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We try to expand the political promotion tournaments in Chinese local governments from raising GDP to the level of increasing fiscal revenues. From the vantage point of officials' performance appraisal, we investigate the impact of local government officials' political ambitions, represented by the ex-ante commitment level of fiscal revenue targets, on carbon emission intensity (CEI). Utilizing a sample of 209 prefecture-level cities in China spanning 2006 to 2019, this paper empirically scrutinizes the influence of local government political ambition on CEI. The findings reveal that the greater the political ambition of local government officials, the more pronounced the reduction in CEI. Furthermore, our study demonstrates that political ambition contributes to the decline of CEI by elevating the levels of environmental attention and green innovation. This research not only aids in comprehending the rationale and necessity of the political promotion tournaments implemented by the Chinese central government but also offers valuable insights for other developing countries seeking to mitigate CEI. [ABSTRACT FROM AUTHOR]

Although the carbon reduction role of green finance has been highlighted in the context of global warming, discussions on green finance have primarily focused on size rather than structure. Based on Chinese panel data from 2008 to 2019, this paper distinguishes itself by investigating the relationship between green financial structures and carbon emission intensity from a structural matching perspective using the two-way fixed effect model, system generalized method of moments model, quantile regression, and the mediating effect model. Our findings indicate that a green financial structure can lower overall carbon emission intensity and that an inverted U-shaped carbon emission mitigation effect results from a green financial structure. Additionally, green financial structures alleviate carbon emission intensity by facilitating the development of energy technology. Furthermore, greater degrees of finance-technology matching effectively lower carbon emission intensity. These findings provide lessons for countries striving to construct comprehensive and reasonable green financial systems to address climate change. [ABSTRACT FROM AUTHOR]

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO 2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO 2 equivalent (MMT CO 2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions. [Display omitted] • The coal-to-clean-energy policy in rural areas has a positive climate benefit. • Priority should be given to replacing coal with natural gas in policy execution. • Heating and cooking with electricity will maximize climate benefits from 2038. • Climate impact caused by CH 4 emission during the energy lifecycle can't be ignored. [ABSTRACT FROM AUTHOR]

The vigorous development of the digital economy (DIEC) offers a substantial potential for China and global economies to realize the goal of "double carbon". This study attempts to analyze the heterogeneous effect of DIEC on carbon emission reduction (CERE), in order to extend a valuable reference for effectively achieving the dual-carbon goal. Accordingly, the effect of DIEC on carbon emission scale (CESC) and carbon emission intensity (CEIN) are examined in this paper by using dual fixed effect model and intermediate effect model, respectively. The study findings show that, at first, DIEC significantly supports the CERE while significantly constraining the uplift in CESC and CEIN. Simultaneously, the CERE effect of DIEC contains digital economy dimensional heterogeneity, industry heterogeneity, production and life heterogeneity, and urban-rural heterogeneity. Finally, the DIEC boosts the technological innovation (TEIN) and residents' income (REIN) levels, in order to heighten the CERE. Further, improving invention technology innovation and TEIN is more conducive to catalyzing the reduction of carbon emission in the whole society and the production field. Conversely, the improvement of non-invention technology innovation and rural- and urban residents' income impedes CERE in the field of life. Thus, the implications of this study are of vital significance for China and the rest of the world to foster CERE and achieve the "dual carbon" goal through DIEC development. [ABSTRACT FROM AUTHOR]

Controlling carbon emissions and sustaining growth constitute essential concerns in the post-financial crisis era combined with low-carbon sustainable development. However, the impact of financial development on carbon emissions remains controversial and lacks mechanisms investigation covering finance spatial attributes. Relying on China province's data during 2005–2019, this paper contributes to the literature by constructing multi-spatial models to investigate how financial geo-density mitigates carbon emission intensity and explore the spatial transmission mechanisms. The results reveal that there is a balance between financial geo-density and carbon emission intensity. The intrinsic mechanisms include: (1) raising financial geo-density is accompanied by the law of marginal diminishing carbon emission intensity tendency; (2) high financial geo-density accelerates technological innovation and industrial structure upgrading, thereby decreasing carbon emission intensity, but drives industrial-scale expansion, thereby increasing carbon emission intensity; and (3) financial institution competition and inter-industry linkage notably influence the relationship between financial geo-density and carbon emission intensity, promoting the emission reduction effect of financial geo-density in accelerating technological innovation and industrial structure upgrading, and suppressing the emission increase effect of financial geo-density in driving industrial expansion. Our findings provide new insights for developing systemic emission reduction policies for employing financial sectors as catch-all and integrating industries and competition. • Mechanism analysis of financial geo-density affects carbon emission intensity (IC). • Propose an integrated spatial model including spatial mediated moderating effects. • Financial geo-density drives IC by industrial-scale expansion. • Reduce IC by technological innovation and industrial upgrading. • Financial institution rivalry and inter-industry link mitigate total driven effect. [ABSTRACT FROM AUTHOR]

Given the severe global warming situation, it is very important to explore the factors influencing carbon emission intensity and accurately analyze the trends in the development of carbon emission intensity to achieve the goal of reducing carbon emissions. In contrast with the existing research, this paper starts from the perspective of carbon emission efficiency, applies stochastic frontier analysis to screen the factors influencing carbon intensity, and constructs a model for predicting carbon emission intensity based on factor analysis and an extreme learning machine. The results suggest that, first, there is a high correlation between carbon emission efficiency and carbon emission intensity. Second, the level of economic development, industrial structure, urbanization level, and government intervention all promote a reduction in carbon emission intensity. The structure of energy consumption and dependence on foreign trade restrain reductions in carbon emission intensity. Finally, the proposed model accurately predicts carbon emission intensity. The research results provide theoretical support for the development of technologies to reduce carbon emissions. This idea can be applied to predict carbon emission intensity in different regions and has practical significance. [Display omitted] • Carbon efficiency is related to carbon intensity. • Indicators of carbon efficiency work in reverse on carbon intensity. • Energy consumption and foreign trade restrain the reduction of carbon intensity. • Economic, industrial, urbanization and government promote the reduction. [ABSTRACT FROM AUTHOR]

The implementation of market-based climate policies represented by the emission trading system (ETS) is an important path for countries to participate in global climate governance and achieve the goals of carbon emission peaking and carbon neutrality. Whether the covered firms can improve financial performance through bearing responsibility for cutting emissions, a "win-win" of environmental and economic achievement, is an important way to evaluate the effectiveness of ETS. Based on the Chinese A-share listed firms in industrial sector during the period of 2010–2017, this paper employs PSM-DID method to investigate the impact of China's pilot ETS on financial performance of the covered firms. The results show that the covered firm's financial performance is improved by the implementation of pilot ETS, which can increase firm's ROA by 0.01 unit. Specifically, the pilot ETS can significantly improve the financial performance of non-state-owned firms, without affecting state-owned firms. Similarly, the financial performance improvement is more significant for firms in non-energy industries. Furthermore, the pilot ETS can motivate the covered firms to gain financial profit through cutting carbon emission as a mediation path, and the mediation effect size of carbon emission intensity is 0.001. Besides, firm's innovation ability weakens this mediation path, and the well-developed institutions in pilot area, proxied by high degree of marketization, only weaken the first part of the path, namely, carbon emission reduction led by ETS. • ETS achieves a win-win of carbon emission reduction and financial performance improvement. • The improvements by ETS are heterogeneous in ownership and industry. • Firm's carbon emission intensity plays a mediation role. • Firms can gain more benefit under the ETS regulation if the market monopoly is strong. [ABSTRACT FROM AUTHOR]

Clarifying the interactive relationship between urban land-use efficiency (ULUE), industrial transformation, and carbon emissions is of great realistic significance for promoting the coordination of 'resources-economy-environment' and achieving green development. This study used the stochastic frontier analysis (SFA), index method (IM), and remote sensing inversion to calculate the ULUE, the industrial transformation degree (ITD), and the carbon emission intensity (CEI) for 108 cities in the Yangtze River Economic Belt (YREB) from 2005 to 2017, and analyzed their spatiotemporal evolution characteristics. The generalized method of moments (GMM) and impulse response function (IRF) in the panel vector autoregressive (PVAR) model are used to empirically test the dynamic interactive effects of ULUE, ITD, and CEI. The empirical results show that: (i) During the study period, the ULUE and ITD of the YREB increased year-by-year, showing the pattern characteristics of high in the east and low in the west. The CEI decreased by 50.20% cumulatively, and the low-value areas spread from the center of the urban agglomeration towards the periphery. (ⅱ) The GMM shows that there is a significant dynamic dependence between the ULUE, ITD, and CEI. The ULUE has a positive driving effect on the industrial transformation and a negative effects on the CEI in the short term. (ⅲ) The IRF shows that the ULUE and industrial transformation show a synergistic effect of interactive growth. The improvement of the ULUE and industrial restructuring will force the reduction of CEI. The article proposes that the city should take the new urbanization path of resource-conserving, cost-effective, and environment-friendly. • The paper depicted the spatiotemporal patterns for ULUE, ITD, and CEI in the YREB. • The dynamic interactive effects of the ULUE, ITD, and CEI are revealed. • The ULUE has negative influence on CEI. • The ULUE and ITD show a synergistic effect of interactive growth. • The improvement of the ULUE and ITD jointly form a carbon reduction mechanism. [ABSTRACT FROM AUTHOR]

On the basis of literature review and current situation analysis, models were established to carryout scientific measurement for carbon emissions and its intensity in China in this paper. With full consideration to the actual situation of energy consumption growth and carbon emission intensity controlling of energy consumption in new-type urbanization construction, the Kaya model was revised. With population intensity of GDP production, urbanization rate, employment rate of urban population, per capita energy consumption of urban employed population and carbon emission density of energy consumption selected as independent variables, test models of multivariate linear correlation were established for new-type urbanization construction, energy consumption growth and carbon emission intensity controlling of energy consumption, and the empirical equilibrium equation and error correction equation were determined through stability test, lag order test and co-integration test. The results are shown as follows: the urban employment rate (UER) has the greatest impact on carbon emission intensity, the per capita urban employment energy consumption (PEC) has the least impact on carbon emission intensity, and the degree of other factors in proper order is: urbanization rate (UR), population intensity of GDP production (PG) and carbon emission density (CD). Image 10106 • Energy consumption is the main source of China's carbon emissions and environmental pollution. • China's urbanization has contributed to the reduction of energy consumption and carbon emission intensity. • The change law of energy consumption carbon emission intensity in China's urbanization construction is analyzed. • Kaya model was adopted to study the influencing factors of carbon emission intensity control. [ABSTRACT FROM AUTHOR]