater levels in the region have caused many problems for grassland ecology. In this paper,the typical sandy grassland- the Tongliao part of Horqin grassland was selected as the study area to study the spatial distribution of normalized difference vegetation index (NDVI) and the relationship between the NDVI and groundwater depth (GD) of each grassland pixel was studied. The temporal variation of the NDVI and its correlations with precipitation were investigated. The relationship between GD and vegetation species diversity in grassland was analyzed based on the vegetation survey. The results of the relation between GD and NDVI and vegetation species showed that GD can buffer the impact of increase in drought events on the vegetation because GD affected the composition and diversity of vegetation species. As the GD increases, the mean NDVI showed a trend of increasing first and then decreasing, and basically remained unchanged when the GD was greater than 3.5 m. The species diversity of grassland decreased with increasing GD and was not related to GD when GD was greater than 3.5 ∼ 4 m. Falling groundwater levels will cause great changes in the structure of grassland; specifically, azonal vegetation will gradually die and 3.5 m may be the critical GD needed to maintain the incomplete extinction of grassland azonal vegetation in the aeolian sandy soil. Correlation analysis proved that the correlation between NDVI and precipitation was significantly enhanced when GD increased sharply from 3 m to 6 m after 1999. This research indicates that the control of grassland degradation should pay attention to controlling the groundwater exploitation to recover a reasonable groundwater level, which was found to be necessary in the support of diverse and climate resilient of vegetation. [ABSTRACT FROM AUTHOR]

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. • Lake water volume estimation, it can roughly be divided into with topographic data and without topographic data. • Estimation of lake water volume can be divided into remote sensing-based and non-remote sensing research. • The application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. [ABSTRACT FROM AUTHOR]

Widespread concern about ecological degradation has prompted development of concepts and exploration of methods to quantify ecological quality with the aim of measuring ecosystem changes to contribute to future policy-making. This paper proposes a conceptual framework for ecological quality measurement based on current ecosystem functions and biodiverse habitat, compared with pixel-scale historical baselines. The framework was applied to evaluate the changes and driving factors of ecological quality for Chinese terrestrial ecosystems through remote sensing-based and ecosystem process modeled data at 1 km spatial resolution from 2000 to 2018. The results demonstrated the ecological quality index (EQI) had a very different spatial pattern based upon vegetation distribution. An upward trend in EQI was found over most areas, and variability of 46.95% in EQI can be explained well by change in climate, with an additional 10.64% explained by changing human activities, quantified by population density. This study demonstrated a practical and objective approach for quantifying and assessing ecological quality, which has application potential in ecosystem assessments on scales from local to region and nation, yet would provide a new scientific concept and paradigm for macro ecosystems management and decision-making by governments. • Proposes an ecosystem functions based ecological quality. • Comparing with historical baselines on the pixel scale. • Appling to measure ecological quality of Chinese ecosystems in recent 20 years. • The 46.95% variability due to climate change, while 10.64% by human activity. [ABSTRACT FROM AUTHOR]

The Changbaishan volcano, located in northeast China, produced a large amount of charcoal during the "Millennium Eruption" (c. 946 CE). In this paper, we report a high-resolution date for the eruption using multiple methods applied to the fossil charcoal and living trees, including wood anatomy, radiocarbon dating and tree-ring cross-dating. In addition, we develop a new floating annual-resolution tree-ring chronology spanning nearly 200 years that provides information about paleoclimate conditions. In our study, we identified 60 samples of charcoal as Larix olgensis based on anatomical characteristics and geographical location. Using these materials, we dated the eruption to the winter of 946 CE based on a combination of radiocarbon dating, traditional dendrochronological cross-dating and cambial cell growth status. This allowed us to develop an L. olgensis tree-ring width chronology covering 764–946 CE and 1715–2016 CE, with significant sensitivities to April–September temperature (p < 0.05). The tree-ring data have great potential to indicate extreme climate events; for example, we identify an extremely cold year in 903 CE. Such marker years can improve the reliability and accuracy of tree-ring data. Our study provides direct and precise tree-ring evidence for volcanic eruptions and anomalous climate years in the Middle Ages. [Display omitted] • Cambial activity enables us to date the Millennium Eruption to winter 946 CE. • The first chronology reaching the Middle Ages so far developed in northeastern China. • The chronology was assembled from volcanic charcoal and living larch. • This chronology is sensitive to temperature. [ABSTRACT FROM AUTHOR]

The goal of carbon neutrality provides a new opportunity for the development of renewable energy, especially for wind power. In this paper, 11 regional climate models (RCMs) including CORDEX-EA and PRECIS at two different resolutions are used to evaluate the performance in simulating the spatio-temporal characteristics for wind speed and energy potential from 1981 to 2005. The results show that most models can reproduce the spatio-temporal patterns, and the simulation of the eastern region is better than that of the western region. Besides, most of the higher-resolution models had better simulation performance for spatial-temporal patterns and inter-annual variation. Then, the weighted multi-model ensemble is used to project the changes of the wind speed and the wind power density over China's mainland during the mid-21st century under the RCP8.5 scenario. In future, a decrease in wind speed is projected by most RCMs over China, although some regions, such as the southern parts of China, are projected to have more wind energy potential. The percentage variation of annual mean wind speed will remain in the range of ±4%. The wind power density will decrease in the north and the largest decrease will be found in the northwest. However, the annual mean wind power density in the southeast China will have an increase of 2.21% in the middle of this century. The inter-annual variation of the wind power density in most regions will increase by more than 20%. However, intra-annual variation in the wind power density is likely to decrease in most regions of China, ranging from about −20% to −50%. • A weighted multi-model ensemble was used to project the changes of wind power density over China. • The changes of annual mean wind power density vary in different sub-regions of China, ranging from −3.21% to 2.21%. • The inter-annual variation of the WPD in most regions will increase by more than 20%. [ABSTRACT FROM AUTHOR]

• A first comprehensive and systematic review on the research of extreme precipitation in China. • Variation and regional characteristics of extreme precipitation under non-stationary conditions due to climate change and human activities. • Supports and basis for engineering application and further research on extreme precipitation and flood in China. Recent years have witnessed global massive property losses and casualties caused by extreme precipitation and its subsequent natural disasters, including floods and landslides. China is one of the countries deeply affected by these casualties. If the statistical characteristics and laws of extreme precipitation could be clearly grasped, then the negative impacts triggered by it may be minimized. China is a vast country and diverse in climate and terrain, hence different regions may be suitable for different analyses and research methods. Therefore, it is necessary to clarify the research progress, methods and current status of extreme precipitation across the country. This paper attempts to provide a comprehensive review of techniques and methods used in extreme precipitation research and engineering practice and their applications. The literature is reviewed focusing on seven aspects: (1) annual maxima method (AM), (2) peaks over threshold method (POT), (3) probable maximum precipitation (PMP), (4) non-stationary analysis of precipitation extremes, (5) intensity-duration-frequency curves (IDF), (6) uncertainty in extreme precipitation frequency analysis, and (7) spatial variability of extreme precipitation. Research on extreme precipitation in China is generally based or centered on the above seven aspects. The current study aims to provide ideas for further research on extreme precipitation frequency analysis and its response to climate change and human activities. [Display omitted] [ABSTRACT FROM AUTHOR]

• A hydrological modeling approach was proposed to distinguish the relative contribution of climate changes and human activities on Daihai Lake's recession. • In the absence of natural runoff and human-induced water withdrawal observations, the natural state's lake water storage changes were reconstructed. • Without considering the high water years, the anthropogenic factor took the responsibility for the lake shrinkage about 58%, while the climatic factor took roughly about 42% in period 1974–2018. • This investigation serves as a useful example of applying a distributed model to the assessment of lake hydrology, especially for the lake catchments with limited observations. In recent decades, water levels in many closed inland lakes over north-western China experienced severe declines, among which the Daihai Lake in Inner Mongolia, China was particularly significant. Remotely sensed investigations indicated that the Daihai Lake had shrunk approximately 64% in an area with the dramatic decline of water level approximately 9 m from the 1980 s to 2010 s, which has caused serious concern on the sustainable development of the surrounding region. Consequently, several previous studies have concentrated on the possible causes of lake shrinkage. However, predicting climate variability and anthropogenic activities' relative contributions to lake water decline is challenging due to the lack of direct water consumption upstream and watershed-scale natural runoff observations. In this paper, a hydrological modeling approach was presented to quantitatively evaluate and separate the relative contributions of climate variations and intensifying anthropogenic activities. The simulation accuracy was evaluated through comparisons with observed data and cross-validation with previous studies. Based on a baseline period, the natural streamflow draining into the lake was reconstructed using the model. The results revealed that the water loss of the Daihai Lake was caused predominately by human activities rather than climate variability. Specifically, for wet conditions, the climate factors posed a negative effect on the water level decline of the lake and delayed the shrinking process of the lake area. The anthropogenic factors took a dominant role (roughly 58%) of lake shrinkage at the annual average scale for normal and dry conditions, while the climate factors accounted for approximately 42%. Hence, the rational policy for water resource management, ecological restoration, and dam and reservoir constructions/operations should be the essential precautions for sustainable development of the Daihai Lake and its surroundings. Additionally, the hydrological modeling approach adopted in this investigation serves as a useful example of the quantitative assessment of climate variations and human activities, especially for the ungauged catchments. [ABSTRACT FROM AUTHOR]

• The mean groundwater table depth in China dropped by approximately 0.2 m (P < 0.01) during 1979–2018. • The Noah-MP land model forced with reanalysis climate data can reasonably capture terrestrial water and radiation processes across China. • Incorporating the groundwater lateral flow process enhances the seasonality of modeled terrestrial water and radiation processes on a regional scale. Faced with intensified climate change and ever-increasing water demand, the groundwater table depth is vital to sustaining terrestrial environments in a country such as China; however, on a regional scale, insufficient research has been conducted on its variability thus far. Using a land model forced with reanalysis climate data, this paper investigates groundwater table depth changes across China for the 1979–2018 period. The results show a significant overall reduction in the groundwater table depth in China during the past 40 years without explicit consideration of direct human influence. There is an approximately 0.2 m decrease on average, but it is approximately 0.5 m in southern China and 0.8 m to the north of 35°N despite a 1.2 m rise in part of this region due to an increasingly wet climate and a topographic water convergence. The findings provide a first-order pattern of historical groundwater table responses to climate change, highlighting inherent links among subsurface-surface-atmosphere water cycles and worsened terrestrial water availability in China. A model evaluation compared with in situ observations has demonstrated the model's ability to realistically portray terrestrial water and energy balances on regional scales, as well as the enhancement of their seasonality with incorporated lateral groundwater flow processes. This ability gives us reasonable confidence in the simulated trends and spatial variability. Nonetheless, the mean groundwater table still shows large biases relative to observations, and the problems of human influence, two-way interactions between groundwater and surface water, and local topographical complexity have yet to be properly addressed in the present study and deserve further research. [ABSTRACT FROM AUTHOR]

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam's (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

The threat of global climate change has caused the international community to pay close attention to atmospheric levels of greenhouse gases such as carbon dioxide. Transportation sector carbon dioxide emissions efficiency (TSCDEE) is a key indicator used to prioritize sustainable development in the transportation sector. In this paper, the epsilon-based measure data envelopment analysis model with undesirable outputs is applied to estimate TSCDEE for 30 provinces in China from 2010 to 2016. We also analyze influencing factors using the spatial Durbin model. Research shows that the overall TSCDEE of the Chinese provinces studied was 0.618, indicating that most regions are still in need of improvements. The provinces with the highest TSCDEE are located in developed coastal regions of China. This study shows that factors such as transportation structure, traffic infrastructure level, and technological progress have prominent positive effects on TSCDEE, while both urbanization level and urban population density exert significantly negative effects on TSCDEE. The findings should have a far-reaching impact on the sustainable development of global transportation. [Display omitted] • Providing more accurate method in estimating CO 2 emissions of the transport sector. • Focusing on the transportation sector carbon dioxide emissions efficiency (TSCDEE). • Technological progress is the key to improve TSCDEE among different factors in China. • Higher mode share of water and rail transport contributes to higher TSCDEE in China. • Urbanization presents significantly negative effect on TSCDEE in China. [ABSTRACT FROM AUTHOR]

Disentangling fire and its controls over thousands of years ago is a major challenge in the study of paleofires. In this paper, we synthesize sedimentary charcoal and black carbon from the coastal plain of Laizhou Bay, China to improve our ability to reconstruct fire history in the past 5000 years, and to assess the controls of fire using principal component analysis and multiple regression approach. The results show that there were three distinct fire episodes at the intervals of 5300–5100 yr BP., 1190–1060 yr BP., and 300–0 yr BP., based on the Changyi (CY) profile. A large-scale fire episode was synchronous with a rapid climate variability that occurred 5300 yr BP., which had frequent drought and cold epoch. High fluxes of black carbon and charcoal were closely related to mass migration and the use of fire for land reclamation from 1190 to 1060 yr BP. Subsequently, anthropogenic biomass burning for cereal cultivation has reached a higher level over the past 300 years. However, between 4600 and 4000 yr BP. the shifts in the frequency of high-magnitude floods and climate aridity consequently resulted in the decline of fire-episode frequency and the abandonment of the late Neolithic settlements in the study region. Therefore, climate is still a prerequisite factor for fire occurrence on the southern coast of Laizhou Bay in the past 5000 years. A rapid climate variability was not only responsible for various fire patterns, but also could affect human settlements and the mode of production during middle-late Holocene. In the past 1000 years, human land use has been a more important control of fire. However, temperature has become one of the evidently identified controls of fire across the study area in recent decades. To synthesize the methods of Principal Component Analysis and Multiple Regression Analysis with multi-proxy evidence is necessary for us to better understand fire and its controls on coastal plain of Laizhou Bay at the region. • Charcoal and BC have recorded fire mid-Holocene at the Laizhou Bay of China. • Climate was still a prerequisite control of fire at the Laizhou Bay mid-Holocene. • In the past 1000 years, human land use has been an important control of fire. • Temperature has become one of the identified controls of fire across the study area. • Principal component analysis will contribute to disentangling fire and its controls. [ABSTRACT FROM AUTHOR]

• Proposes an analytic framework to identify when a adaptation operating rule is needed. • Introduces the probability change-point analysis technique into failure warning time. • Evaluates the proposed framework based on a real-world case study in China. This paper presents a methodology for the identification of the time tipping point where historical operating rules of a reservoir system should be replaced by new alternatives due to climate change. The time tipping point is a time indicator of the failure probability change point of the historical operating rules for the reservoir system under future climate change, called the failure warning time. For this study, the primary purpose of the reservoir system is hydropower generation. We first estimate the probability density function of the annual benefit of hydropower generation. Then, based on the estimated probability density function and the given risk tolerance level of the reservoir system, we determine the risk-based warning threshold, and further identify the failure warning time of the historical operating rules via the probability change-point analysis technique. We apply the proposed methodology to the Xiluodu-Xiangjiaba-Three Gorges cascade reservoir system on the Yangtze River in China. The results indicate that the failure warning time for the cascade reservoir system will occur in at least another 10 years in the future under climate change. We also find that the failure response in the cascade reservoir system is determined by both the reservoir that has the first failure occurrence and its storage capacity. The developed methodology can be used to determine the time tipping point to launch adaptation strategies for the river basin management, and further can help policymakers cope with climate change. [ABSTRACT FROM AUTHOR]

• Dynamic analysis of mixed forest species. • Potential suitable range of simulated species. • Dominant factors of species distribution. • P. tabuliformis and O. davidiana are mixed tree species. • R's ENMeval language package to optimize Maxent model. The outstanding self-regulation ability of mixed forest plays an important role in maintaining ecosystem stability. However, in recent years, climate change has caused geographical changes of species. This paper studies the potential geographical location of mixed species for the first time, so as to formulate the planting plan of mixed species in suitable areas. Therefore, we use the species distribution model based on Maxent to predict the potential suitable area of Chinese Pinus tabuliformis and Ostryopsis davidiana mixed forest under the climate change scenario, and provide a scientific basis for expanding the construction of P. tabuliformis and O. davidiana mixed forest in the future under three greenhouse gas emission scenarios (RCP2.6, RCP4.5 and RCP8.5) of current and future climate (2041–2060 and 2081–2100). The simulation accuracy of Maxent model is verified by the area under receiver operating characteristic curve (AUC). The results show that the distribution range of P. tabuliformis is much larger than that of O. davidiana in China. Under the current climate conditions, the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana is 64.40 × 104 km2, accounting for 6.71% of China's land area, mainly distributed in most areas of North China, Northeast China (Western Liaoning), Northwest China (Shaanxi, Ningxia, the Southernmost part of Inner Mongolia and Eastern Gansu) and Central China (Northern Hubei). Under the future high concentration emission scenario (RCP8.5), the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana will be reduced. Under the scenario of medium concentration climate emission (RCP 4.5), the centroids of P. tabuliformis and O. davidiana tend to migrate from west to north. The annual mean temperature (bio1) has a significant effect on the geographical distribution of P. tabuliformis and O. davidiana. In addition, the mean temperature of the driest quarter (bio9) and annual precipitation (bio12) also have a significant impact on the geographical distribution of P. tabuliformis. Similarly, there are obvious factors on the geographical distribution of O. davidiana , as well as isothermality (bio3) and precipitation of the wettest quarter (bio16), indicating that the important climate factors affecting the geographical distribution of P. tabuliformis and O. davidiana are not completely consistent. We believe that mixed forests play a positive role in coping with climate change. The research results can help decision-makers to formulate adaptation countermeasures based on climate change. [ABSTRACT FROM AUTHOR]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]

Universities, the important locations for scientific research and education, have the responsibility to lead ecological civilization and low carbon transition. Ecological footprint evaluation (EFE) is usually used to measure sustainability of campuses. Although it can provide guidance and reference for overall campus planning, it lacks effective significance for individual behavior, especially when the reduction of carbon emissions is the aim. On the other hand a possible solution can be represented by machine learning. It can identify the key factors that will influence individual's overall carbon emissions caused by students' daily behavior, it can be used to find effective ways to reduce individual carbon emissions. This paper applied EFE and machine learning to comprehensively evaluate campus sustainability and students' carbon emissions. Huazhong University of Science and Technology (HUST), a "University in the Forest", was used as a study case in China. Even if HUST is endowned with a forest coverage of 72%, here we showed that its Ecological Footprint Index was −12.52, indicating strong unsustainability. This is mainly due to the high energy and food consumption, caused by the large population living in the campus and the lacking of energy saving measures. The per capita ecological footprint was relatively high, compared with other universities in the world, which meant more efforts needed to be done on ecological sustainability. Low carbon emission is a key feature for a sustainable campus. Based on the questionnaire survey delivered to 486 students who live in the campus, their daily active data were collected in terms of students' personal clothing, food, housing, consumption and transportation. And their associated carbon emissions were calculated based on emission intensities of Chinese population. Based on 486 detailed datasets, machine learning was then used to identify the key daily behavior to influence students' total carbon emission. Results showed that making behavior changes in air conditioning, food and electric bicycle were the most effective ways to reduce carbon emissions. Finally, while effective suggestions were proposed based on qualitative and quantitative evaluations, it is concluded that it is imperative for universities in China to formulate effective low-carbon policies, to achieve sustainable development and to confront global climate change. • A review of main initiatives of sustainable campus construction worldwide. • An evaluation combining campus ecological footprint and individual carbon footprint. • The ecological footprint of "China Forest University" reflects unsustainable. • Machine learning identifies internal driving force of campus carbon emissions. • Targeted guidelines on campus low-carbon construction are provided. [ABSTRACT FROM AUTHOR]

The intensification of heat stress in a changing climate poses great threats to both human health and labor productivity. It is of great practical importance to assess the impacts of climate-induced heat stress on labor productivity and to develop effective adaptation strategies. In this paper, an integrated optimization-based productivity restoration modeling framework is proposed for the first time to develop the optimal policies for adaptation to climate change. To address underlying uncertainties associated with climate and labor management systems, we take into account ensemble projections from five global climate models (GCMs) under two Representative Concentration Pathways (RCP2.6 and RCP8.5) and inexact system costs. The system costs, including direct and indirect costs such as management costs, energy costs, and labor costs, are presented as interval numbers due to inherent uncertainty caused by population growth, technology development, and other social-economic factors. Uncertain information can be effectively communicated into the optimization processes in this study to generate optimal and reliable decision alternatives. We find that the increased Wet-Bulb Globe Temperature (WBGT) will lead to a large reduction in labor capacities over China except for the Tibetan Plateau under both RCPs by the end of the 21st century. The less developed regions tend to achieve the minimum system cost by having labor productivity recovered through working overtime due to the relatively low cost of overtime. This could result in more heat-related work injuries in the less developed regions. Since the less developed regions are not heat-prone areas in China, the changing climate would be a more dangerous threat and cause more damages to these regions where the residents are less acclimatized to heat stress. Moreover, we obtain a range of minimum system costs from 1.86 to 8.97 billion dollars under RCP2.6 and from 9.42 to 32.31 billion dollars under RCP8.5 (about 0.2% of China's GDP in 2019, 0.01% of China's GDP projected in 2100 under a sustainable socio-economic development scenario) for the restoration of labor productivity in a warming climate. We argue that urgent actions are needed to mitigate global warming impacts on labor productivity. • An integrated optimization modeling framework is developed to achieve optimal labor productivity restoration in a warming climate. • Various uncertainties are addressed through ensemble climate projections and interval programming models. • Intensification of heat stress leads to a large decrease in labor capacity over China except for the Tibetan Plateau. • More losses in working hours are projected for moderate labor activities compared to light and heavy labor activities. • Less developed regions tend to have more working hours recovered by working overtime than air conditioning. [ABSTRACT FROM AUTHOR]

• 170 rainfall-related excavation failure cases in China were collected for analyses. • 10 conceptual models were developed for illustration of the excavation failures. • Soil conditions and technical factors involved in the failures were summarized. Over the last 30 years, intense rainfall events due to abnormal climate change have brought about numerous excavation failures in the urban areas of China. These heavy rainfall-related engineering failures, characterized by failure or collapse of retaining structures and/or retained slopes, have caused large-scale damages to urban environment as well as injuries and casualties. Thus, a summary of such failures along with corresponding statistical patterns and contributing factors is essential, which can help practitioners further understand the risk of excavation failures associated with heavy rainfall and then could develop or adopt appropriate measures for prevention of future failures. Based on these considerations, this paper reviewed 170 excavation failure cases occurring during 1994–2018 in China, using a method of descriptive statistics. The review mainly focused on their statistical failure patterns (temporal distributions of failures, types of failures and types of failed soil strata, etc.) and contributory factors (e.g., heavy rainfall influences and technical factors). It was disclosed that the failures occurred in those deep excavations in sandy soils during summer more frequently. In general, the failures can be categorized into six basic types, which are mainly governed by 11 kinds of adverse influences of heavy rainfall (e.g., seepage erosion under high hydraulic gradient, intense runoff scouring and water gushing impact from broken storm sewers nearby, etc.) and 16 technical factors (e.g., ignorance or improper protection of adjacent preexisting drainage structures, deficiencies in drainage or dewatering system, and poor construction quality of temporary retaining structures, etc.). The findings and lessons learned from this review are practically useful for designers and contractors to reduce the incidence of future excavation failures in the context of global climate change. [ABSTRACT FROM AUTHOR]

In order to mitigate global climate change and air pollution, the Chinese government has assigned high priority to expanding low-carbon power generation in China. Recent studies have shown that wind power is one of the most promising renewable energy option in China. Although many studies have estimated the generation potential of onshore wind power, their results vary widely from 1783 TWh to 39,000 TWh. Therefore, we examine the different assumptions in these papers and identify three main factors influencing the results. The three influencing factors are: weather data set, land utilisation factor, and wind turbine configuration. For our model-based analysis, we define a reference scenario which is used to compare the results. Our analysis shows using a different weather data set increases the generation potential to roughly 35,000 TWh. This is 54% higher than the generation potential of the reference scenario. The land utilisation factor also has a large influence, ranging between −10% and −51%. The studies' assumptions and data should be subjected to careful scrutiny, as the calculated wind power potentials are widely used to develop decarbonisation strategies for the energy system. • Study results on wind power potentials in China vary from 1783 TWh to 39,000 TWh • Influencing factors: weather data set, land utilisation, and wind turbine configuration. • Model-based sensitivity analysis with nine scenario settings. • Chosen weather data set has the highest impact on the calculated results with a variation of 54%. [ABSTRACT FROM AUTHOR]

• Nonlinearity and interaction of drivers of runoff and nitrate were identified. • Agricultural expansion and climate change offset positive effect of forest restoration. • Landscape configuration determined surface runoff and nitrate load in wet season. • Cropland fragmentation is crucial to alleviate nitrate load. Climate variability and landscape modifications directly influence watershed hydrology and processes of nonpoint source pollution, while remedial action requires distinguishing their effects. However, nonlinearity and multiple causality limit our ability to diagnose causes. Therefore, this study developed an approach that integrates hydrological modeling, random forests, regression trees, and variation partitioning analysis, to identify the effects of climate and landscape pattern changes upon runoff and nitrate loading in two typical watersheds in the Three Gorges Reservoir area of China. The Soil and Water Assessment Tool (SWAT) was used to track the spatiotemporal dynamics of runoff and nitrate loading (2000–2015). The findings showed that drylands and orchards were the dominant sources of nitrate and baseflow was the key mode of nitrate transport. Water yield and baseflow were mainly influenced by precipitation change, while the surface runoff and nitrate load were affected primarily by landscape pattern changes, especially in the wet season. Although ecological restoration programs have improved forest cover and forest fragmentation, the effects of forest restoration on the reduction of surface runoff and nitrate at the watershed scale have been offset by increased precipitation and agricultural expansion. Nevertheless, the role of landscape configuration is so dramatic that it can override variation in nitrate losses driven by changes in land cover and precipitation. Effective control of nitrate loss under intensive ecological restoration can be achieved by using a mosaic of "sink" patches to divide larger areas of cropland into smaller patches, maintaining cropland fragmentation, and limiting the increase in edge density of cropland. This paper's proposed and implemented approach provides a new understanding of the interactions and nonlinear relationship between hydrological processes and environmental change, providing explicit ideas and useful insights for landscape planners and managers for improving eco-hydrological functions of watershed at the practical level. We emphasize that the impact of land use change cannot be assumed to be linear in restoration strategies, instead nonlinear impacts, clear details of landscape configuration, and seasonal climatic characteristics should be explicitly considered. [ABSTRACT FROM AUTHOR]

Coastal morphodynamics and environmental changes have been obviously altered by global warming, sea-level fluctuations, and human activities. Palynological analysis is one of the most important tools for providing information on vegetation, climate, and environmental change, which can be relatively sensitive indicators of human activity during the Holocene. However, Holocene coastal morphodynamics and palynological evidence from the Pearl River Delta and coastal areas has not been sufficiently studied. In this paper, we carry out analyses using detailed grain-size and palynological records of pollen, spores, freshwater algae, and marine dinoflagellate cysts from Borehole QZK13 in the Pearl River Estuary (PRE), southern China. The results show information relating coastal morphodynamics, vegetation evolution, climate changes, and anthropogenic activities during the Holocene based on radiocarbon chronology. In general, the PRE experienced marine transgressive processes; sea-level and the coastline tended to migrate landward between 10,700 and 4250 cal yr BP. Meanwhile, abundant arboreal pollen (mainly Castanopsis , Quercus -evergreen, Oleaceae, and Castanea) and small amounts of non-arboreal pollen (mainly Poaceae, Cyperaceae, and Artemisia) were observed in Borehole QZK13, which suggests that subtropical evergreen broadleaved forests were distributed throughout the PRE and adjacent areas, and relatively warm and moist climatic conditions were present during the early-middle Holocene. After that, there were relatively cool and wet climatic conditions, and marine regressive processes occurred in the PRE during the Late Holocene (ca. 4250–960 cal yr BP) indicated by an abrupt increase in aquatic herbs and Dicranopteris. Moreover, we hypothesize that the Neolithic "cultural fault" in the PRE is likely related to frequent storm surges induced by extreme typhoon events that occurred ca. 3000–2700 yr BP. • Grain size, pollen, spores, freshwater algae and dinoflagellate cysts from the Pearl River Estuary were investigated. • Three major phases shown by palynological results were corresponding to the changes in vegetation and climate. • We hypothesized that the Neolithic "cultural fault" is probably related to the storm surges induced by extreme typhoon events. • Natural vegetation cover has suffered large-scale destruction by ancient humans during the Late Holocene. [ABSTRACT FROM AUTHOR]

Linking sinuosity, a fairly recently developed metric, with high temperature extremes (HTEs) can be both useful and insightful to better understand the physical mechanisms behind HTEs. However, it is not clear whether there exists a relationship between the sinuosity changes and HTE changes in present and future climate conditions over southeastern China. In this paper, the anomalous characteristics of the atmospheric circulation are quantified by sinuosity. Three sinuosity metrics are used in this study: individual sinuosity (SIN), aggregate sinuosity (ASIN), and comprehensive sinuosity (CSIN). Furthermore, we examine the relationship between sinuosity changes and HTE changes in present and future climate conditions. ASIN is strongly correlated with surface air temperature (SAT). We find that the influence of individual sinuosity (SIN) at different latitudes on the SAT of southeastern China is different. The SIN of low (middle) latitude isohypses has significant positive (negative) correlations with the SAT of southeastern China. The SIN of high-latitude isohypses is rather limited and can therefore be ignored. The projected relationship between the sinuosity changes and HTE changes in the late 21st century suggests similar results. The change in SAT is related to the changes in climate variables over southeastern China in the future, and these changes increase with the increase in Z500 or V850 and the decrease in U500. Moreover, the frequencies of large (small) comprehensive sinuosity (CSIN) values at low (mid) latitudes will increase. At the end of the 21st century, Z500 isohypses at different latitudes will have an obvious poleward shift. Our results indicate that measuring the aggregate waviness of the midtropospheric flow (via sinuosity) can provide insight regarding HTEs, and the climate model output can be used to examine the future likelihood of increased HTE. [ABSTRACT FROM AUTHOR]

• We review the state of research on human-environment interaction in Holocene China. • We demonstrate the benefits of a multidisciplinary, regionally focused approach. • We conclude datasets must be local and specific, and integrate data on multiple scales. • China is large, well-documented, and critical for understanding social-natural systems. This paper reviews recent archaeological research on human-environment interaction in the Holocene, taking continental China as its geographic focus. As China is large, geographically diverse, and exceptionally archaeologically and historically well-documented, research here provides critical insight into the functioning of social-natural systems. Based on a broad review of the field as well as recent advances and discoveries, the authors reflect on research themes including climate change and adaptive systems theory, spatial and temporal scale, anthropogenic environmental change, risk management and resilience, and integration of subdisciplines. These converge on three overarching conclusions. First, datasets relevant to climate change and ancient human-environment interaction must be as local and specific as possible, as the timing of environmental change differs locally, and the human response is highly dependent on local social and technological conditions. Second, the field still needs more robust theoretical frameworks for analyzing complex social-natural systems, and especially for integrating data on multiple scales. Third, for this work to contribute meaningfully to contemporary climate change research, effective communication of research findings to the public and to scientists in other disciplines should be incorporated into publication plans. [ABSTRACT FROM AUTHOR]

• Identify ancient flood events, which may be the reason for decline of the culture. • Pollen and heavy metals can be used to reflect the strength of human activities. • Pollen and heavy metals revealed the process of culture from prosperity to decline. • This paper defined the chronology from prosperity to decline of Shijiahe culture. • Climate change has been revealed by pollen and heavy metals since 4800 cal. yr BP. The Shijiahe Culture (ca. 4800–4100 yr BP), which originated in the middle Yangtze Basin, was a milestone of prehistoric Chinese civilization. To reveal the interactions between climatic changes and human activities during this time interval, the geochronology and multiple proxies (pollen and heavy metals) of samples from a 220-cm-deep outer wall at the Sanfangwan Site (a typical site of the Shijiahe Culture) were analyzed. Radiocarbon dating indicates that the age range of the Sanfangwan Site is ca. 4800 to 4100 cal. yr BP. From ca. 4800 to 4600 cal. yr BP (the early Shijiahe Culture), pollen assemblages were dominated by Gramineae and an anthropogenic plant community (e.g. Ranunculaceae, Chenopodiaceae, Labiatae, and Cruciferae), indicating an expansion in rice agriculture during this interval. High metal concentrations in the same interval indicate a large flux of metals from smelting and farming activities. Between ca. 4600 and 4100 cal. yr BP (the middle and late Shijiahe Culture), decreases in Gramineae and anthropogenic pollen mirrored the recession of farming. Concurrent decreases in heavy metals may be attributable to a decline in the smelting industry. Three episodes of high pollen concentrations and visible increases in hygrophyte pollen, Pinus pollen, and fern spores at 4600–4550, 4450–4350, and 4200–4100 cal. yr BP probably indicate the occurrence of several flooding events during the middle and late Shijiahe Culture, resulting in the migration of local inhabitants. This study highlights the driving effect of flood events on the collapse of the Shijiahe Culture. [ABSTRACT FROM AUTHOR]

The diffusion of renewable energy sources (RES) is a fundamental objective of the worldwide policy actions for sustainable development, at the UN level with the sustainable development goals (SDG) recommendations, to ensure access to affordable, reliable, sustainable and modern energy for all (SDG 7). Also, primary attention to RES has been given at the EU level with the new Green Deal and the new objectives of the Next Generation EU after the Covid pandemic, and at the level of national Governments worldwide. So far, there has not been an analysis of the RES convergence process across countries worldwide, given that the issue of climate change is a global externality. Previous analyses have focused on specific regions, such as EU, OECD, provinces of China. This paper fills this gap, providing new evidence on the convergence process of RES for the 176 countries that account for more than 98% of the world population, from 1990 to 2018. A common panel data set has been used to take into account countries' specific effects. Several socio-economics and political variables are introduced to test conditional convergence such as openness to trade, developments in financial markets, income distribution, level of education. The results of this new contribution reveal that there is evidence of sigma-absolute and conditional beta-convergence process for several groups of countries. Moreover, the conditional convergence analysis shows that spatial spillover effects exert rich and complex impact on convergence speed. Finally, we provide policy recommendations, highlighting that the decarbonization target in 2050 needs additional mobilization of public and private resources to pursue a common, convergence path worldwide. • We analyze the renewable energy convergence process across countries worldwide. • We analyses the catching-up measuring the gap between benchmark and non-benchmark. • We use variables RES as percentage of electricity production and energy consumption. • We find that heterogeneity exists in the worldwide RES convergence process. • A possible line for future research could be to disaggregate renewable sources. [ABSTRACT FROM AUTHOR]

[Display omitted] • Grassland degradation is the main reason for the decline in carbon storage. • The carbon storage of farmland has increased significantly. • The risk of carbon storage reduction in the future is still high. The carbon storage of terrestrial ecosystems is closely related to global climate change. Therefore, assessing the impact of land-use changes on carbon storage is instructive to reduce global carbon emissions. Taking an arid region in northwest China as an example, this paper analyzed the land-use changes in arid region from 1980 to 2015. It used the CA-Markov model to predict the land-use pattern from 2020 to 2050, the carbon storage and sequestration module in Integrated Valuation of Ecosystem Services and Tradeoffs (Invest) mode to assess and predict ecosystem carbon storage over the past 35 years and in the next 30 years and discusses the impact of land-use changes on the carbon storage of terrestrial ecosystems. The results showed that: (1) The high-value areas of carbon storage in arid region were primarily concentrated in grassland, forests and farmland, and the low-value areas of carbon storage were mainly in desert areas. (2) The carbon storage in arid region showed a downward trend. From 1980 to 2015, the carbon reserves of terrestrial ecosystems in arid region decreased by 90.95 Tg, and the net loss of carbon reserves from 2020 to 2050 was 14.72 Tg. Grassland degradation was the main reason for the reduction of carbon storage in arid region. (3) The carbon storage of farmland had increased significantly, but the expansion of farmland dominated by high carbon density grassland, wetland and forest, had reduced the overall carbon storage of the arid region. [ABSTRACT FROM AUTHOR]

Agroforestry systems are widely promoted for their economic and environmental benefits. Food, energy, water and land resources in agroforestry systems are inextricably intertwined and expected to be severely impacted by climate change. Socioeconomic development and increasing populations have posed unique challenges for meeting the demand for food, energy, water and land, and the challenge will become more pressing under projected resource shortages and eco-environmental deterioration. Thus, a method of optimizing and sustainably managing the water-land-food-energy nexus in agroforestry systems under climate change must be developed. This paper develops an optimization model framework for the sustainable management of limited water-land-food-energy resources in agroforestry systems under climate change. The aims are to (1) quantify the interactions and feedbacks within water, land, food and energy subsystems; (2) provide trade-offs among water and energy utilization efficiency, economic benefits and environmental protection in agroforestry systems; and (3) generate optimal policy options among water and land resources for different crops and woodlands in different regions under different climate change patterns. The model framework is based on multiobjective fractional programming, and compromise programming is used to solve it. Climate change patterns are obtained from atmospheric circulation models and representative concentration pathways. The above aims are investigated through an actual nexus management problem in northeast China. Spatiotemporal meteorological and report-based databases, life cycle assessments, Pearson correlation analyses, data envelopment analyses and analytic hierarchy processes are integrated to realize practical application. The results show that climate variation will change the water and land allocation patterns and these changes will be more pronounced for major grain-producing areas. The optimized water allocation decreased (especially for rice, e.g., the optimal average value of the irrigation quota of rice was 4226 m3/ha, while the corresponding actual irrigation requirement of rice was [4200–7200] m3/ha) to improve the water use efficiency, and surface water allocation accounted for two-thirds. Maize had the largest planting area, although planting soybean generated the most greenhouse gases (greenhouse gas emissions from field activities for rice, maize, and soybean were 43.46%, 84.06% and 91.16%, respectively); However, these gases can be absorbed by forests. The model improved the harmonious degree of the resource-economy-environment system from 0.24 to 0.56 after optimization. Integrated models contribute to the sustainable management of water, food, energy and land resources and can consider the complex dynamics under climate change. It can be used as a general model and extended to other agroforestry systems that show inefficient agricultural production. [Display omitted] • Food, energy, water and land resources in agroforestry systems are inseparable and are impacted by climate change. • A cooperative optimization model is proposed to manage water-land-food-energy nexus (WLFEN) and cope with climate change. • Resources reallocation in WLFEN improve synergy of resource use efficiency, economic benefit and environmental impacts. • Inner linkage and synergy exist among resources in WLFEN in agroforestry systems and they are sensitive to climate change. • We put forward a quantitative way to assist managing agricultural resources sustainability in a change environment. [ABSTRACT FROM AUTHOR]

• China's water use efficiency showed an increasing trend from 2001 to 2017. • The water use efficiency of forest land is higher than that of low vegetation. • Human activities have a greater contribution to the increase in water use efficiency. • China has more areas with positive correlation between water use efficiency and meteorology. In the context of increasing global carbon emissions, and the relative shortage of water resources, research on the relationships between climate change, human activities and the carbon–water coupling response of China's ecosystems is crucial. Water use efficiency (WUE) is an important indicator reflecting the coupling of ecosystem carbon and water cycles. Based on trend analysis, correlation analysis and multiple regression residual analysis, this paper analyzes the spatiotemporal distributions, change trends, correlations with meteorological factors, changes in different vegetation coverage types, and relative contributions of the main driving factors of China's vegetation WUE from 2001 to 2017. The results show the following: (1) For the past 17 years, the multiyear average value of vegetation WUE in China is 1.08 g C m - 2 mm - 1 , the average annual growth rate is 0.003 g C m - 2 mm - 1 a - 1 . The area with increasing trend of WUE accounts for 59.09% of the total area. (2) The seasonal WUE is highest in autumn, followed by summer, spring and winter. (3) The areas in which vegetation WUE is positively correlated with temperature and precipitation account for approximately 50.21% and 66.16% of the total area, respectively. (4) In terms of the relative annual average value of the WUE, the different vegetation cover types, in descending order, are mixed forests > needleleaf forests > broadleaf forests > shrublands > grasslands > croplands > wetlands > barren lands. (5) Human activities and climate change contributed 66.75% and 33.25%, respectively, to the increase in vegetation WUE in China in the past 17 years. The research results have important scientific significance for clarifying the impacts of climate change and human activities on the carbon–water cycle of the terrestrial ecosystems of China and assessing regional differences in the potential of terrestrial ecosystems to increase carbon sinks. [ABSTRACT FROM AUTHOR]

Green bonds have increasingly been utilized around the world as a source of financing for renewable energy development, designed with compliance requirements and measurable economic returns to investors, while mitigating climate change. However, the efficacy of green bond arranged in the emerging economies for financing renewable energy assets and how the underlying risks are managed have remained to be explored. The paper aims to examine the evolving green financial system sponsored by both public and private institutions in managing such risks within China's emerging economy. A case study of green financing for a bundle of wind power assets led by a state-owned enterprise (SOE) reveals an alternative approach by structuring public–private collaboration while stipulating market-based financial incentives to institutional stakeholders under a political economy. This institutional consortium is composed of a state development bank, a commercial bank, credit rating agencies, institutional and private investors, regional power purchasers, and carbon trading entities. Financial stakeholders' risk in such emerging sustainable investment is moderated by these participating institutions and structured "upsides" from carbon trading aligned with the framework of green finance and standards for green bond development. The results reveal the potentials of scaling up the development of renewable energy by adequately managing and sharing key risks, while allocating substantial funding into renewable energy projects under such a green financial system that is to be complementary with a scalable post COVID-19 economic recovery. [ABSTRACT FROM AUTHOR]