Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City
1Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
2Aerodyne Research Inc., Billerica, MA, USA
3Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, USA
4Molina Center for Energy and the Environment, La Jolla, CA and Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
Abstract. The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are responsible for 97% of mobile source emissions of CO, 22% of NOx, 95–97% of aromatics, 72–85% of carbonyls, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction. Nevertheless, the fuel-based inventory suggests that mobile source emissions of CO and NOx are overstated in the official inventory while emissions of VOCs may be understated. For NOx, the fuel-based inventory is lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory.