Carbon Emission Reduction Policies Research Articles

Analysis on Evolutionary Stability Strategies of Carbon Emission of Logistics Enterprises Based on Carbon Tax

In view of the problem of high carbon emissions of logistics enterprises, the government’s carbon tax policy, consumers’ willingness to purchase low-carbon services, and the carbon emission reduction behavior of logistics enterprises, the evolutionary game model between the government, consumers, and logistics enterprises is established by using the theory and method of evolutionary game, and the evolutionary stabilization strategies of the three parties under different parameters are analyzed. The research results show the following. (1) When setting the carbon tax rate, the government can ignore the impact on consumers and give more consideration to the influencing factors of logistics enterprises, which is conducive to the formulation of carbon emission reduction policies for logistics enterprises. (2) When the government sets a lower carbon tax rate, it can not only promote the carbon emission reduction of logistics enterprises but also be conducive to government supervision. (3) The evolution direction of the government’s final decision will not change due to the size of Y and Z. The government’s final decision is to adopt a regulatory strategy. The study provides theoretical guidance for the government to formulate carbon tax policies, guides consumers to purchase low-carbon services, and promotes carbon emission reduction in logistics enterprises.

Difference in the drivers of industrial carbon emission costs determines the diverse policies in middle-income regions: A case of northwestern China

Carbon reduction actions may cause regions that recently entered the middle-income threshold to fall into “ecological poverty”. Identifying the factors driving industrial carbon emission costs (ICECs) growth is difficult and important for achieving “peak carbon dioxide emissions” and “carbon neutrality” goals. This study considers the northwestern provinces (NWPs) of China as a case, innovatively adopts the ecological service value (ESV) to convert the physical cost of industrial carbon emissions (PCICE) to the cost value of industrial carbon emissions (CVICE). The logarithmic mean Divisia index decomposition method is employed to analyze the impacts of the carbon emission coefficient, energy intensity, industrial structure, population size and economic factors on ICECs. Consequently, PCICE and CVICE in NWPs are increased, and CVICE is faster. The energy intensity and population size factors inhibit the increase in CVICE, and the energy intensity factor effect is stronger, the average contribution rate is in [-14.63%, −111.91%]. The carbon emission coefficient factor has a significant positive effect on CVICE, the average contribution rate is in [75.91%, 409.72%]. The economic and industrial structure factors have different effects on the direction and average contribution rate of CVICE in different provinces, the economic factor effect is obvious. The results show that the factors driving ICECs changes in middle-income regions are different. This study provides a novel theoretical framework and ideas for formulating diversified carbon emission reduction policies. It has important practical significance for different middle-income regions worldwide to formulate carbon emission reduction policies based on actual industrial economic development.

Forecasting of Carbon Emission in China Based on Gradient Boosting Decision Tree Optimized by Modified Whale Optimization Algorithm

As the global temperature continues to rise, people have become increasingly concerned about global climate change. In order to help China to effectively develop a carbon peak target completion plan, this paper proposes a carbon emission prediction model based on the improved whale algorithm-optimized gradient boosting decision tree, which combines four optimization methods and significantly improves the prediction accuracy. This paper uses historical data to verify the superiority of the gradient boosting tree prediction model optimized by the improved whale algorithm. In addition, this study also predicted the carbon emission values of China from 2020 to 2035 and compared them with the target values, concluding that China can accomplish the relevant target values, which suggests that this research has practical implications for China’s future carbon emission reduction policies.

Understanding the Impact of Land Resource Misallocation on Carbon Emissions in China

In order to achieve growth in fiscal revenue and the regional economy under the Chinese decentralization system, the land resources misallocation (LRM) among different industries was promoted through the differentiated land supply strategy, which has a vital role in carbon emissions. This study theoretically analyzes the overall effect and the effect of the intermediate LRM mechanism on carbon emissions and empirically tests the impact of LRM on carbon emissions based on panel data collected from 30 provinces in China from 2005 to 2017 using the environmental Kuznets curve theory. The results show that (1) the local governments have monopolized the primary land market across the nation, leading to resource misallocation among industrial, commercial, and residential land. This inefficient and unsustainable allocation aggravated the release of carbon emissions. (2) The impact of LRM on carbon emissions has varied among different regions. LRM in the eastern and central regions significantly exacerbated carbon emissions. A greater impact on carbon emissions occurred in the eastern region, while the impact was insignificant in the western region. (3) There are two mechanisms through which LRM affects carbon emissions. One is the restraint of upgrading industrial structure, and the other is the restriction of technological innovations. In conclusion, speeding up the reform of the tax sharing system is suggested to reduce the excessive dependence of local governments on land resources. Meanwhile, in order to reduce carbon emissions, the land acquisition and transfer system should be reformed to gradually achieve the market-oriented allocation of land resources, and the benefits coordination mechanism of different land transfer modes should be established. Finally, we propose different carbon emission reduction policies for the heterogeneity of regional economic development.

Research on the heterogeneous impact of carbon emission reduction policy on R&D investment intensity: From the perspective of enterprise's ownership structure

Confronted with the constraints of carbon dioxide reduction, R&D improves the production efficiency of enterprises. However, China's diversified economic entity structure makes enterprises with different attributes exhibit different R&D behaviors under the constraints of external carbon dioxide reduction. This paper takes Ten Thousand Enterprises Plan as an example, which belongs to the front-end policy and restricts the enterprise's carbon emission rights, reveals the impact of carbon dioxide reduction constraint on enterprises' R&D investment and alleviates the endogenous bias of previous research. Moreover, this paper explores the moderating effect of ownership structure on the relationship between carbon dioxide reduction policy and enterprises' R&D investment. The results show that the relationship between carbon reduction policy and enterprises' R&D investment in China is manifested as a significant “cost effect”, that is, mandatory carbon emission reduction policy limits the expansion of enterprises' R&D investment scale. Comparing state-owned enterprises with non-state-owned enterprises, carbon dioxide reduction policy can hardly stimulate the R&D investment in non-state-owned enterprises, while the state-owned enterprises can easily obtain factor resources, which decreases carbon emission reduction costs and improve R&D investment intention, resulting in stronger R&D behaviors.

The impact of network topological structures on systematic technology adoption and carbon emission reduction

This paper investigates how the topological structure of the technological spillover network among agents affects the adoption of a new clean technology and the reduction of system’s carbon emissions. Through building a systematic technology adoption model with technological spillover effect among agents from the network perspective, this paper first illustrates how the new technology diffuses from the earlier adopters to the later adopters under different network topological structures. Further, this paper examines how the carbon emission constraints imposed on pilot agents affect the carbon emissions of other agents and the entire system under different network topological structures. Simulation results of our study suggest that, (1) different topological structures of the technological spillover network have great influence on the adoption and diffusion of a new advanced technology; (2) imposing carbon emission constraints on pilot agents can reduce carbon emissions of other agents and thereby the entire system. However, the effectiveness of the carbon emission constraints is also largely determined by the network topological structures. Our study implies that the empirical research of the network topological structure among the participating entities is a pre-requisite to evaluate the real effectiveness of a carbon emission reduction policy from the system perspective.

Airline environmental efficiency comparison through two non-separable inputs disposability Range Adjusted Measure models

The aviation industry contributes to climate pollution while facilitating commercial trade and international exchanges. How to improve the overall efficiency of airlines has become a hot issue of social concern. Based on the Range Adjusted Measure model (RAM), this paper proposes two improved by-production models, namely mixed input sharing model and good output sharing model, which decompose the air transport process to explore the driving factors of airline efficiency. We take the Number of Employees (NE), Fleet Size (FS) and Aviation Kerosene (AK) as the inputs, the Revenue Passenger Kilometers (RPK) as the desirable output, and the Greenhouse gas emission (GHG) as the undesirable output. The empirical study is based on the data of 22 global airlines from 2014 to 2019. We have some findings: (1) The average efficiency scores of mixed input sharing model are higher for most airlines than the good output sharing model. (2) The efficiency scores of the good output sharing model are more distributed than the mixed input sharing model. (3) Fleet renewal and carbon emission reduction policies play an important role in improving environmental efficiency. In addition, the possible future research directions and policy implications are also proposed in this paper.

Regional inequality of total factor CO2 emission performance and its geographical detection in the China's transportation industry.

The total factor CO2 emission performance (TFCEP) of transportation industry has received increasing research interests, while existing literature pays little attention to its regional inequality and driving factors. In order to uncover the regional inequality of TFCEP in China's transportation industry, this paper used Theil index and combined with geographical detector model (GDM) to explore the driving factors and their interactions on TFCEP in Chinese transportation industry. The results revealed that the TFCEP of transportation industry showed a promising increase during 2003-2017 with an annual growth rate of 0.12%, and the improvement was contributed by the technical efficiency change. The TFCEP in the Eastern region performed better than that in the Northeast, Central, and Western region. Regional inequality of TFCEP did exist and exhibited an obvious downward trend. The within-region inequality had a greater impact on the inequalities than between region. Freight turnover was the main driving factor of TFCEP in the transportation industry, followed by the energy intensity and per-capita GDP. In the Eastern and Western regions, freight turnover had the greatest impact on TFCEP, while in the Central and Northeastern regions, urbanization rate and energy intensity were the dominant factors, respectively. The interactions between energy intensity and freight turnover were highly influential. This paper provides important insights for different regions to formulate targeted carbon emission reduction policies.

Does the promotion pressure on local officials matter for regional carbon emissions? Evidence based on provincial-level leaders in China.

This paper constructs data from 30 provinces in mainland China from 1997 to 2016 and mainly adopts panel data fixed effects models to investigate how the promotion pressure on local officials affects regional carbon emissions. Our empirical results show that the relationship between the promotion pressure on local officials and regional carbon emissions has a dynamic evolution characteristic during our research period. Specifically, the promotion pressure on local officials is positively associated with regional carbon emissions before 2009; however, this relationship weakened after China's carbon emission regulatory policies were strengthened in 2010. Furthermore, our heterogeneity analysis results show that the effect of promotion pressure on regional carbon emissions is moderated by the regional industrial structure, the economic development level, regional innovation capability, the tenure of officials and the age of officials. The conclusions of this study are helpful for understanding the driving factors of regional carbon emissions from the political economy perspective, and they also have implications for the formulation of performance evaluation and carbon emission reduction policies.

The impact of carbon market pilots on air pollution: evidence from China.

As China's economic development enters a transitional stage, the government has put forward higher requirements for efficient air pollution control. Different from the traditional environmental regulation methods, China's carbon market pilots (CMP) can use market mechanism to achieve carbon emission reduction policy goals while also providing more efficient control methods for air pollution. Using the unique daily air pollution data of 324 prefecture-level and above cities in China from December 1, 2013, to December 18, 2017, and matching them with the daily data of carbon allowance trading in each CMP, we employ the time-varying difference-in-differences (DID) method to explore the casual relationship between CMP and air pollution, and its influence mechanism. Our results show that (1) the establishment of CMP can reduce air pollution by at least 4.9%, especially on sulfur dioxide, inhalable particulate matter, fine particles, and carbon monoxide. This conclusion is still robust after we use the instrumental variable (IV) method to deal with endogeneity. (2) Mechanism analysis shows that the reducing effect of CMP on air pollution is achieved mainly through three channels, including energy consumption reducing, technological progressing, and industrial structure upgrading. (3) Since CMP have just been established, government regulation plays a stronger role than the market mechanism in the process of CMP affecting air pollution. However, with the continuous improvement of CMP, the market mechanism has also played an increasingly important dynamic effect.

Examining Effect of Green Transformational Leadership and Environmental Regulation through Emission Reduction Policy on Energy-Intensive Industry’s Employee Turnover Intention in China

This study explored a theoretical model of factors affecting employee turnover intentions in the energy-intensive industry from the perspective of environmental regulation through emission reduction policy. Moreover, we examined whether green transformational leadership has a negative effect on the perception of turnover risk of energy-intensive corporate employees and their turnover intentions; we collected data on 531 employees in the energy-intensive industries in China. Data analysis was conducted using exploratory factor analysis, reliability and validity analysis, stepwise regression model analysis, and a structural equation model to test the research hypothesis. The results revealed that environmental regulation through emission reduction policy has a significant impact on employee perception of turnover risk and turnover intention in energy-intensive industries in China. The perception of turnover risk has a greater effect on the turnover intention among employees than the emission reduction policy. Moreover, we found that the perceived risk of turnover has a mediating effect in the relationship between environmental regulation through carbon emission reduction policy and turnover intention. However, green transformational leadership has an inhibiting effect on the perception of turnover risk and turnover intention among employees. This research has crucial theoretical significance for the transformation of energy-intensive enterprises and promoting the sustainable development of energy-intensive enterprises in China.

Spatial distribution and convergence of provincial carbon intensity in China and its influencing factors: a spatial panel analysis from 2000 to 2017.

Unbalanced and inadequate development in China has resulted in significant temporal and spatial differences in carbon intensity, impeding the achievement of carbon reduction targets. This paper explores the spatial distribution and convergence of China's provincial carbon intensity during 2000-2017 and its influencing factors employing spatial panel techniques. The spatial distribution analysis supports the existence of significant spatial agglomeration and radiation effects in China's provincial carbon intensity, and several provinces play key roles in the spatial distribution of carbon intensity, which are an important focus of carbon emission reduction policies. The results of spatial convergence estimation support that China's provincial carbon intensity presents significant spatial absolute and conditional convergence, and after considering regional differences, the spatial convergence speed is significantly accelerated. Meanwhile, economic level, urbanization, energy consumption structure, and industrial structure have significant spatial radiation effects on carbon intensity, and carbon intensity itself also has a spatial diffusion effect, indicating that carbon emission reduction requires multi-regional coordinated actions. This paper examined the spatial distribution and convergence of China's provincial carbon intensities over 2000-2017. The empirical findings verified the spatial agglomeration and radiation effects, as well as the absolute and conditional spatial convergence of China's provincial carbon intensities, which supports the policy-making related to the carbon reduction in China.

Characteristics of industrial driving effects network and impacts on carbon emissions

To study the impact of industrial driving effects on carbon emissions, this article integrated multiregional input–output theory with complex network theory to construct the industrial driving effect network (IDEN). Then, the impacts of the roles of regions on carbon emissions are quantified by econometric theory. The results show that the core driving effects occur in capital, raw material consumption, and material processing industries, such as the smelting and pressing of ferrous and nonferrous metals. From a regional perspective, 86.28% of driving effects come from central and eastern areas. The top 20% of regions account for 73.64% of the total driving effects. Zhejiang (ZJ) and Guangdong (GD) drive 76.67% of China’s regional development. The different roles of the industrial driving effect have a positive impact on carbon emissions. This study indicates that carbon emission reduction policies should consider the roles of regions in the industrial driving effect.

How Does Carbon Emission Reduction Efficiency Affect Regional Income Inequality? The Mediator Effect of Interregional Labor Flow

Global income inequality is widening and carbon emissions remain high. So, reducing carbon emissions and income gap are urgent challenges. The purpose of this paper is to analysis how carbon emission efficiency influences the region income inequality. The improvement of carbon emission reduction efficiency has widened the regional income inequality with the flow of high-tech labor as an intermediary variable in China. Methods used in this article are mediating effect model and DEA method. This paper constructs a disposable income model of income and health costs, where health costs are a function of carbon reduction. If income is fixed, then the expectations of disposable income will change as the level of carbon emission reduction changes. This study finds that the disposable income expectations of high-income areas increases, while the disposable income expectations of lower-income areas decrease with the improvement of carbon emission reduction efficiency. High-income regions attract high-income labor from other regions, resulting in the widening of regional income inequality under the constraint of high cost of living. This result is verified by the data of China from 2007 to 2017. The regression model with Geordie coefficient as the dependent variable, carbon emission reduction efficiency as the core independent variable, gravitation of high-tech talent as the mediator variable, and urbanization rate, educational level, social security coverage, and highway and railway traffic mileage as control variables not only verifies the above results but also finds that high-tech talents’ flow is not the only intermediary between carbon emission reduction efficiency and regional income inequality. This paper finds that when the carbon emission reduction efficiency increases by one unit, the income inequality gap of 25 provinces increases by 0.0202 units, provinces with high carbon emission reduction efficiency increases by 0.107 units, and provinces with medium carbon emission reduction efficiency increases by 0.026 units. However, the income inequality gap of provinces with low carbon emission reduction efficiency decreases by 0.0390 units. The carbon emission reduction efficiency of the high and medium carbon emission reduction efficiency groups is proportional to the income inequality, while the low carbon emission reduction efficiency group is the opposite, when the carbon emission reduction efficiency is grouped into high efficiency group, medium efficiency group, and low efficiency group. The reason for this result is that the high carbon emission reduction efficiency of the former attracts high-income high-tech talent, while the latter's narrowing regional income inequality benefits from the reduction costs of health and the government’s ecological compensation. The effective measures to narrow the income inequality are to implement carbon emission reduction policy, industrial policy, education investment policy, and public service policy, according to the above findings.

Production decision-making system for manufacturing enterprises constrained by carbon reduction policies

This paper studies the optimal low carbon production decision system with considered the constraints of carbon emission reduction policy for manufacturing enterprises producing two kinds of products in the free market. Firstly, The research proved the optimal production combination exists and it is unique under the carbon emissions limits, and next, the research analyzed the low-carbon production decision-making system in three situations, which are carbon emission trade decision, green technology input decision, and joint decision. The research results showed that carbon emission permits trade can increase more flexibility to manufacturing enterprises and increase their profits as well. However, the carbon emissions limits set by the government would have an important impact on the production decision system of manufacturing enterprises. Carbon emission permits trade and green technology investment can optimize and improve the production decision system of manufacturing enterprises to a certain extent. Meanwhile, the government's scientific and reasonable formulation of initial carbon quotas would mobilize the enthusiasm and initiative of manufacturing enterprises to participate in carbon emission reduction. The government should also guide and encourage enterprises to invest in and develop low-carbon emission reduction technologies through tax relief, so as to improve carbon emission reduction technologies and its innovations to reduce carbon dioxide emissions.

Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data

In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%–65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis (ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association (LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time.

Spatiotemporal patterns of industrial carbon emissions at the city level

Research on the dynamic distribution characteristics of carbon emissions and their evolution patterns is of importance to unify carbon reduction targets. This study aimed to measure the industrial carbon emissions by energy consumption and the cement production process in Guangdong from 2005–2015, and it empirically analyzed the distribution dynamics and evolution of the inter-regional carbon emissions. It concludes that, there was significant spatial non-equilibrium in the industrial carbon emissions, the carbon intensity in the Pearl River Delta (PRD) was less than that of the peripheral cities, and the results showed that the overall gap in the spatial distribution of the industrial carbon emissions showed an expanding trend with its evolution to the east. Among them, Northern Guangdong showed a downward trend. The carbon emissions of the PRD were greatly reduced with the external strong radiation. The carbon emission reduction policies should be tailored to local conditions according to the development levels.

Carbon reduction decisions under progressive carbon tax regulations: A new dual-channel supply chain network equilibrium model

Since the production process in manufacturing industry is one of the main sources of carbon emissions, most governments have enacted relevant carbon policies to encourage manufacturers to invest in green production technology and reduce carbon emissions. However, the effectiveness of the carbon policy deserves further investigation because the manufacturers focus more on economic profits in actual operations. For this purpose, this paper proposes a dual-channel supply chain network (DCSCN) equilibrium model based on variational inequality theory to examine progressive carbon tax mechanism design of the government and its impacts on the production/pricing and abatement level decisions of the manufacturers in the DCSCN. In addition, this paper also examines the influences of the online channel introduction on supply chain network equilibrium decisions, carbon emissions and profits. We employ the modified projection and contraction algorithm to obtain the numerical solutions for several examples, and analyze the impacts of the key parameters on the equilibrium decisions and derive several managerial insights. The results show that if the government sets the high-level carbon tax and the cut-off value in progressive carbon tax policy appropriately, it can induce the manufacturers to improve abatement level actively; meanwhile the profit maximization goal of the manufacturer and the whole DCSCN can be consistent with the government's low-carbon emission target. Moreover, the introduction of online channel may depress the economic activities and lead to profit loss for the supply chain network but contributes to reducing the carbon emissions under progressive carbon tax policy. The conclusions may be useful for reference in the study of the low-carbon supply chain and the design of carbon emission reduction policy for government.

The Impact of Different Government Subsidy Methods on Low-Carbon Emission Reduction Strategies in Dual-Channel Supply Chain

With the implementation of national carbon emission reduction policies and the development of online shopping, manufacturers are making low-carbon efforts and selling products through dual channels. This paper constructs a dual-channel supply chain decision-making model composed of low-carbon emission reduction manufacturers and retailers and studies the optimal decision-making problem of the supply chain under subsidies by the government based on emission reduction R&D and per unit product emission reduction. The research results show the following: (1) when the government subsidizes emission reduction R&D, the emission reduction will have an impact on retailers’ optimal prices, manufacturers’ optimal wholesale prices, and optimal direct sales channel sales prices. The profit of the manufacturer increases with the increase in carbon emissions, and the profit of the manufacturer increases to a certain level and then appears to decline. (2) When the government adopts a subsidy method based on the emission reduction per unit product, the manufacturer’s wholesale price and the selling price of direct sales channels, as well as the retailer’s own optimal price, will increase with the increase in emission reductions. Retailers’ profits will increase linearly with the increase in carbon emissions. Manufacturers’ profits will first increase in a straight line and then increase in a curve.

Structural evolution of China's intersectoral embodied carbon emission flow network.

Mount of embodied carbon emissions flow along industrial chains and form a complex network. In order to reveal the structure and evolution characteristics of embodied carbon emission flow network among China's industrial sectors, this study applies a complex network theory to construct six embodied carbon emission flow networks with 30 sectors on the basis of China's input-output tables from 2002 to 2015. Through the analysis of complex network technology indicators, the overall structural characteristics of the network, the key sectors, and the key flow paths are analyzed. Main results show that six embodied carbon emission flow networks all have the small-world characteristics; there is an industrial cluster phenomenon in the network. During the study period, construction, manufacturing, and service-related industry community are the absorption sites for embodied carbon emissions. Coal- and petroleum-related industry communities are the divergent sites for embodied carbon emissions; moreover, electric and heat power and fuel processing are the important "suppliers" of embodied carbon emissions; construction and other service are the important "consumers" of embodied carbon emissions. Non-metallic products are the important "transmitters" of embodied carbon emissions. Metal smelting and chemical industry are at the core of the network because of their high weighted degree and betweenness centrality. The central effect of key sectors continues to increase over time; furthermore, the distribution of embodied carbon emission flows in the six networks all have long-tail characteristics, and this characteristic became more prominent over time. There are key edge-weights in the networks. About 11 to 15% of the edges carry 80% of the embodied carbon emissions. Further based on edge-weight analysis, this study identifies the key paths of embodied carbon emission flow in the six networks, and most key paths pass through construction. Thus, such key sectors and key flow paths should receive more attention when making carbon emission reduction policies.