A Study Of The Estimation Of PM2.5 Emission Factors Induced By Different Vehicles Based On Tunnel Test Method

At present,China has begun the process of transforming from a transportation country into a transportation powerful country.According to relevant statistics,by the end of 2019,the national highway mileage has reached 5.013 million kilometers,and the number of motor vehicles has reached 384 millions.The progress of society and economy brings not only the appearance of prosperity,but also increasingly serious air quality problems.Beijing,as the capital of China,has suffered from traffic pollution.Therefore,it is of great significance to obtain the PM2.5 concentrations under different traffic conditions and meteorological conditions in Beijing and estimate the PM2.5emission factors induced by vehicles.Moreover,studies that focus on vehicles emission under frequent haze events in autumn and winter can help understand vehicle emission characteristics and be a supplement of corresponding policies of our government.Focused on the combination of theory and Practice,this study pays equal attention to the field experiment and emission modeling.A series of monitoring experiments are designed and carried out by using the developed particle monitoring equipment based on laser scattering method,and two sets of corresponding models are also established for separate traffic and meteorological scenarios.On the one hand,for normal weather,when the pollution events defined in the study do not occur,this study builts a calibration experimental platform.By comparing the collected environmental PM2.5 concentration data with the reference standard instrument,and introducing meteorological parameters as variables,the equipment calibration models based on multiple linear regression are established.The South Ring Railway Bridge of the South sixth ring road is selected to carry out the tunnel test to obtain emission factors of different vehicle types.The corresponding calculation models are constructed by considering meteorological data,traffic information and PM2.5concentration data together.The parameters and errors of the model are estimated by the least square method and compared with other studies.On the other hand,performance of the particulate matter monitoring equipment and the calculation of emission factors under haze weather are also evaluated.In the tunnel test experiment,meteorological data and vehicle information that meet the definition of haze events are selected and a multiple regression model is established by introducing the secondary particulate matter emission factors from other references.The calculation results of emission factors of light vehicles and heavy vehicles are estimated according to the least square method,and compared with domestic and foreigh research.