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In order to achieve the goal of carbon peaking and carbon neutralization, we must vigorously develop renewable energy. As one of the important renewable energy sources, the development and utilization of biomass energy has a high cost, and it is difficult to compete with traditional fossil energy in the early stage of development. Therefore, it is necessary for the government to escort the development of the biomass energy industry through legal means. First of all, on the basis of fully analyzing the development prospects of China's biomass energy, the article sorts out the laws and regulations related to biomass energy in China, and finds the shortcomings. Secondly, this paper draws on the institutional experience of the United States, Brazil, Sweden and other countries with relatively developed biomass energy industry, and provides suggestions for improvement from three aspects: law, policy and administrative system, with a view to supporting China's development of biomass energy industry and realizing the "dual carbon target" theoretically. [ABSTRACT FROM AUTHOR]

This paper proposes the network data envelopment analysis (DEA) model accounting for negative externalities and applies it for decomposition of profit inefficiency in the biomass-agriculture circular system (Bio-AG system). A circular structure of the Bio-AG system which is different from the previously applied network structures is assumed. Since the negative externalities (i.e., pollutant emissions from the biomass industry) occur in the Bio-AG system, the property rights are taken into consideration to model the externalities-adjusted profits. Therefore, the changes in profits due to changes in the property rights (assuming no property rights, allocating property rights to agricultural sector, and allocating property rights to biomass power generation sector) are quantified. Further, the decomposition shows that the biomass power generation sector is less affected by technical inefficiency if contrasted to allocative inefficiency in terms of the profit loss. The findings suggest that the biomass power generation technology influences the profits of the biomass industry. What is more, the inefficient allocation of resources is now the key factor undermining performance of the biomass industry. Therefore, the government should adopt measures to improve the allocation of resources and prevent excessive investments or development of less efficient technologies. [ABSTRACT FROM AUTHOR]

Biofuel production in China suffers from many uncertainties due to concerns about the government's support policy and supply of biofuel raw material. Predicting biofuel production is critical to the development of this energy industry. Depending on the biofuel's characteristics, we improve the prediction precision of the conventional prediction method by creating a dynamic fuzzy grey-Markov prediction model. Our model divides random time series decomposition into a change trend sequence and a fluctuation sequence. It comprises two improvements. We overcome the problem of considering the status of future time from a static angle in the traditional grey model by using the grey equal dimension new information and equal dimension increasing models to create a dynamic grey prediction model. To resolve the influence of random fluctuation data and weak anti-interference ability in the Markov chain model, we improve the traditional grey-Markov model with classification of states using the fuzzy set theory. Finally, we use real data to test the dynamic fuzzy prediction model. The results prove that the model can effectively improve the accuracy of forecast data and can be applied to predict biofuel production. However, there are still some defects in our model. The modeling approach used here predicts biofuel production levels based upon past production levels dictated by economics, governmental policies, and technological developments but none of which can be forecast accurately based upon past events. [ABSTRACT FROM AUTHOR]