Analysis of Carbon Dioxide Concentration in Landfill Based on Field Monitoring and Artificial Neural Network
Landfills produce a large amount of landfill gas,40%-60%of which is CO2.CO2 causes greenhouse effect and reduces the efficiency of landfill gas utilization.Understanding the emission mechanisms of CO2 from the landfill is key to control its dispersion and release.This study inverstigated the CO2 concentration in 2018 of a landfill in Hang-zhou.The concentration of CO2 and H2S showed a strong linear correlation in spring and autumn,with the absolute val-ue of the Pearson correlation coefficient of 0.77 in autumn.Meanwhile,an artificial neural network model based on the multi layer perceptron(MLP)was developed to predict and analyze the concentration of CO2.In order to eliminate the abnormal values,box chart method was used to screen the concentration data for the whole year of 2018.Five in-put indicators including PM2.5,wind speed,wind direction,air temperature and air humidity were finally chosen as the input variables through combination and comparison.The results indicate that the predicted results of the model are in agreement with the field measurement results with about R=0.7.In addition,the missing data in September was ob-tained and the results were consistent with the annual CO2 release law.The MLPNN model established based on the on-site monitoring data can be used to predict and evaluate the carbon dioxide release,which is of great significance for the control of CO2 and other landfill gas emission.
NETL
NSTL
万方数据
维普
