Carbon Emission Reduction Effect Research Articles

Can green finance reduce carbon emission? A theoretical analysis and empirical evidence from China.

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction.

Digital carbon neutrality: evidence of carbon emission reduction based on digital inclusive finance.

As a powerful engine for economic reform and curbing carbon emissions, digital inclusive finance provides solid support for achieving the goal of digital carbon neutrality. This study reveals the positive effect of digital inclusive finance on carbon emission reduction and the deeper reasons behind it by digging deeper into the panel data of 213 cities in China. The study adopts advanced empirical analysis methods to rigorously test the association between digital inclusive finance and carbon emissions. The results show that there is a strong positive correlation between the booming development of digital inclusive finance and the significant decline in carbon emissions. This finding remains solid after several rounds of robustness tests, which fully proves the reliability of the research results. Further mechanism analysis reveals the multiple paths of digital financial inclusion on carbon emission reduction. First, it promotes the optimization and upgrading of industrial structure by optimizing the allocation of financial resources, thus reducing the proportion of high-carbon emission industries. Second, digital inclusive finance attracts more foreign capital inflows and introduces advanced low-carbon technologies and management experience, further promoting the development of low-carbon economy. In addition, the study also found that the differences between different cities in terms of geographic location and city size have a significant impact on the carbon emission reduction effect of digital inclusive finance. In particular, the carbon emission reduction effect of digital inclusive finance is particularly significant in western regions, central cities, and first-tier cities. In response to these findings, this paper proposes a series of targeted policy recommendations. First, the financial service system should be further optimized to increase the coverage and penetration of digital inclusive finance, especially in less developed regions and small- and medium-sized cities. Second, regional policy synergies should be strengthened to form a strong synergy to promote the development of a low-carbon economy. In addition, it should guide capital flows to low-carbon industries and encourage enterprises to increase green technology research and development and application, while actively promoting low-carbon consumption concepts and guiding consumers to form green consumption habits. Through the implementation of these measures, it is expected that the potential of digital inclusive finance in the development of a low-carbon economy will be further stimulated, making a greater contribution to the realization of the goals of carbon peaking and carbon neutrality.

The Carbon Emission Reduction Effects of the Quality and Quantity of R&D Activities: Evidence from Chinese Provinces

Research and Development (R&D) have significant impacts on carbon emissions, yet the specific data on R&D capital stock and carbon emissions have not been released by Chinese officials, hindering in-depth analysis. In light of this, this study calculates the R&D capital stock of Chinese provinces based on the SNA2008 framework and the BEA method, and estimates the carbon emissions from energy consumption and cement production using the carbon emission factor method. It then examines the carbon emission reduction effects of the quality and quantity of R&D activities at the provincial level. We find that the quality of R&D activities has a significant carbon emission reduction effect, which is stronger in regions with high levels of economic growth and marketization, and this effect strengthens over time. Moreover, mechanism analysis shows that both the quality and quantity of R&D activities reduce carbon emissions by promoting industrial structure upgrading. This paper expands the analytical approach and framework for the carbon reduction effects of R&D activities and offers significant policy and practical implications.

Analysis of the impacts of carbon neutral policy portfolios on the economy, environment, and residents' welfare based on computable general equilibrium models

The efficacy of the synergistic interplay of various programs about energy efficiency and emission reduction in China's endeavor to achieve carbon peaking and carbon neutrality remains to be determined. This research constructed a computable general equilibrium (CGE) model to examine the economic, environmental, social, and energy consequences of various policy combinations. Using data from the 2018 input-output table of China, we create 21 industry sectors and examine the combined impacts of different carbon policies. Our findings indicate that the effects of carbon emission reduction are more favorable when multiple carbon-neutral policies are implemented together, compared to the impact of a single policy. Among the various combinations of policies examined, the combination of feed-in tariff subsidy policy (FIT), renewable energy quota policy (RPS), carbon trading, carbon tax, and carbon capture, utilization, and sequestration (CCUS) technology proves to be the most effective. The study predicts that by 2060, this combination of policies could lead to a reduction of 32.5% in carbon dioxide emissions. At the same time, it was discovered that a combination of lower-intensity renewable energy quotas, carbon trading, carbon taxes, and higher-intensity subsidies for carbon capture, utilization, and storage (CCUS) technologies, the synergy indicator θ exceeds 1, indicating a more stable economy; When the carbon tax policy is more robust, and the remaining three policies are more minor, carbon emissions fall the most and are the most ecologically beneficial. Imposing excessively high renewable energy quotas while maintaining the same level of technology and substitutability between fossil fuels and electric energy sources will result in economic instability afterward. Therefore, we suggest that to attain balanced growth of the environment, society, and economy, the government should increase the function of policy combinations and balance several objectives.

Examining the emission reduction effect of carbon emission trading and carbon tax synergism and their impact mechanisms to reduce the carbon emission of company: based on 247 listed companies of China

ABSTRACT Using the panel data of Shanghai and Shenzhen A-share listed companies spanning from 2007 to 2021, we explore the impact of the synergism of carbon emission trading policy and carbon tax policy on the carbon emission level of enterprises through the difference-in-difference model, intermediary effect model, regulatory effect model. The research results show that: (1) Carbon emission trading and carbon tax both promote enterprises’ carbon emission reduction. (2) There are three paths for carbon emission trading and carbon tax policies to encourage enterprises’ carbon emission reduction actions synergistically: improving enterprises’ green technology innovation level, optimising energy structure, and accelerating industrial structure optimisation. (3) Mediated regulatory effect results show that the greater the company’s government support and R&D investment, the greater the synergism between carbon trading and carbon tax policies to drive green technology innovation and the better the carbon emission reduction effect of the company. (4) The synergism between carbon trading and carbon tax policies positively fosters public ownership companies’ carbon emissions reductions and heavily polluted industry companies.

The impact of trans-provincial watershed eco-compensation policy on carbon emissions: Evidence from China

To manage transboundary pollution, China has promoted trans-provincial watershed eco-compensation (WEC), which is a market-oriented policy that adjusts ecological and economic interests between upstream and downstream areas and promotes regional green and low-carbon transformation. Hence, a reasonable evaluation of the carbon emission reduction effect of WEC is of great value for achieving green transformation. Using data from Chinese counties between 2003 and 2020, we consider 11 trans-provincial WEC agreements and evaluate their influence on carbon emissions. We find that trans-provincial WEC policies reduce water pollution emissions and significantly lower carbon emission levels. Mechanism tests show that the policy reduces carbon emissions by limiting polluting industrial development and stimulating low-carbon technological innovations. Moreover, this policy improves regional low-carbon economic development, and there are significant heterogeneity effects of the WEC in different regions and compensation modes. This research provides new insights for transitional countries to design green transformation policies.

The agricultural carbon reduction effect of digital rural construction under the dual carbon target.

The exploration of the agricultural carbon emission reduction effect of digital rural construction offers a promising path towards achieving dual carbon goals. This study establishes an evaluation system for digital rural construction and analyzes its impact on agricultural carbon emissions using various creative techniques including panel fixed effects, mediation effects, threshold effects, and spatial Durbin models based on provincial panel data from 2011 to 2021.It is found that: (1) The impact of digital rural construction on agricultural carbon emissions exhibits a "inverted U-shaped" pattern, with a nonlinear effect on emissions through promoting agricultural green total factor productivity and adjusting agricultural structure.(2) Digital rural construction has both promoting and inhibiting effects on agricultural carbon emissions, both locally and in adjacent areas. It also demonstrates a threshold effect, with rural human capital as the sole threshold. Once the threshold value 8.830 is surpassed, the agricultural carbon emission reduction effect becomes prominent.(3)Digital rural construction has a dual effect on local agricultural carbon emissions in terms of both promoting and then restraining the emissions, which has a spatial spill-over effect in the neighboring areas. This study contributes to our understanding of carbon reduction pathways by highlighting the comprehensive utilization of digital rural construction and expanding research on the dynamic context of its impact on carbon emissions.

Spatial effects of green innovation and carbon emission reduction in China: Mediating role of infrastructure and informatization

Green innovation (GI) plays a vital role in mitigating urban carbon dioxide (CO2) emissions and fostering sustainable development in China. This study examines the impact of GI on CO2 emissions, underscoring its significance for environmental sustainability. The analysis of data from 253 Chinese cities from 2010 to 2020 shows a transition in GI from a “multipoint” sporadic pattern to a “clustered” aggregation, indicative of significant polarization. Concurrently, a converging trend in the CO2 emissions kernel density curve reflects the initial success of carbon reduction initiatives, demonstrating a notable “high in the north and low in the south” spatial disparity. Critically, the findings reveal that GI induces significant spatial spillover effects, reducing CO2 emissions not only locally but also in adjacent areas. The mediation analysis reveals that the level of infrastructure development acts as a masking factor, suggesting that despite infrastructure expansion potentially escalating CO2 emissions, alignment with GI principles steers its environmental impact towards a positive direction. Additionally, informatization's modest mediating role suggests that its enhancement, driven by GI, further mitigates CO2 emissions through improved resource efficiency. These insights highlight the importance of integrating GI into urban policy frameworks, emphasizing its role in environmental management and CO2 emission reduction.

Research on the Mechanism of the Carbon Emission Reduction Effect of Green Finance

Under the background of China’s “double carbon” policy, determining how to use the carbon emission reduction effect of green finance is an important starting point for China to achieve stable economic development and sustainable ecological development. By integrating provincial data from the CEADS, EPS, CSMAR, and CNRDS databases from 2003 to 2021, the two-way fixed-effect models are used to empirically test how green finance can exert a carbon emission reduction effect. This study finds that green finance can significantly reduce carbon emission intensity. A mechanism analysis shows that green finance can promote green technology innovation, induce social investment, and promote the disclosure of the social responsibility information of listed companies to reduce carbon emissions, which is still valid after a series of robustness tests. A heterogeneity analysis finds that the government’s environmental attention and the scale of financial industry development have heterogeneous effects on the carbon emission reduction mechanism of green finance. Both the government’s environmental attention and the scale of financial industry development can induce social investment, but the government’s environmental attention cannot promote the growth of green technology innovation, and the scale of financial industry development cannot promote the disclosure of the social responsibility information of listed companies. This paper broadens the research perspective of green finance to reduce carbon emissions and provides some empirical evidence and a theoretical reference to further promote the green transformation of the “two high and one surplus” industry and the sustainable development of the financial industry.

Impact of Environmental Protection Tax on carbon intensity in China.

In the context of increasingly severe global climate change, finding effective carbon emission reduction strategies has become key to mitigating climate change. Environmental Protection Tax (EPT), as a widely recognized method, effectively promotes climate change mitigation by encouraging emission reduction behaviors and promoting the application of clean technologies. Based on data from 282 cities in China, this paper takes the official implementation of the EPT in 2018 as the policy impact and the cities with increased tax rates for air taxable pollutants as the treatment group and uses DID model to systematically demonstrate the relationship between the implementation of the EPT and carbon intensity (CI) and further explores the possible pollutant emissions and green innovation mediating effects. The findings show that (1) the implementation of EPT can effectively reduce CI by about 4.75%, and this conclusion still holds after considering the robustness of variable selection bias, elimination of other normal effects, policy setting time bias, and self-selection bias. (2) The implementation of EPT can reduce CI by reducing pollutant emissions and improving the level of green innovation. (3) There is obvious regional heterogeneity in the carbon reduction effect of EPT, and the implementation of EPT has a more significant effect on CI in medium-tax areas, low environmental concern areas, general cities, and eastern regions. This paper not only provides a new analytical perspective for systematically understanding the carbon emission reduction effect of EPT but also provides policy insights for promoting regional green transformation and advancing carbon peak carbon neutralization.

Dynamic assessment of the abatement effects of the low-carbon practices in the prefabricated building supply chain

PurposePrefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.Design/methodology/approachThis study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.FindingsResults show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.Originality/valueThis study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

Digital Economy, Energy Structure and Carbon Emissions: Evidence from China

The digital economy is an important driving force for China’s economic transformation and upgrading, while “carbon peaking and carbon neutrality” is the goal to be achieved in China. Based on the panel data of 30 Chinese provinces (cities and districts) from 2012 to 2019, the article empirically investigates the impact of the digital economy on regional carbon emissions and its mechanism of action by using a two-way fixed-effects model and mediated-effects model. The study shows that, firstly, the digital economy has a significant carbon emission reduction effect, and the conclusion still holds after robustness testing. Secondly, the emission reduction effect of industry digitization in the digital economy dimension is the most obvious. Again, the carbon emission reduction effect of digital economy development on different regions varies, with the strongest carbon emission reduction effect on western regions and regions with high carbon emission levels. Finally, the analysis of mediating effects shows that the energy structure is an important mechanism for the digital economy to suppress regional carbon emissions. The findings of the study provide a feasible path and policy reference for the digital economy to contribute to the goal of “carbon peaking and carbon neutrality.”

The heterogenicity features revealed based on the regional and sectoral carbon metabolic system: An empirical analysis of heavy-polluted cases in China

The Chinese government has made a positive response and policies to address global climate change, regions and sectors has become more important in reducing carbon emission. This study used the indicator of carbon emission intensity to evaluate the reduction effect of carbon emission of heavy-polluted regions and sectors, and also their features in China. The results indicated firstly, the aggregated carbon emission intensity of regions was primarily influenced by their embodied added value. From 2012 to 2015, the regions’ embodied added value increased more than 2 times. Secondly, the embodied carbon emission of the manufacture of chemical products sectors in regions were dominated by emission implied in metabolic path length greater than five, which took the proportion of more than 30% of emission. This showed that emission reduction policies for heavy-polluted sectors should focus on controlling the emission implied in trading with downstream sectors, and also demonstrated that the heavy-polluted sectors drove the reduction of carbon emission of other sectors. Thirdly, the carbon emission of heavy-polluted sectors in coastal regions fell due to implementing the carbon emission trading scheme policy, while heavy-polluted sectors in the inland regions radiated to their upstream and downstream sectors. This study analyzes regional and sectoral carbon emission reduction effect and provides theoretical and practical bases for urban development.

Evaluation of Contribution to Greenhouse Gas Reduction and Economic Benefits of Livestock Manure based Solid Fuel

Objectives : In the context where the greenhouse gas (GHG) emissions from livestock manure (LSM) account for more than half of the GHG emissions in the livestock sector, it is necessary to find alternatives to composting due to the decrease in agricultural land. This study aims to calculate the GHG reduction contribution and economic benefits when converting LSM into solid fuel as an alternative to traditional composting.Methods : The study compares the results of converting the entire LSM generated domestically into solid fuel replacing it with hard coal for fuel (HC-F), bituminous coal for raw materials (BC-R), bituminous coal for fuel (BC-F). The GHG reduction contribution is calculated following the domestic GHG inventory methodology, using the IPCC guidelines and the method for calculating carbon emission reduction effects. For the assessment of economic benefits, were evaluated by aggregating the impacts of reducing coal imports and GHG reduction benefits in line with EU-ETS standards. Economic benefits are assessed by combining the effects of avoiding coal imports and the GHG reduction benefits according to the EU-ETS.Results and Discussion : The GHG reduction effect was found to be highest when replacing with HC-F, and this is attributed to the lower heating value and higher GHG emission coefficient of HC-F compared to BC-R, and BC-F, indicating that the substitution with HC-F is most effective in terms of import avoidance. If 20% of the annual coal consumption in 2022 is replaced with solid fuel from LSM, the GHG reduction effects for coal substitution are 1.4% for HC-F, 2.1% for BC-R, and 1.9% for BC-F based on the LSM generation CO<sub>2</sub> emissions from biomass fuel are considered climate-neutral and are excluded from the national total emissions. Solid fuel from LSM serves as an alternative in addressing the GHG generated during the LSM treatment process, contributing to potential reduction. If all generated LSM is replaced with HC-F, BC-R, or BC-F, there are respective GHG reduction effects of 13,193,591 tGHG, 11,320,572 tGHG, and 11,226,331 tGHG.Conclusion In 2018, the livestock sector accounted for approximately 42% of the GHG emissions in the agricultural sector, totaling 9.4 million tCO<sub>2</sub> eq. Assuming the complete conversion of LSM into solid fuel for coal substitution, regardless of the type of coal replaced, it offsets the entire GHG emissions from the agricultural sector. Currently, there is limited demand for the conversion of LSM into solid fuel due to a lack of proof and awareness, but with some coal-fired power plants scheduled for partial shutdown and the government considering energy options for LSM, a promising stage is anticipated in the future for the substitution and expanded use of solid fuel from LSM in place of coal in the coal fuel. Although it may not be possible to entirely replace the coal used in power plants and steel mills with solid fuel from LSM, it can be utilized by increasing the proportion of coal blending. However, even if not reported in the national GHG inventory, the treatment of pollutants generated by solid fuel combustion remains an ongoing challenge. As solid fuel becomes more commonplace in the future, a comprehensive assessment of the entire process, including potential environmental impacts throughout the life cycle, will be necessary to establish a basis for GHG reduction measures.

The Carbon Emission Reduction Effect and Spatio-Temporal Heterogeneity of the Science and Technology Finance Network: The Combined Perspective of Complex Network Analysis and Econometric Models

With the active promotion of the “carbon peaking and carbon neutrality” goals, science and technology finance (STF) is the important driving force of low-carbon development, and financial networks facilitate the aggregation and transformation of resources in space, so it is of great theoretical and practical significance to investigate the impact of science and technology finance networks (STFN) on carbon emissions (CE). Based on the 30 provinces of China from 2011 to 2019, this article used the STF development level in each province as the main indicator to construct the STFN. The complex network analysis and econometric models are combined, with the weighted degree values and betweenness centrality selected as typical network structure indicators incorporating into the econometric model to explore their impact on CE. Then, the Geographically and Temporally Weighted Regression (GTWR) model is applied to analyse the spatio-temporal heterogeneity of influencing factors. The results show the following: (1) From 2011 to 2019, the spatial structure of China’s STFN has changed significantly, and the status of the triangle structure consisting of Beijing–Tianjin–Hebei (BTH)–Yangtze River Delta (YRD)–Pearl River Delta (PRD) is gradually consolidated in the overall network, and the network structure tends to be stable. (2) The results of the benchmark regression show that the weighted degree value of the STFN has a significant inhibitory effect on CE, while betweenness centrality shows a certain positive effect on CE. (3) The weighted degree value has a more significant effect on CE reduction in the eastern region, while the betweenness centrality has a more significant effect on CE reduction in the central and western regions, but shows a significant promotion effect in the eastern region. (4) There is spatio-temporal heterogeneity in the effects of residents’ affluence, energy consumption, industrial structure, and environmental pollution on CE.

The carbon emission reduction effect of renewable resource utilization: From the perspective of green innovation

In the face of pressing global challenges posed by climate change, resource constraints, and environmental pollution, understanding the role of renewable resource utilization in carbon emission reduction has become paramount. This study aims to investigate this relationship, particularly within the context of the dual carbon goals, which emphasizes both carbon peak and carbon neutrality. Focusing on the national "urban mineral" demonstration bases as a case study, this research employs the directional distance function incorporating non-expected output alongside the Malmquist index to assess the dynamic changes in urban carbon dioxide emission performance. A multi-period difference-in-difference model is utilized to examine the impact of these demonstration bases on CO2 emissions. The Baseline results reveal that renewable resource utilization significantly enhances carbon emission performance. The channel analysis indicate that the establishment of national "urban mineral" demonstration bases positively influences carbon emission performance through three primary pathways: green technology agglomeration, green technology spillover, and energy structure optimization. Based on these findings, this study advocates for policies that promote renewable resource utilization and carbon emission reduction. Specifically, it highlights the need for increased investment in green technology innovation and diffusion, as well as the optimization of energy structures to mitigate carbon emissions. These findings provide valuable policy implications for governments and stakeholders seeking to reduce carbon emissions and promote sustainable development.

Environmental regulation and carbon emissions: New mechanisms in game theory

The effective implementation of environmental regulations is crucial for mitigating environmental pollution. During the regulatory process, local governments engage in an interactive game. Based on sample data from 275 Chinese cities between 2012 and 2020, our findings demonstrate that local governments adopt imitative strategies, resulting in a “race to the top competition” in environmental regulation. The attention given by local governments to environmental protection, combined with the central government's restrictions on emission reduction targets, enhances the effectiveness of carbon emission reduction through environmental regulation. However, the inhibitory effect of environmental regulation on carbon emissions is diminished when local governments attract low-quality foreign direct investment (FDI). Additionally, both local and neighborhood effects of environmental regulation exhibit significantly positive impacts on carbon emissions in the eastern and central regions. In contrast, the western regions show significantly negative effects. Finally, our study reveals that environmental regulation has positive carbon emission reduction effects in non-pollution and pollution-prevention cities, as well as resource and non-resource cities. This study provides insight for China's “double‑carbon goal” and offers positive implications for the effective implementation of environmental regulations.

Assessing the carbon emission reduction effect of flexibility option for integrating variable renewable energy

Integrating a high-penetration level of variable renewable energy into power systems requires the pro-rata deployment of flexibility technology in the recent trends of low-carbon transition. This study proposes a multi-regional power system optimization model to assess the carbon emission reduction effect of different flexibility options in the Chinese power sector, including total carbon emissions, peaking timetables and values, carbon emission transfer between regional power systems, and carbon emission source changes between technologies. The results reveal that the combinations of dispatchable generation, inter-regional transmission, energy storage, and demand-side response can significantly reduce carbon emissions from power systems, but will lead to higher expenditure. Carbon emissions would peak 1–6 years in advance under the integrated flexibility option consisting of all flexibility technologies, and the corresponding peaking value would decrease by 0.26–0.48 billion tonnes compared to other configuration scenarios. However, this does not apply to all the regions. The coupling relationship between the flexibility option and carbon emission reduction in regional power systems changes with the disparities in power demand, system structure, and renewable energy consumption targets.

The power of attention: Government climate-risk attention and agricultural-land carbon emissions

Climate change is a common challenge faced by all humanity. Promoting emission and carbon reduction in agricultural land is the most important priority for addressing climate change and realizing sustainable development. Based on data from 296 prefecture-level cities in China from 2011 to 2021, this study utilizes machine-learning and text-analysis methods to construct an indicator of government climate-risk attention (GCRA). It combines a two-way fixed-effects model to investigate how GCRA affects agricultural-land carbon emissions (ALCE) and carbon intensity (ALCI) and the mechanism of the impact. The results indicate that (1) GCRA substantially reduces ALCE and ALCI, and the conclusions are robust to a battery of tests. Furthermore, (2) mechanism analysis reveals that GCRA primarily uses three mechanisms—strengthening environmental regulation, promoting agricultural green-technology innovation, and upgrading agricultural-land mechanization—to reduce ALCE and lower ALCI. Additionally, (3) heterogeneity analysis suggests that the carbon-emission reduction effect of GCRA is more significant in the east, in arid and humid climate zones, and in non-grain-producing regions. Finally, (4) spatial-spillover effect analysis and quantile regression results demonstrate that GCRA also significantly inhibits carbon emissions and the carbon intensity of nearby agricultural land, with the inhibition effect becoming more pronounced at higher levels of government attention. This study's discoveries are helpful in promoting the emission reduction and carbon sequestration of agricultural land and provide references for developing countries to cope with climate change.

Digitization and carbon emissions: how does the development of China's digital economy affect carbon intensity?

The digital economy and the pursuit of carbon peak and carbon neutrality have emerged as crucial focal points for China's future development. However, the intricate relationship between the digital economy and carbon intensity remains uncertain. Based on the construction of the digital economy evaluation index system, using panel data for 30 provinces in China from 2011 to 2019, this study estimates the impact of the digital economy development on carbon intensity by adopting the system-generalized method of moments (SYS-GMM) technique. The results show that the digital economy can effectively reduce the carbon intensity. This conclusion was supported by robustness tests. However, the carbon emission reduction effect of the digital economy exhibits heterogeneity with respect to the digital economy dimensions and regions. In addition to digital industrialization and industrial digitization reducing the carbon intensity, the digital economy development carrier has an inverted U-shaped nonlinear relationship with carbon intensity. Additionally, the digital economy has a more obvious inhibitory effect on carbon intensity in the eastern region. Most importantly, besides the mediating effects of technological progress and financial development, this paper finds that the digital economy can increase carbon intensity through human capital accumulation. These conclusions provide a certain scientific basis for the effective implementation of China's digital economy and carbon peak and carbon-neutral development strategy.