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In the context of climate change, innovative financing solutions and the rapid development of financial technology (fintech) offer great potential for the growth of renewable energy. Based on panel data from 30 provinces in China, this paper explores the impact of fintech on renewable energy growth by employing the instrumental variable-generalized method of moments (IV-GMM). We also pay attention to the nexus between fintech and renewable energy growth at different quantiles. This paper also explores the moderating role of the digital economy and the mediating role of green technological innovation. The main results indicate that (1) fintech positively affects renewable energy growth in China; (2) the positive effect between fintech and renewable energy is stronger in provinces with lower levels of renewable energy growth; (3) the digital economy, on the one hand, can significantly accelerate renewable energy growth; on the other hand, under the help of the digital economy, fintech can play a more effective role in increasing renewable energy growth; and (4) fintech indirectly promotes renewable energy growth by increasing the level of green technology innovation. The findings provide meaningful references for governments and policymakers and encourage the accelerated adoption of fintech in the sustainable energy sectors. • The role of financial technologies "fintech" on renewable energy growth is explored. • Fintech successfully stimulates the development of renewable energy. • The impact of fintech on renewable energy growth is asymmetric. • Digital economy facilitates the positive role of fintech in increasing renewable energy growth. • Green technology innovation is the path through which fintech affects renewable energy growth. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions and climate change risk have become constraints on global economic sustainable development. Environmental regulation (ER) is a key method for achieving synergy in CO 2 and pollution reduction in China. This paper is the first study to explore the effects of ER on CO 2 emissions by exploiting the National Environmental Protection 11th Five-Year Plan (NEP11-FYP). The implementation of the NEP11-FYP significantly decreases CO 2 emissions by 19.73% in key environmental cities relative to other cities. Heterogeneity analyses suggest that this negative impact is larger in western cities and cities with more pressure to reduce CO 2 emissions. Scale effects, structural effects, and technical effects might be three potential influencing channels through which ER contributes to the CO 2 reduction effect. In addition, the results of the spatial externality of the NEP11-FYP demonstrate a positive spillover effect in neighboring cities within a distance of 300 km and a negative spillover effect in cities more than 500 km away. Our empirical findings provide policy implications for implementing low-carbon transition strategies and reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

This paper examines the impact of extreme precipitation on Chinese industrial output and its total factor productivity (TFP) using data from the annual survey of industrial firms (ASIF) and daily weather data. The findings demonstrate a significant reduction in industrial firm output as a result of precipitation, with extreme daily precipitation decreasing output by approximately 1.22%. We provide an explanation for this precipitation-industrial output relationship from four perspectives: per capita wages, labor productivity, inventory, and depreciation. The effects of extreme precipitation are more pronounced in high-income and high-precipitation regions, as well as among foreign firms and low-technology firms. Our research suggests that extreme daily precipitation poses a serious obstacle to the development of the manufacturing industry. These results are crucial for understanding the economic impact and concealed costs of climate change, highlighting that extreme precipitation should be recognized as one of the primary sources of damage associated with climate change in the future. [ABSTRACT FROM AUTHOR]

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

China is currently facing a critical challenge in completing its second radical energy transition from fossil to zero-carbon energy amidst the impacts of climate change and the international landscape. In order to clarify the concept of energy transition and the challenges facing China's energy transition, this paper adopts a research framework with Multi-Level Perspective to sort out China's energy history. Drawing on China's energy transition experience, this paper derives four key conclusions. Firstly, the energy transition is a comprehensive transformation of the energy system, which is influenced by the macro landscape, socio-technical regime and innovation niche. Secondly, based on the intensity of the transition, the historical energy transitions can be divided into two categories: incremental energy transitions and radical energy transitions. Thirdly, China's past energy transitions are mainly incremental energy transitions. Influenced by the macro environment and socio-technical regime, the transition process is mostly iterative and tortuous. Fourthly, China's energy transition is facing significant challenges in the current stage, with a tight schedule and heavy tasks, and a lack of basic scientific and technological theories and niche innovations. Building on these findings, specific recommendations to policy makers are provided. • The energy transition is a comprehensive transformation of the energy system. • China's past energy transitions are mainly incremental energy transitions. • China's energy transition faces great difficulties at this stage. • China must champion robust institutional reforms and expedite niche innovations. [ABSTRACT FROM AUTHOR]

Minimizing the detrimental effects of road transport greenhouse gas (GHG) emissions on climate change and global warming requires accurate emission forecasting. To forecast greenhouse gas emissions from industrial and civilian transportation on roads in China, we present new approaches that use data extraction and managed machine learning methods for regression and identification. Four methods are examined: decision tree, multinomial logistic regression, multivariate linear regression, and artificial neural network (ANN) multiple-layer perceptron. The findings suggest that the multiple-layer perceptron approach of ANN has superior prediction accuracy compared to other models. Ensemble modelling techniques, such as Bagging and Boosting, significantly improved the predictive performance of the developed multilayer perceptron system. The paper's conclusions are significant for transport policymakers, regulators, and international organizations in mitigating GHG emissions. [ABSTRACT FROM AUTHOR]

Low-carbon industrial upgrading is a central means to achieve long-term climate change mitigation and sustainable industrial development. Yet the empirical evidence on the effects of environmental policies on low-carbon industrial upgrading remains relatively rare, and the analysis of channels is unexamined. Based on the panel data of 30 provinces in China from 2000 to 2016, this paper has contributed to the literature by testing the impacts of four distinct environmental policies on low-carbon upgrading and their possible channels. We found that energy-saving goals (ESGs) and new energy subsidies (NESs) promoted low-carbon upgrading, while pollution discharge fees (PDFs) restrained low-carbon upgrading and emission trading schemes (ETSs) had no impact. These conclusions were still tenable after a series of robustness tests. Channel analysis reveals that ESGs realized both low-carbon innovation and high-carbon industry restructuring (especially reflected in manufacturing), NESs were effective, but only in directing innovation. PDFs did not improve low-carbon upgrading, possibly due to their negative effects in low-carbon fields (including two sub-fields: energy efficiency and renewable energy). The restructuring and innovative effects of ETSs were insignificant. Finally, this paper put forward several policy implementations, including the promotion of market mechanisms, more strict law enforcement, and low-carbon industry development. • The impact of four distinct environmental policies on low-carbon industrial upgrading is examined. • The unique data of low-carbon patents and newly formed enterprises enable channel analysis. • Energy-saving goals (ESGs) promote industrial upgrading through restructuring and innovation effects. • New energy subsidies (NESs) advance industrial upgrading through the channel of inducing innovation only. • Emission trading schemes (ETSs) have no impact while pollution discharge fees (PDFs) restrain industrial upgrading. [ABSTRACT FROM AUTHOR]

China's wide-ranging circular economy (CE) efforts have been studied multiple times from a range of perspectives. Synthesizing the relevant literature, this paper provides a critical reflection on the transition to a CE in China. Key factors for China's success in shifting towards a CE are seen in multi-level indicators and upscaling niches. This paper makes a novel contribution on limitations to progress, based on emerging evidence on CE projects that fail to sustain. Enriched by experts feedback, this paper critically addresses future challenges to a deep transition resulting from implementation gaps between early majorities and mass markets and coordination challenges arising through regional and sectoral differences. In light of China's commitments to climate neutrality by 2060, such challenges are considered serious. Based on feasible policy learning, the paper however proposes synergies between the CE and decarbonisation driven by efficiency improvements, comprehensive core indicators, upscaling and urban policies as trigger for deeper transformations. Finally the paper undertakes broader reflections and an outlook on evidence-orientated policy learning for a CE and decarbonisation in China. [ABSTRACT FROM AUTHOR]

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

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

• Average start of the photosynthetic period in China was on the 123rd day of the year. • The average start of the photosynthetic period advances at a rate of 4.3 d (10 a)−1. • 64% of the region is temperature controlled, others are precipitation controlled. • Importance of temperature and precipitation determined by pre-season precipitation. • Climate change increases NPP by advancing the start of the photosynthetic period. In the context of global warming, the advancement of spring phenology in northern and temperate regions due to increased temperatures has been widely reported. Early and delayed start of the photosynthetic period (SOP) directly affects the vegetation net primary productivity (NPP). However, the interrelationship between climate change, the SOP, and the NPP is unclear. In this paper, we use the dynamics of decadal daily solar-induced chlorophyll fluorescence data to calculate the response of Chinese vegetation photosynthetic phenology to climate change and its impact on the NPP over the last 20 years. The results found that over the last 20 years, the average SOP in China was on the 123rd day of the year, and the SOP has advanced at an average rate of 4.3 d (10 a)−1, with a faster trend of SOP advancement in highland and high-altitude areas. 64% of SOP in China is controlled by temperature; 36% of the SOP in China is controlled by precipitation, and the relative importance of temperature and precipitation was reversed as the precipitation gradient decreased, with SOP dominated by temperature when pre-season precipitation ≧300 mm, and SOP dominated by precipitation when pre-season precipitation ≦300 mm. Finally, we find that climate change indirectly increases vegetation NPP by advancing SOP. Our study emphasizes the importance of precipitation on phenology. It provides a scientific basis for understanding and predicting the response of spring photosynthetic phenology to climate change and the contribution of spring phenology to carbon estimation in terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

• The innovative effects of three types of carbon-abatement policies (energy-saving goals (ESGs), new energy subsidies (NESs), and carbon emission trading schemes (ETSs)) were examined. • The contributions of both ESGs and NESs policies were relatively stable in the 11th five-year period (2006–2010), but weakened in the 12th five-year period (2010–2015) that followed. • In terms of synergies between policies, no significant estimates for policy coordination were discovered. • Only administrative regulation had a positive effect on the tendency to pursue technology investment. • With an improvement in enforcement strength, the innovation influences from TIPs were not static, but changed differently, even oppositely, on each side of the threshold. Low-carbon technology innovation is considered to be one of the most effective remedial measures for reducing climate change. Based on panel data from 30 provinces in China which were collected firms in operation between 1999 and 2016, this paper used a difference-in-differences (DID) approach to assess whether China's current carbon-abatement policies (i.e. energy-saving goals (ESGs), new energy subsidies (NESs), and carbon emission trading schemes (ETSs)) can direct innovation activities towards low-carbon technologies; then, this paper analyzed the channels involved from the perspective of investment preferences. In terms of policy-induced effects, the contributions of both ESGs and NESs policies were discovered to be relatively stable in the 11th five-year period (FYP) (2006–2010), but weaker in the following 12th FYP, and the ETSs' effect on innovation was found to be not significant. In particular, the estimates for policy coordination were not significant, and the innovation-inducing effects of NESs were moderated by market performance. For the analysis of channels, only administrative regulation had a reinforcing effect on the propensity to pursue technological investment. As enforcement increases, the innovation influence from technology investment preferences (TIPs) has also changed: it is distinct, and even opposite, on each side of the threshold. [ABSTRACT FROM AUTHOR]

In view of the climate emergency, it is necessary to model and forecast road transport emissions for implementing more effective climate policy. This paper fills an important research gap by quantifying the challenges, barriers and remedies of achieving road transport emission reduction and air quality improvement in developing countries. It contributes to the debate on top-down and bottom-up approaches to reconcile carbon and other transport related emissions. China and India are chosen as case studies. Using various official statistics and proxy variables, we estimate and compare the road transport carbon emissions of the two countries systematically from 2009 to 2020. Insights from detailed mode-specific estimations of the bottom-up approach are valuable for targeted policies and measures. An analysis of the major components of road transport carbon emissions points to strategies of promoting electric vehicles, reducing transport demand, accelerating modal shift to low-carbon modes, and cleaner electricity to achieve climate policy. [ABSTRACT FROM AUTHOR]

Extreme weather events and anthropogenic activity have severely impacted the Minjiang estuary (MJE) with evolution patterns in recent decades. Determining the estuarine alluvial evolution pattern is crucial for the sustainable development of densely populated coastal areas. Using chart data, this paper analyzed how the MJE's flushing and siltation changed over time (1950–2019). The findings indicate that, in the past 70 years, the MJE has evolved through seven stages of flushing and siltation under the condition of decreasing incoming sediment: "significant siltation - siltation - minor siltation - significant erosion - significant siltation - minor siltation - significant erosion". Despite decreased incoming material, the estuary underwent substantial siltation from 1998 to 2005. Extreme meteorological conditions were the cause of this anomaly. The "severe flushing" phenomenon occurred in the study area from 2011 to 2019, and the comparison of pre-dam and post-dam at the estuary revealed that extreme weather can only adjust in stages and cannot change the overall state of the estuary flushing due to the reduction of incoming sediment in the basin. According to the EOF (Empirical Orthogonal/Eigen Function) study of four sections of the estuary, it is most impacted by incoming sediment from the watershed, followed by severe weather conditions. Our research is crucial for comprehending how human behavior and harsh weather might affect the development of MJE, and it offers sound advice for the long-term management of MJE. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new repeatable batch processing method is developed for regional SUHI assessment. • A framework is proposed to explain the formation of SUHI effect. • The impacts of most driving factors on SUHI effect are spatial heterogeneous. • More attention should be paid to small cities. The urban heat island (UHI) effect has become a hot topic worldwide because of the double stress of global climate change and rapid urbanization. However, the deficiencies of existing methods hinder the monitoring and assessment of the surface urban heat island (SUHI) effect at the regional scale. This paper presented a new method to assess SUHI intensity, and then applied it in China. The results indicated that: (1) compared with other methods, this new method has some merits like higher accuracy, fewer operational steps, and higher portability. It enables accurate, semi-automated assessment of SUHI intensity at the regional scale. (2) SUHI effect exists in 81.02% of the cities in China. These cities were mainly concentrated in southeastern China, which presented the significant characteristic of spatial agglomeration. (3) Urban-rural differences in relative humidity, vegetation coverage, evapotranspiration, waterbody coverage, and the number of industrial enterprises are the main driving factors for the SUHI effect in China. Furthermore, there are significant interactions among these driving factors. (4) The spatial heterogeneity of the influence directions and intensities of many driving factors is obvious. Therefore, traditional regression models should be utilized more cautiously because they cannot capture the spatial heterogeneity of variables. (5) The hypothesis of "the larger the city size, the higher the SUHI intensity" is not valid, so more attention should be paid to small cities in the future. [ABSTRACT FROM AUTHOR]

Global climate change has become one of the greatest challenges to human development, the study of the dynamic evolution of carbon emissions at the building operation stage and its driving mechanism is of great significance for the reasonable control of carbon emissions, and helpful to provide more scientific and reasonable decision support for proposing an implementable carbon neutral pathway. According to the geospatial differences of carbon emissions at the building operation stage, this paper constructs a research framework on the influencing factors and driving mechanisms of carbon emissions at the building operation stage based on CV, kernel density, Geodetector and other methods. The study shows that first, that the carbon emissions at the building operation stage are unequally distributed in space in provinces of China, and the building carbon emissions vary greatly in structure among different regions. Second, different factors vary greatly in influence. Third, there are great differences in the driving mechanisms of carbon emissions over time, but factors such as urban population and refrigerator ownership are both key influencing factors that have a comprehensive influence on the spatio-temporal changes of carbon emissions. Fourth, all the factor pairs are bifactor-enhanced or non-linearly enhanced, and they can be classified into three types of high, medium, and low levels. Fifth, a carbon neutral pathway map for the building sector is proposed based on the spatial distribution of carbon emissions and its driving mechanism, to provide reference for foreign regions with similar conditions. • Calculated the carbon emission at the building operation stage in Chinese provinces. • Analyzed trend and composition of carbon emission at the building operation stage. • Analyze spatial-temporal changes of carbon emissions by GIS. • For the first time, analyzed driving factors of carbon emissions by Geodetector. • Proposed a carbon neutral pathway map for the building sector. [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 database consisting of 378 failure cases was established for analyses. • Trends and distributions of heavy rainfalls in China were characterized. • Spatio-temporal distribution patterns of the failures were identified. • Urbanization, climate and geological conditions were key factors. Currently, global warming is increasing rainfall intensities worldwide, particularly in China. This climate change has caused numerous underground infrastructure failures, which threatens the sustainable development of urban environments. Most failures brought about secondary hazards in densely populated areas, which often caused massive damages and casualties and/or injuries. Thus, a summary of such failures and their contributing factors on a national scale is essential for understanding the adverse influences of climate change on infrastructures, which can help urban planners, designers and engineers to improve city resilience. In this paper, an overview of 378 underground infrastructure failures in China associated with heavy rainfall was conducted. First, the latest rainfall characteristics in China were analyzed. Then, a review was conducted in four aspects, i.e., infrastructure types, involved strata, and temporal and geographic distributions. Finally, contributing factors of the failures were discussed. Several major findings were obtained: (1) the failure numbers had increased significantly since 2010, mainly attributed to the intensification of rainfall in rapidly urbanizing regions; (2) the resilience of underground infrastructures against heavy rainfall is governed by the performance of existing drainage facilities nearby; and (3) more failures clustered in the urban environments featuring highly concentrated rainfalls and thick-layered unsaturated coarse-grained soils. [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]

• 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]