Multi-objective optimization of VOCs and NOx co-reduction strategies under carbon emission constraints: A petrochemical case study in China

PurposeUnder the carbon regulation mechanism, managing operational strategies is a challenging task. Green innovation is introduced into a hybrid system of manufacturing and remanufacturing to handle the carbon emission constraints in a dynamic market environment. This paper aims to investigate the joint dynamic green innovation policy and pricing strategies in a hybrid manufacturing and remanufacturing system.Design/methodology/approachThis paper first considers a monopolistic manufacturer who offers brand-new products and remanufactured items at the same price to consumers. Subsequently, the authors extend their analyses to distinct pricing strategies for both newly manufactured products and refurnished ones in such a hybrid system. Two different cases are considered: a loose carbon emission constraint and a binding carbon emission constraint. By solving the dynamic optimization problem, the differential game and Pontryagin’s maximum principle are used to obtain the joint green innovation and pricing strategies.FindingsThe retail price first increases then declines over a single period. The green innovation diminishes in the same pricing decision model, while it first increases then declines in a distinct pricing decision model over a single planning horizon. The green innovation investment as well as the retail price are discouraged by an emission cap and recycling fraction. The distinct retail price fluctuates violently, and they are, in descending order of the highest peak price as follows: the newly manufactured product, the same pricing product and the repaired product. Carbon emission caps that are either too high or too low decrease the revenue of the manufacturer. A small emission constraint margin benefits the manufacturer. The recycling policy, as well as other parameters, affects whether the hybrid system attains the carbon emission constraint or not, which suggests that the recycling policy is complementary to the carbon emission constraint mechanism in the hybrid system.Practical implicationsThese results offer managerial implications to the hybrid system in terms of green innovation, pricing strategies and recycling policy.Originality/valueThis paper is among the first papers to research the joint dynamic green innovation policy and pricing strategies with/without a carbon emission constraint in a hybrid manufacturing and remanufacturing system with a differential game. Moreover, this paper presents a potential way of investigating other common resource constraints by a differential game in a manufacturing/remanufacturing system or closed loop supply chain.

Efficiency of urban water supply under carbon emission constraints in China

In recent years, deep learning and reinforcement learning algorithms have attracted wide attention in the field of power investment and planning. This paper takes the low-carbon power investment model in the process of power investment as the research object, and analyzes the influence of carbon emission and coal burning constraints on power investment. Firstly, the optimal power investment model considering coal supply constraint and carbon emission constraint is established. Then, considering the advantages of deep learning and reinforcement learning algorithms, a deep deterministic policy gradient (DDPG) algorithm is proposed to select and optimize power investment schemes. Finally, the effectiveness of the proposed model and algorithm is verified by the sensitivity analysis of an example.

Carbon emission constraints and trading policies in e-commerce environments have brought huge challenges to the operation of supply chain enterprises. In order to ensure the good operation of the e-commerce supply chain in a low-carbon environment, a supply chain scheduling optimization method based on integration of production and transportation with carbon emission constraints is proposed; we use it to analyze the impact of centralized decision-making mode and decentralized decision-making mode on supply chain scheduling and establish a scheduling optimization model that aims at optimal carbon emissions and costs. A multilevel genetic algorithm was designed according to the characteristics of the model, and numerical examples are used to verify the effectiveness of the model and algorithm. The results show that the centralized decision-making mode plays the role of the carbon emission constraints to the greatest extent; the carbon emissions and the cost are smallest in the centralized decision-making mode. The decentralized decision-making mode leads to the overall cost preference of the supply chain due to separate decisions made by enterprises, and the carbon emissions in the supply chain are greater. Transportation experts, business managers and government departments are interesting for integrated production and transportation scheduling in e-commerce supply chain with carbon emission constraints. Further research should address integrated production and transportation scheduling in dual-channel low supply chains.

Manufacturing/remanufacturing decisions for a capital-constrained manufacturer considering carbon emission cap and trade

In the light of recent knowledge about the seriousness of climate change, a lot of attention is being paid to low carbon societies, which reduce their carbon emissions. On the other hand, in terms of sustainability, some countries are seeking a dematerialized society. Such a dematerialized society aims to reduce material inputs and waste discharge. The question follows as to how these two types of societies are related. Presumably, the carbon emission in a dematerialized society can be expected to be lower than in a non-dematerialized society. However, just how much lower? This study answers to this question with a quantitative analysis by using a global CGE (Computable General Equilibrium) model. The CGE model has the advantage that it can analyze a whole economic system, its energy use and CO2 emission consistently. We conduct scenario analysis using this CGE model. Four comparative scenarios are simulated; (1) business as usual without carbon emission constraints, (2) dematerialization without carbon emission constraints (3) business as usual with carbon emission constraints, and (4) dematerialization with carbon emission constraints. For each scenario CO2 emissions and material inputs for the whole society are estimated and analyzed. The time period covered is from 2005 to 2050 and the target area is the world divided into 12 regions. In this study, we focus on steel as an indicator of the dematerialization. For developing a dematerialized society scenario, we examine changes in investment and assume other materials are substituted for steel. There are two main findings. One is that dematerialization certainly reduces the CO2 emission globally, especially in Asian developing countries and reduces the carbon cost. The other is that even though dematerialization contributes to the development of a low carbon society, there still seems to be difficulties in achieving a large CO2 emission reduction. Energy and Sustainability III 315 www.witpress.com, ISSN 1743-3541 (on-line) WIT Transactions on Ecology and the Environment, Vol 143, © 2011 WIT Press doi:10.2495/ESUS110271

Study on agricultural water resource utilization efficiency under the constraint of carbon emission and water pollution

Multi-period closed-loop supply chain network equilibrium with carbon emission constraints

Selecting the correct equipment is a multifaceted cost and benefit evaluation process due to the complexity of today’s construction projects and lack of considerations of all factors. Based on the analysis of traditional influence factors on the selection of construction equipments, carbon emission constraints were introduced to facilitate green construction. These factors were divided into three categories, which are certain factors, soft factors and carbon emission constraints, based on their own characteristics. By the classification of the factors, their impact on the selection of the construction equipments was studied in detail, especially the carbon emission constraints was investigated from three aspects: relationship between the emissions of CO2 and fuel consumption, standard and regulations of CO2 and carbon tax. The purpose of this paper is to find the main influence factors and provide a basic theoretical reference to the selection of construction equipments for decision-makers.

Efficiency of China's urban development under carbon emission constraints: A city-level analysis

With the increase of carbon dioxide concentration in the atmosphere, the living environment of human beings is seriously affected. As a high carbon emission industry in China, thermal power enterprises are the key areas of carbon emission reduction in China. This paper first uses Super-SBM model to measure the performance of China's 18 major thermal power enterprises in 2009-2018 from a static point of view. After considering the carbon emission constraints, it analyzes the degree of change in enterprise performance, and finds that the impact of carbon emission constraints on enterprise performance is not absolute. After that, with the help of Malmquist index model, this paper discusses the dynamic changes of thermal power enterprises' performance under carbon emission constraint in recent 10yrs. The results show that the overall performance of carbon emission constraint is in a weak regression stage and summarizes the disadvantages of different enterprises. On the basis of the research conclusion, this paper puts forward countermeasures and suggestions to further improve the performance of Chinese thermal power enterprises under the carbon emission constraints in the future, which is conducive to different enterprises to optimize their own disadvantages.

PurposeThe development of low-carbon production is impeded by the investment costs of green technology research and development (R&D) and carbon emission reduction while facing the uncertain risk of emission reduction investment. With the government's carbon emission constraints, green manufacturers implement the advance selling strategy to increase both profit and reduction level. However, few studies consider the consumer's green preference and emission constraints in advance selling market and spot market independently. The authors' paper investigates the optimal strategies of advance selling pricing and reduction effort for green manufacturers to maximize profits.Design/methodology/approachThe authors' paper designs a stochastic model and investigates the manufacturer's optimal strategies of advance selling price and emission reduction efforts by categorizing different purchasing periods of low-carbon consumers. With the challenges of uncertain demand and government's emission constraints, the authors' develop the non-linear optimization model to investigate the manufacturer's profit-oriented decisions.FindingsThe results show the government's carbon constraints cannot influence the manufacturer's profit, but the consumer's low-carbon preference in the advance selling period can. Interestingly, the manufacturer will make fewer reduction efforts even when the consumers have stronger environmental awareness. In addition, the increasing consumer price sensitivity will exacerbate the profit loss from mandatory emissions reduction. Overall, for achieving a win–win situation between emission reduction and profit growth, green manufacturers should not only consider the sales strategies, market demand, and government constraints in a low-carbon market, but also pay attention to the uncertainty of green technology innovation.Originality/valueWith the consideration of the government's carbon emission constraints, uncertain demand, and low-carbon consumer's preferences, the authors' study innovatively incorporates the joint impacts of advance selling strategy and emission reduction effort strategy and then differentiates between two cases that pertain to the diverse carbon emission regulations.

Energy Supply and demand, and carbon emission constraints are the problems that must be considered in the process of rapid economic development by national and every province. Under the constraints of energy supply and demand, and carbon emissions, there has practical significance to rational allocate regional energy utilization. With carbon pinch method, this paper research the energy allocation of Tianjin, establish analysis model. Considering the overall and regional energy demand and carbon emission constraints, to determine the usage amount of every kind of fossil energy and clean energy, in order to achieve the best energy structure and optimal balance between energy supply and demand. To provide scientific evidence for local government to make reasonable energy supply and carbon emission constraint index.

With the worsen of environmental problems, the carbon emission of the energy system has quickly become the spotlight. However, Most of the existing works focus on the economic dispatch without carbon emission constraints. In this paper, we focus on the economic dispatch with carbon emission constraints. First, a novel mathematical model which characterizes the economic dispatch with carbon emission constraints is given. Then it is followed by the distributed carbon-aware dispatch strategy design based on the singular perturbation system.

Based on the real-time environmental constraints in urban regional construction, this paper constructed a bi-level decentralized low-carbon optimal dispatching model of the urban regional integrated energy system (RIES), including the park integrated energy systems (IESs). In this model, a bi-level optimal allocation model of carbon emission constraints between the urban and the park is proposed for the first time. The upper urban will formulate the real-time carbon emission constraints based on real-time environmental monitoring, decomposing the historical carbon emissions to the lower park IESs; the lower park will meet the real-time carbon emission constraints during optimization. We through the upper urban with the lower park between the bi-level decentralized optimization to ensure that the objective function’s upper urban power, natural gas, and heat distribution network system is minimum total network loss. In addition, it is necessary to ensure the minimum operating cost of each park IESs and focus on how to meet the requirements of the overall environment of urban RIES. Furthermore, we study the influence of optimal allocation strategy of carbon emission constraints on network loss, and operating cost of urban RIES under different scenarios. Then, an improved analytical target cascading (ATC) method is applied to solve the bi-level decentralized optimal dispatching model of urban RIES. Finally, an example under three different scenarios is given to verify the superiority and effectiveness of the proposed model and the improved method.