Faced with increasing conflicts between economic and environmental development, it is extremely urgent to promote the green growth of enterprises. As an incentive environmental regulation measure, an environmental tax has been proven to effectively alleviate environmental problems and reduce corporate pollutant emissions. From the perspective of environmental tax equity and efficiency, this study collects more than 100,000 enterprises’ pollutant-discharge and pollutant-discharge fee data from 4300 pollutant disposal enterprises in Yunnan Province, China in 2017. The study analyzes the marginal abatement cost (MAC) of water pollution and air pollution in key industries by using the MAC accounting method. Under the three scenarios of low, medium and high tax rates set by the study, the study evaluates the applicable tax rates of environmental tax of enterprises under different tax rates. The main findings of the study are: (1) the MAC of pollutants in various industries is quite different in different industries; (2) the environmental tax rate of 2018 is generally low and is not enough to encourage enterprises to reduce more pollution; (3) most enterprises will not invest a large amount of funds to carry out technological transformation for green production, without the government’s mandatory environmental regulation measure. The study recommends that the government needs to increase the environmental tax rate, gradually approach the cost of corporate pollutant-treatment and force the technological transformation of enterprises. At the same time, the government itself needs to do a good job of tax neutrality, increase the compensation for environmental protection behaviors of enterprises, and encourage green development of enterprises. Finally, the taxation supervision should be strengthened, and the tax violations of enterprises should be checked strictly for avoidance of tax cuts against rules.
Operating rules have been used widely in the reservoir long-term operation duo to its characteristics of coping with inflow uncertainty and easy implementation. And implicit stochastic optimization (ISO) has been widely applied to derive reservoir operation rules, based on linear regression or nonlinear fitting method. However, the maximum goodness-of-fit criterion of fitting method may be unreliable to determine the effective rules. Therefore, this paper develops a self-optimization system dynamics (SD) simulation of reservoir operation for optimizing the operating rules, by taking advantages of feedback loops in SD simulation. A deterministic optimization operation model is firstly established, and then resolved using dynamic programming (DP). Simultaneously, the initial operating rules (IOR) are derived using the linear fitting method. Finally, the refined optimal operating rules (OOR) are obtained by improving the IOR based on the self-optimization SD simulation. China’s Three Gorges Reservoir is used as a case study. The results show that the SD simulation is competent in simulating a complicated hydropower system with feedback and causal loops. Moreover, it makes a contribution to improve the IOR derived by fitting method within an ISO frame. And the OOR improve effectively the guarantee rate of power generation on the premise of ensuring power generation.
This paper aims to explore the evolution of bioenergy from a comprehensive and dynamic perspective and study how stakeholders in the industry exert influence during the development. Taking the development of bioenergy in the Yangtze River Delta as an example, the research builds a dynamic network of bioenergy stakeholders from a social network analysis method. This paper selects six typical cities and six stakeholder groups in the Yangtze River Delta to conduct field surveys and interviews. This study integrates social network analysis with multilevel perspective theory to analyse the evolution of bioenergy from a dynamic perspective. The results show that the relationship among the stakeholders is a network based on central stakeholders involved in the material flow and is affected by multiple peripheral stakeholders. Through the analysis of the dynamic evolution relationship between stakeholders, this paper reveals the existing problems during the development of bioenergy in the Yangtze River Delta. The research results also show that the development of bioenergy has the following characteristics: (i) It is initiated by technological development during the energy transition period; (ii) It is led by policy formulation; (iii) It has evolved with the development of material flow, marketing, infrastructure, and social awareness.
This study aimed to explore the impact of the interaction between stakeholders in the sustainable development of the biomass industry and to reveal network issues relating to material flow and information flow under the current biomass energy development model. This study focused on the agriculture and forestry waste power generation industry. Taking the biomass industry in Nanjing, Suqian, and Yancheng as examples, the study selected six stakeholder groups involved in the industry and conducted field investigations by using semi-open interviews and questionnaires. The research mainly applied social network analysis methods, combined with UCINET software, to draw a network diagram of the stakeholder relationships and to quantitatively analyze stakeholder centrality and overall network density. The results revealed that (1) the biomass enterprises had the highest centrality in the overall network, which played a vital role in the construction of the overall network; (2) the farmers were positioned at the outer fringes of the industrial social network and their information acquisition capabilities and degree of control over the network were the lowest; and (3) the overall network density was low, which showed that the connections between stakeholders were not close enough to support the circulation of material and information in the overall network.
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