Carbon Emission Reduction Policies Research Articles

Operational and environmental decisions for a two-stage supply chain under vendor managed consignment inventory partnership

Supply-chain-based organisations are nowadays facing intense pressure to abide to environmental regulatory requirements while they are striving to be responsive to customers’ needs at the least cost possible. As supply chain activities are among the top contributors to carbon emissions, several recent research works have investigated the impact of carbon regulation policies on economic and environmental supply chain performance. This paper presents integrated economic and environmental models for the one-vendor one-buyer supply chain problem under a vendor managed consignment inventory (VMCI) arrangement. Through the developed models, we study the impacts of two carbon reduction policies, namely carbon cap and carbon tax policies, on supply chain wide costs and carbon emissions. We first provide a much simpler and more compact formulation for the basic single-vendor single-buyer supply chain under VMCI agreement. We also present an environmental-based VMCI model where reduction of carbon footprint is considered as the only objective function. We then extend these two basic models to include each of the two carbon emissions reduction policies. We identify structural properties for the optimal solutions of the two hybrid economic and environmental models and propose algorithms to generate optimal solutions. The results of the computational experiments reveal that the implementation of carbon reduction policies, through carbon cap and carbon tax, may call for the adjustment of the vendor’s production and buyer’s delivery quantities to reduce carbon footprint without significantly increasing the operational costs.

Constructing the Embodied Carbon Flows and Emissions Landscape from the Perspective of Supply Chain

From the perspective of supply chain, benchmarking the embodied carbon flows and emissions landscape is to study the carbon footprint in supply chain production and process management. On the basis of the theory of a green supply chain, this paper conducted its research through the following steps. First, a multi-level supply chain model was proposed and established, and various sectors, production and management processes, and inputs and outputs of different resources were integrated into the supply chain network, and then divided into multiple levels. Second, a multi-level embodied carbon flow and emissions model was established through the Leontief Inverse. Third, based on the operation data of forestry-pulp and paper companies, the embodied carbon flows and emissions at all levels and sectors were estimated and analyzed. Finally, the dismantling and processing methods of complex carbon network structures were explored, the hot-spot carbon sources and paths were obtained, and the low-carbon innovation and development strategies were proposed. The research results show that: (1) Supply chain is a new idea and carrier to study the spatial and state changes of carbon, and also provides a platform for spatial landscape analysis of carbon; (2) The modeling and calculation of carbon flows and emissions offer a new solution of evaluating the environmental performance of companies with high pollution and emission such as forestry-pulp and paper companies, and provide the government effective technical support to implement environmental regulations and formulate carbon emission reduction policies.

Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry

Global climate change is a significant environmental problem. A major trigger of climate change is the excess carbon emissions. Based on 44 scenarios in the second generation of new dry cement technology systems, this paper establishes IPSO-BP model to forecast the carbon emissions peak of China‘s cement industry for 2016–2050 years. The results indicate that China's cement industry only implements capacity reduction plans and the second generation of new dry cement technology systems, so that carbon emissions can reach the peak before 2030. It is up to 19 years ahead of the carbon emissions peak of the basic scenario and the carbon emissions peak is reduced by 38 Mt. Moreover, this paper analyzes the technical combination of the earliest carbon emissions and the lowest carbon emissions. As for the earliest carbon emissions technical combination, China's cement industry carbon emissions will peak at 789.95 Mt in 2021. According to the lowest carbon emissions technical combination, China's cement industry carbon emissions will peak at 742.37 Mt in 2025. Accordingly, the conclusions will be helpful for making carbon emissions reduction policies for China's cement industry.

It is Worth Pondering Whether a Carbon Tax is Suitable for China’s Agricultural-Related Sectors

Studying the characteristics, trends, and evolution of carbon emissions in agricultural related sectors is of great significance for rational formulation of carbon emission reduction policies. However, as an important carbon emission reduction policy, carbon tax has been controversial over whether or not it should be levied on China. Based on this consideration, this paper takes China’s agricultural related sectors as an example and analyzes the degree of carbon tax on macro-environment, macroeconomy, and agricultural sectors during the period 2020–2050 by constructing a 3EAD-CGE (economy-energy-environmental-agricultural-dynamics Computable General Equilibrium) model. The results show that: (1) carbon tax has a time effect, specifically, the short-term effect is better than the long-term. (2) If the incremental rate of carbon tax is carried out alone, it will exert a great influence on the macroeconomy as well as on most of the agricultural related sectors. (3) If a carbon tax is introduced at the same time as indirect taxes are cut (proportionally), the policy will exert a negative impact on agriculture-related sectors that are subsidized. However, the policy will have a positive impact on those nonsubsidized sectors. Finally, based on the results, we put forward some suggestions that are more suitable for the introduction of a carbon tax in China’s agricultural-related sectors.

Heterogeneous impacts of households on carbon dioxide emissions in Chinese provinces

As unequal carbon dioxide emissions exist among households with diverse consumption patterns resulting from different income and spatial contexts, the same carbon emission reduction policies for households will go against the principle of social equality. Though a lot of attention has been paid to estimating the emissions from different income households in previous literature, the full impacts of households on carbon emissions of production sectors through changing income are not well captured. Therefore, for better supporting the fair but different carbon emission reduction policy design for households and provinces, this paper investigates the unequal impacts of households on total emissions and sectoral emissions by specifically taking into account the heterogeneity among different income households in different provinces under the empirical context of China. A combination of semi-closed input-output model and hypothetical extraction method is used here to quantify the unique effect of each income class of households. We find five aspects of seriously unequal impacts of different income households among Chinese provinces: (1) the more responsibility for reducing carbon emissions should be allocated to Shandong, Hebei, Jiangsu, Inner Mongolia, Henan, Guangdong, Shanxi and Liaoning; (2) more unequal impacts on total provincial emissions between urban and rural households in Beijing, Tianjin, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Zhejiang, Guangdong and Chongqing; (3) unequal impacts of urban (or rural) households on total provincial emissions exist among provinces; (4) unequal impacts of households on total provincial emissions exist among income classes and among provinces; (5) unequal impacts of urban households on emissions of sectors exist among provinces. These pictures of the inequality can provide more evidence for making fair but distinguishing carbon emission reduction policies for different income households across Chinese provinces.

Carbon emission reduction and promotion policies considering social preferences and consumers' low-carbon awareness in the cap-and-trade system

Abstract We incorporate social preferences, which are divided into relationship preferences and status preferences, and consumer low-carbon awareness into a supply chain with one manufacturer and one retailer under the cap-and-trade system. First, we suppress the price policies and investigate the manufacturer's carbon-emission reduction strategy and the leading retailer's low-carbon-related promotion strategy with and without the agents' social preferences. Then, we analyze the game dominated by the manufacturer with and without considering pricing policies. We prove that consumer low-carbon awareness improvement incentives channel members to invest in emission reduction and promotion and that this investment is beneficial to member profits and utilities. The channel members' utilities increase with their social preference value. However, their profits, emission-reduction level and promotion level might not necessarily do so. In the manufacturer-led supply chain, wholesale price increases with the retailer's social preference value and decreases with that of the manufacturer. The retail price decreases with the manufacturer's social preference value and increases with that of the retailer. The manners that the leader's decision affects the follower's decision-making and the channel members' social preferences affect their decision-making depend on who the dominator is in the supply chain. In addition, we design a new contract and coordinate the supply chain in the presence of the agents' social preferences. With the contract, the company's utility increment increases with its own social preference value and decreases with that of its cooperator.

Economic Growth Effect and Optimal Carbon Emissions under China’s Carbon Emissions Reduction Policy: A Time Substitution DEA Approach

In this paper, provincial panel data for China during 1995–2015 and the time substitution data envelopment analysis (DEA) model were used to measure the influences of China’s carbon emissions reduction policy on economic growth under various reduction targets and to determine optimal economic growth and optimal carbon emissions of each province. In addition, this paper empirically examines the factors that influence the optimal economic growth and carbon emissions. The results indicate that not all provinces will suffer from a loss in gross domestic product (GDP) when confronted by the constraints of carbon emissions reductions. Certain provinces can achieve a win-win situation between economic growth and carbon emissions reductions if they are allowed to reallocate production decisions over time. Provinces with higher environmental efficiency, higher per capita GDP, smaller populations, and lower energy intensity might suffer from a larger loss in GDP. Therefore, they should set lower carbon emissions reduction targets.

The assessment framework of provincial carbon emission driving factors: An empirical analysis of Hebei Province

The achievement of emission reduction targets in each province is necessary for Chinese government to reach its international obligations. Research on the detailed disaggregate driving factors based on provincial carbon emission changes could inform better carbon emission reduction policies. This paper establishes an assessment framework of provincial carbon emissions drivers using system dynamics modelling and makes an empirical analysis of Hebei Province. The model attempts to simulate the dynamic relationship between carbon emissions generation and suppression through seven subsystems including population economy, secondary industry, and policies. In addition, carbon sinks and carbon markets are also incorporated into this framework. Based on the socio-economic conditions, policy guidance and emission reduction targets of Hebei Province, we analyze the impact of single-factor changes and make a four scenario evaluation to explore the mitigation strategies in the light of provincial level. The simulation results are acquired as listed; (1) The impact of technology and energy structure on emission reduction is seen to be obviously, and excessive reliance on carbon emissions trading could not be generated conducive to emission reduction. (2) The combined effectiveness of driving factors is not equal to the aggregation of simple summation of each single factor. (3) The role of carbon sinks in reducing emissions should not be ignored. Therefore, the results of empirical analysis show that targeted emission reduction measures should be formulated according to the actual carbon emission sources. Policy implications in terms of our study results are recommended alternatively.

Analyze the energy consumption characteristics and affecting factors of Taiwan's convenience stores-using the big data mining approach

This study applies big data mining, machine learning analysis technique and uses the Waikato Environment for Knowledge Analysis (WEKA) as a tool to discuss the convenience stores energy consumption performance in Taiwan which consists of (a). Influential factors of architectural space environment and geographical conditions; (b). Influential factors of management type; (c). Influential factors of business equipment; (d). Influential factors of local climatic conditions; (e). Influential factors of service area socioeconomic conditions. The survey data of 1,052 chain convenience stores belong to 7-Eleven, Family Mart and Hi-Life groups by Taiwan Architecture and Building Center (TABC) in 2014. The implicit knowledge will be explored in order to improve the traditional analysis technique which is unlikely to build a model for complex, inexact and uncertain dynamic energy consumption system for convenience stores. The analysis process comprises of (a). Problem definition and objective setting; (b). Data source selection; (c). Data collection; (d). Data preprocessing/preparation; (e). Data attributes selection; (f). Data mining and model construction; (g). Results analysis and evaluation; (h). Knowledge discovery and dissemination. The key factors influencing the convenience stores energy consumption and the influence intensity order can be explored by data attributes selection. The numerical prediction model for energy consumption is built by applying regression analysis and classification techniques. The optimization thresholds of various influential factors are obtained. The different cluster data are compared by using clustering analysis to verify the correlation between the factors influencing the convenience stores energy consumption characteristic. The implicit knowledge of energy consumption characteristic obtained by the aforesaid analysis can be used to (a). Provide the owners with accurate predicted energy consumption performance to optimize architectural space, business equipment and operations management mode; (b). The design planners can obtain the optimum design proposal of Cost Performance Ratio (C/P) by planning the thresholds of various key factors and the validation of prediction model; (c). Provide decision support for government energy and environment departments, to make energy saving and carbon emission reduction policies, in order to estimate and set the energy consumption scenarios of convenience store industry.

Carbon emission reduction and pricing policies of a supply chain considering reciprocal preferences in cap-and-trade system

The traditional self-interest hypothesis is far from perfect. Social preference has a significant impact on every firm’s decision making. This paper incorporates reciprocal preferences and consumers’ low-carbon awareness (CLA) into the dyadic supply chain in which a single manufacturer plays a Stackelberg-like game with a single retailer. This research intends to investigate how reciprocity and CLA may affect the decisions and performances of the supply chain members and the system’s efficiency. In this study, the following two scenarios are discussed: (1) both the manufacturer and the retailer have no reciprocal preferences and (2) both of them have reciprocal preferences. We derive equilibriums under both scenarios and present a numerical analysis. We demonstrate that reciprocal preferences and CLA significantly affect the equilibrium and firms’ profits and utilities. First, the optimal retail price increases with CLA, while it decreases with the reciprocity of the retailer and the manufacturer; the optimal wholesale price increases with CLA and the retailer’s reciprocity, while it decreases with the manufacturer’s reciprocity. The optimal emission reduction level increases with CLA and the reciprocity of both the manufacturer and the retailer. Second, the optimal profits of the participants and the supply chain increase with CLA, the participants’ optimal profits are concave in their own reciprocity and increase with their co-operators’ reciprocity. Third, the participants’ optimal utilities increase with CLA and their reciprocity. Finally, the supply chain efficiency increases with the participants’ reciprocity, while the efficiency decreases with CLA.

Evaluating the effects of environmental regulations on a closed-loop supply chain network: a variational inequality approach

Global climate change has encouraged international and regional adoption of pollution taxes and carbon emission reduction policies. Europe has taken the leadership in environmental regulations by introducing the European Union Emissions Trading System (EU-ETS) in 2005 and by promoting a set of policies destined to lower carbon emissions from energy, industrial, and transport sectors. These environmental policies have significantly affected the production choices of these European sectors. Considering this framework, the objective of this paper is to evaluate the effects of the application of environmental policies in a multitiered closed-loop supply chain network where raw material suppliers, manufacturers, consumers, and recovery centers operate. In particular, we assume that manufacturers are subject to the EU-ETS and a carbon tax is imposed on truck transport. In this way, the developed model captures carbon emission regulations, recycling, transportation and technological factors within a unified framework. In particular, it allows for evaluating the impacts of the considered environmental regulations on carbon emissions, product flows, and prices. The proposed model is optimized and solved by using the theory of variational inequalities. Our analysis shows that the combined application of the EU-ETS at the manufacturers’ tier and the carbon tax on truck transport implies additional costs for producers that reduce their good provisions. On the other side, this has a positive outcome for the environment since $$\hbox {CO}_2$$ emissions reduce. Moreover, an increase of the efficiency level of the recycling process increments the availability of reusable raw material in the reverse supply chain. Finally, the distance between a couple of CLSC tiers plays a very important role. The lower is the distance covered by vehicles, the higher is the production of goods and the lower is the amount of $$\hbox {CO}_2$$ emitted.

Optimal Implementation Strategy of Carbon Emission Reduction Policy Instruments in Consideration of Cost Efficiency

Abstract In this paper, regulatory and optimum programming model has been adopted. Considering the costs of emission reduction, supervision and penalty, we went all out to analyze the optimal decision of cost efficiency of regulators when implementing these three policy instruments: carbon emission standards, carbon emission trading permissions, and carbon taxes as well. Its result has indicated: In strict accordance with control target of total carbon emissions, regulators are willing to render social and economic cost able to achieve the goal of optimal cost efficiency by regulating carbon emission standards and supervising marginal cost caused by variations in the probability; fortunately, under the conditions of low supervisory cost and certain criteria which is met, the implementation of carbon emission trading permissions could provide social and economic cost with opportunities to realize that objective; through comparative analysis, carbon emission trading permissions have the advantages of higher efficiency than carbon emission standards on the premise of incomplete information. During the implementation of carbon taxes strategy, when there exists uncertainty information in the enterprises reduction behaviors, the condition which enterprises can fully comply with is the tax rate level is not higher than marginal penalty function; the tax rate level of enterprises perfect compliance ought not to be lower than the division of marginal penalty cost and marginal supervisory cost. The optimal strategy of enterprises imperfect compliance is that regulators varying the marginal cost of emission standards is equal to varying that of supervisory probability.

Awareness of health co-benefits of carbon emissions reduction in urban residents in Beijing: a cross-sectional survey

Objective: To understand the awareness of the health co-benefits of carbon emission reduction in urban residents in Beijing and the influencing factors, and provide information for policy decision on carbon emission reduction and health education campaigns. Methods: Four communities were selected randomly from Fangshan, Haidian, Huairou and Dongcheng districts of Beijing, respectively. The sample size was estimated by using Kish-Leslie formula for descriptive analysis. 90 participants were recruited from each community. χ(2) test was conducted to examine the associations between socio-demographic variables and individuals' awareness of the health co-benefits of carbon emission reduction. Ordinal logistic regression analysis was performed to investigate the factors influencing the awareness about the health co-benefits. Results: In 369 participants surveyed, 12.7% reported they knew the health co-benefits of carbon emission reduction. The final logistic regression analysis revealed that age (OR=0.98), attitude to climate warming (OR=0.72) and air pollution (OR=1.59), family monthly average income (OR=1.27), and low carbon lifestyle (OR=2.36) were important factors influencing their awareness of the health co-benefits of carbon emission reduction. Conclusion: The awareness of the health co-benefits of carbon emissions reduction were influenced by people' socio-demographic characteristics (age and family income), concerns about air pollution and climate warming, and low carbon lifestyle. It is necessary to take these factors into consideration in future development and implementation of carbon emission reduction policies and related health education campaigns.

Taking climate, land use, and social economy into estimation of carbon budget in the Guanzhong-Tianshui Economic Region of China.

Carbon sequestration is an indispensable ecosystem service provided by soil and vegetation, so mapping and valuing the carbon budget by considering both ecological and social factors is an important trend in evaluating ecosystem services. In this work, we established multiple scenarios to evaluate the impacts of land use change, population growth, carbon emission per capita, and carbon markets on carbon budget. We quantified carbon sinks (aboveground and belowground) under different scenarios, using the Carnegie-Ames-Stanford Approach (CASA) model and an improved carbon cycle process model, and studied carbon sources caused by human activities by analyzing the spatial distribution of human population and carbon emission per capita. We also assessed the net present value (NPV) for carbon budgets under different carbon price and discount rate scenarios using NPV model. Our results indicate that the carbon budget of Guanzhong-Tianshui Economic Region is surplus: Carbon sinks range from 1.50×1010 to 1.54×1010t, while carbon sources caused by human activities range from 2.76×105 to 7.60×105t. And the NPV for carbon deficits range from 3.20×1011 RMB to 1.52×1012 RMB. From the perspective of ecological management, deforestation, urban sprawl, population growth, and excessive carbon consumption are considered as the main challenges in balancing carbon sources and sinks. Levying carbon tax would be a considerable option when decision maker develops carbon emission reduction policies. Our results provide a scientific and credible reference for harmonious and sustainable development in the Guanzhong-Tianshui Economic Region of China.

Analyzing Long-run Relationship between Energy Consumption and Economic Growth in the Kingdom of Bahrain

Since the relation between energy consumption and economic growth is important to design effective energy policies that will promote economic growth, this study investigates the short run dynamics and causality among energy consumption, co2 emissions, oil prices and economic growth in Kingdom of Bahrain. To do so, annual data that covers the period from 1960 till 2015. Empirical work tests for unit root, co-integration relationship using Johansen (1988) approach and then estimate both long and short run dynamics using the vector error correction model (VECM). Results indicate that there is a long-run relationship between the suggested variables. Since economic growth has a predictive power to estimate the energy demand of Kingdom of Bahrain, it is recommended that the government of Bahrain and policy designers shed the light on energy efficiency strategies and carbon emissions reduction policy in the long run without impeding economic growth in order to move towards sustainability.

Carbon emissions in China’s industrial sectors

Environmental input-output (EIO) analysis has been extensively used in researching energy-related CO2 emissions embodied in intermediate production processes. This research used an improved EIO model to analyze the latest adjusted data for emissions from all economic sectors (45 industries) of China in 2012. The construction sector emitted the most consumption emissions, contributing 27.9%, 46.9% and 72.1% to the production emissions from the supply sectors of “Production and Supply of Electric Power and Heat Power”, “Smelting and Pressing of Ferrous Metals” and “Manufacture of Non-metallic Mineral Products”, respectively. The “Production and Supply of Electric Power and Heat Power” sector emitted the most production emissions, contributing 27.9%, 11.6% and 44.2% of emissions from the demand sectors of “Construction”, “Others” and “Manufacturing (No. 8–38)”, respectively. The current policies caused a significant waste of resources. Capital investments were responsible for nearly half of total emissions, and the emissions avoided by imports (22.20%) were approximately equal to the exported emissions (22.95%). Although combustion of raw coal dominated the embodied emissions in most sectors, the composition of embodied CO2 emissions in certain sectors differed significantly. This research provides a more comprehensive picture on sectoral carbon emissions than is currently available; the results will be helpful for making carbon emission reduction policies.

Measurement of carbon dioxide flux from tropical peatland in Indonesia using the nocturnal temperature-inversion trap method

Evaluation of CO2 flux from peatland soil respiration is important to understand the effect of land use change on the global carbon cycle and climate change and particularly to support carbon emission reduction policies. However, quantitative estimation of emitted CO2 fluxes in Indonesia is constrained by existing field data. Current methods for CO2 measurement are limited by high initial cost, manpower, and the difficulties associated with construction issues. Measurement campaigns were performed using a newly developed nocturnal temperature-inversion trap method, which measures the amount of CO2 trapped beneath the nocturnal inversion layer, in the dry season of 2013 at a drained tropical peatland near Palangkaraya, Central Kalimantan, Indonesia. This method is cost-effective and data processing is easier than other flux estimation methods. We compared CO2 fluxes measured using this method with the published data from the existing eddy covariance and closed chamber methods. The maximum value of our measurement results was 10% lower than maximum value of eddy covariance method and average value was 6% higher than average of chamber method in drained tropical peatlands. In addition, the measurement results shows good correlation with groundwater table. The results of this comparison suggest that this methodology for the CO2 flux measurement is useful for field research in tropical peatlands.

The effect of new carbon emission reduction targets on an apartment building in South Korea

A heavily industrial nation, South Korea has one of the highest carbon emission production rates in the world. To participate in the global efforts to reduce carbon emissions, the South Korean government has recently proposed four national targets for carbon emission reduction: 14.7%, 19.2%, 25.7%, and 31.3% from the predicted 2030 BAU level. As the embodied environmental impacts of apartment building are becoming increasingly apparent, this study develops a carbon emission reduction policy model using a system dynamics approach to estimate the required amount of carbon emission reduction of apartment building construction. The results of this study indicate that apartment buildings require the reduction of 190 million kg CO2 for policy one, 248 million kg CO2 for policy two, 332 million kg CO2 for policy three, and 404 million kg CO2 for policy four, respectively, in the year 2030. This study also conducts a sensitivity analysis to investigate the impact of apartment floor demand on the expected total carbon emission amount and the carbon emission reduction amount of an apartment. Based on those results, this study develops a mathematical model for determining the optimal numbers of apartment units.

Measuring the Total-Factor Carbon Emission Performance of Industrial Land Use in China Based on the Global Directional Distance Function and Non-Radial Luenberger Productivity Index

Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development.

Carbon emissions, energy consumption, and economic growth relationship in Sri Lanka

ABSTRACTThis study attempts to investigate the long-run Granger causality relationship between energy consumption, carbon emissions, economic growth, and trade openness in Sri Lanka. Our analysis reveals that, there exists long-run causal relationship between carbon emission and economic growth for Sri Lanka over the period of 1971–2006. In addition, there is unidirectional causality running from economic growth to the carbon emission and energy consumption. The result implies that carbon emission reduction policies will hurt economic growth if no supplementary policies are taken to modify this causal relationship.