Source apportionment of fine particulate matter in Houston, TX, using organic molecular markers

Fraser, Matthew P.; Yue, Z. W.; Buzcu, Birnur

doi:10.1016/s1352-2310(03)00075-x

Cited by 130 publications

(91 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The model provides assessments of the amount of PM 2.5 mass contributed by discrete sources to that receptor site, and it has been demonstrated that the mass of a key organic molecular tracer is linked quantitatively to different source types. 8,177,178,[193][194][195][196] It is important to note that organic compounds simultaneously emitted from many different sources can be used in atmospheric mass balance calculations as long as all of the contributing sources are included in the calculations. Nevertheless, in practice, it is the most unique compounds that clearly differentiate one source from another that adds the most power to the method.…”

Section: Cmb Modelmentioning

confidence: 99%

Review of Recent Advances in Detection of Organic Markers in Fine Particulate Matter and Their Use for Source Apportionment

Lin

Lee

Eatough

2010

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

Fine particulate matter is believed to be more toxic than coarse particles and to exacerbate health problems such as respiratory and cardiopulmonary diseases. Specific organic compounds within atmospheric fine particulate material can be used to differentiate specific inputs from various emissions and thus is helpful in identifying the major urban air pollution sources that contribute to these health problems. Particular marker compounds that carry signature information about different emission sources (i.e., gasoline or diesel motor vehicles, wood smoke, meat cooking, vegetative detritus, and cigarette smoke) are reviewed. Aerosol organic types (e.g., from mass spectrometry data, which can also help in elucidation of carbonaceous material sources) are also discussed. Apportionment of the primary source contributions and atmospheric processes contributing to fine particulate matter and fine particulate organic material concentrations are outlined. This review provides an overview of the latest developments in chemical characterization approaches for identification and quantification of compounds in complex organic mixtures associated with fine atmospheric particles and their use in chemical mass balance (CMB) and positive matrix factorization (PMF) source apportionment models.

show abstract

Section: Cmb Modelmentioning

confidence: 99%

Review of Recent Advances in Detection of Organic Markers in Fine Particulate Matter and Their Use for Source Apportionment

Lin

Lee

Eatough

2010

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

show abstract

“…[57][58][59][60][61] For example, high-temperature EC (e.g., EC2, EC evolved at 740°C in a 98% helium [He]/2% oxygen [O 2 ] atmosphere) dominates particulate emissions from diesel engines. 54 Specific organic markers (Table 2) have also proven useful in PMF modeling studies, [63][64][65][66] but advances are needed to make them more available in source and receptor samples. 61 Modern PM source profiles that include organic compounds were obtained and applied for source apportionment at Fresno 64 and Pittsburgh.…”

Section: Receptor Modeling Proceduresmentioning

confidence: 99%

“…As SOA was not included in the CMB calculations in Houston, calculated mass was lower than the measured mass most of the time. 63 …”

Section: Quantification Of Soamentioning

confidence: 99%

Source Apportionment: Findings from the U.S. Supersites Program

Watson

Chen

Chow

et al. 2008

Journal of the Air & Waste Management Association

222

132

View full text Add to dashboard Cite

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions. INTRODUCTIONReceptor-oriented source apportionment models infer source contributions and atmospheric processes from air quality measurements. Receptor models complement, rather than replace, source-oriented dispersion and chemical transformation models that begin with source emission rates to estimate ambient concentrations. 1,2 Source and receptor models are mathematical representations of reality, requiring simplifying assumptions that create uncertainty. Applying both types of models to the same situation allows them to be improved when their results diverge and lends confidence to their results when they agree. 3

show abstract

“…Efforts to measure the chemical composition of particulate matter emissions from motor vehicles have largely relied on the measurement of typical vehicles operating over a standardized driving cycle (Hildemann et al 1991;Cadle et al 1997Cadle et al , 1999Schauer et al 1999. These "representative" mass emissions rates and chemical compositions have been used in air quality models without adjustment for specific vehicle activity patterns (i.e., actual driving cycles and the actual distribution of cold starts), or for actual vehicle cold start temperatures (Schauer et al 1996Lurmann et al 1997;Kleeman and Cass 1998;Schauer and Cass 2000;Zheng et al 2002;Fraser et al 2003). However, as efforts are being made to develop models that more accurately quantify the effect of motor vehicles on air quality and human health in regions with diverse vehicle driving cycles and cold start temperatures, there is a need to develop location specific source profiles for particulate matter emissions from mobile sources.…”

Section: Introductionmentioning

confidence: 99%

Impact of Ambient Temperatures and Driving Conditions on the Chemical Composition of Particulate Matter Emissions from Non-Smoking Gasoline-Powered Motor Vehicles

Schauer

Christensen

Kittelson

et al. 2008

Aerosol Science and Technology

View full text Add to dashboard Cite

The detailed chemical composition of particulate matter emissions from four non-smoking gasoline powered motor vehicles were measured using three different driving conditions: a cold-cold start Unified Driving Cycle (UDC), a hot UDC, and a steady state cruise driving cycle. The cold-cold start UDC tests were performed with a cold-cold start temperature of 0• C, which is significantly lower than the 24• C cold start temperature widely used for motor vehicle testing. Each vehicle was operated over three cold-cold UDC cycles, three hot UDC cycles, and a steady state driving cycle comprised of 2 hours at 100 kilometers per hour (kph) plus 1 hour at 50 kph. Particulate matter emissions were characterized for elemental carbon (EC), organic carbon (OC), sulfate ions, nitrate ions, ammonium ions, and organic compounds using gas chromatography mass spectrometry (GCMS). Mass emissions rates for the test vehicles using both the hot UDC and steady state driving cycles ranged from <0.1 to 1.3 mg km −1 , while the average cold-cold UDC cycle emissions ranged from 1.0 to 7.1 mg km −1 for the four vehicles. The cold-cold start UDC emissions averaged 5-30 times higher than the hot start UDC emissions. EC was an important contributor to the particulate matter emissions for the cold-cold start UDC emissions. Speciation of the organic compounds in the particulate matter emissions demonstrates differences in the composition of the organic aerosol emissions for the different driving cycles. The results of the present study demonstrate the important impact of cold-cold start temperature and driving conditions.

show abstract

Source apportionment of fine particulate matter in Houston, TX, using organic molecular markers

Cited by 130 publications

References 19 publications

Review of Recent Advances in Detection of Organic Markers in Fine Particulate Matter and Their Use for Source Apportionment

Review of Recent Advances in Detection of Organic Markers in Fine Particulate Matter and Their Use for Source Apportionment

Source Apportionment: Findings from the U.S. Supersites Program

Impact of Ambient Temperatures and Driving Conditions on the Chemical Composition of Particulate Matter Emissions from Non-Smoking Gasoline-Powered Motor Vehicles

Contact Info

Product

Resources

About