Data associated with "Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NOx"
| dc.contributor.author | Akherati, Ali | |
| dc.contributor.author | Cappa, Christopher D. | |
| dc.contributor.author | Kleeman, Michael J. | |
| dc.contributor.author | Docherty, Kenneth S. | |
| dc.contributor.author | Jimenez, Jose L. | |
| dc.contributor.author | Griffith, Stephen M. | |
| dc.contributor.author | Dusanter, Sebastien | |
| dc.contributor.author | Stevens, Philip S. | |
| dc.contributor.author | Jathar, Shantanu H. | |
| dc.coverage.spatial | Southern California with a focus on the four-county region of Los Angeles, Riverside, Orange County, and San Bernardino. | en_US |
| dc.coverage.temporal | 2005-07-15-2005-08-02 | en_US |
| dc.date.accessioned | 2019-03-22T22:31:17Z | |
| dc.date.available | 2019-03-22T22:31:17Z | |
| dc.date.issued | 2019 | |
| dc.description | The dataset includes model predictions of gas- and particle-phase organic compounds from the UCD/CIT model and measurements over southern California. The dataset is limited to the information presented in the figures. | en_US |
| dc.description | Department of Mechanical Engineering | |
| dc.description.abstract | Semi-volatile and intermediate-volatility organic compounds (SVOCs and IVOCs) from anthropogenic sources are likely to be important precursors of secondary organic aerosol (SOA) in urban airsheds, yet their treatment in most models is based on limited and obsolete data or completely missing. Additionally, gas-phase oxidation of organic precursors to form SOA is influenced by the presence of nitric oxide (NO), but this influence is poorly constrained in chemical transport models. In this work, we updated the organic aerosol model in the UCD/CIT (University of California at Davis and California Institute of Technology) chemical transport model to include (i) a semi-volatile and reactive treatment of primary organic aerosol (POA), (ii) emissions and SOA formation from IVOCs, (iii) the NOx influence on SOA formation, and (iv) SOA parameterizations for SVOCs and IVOCs that are corrected for vapor wall loss artifacts during chamber experiments. All updates were implemented in the statistical oxidation model (SOM) that simulates the oxidation chemistry, thermodynamics, and gas–particle partitioning of organic aerosol (OA). Model treatment of POA, SVOCs, and IVOCs was based on an interpretation of a comprehensive set of source measurements available up to the year 2016 and resolved broadly by source type. The NOx influence on SOA formation was calculated offline based on measured and modeled VOC:NOx ratios. Finally, the SOA formation from all organic precursors (including SVOCs and IVOCs) was modeled based on recently derived parameterizations that accounted for vapor wall loss artifacts in chamber experiments. The updated model was used to simulate a 2-week summer 30 episode over southern California at a model resolution of 8 km. When combustion-related POA was treated as semi-volatile, modeled POA mass concentrations were reduced by 15%-40% in the urban areas in southern California but were still too high when compared against "hydrocarbon-like organic aerosol" factor measurements made at Riverside, CA, during the Study of Organic Aerosols at Riverside (SOAR-1) campaign of 2005. Treating all POA (except that from marine sources) to be semi-volatile, similar to diesel exhaust POA, resulted in a larger reduction in POA mass concentrations and allowed for a better model–measurement comparison at Riverside, but this scenario is unlikely to be realistic since this assumes that POA from sources such as road and construction dust are semi-volatile too. Model predictions suggested that both SVOCs (evaporated POA vapors) and IVOCs did not contribute as much as other anthropogenic precursors (e.g., alkanes, aromatics) to SOA mass concentrations in the urban areas (<5% and <15% of the total SOA respectively) as the timescales for SOA production appeared to be shorter than the timescales for transport out of the urban airshed. Comparisons of modeled IVOC concentrations with measurements of anthropogenic SOA precursors in southern California seemed to imply that IVOC emissions were underpredicted in our updated model by a factor of 2. Correcting for the vapor wall loss artifact in chamber experiments enhanced SOA mass concentrations although the enhancement was precursor-dependent as well as NOx-dependent. Accounting for the influence of NOx using the VOC:NOx ratios resulted in better predictions of OA mass concentrations in rural/remote environments but still underpredicted OA mass concentrations in urban environments. The updated model's performance against measurements combined with the results from the sensitivity simulations suggests that the OA mass concentrations in southern California are constrained within a factor of 2. Finally, simulations performed for the year 2035 showed that, despite reductions in VOC and NOx emissions in the future, SOA mass concentrations may be higher than in the year 2005, primarily from increased hydroxyl radical (OH) concentrations due to lower ambient NO2 concentrations. | en_US |
| dc.description.sponsorship | Ali Akherati and Shantanu H. Jathar were partially supported by the National Oceanic and Atmospheric Administration (NA17OAR4310003). Jose L. Jimenez was supported by the Environmental Protection Agency (EPA) STAR program (83587701-0). Stephen M. Griffith, Sebastien Dusanter, Philip S. Stevens, and Christopher D. Cappa were supported by the National Science Foundation (AGS-0612738, AGS-1104880, and AGS-1523500). | en_US |
| dc.format.medium | ZIP | |
| dc.format.medium | RTF | |
| dc.format.medium | CSV | |
| dc.identifier.uri | https://hdl.handle.net/10217/194377 | |
| dc.identifier.uri | http://dx.doi.org/10.25675/10217/194377 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | en_US |
| dc.relation.ispartof | Research Data | |
| dc.relation.isreferencedby | Akherati, A., Cappa, C. D., Kleeman, M. J., Docherty, K. S., Jimenez, J. L., Griffith, S. M., Dusanter, S., Stevens, P. S., & Jathar, S. H.: Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NOx, Atmos. Chem. Phys., 19, 4561-4594, https://doi.org/10.5194/acp-19-4561-2019, 2019. | |
| dc.relation.isreferencedby | Jathar, S. H., Cappa, C. D., Wexler, A. S., Seinfeld, J. H., and Kleeman, M. J.: Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model, Geosci. Model Dev., 8, 2553-2567, https://doi.org/10.5194/gmd-8-2553-2015, 2015. | en_US |
| dc.relation.isreferencedby | Jathar, S. H., Cappa, C. D., Wexler, A. S., Seinfeld, J. H., and Kleeman, M. J.: Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 1: Assessing the influence of constrained multi-generational ageing, Atmos. Chem. Phys., 16, 2309-2322, https://doi.org/10.5194/acp-16-2309-2016, 2016. | en_US |
| dc.relation.isreferencedby | Cappa, C. D., Jathar, S. H., Kleeman, M. J., Docherty, K. S., Jimenez, J. L., Seinfeld, J. H., and Wexler, A. S.: Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses, Atmos. Chem. Phys., 16, 3041-3059, https://doi.org/10.5194/acp-16-3041-2016, 2016. | en_US |
| dc.subject | secondary organic aerosol (SOA) | |
| dc.subject | statistical oxidation model (SOM) | |
| dc.subject | intermediate-volatility organic compounds (IVOC) | |
| dc.subject | chemical transport nodel (CTM) | |
| dc.subject | NOX | |
| dc.subject | southern California | |
| dc.title | Data associated with "Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NOx" | en_US |
| dc.type | Dataset | en_US |