The USEPA/DRI chemical mass balance receptor model, CMB 7.0

Watson, John G.; Robinson, Norman F.; Chow, Judith C.; Henry, Ronald C.; Kim, B.M.; Pace, Tom; Meyer, E.L.; Nguyen, Quyen

doi:10.1016/0266-9838(90)90015-x

Cited by 203 publications

(94 citation statements)

References 3 publications

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“…[15][16][17] In CMB, the ambient concentrations of chemical species are expressed as the sum of the products of source contributions and source compositions. 26 The concentration of chemical species i at the receptor site k, c ik , is calculated as:…”

Section: Cmb Analysismentioning

confidence: 99%

“…Therefore, the selection of mass balance species must be limited to species for which all of the major sources are included in the model and species that are conserved in the atmosphere with no significant removal through dry and wet depositions or formation by chemical reactions over time during transport from the source to the receptor site. In the present study, CMB analysis was computed using the CMB7.0 software developed by Watson et al 26 The diagnostics of CMB include the percentage of mass explained (target: 100 Ϯ 20%), R 2 (target: 0.8 -1), 2 (target: 0 -4), t test (target: Ͼ2), degrees of freedom (target: Ͼ5), no cluster sources, and calculated-to-measured ratio for fitting species (target: 0.5-2). 26 The selection criteria for particle-phase organic compounds used as tracers in the present study are based on the previous work by Schauer et al 14 The list of organic tracers adopted by Schauer et al 14 has been extended for the recent development in quantification of some molecular markers in the source testing studies, such as levoglucosan 28 and cholesterol.…”

Section: Cmb Analysismentioning

confidence: 99%

“…In the present study, CMB analysis was computed using the CMB7.0 software developed by Watson et al 26 The diagnostics of CMB include the percentage of mass explained (target: 100 Ϯ 20%), R 2 (target: 0.8 -1), 2 (target: 0 -4), t test (target: Ͼ2), degrees of freedom (target: Ͼ5), no cluster sources, and calculated-to-measured ratio for fitting species (target: 0.5-2). 26 The selection criteria for particle-phase organic compounds used as tracers in the present study are based on the previous work by Schauer et al 14 The list of organic tracers adopted by Schauer et al 14 has been extended for the recent development in quantification of some molecular markers in the source testing studies, such as levoglucosan 28 and cholesterol. 29 In the present study, a total of 31 individual organic tracers along with three additional chemical constituents were applied in the CMB model to quantify the contribution of up to seven primary emission source categories to fine OC.…”

Section: Cmb Analysismentioning

confidence: 99%

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Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter

Zheng

Cass

Lin

et al. 2007

Journal of the Air & Waste Management Association

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The primary emission source contributions to fine organic carbon (OC) and fine particulate matter (PM 2.5 ) mass concentrations on a daily basis in Atlanta, GA, are quantified for a summer (July 3 to August 4, 2001) and a winter (January 2-31, 2002) month. Thirty-one organic compounds in PM 2.5 were identified and quantified by gas chromatography/mass spectrometry. These organic tracers, along with elemental carbon, aluminum, and silicon, were used in a chemical mass balance (CMB) receptor model. CMB source apportionment results revealed that major contributors to identified fine OC concentrations include meat cooking (7-68%; average: 36%), gasoline exhaust (7-45%; average: 21%), and diesel exhaust (6 -41%; average: 20%) for the summer month, and wood combustion (0 -77%; average: 50%); gasoline exhaust (14 -69%; average: 33%), meat cooking (1-14%; average: 5%), and diesel exhaust (0 -13%; average: 4%) for the winter month. Primary sources, as well as secondary ions, including sulfate, nitrate, and ammonium, accounted for 86 Ϯ 13% and 112 Ϯ 15% of the measured PM 2.5 mass in summer and winter, respectively.

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Section: Cmb Analysismentioning

confidence: 99%

Section: Cmb Analysismentioning

confidence: 99%

Section: Cmb Analysismentioning

confidence: 99%

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Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter

Zheng

Cass

Lin

et al. 2007

Journal of the Air & Waste Management Association

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“…4 Using chemical mass balance receptor modeling software available from the U.S. Environmental Protection Agency (CMB 8.2), 29 the best fit combinations of source effluents needed to reproduce the organic compound distribution in atmospheric particle samples is computed, and from knowledge of the ratio of compound concentrations to mass concentrations at the source, source contributions to atmospheric particle mass concentrations are calculated. The methodologies for the measurement of source profiles, the selection of chemical mass balance species, and the implementation of the molecular-marker source apportionment calculations are discussed in detail in the previous references and are only summarized briefly here.…”

Section: Source Apportionment Modelingmentioning

confidence: 99%

The Distribution of Particle-Phase Organic Compounds in the Atmosphere and Their Use for Source Apportionment during the Southern California Children’s Health Study

Manchester-Neesvig

Schauer

Cass

2003

Journal of the Air & Waste Management Association

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Atmospheric particulate matter (PM) samples from 12 sites in southern California, collected as part of the Southern California Children's Health Study (SCCHS), were analyzed using gas chromatography/mass spectrometry (GC/MS) techniques. Ninety-four organic compounds were quantified in these samples, including n-alkanes, fatty acids, polycyclic aromatic hydrocarbons (PAH), hopanes, steranes, aromatic diacids, aliphatic diacids, resin acids, methoxyphenols, and levoglucosan. Annual average concentrations of all detected compounds, as well as average concentrations for three seasonal periods, were determined at all 12 sites for the calendar year of 1995. These measurements provide important information about the seasonal and spatial distribution of particlephase organic compounds in southern California. Also, co-located samples from one site were analyzed to assess precision of measurement. Excellent agreement was observed between annual average concentrations for the broad range of organic compounds measured in this study. Measured concentrations from the 12 sampling sites were used in a previously developed molecularmarker source apportionment model to quantify the primary source contributions to the PM 10 organic carbon and mass concentrations at these 12 sites. Source contributions to atmospheric PM from six important air pollution sources were quantified: gasoline-powered motor vehicle exhaust, diesel vehicle exhaust, wood smoke, vegetative detritus, tire wear, and natural gas combustion. Important trends in the seasonal and spatial patterns of the impact of these six sources were observed. In addition, contributions from meat smoke were detected in selected samples.

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“…The formalized protocol for CMB model application and validation 5,14,15 was applied during this study. This required the application of initial CMB tests designed to select a core set of source profiles and fitting species for the ambient data.…”

Section: Data Analysis Methodsmentioning

confidence: 99%

Source Apportionment of Airborne Fine Particulate Matter in an Underground Mine

McDonald

Zielińska

Sagebiel

et al. 2003

Journal of the Air & Waste Management Association

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The chemical mass balance source apportionment technique was applied to an underground gold mine to assess the contribution of diesel exhaust, rock dust, oil mists, and cigarette smoke to airborne fine (Ͻ2.5 m) particulate matter (PM). Apportionments were conducted in two locations in the mine, one near the mining operations and one near the exit of the mine where the ventilated mine air was exhausted. Results showed that diesel exhaust contributed 78 -98% of the fine particulate mass and greater than 90% of the fine particle carbon, with rock dust making up the remainder. Oil mists and cigarette smoke contributions were below detection limits for this study. The diesel exhaust fraction of the total fine PM was higher than the recently implemented mine air quality standards based on total carbon at both sample locations in the mine.

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The USEPA/DRI chemical mass balance receptor model, CMB 7.0

Cited by 203 publications

References 3 publications

Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter

Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter

The Distribution of Particle-Phase Organic Compounds in the Atmosphere and Their Use for Source Apportionment during the Southern California Children’s Health Study

Source Apportionment of Airborne Fine Particulate Matter in an Underground Mine

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