Search

The widespread use of digital technology has driven a huge change in the way payments are made. Based on the micro-data of the China Family Panel Studies (CFPS), this paper explores the relationship between mobile payment and carbon emissions from the consumption side. With the exogenous impact of Alipay's "Collecting Five Blessings" campaign, this paper finds that mobile payment significantly increases household consumption carbon emissions, but the marginal effect is gradually decreasing. Mechanism analysis shows that mobile payment mainly realizes the above impact through promoting the increase of consumption expenditure and upgrading of consumption structure. Further analysis indicates that carbon reduction policies introduced by the Chinese government in the personal consumption sector can mitigate the carbon emissions growth associated with mobile payments. Still, there is a need to strengthen policy measures further to effectively address the issue of rising carbon emissions from household consumption. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

Exploring the key influencing factors (KIFs) of Urban Low-Carbon Innovation (ULCI) from urban characteristics is essential for devising customized promotion strategies. However, existing studies are hampered by methodological limitations that lead to an inability to effectively discern KIFs among urban characteristics or unravel complex, non-linear relationships, and interaction effects. To address these gaps, this paper adopts a synthetic approach based on interpretable Machine Learning (ML). Firstly, the influencing factors are identified through the Delphi method and a systematic literature review. Subsequently, three single AI models (KNN, SVR, and CART) and three ensemble models (RF, XGBoost, and LBGM) are employed to fit the data. Finally, the SHapley Additive exPlanations (SHAP) algorithm is integrated to identify the KIFs and disentangle their impact effects. The findings indicate that (1) 41 influencing factors are identified, from which 10 KIFs, such as Expenditure on Research, Carbon Emissions, Local General Budgetary Revenue, and Education Expenditure, are determined, (2) the developed interpretable ML model tailored for ULCI's KIFs analysis demonstrates high precision and effectively capturing non-linear relationships (R2 = 0.841, RMSE = 0.591, MAE = 0.463), and (3) the global impact, interactive effects, and individual sample impact of the KIFs are explained, and two categories of KIFs dominated by positive and negative influences are revealed respectively. Results of the KIFs identification can provide policy-makers with insight for designing ULCI enhancement paths and consequently promote emission mitigation in China. • 41 influencing factors of ULCI is identified from urban characteristics. • An interpretable ML model is developed to quantitatively explore KIFs. • 10 KIFs are determined and the comprehensive impact, interactive effects, and individual sample impact of the them are explained. [ABSTRACT FROM AUTHOR]

• Integration of blockchain characteristics into the collaborative carbon emission reduction game model of both the supply and demand sides of electricity is proposed to encompass source control and terminal suppression. • Blockchain is utilized to trace electricity types within the electricity market and to quantify the carbon emissions generated by the demand side of electricity. • By incorporating blockchain, users can actively engage in individual-level carbon trading to control and reduce carbon emissions. • Blockchain facilitates enhanced carbon emission reduction efforts by the power supply side. The task of carbon emission reduction is severe in the power industry in China under the national goal of "carbon peaking and carbon neutrality". The current carbon reduction is mainly based on supply side, but the effect is limited. To solve this problem, this paper proposed a coordinated supply–demand carbon emission reduction strategy based on blockchain technology. Based on the carbon emission reduction of complementary thermal power and renewable energy under the carbon trading mechanism of power supply side, users are made to participate in the individual level carbon trading mechanism with the help of blockchain technology, and the carbon emission reduction in power demand side is guided through the market mechanism, thus forming a supply–demand collaborative carbon emission reduction strategy of source side control and terminal inhibition. By analyzing the decision changes of both the supply and demand sides of electricity before and after the introduction of blockchain, quantifying the influence of blockchain on electricity quantity, electricity price and users' utility in turn, and establishing the personal carbon trading mechanism supported by blockchain, a game model of two-side interaction between supply and demand was constructed. The simulation results show that the collaborative carbon emission reduction strategy based on blockchain gives full play to the potential of carbon reduction in power demand side, and the personal carbon trading mechanism can better inhibit terminal carbon emissions, which is conducive to the deep carbon emission reduction of the power industry. [ABSTRACT FROM AUTHOR]

This paper delineates the impact of digital infrastructure construction (DIC) on carbon emission efficiency (CEE) within the ambit of China's "Broadband China" pilot policy (BCP). A quasi-natural experimental framework reveals direct effects, indirect influences, non-linear relationships, and spatial heterogeneity of DIC on CEE. The research distills several pivotal insights: (1) DIC exerts a markedly positive impact on CEE, as evidenced by comprehensive robustness analyses. (2) The digital service industry agglomeration and green technology innovation act as key mechanisms through which DIC influences CEE. (3) The intensity of BCP exhibits an "inverted U-shaped" relationship with CEE. As the level of CEE increases, the impact of DIC on CEE gradually rises, demonstrating a marginal increasing effect. (4) The spatial spillover effects of DIC on CEE vary with increasing distance, revealing a dichotomy: an "agglomeration shadow" within 200 km of policy pilot cities and a pronounced stimulative effect on CEE within a 200–300 km radius. (5) The efficacy of DIC in enhancing CEE is augmented by proximity to central cities, with the optimal radius of influence for central cities determined to be 200 km, beyond which a diminishing gradient effect is observed, forming a "core-peripheral" spatial pattern. The findings endorse the strategic augmentation of digital infrastructure as a lever for economic and environmental co-benefits, steering towards carbon neutrality and equitable regional development. [ABSTRACT FROM AUTHOR]

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age. • A decision-making optimization model of CCPs low-carbon technology is proposed. • A dynamic CET system with upper-lower layer interaction is introduced. • The proposed dynamic CET system results in 27% reduction in total costs. • The high-resolution data of coal power in Beijing-Tianjin-Hebei region are used. • The strategy to solve the conflict between cleanliness and flexibility is given. [ABSTRACT FROM AUTHOR]

The aim of the paper is to evaluate empirically the main implications of digital technology (DT) on carbon emissions (CE). Our sample focuses on 283 cities of China over the period from 2003 to 2019, and the effect of DT on CE is examined with a threshold spatial effect model. Empirical results show that DT has a negative impact on carbon emissions and the transmission mechanism contains both a direct impact on local region and a spillover effect across regions. There is empirical evidence of a threshold effect in the relationship between DT and CE, with stronger carbon reduction effect for DT values larger than the established threshold. Moreover, CE reduction effect of DT appear to be amplified by the level of marketization. Regions with a higher level of marketization thus show a more significant manifestation of CE reduction effect attributed to DT. Our results provide empirical evidence that DT development may contribute to achieving carbon neutrality at least partially. [ABSTRACT FROM AUTHOR]

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]

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction. • It explores the impact of Broadband China Policy on carbon emissions reduction. • Digital infrastructure development has positive impact on reducing carbon emissions. • The reduction effect is heterogeneous in regions with different characteristics. • Carbon emissions can be reduced at both industrial and individual levels. [ABSTRACT FROM AUTHOR]