Emission Reduction In China Research Articles

Artificial Intelligence As An Accelerator For Urban Carbon Emission Efficiency Based On Spatial Durbin Model

The explosive growth of the Artificial Intelligence market signifies the acceleration of a new phase in the industrial revolution. The challenges of global climate change and rapid technological evolution necessitate innovative approaches to improve carbon emission efficiency. While advancements in renewable energy and carbon capture technologies have been widely explored, the transformative potential of artificial intelligence in optimizing carbon emission efficiency remains underexamined. Based on the data of 285 Chinese cities from 2010 to 2022, this study examines the impact and mechanism of artificial intelligence on carbon emission efficiency through the Spatial Durbin Model (SDM). The research findings indicate that the development of artificial intelligence has effectively promoted the improvement of carbon emission efficiency, and the reduction effect remains consistent across different spatial weights. In terms of mechanism analysis, both technological research and development innovation and environmental policies have enhanced carbon emission efficiency. Finally, some suggestions are put forward to promote the development of artificial intelligence and energy conservation and emission reduction in China.

Does the carbon emission trading system facilitate public building carbon dioxide emission reduction in China?

Does the carbon emission trading system facilitate public building carbon dioxide emission reduction in China?

Integrating policy design with agricultural emissions reduction in China: A multi-sector DSGE Approach

Integrating policy design with agricultural emissions reduction in China: A multi-sector DSGE Approach

Synergistic strategies for pollution and carbon emission reduction in China's wastewater treatment: A comprehensive tiered assessment and benchmarking framework.

Synergistic strategies for pollution and carbon emission reduction in China's wastewater treatment: A comprehensive tiered assessment and benchmarking framework.

The impact of Carbon Trading Pilots on carbon emission reduction in China's power industry: A study using the Generalized Synthetic Control Method

The impact of Carbon Trading Pilots on carbon emission reduction in China's power industry: A study using the Generalized Synthetic Control Method

Efficiency evaluation and spill-over effect of energy saving and emission reduction in China under the New Normal of Economic Development.

Efficiency evaluation and spill-over effect of energy saving and emission reduction in China under the New Normal of Economic Development.

Digital agriculture drives carbon emission reduction in China

Agricultural activities markedly influence China’s goals of reaching carbon emission peaks and achieving carbon neutrality. This study explores the mechanisms by which digitalization in agriculture impacts carbon emissions and develops a corresponding analytical model. It examines the extent of agricultural digitalization and carbon emissions across 31 Chinese provinces from 2013 to 2020. Empirical findings demonstrate that digital agricultural practices significantly reduce carbon emissions within the agricultural sector, exhibiting notable spatial spillover effects. Additionally, green technological innovation and environmental regulatory frameworks act as crucial intermediary factors. The efficacy of digital agricultural technologies in reducing emissions varies across regions, showing stronger effects in inland provinces and areas primarily engaged in grain production, compared to non-grain-producing regions. The results contribute to the ongoing discussions on pathways for agricultural carbon mitigation in the context of rapid digital transformation in China’s agriculture. Furthermore, the study emphasizes the necessity of addressing agricultural environmental externalities and emphasizes the pivotal role of environmental regulations in reducing agricultural carbon emissions, aligning with China’s ecological governance objectives.

Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit

Abstract. Carbon monoxide in the atmosphere adversely affects air quality and climate, making knowledge about its sources crucial. However, current global bottom-up emission estimates retain significant uncertainties. In this study, we attempt to reduce these uncertainties by optimizing emission estimates for the second half of the year 2018 on a global scale with a focus on the Northern Hemisphere through the top-down approach of inverse modeling. Specifically, we introduce observations from the TROPOspheric Monitoring Instrument (TROPOMI) into the TM5-4DVAR model. The emissions are further constrained using NOAA surface flask measurements. We conducted six experiments to investigate the impact of data use in our inversions, varying the a priori emissions and observational datasets. Notably, the inversion driven by satellite observations alone agrees with flask measurements south of 55° N almost as well as the inversions that included those measurements. This indicates that our method could be suitable for inversions based purely on satellite observations. Compared to the bottom-up estimates, all experiments result in strong (up to 75 %) broad-scale emission reductions in China and India throughout the entire inversion period. Part of the reduction in China can be attributed to policy and technology changes (e.g., coal to gas). Additionally, the OH climatology used to simulate chemical loss appears to be underestimated in that region, which also skews the inversions towards lower emissions. In the experiments that include the surface flask measurements, we find strong localized emission increments over Europe and the Sahara, which are traced back to limitations of the model in reproducing point measurements on mountain tops.

Carbon emission reduction effects of digital infrastructure construction development: the broadband China strategy as a quasi-natural experiment

Research on carbon emission reduction in China has focused on carbon market policies, technological innovation, and industrial institutional adjustment, but few studies have been concerned with the effects of the rapid development of China’s digital economy on carbon emission reduction. China’s vigorous development of digital infrastructure has led to the establishment of the Broadband China strategy as a quasi-natural experiment. A difference-in-differences model with data from 2006 to 2023 about 283 prefecture-level cities was applied to investigate the effects of China’s digital infrastructure construction on carbon emission reduction. The conclusions are as follows. First, digital infrastructure construction in these cities had significant reduction effects on carbon emissions and intensity. This conclusion was proven after a series of robustness tests such as parallel trends, the exclusion of central cities, and the replacement of explanatory variables. Second, a mediating effect test showed that green technology innovation investment and industrial structure upgrading are important mechanisms for digital infrastructure construction’s carbon emission reduction effects. Third, these effects have obvious heterogeneity and are stronger in the eastern region than in the central and western ones. Moreover, the effects are stronger with the expansion of urban scale, the improvement of urban economic development level, and the environmental regulation intensity. These conclusions have important relevance to China’s Digital Economy and “Dual Carbon” Policies.

The Impact of Green Credit on Carbon Emission Reduction in China — A Case Study of Six Major Energy-Intensive Industries

The Impact of Green Credit on Carbon Emission Reduction in China — A Case Study of Six Major Energy-Intensive Industries

Research on fiscal and tax incentive policies for carbon emission reduction in China under the “dual carbon” goal

Against the backdrop of global climate change, China has proposed the "dual carbon" goal, namely, achieving carbon peak by 2030 and carbon neutrality by 2060. This paper aims to study the impact of fiscal and tax incentive policies on China's carbon emission reduction. Through literature research and comparative analysis, this paper first sorts out the relevant literature on carbon emission reduction and fiscal and tax policies, analyzes the basic theory of fiscal and tax policies promoting carbon emissions, and forms a theoretical basis. Subsequently, this paper describes the current status of China's carbon emissions and corresponding carbon emission reduction actions, measures and analyzes the current practice status of China's current carbon emission reduction fiscal and tax policies, and points out the existing problems. Through the analysis of typical cases such as the Beijing carbon emission trading pilot and Shanghai's green finance policy, this paper reveals the specific role and actual effect of fiscal and tax policies in carbon emission reduction. International comparative analysis shows the successful experience of countries such as Sweden, the United Kingdom, Denmark and Japan in carbon tax and environmental protection tax. Finally, based on the above research conclusions, this paper puts forward countermeasures and suggestions for optimizing China's carbon emission reduction fiscal and tax policies, aiming to better achieve the "dual carbon" goals. This study provides a scientific basis for policymakers and helps promote China's low-carbon transformation and sustainable development.

Travel intensity of private electric vehicles and implications for GHG emission reduction in China

Travel intensity of private electric vehicles and implications for GHG emission reduction in China

Emission factors and driving forces of provincial-level CO2 from electricity production and consumption in China from 2013 to 2020.

Emission factors and driving forces of provincial-level CO2 from electricity production and consumption in China from 2013 to 2020.

Long-Term Annual Changes in Agricultural Carbon Footprints and Associated Driving Factors in China from 2000 to 2020

China is one of the world’s largest agricultural producers, and its agricultural carbon footprint (CF) is a major contributor to global warming. However, the long-term annual changes in its agricultural CF and the underlying driving factors remain largely unknown, compromising the scientific basis for effective carbon reduction and sustainable agriculture management. To this end, we used the life cycle assessment (LCA) method and statistical data to calculate long-term annual agricultural CFs in China. We then adopted the linear regression slope and the Moran’s I method to analyze the temporal trends and spatial clustering characteristics and revealed the correlations between the main drivers and agricultural CFs. The results showed that the total (TCF) and farmland-averaged carbon footprint (FCF) of crop production both increased first and then decreased in China from 2000 to 2020, with a turning point in 2015. Overall, the TCF increased by 6.82% (3022.16 × 104 t CO2 eq), while the FCF slightly decreased by 0.004% (0.01 t CO2 eq/ha). Both the TCF and the FCF showed spatial heterogeneity, with high values in the east and low values in the west, and the spatial clustering of the TCF and its components has weakened over time. Fertilizer (39.26%) and paddy (27.38%) were the main contributors to TCF. Driver analysis found that grain yield was positively correlated with TCF in most provinces, indicating that the continuous yield increase has brought greater pressure on agricultural carbon emission reduction in China. Agricultural stakeholders should optimize crop planting structures and patterns and improve resource-use efficiencies through technological and management innovation to adapt to these threats and achieve low-carbon agriculture. The findings of our research can aid the scientific research on spatiotemporal estimation and driver analysis of agricultural CFs and provide decision-making support for sustainable agricultural practices.

Environmental technology’s diminishing marginal returns: a study of green patents and emission reductions in China

IntroductionDo environmental technologies always yield desirable returns? This study addresses this question through the lens of command-and-control environmental regulation. It explores the theoretical and empirical mechanisms influencing the efficacy of technology in reducing emissions, focusing on the non-linear characteristics of technological returns under equilibrium conditions.MethodsA socio-economic model integrating pollution discharge issues was developed to examine the marginal effects of emission reduction technology. Empirical validation was conducted using green patent data from Chinese listed companies (2005–2020) and pollution emissions data from various cities. Fixed effects models and generalized random forest models were employed to analyze the relationships.ResultsThe analysis revealed that technological innovation exhibits diminishing marginal returns in reducing emissions due to existing technological constraints. The results were further dissected by categorizing patents and city characteristics, shedding light on the factors influencing emission reduction effectiveness.DiscussionThe findings emphasize the importance of addressing the non-linear nature of technological innovation in environmental regulation. Policy recommendations include fostering tailored innovation strategies and supporting cities with unique characteristics to maximize technological impact on emission reduction.

Comparative analysis of certified emission reduction methodologies for methane emission reduction in China.

Comparative analysis of certified emission reduction methodologies for methane emission reduction in China.

Exploring the Role of Government Assessment Policy and Financial Development in Energy Conservation and Carbon Emissions Reduction in China

Exploring the Role of Government Assessment Policy and Financial Development in Energy Conservation and Carbon Emissions Reduction in China

The Green Effects of Digital Economy: Evidence from Carbon Emission Reduction in China

The Green Effects of Digital Economy: Evidence from Carbon Emission Reduction in China

Carbon emission reduction in China’s iron and steel industry through technological innovation: a quadrilateral evolutionary game analysis under government subsidies

The steel industry is notable for its significant environmental impact, highlighting the pressing need to promote technological innovation within the sector in order to reduce carbon emissions. This paper utilizes a quadrilateral evolutionary game model to analyze the strategic behaviors of steel producers, construction companies, scrap steel recyclers, and the government throughout the entire steel production, consumption, and recycling processes and their impact on carbon emission reduction. The analysis and simulation of the model provide policy insights for these four key players. The study’s findings are as follows: (i) Government subsidies can effectively stimulate low-carbon production methods and encourage green consumer behavior. (ii) The strategic choices for technological innovation by steel manufacturers and scrap steel recyclers are primarily influenced by cost factors. Government subsidies for technological innovation play a crucial role in incentivizing a smooth transition to low-carbon production methods. (iii) For steel manufacturers, the carbon benefits derived from technological innovation are a critical factor influencing their engagement in such initiatives. If these manufacturers can benefit from environmental regulations, they are more likely to engage in technological innovation. (iv) The strategies of construction companies are influenced by production costs and carbon benefits associated with steel manufacturers, exhibiting threshold effects.

Evaluating and prioritizing strategies to reduce carbon emissions in the circular economy for environmental sustainability.

Evaluating and prioritizing strategies to reduce carbon emissions in the circular economy for environmental sustainability.