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Climate change is the dominant factor affecting the hydrological process, it is of great significance to simulate and predict its influence on water resources management, socio-economic activities, and sustainable development in the future. In this paper, the Xiying River Basin was taken as the study area, China Atmospheric Assimilation Driven Data Set (CMADS) and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters. On this basis, runoff change of the basin under the future climate scenario of CMIP6 was predicted. Our research shows that: (1) The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17% and 10.83%, respectively. Climate change is the most important factor affecting runoff change of the Xiying River. (2) In these three different emission scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6 climate model, the average temperature increased by 0.61, 1.09 and 1.74 °C, respectively, in the Xiying River Basin from 2017 to 2050. Average precipitation increased by 14.36, 66.88, and 142.73 mm, respectively, and runoff increased by 15, 24, and 35 million m³, respectively. The effect of climate change on runoff will continue to deepen in the future. [ABSTRACT FROM AUTHOR]

Climate change is considered one of the major systemic risks facing the world in the 21st century. To address climate change, China has adopted a series of climate policies, but the uncertainty brought about by frequent climate policy issuance has increased pressure on enterprises, which may not be conducive to enterprises reducing emissions. This paper uses data on 1211 listed companies on the A-share market in China from 2012 to 2022 to study the impact of climate policy uncertainty on enterprise pollutant emissions. The research findings show that climate policy uncertainty increases corporate pollution emissions; climate policy uncertainty mainly generates negative impacts on enterprise environmental regulation, social responsibility, and R&D investment, thereby negatively affecting enterprise emissions reduction. Further heterogeneity analysis shows that climate policy uncertainty in China has a more significant impact on non-state-owned enterprises, technology-intensive enterprises, lightly polluting enterprises, and enterprises in western regions. These findings emphasize the importance of enterprise social responsibility, environmental regulation, and R&D investment in enterprise emissions reduction and provide policy implications for Chinese enterprises to optimize their energy-saving and emission reduction strategies in the face of climate policy uncertainty. • We investigate the correlation between uncertainty in climate policy and the corporate pollution emissions. • We utilized an extensive dataset comprising publicly listed Chinese firms spanning the period from 2012 to 2022. • Climate policy uncertainty negatively impacts corporate environmental regulation, social responsibility, and R&D investment. [ABSTRACT FROM AUTHOR]

Increased temperature and carbon dioxide concentration caused by climate change will aggravate the creep shrinkage and structural durability of concrete bridges. Overloading also has a great impact on the time-dependent reliability of existing bridges. This research paper analyses the time-dependent reliability of bridges based on climate change and overload. By improving the concrete carbonation model and referring to the B4 model of concrete creep, the effects of ambient temperature and humidity on concrete under different emission-reduction scenarios were considered. At the same time, given the serious problems of vehicle overload in China, combining different overload scenarios with climate change led to the establishment of a time-dependent reliability model for precast-concrete bridges. The results showed that as the overload rate increased, the time-dependent reliability degradation rate of a case study bridge accelerated. Under the scenario considering both high greenhouse gas emissions and the maximum overload rate, the service life of the case study bridge decreased to 50% of its design life. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

The majority of the total greenhouse gas (GHG) emissions in China are energy-related. Thus, full understanding of energy-related GHG emissions is crucial for local governments to establish a baseline for tracking emission trends and developing mitigation strategies. In this paper, we present a survey-based GHG emission accounting method for sectoral energy consumption and apply it in Xiaolan, a typical town of Zhongshan. The method combines scope and sectoral analyses on the basis of local statistical approach, and pays more attention to data collection process. Scenarios of core findings in the study are list as below: (1) The energy-related GHG emissions of Xiaolan in 2010 was 2,072,444 tons of carbon dioxide equivalents (CO 2 e). Of this, 31.83% was Scope 1 emissions (direct emissions) and 68.17% was Scope 2 emissions (indirect emissions); (2) Emissions from “manufacturing”, “residents”, and “power, gas & water production and supply” made up 90.27%, among which, “manufacturing” represents the biggest emitting sector as 69.09%; (3) In 2010, the per capita GHG emissions was lower than that in most of the other Chinese cities, but higher than several Asian cities including Amman and Tokyo. Some strategic approaches to reduce GHG emissions were proposed: (1) save energy and improve energy efficiency; (2) optimize energy structure and develop low-carbon energy; (3) update manufacturing structure; (4) improve GHG emission management for the resident sector. Finally, we identified a number of key research issues to advance the town level GHG emission method for future research needs. This paper provides a useful method to understand and profile GHG emissions for towns. [ABSTRACT FROM AUTHOR]

The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today's 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a "no-regret option" in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits. [ABSTRACT FROM AUTHOR]

This paper examines China's policy and position in relation to the evolving climate change negotiations in order to explain how China is dealing with the dilemma of meeting its growing development needs while reducing GHG emissions. It argues that global climate governance requires steering and leadership to deal with the interlocked political process; that the developing countries (DCS) right to develop is challenged by the need for ecosystemic standards especially as climate change is seen as a zero-sum game as the more one country emits the less another one can. This is especially problematic as Industrialized countries (ICS) appear to be both unwilling and unable to increase growth without increasing emissions. This explains China's policy of insisting on its right to develop, of demanding that ics reduce their emissions and that they fulfil their obligations under the FCCC, while expressing its willingness to take on a voluntary target. The paper argues that China's state-led transition has eight unique characteristics that may allow it to lead as it moves beyond a no-regrets policy to a circular and green economy, cooperating with other DCS and mobilizing conscious green values in citizens. The question remains--will the initial success and scale of state-led transition lead the global green transition to a sustainable world? [ABSTRACT FROM AUTHOR]

Alleviating global climate change requires the development and adoption of green innovation. This study compares the impact of cooperative and independent green innovation on carbon reduction based on the panel data covering 252 cities in China from 2003 to 2019. We examine the heterogeneous impacts of cooperative green innovation across units, and explain the transmission mechanism. The two-way fixed effects model and interaction model are adopted. Results show that: (1) Cooperative green innovation can reduce carbon emissions more effectively than independent green innovation. A 1% increase in cooperative green patents (inventions) will reduce carbon emissions by 0.023% (0.037%), while independent green patents or inventions play a weak role. (2) For research and development (R&D) partners, firms' cooperative green innovation has a stronger positive effect on carbon reduction than research organizations. The carbon reduction effect of cooperative green innovation is better for listed firms and universities. (3) Mechanism analysis shows cooperative green innovation can reduce carbon emissions by improving the industrial structure and decreasing energy intensity. These effects are stronger when cities have more talent, funds and higher marketability. (4) We also find that listed firms' cooperative green inventions with a ten-year lag can still reduce carbon emissions effectively. Cooperative green innovation is conducive to carbon reduction among eastern and central cities of China. [Display omitted] • This paper explores the impact of green innovation on carbon reduction from the new perspective of cooperation. • Cooperative green innovation is more effective than independent green innovation in carbon reduction. • Cooperative green innovation of listed firms and universities is more conducive to carbon reduction. • Cooperative green innovation can optimize the industrial structure and decrease energy intensity for better carbon reduction. • Cooperative green innovation with more talent, funds and market has better carbon reduction effect. [ABSTRACT FROM AUTHOR]

China has a large economic and demographic exposure to extreme events that is increasing rapidly due to its fast development, and climate change may further aggravate the situation. This paper investigates China's socioeconomic risk from extreme events under climate change over the next few decades with a focus on sub-national heterogeneity. The empirical relationships between socioeconomic damages and their determinants are identified using a hierarchical Bayesian approach, and are used to estimate future damages as well as associated uncertainty bounds given specified climate and development scenarios. Considering projected changes in exposure, we find that the southwest and central regions and Hainan Island of China are likely to have a larger percentage of population at risk, while most of the southwest and central regions could generally have higher economic losses. Finally, the analysis suggests that increasing income can significantly decrease the number of people affected by extremes. [ABSTRACT FROM AUTHOR]

The issue of climate change has become an increasing concern for the international community. At the same time, climate change and, particularly, global warming affects the amount of energy required in China and the structure of this demand, thereby influencing the amount of CO 2 (carbon dioxide) emissions produced. To investigate the possible influence of climate change on China's CO 2 emissions, this paper utilizes the degree-day method to calculate the heating degree days (HDD) and cooling degree days (CDD) in 29 provinces in China from 1995 to 2011. A series of appropriate econometric models are subsequently estimated to measure the impact of climate change on CO 2 emissions per capita. To enhance the explanatory power of the estimation results, several indicators, such as income per capita, industry structure, urbanization rate and population density, are incorporated in the estimation equations as control variables. The estimation results indicate that the feedback effect of climate change on China's carbon emissions is statistically significant but not large in magnitude. During the sample period between 1995 and 2011, approximately 1.687% of China's increased total CO 2 emissions could be attributed to climate change. Moreover, the impacts of climate change on different regions of China are notably different. For example, the influence of HDD on CO 2 emissions per capita are most significant in the middle and southern regions, while the impacts of CDD are most significant in the eastern and northern regions. However, there is no obvious evidence that climate change has affected CO 2 emissions in the western region. [ABSTRACT FROM AUTHOR]

This paper assesses how the Paris Agreement on climate change affects China and India. Taking a TWAIL (third-world approaches to international law) approach, it argues that patterns of exploitation are repeated in different fields. The UNFCCC required developed countries to reduce their emissions before developing countries would be required to do so. While some developed countries are keeping to their side of the bargain, others are failing to do so. Nevertheless, China and India have accepted an agreement with targets for all countries which requires considerable sacrifices in the energy field but possible gains in the water field. While both countries have agreed to reduce the rate of growth of their emissions, they have high expectations of climate finance, which are unlikely to be fulfilled. Their commitments require major changes to national policy, scarcely the sort of tinkering that the no-regrets policy in India has achieved. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions in China and India have been increasing rapidly over the last decade. Scenario studies can provide insight into expected future trends and the emission reduction potential in these regions. The scenarios show that growing population, gross domestic product, and energy demand are likely to lead to a further increase in emissions. At the same time, a decreasing emission intensity would still allow to create decarbonization scenarios in line with the requirements for reaching a maximal warming of 2 °C. There is, however, a wide range of assumptions across these studies. Based on the literature review, this paper observes that key assumptions in scenarios developed by national institutes in China and India differ from those presented by international studies or modeling teams. We explore how this-and other factors like data availability-may influence the interpretation of the scenarios and how international and national modeling groups could learn from each other. Our main recommendation is for more extensive collaboration between national and international research groups, so that national and international scenario studies can be compared in more detail in order to support international negotiations. [ABSTRACT FROM AUTHOR]

Natural wetlands are among the most important sources of methane; thus, these areas are important for better understanding long-term temporal variations in atmospheric methane concentration. During the last 60 years, wetlands have experienced extensive conversion and global impacts from climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we present a modeling framework, integrating CH4MODWETLAND, TOPMODEL and TEM models, to analyze the temporal and spatial variations in CH4 emissions from natural wetlands (including inland wetlands, coastal wetlands, lakes and rivers) in China. Our analysis revealed an increase of 25.5 %, averaging 0.52g m-2 per decade, in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Higher rates of increasing CH4 fluxes occurred in northeastern, northern and northwestern China, associated with large temperature increases. However, decreases in precipitation due to climate warming o_set the increase in CH4 fluxes in these regions. The CH4 fluxes from the wetland on the Qinghai Tibetan Plateau exhibited a lower rate of increase, which was approximately 25% of that simulated in northeastern China. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91-2.81 Tg), i.e., from 4.50 Tg in the early 1950s to 2.15 Tg in the late 2000s, due to a large wetland loss of 17.0 million ha. Of this reduction, 0.26 Tg 0.24-0.28 Tg) was derived from lakes and rivers, 0.16 Tg (0.13-0.20 Tg) from coastal wetlands, and 1.92 Tg (1.54-2.33 Tg) from inland wetlands. Northeastern China had the largest contribution to this reduction, with a loss of 1.68 Tg. The CH4 emissions were reduced by more than half in most regions in China except for the Qinghai Tibetan Plateau, where only a 23.3% decrease in CH4 was observed. [ABSTRACT FROM AUTHOR]

At the Conference of the Parties held in Copenhagen in 2009 (COP15), the Chinese government announced its 2020 commitment to reduce the carbon intensity of the Chinese economy to 40–45% of its 2005 level. A number of analysts have criticised this target, indicating that these reductions can be achieved without the implementation of any active climate change policy. In this paper, we test this argument using a combined input–output based econometric projection approach and the World Input–Output Database (WIOD). Our results show that the projected carbon intensity for 2020 is likely to be 50% lower than the carbon intensity of 2005, without additional active climate change policy measures performed by the Chinese government. On top of it, our study indicates that the total volume of CO 2 emissions would be by 2020 seven times the volume of the year 2005. [ABSTRACT FROM AUTHOR]

Transportation industry accounts for the majority of air pollutant emission, which is one of the leading factors of climate change. Many vehicle emission models have been proposed focusing on emission factors to study the pollutant emission issue. However, little research has been done in China on emission models, though China is a major air pollutant-emitting country. This paper first introduces two emission models- MOBILE model and MOVES model, then proposes model selection methods including AIC (Akaike information criterion) and BIC (Bayesian information criterion) to compare and select the better model which could be applied in China. Experimental results show that the value of AIC and BIC for MOVES model is significantly lower than MOBILE model, which implies that MOVES model has better performance on real data fitness and prediction. Our experimental findings may be useful for future research on air pollutant emission modelling in China. [ABSTRACT FROM AUTHOR]