Emission Reduction Strategies Research Articles

Spatio-temporal Change in City-level Greenhouse Gas Emissions from Municipal Solid Waste Sector in China During the Last Decade and Its Potential Mitigation

The waste sector is a significant source of greenhouse gas(GHG) emissions and clarifying its emission trends and characteristics is the premise for formulating GHG emission reduction strategies. Using the IPCC inventory model, the GHG emissions from the municipal solid waste(MSW) sector in China during 2010 to 2020 were estimated. The results showed that GHG emissions increased from 42.5 Mt in 2010 to 75.3 Mt in 2019, then decreased to 72.1 Mt in 2020. MSW landfills were the main source of GHG emissions. Further, with the increase in the proportion of waste incineration, the proportion of GHG incineration increased rapidly from 16.5% in 2010 to 60.1% in 2020. In terms of regional distribution, East and South China were the regions with the highest emissions, and Guangdong, Shandong, Jiangsu, and Zhejiang were the provinces with the largest GHG emissions. Implementing MSW classification, changing the MSW disposal modes from landfilling to incineration, improving the LFG collection efficiency of landfills, and using biological functional materials as the cover soil to strengthen the methane oxidation efficiency are the main measures to achieve GHG emission reduction in waste sectors.

Temporal and spatial evolution of agricultural carbon emissions and their impact on functional zoning: evidence from Hubei Province

IntroductionTo investigate the spatiotemporal evolution of agricultural carbon emissions and carbon absorption, analyse the spatiotemporal variations in the carbon balance, delineate carbon-offsetting regions, and formulate low-carbon development strategies tailored to various major functional zones, this study aims to promote coordinated regional ecological and environmental governance.MethodsThis study takes a perspective based on major functional zones, focuses on 17 cities in Hubei Province, studies the spatiotemporal variations in agricultural carbon budgets and carbon offsets in each city from the perspective of functional zoning and proposes a spatial optimization scheme for reducing carbon emissions.Results and discussionThe results show that both agricultural carbon emissions and carbon absorption in Hubei Province gradually increased, although the agricultural carbon budgets varied significantly among cities. Arable lands were the main agricultural carbon sinks in Hubei Province. Overall, carbon emissions exhibited declining core–periphery zonation, with Xiangyang, Jingzhou, and Huanggang serving as the centre (high emissions) and the cities of Shennongjia, Enshi, and Yichang serving as the periphery (low emissions). Carbon absorption displayed a U-shaped distribution, with high values in the east, south, and west and low values in the centre and north. The cities of Yichang, Jingmen, and Huanggang were the peak carbon sink areas. In recent years, the coordination between the agricultural carbon emissions and carbon budgets in Hubei Province has gradually improved, and agricultural carbon absorption and emissions have become increasingly balanced. Seven carbon-positive, five carbon-neutral, and five carbon-negative areas were identified in the province. Based on these findings, differentiated carbon emission reduction strategies were proposed to promote coordinated and low-carbon agriculture.

The quest to mitigation of aviation emissions and pollutions

With the aviation industry's continuous development and commercial air travel's growing popularity, the emissions and pollution resulting from air transportation have experienced a rapid surge. In recent years, as environmental awareness has increased and there has been a growing reflection on the pollution caused by technology, the significance of aviation emissions has been increasingly acknowledged. This article aims to summarize achievements and challenges concerning the current state of aviation emissions and the technologies employed for their reduction. It begins by outlining the present state of aviation emissions, followed by an analysis of common pollutants emitted by the aviation sector, such as NOx, CO, and HC, as well as the mechanisms underlying greenhouse gas emissions and their associated hazards. Furthermore, the article explores several prevalent emission reduction strategies, including applying biofuels, improving combustion chambers, and optimizing flight procedures. Finally, the article provides an outlook on potential future directions for aviation emission reduction technologies.

Study on the spatio-temporal evolution characteristics and driving mechanism of China’s carbon emissions

The present study aims to explore the spatial and temporal changes and drivers of carbon emission patterns in China, with the aim of encouraging county-level carbon reduction policies in pursuit of sustainable development. To this end, we have studied the spatial disparities, spatio-temporal patterns, and evolution characteristics of carbon emissions using county-level carbon emissions data from China between 2002 and 2017. Additionally, we have comprehensively considered the dynamic impacts of both county-level and city-level environmental factors on carbon emissions based on an optimized hierarchical random forest model. The results show that the carbon emissions of China’s counties have generally followed an upward trend before stabilizing. Notable characteristics include elevated carbon emissions in the northern regions and reduced carbon emissions in the southern areas. Additionally, there are higher carbon emissions in the eastern regions compared to lower emissions in the western and inland areas, with discernible local clustering patterns. These findings underscore the importance of tailoring the government’s emission reduction strategy to address the phased variations in carbon emissions across different districts and counties. It is essential to emphasize the key role of major urban agglomerations and metropolitan areas in carbon emission reduction, while also addressing potential emission sources in the resource-rich, yet technologically disadvantaged, northwest region. Furthermore, improving energy efficiency through technological innovation should be the primary means of carbon emission reduction at the county level.

Long-term emission reduction strategy in a three-echelon supply chain considering government intervention and Consumers’ low-carbon preferences

This paper investigates a three-echelon supply chain that consists of a supplier, a manufacturer, and a retailer. Owing to the government intervention and consumers’ low-carbon preferences, the market share is influenced by the carbon emission reduction technology improvement of the supplier and manufacturer and the low carbon advertisement of the retailer. We then construct the differential game model of three-echelon supply chain from the perspectives of decentralized, governmental intervention, supplier cost sharing and governmental intervention, and retailer cost sharing and governmental intervention. Main results are as follows: (1) the manufacturer and supplier's active investment in emission reduction technologies and retailer's advertisement will consistently increase the profits of supply chain members; (2) given that the government subsidizes the manufacturer's carbon emission reduction technology through tax exemption or tax reduction, the manufacturer will always fall into a prisoner's dilemma once the government's carbon emission limit exceeds a certain threshold range; (3) consumer preferences will have a positive effect on manufacturer and supplier's emission reduction strategies, whereas it has nothing to do with retailer's advertisement, and retailer's investment in advertising only depends on manufacturer's subsidy policy; (4) compared with decentralized scenario, Pareto improvement can always be realized whether the manufacturer chooses to cooperate with the supplier or retailer. Our results can provide theoretical basis for the carbon emission strategy of three-echelon supply chain members in low-carbon environment.

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

Deep learning based emulator for simulating CMAQ surface NO2 levels over the CONUS

This study details the development and evaluation of an emulator model of the Community Multiscale Air Quality (CMAQ) model, utilizing a U-Net deep learning architecture to accelerate the simulation of surface NO2 concentrations across the Contiguous United States (CONUS). The emulator employs a subset of meteorological, land cover, and emission input variables identical to those in CMAQ. An initial assessment of the model based on 3-fold monthly cross-validation during the summer (JJA) demonstrates excellent accuracy for 1-h NO2 concentration, with a correlation coefficient (R) of 0.979 and an Index of Agreement (IOA) of 0.989. Subsequently, the model's robustness is examined by training it with NEI 2011 and 2014 data and then evaluating it using NEI 2017 data. This yields an R of 0.949 and an IOA of 0.974. We utilize the emulator to investigate the semi-normalized sensitivity of NO2 concentrations to NOx emissions, which exhibits a satisfactory alignment with CMAQ Decoupled Direct Method (DDM) sensitivities, with an MAE of 0.271 ppb for 1-h sensitivity coefficients. Diurnal cycle analysis of NOx sensitivity coefficients spatially averaged in 15 major urban environments indicates slight over- and underestimations of the morning and evening peaks, respectively, with the MAE varying from 0.27 (Dallas) to 0.92 ppb (Los Angeles). Remarkably, the emulator's computational efficiency significantly surpasses CMAQ's, providing more than 400 times the simulation speed on a single CPU and over 600 times when utilizing both CPU and GPU. As such, the emulator represents a promising tool for efficient CMAQ modeling, with potential applications in health impact assessments, emission reduction strategies, and emission inventory optimization.

Livestock greenhouse gas emission and mitigation potential in China

Livestock is an important source of greenhouse gas emissions (GHGE) in China. Understanding the greenhouse gas (GHG) emission trends and reduction strategies in livestock is crucial for promoting low-carbon transformation of the livestock sector (LS) and achieving the goal of “carbon peak and carbon neutralization”. First, based on the life cycle assessment and IPCC coefficient methods, we calculated the GHGE of the LS in 31 provinces of China from 2000 to 2020 and identified the temporal and spatial evolution of GHG emission intensity. The LMDI method was then used to analyze the influence of efficiency, structure, economy, and population size on GHGE. Finally, the STIRPAT model was used to simulate the future evolution trend of the LS emissions under the SSPs scenario. The results revealed that the GHGE in the life cycle of livestock production decreased from 535.47 Mt carbon dioxide equivalent (CO2e) in 2000 to 532.18 Mt CO2e in 2020, and the main source was CH4 emissions from enteric fermentation of livestock. Economic and efficiency factors markedly influenced the changes in GHGE from the LS in China. Further, economic factors contributed >40% to the increase in GHGE in most provinces. Under the SSP1, SSP2, and SSP4 scenarios, livestock production can achieve the carbon peak target in 2030. Under the baseline scenario (SSP2), the GHGE of China's LS in 2030 and 2060 are expected to be 491.48 Mt CO2e and 352.11 Mt CO2e, respectively. The focus of mitigation measures for livestock production in the future is to optimize the production structure of the LS, promote the low-carbon transformation of the energy structure of livestock feeding, and establish an efficient and intensive management model. In addition, we focus on emission reduction in key areas, such as Northeast and Northwest China, while optimizing diet and reducing food waste from the consumer side.

Climate Justice Implications of Banning Air-Freighted Fresh Produce

Background: Airfreight transport refers to the shipment of goods by air from one location to another and is often perceived as a contributor to global carbon emissions. The environmental impacts associated with airfreight are of notable and genuine concern. Such concerns have often led to calls for measures to ban or limit air freight as a mode of transportation for goods. Whilst the majority of these calls are perceived to be well placed, it is nevertheless essential to acknowledge the climate justice implications associated with such measures, particularly in the context of perishable products like fresh produce. Methods: The aim of this study is to thoroughly examine the socioeconomic implications of banning air-freighted fresh produce and to recommend practices that can minimize the environmental impacts. Utilizing Blue Skies Holdings Ltd., Pitsford, UK as a case study, this paper undertakes a comprehensive analysis of the potential climate justice ramifications associated with the prohibition of air-freighted fresh produce. Results: The analysis highlights the intricate interplay between the environmental and socioeconomic dimensions of the issue. By investigating the carbon emissions attributed to aviation and air logistics in particular and meticulously scrutinizing the possible consequences of an airfreight ban in relation to vulnerable communities within developing economies that are heavily reliant on fresh produce exports, the study contributes insights to guide policy discourse and the decision-making processes within commercial entities with respect to their carbon emissions reduction strategies. Conclusions: Accordingly, this study provides a number of recommendations for various actors, particularly commercial stakeholders, who deal with air-freighted fresh produce.

Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition

Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks.

Assessment of carbon footprint in Qatar's electricity sector: A comparative analysis across various building typologies

Carbon footprint (CF) estimation has emerged as an integral tool for greenhouse gas (GHG) management, providing direction for emission reduction strategies and verification processes. Since capturing the full lifecycle emissions of goods and services at the city level can be methodologically challenging due to the fact that cities have multiple sources of emissions (e.g. transportation, waste, buildings), our study focused on evaluating the carbon footprint of various types of urban buildings across six sectors. This evaluation was conducted in one of the most rapidly urbanized cities in the Middle East, Doha City, Qatar, and was based on electricity consumption data from 2017 to 2020. Using multiregional input–output life cycle assessment (MRIO-LCA) and hot/coldspot analysis, this study identified CF emission spatiotemporal patterns and the major buildings responsible for the highest emissions. The results indicated that residential villas and the commercial sector had the highest electricity consumption and steady increases in CF emissions during the study period, whereas hotels had the lowest annual electricity consumption among all sectors. The study also identified significant CF emission hotspots from Doha residential buildings in the southwestern and northeastern areas. In contrast, the CF hotspots from commercial buildings were concentrated in the industrial area in the southern part of the city and in the West Bay area in the eastern part. Overall, the findings of this study provide important policy implications and a comprehensive assessment of dynamic changes in CF emissions from different building types.

Evaluating provincial carbon emission characteristics under China’s carbon peaking and carbon neutrality goals

This study defines Provincial Carbon Emission Characteristics (PCEC) as the socioeconomic conditions influencing provincial carbon emissions, the potential for carbon neutrality, and carbon management strategies. Given China’s commitment to peak carbon emissions and to achieve carbon neutrality, the development of a robust and versatile PCEC evaluation system is imperative. However, previous studies that rely on single-objective evaluation models are limited. To address this gap, we propose a multi-objective PCEC evaluation system using a novel three-layer approach. This approach enhances the scientific rigor, comprehensiveness, and comparability of PCEC evaluation indicators (PCEC-EIs) by segregating the extraction process into three layers: (1) a factor layer, which identifies critical socioeconomic conditions; (2) a quantitative layer, which selects optimal quantitative indicators for each identified condition; and (3) a standardized layer, which standardizes these indicators, thereby improving their comparability. By applying hierarchical cluster analysis, our study classified 30 Chinese provinces into 7 distinct clusters, each with unique carbon emission characteristics. Further investigation of these clusters across various climate governance issues revealed the versatility of our multi-objective PCEC evaluation system. Our system supports the identification of provinces qualified to reach the emission peak earlier than 2030, differentiation of carbon intensity reduction efforts during the carbon peaking stage, and exploration of various emission reduction pathways to achieve carbon neutrality. Hence, our findings can guide the creation of bespoke emission-reduction strategies for each province; thus, aiding China’s national ambition to achieve peak carbon emissions and carbon neutrality. Importantly, our three-layered approach has broader implications beyond China, potentially assisting other regions or countries in grappling with similar climate-mitigation challenges.

A comprehensive review on methane's dual role: effects in climate change and potential as a carbon-neutral energy source.

The unprecedented population and anthropogenic activity rise have challenged the future look up for shifts in global temperature and climate patterns. Anthropogenic activities such as land fillings, building dams, wetlands converting to lands, combustion of biomass, deforestation, mining, and the gas and coal industries have directly or indirectly increased catastrophic methane (CH4) emissions at an alarming rate. Methane is 25 times more potent trapping heat when compared to carbon dioxide (CO2) in the atmosphere. A rise in atmospheric methane, on a 20-year time scale, has an impact of 80 times greater than that of CO2. With increased population growth, waste generation is rising and is predicted to reach 6 Mt by 2025. CH4 emitted from landfills is a significant source that accounts for 40% of overall global methane emissions.Various mitigation and emissions reduction strategies could significantly reduce the global CH4burden at a cost comparable to the parallel and necessary CO2reduction measures, reversing the CH4burden to pathways that achieve the goals of the Paris Agreement. CH4mitigation directly benefits climate change, has collateral impacts on the economy, human health, and agriculture, and considerably supports CO2mitigation. Utilizing the CO2from the environment, methanogens produce methane and lower their carbon footprint. NGOs and the general public should act on time to overcome atmospheric methane emissions by utilizing the raw source for producing carbon-neutral fuel. However, more research potential is required for green energy production and to consider investigating the untapped potential of methanogens for dependable energy generation.

Emission reduction technologies for shipping supply chains under carbon tax with knowledge sharing

In response to the gradually increasing pressures of global climate change, governments and enterprises around the world are taking proactive measures to encourage the shipping industry to reduce emissions. Meanwhile, knowledge sharing plays an important role in uncertain market environment and has a profound impact on the development of emission reduction strategies. This paper constructs a shipping supply chain consisting of the port and liner company, and explores the impact of carbon tax policies on carbon emission reduction technologies. By using the Stackelberg game model, the benefits of port and liner company are compared and analyzed in order to explore the interrelationship between knowledge sharing and the use of emission reduction technologies. The results of the study show that: (1) Under the conditions of different emission reduction technologies, the state of knowledge sharing has a significant impact on carbon emission benefits, and the determination of the optimal reduction technology is affected by both knowledge sharing and carbon tax rate. (2) Although the impact of knowledge sharing on total carbon footprint is not obvious, it can effectively reduce the redundant carbon footprint. (3) The inclusion of consumers’ green preferences and knowledge sharing in the model is conducive to the port and liner company to realize mutual benefits and win-win situation. The findings of this paper provide a reference for the adoption of emission reduction technologies by shipping supply chain stakeholders under market uncertainty.

Study on the Decoupling Effect of Energy and Carbon Emissions in the Yangtze River Economic Belt under the Dual Carbon Target

To achieve the goal of "double carbon" is the only way for our country to achieve emission reduction strategy. The Yangtze River Economic Belt is one of the strategic support belts for emission reduction, so it is of great significance to study the decoupling effect of energy and carbon emissions. Based on the carbon emission data of the Yangtze River Economic Belt from 1995 to 2021, this paper firstly analyzes the basic characteristics and spatial pattern of carbon emission in the Yangtze River Economic Belt. Secondly, a spatial econometric model is constructed to decompose the main influencing factors of carbon emissions in the Yangtze River Economic Belt, and the main influencing factors of economic and energy decoupling in the Yangtze River Economic Belt are explored by using the canonical correlation analysis method. Finally, BP neural network is used to forecast and analyze the carbon emission of the Yangtze River Economic Belt from 2022 to 2030. The results show that: (1) The center of gravity of carbon emissions in the Yangtze River Economic Belt is gradually shifting to the southeast, and there is a spatial correlation between regional carbon emissions. (2) The strong influencing factors of carbon emission in the Yangtze River Economic Belt are industrial composition and development differences; The influencing factors are city size and resource consumption intensity. The weak factor is the level of energy #consumption. The level of energy consumption and industrial composition are the main influencing factors of economic and energy decoupling in the Yangtze River Economic Belt. (3) Carbon emissions in the Yangtze River Economic Belt will continue to grow from 2022 to 2030, and will grow fastest from 2029 to 2030.

Spatio-temporal dynamic evolution of carbon emissions from land use change in Guangdong Province, China, 2000–2020

Global warming caused by massive carbon emissions poses a serious threat to the environment and human beings. Dynamic monitoring of the spatio-temporal evolution of carbon emissions is an essential way to achieve carbon reduction goals, especially in coastal areas like Guangdong Province faced with dual challenges of massive carbon emissions and rigorous reduction targets. To reveal the spatio-temporal characteristics of carbon emissions and provide a basis for further fine-grained carbon emission reduction strategies, we analyzed spatio-temporal distribution characteristics of carbon emissions in Guangdong Province at the county-level scale from 2000 to 2020. Based on the land-use data obtained from the Data Center for Resources and Environmental Sciences of the Chinese Academy of Sciences and energy consumption data from the Statistical Yearbook, the carbon emission of each county is estimated, and the spatio-temporal evolutionary features of them are explored by a series of methods of the exploratory spatio-temporal data analysis (ESTDA). The shift of spatial distribution characteristics and gravity center is further revealed with the standard deviational ellipse and gravity center migration analysis.The results reveal that the net carbon emissions increased from 6179.229 × 104 tons to 20765.723 × 104 tons during 2000–2020. The net carbon emissions of county-level administrative regions show a significant positive spatial correlation, and the spatial convergence shows a trend of first decreasing and then increasing. The spatio-temporal pattern of carbon emissions has an obvious path dependence and locked spatial features, and shows a gradually strengthening trend. The spatial distribution of carbon emissions formed a stable “northeast-southwest” pattern, and the gravity center of carbon emissions in the past 20 years has been distributed between 113.208°–113.357°E and 22.760°–22.878°N, tending slightly shifting to the northeast. The results of the study can help understand the spatio-temporal evolution of carbon emissions in Guangdong, and provide a reference for formulating effective carbon reduction policies.

CO2 emissions change in Tianjin: The driving factors and the role of CCS

The environmental damage caused by the greenhouse effect is intensified by the continuous rise of carbon dioxide emissions. As a major industrial base in northern China, Tianjin has been emitting more carbon and thus faces a greater challenge to reduce its emissions. To meet the dual carbon goals of Tianjin, it is critical to identify influencing factors of carbon emissions and to find suitable technologies to effectively reduce emissions. In this study, the energy consumption data of Tianjin from 2005 to 2020 were analyzed via the Logarithmic Mean Divisia Index (LMDI). The carbon emission driving factors were decomposed and the contributions of four primary factors, including energy structure, energy intensity, gross domestic product (GDP) per capita, and population to CO2 emissions of this region, were evaluated. The ideal characteristics of the oil reservoirs with low permeability and the suitable carbon dioxide sinks make carbon capture and storage(CCS) technology implementation feasible in Tianjin. Despite this, the effect of CCS technology on CO2 emissions in the future is still uncertain. Thus, the Bass model was firstly introduced to assess the future development trend of CCS technology and its capacity of CO2 emission reduction. The results revealed that energy intensity was the primary contribution to reducing carbon emissions, while GDP per capita was the main contributor to the overall increase of CO2 emissions in 2005–2020. The CCS technology diffusion process is fast, with rapid growth starting in 2030 and reaching growth saturation in 2040. According to the scenario analysis, CCS could make a substantial contribution of 2674.78× 104 tons per year after 2040 to the carbon emission reduction of Tianjin. Therefore, the implementation of energy conservation and emission reduction policies as well as the expansion of CCS projects are essential to ensure that Tianjin achieves its carbon neutrality goal by 2060. This study offers helpful guidance for other cities to forecast their carbon emission reduction trajectories and establish emission reduction strategies.

Does industrial convergence mitigate CO2 emissions in China? A quasi-natural experiment on “Triple Play” Reform

As a crucial aspect of industrial development, the influence of industrial convergence on the environment cannot be ignored. This paper uses the “Triple Play” Reform (TPR) policy as a representative case of industrial convergence for constructing a quasi-natural experimental analysis framework. Using panel data from 285 Chinese cities from 2004 to 2016, we examine the influence of the industrial convergence policy on per capita CO2 emissions using a multi-period difference-in-differences (DID) model. The results indicate that the TPR reduces CO2 emissions in China. Furthermore, the TPR policy indirectly decreases per capita CO2 emissions through industrial structure upgrading and the promotion of green technology innovation. Most importantly, the carbon emission-reduction effect of TPR is heterogeneous according to geographical differences, resource endowment, and city size. The research findings contribute to filling a gap in the literature by demonstrating how industrial convergence policies can mitigate CO2 emissions in China and offer valuable insights for future industrial convergence practices and emission reduction strategies in China.

Research on Transportation Carbon Emission Peak Prediction and Judgment System in China

The transportation sector is a major contributor to carbon emissions, and managing its carbon peak is essential for China to reach the 2030 carbon peak target. This paper uses the autoregressive integrated moving average model (ARIMA) to design baseline scenarios and “double carbon” scenarios (carbon peak and carbon neutrality) based on the accounting of transportation carbon emissions in 30 provinces and cities in China to facilitate regional differentiation and forecast the development trend of transportation carbon emissions. Using the fuzzy comprehensive evaluation method, a comprehensive transportation carbon emission research and judgment system has been developed based on the forecast results. The research indicates a substantial increase in carbon dioxide (CO2) emissions from transport in China over the past 15 years, with an average growth rate of 5.9%, from 387.42 mt in 2005 to 917.00 mt in 2019. In the scenario prediction analysis, the overall carbon emission of the “two-carbon” scenario exhibits varying levels of reduction compared with the baseline scenario. According to the comprehensive research and judgment system, when the comprehensive evaluation index corresponding to the turning point year of transportation carbon emissions is greater than 0.85, and the index remains above 0.85 after the turning point, it can be judged that a region has achieved the peak of transportation carbon dioxide emissions under 95% possibility. It shows that China’s policies and strategies for carbon and emission reduction have played a significant role in transportation, but the low-carbon transformation and development still face great challenges.

Effects of dual-credit policy and subsidy cancellation on decisions in an automotive supply chain

The green development of China's automotive supply chain is driven by policies. This study uses game theory to explore the pricing and emission reduction strategies of the automotive supply chain under dual-credit policy and subsidy policy (scenario DS), as well as dual-credit policy and subsidy cancellation (scenario DC). This study discusses the effects of dual-credit policy and subsidy cancellation on optimal decisions. The results show that increasing the intensity of dual-credit policy hinders the production and emission reduction of H-type fuel vehicles (FVs). Tougher corporate average fuel consumption (CAFC) standards do not affect L-type FVs; however, they can increase the production and emission reduction of E-type FVs. The more stringent production proportion target of new energy vehicles (NEVs) will limit the production of all types of FVs. Subsidy cancellation reduces the wholesale price of NEVs; however, its effects on the selling price and market size of NEVs are uncertain and depend on their respective thresholds. The government should formulate differentiated dual-credit policies based on different types of fuel consumption. This will ensure that FV manufacturers with different types of fuel consumption can reduce their emissions or increase the production of NEVs. Additionally, the government should ensure a smooth transition before subsidy cancellation to prevent negative effects on the NEV market.