中国沼气产业对减排CO2量的模拟与预测

沼气是中国可再生能源建设的重点项目,可提供清洁能源替代化石燃料燃烧,减少温室气体排放,对缓解全球变暖趋势具有重要意义。该文利用复合回归模型对中国沼气行业的CO2减排量(CO2ER)与生物质资源、农村用能结构以及沼气利用现状等指标之间的数值关系进行模拟分析,结果表明:中国户用沼气行业的CO2减排量与沼气池使用量存在显著的线性关系(R2=0.992),与户均产气量存在明显的S函数关系(R2=0.677),大中型沼气工程行业的CO2减排量与池容之间存在显著的线性关系(R2=0.977);经多元线性回归和曲线拟合所得到的复合回归模型对户用沼气行业CO2减排量的拟合较好,各种替代情景下误差率均在5%以内;对大中型沼气工程行业CO2减排量的模拟在2006年后呈现较好的拟合效果,各种替代情景下误差率均在2%以内。依据《可再生能源发展‘十二五’规划》进行预测,2015年中国沼气行业可减少CO2排放6.18×107～1.38×108t。加强沼气科技研发,促使沼气工业化、规模化发展以及提升沼气利用品味,是保持沼气利用CO2减排重要地位的有效途径。

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.