Journal article
Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City
Atmospheric chemistry and physics, v 10(8), pp 3629-3644
20 Apr 2010
Featured in Collection : UN Sustainable Development Goals @ Drexel
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 found to be responsible for 97% of total vehicular emissions of CO, 22% of NOx, 95-97% of each aromatic species, 72-85% of each carbonyl species, 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.The resulting fuel-based estimates of emissions are lower than in the official inventory for CO and NOx and higher for VOCs. For NOx, the fuel-based estimates are lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory. While conclusions regarding the inventory should be interpreted with care because of the small sample size, 3.5 h of driving, the discrepancies with the official inventory agree with those reported in other studies.
Metrics
Details
- Title
- Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City
- Creators
- D. A. Thornhill - Virginia TechA. E. Williams - Virginia TechT. B. Onasch - Aerodyne ResearchE. Wood - Aerodyne ResearchS. C. Herndon - Aerodyne ResearchC. E. Kolb - Aerodyne ResearchW. B. Knighton - Montana State UniversityM. Zavala - Molina Center for Energy and the EnvironmentL. T. Molina - Molina Center for Energy and the EnvironmentL. C. Marr - Virginia Tech
- Publication Details
- Atmospheric chemistry and physics, v 10(8), pp 3629-3644
- Publisher
- Copernicus Gesellschaft Mbh
- Number of pages
- 16
- Grant note
- Molina Center for Strategic Studies in Energy and the Environment Fulbright Fellowship National Science Foundation; National Science Foundation (NSF) DE-FG02-05ER63982 / US Department of Energy; United States Department of Energy (DOE) ATM-0528170; ATM-0528227 / US National Science Foundation; National Science Foundation (NSF) National Aeronautics and Space Administration; National Aeronautics & Space Administration (NASA)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemistry
- Web of Science ID
- WOS:000277185400012
- Scopus ID
- 2-s2.0-77951603593
- Other Identifier
- 991020902863904721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Environmental Sciences
- Meteorology & Atmospheric Sciences