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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]

This study presented life cycle water footprints (WFs) of biofuels from biomass in China based on the resource distribution, climate conditions, soil conditions and crop growing characteristics, life cycle WFs including blue, green and gray water were evaluated for the selected fuel pathways. Geographical differences of water requirements were revealed to be different by locations. The results indicated that water irrigation requirements were significantly different from crop to crop, ranging from 2- 293, 78-137, and 17-621 m3/ha, for sweet sorghum, cassava, and Jatropha curcas L., respectively. Four biofuel pathways were selected on this basis to analyze the life cycle WF: cassava based bioethanol in Guangxi, sweet sorghum based bioethanol in Northeast China, Jatropha curcal L. based biodiesel in Yunnan and microalgae based biodiesel in Hainan. The life cycle WFs of bioethanol from cassava and sweet sorghum were 3708, and 17 156 m3 per ton of bioethanol, respectively, whereas for biodiesel produced from Jatropha curcas L. and miaroaigae, they were 5787, and 31 361 m3 per ton of biodiesel, respectively. The crop growing stage was the main contributor to the whole life cycle of each pathway. Compared to blue and green water, gray water was significant due to the use of fertilizer during die growing of biomass. From the perspective of the WF, cassava based bioethanol in Guangxi and Jatropha based biodiesel in Yunnan were suitable for promotion, whereas die promotion for microalage based biodiesel in Hainan required improvement on technology. [ABSTRACT FROM AUTHOR]

Abstract: Effective spatial planning is crucial for cost-effectively and sustainably developing biomass energy resources due to the diffuse nature of biomass and high transportation cost. Using the spatial analysis technology, economic models and scenario analysis, this paper presents a spatial planning framework to identify the appropriate developing areas of biomass energy at regional level. The methodology is applied in a case study of Fujian Province, China. Firstly, spatial distribution of two kinds of biomass resources and the technical potential, i.e. the amount of power generation from agricultural and forestry residues in each supply area, were estimated by incorporating the spatial data and the statistical data. The results indicate that total technical potential of agricultural and forestry residues is estimated at 25.13TWhy−1, equivalent to approximately 19% of total electricity consumption in Fujian in 2010. In the second step, the economic analysis assesses the cost of biomass generation for each supply area on the basis of current market conditions. Ranking of the supply areas is then performed by using the priority development index (PDI), which can measure the priority of each biomass supply area by combining several influencing indicators. Finally, the selection of supply areas for power plants can be carried out according to its order in PDI until the total planed capacity in the region is met. The priority of the subregions and the corresponding cost of biomass generation for different planning scenarios can be explicitly visualized. The methodology can be applied to a wide area and can support the local authorities to define and implement a strategy for future biomass energy development. [Copyright &y& Elsevier]