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Carbon dioxide capture, utilization, and storage (CCUS) technology is an emerging technology with large-scale emission reduction potential and an essential component of the global response to climate change to achieve net-zero goals. As the two most important countries in global climate governance, it is necessary to review and examine the current status and trends of research in the field of CCUS in China and the USA. This paper uses bibliometric tools to review and analyze peer-reviewed articles in the Web of Science from both countries during 2000–2022. The results show a significant increase in research interest among scholars from both countries. The number of publications in the CCUS field in China and the USA was 1196 and 1302, respectively, showing an increasing trend. China and the USA have become the most influential countries in CCUS. And the USA has a more significant academic influence on a global scale. Furthermore, the research hotspots in the field of CCUS are diverse and differentiated. That is, China and the USA pay attention to different research hotspots or have different focuses in different periods. This paper also finds that new capture materials and technology development, geological storage monitoring and early warning, CO2 utilization and new energy development, sustainable business models, incentive policies and measures, and public awareness are critical directions for future research in the field of CCUS, to provide a comprehensive review and comparison of CCUS technology development in China and the USA. It helps to gain insight into the research differences and linkages between the two countries in the field of CCUS and identify the research gaps between them. And place some consensus that policymakers can use. [ABSTRACT FROM AUTHOR]

As two major powers that are willing to lead the design and evolution of the global climate regime, the EU and China have maintained a dialogue on climate change and biodiversity while clashing over other economic and political issues. This paper investigates EU-China relations in the global climate regime by briefly analysing three main areas that are key for the global green transition: standardization, green taxonomy, and the renewables sector. The paper claims that EU-China relations in the global climate regime develop within the dialectical collaboration-competition nexus, showing moments of consensus as well as contention between the two major powers in the three selected cases. [ABSTRACT FROM AUTHOR]

To effectively shift from economic growth based on high levels of energy expenditure and pollution and to actively address global climate change, the purpose of this paper is to explore whether environmental regulation in developing countries helps promote TFP from a credit resource allocation perspective. This paper examines the impact of environmental regulation on firm TFP and the underlying mechanism of TFP using data on Chinese listed A-share companies from 2011 to 2018. The relationship between ERS and enterprise TFP is found to exhibit a clear U shape, that is, it shows the characteristics of inhibition followed by promotion. The mechanism analysis indicates that credit allocation is a significant mediator between environmental regulation and its effect on firm TFP through such allocation, while the heterogeneity analysis shows that in the central and western regions and in highly competitive industries, environmental regulation significantly affects firm TFP through credit allocation. The empirical results, which indicate that ERS in China is still at the left-hand side of the U-shaped curve inhibition area, suggest that government regulation should be strengthened, differentiated regional environmental regulation should be implemented, the bank credit system should be improved, and the U-shaped inflection point must be crossed if high-quality economic development is to be achieved in China. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

The "Dual Carbon" initiative is a two-stage carbon reduction goal proposed by China, with significant implications for global climate change mitigation. This article examines the impact of the "Dual Carbon" strategy on China's forestry development and explores how to leverage this strategy to facilitate the transformation and advancement of the forestry sector. Current review indicated that forestry has the advantage of achieving higher emission reduction targets at a low cost. Starting with an overview of the "Dual Carbon" strategy, this paper analyzes the carbon sequestration potential of plants and soil, and the challenges and opportunities faced by forestry development under this framework. Furthermore, we outline implementation pathways for forestry development, aiming to provide insights for the progress of China's forestry sector. Overall, it should be noted that the priority is to vigorously develop timber resources, and we also need to vigorously develop and protect forestry talent with the support of China's policies. By trapping into the carbon storage capabilities and leveraging carbon trading mechanisms of forests, a favorable ecological environment can be created, thus achieving the goal of carbon neutrality. Highlights: • Forest development and its carbon sinks, attributed to plant and soil have the potential in carbon sequestration process, thus helping China achieve carbon neutrality. • The supply of forest products and the balance of economic growth and environmental protection are the key difficulties under the "Dual Carbon" strategy. • Trading forest carbon sinks can boost China's sequestration. [ABSTRACT FROM AUTHOR]

The boom of building various industrial agglomerations in China has continued for many years. The relationship between industrial agglomeration and environmental pollution is the core issue of this paper. At the same time, green finance is a new financial development model that takes environmental protection as the core, and effectively promotes the sustainable development of the environment, the economy, and society while maintaining its own sustainable development, so green finance is a major direction for future financial development. This paper selects the data of 30 Chinese provinces from 2004 to 2020 as the research object and uses a system-GMM method to verify the relationship between industrial agglomerations, green finance on regional environmental pollution. It provides theoretical reference for improving global climate change and reduces environmental pollution (EP), concludes as follows. (1) Industrial agglomeration can exacerbate EP level in China, and also exacerbates EP in the western region, but the effect of industrial agglomeration on EP in the eastern and central regions has been insignificant. (2) Green finance can improve environmental pollution. The intensity of EP in economically less developed regions is more sensitive to green finance policies. (3) The correlation effect of industrial agglomeration and green finance can improve environmental pollution, i.e., green finance has an important role in improving EP. However, there are significant differences in different regions. The interaction term between industrial agglomeration and green finance with a non-significant positive coefficient in the eastern region, and it is non-significant negative coefficient in the central region, and a significant negative coefficient in the western region. The work has important theoretical value for achieving the goal of regional sustainable development and green transformation. [ABSTRACT FROM AUTHOR]

The global value chain has introduced profound changes in international trade, economic development, and technology progress as well as greenhouse gas emissions worldwide. This paper investigated the impact of the global value chain and technological innovation on greenhouse gas emissions by introducing a partially linear functional-coefficient model based on panel data of 15 industrial sectors in China from 2000 to 2020. Moreover, the greenhouse gas emission trends of China's industrial sectors from 2024 to 2035 were predicted using the autoregressive integrated moving average model. The results showed that (1) Greenhouse gas emissions were affected negatively by global value chain position and independent innovation. Nevertheless, foreign innovation had the opposite effect. (2) The results of the partially linear functional-coefficient model implied that the inhibitory effect of independent innovation on GHG emissions decreased with an improvement in the global value chain position. (3) The positive effect of foreign innovation on greenhouse gas emissions increased and then, decreased as the global value chain position improved. (4) The prediction results indicated that greenhouse gas emissions will continue on an upward trend from 2024 to 2035, while industrial carbon dioxide emissions should peak at 10.21 Gt in 2028. This carbon-peaking goal would be achieved in China's industrial sector by actively improving the global value chain position. Addressing these issues will enable China to take full advantage of the development opportunities of participating in the global value chain. [ABSTRACT FROM AUTHOR]

As global climate change becomes increasingly severe, energy technology innovation has become a key means of coping with the climate crisis and realizing green and low-carbon development. However, existing literature rarely examines the effects of carbon emission reduction policies based on the perspective of energy technology progress for both short-term economic fluctuations and long-term equilibrium. This paper introduces the fossil energy technology sector and the renewable energy technology sector into the dynamic stochastic general equilibrium (DSGE) model, and compares the effectiveness of the carbon emission cap policy, the fossil energy technology subsidy policy, and the renewable energy technology subsidy policy under the framework of China's carbon trading market in promoting macroeconomic growth and controlling pollutant emissions. We found that in long-term, the emission reduction effect of the carbon emission cap policy falls short of the other two policies, and subsidizing fossil fuel technologies is more cost-efficient comparatively. The government expenditure shock can all stimulate macroeconomic growth with crowding out of private investment and household consumption, whereas the energy technology research productivity shock leads to a decline in total output and an increase in renewable energy technology demand. In addition, pollutant emissions are pro-cyclical under the impact of total carbon policies and counter-cyclical under the impact of energy technology subsidy policies. This article constructs a multi-technology sectoral dynamic stochastic general equilibrium model, expanding the research perspective and theoretical framework for evaluating carbon emission reduction policies. At the same time, it proves the importance of the government to implement the phased energy technology subsidy policy while implementing the carbon emission cap policy, which provides important enlightenment for the implementation and adjustment of carbon emission reduction policy. [ABSTRACT FROM AUTHOR]

The 2015 Paris Agreement has set out the climate change target of limiting global warming to 1.5 °C, which poses a serious challenge to countries to reduce emissions. As the world's largest carbon emitter, promoting the realization of the "dual-carbon" goal is the key to realizing China's green transformation and high-quality development. Chinese asset managers play active roles in the capital market as an important channel of asset allocation. Currently, the vast majority of Chinese asset managers hold high percentages of high-carbon industries in their portfolios, and lack quantitative data of their carbon footprints embodied in equity investments, which faces huge carbon-related risks. Therefore, it's an urgent need to comprehensively and scientifically measure financed emissions of Chinese asset managers, which is of great significance for asset managers' carbon risk management and sustainable investment. This paper develops a detailed inventory of carbon emissions for equity portfolios managed by Chinese asset managers from 2010 to 2020, which stands as a pivotal reference for in-depth analysis of emission characteristics. [ABSTRACT FROM AUTHOR]

The rapid development of the aviation industry significantly impacts global climate change. The carbon Emissions Trading Scheme (ETS) and Sustainable Aviation Fuels (SAFs) are considered two essential ways for the aviation industry to reduce emissions. This paper uses China-foreign routes, the fastest growing region in the world, as an example to calculate the actual emissions (CO2, CO, HC, NOx, SO2, and PM2.5), calculate the Carbon Dioxide Equivalent Concentration (CDEC) using the Aviation FAIR-GWP concentration method, to compare the role of the ETS and SAFs in controlling emissions until the year 2100. The results show that SAFs are more effective in controlling the pollutant emissions of the aircraft than ETS, as ETS mainly covers CO2 and ignores other greenhouse gases. However, the best way is to combine SAFs and ETS; the combined effect is much better than SAFs alone or ETS alone. The research results provide systematic suggestions for the aviation industry to reduce emissions effectively. [ABSTRACT FROM AUTHOR]

Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development. The paper reveals areas of common and differentiated SDG priority at the national and subnational levels in China considering synergy and trade-off. The findings suggest that provincial governments should formulate more targeted policy aligning with national priority to achieve SDGs. [ABSTRACT FROM AUTHOR]

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Climate change is an important issue for cities today and in the future. At present, China has a large population and complex climate conditions, and cities are also vulnerable to the adverse effects of climate change (Tian, Environ Sustain Dev 6: 153-155 2020). Three-dimensional greening can not only improve the green space system of a city but also have a far-reaching impact on the ecology, image, and economic benefits of a city. Therefore, the study of urban three-dimensional greening is an effective means to deal with climate change strategies. By exploring the influence of traditional greening and three-dimensional greening on Local Climate in Beilin District of Xi'an, Shaanxi Province, the mechanism of three-dimensional greening on urban ecological environment was discussed, and the ecological theory, urban three-dimensional greening theory, and urban local climate zone (LCZ) were referred to. Based on the methods of national climate monitoring, ENVI-met simulation, and field independent measurement, this paper selected a research sample site in the east section of Jianshe Road, Beilin District, Xi'an City, Shaanxi Province, China, and applied ENVI-met software to simulate the thermal stress relationship among building exterior surfaces, plants, and air in the street; quantified the overall ecology of the area; and used measuring instruments. The influence of different types of greening in the base on the site temperature, humidity, CO2 (carbon dioxide) concentration, wind speed, and other climate factors data was, respectively, measured and analyzed. The grid analysis was used to compare the traditional greening and three-dimensional greening, then the numerical differences of each impact factor were sorted out, and the effect of three-dimensional greening on the improvement of urban ecological environment was discussed by analyzing the climate factors with greater impact. The results show that (1) three-dimensional greening plus traditional greening is the most beneficial mode; (2) in the same environment, according to the parameter of 1.5 m from the ground in the model environment, it can be seen that the temperature of the space treated with three-dimensional greening of buildings is reduced by 3.5–3.6 ℃ compared with the control group, the relative humidity is different by 7–8%, the CO2 concentration is reduced by about 5%, and the spatial wind speed is relatively small. (3) When the urban green coverage rate is more than 40%, the improvement of temperature is more obvious, if it reaches 50%, the cool phenomenon in summer can be fundamentally changed. From the perspective of human perception, the PMV index increased by 0.27 on average. This paper discusses and analyzes the three-dimensional greening of urban streets in Beilin District, Xi'an City, Shaanxi Province, China, and studies its influence on urban ecology to different degrees. The conclusions are as follows: Different types of greening have different degrees of influence on urban climate. Meanwhile, the experimental results of this paper show that in cities like Xi'an, Shaanxi Province, China, where summer is hot, adding three-dimensional greening to traditional street greening can significantly improve the environmental microclimate, which is an effective means to cope with climate change, improve the site environment, and stabilize the urban ecosystem. [ABSTRACT FROM AUTHOR]

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

Climate change has been a widely concerned issue for decades. As the key policy target, the economic impact caused by climate change has received general attention from scholars and governments around the world. For the number of literatures is huge and the relationships among the literatures are not clear, we aim to clarify the research hotpots and the research trends of current literatures and provide inspiration for the development directions of future research in this paper. Using the bibliometric method, this paper characterizes the literatures on the economic impact of climate change based on the Web of Science (WoS) Core Collection. The results reveal that the USA occupies the leading position of the studies, which publishes most documents, and contains the most productive institutes and well-known scholars. From 2009, the number of documents published by a Chinese scholar started to increase rapidly, which makes China the second most productive country in recent years. The journals both belong to the WoS Categories of economics and environmental sciences and tend to publish more literatures than others. Adaptation, vulnerability, uncertainty, economic growth, climate policy, ecosystem service, energy consumption, renewable energy, food security, and land use are the representative keywords that have both high frequency and high centrality. Potential benefits, fat-tailed risk, social cost, international migration, and sustainable intensification are the top five main research hotspots. Based on the citation network of the top 50 documents with the highest local citation score, four research trends are sorted out: (i) the methodological innovation to monetized estimate the economic impact of climate change, (ii) the effect of current and future adaptive measures on agriculture, (iii) the interactional relationship between induced technological change and carbon tax, and (iv) the effect on labor market caused by climate change. [ABSTRACT FROM AUTHOR]

The world is facing the challenges of climate change and energy structure adjustments. The role of digital finance, a new branch of business that combines digital technology and traditional financial products, in reducing global carbon emissions needs to be studied. This paper uses panel data on 280 cities in China from 2011 to 2019 to empirically examine the efficacy of digital finance for governing carbon emission reductions and the mechanism by which it does so. The results show that (1) digital finance can facilitate carbon emission reductions and help reduce carbon emission intensity within regions; (2) digital finance helps promote the rational allocation of resources and alleviates factor distortions by encouraging firms to rationally use their own factor endowments so as to reduce carbon emission intensity, which holds robustly after considering the endogenous issues such as possibly omitting variables and collinearity; and (3) differences in geographical location, the vitality of regional innovation and entrepreneurship, regional willingness to protect the environment, and environmental protection levels lead to heterogeneity in the effect of digital finance on carbon emission intensity. Therefore, it is necessary to vigorously develop digital finance as a long-term tool for carbon governance. [ABSTRACT FROM AUTHOR]

Based on the annual mean PM2.5 concentration data of 30 provinces and cities in China from 2006 to 2020, this paper constructs a structural model of manufacturing haze pollution, expounds the main mechanisms affecting haze pollution, then statistically decomposes the main factors affecting the change of pollution emissions, and examines the direct and indirect impact paths of the change of haze pollution emissions in China. The study found that (1) the inhibitory effects of latent variables on manufacturing haze pollution is from strong to weak in order: industrial structure upgrading, environmental regulation, trade opening, productivity improvement, and economic scale expansion, while the optimal path for the indirect effect of exogenous latent variables on haze pollution is to rely on environmental regulation and opening up to achieve the improvement of productivity, so as to achieve the purpose of reducing haze pollution. (2) The analysis based on the PVAR model found that industrial structure adjustment is the key factor of haze decline in both the short and long term. Environmental regulation has an obvious effect on haze control in the short term, but in the long run, it still needs to rely on industrial structure adjustment, production efficiency improvement, and trade opening to achieve the goal of reducing haze. (3) There is an inverted U-shaped nonlinear relationship between output scale and environmental regulation. In addition, trade openness has a long-term effect on productivity. Technology spillovers from opening up can reduce haze pollution in the long run by improving productivity. (4) The environmental regulation policy in the central region is characterized by "race to the bottom," while the eastern region shows the characteristic of "race to the top" in the policy game of improving productivity and optimizing the industrial structure. Therefore, haze control requires an appropriate intensity of environmental regulation to reduce the proportion of high pollution and high energy consumption industries. Make full use of the international cooperation platform of the "the Belt and Road Initiative" and the pilot free trade zone to promote substantive cooperation between Chinese enterprises and developed countries in the field of environmental protection technology, increase investment in research and development of clean equipment and cleaner production technology, improve productivity, help China's green manufacturing, and contribute Chinese wisdom and Chinese solutions to global environmental governance and climate change. [ABSTRACT FROM AUTHOR]

Climate change has a profound impact on human survival and development. Climate change is an energy and economic issue, which should be driven by technology. Total factor energy efficiency (TFEE) improvement is undoubtedly a breakthrough in solving energy problems. In this paper, the fixed effect model, impulse response function, and threshold regression model are used to test the complex relationship between export sophistication and TFEE. The results reveal that export sophistication improvement leads to higher TFEE. The impulse response results verify the existence of a phased and positive correlation between export sophistication and TFEE. Finally, the relationship between export sophistication and TFEE significantly varied across different threshold levels of regional corruption score, economic development, and openness. This article led the foundation for supporting China's export sophistication promotion strategy and also provides a reference for energy efficiency improvement and energy crisis response in the post-pandemic era. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to strengthen research concerning the impact of climate change on China's water resources, in order to avoid extreme weather events such as regional rainstorms and floods affecting the stable supply of energy and electricity. The goal is to reorganize energy industry allocation to make China's energy the most efficient, which would thus help achieve sustainable development goals. The biggest contribution and of this paper is not only to enlarge the scale and take into account the sustainable aspects, but also to consider climate change factors that have been ignored in the past as exogenous variables. For the first time, we take stock of the optimal allocation of new and tradition energy sources and carbon dioxide. This study uses the Dynamic ZSG-DDF model with exogenous variables and undesirable outputs to find a way to redistribute carbon dioxide, new energy, and tradition energy from different provinces on the premise of maximizing efficiency, thus achieving the goal of reducing carbon and saving the earth. The research results show that the energy efficiency of tradition energy is higher than that of new energy in various provinces. At the same time, the China government must comprehensively review the quota targets of new energy, tradition energy, and carbon dioxide (CO2) in each province as quickly as possible. Currently, the quotas of various provinces are seriously misplaced, and 26 provinces in total have great room for improvement. [ABSTRACT FROM AUTHOR]

As the primary source of carbon dioxide fixation, vegetation is critical to the carbon sink process. In this paper, the Net Primary Productivity (NPP) and the Gross Primary Productivity (GPP) were simulated using the Carnegie-Ames-Stanford Approach (CASA) model and the Vegetation Photosynthesis Model (VPM), respectively, and then the Potential Gross Primary Productivity (PGPP) and the GPP affected by human activities (AGPP) were simulated by combining Potential Net Primary Productivity (PNPP), and then the impact of climate change and human activities on GPP was assessed in the Heihe River Basin (HRB). The results showed that the GPP of grassland and Bare or Sparse Vegetation (BSV) exhibited a fluctuation rise, with increases of 0.709 gCm−2 a−1 and 0.115 gCm−2 a−1, respectively, whereas the GPP of cropland showed a fluctuation reduction, with a decline rate of −0.465 gCm−2 a−1. Climate change and human activity are both positive for vegetation growth, and human activity being the primary factor influencing GPP change. Human-dominated vegetation restoration accounted for 56.1% of the overall restoration area, with grassland GPP being the most visible response to human activities. The GPP changes in crop and grassland had a positive correlation with precipitation but a negative correlation with temperature among climate change factors, whereas the GPP changes in BSV had a negative correlation with both precipitation and temperature. Quantitative analyses of climate change and human activities' dynamic contributions to vegetation can give scientific and theoretical insight for dealing with global climate change. [ABSTRACT FROM AUTHOR]

Temperature-economic growth relationships are computed to quantify the impact of climate change on the economy. However, model performance and differences of predictions among research complicate the use of climate econometric estimation. Machine learning methods provide an alternative that might improve the predictive effects. However, time series and extrapolation issues constrain methods such as random forests. We apply a simple thought experiment with national marginal GDP growth by aggregating subnational climate impact to alleviate the shortcomings in random forests. This paper uses random forests, multivariate cubic regression, and linear spline regression to examine the direct impacts of temperature on economic development and conducts a performance comparison of the methods. The model results indicate an optimal temperature of 15°C, 15°C or 21°C for each model. Furthermore, a thought experiment indicates that the marginal predictions of national GDP changes by approximately 1%, −3%, or −6% for models with 1°C warming. The performance comparison suggests that random forests have stable model performance and better prediction performance in bootstrapping. However, the extrapolation problem in random forests causes underestimation of climate impact in 5% of cells under 6°C warming. Overall, our results suggest that temperature should be considered in economic projections under climate change scenarios. We also suggest the use of more machine learning methods in climate impact assessment. [ABSTRACT FROM AUTHOR]

Green credit encompasses financial instruments and services utilized to mitigate greenhouse gas emissions and facilitate adaptation to global climate change. Establishing a long-term stable green credit institution is crucial to promoting carbon abatement goals. This study uses the difference-in-difference (DID) model to discuss the impact of green credit policy (GCP) on environmental performance based on the China industrial enterprise data. Our results show that GCP inhibits the pollution emissions and improve firm environmental performance. This improvement effect is attributed to a reduction in production scale, and financing constraints. Moreover, GCP increases the firms' exit risk from market and promotes the technological innovation of incumbent firms. Economic growth target constraints trigger a positive moderation role in the implementation of GCP. Heterogeneity results show that such improvement effect is more pronounced in state-owned firm, large-scale firms, and high R&D intensity firms. Importantly, our findings also suggest the environmental monitoring effect of green credit is dependent on the institutional quality. Only in a sound market environment can GCP effectively improve firm environmental performance. Finally, we propose to build a systematic incentives and constraints mechanism to achieve the sustainable development. The conclusions of this paper provide empirical evidence and policy implications for the implementation of GCP. [ABSTRACT FROM AUTHOR]

Agro-pastoral ecotone of northern China is the prominent area for agricultural production, but it is also the most typical ecological fragile area with frequent drought disasters. Taking Yulin City at Shaanxi Province in China as the case area, the paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought in China's agro-pastoral ecotone in the period 2000 to 2020. The results show that: 1) the agricultural vulnerability to drought in Yulin City has shifted from high vulnerability in the period 2000–2010 to low vulnerability in the period 2011–2020. 2) There exist obvious spatio-temporal differences of the agricultural vulnerability to drought in Yulin City during the research period. 3) Four sensitive events and 14 resilient events were identified in the research and the crops of Yulin had become more resilient to drought. Finally, the paper put forward with policy implications to make adaptive strategies of agriculture to climate change in China's agro-pastoral ecotone in the future, e.g., carrying out agricultural zoning based on agricultural production conditions, intensifying the construction of disaster prevention and relief system, and integrating with modern agricultural technology to develop new type agriculture. [ABSTRACT FROM AUTHOR]

Changing climate has altered the trends and variability of precipitation and temperature globally and thereby increasing the risk of natural and social disasters, especially in coastal climatic transitional zones such as the Huaihe river basin (HRB). This paper applies the Empirical Quantile Mapping (EQM) method for bias correction and systematically evaluates the performance of the 30 Global climate models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating precipitation and temperature over the Huaihe river basin (HRB) for 1979–2014. A suitable multi-model ensemble subset (BMME) is selected based on the Euclidean Distance (ED) synthetic metric. Results show that in comparison to the baseline period 1995–2014, precipitation (temperature) over HRB is projected to increase at the rate of around 15 mm/decade (0.1 °C/decade), 16 mm/decade (0.3 °C/decade), 20 mm/decade (0.5 °C/decade), and 15 mm/decade (0.6 °C/decade) for the period 2015–2100, under Shared Socioeconomic Pathways SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. In the long-term (2081–2100), the annual precipitation is projected to increase by 32%, 27%, 35%, and 26%, under the four scenarios, respectively. The temperature is projected to remain stable or slightly decrease under SSP1-2.6 (2 °C) and SSP2-4.5 (3 °C), while will keep rising and increasing by 6 °C under SSP5-8.5 and by 4 °C under SSP3-7.0 by 2100. The isotherm and isohyet are projected to shift northwest from southeastern coastal China to inland in the future, which is likely associated with the northwestward shift of the western Pacific anticyclone in summer. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between climate change and the spatial distribution of population in China. We establish a two-way fixed effects model to investigate the role of temperature difference in the spatial distribution of China's population. We find that the annual variation of temperature has an impact on city size in both large and small cities, and that city size tends to shrink as the temperature difference increases. Meanwhile, we also find that the population in the cities located south of Qinling-Huaihe Line and Aihui-Tengchong Line (Hu's Line) is more sensitive to temperature effects, and that the temperature difference has a significant negative effect on city size. Similarly, the same results are found for prefecture-level cities with low administrative levels. Considering the endogeneity between temperature change and city size, we adopt an instrumental variable using latitude to perform a more robust empirical analysis, the results of a series of robustness tests support these conclusions. [ABSTRACT FROM AUTHOR]

Rubber plantations are among the most important in the world's tropical regions. They play a positive role in carbon sequestration and in delaying climate change, supplying strategic resources of natural rubber (NR), and aiding in poverty alleviation and rural revitalisation. This paper reviews six methods of research on carbon sinks in rubber plantations: the biomass inventory method, the biomass conversion factor continuous function method, the trade potential of carbon sinks method, the calculation method for carbon storage of rubber latex, the eddy covariance method, and the remote sensing image model method. This study clarifies the carbon sink assessment and enhancement model for rubber plantations and describes the composition of the carbon pool, which includes the aboveground and belowground vegetation biomass carbon pools, litter carbon pool, latex carbon pool, and soil carbon pool. It also examines influencing factors such as tree age, global climate change, and human disturbance, as well as improvement pathways including afforestation, fertilisation, irrigation, and tapping, and evaluation methods like field surveys, positional observations, remote sensing monitoring, and model simulation. Research on carbon sequestration in rubber plantations faces challenges, including the unclear dynamics of carbon sources and sequestration, uncertain spatial and temporal patterns, and the long-term lack of accurate monitoring of carbon sinks and technologies for increasing sinks and reducing emissions. Future research should focus on the methodology of rubber plantation carbon sequestration projects, the dynamics of carbon sequestration, and the spatial allocation pattern of carbon sequestration in rubber plantations. [ABSTRACT FROM AUTHOR]

With the acceleration of the global response to climate change, increasing attention has been paid to the risks associated with climate change mitigation, such as regulation uncertainties and market interactions. As the country with the greatest CO2 emissions globally, China has launched a national carbon market to speed up its climate mitigation. While the national carbon market provides a platform for regional coalitions to reduce emissions, its incomplete sectoral coverage might allow for the strategic behavior of industries in different regions and ultimately affect the efficiency of the carbon market. This paper explores how the sectoral expansion of the national carbon market affects regional emission reductions in China when emissions trading sectors engage in strategic behavior in the output market. From the sectoral perspective, our numerical results show that the strategic effect in the electricity and steel sectors is more significant than in other sectors. From a regional perspective, the western regions of China, which are mostly permit sale regions, have less strategic power than the eastern regions in the output and carbon markets. Finally, this paper suggests that measures, such as the dynamic adjustment of emission allowance allocation, should be considered by policy makers to prevent the widening of regional economic disparities when extending the sectoral coverage of the carbon market in China. [ABSTRACT FROM AUTHOR]

The problem of global climate change is a common problem faced by all countries, and developing countries will face heavier pressure to reduce carbon emissions while promoting economic development. China is currently in a period of economic transformation, and the contradiction of industrial structure upgrading is becoming more and more prominent. The unreasonable industrial structure has caused a large consumption of resources, hindering the optimal allocation of resources and affecting carbon emissions. Technological innovation is an important force to cope with environmental changes, promote economic growth, and improve comprehensive competitiveness. Can technological innovation achieve carbon emission reduction under industrial structure upgrading? In this paper, industrial structure upgrading, technological innovation, and carbon emissions are studied together, and the impact of industrial structure upgrading, technological innovation on carbon emissions is theoretically analyzed, as well as how industrial structure upgrading acts on carbon emissions through technological innovation. An empirical test is conducted using 30 provincial panel data in China from 2005 to 2017, and it is found that industrial structure upgrading can reduce carbon emissions. An econometric analysis based on the mediating effect model finds that industrial structure upgrading has both a direct carbon emission reduction effect and a mediating effect of reducing carbon emissions through technological innovation, and the mediating effect of technological innovation in reducing carbon emissions remains significant in the regression analysis of sub-regions. Based on the research of this paper, it is suggested that the advanced development of industrial structure should be promoted, the rationalization of industrial structure should be promoted, the innovation development strategy should be firmly implemented, and the level of technological innovation should be promoted. [ABSTRACT FROM AUTHOR]

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

The Chinese government has established carbon emissions trading schemes (CETS) to cope with climate change and reduce carbon emissions. This paper uses the multi-period difference in difference (DID) model to explore the impact of CETS on cities' GDP and GDP growth rates in China based on data from 285 prefecture-level cities from 2008–2019. We find that CETS increase the level of GDP by 3.4% and the GDP growth rate by 0.004. The mechanism of increasing GDP includes promoting investment and innovation, and the mechanism of increasing the GDP growth rate includes only promoting the investment growth rate. Thus, CETS satisfy both the weak and strong versions of the Porter Hypothesis from the GDP and growth rate perspectives. In the heterogeneity analysis, we find that the impacts of CETS on cities' GDP and GDP growth rates decrease with the increase of the corresponding dependent variable. In the spatial spillover analysis, we find that the establishment of CETS has a positive spillover effect on the GDP of cities around 50 km and 150 km, and a negative spillover effect on the GDP of cities around 200 km, but there is no spatial spillover effect on the GDP growth rate. [ABSTRACT FROM AUTHOR]

Building a more resilient response system to climate change for sustainable development and reducing uncertainty in China's food markets, requires access to historical research gaps and mapping future research progress for decision making. However, the lack of quantitative and objective analyses to ensure the stability and development of agroecosystems increases the complexity of agro-climatic mechanisms, which leads to uncertainty and undesirable consequences. In this paper, we review the characteristics of climate change in China (1951–2020), reveal the mechanisms of agroecosystem structure in response to climate, and identify challenges and opportunities for future efforts in the context of research progress. The aim is to improve the scientific validity and relevance of future research by clarifying agro-climatic response mechanisms. The results show that surface temperature, precipitation, and frequency of extreme weather events have increased to varying degrees in major agricultural regions of China in 1951–2020. And they have strong geographic variation, which has resulted in droughts in the north and floods in the south. Moreover, climate change has complicated the mechanisms of soil moisture, Net Primary Productivity (NPP), soil carbon pool, and crop pest structure in agroecosystems. This lends to a reduction in soil water holding capacity, NPP, soil carbon content, and the number of natural enemies of diseases and insects, which in turn affects crop yields. However, human interventions can mitigate the deterioration of these factors. We have also realized that the methodology and theory of historical research poses a great challenge to future agroecosystem. Historical and projected climate trends identified current gaps in interdisciplinary integration and multidisciplinary research required to manage diverse spatio-temporal climate change impacts on agroecosystems. Future efforts should highlight integrated management and decision making, multidisciplinary big data coupling, and numerical simulations to ensure sustainable agricultural development, ecological security, and food security in China. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable basis for carbon pricing and ensuring the healthy development of carbon markets. Therefore, this paper proposes a two-stage interval-valued carbon price combination forecasting model based on bivariate empirical mode decomposition (BEMD) and error correction. In Stage I, the raw carbon price and multiple influencing factors are decomposed into several interval sub-modes by BEMD. Then, we select artificial intelligence-based multiple neural network methods such as IMLP, LSTM, GRU, and CNN to conduct combination forecasting for interval sub-modes. In Stage II, the error generated in Stage I is calculated, and LSTM is used to predict the error; then, the error forecasting result is added to the first stage result to obtain the error-corrected forecasting result. Taking the carbon trading prices of Hubei, Guangdong, and the national carbon market, China, as the research object, the empirical analysis proves that the combination forecasting of interval sub-modes of Stage I outperforms the single forecasting method. In addition, the error correction technique in Stage II can further improve the forecasting accuracy and stability, which is an effective model for interval-valued carbon price forecasting. This study can help policymakers formulate regulatory policies to reduce carbon emissions and help investors avoid risks. [ABSTRACT FROM AUTHOR]

Recent years have witnessed climate change characterized by increasingly frequent extreme precipitation events, and the assumption of stationarity in traditional frequency analyses is gradually being questioned. In terms of the current research status in China, there is a lack of thorough investigations on the linkage between extreme precipitation and climate change. This paper aims to determine the dominant climate indices as well as the corresponding significant time scales and periods affecting extreme precipitation over China for dynamic assessments of the upcoming rainstorm risk. Correlations between 15 climate indices and precipitation extremes, as well as the correlations among climate indices, are fully explored to identify potential predictors for non-stationary modeling. Then, 21 non-stationary generalized extreme value (GEV) models are constructed, and the optimal covariates as well as their lag times with extreme precipitation at 769 stations are ascertained in a Bayesian framework. Finally, a complete predictive process is developed, and the national rainstorm risk under non-stationary conditions is assessed. The results indicate that precipitation extremes remain stationary only at 74 stations (less than 10%). WPI is dominant in modeling the variability in precipitation extremes for nearly 22% of the total stations, ranking first among all the climate indices. The predominant time scale affecting extreme precipitation at the majority of stations is 3 months. Ignoring the non-stationarity of extreme precipitation inevitably leads to misperceptions of rainstorm risks, and the spatial distribution of the maximum case of the design rainstorms under non-stationary conditions differs remarkably from that under stationary conditions. Our findings have important implications for the in-depth understanding of the real drivers of extreme precipitation non-stationary and enable advanced predictions of rainstorm risks for mitigating subsequent disasters. [ABSTRACT FROM AUTHOR]

This paper studies climate change impacts on total factor productivity (TFP) in China using economic and climatic data for provincial capital cities and municipalities from 1998 to 2017. We employ a novel nonparametric quantile method to decompose historical temperature data into multiple temperature quantiles, which are then used in our regression analysis to avoid estimation bias caused by seasonal heterogeneity of temperatures across China. Specifically, we create three temperature quantiles for each city to represent their extremely high temperatures in summer, extremely low temperatures in winter, and mild temperatures in spring and fall. In general, we find that a warming climate has a significant negative impact on TFP in the long-run, while in the short term, only increases in extreme temperatures exert significant negative effects on TFP growth. However, the temperature effects on TFP vary substantially across coastal capital cities, inland capital cities, and municipalities due to their differences in geography, development levels, and political positions. Finally, our results are robust when spatial spillover, temporal lagging, and labor intensity effects are taken into account. [ABSTRACT FROM AUTHOR]

The reconstruction of high-resolution chronologies for prehistoric cultures is a prerequisite for understanding the history of human evolution and its relationship with environmental change, and is valuable for exploring the trajectory of transcontinental cultural exchanges in prehistoric time. The Hexi Corridor of northwest China was one of the earliest centers for long-distance culture exchange in the prehistoric world. The timing and sequence of cultural changes in this area remains poorly understood resulting from the lack of radiometric age control. This paper presents a refined radiocarbon (14C) chronology to resolve the timing of human occupation and cultural evolution in the Hexi Corridor. Radiocarbon dating of crop remains, which have an annual life cycle, has the advantage of eliminating problems such as the carbon stored in 'old wood'. As a result, 14C dates from crop remains are used to test the validity of the 14C dates derived from charcoal, bone and plant remains. The resultant database of ages is modelled using the Bayesian approach. The updated chronology presented in this paper shows generally good agreement with the original dates used to constrain cultural evolution in the Hexi Corridor. However, the occupation of the corridor by the Shajing and Shanma Late Bronze Age-Early Iron Age cultures appears to have taken place ~300 years later than previously thought. On the basis of comparing this updated chronology of cultural evolution with palaeoclimatic and historical records, it is proposed that the collapse of the Shajing and Shanma cultures occurred as a result of geopolitical impact rather than climate change. [ABSTRACT FROM AUTHOR]

Green transformation of energy use in China's transport sector will promote sustainable development in the country. This paper extends the Bounded-adjusted Measure and Luenberger indicators to detect the performance of China's inland transport sector across 2006–2015. In the framework, the climate change and traffic accident risks are taken as undesirable outputs. In addition, source-specific and variable-specific decomposition are proposed for investigating the sources of inefficiency and productivity, and quantifying the contributions of climate change and traffic accident risks. This paper opens up the "black box" of technological progress, identifying the different channels (i.e., quantity and time-dimensions) through which affect economic growth. Therefore, policymakers can find out the most effective pathway to boost productivity growth and mitigate climate change and traffic accident risks in the transport sector, which are ignored in the conventional framework. Empirical results indicate great variances exist among 30 provinces in inefficiency scores, productivity change, and technological progress. Hence, classified regulations help to tackle this issue. We clustered 30 provinces into 4 groups according to their technological progress along quantity and time-dimensions. Variable-wise, CO2 emission-reduction and civil vehicle gains promote the TFP gains most. Also, we verify that economic development and environmental regulations can coordinate to promote the sustainable development of the transport sector. [ABSTRACT FROM AUTHOR]

The purpose of this article is to investigate the new driving forces behind China's green energy and further assess the impact of green energy on climate change. The existing literature has used linear methods to investigate green energy, ignoring the non-linear relationships between economic variables. The nonparametric models can accurately simulate nonlinear relationships between economic variables. This paper constructs a nonparametric additive model and uses it to explore green energy. The empirical results show that the impact of green finance on green energy is more prominent in the later stage (a U-shaped impact). Fiscal decentralization also exerts a positive U-shaped impact, meaning that expanding local fiscal autonomy has contributed to green energy growth in the later stage. Similarly, the impact of oil prices and foreign direct investment demonstrates a positive U-shaped pattern. However, the nonlinear impact of environmental pressure displays an inverted U-shaped pattern. Furthermore, this article explores the impact of green energy on climate change and its impact mechanisms. The results exhibit green energy generates a positive U-shaped impact on climate change, meaning that the role of green energy in mitigating climate change gradually becomes prominent over time. Mechanism analysis exhibits that industrial structure and energy structure both produce a nonlinear influence on climate change. [ABSTRACT FROM AUTHOR]

China is the largest carbon emitter in the world. Understanding carbon emissions of China, especially at the provincial level, will help identify the critical factors behind carbon emissions and effectively implement carbon emission reduction measures. There are significant achievements in the study of carbon emissions of China's provinces. However, there is a gap for improvement in the study from periods and groups' perspectives using a decomposition-clustering method. This paper adopts the Logarithmic Mean Divisia Index (LMDI) to decompose each province's carbon emissions, introduces the elbow and K-means methods to cluster provinces based on the driving factors of decomposition, and analyzes the driving factors of carbon emissions from the view of groups and periods. By analyzing the carbon emissions data of 28 provinces in China from 1998 to 2018, a breakthrough has been found that economic activities and energy intensity were the main driving factors of carbon emissions. Some possible countermeasures, such as optimizing the industrial structure and the energy structure, significantly increasing clean energy consumption, would receive effective carbon emission reduction feedback. The results provide better decision-making support for emission reduction policies in China and contribute to global climate change issues. [ABSTRACT FROM AUTHOR]

Blue-green algae (CyanoHABs), photosynthetic bacteria that create a harmful aquatic environment, have been a trending issue on Taihu for over a decade. CyanoHABs adapt to varying climatic changes, which explains why the problem on Taihu still thrives. One major drive that keeps the algae is Sediment Oxygen Demand (SOD). In this paper, seasonal and spatial variations of SOD that contribute immensely to nutrient growth in Lake Taihu were done using the Environmental Fluid Dynamics Code (EFDC). The results were analyzed based on Nitrogenous SOD (NSOD) and Total SOD (TSOD). Summer results ranged from − 0.05754 to − 0.0826 (− 0.75658 to − 0.83902) (g/m2/day) and Winter values ranged from − 0.3022 to − 0.40171 (− 1.34486 to − 1.48856) (g/m2/day) indicate a gradual decrease in NSOD (TSOD) values respectively. Relatively higher values in summer are attributed to warmer surface water which sets up thermal stratification to increase the internal loading of nitrogen. Lower winter values are related to inverse stratification, where lower oxygen concentration decreases the SOD to trigger ammonium accumulation in the water column. NSOD (TSOD) values for Autumn results ranged from − 0.1039 to − 0.24786 (− 0.96251 to − 1.39454) (g/m2/day) and Spring values of − 0.43019 to − 0.35959 (− 1.48297 to − 0.54089) (g/m2/day). Transition seasons (i.e., Autumn and Spring) results are impacted by wind mixing that allows dissolved oxygen and nutrients in the whole water column. However, spring values depict a gradual increase in SOD value attributed to spring turnover and gradual stratification, which decrease nutrient concentration. In contrast, decreasing SOD values in autumn are related to mixing, but temperature decreases tend to increase nutrient concentrations. Carbonaceous sediment oxygen demand (CSOD), due to sulfide oxidation, presents high values from the difference between TSOD and NSOD. Based on the high values of CSOD, it is highly recommended that more research on eutrophic Taihu lakes would consider delving into CSOD. [ABSTRACT FROM AUTHOR]

Since the early 2000s, China has carried out extensive "grain-for-green" and grazing exclusion practices to combat desertification in the desertification-prone region (DPR). However, the environmental and socioeconomic impacts of these practices remain unclear. We quantify and compare the changes in fractional vegetation cover (FVC) with economic and population data in the DPR before and after the implementation of these environmental programmes. Here we show that climatic change and CO2 fertilization are relatively strong drivers of vegetation rehabilitation from 2001-2020 in the DPR, and the declines in the direct incomes of farmers and herders caused by ecological practices exceed the subsidies provided by governments. To minimize economic hardship, enhance food security, and improve the returns on policy investments in the DPR, China needs to adapt its environmental programmes to address the potential impacts of future climate change and create positive synergies to combat desertification and improve the economy in this region. This paper shows that desertification combating practices decline incomes of farmers and herders, and China needs to adapt its ecological programmes to address the impacts of climate change and create positive synergies to combat desertification. [ABSTRACT FROM AUTHOR]

Financial activity plays an important role in the analysis of environmental and ecological implications. Previous research shows that shadow banking activities, informal and less regulated financial activities, have become an important part of financial systems after the 2008 financial crisis. However, the impact of shadow banking activities on carbon dioxide emissions has been ignored in previous research. In this paper, we use the panel annual data of 30 Chinese provinces over the period 2013–2020 to study the effect of shadow banking activities on carbon dioxide emissions. The result shows that shadow banking activities have a positive impact on carbon dioxide emissions, and the result is still robust by using dynamic panel regression with general method of moments (GMM) method. Heterogeneity analysis shows that the impact of shadow banking activities on carbon emissions is more pronounced for the secondary industry, which proves that shadow banking activities support more for environmentally unfriendly businesses. Furthermore, by using difference-in-difference (DiD) method, we examine the causal effect of shadow banking regulation policy on carbon dioxide emission reduction and demonstrate that the shadow banking regulation can reduce carbon dioxide emissions. Our research contributes to environment protection and achieving the goal of low-carbon economy by exploring the role of shadow banking activities and financial regulation in carbon dioxide reduction. [ABSTRACT FROM AUTHOR]

Water use efficiency (WUE) is an important link between carbon and water cycles, which is critical for the forests under future global climatic changes. WUENDVI was calculated by accumulated normalized difference vegetation index (NDVI) and actual evapotranspiration (ET) and could reflect the impacts of climatic changes and human activities on WUE. The three forestry regions of China are the northeast, southwest, and southeast areas. Among them, the northeast forest region is a natural forest region with forest stock accounting for more than 1/4 of China, and the southwest mountainous forest region is another natural forest region in China, with forest stock accounting for more than 1/3 of China, while the southeast forest area is mainly plantations. In 2018, the forest areas over three forestry regions of China were around 1,725,988 km2. This paper evaluated the changes in forest WUE and their relationships with climatic change and human activities over three forestry regions of China during 1961–2019. The main findings of this study were summarized as follows: (1) the spatial changes of WUE were gentle in the artificial forest region but fluctuant sharply in the natural forest regions. In the southwest forest region, the WUE increased with elevation, while it showed the opposite trends in the artificial forest region. Overall, the annual mean forest WUE increased in almost all regions of the study areas during 1961-2019; (2) in the northeast and southeast forest regions, the WUE presented a negative relationship with the temperature. In the southwest forest region, the WUE was positively correlated with the temperature and its increase rate slowed down significantly when the temperature increases by more than 1 °C. The WUE was negatively correlated with precipitation in the three regions and was more sensitive to the decrease of precipitation. The sensitivity of WUE to precipitation reduction was highest in the artificial forest region and lowest in the northeast forest region; (3) the forest WUE and WUENDVI were lowest in the artificial forest region but highest in the northeast forest region, while the net increase in forests area during 1980–2018 was largest in the artificial forest region (155,975 km2) but lowest in the northeast forest region (78,766 km2). In general, human activities had the greatest impact on the forest WUE in the northeast forest region. Human activities and climatic change had quite complex and interactive effects on forest WUE. Therefore, more attention should be paid to the joint influences of climate change and human activities on WUE. [ABSTRACT FROM AUTHOR]

Increasing carbon productivity is an important measure taken by China to deal with global climate change, and technological innovation is the fundamental way to promote industrial carbon productivity. To explore the low-carbon effects of technological innovation, based on the panel data of 30 provinces in China from 2009 to 2017, this paper established a spatial panel measurement model and a panel threshold regression model to explore the spatial spillover effects and threshold characteristics of technological innovation on industrial carbon productivity. The research shows the following: on the one hand, technological innovation and industrial carbon productivity each has obvious spatial correlation, and technological innovation has a significant spatial spillover effect on the improvement of industrial carbon productivity, and the indirect spillover between regions is greater than the direct spillover effect within the area. On the other hand, the impact of technological innovation on industrial carbon productivity has a double threshold effect. With the continuous improvement of technological innovation capabilities, the promotion of industrial carbon productivity has become increasingly more influential. Through the division of threshold values, the technological innovation capabilities of various regions in China are significantly heterogeneous, and the overall level is low. Although technological innovation capabilities have improved in recent years, there is still much room for improvement. Finally, this article puts forward relevant suggestions from the construction of regional technological innovation system, economical green circular development, and the establishment of a green technological innovation system. [ABSTRACT FROM AUTHOR]

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb–Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb–Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions. [ABSTRACT FROM AUTHOR]

The carbon mitigation response encompasses a variety of strategies aimed at mitigating greenhouse gas emissions resulting from human activities. These measures are crafted to address the challenges posed by climate change and facilitate the transition of businesses towards a low-carbon paradigm. Leveraging the analytical outcomes of the extended STIRPAT model and the PSO-BP prediction model, this paper suggests countermeasures for reducing carbon emissions in China's metal smelting industry. The overarching objective is to contribute to China's attainment of the "dual carbon objectives." The study identifies key factors influencing carbon emissions in the metal smelting industry, ranked in descending order of sensitivity: population, coal consumption, urbanization rate, total metal production, carbon intensity, proportion of secondary industry, and GDP per capita. Results from three established scenarios—namely, low carbon, standard, and high carbon—indicate a consistent decline in carbon emissions from China's metal smelting industry over the next 15 years. This research not only enhances the findings of existing studies on carbon emissions in the metal smelting sector but also introduces an innovative approach to carbon emission reduction within China's metal smelting industry. [ABSTRACT FROM AUTHOR]

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

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

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