Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models

<p>Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) re...

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Main Authors: S. Eluri, C. D. Cappa, B. Friedman, D. K. Farmer, S. H. Jathar
Format: Article
Language:English
Published: Copernicus Publications 2018-10-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/18/13813/2018/acp-18-13813-2018.pdf
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spelling doaj-362e04fe9767403489012a8a048363262020-11-25T02:30:07ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-10-0118138131383810.5194/acp-18-13813-2018Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic modelsS. Eluri0C. D. Cappa1B. Friedman2D. K. Farmer3S. H. Jathar4Department of Mechanical Engineering, Colorado State University, Fort Collins, CO, 80523, USADepartment of Civil and Environmental Engineering, University of California Davis, Davis, CA, 95616, USADepartment of Chemistry, Colorado State University, Fort Collins, CO, 80523, USADepartment of Chemistry, Colorado State University, Fort Collins, CO, 80523, USADepartment of Mechanical Engineering, Colorado State University, Fort Collins, CO, 80523, USA<p>Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility, and volatile organic compounds (SVOC, IVOC and VOC); NO<sub><i>x</i></sub>-dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70&thinsp;% of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28&thinsp;% for OA atomic O&thinsp;:&thinsp;C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.</p>https://www.atmos-chem-phys.net/18/13813/2018/acp-18-13813-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author S. Eluri
C. D. Cappa
B. Friedman
D. K. Farmer
S. H. Jathar
spellingShingle S. Eluri
C. D. Cappa
B. Friedman
D. K. Farmer
S. H. Jathar
Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
Atmospheric Chemistry and Physics
author_facet S. Eluri
C. D. Cappa
B. Friedman
D. K. Farmer
S. H. Jathar
author_sort S. Eluri
title Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
title_short Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
title_full Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
title_fullStr Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
title_full_unstemmed Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
title_sort modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2018-10-01
description <p>Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility, and volatile organic compounds (SVOC, IVOC and VOC); NO<sub><i>x</i></sub>-dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70&thinsp;% of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28&thinsp;% for OA atomic O&thinsp;:&thinsp;C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.</p>
url https://www.atmos-chem-phys.net/18/13813/2018/acp-18-13813-2018.pdf
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