Particulate emission factors for mobile fossil fuel and biomass combustion sources
2011
Watson, John G. | Chow, Judith C. | Chen, L.-W Antony | Lowenthal, Douglas H. | Fujita, Eric M. | Kuhns, Hampden D. | Sodeman, David A. | Campbell, David E. | Moosmüller, Hans | Zhu, Dongzi | Motallebi, Nehzat
PM emission factors (EFs) for gasoline- and diesel-fueled vehicles and biomass combustion were measured in several recent studies. In the Gas/Diesel Split Study (GD-Split), PM₂.₅ EFs for heavy-duty diesel vehicles (HDDV) ranged from 0.2 to ~2g/mile and increased with vehicle age. EFs for HDDV estimated with the U.S. EPA MOBILE 6.2 and California Air Resources Board (ARB) EMFAC2007 models correlated well with measured values. PM₂.₅ EFs measured for gasoline vehicles were ~two orders of magnitude lower than those for HDDV and did not correlate with model estimates. In the Kansas City Study, PM₂.₅ EFs for gasoline-powered vehicles (e.g., passenger cars and light trucks) were generally <0.03g/mile and were higher in winter than summer. EMFAC2007 reported higher PM₂.₅ EFs than MOBILE 6.2 during winter, but not during summer, and neither model captured the variability of the measured EFs. Total PM EFs for heavy-duty diesel military vehicles ranged from 0.18±0.03 and 1.20±0.12g/kg fuel, corresponding to 0.3 and 2g/mile, respectively. These values are comparable to those of on-road HDDV. EFs for biomass burning measured during the Fire Laboratory at Missoula Experiment (FLAME) were compared with EFs from the ARB Emission Estimation System (EES) model. The highest PM₂.₅ EFs (76.8±37.5g/kg) were measured for wet (>50% moisture content) Ponderosa Pine needles. EFs were generally <20g/kg when moisture content was <20%. The EES model agreed with measured EFs for fuels with low moisture content but underestimated measured EFs for fuel with moisture content >40%. Average EFs for dry chamise, rice straw, and dry grass were within a factor of three of values adopted by ARB in California's San Joaquin Valley (SJV). Discrepancies between measured and modeled emission factors suggest that there may be important uncertainties in current PM₂.₅ emission inventories.
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