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The shadow price of carbon emissions can measure the marginal output effect under the carbon emission regulation and is also one of the key indicators to construct a low-carbon development path for production units. Currently, international research on shadow price is focused on the industrial and energy sectors. However, in the context of carbon peaking and carbon neutrality targets in China, the use of shadow price to study the cost of reducing emissions from agricultural production, especially forestry fruit industries, is significant. In this paper, we use a parametric approach to construct the quadratic ambient directional distance function. Using the input–output data of peach, we then calculate the environmental technical efficiency and shadow price of carbon emissions from peach production in Guangxi, Jiangsu, Shandong, and Sichuan provinces, and further estimate the values of green output in each province. The results show that (i) the environmental technology efficiency of peach production in Jiangsu province, located in the coastal plain area of eastern China, is the highest among the four provinces, while that in Guangxi province, located in the hilly area of southeast China, is the lowest. (ii) Guangxi province has the smallest carbon shadow price of peach production among the four provinces, while Sichuan province, located in the mountainous area of southwest China, has the largest. (iii) The green output value of the peach production in Jiangsu province is the highest among the four provinces, and that in Guangxi province is the lowest. In order to effectively reduce carbon emissions in peach production without affecting economic benefits, the paper puts forward the following suggestions: for peach-producing areas in the southeast hills of China, it is necessary to increase the application of green environmental technology while reducing the input of production factors in peach production. For peach-producing areas in the northern plains of China, the input of production factors should be reduced. It is not easy for peach-producing areas in the southwest mountains of China to reduce the input of production factors while increasing the application of green technologies. Finally, for peach-producing areas in China's eastern coastal plain, the implementation of environmental regulations for peach production should be gradual. [ABSTRACT FROM AUTHOR]

Green residences have enormous potential for energy savings, emission reduction, and other comprehensive benefits, and their growth is crucial to achieving China's carbon neutrality and carbon peaking targets. Nevertheless, at the moment, the national green residence is impacted by complicated factors at several levels, including government agencies, green residence builders, and green residence consumers, which results in the low-quality development of domestic green residences overall. As of 2020, 94% of all labeled green residences are design-label residences that can only be achieved during the design stage, while less than 10% are operational-label residences with stronger energy and emission-saving benefits. This causes the phenomenon of "green residences on the planning" to be serious. In order to accomplish the promotion of high-quality development of green residences and to promote green residences in China, this paper analyzes the influencing factors of green residence promotion from the multi-level perspective of macro-landscape signals, meso-collective agent green residences, and micro-individual agent consumers, based on the multi-level perspective (MLP) framework of sustainability theory. The paper subsequently builds a simulation model of green residence promotion using the agent-based system dynamics modeling method. Additionally, Jiangsu Province's green residence promotion data are chosen for analogue simulation experiments, and the simulation results are also used to analyze the success conditions as well as the path to green residence promotion. This study demonstrates that (1) the agent-based simulation model of dynamics for the green residence promotion system has high reference value for the simulation of the promotion of green residences, and the model can clearly simulate the impact of micro-individual agent–consumer factors on the promotion of green residences; (2) in order to promote green residences, exterior landscape signals must be continuously improved; the stronger the landscape signals, the quicker the development of operationally labeled green residences; (3) priority is given to the development of two-star design-labeled green residences before 2035, and three-star operationally labeled residences will occupy the majority of the market after 2040. Meanwhile, the duration of landscape signals and the change in behavioral preferences of individual agents must be maintained for a long time. [ABSTRACT FROM AUTHOR]

The achievement of the carbon peaking and carbon neutrality targets requires the adjustment of the energy structure, in which the dual-carbon progress of the power industry will directly affect the realization process of the goal. In such terms, an accurate demand forecast is imperative for the government and enterprises' decision makers to develop an optimal strategy for electric energy planning work in advance. According to the data of the whole social electricity consumption in Jiangsu Province of China from 2015 to 2019, this paper uses the improved particle swarm optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and establishes a metabolic FGM (1, 1) model to predict the whole social electricity consumption in Jiangsu Province of China from 2020 to 2023. The results show that in the next few years the whole social electricity consumption in Jiangsu Province will show a growth trend, but the growth rate will slow down generally. It can be seen that the prediction accuracy of the metabolic FGM (1, 1) model is higher than that of the GM (1, 1) and FGM (1, 1) models. In addition, the paper analyzes the reasons for the changes in the whole society electricity consumption in Jiangsu Province of China and provides support for government decision making. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, China vigorously develops clean energy and renewable energy. As a result, offshore wind power projects have grown rapidly. The success of offshore wind power projects depends on the location of offshore wind power station(OWPS), and this paper aims to develop a hybrid decision-making framework to address the location of offshore wind power stations. Firstly, a comprehensive evaluation attribute system of offshore wind power station site selection is innovatively constructed, including wind resources, construction conditions, economy, environment and risks. Secondly, probabilistic linguistic term set(PLTS) is used to describe uncertain information, which improves the reliability of decision information. Thirdly, The Best-worst method (BWM) based on probabilistic language term sets determines the weights of attributes, which ensures the accuracy of the attribute weight. Finally, an extended TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method is proposed to rank the alternatives. The proposed method is applied to the location selection of offshore wind power station in Jiangsu Province, China. Through sensitivity analysis and comparative analysis, it is verified that the proposed model has good stability and applicability. • A new multi-attribute decision-making model is proposed. • Establish the evaluation attribute system of offshore wind power station location. • Expression of evaluation information by probability language. • Probability Language and Best-worst Method Combined to Calculate Attribute Weight. • An improved Interactive and Multicriteria Decision Making method is proposed. [ABSTRACT FROM AUTHOR]

In the context of the high incidence of flooding disputes among neighboring subjects in the basin, exploring the drainage rights trading mechanism and clarifying the pricing method of drainage rights are new ideas to manage flooding disasters. In this study, the trading mechanism of drainage rights is constructed using a bilateral call auction model, in which the price constraint, the control total quantity constraint, the clearing rule, and the matching rule are explained. In addition, we adopt the wealth utility concept to construct a function, apply the social welfare function to associate the wealth utility functions of both sides of the transaction, and draw on the environmental Gini coefficient concept to construct a pricing model for drainage rights transactions based on fairness and efficiency. Finally, we conduct an arithmetic simulation of the drainage rights trading mechanism and transaction pricing for China's Jiangsu section of the Huaihe River Basin. The study's results show that the trading mechanism model can give the optimal trading scheme when multiple subjects are trading drainage rights. This fills the gap in existing studies and can lead to efficient trading of drainage rights. At the same time, the pricing model can give the optimal transaction price that considers efficiency and fairness, providing a more practical pricing theory for drainage rights trading. [ABSTRACT FROM AUTHOR]