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Using a dispersion model to estimate emission rates of particulate matter from paved roads
Institution:1. Indian Institute of Tropical Meteorology, Pune, India;2. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy;3. Lancaster Environment Centre, Lancaster University, Lancaster, UK;1. The Joint Graduate School of Energy and Environment, King Mongkut''s University of Technology Thonburi, Thailand;2. Center of Excellence on Energy Technology and Environment, Ministry of Education, Thailand;3. Faculty of Environment and Resource Studies, Mahasarakham University, Thailand;4. Pollution Control Department, Ministry of Natural Resources and Environment, Thailand;5. Department of Industrial Works, Ministry of Industry, Thailand
Abstract:From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM10 from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM10, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT-1 for freeways to about 3 g VKT-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM10 emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT-1; there is some indication that it is about 0.1 g VKT-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM10 emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.
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