A Study Of The Estimation Of Traffic-induced PM_2.5 On Fast Road Beijing Based Laser Scattering Method

Beijing,China's capital,changes in each passing day with China's industrialization process.The number of motor vehicles has increased to 5.909 million.And traffic congestion and exhaust pollution have become increasingly serious.On the issue of air pollution,PM2.5 is the primary pollutant which can easily enter the human respiratory tract and do harm to human health.Among the main sources of PM2.5,mobile sources account for up to 45%.Therefore,it is necessary to analyze the particulate matter concentrations and distribution under meteorological conditions and traffic conditions.Setting up the relation between environment and traffic by estimating traffic-induced PM2.5 emission factors has theoretical and practical significance.In recent years,pollutant emissions from transportation sources have risen rapidly.This paper is based on the traffic and environmental sciences.The concentration of PM2.5 and CO in the air is monitored by the particle concentration monitoring device KOALA which is applied by laser scattering method.This paper takes the mass conservation theory as the foundation,and combines with real-time collected meteorological information and traffic state information which can establish the model that can estimate traffic-induced PM2.5 emission factors.The thesis includes the following three parts.First,the thesis sets up a calibration experimental platform,selects the Beta attenuation monitor used by the China Academy of Environmental Sciences(CRAES)as a reference instrument.The PM2.5 and CO concentration data are collected simultaneously with the particle concentration monitoring equipment and the reference instrument.This paper establishs the multivariate regression overall mode by taking the influence of temperature and humidity on the measurement of particulate matter concentration.The KOALA equipment was locally calibrated into consideration.Then,the thesis builds a particle monitoring experiment platform under actual road conditions and selects the road section with anti-noise baffle on the Beijing North Fifth Ring Road for on-site experiment.This paper analyzes the correlation and does the K-S test between PM2.5 and CO concentration data measured by experimental road sections.Based on the theory of mass conservation,the thesis establishs a double-box model for calculating the particulate matter emission factor of traffic source and determines the model parameters.Finally,the input data of the model,including the measured values and background values of particle concentration,temperature and humidity data,and traffic flow and speed data are collected,cleaned and integrated.The thesis analyzes the PM2.5 emission characteristics from three aspects:time distribution,weather distribution and traffic distribution.This paper estimates the traffic-induced PM2.5 emission factors within a certain range of driving speed,that is,under steady-state conditions.The model estimation results are compared with the existing literature research results and provide a basis for the macro emission model.