Research On CO₂ Emission Estimation And Wood Carbon Sequestration Method Of Urban Road Traffic

Due to the rapid growth of national economy, China’s transportation has been developing steadily since 2000. Transportation using fossil fuel emissions of carbon dioxide accounts for about 30% of the total emissions. Because of the vehicle and energy consumption grew rapidly, carbon dioxide will increase several times than before. The emission of is hard to recycled and it effects the greenhouse greatly. People has regarded the emission of carbon dioxide as an unneglectable problem. Carbon sequestration fixed carbon dioxide from the air into trees so it can largely reduce or prevent greenhouse gases in the air (mainly carbon dioxide). To forecast the carbon fixation can quantitatively show the carbon fixation in the trees in order to evaluate its effect on carbon emissions. The study of carbon sequestration will be essential for low-carbon transportation research.This paper regarded wood carbon sequestration as a method of carbon reduction. Urban road traffic of CO2 emissions calculation model was established to estimate the emissions of motor vehicle on the urban road. It built the BP and GA-BP neural network to predict the annual carbon fixation. The results showed:the BP neural network prediction model’s average relative error and mean square error were 6.82% and 0.5564; GA-BP neural network prediction model’s average relative error and mean square error were 4.73% and 0.2578; multiple linear regression analysis model’s average relative error and mean square error were 20.13% and 4.6950. The BP neural network prediction model and the GA-BP neural network prediction model average relative error and the mean square error was less than the existed multiple linear regression analysis model. GA-BP neural network prediction model has higher precision and smaller error. In the end it combined with previous research content, the carbon dioxide emissions control optimization model has been built based on carbon sequestration aiming at the least carbon cost. Through this model in Yingbin Road of Rizhao calculated the different age of red pine best plant optimization through the analysis of carbon reduction target to determine the minimum 2015 carbon dioxide emissions reductions, it was concluded that the carbon cost is 0.46yuan/kg and China’s average urban marginal cost is 0.976yuan/kg.Using tree carbon sequestion to achieve CO2 emission reduction’s economic benefit is very considerable.