The Effect Of Temperature And Relative Humidity On Nanoparticle Number Concentration Of Vehicular Emission

The number of motor vehicles increases year by year, which makes the motor vehicle exhaust become main air pollutants in many cities. Motor vehicle exhaust, especially the particle emission, has a great effect on human health. Some studies show that more than 80% of vehicle exhaust particle emissions is ultrafine particle (Dp <100nm particles) pollution. They have so small size and light weight that they can easily be into human respiratory tract. Particles emitted by vehicles are also toxic. Further more, some particles attaching toxic gases has a great harmful impact on human health. Therefore, studying particles emission of vehicles is of great significance in predicting and assessing the risk of people who expose to streets in city.In this paper, the effect of temperature and relative humidity (RH) on nanoparticles number concentration of vehicular emission in the size range of 20-400 nm is studied using statistical methods. The date set used in this study was collected in a street canyon located in central Stockholm, Sweden. The measurements for particle number concentrations were performed from 1 June 2002 to 31 January 2003 at two sites. The first site is an urban canyon street monitoring site at HG. The second site corresponds to the urban background site of RG. Measurements of hourly-average particle number concentration and particle spectrum and traffic flow rate were conducted at the two monitoring sites.Meteorological conditions were observed at meteorological located 500 from the HG street canyon. The overall particles with diameter range of 20-400 nm was divided into four size classified intervals:20-32 nm, 32-50 nm,50-126 nm, and 126-400 nm particles, which are denoted as N20-32, N32-50, N50-126 and N126-400, respectively.The variables used for statistic analysis in this study are particle number concentration, traffic volume, and meteorological parameters including wind velocity, relative humidity and temperature. The degree of linear relationship between each pair of variables is assessed using the correlation analysis. Factor analysis method is used in this study to assess multivariate effects to get the degree between each pair of variables, and to analyze the indirect effect of temperature and relative humidity on the ND1-D2. The nonparametric regression tree method is used to explore interaction among variables more carefully. The results show that there is a negative relationship between temperature and particle number concentrations, and a positive correlation between relative humidity and N126-400.When temperature is more than 9.47℃, temperature has an obvious effect on the nuclei mode particle number concentration (N20-32). The higher temperature, the lower nuclei mode particle number concentration. However, with the increase of particle size, influence of temperature on particle number concentration decreases. When relative humidity is greater than 91.25%, N126-400 depends on relative humidity greatly. There is no significant correlation between classified particle number concentration,N20-126, and relative humidity.