Simulation and prediction of CO2 emission reductions of biogas industry in China

Abstract: Biogas project is a key program to renewable energy construction in China. As a daily-consumed energy for livelihood, biogas can substitute traditional energy and provide clean energy for rural residents, which can reduce the emissions of greenhouse gases such as CO2, CH4, et al. The CO2 emissions by biogas utilization are always calculated by IPCC methods, while, the CO2 emissions reduction (CO2 ER) by biogas utilization should be calculated by many indexes, such as living energy structure, biogas development conditions, the calorific value, used way, converting efficiency and carbon emissions coefficient of biogas and substituted fuel. It is a complicated process with large amount of manpower and material resources consumed. Therefore, it would be very useful to develop a simple and fast method to estimate CO2 emissions reduction by biogas utilization. This thesis research is about the application of composite regression method in estimating the process of CO2 emissions reduction by biogas utilization; the research indices include biomass resource, structure of rural living energy, and biogas development condition. The results showed that the amounts of rural household biogas digester, biogas production per household and the digester volumes of middle-scale biogas project were significant impact factors of CO2 emissions reduction by biogas utilization in China. Among which, there was prominent linear relation between the amounts of rural household biogas digester and CO2 emission reductions with correlation coefficient (R2) equal to 0.992 and error rate less than 5%, S function relations between biogas production per household and CO2 emission reductions with correlation coefficient (R2) of 0.677 and error rate below 5%, and linear relation between the digester volumes of middle-scale biogas project and CO2 emissions reduction with correlation coefficient (R2) of 0.977 and error rate less than 2%. It indicated that all the simulation results were trustworthy and useful, that was to say the composite regression model that composed by multiple linear regression and curve fitting could effectively reflect the numerical relations between CO2 emissions reduction and influencing factors, also could be applied to predict the CO2 ER by biogas utilization. According the 12 th Five Year Development Program for Renewable Energy, the prediction results based on the method above indicated that the CO2 emissions reduction of biogas utilization could reach 6.18×107-1.38×108 t in 2015. It is an effective way for keeping important station of reducing greenhouse gas emissions to strengthen research on biogas utilization technology, and promoting biogas project development in livestock farms.