There is a need to quantify real-world particle number emissions from light-duty gasoline vehicles (LDGVs) because of the known toxic properties of ultrafine and nanoparticles, the large number of LDGV on the road, and the lack of field measurements of particle number (not mass) emissions during real-world vehicle operation. On-board tailpipe gas and particle emissions and vehicle operating data were collected second-by-second using an instrumented 1999 Toyota minivan driven on a seventeen-mile test route at least twice in sequence by 22 drivers. Time-series cross-section regression analysis was applied to individual test runs to develop a suitable model for predicting particle number concentration based on gaseous pollutant emissions and sampling conditions. The results indicate that particle number concentration can be effectively predicted by gas emissions, ambient air temperature and relative humidity and exhaust temperature. The model signifies the physical relationships between particle number and gas emissions with respect to gas-to-particle formation processes and implies the possibility of future use of existing gaseous pollutant emissions databases for particle number prediction from a wider range of vehicles.
Samenvatting