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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 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]

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]

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 most significant global challenge is global climate change; carbon emission reduction and carbon neutralization are the last way to solve global climate change. Achieving carbon neutrality will significantly impact the global economy and the national economy. The "dual carbon goals" proposed by China will also substantially impact the global economy and regional economic development. Focusing on regional economic development, achieving carbon neutrality is not only an opportunity for regional economic development but also a challenge. To achieve the goal of carbon neutrality, there must be institutional innovation and management innovation, which will provide new opportunities for balanced development among regions. With the development of inclusive finance, financial services for many disadvantaged groups and small and medium-sized enterprises have been further developed, thereby promoting economic development. With the development of Internet finance, big data, cloud computing, and other technologies, the development of inclusive finance, etc., the concept has also emerged. However, due to the short time of digital financial inclusion, the imperfect regulatory system, and the low degree of public participation, it is worth investigating whether the development of digital financial inclusion has a catalytic effect on the improvement of economic growth. Using the data of 31 provinces to build a panel regression model, this paper studies the market development, the development degree of digital financial inclusion, and the impact of digital financial inclusion on the relationship between factor markets and product markets and regions from the perspective of factor markets and product markets. [ABSTRACT FROM AUTHOR]

Carbon intensity is one of the key indexes in the process of decarbonizing development. Therefore, our paper investigates possible pathways of China's carbon intensity to 2050 depending on China's development stage and trends. We first investigate the major influence factors of carbon intensity based on the Kaya identity, and then forecast China's future carbon intensity with a generalized regression neural network model coupled with a scenario analysis with official data from 1978 to 2020. Our results show that: (1) China's carbon intensity will decrease under the benchmark growth, high growth, and low growth scenarios but vary by amounts and rates of decrease due to the settings of the influences factors; (2) China is able to achieve the reduction targets of 2025 under the benchmark growth and low growth scenario, but cannot achieve the target under the high grow scenario. However, China can meet its reduction target by 2030 in all scenarios. (3) The Chinese government should aim to reduce carbon intensity by 23–25%, 40–44% and 64–70% by 2035, 2040 and 2050 as compared to the level in 2030. Therefore, China should keep promoting the deep low-carbon transformation of economic development model, and realize high-quality economic development in order to achieve these objectives. [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]

The abnormity of climate change poses environmental concerns and indirectly promotes the development of low-carbon economic growth pattern. Climate change mitigation technology innovations contribute significantly to achieve environmental goals in China, and thus, technological cooperation has become a strategic choice for the Chinese provinces to achieve technological breakthroughs. Based on 3, 280, 808 patents, this study uses social network analysis (SNA) method and similarity measurement to discuss the evolution process and structural features of the spatial correlation network to analyze the patent data from 1985 to 2020. The process for the research is as follows. First, a form solution of the correlation problem to calculate the minimum Euclidean distance is available in the field of social network. Second, the European distance is used to measure the similarity between provinces, and then, SNA is used to construct the spatial correlation network. Finally, the similarity of growth trend of provincial patent applications in different years from a nonlinear perspective is described, so as to calculate the potential provincial linkage strength. The results demonstrate that low-carbon technology innovation in China takes the form of a network structure. The network exhibits significant characteristics of regional agglomeration, and several central provinces exert the role of mediation and transmission, such as Tianjin, Hubei, and Henan. The study contributes by illustrating the current situation of green technology innovation and provides a critical theoretical foundation for the government when formulating future low-carbon economy development policies. [ABSTRACT FROM AUTHOR]

Under the background of the gradual scarcity of terrestrial resources and the increasingly fierce competition for global marine resources, the task of green development of marine economy and green transformation of marine industry is imminent. Carbon finance is a product of low-carbon economic development and a derivative of green finance. It is an effective way to alleviate the global climate crisis and promote the transformation of the global economy to a low-carbon economy to achieve sustainable development. Studying the mechanism of carbon finance on the development of marine economy will help to grasp the influencing factors of the green transformation of the marine industry in an all-round way, better promote the sustainable development of China's marine economy, and realize the strategy of marine power at an early date. Based on this, this paper selects China's data from 2006 to 2020, and uses the AHP-entropy method to select 26 indicators from five levels: economic growth, energy conservation and emission reduction, marine ecology, structural adjustment and scientific and technological innovation to construct a comprehensive evaluation index system for the green transformation of China's marine industry. Based on the PLSR model, the impact of carbon finance on the green transformation of China's marine industry is empirically analyzed, and the results show that: (1) The comprehensive score of China's marine industry green transformation from 2006 to 2020 fluctuates and rises: from 2006 to 2009, the comprehensive score of China's marine industry green transformation is low, and the transformation effect is not obvious. From 2009 to 2012, the comprehensive score of green transformation of the marine industry improved significantly. From 2012 to 2018, the comprehensive score of China's marine industry green transformation fluctuated little and showed a slow growth trend, while China's marine economic transformation grew steadily at a low speed. In 2019–2020, due to the impact of the epidemic, the speed of transformation has decreased again. (2) The carbon ratio and the green credit balance of commercial banks have a role in promoting the green transformation of China's marine industry, while the carbon trading volume and carbon intensity have a restraining effect on the green transformation of China's marine industry. From the perspective of effect, carbon intensity has the strongest effect, followed by carbon ratio, carbon trading volume is slightly weaker, and the role of green credit balance of commercial banks is the weakest. Based on the research conclusions, relevant policy recommendations were put forward. [ABSTRACT FROM AUTHOR]

Multi-level governance (MLG) theory has become the main explanation for how climate action is realized in polycentric, multi-sector, multi-actor policy landscapes. In this paper, we examine processes of climate change governance in a given city in China, Rizhao, and evaluate how MLG arrangements operate. We do so by examining primary data collected through in-depth interviews with local stakeholders. Our results show that the focus on multi-level – and in particular transnational – interactions obscures the ways in which urban low carbon transitions happen in three ways. First, in spite of Rizhao being a well-known case in environmental politics, there is an absence of international actors and non-governmental organizations operating on the ground. Second, the emphasis on opportunities of local authorities to build political agendas through participation in global networks conceals how structures of power, political-economic coalitions, and technological practices are firmly fixed in a local context. Third, the case study illustrates the enduring authority of formal top-down channels of control in this political system. Based on these results, we caution against the uncritical application of MLG theory to environmental politics in settings where deliberative democracy is lacking and the full benefits of multi-level interactions are unlikely to be achieved. [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]

Environmental problems caused by carbon emissions have negative impacts on human life and society. It is therefore important to identify potential approaches to carbon emission reduction. In this study, we analyze the impact fiscal expenditure on science and technology has on carbon emissions using a panel dataset from 2007 to 2016 at Chinese provincial levels. An instrumental variable approach is employed to address the potential endogeneity of fiscal expenditure. Our results show that fiscal expenditure on science and technology has a significant and negative effect on carbon emissions by improving green innovation, economic structure upgrade, energy consumption structure, and energy efficiency. A one hundred RMB yuan increase in fiscal expenditure on science and technology would lower carbon emissions by 0.654 tons. Heterogeneity analysis reveals that the carbon reduction effects of fiscal expenditure on science and technology are larger in regions where internet coverage and the share of industry in the economy are high. Our results highlight the significant role of fiscal expenditure on science and technology in carbon reduction. [ABSTRACT FROM AUTHOR]

To mitigate the detrimental effects of climate change exacerbated by excessive carbon emissions, China has introduced a series of environmental regulations designed to promote low-carbon technology diffusion among enterprises. The existing literature ignores the heterogeneity of the scales of enterprises, making it extremely difficult to put forward targeted policies for enterprises of different scales. In this study, we employ a complex network-based evolutionary game approach to analyze the effect of environmental regulations on the diffusion of low-carbon technology, and thereby determine the relationship between the degree of diffusion and the strength of regulations at different scales of enterprise. The results revealed that with respect to the degree of diffusion, there are significant differences in the sensitivity of enterprises in 20- and 100-scale networks to the imposition of three types of environmental regulation (innovation subsidy, carbon tax, and punishment). When the scale of the network is fixed, fluctuation in the change in degree becomes larger, and even irregular, with an increase in enterprise scale. With an increase in network scale for small, medium, and large enterprises, the range of variation in the degree of diffusion becomes smaller. In small, medium, and large enterprises, when the scale of the network increases from 20 to 100, the degree of diffusion will increase in response to the same strength of innovation subsidy, carbon tax, and punishment. With an increase in innovation subsidies, the diffusion degree of large enterprises will improve slightly. Moreover, for large enterprises, increasing the strength of punishment has no obvious effects with regards to improving the degree of diffusion. At all scales of enterprise, in both the 20- and 100-sacle networks, the degree of diffusion will increase with an increase in the strength of the carbon tax. [ABSTRACT FROM AUTHOR]

Climate change caused by carbon emissions has a strong influence on the economy and human society. Though numerous previous studies have emphasized the importance of low-carbon innovation on curbing or mitigating carbon emissions, not much attention has been given to the reverse effect. We used a panel of 285 Chinese prefecture-level cities from 2005 to 2016 and Cooperative Patent Classification (CPC)-Y02 patents as low-carbon innovation indicators. The results show that the increasing carbon emissions accelerate cities' low-carbon innovation in China, and the predicted effect varies across low-carbon innovation types. As carbon emissions rise, more low-carbon innovation will occur in activities with higher carbon emissions. Besides, we explore environmental awareness as the mediation channel for carbon emissions to impact low-carbon innovation. With the help of media, government, and enterprises, the growing carbon emissions promote public environmental awareness and change consumers' behaviors, motivating companies to speed up low-carbon innovation. [ABSTRACT FROM AUTHOR]