Grantee Research Project Results
2010 Progress Report: Sources of Organic Aerosol: Semivolatile Emissions and Photochemical Aging
EPA Grant Number: R833748Title: Sources of Organic Aerosol: Semivolatile Emissions and Photochemical Aging
Investigators: Robinson, Allen , Adams, Peter
Institution: Carnegie Mellon University
EPA Project Officer: Chung, Serena
Project Period: September 1, 2007 through August 31, 2010 (Extended to October 31, 2011)
Project Period Covered by this Report: November 1, 2009 through October 31,2010
Project Amount: $600,000
RFA: Sources and Atmospheric Formation of Organic Particulate Matter (2007) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
Objective:
- To determine emission factors and volatility distributions of low volatility organics emitted by three key sources: a diesel engine, gasoline engine, and a wood stove.
- To measure the production of secondary organic aerosol and changes in the volatility distribution by photochemical aging of diluted primary emissions from the three target sources in a smog chamber across a range of atmospheric conditions.
- To develop a photochemical aging operator suitable for a regional air quality model that describes transformations of higher volatility products into lower volatility products for primary emissions from each source class.
- To develop a module for chemical transport models (CTM) based on the volatility basis-set framework that represents gas-particle partitioning and photochemical aging of primary emissions.
- To conduct simulations to investigate the effects of both gas-particle partitioning and photochemical aging of primary emissions on organic aerosol levels.
Progress Summary:
Task 1. Emissions and gas-particle partitioning of low-volatility organics
A paper describing a new experimental technique to characterize gas-particle partitioning behavior of primary organic aerosol (POA) emissions from combustion sources at atmospherically relevant concentrations was submitted for publication. The technique involves slowly filling a Teflon chamber with a constant emission source. As aerosol concentrations increase inside the chamber, the gas-particle partitioning of semivolatile organics shifts to the particle phase, increasing the fuel-based POA emission factor. The technique allows characterization of partitioning under isothermal conditions and atmospherically relevant concentrations. The technique was evaluated using emissions from a small diesel engine; the measured changes in gas-particle partitioning agreed well with previously published data for this engine measured with a dilution sampler. The temperature dependence of the gas-particle partitioning was investigated by conducting experiments at three different temperatures (15o C, 26o C, and 33o C). Increasing organic aerosol concentration and decreasing temperature increased the fuel-based organic aerosol emission factor. The gas-particle partitioning data were fit using absorptive partitioning theory to determine the volatility distribution and enthalpy of vaporization (ΔHv) of the emissions. We have derived two fits; one using the volatility basis set approach and a second using a two product model. Both fits are suitable for use in chemical transport models. These fits were tested using previously published thermodenuder data. Partitioning calculations predict that the gas-particle partitioning from POA emissions from this engine vary by about a factor of four across the atmospherically relevant range of temperature and organic aerosol concentrations. This underscores the semivolatile nature of POA emissions.
We also analyzed a large dataset of gas-particle partitioning measurements collected as part of the FLAME-III project. This work was done in collaboration with Colorado State University (EPA STAR R833747, S.M. Kreidenweis PI). The dataset included thermodenuder measurements of POA emissions from 12 different fuels commonly burned in North American wildfires. The data indicate that the POA emissions from every burn evaporate significantly with small, atmospherically relevant changes in temperature. Therefore, the POA emissions are semivolatile. To determine the volatility distribution of the POA, the thermodenuder data were analyzed using an evaporation kinetics model. However, a challenge is non-unique solutions, since different combinations of ΔHvap and evaporation coefficient (alpha) can result in statistically acceptable fits of the data. We determined the best estimates for ΔHvap and alpha by systematically varying these inputs to the model. Using a least-squares analysis, the best statistical fits for these results are determined. Gas-particle partitioning for these fits is compared across a range of atmospheric conditions to determine how they diverge as predictions are extrapolated away from the data. Within experimental uncertainty, the POA data from all 12 fuels could be fit using the same volatility distribution, which predicts that the gas-particle partitioning will change the POA emission factor from these fuels by about a factor of 5 across the atmospherically relevant range of temperature and organic aerosol concentrations. The fit is suitable for use in chemical transport models that have implemented the volatility basis set approach.
We also continued to develop an indirect method for characterizing gas-particle partitioning of POA emissions from combustion systems. The method uses Thermal Desorption-Gas Chromatography-Mass Spectrometry analysis of quartz filter and Tenax sorbent samples. The volatility of the emissions is defined based on the elution time from the gas chromatography column. The method is calibrated using a suite of standard compounds. We are evaluating the technique by comparing with direct partitioning measurements made by isothermally diluting the diesel engine emissions. There is excellent agreement between the predicted partitioning based on the GC-MS data and direct measurements. This method appears to provide a quick and simple way to measure the volatility distribution of all low-volatility organics.
The practical implications of this work are that emerging techniques may be a quick and relatively simple way to measure the volatility distribution of all low-volatility organics emitted by combustion systems.
Task 2. SOA production from photochemical aging of primary emissions
A central theme of this project is that low volatility organic vapors are an important class of secondary organic aerosol (SOA) precursors. These vapors are comprised of intermediate volatility organic compounds (IVOCs) and semi-volatile organic compounds (SVOCs). SVOCs exist in both the gas and particle phase while IVOCs exist exclusively in the vapor phase but are less volatile than VOCs. Although source test data indicate that SVOC and IVOC emissions are substantial, relatively little is known about the molecular composition of these emissions as the vast majority of which are categorized as an unresolved complex mixture (UCM). This UCM is presumably made up of branched and cyclic structured compounds. To better understand the contribution of low volatility organic vapors to ambient SOA, we have been investigating the effects of alkane structure on SOA yields, oxygenation, and volatility. This project period we have been conducting smog chamber experiments with a set of cyclic-, substituted cyclic-, and branched-alkanes. All experiments were hydroxyl radical-initiated and were performed under high NOx conditions. SOA yields required knowledge of the particle mass concentration, monitored by a scanning mobility particle sizer (SMPS), and the amount of decay of the parent alkane, quantified using Tenax TA sorbent samples analyzed offline by a thermal-desorption gas chromatography mass spectrometer (GC-MS) system. An Aerodyne high-resolution time-of- flight aerosol mass spectrometer (HR-ToF-AMS) was used to monitor changes in changes in chemical composition as well as molar oxygen-to-carbon ratios (O/C) as a measure of oxygenation of the SOA. The results provide evidence of larger molecules producing larger yields but less-oxygenated SOA than smaller molecules, thus illustrating the importance of molecular structure on SOA formation and composition.
These provide further evidence of that photo-oxidation of low-volatility organic compounds is an important source of atmospheric secondary organic aerosol.
Task 4. Chemical Transport Modeling
The GISS GCM II “unified” climate model was modified to simulate semi-volatile and reactive primary organic aerosols on a global scale using the volatility basis set framework. The model accounts for the chemical reaction and phase partitioning of primary and secondary organic aerosol (POA and SOA). The model also incorporates the emissions and reactions of intermediate volatility organic compounds (IVOCs) as a source of organic aerosol (OA), one that has been missing in most prior work. Model predictions are evaluated against a broad set of observational constraints including mass concentrations, degree of oxygenation, volatility and isotopic composition. A traditional model that treats POA as non-volatile and non-reactive is also compared to the same set of observations to highlight the progress made in this effort. The revised model predicts a global dominance of SOA and brings the POA/SOA split into better agreement with ambient measurements. This change is due to traditionally defined POA evaporating and the evaporated vapors oxidizing to form non-traditional SOA. IVOCs (traditionally not included in chemical transport models) oxidize to form condensable products that account for a third of total OA, suggesting that global models have been missing a large source of OA. Predictions of the revised model for the SOA fraction at 17 different locations compared much better to observations than predictions from the traditional model. Model- predicted volatility is compared with thermodenuder data collected at three different field campaigns: FAME-2008, MILAGRO-2006 and SOAR-2005. The revised model predicts the OA volatility much more closely than the traditional model. When compared against monthly averaged OA mass concentrations measured by the IMPROVE network, predictions of both the revised and traditional model lie within a factor of two in summer and mostly within a factor of five during winter. A sensitivity analysis indicates that the winter comparison can be improved either by increasing POA emissions or lowering the volatility of those emissions. Model predictions of the isotopic composition of OA are compared against those computed via a radiocarbon isotope analysis of field samples. The contemporary fraction, on average, is slightly under-predicted (20%) during the summer months but is a factor of two lower during the winter months. We hypothesize that the large wintertime under-prediction of surface OA mass concentrations and the contemporary fraction is due to an under-representation of biofuel (particularly, residential wood burning) emissions in the emission inventory. Overall, the model evaluation highlights the importance of treating POA as semi-volatile and reactive in order to predict accurately the sources, composition and properties of ambient OA.
The practical implication of this work is that explicit accounting for partitioning and aging of primary emissions improves predictions of chemical transport models used for SIP development and evaluating the effects of climate change on urban and regional air quality.
Future Activities:
During the remainder of the project, we shall focus on the following objectives: 1) develop an updated volatility operated using the experimental results from this and other projects, and 2) conduct CTM calculations to quantify the effects of the revised framework on source apportionment.
References:
Journal Articles on this Report : 13 Displayed | Download in RIS Format
| Other project views: | All 83 publications | 21 publications in selected types | All 21 journal articles |
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Asa-Awuku A, Miracolo MA, Kroll JH, Robinson AL, Donahue NM. Mixing and phase partitioning of primary and secondary organic aerosols. Geophysical Research Letters 2009;36(15):L15827 (5 pp.). |
R833748 (2010) R833748 (Final) |
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Donahue NM, Robinson AL, Pandis SN. Atmospheric organic particulate matter: from smoke to secondary organic aerosol. Atmospheric Environment 2009;43(1):94-106. |
R833748 (2008) R833748 (2010) R833748 (Final) R833746 (2008) R833746 (2009) R833746 (2010) R833746 (Final) |
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Grieshop AP, Logue JM, Donahue NM, Robinson AL. Laboratory investigation of photochemical oxidation of organic aerosol from wood fires 1: measurement and simulation of organic aerosol evolution. Atmospheric Chemistry and Physics 2009;9(4):1263-1277. |
R833748 (2008) R833748 (2009) R833748 (2010) R833748 (Final) |
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Grieshop AP, Miracolo MA, Donahue NM, Robinson AL. Constraining the volatility distribution and gas-particle partitioning of combustion aerosols using isothermal dilution and thermodenuder measurements. Environmental Science & Technology 2009;43(13):4750-4756. |
R833748 (2008) R833748 (2009) R833748 (2010) R833748 (Final) |
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Grieshop AP, Donahue NM, Robinson AL. Laboratory investigation of photochemical oxidation of organic aerosol from wood fires 2: analysis of aerosol mass spectrometer data. Atmospheric Chemistry and Physics 2009;9(6):2227-2240. |
R833748 (2008) R833748 (2009) R833748 (2010) R833748 (Final) |
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Jathar SH, Farina SC, Robinson AL, Adams PJ. The influence of semi-volatile and reactive primary emissions on the abundance and properties of global organic aerosol. Atmospheric Chemistry and Physics 2011;11(15):7727-7746. |
R833748 (2010) R833748 (Final) R833374 (2007) R833374 (2008) R833374 (2010) R833374 (Final) |
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Jimenez JL, Canagaratna MR, Donahue NM, Prevot AS, Zhang Q, Kroll JH, DeCarlo PF, Allan JD, Coe H, Ng NL, Aiken AC, Docherty KS, Ulbrich IM, Grieshop AP, Robinson AL, Duplissy J, Smith JD, Wilson KR, Lanz VA, Hueglin C, Sun YL, Tian J, Laaksonen A, Raatikainen T, Rautiainen J, Vaattovaara P, Ehn M, Kulmala M, Tomlinson JM, Collins DR, Cubison MJ, Dunlea EJ, Huffman JA, Onasch TB, Alfarra MR, Williams PI, Bower K, Kondo Y, Schneider J, Drewnick F, Borrmann S, Weimer S, Demerjian K, Salcedo D, Cottrell L, Griffin R, Takami A, Miyoshi T, Hatakeyama S, Shimono A, Sun JY, Zhang YM, Dzepina K, Kimmel JR, Sueper D, Jayne JT, Herndon SC, Trimborn AM, Williams LR, Wood EC, Middlebrook AM, Kolb CE, Baltensperger U, Worsnop DR. Evolution of organic aerosols in the atmosphere. Science 2009;326(5959):1525-1529. |
R833748 (2010) R833748 (Final) R831080 (Final) R832161 (Final) R833746 (2009) R833746 (2010) R833746 (Final) R833747 (Final) |
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Miracolo MA, Presto AA, Lambe AT, Hennigan CJ, Donahue NM, Kroll JH, Worsnop DR, Robinson AL. Photo-oxidation of low-volatility organics found in motor vehicle emissions: production and chemical evolution of organic aerosol mass. Environmental Science & Technology 2010;44(5):1638-1643. |
R833748 (2010) R833748 (Final) |
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Presto AA, Miracolo MA, Kroll JH, Worsnop DR, Robinson AL, Donahue NM. Intermediate-volatility organic compounds: a potential source of ambient oxidized organic aerosol. Environmental Science & Technology 2009;43(13):4744-4749. |
R833748 (2008) R833748 (2009) R833748 (2010) R833748 (Final) R834554 (Final) |
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Presto AA, Miracolo MA, Donahue NM, Robinson AL. Secondary organic aerosol formation from high-NOx photo-oxidation of low volatility precursors:n-alkanes. Environmental Science & Technology 2010;44(6):2029-2034. |
R833748 (2010) R833748 (Final) |
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Ranjan M, Presto AA, Robinson AL. Temperature dependence of gas-particle partitioning of primary organic aerosol emissions from a small diesel engine. Aerosol Science and Technology 2012;46(1):13-21. |
R833748 (2010) R833748 (Final) |
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Robinson AL, Grieshop AP, Donahue NM, Hunt SW. Updating the conceptual model for fine particle mass emissions from combustion systems. Journal of the Air & Waste Management Association 2010;60(10):1204-1222. |
R833748 (2010) R833748 (Final) |
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Shrivastava MK, Lane TE, Donahue NM, Pandis SN, Robinson AL. Effects of gas particle partitioning and aging of primary emissions on urban and regional organic aerosol concentrations. Journal of Geophysical Research-Atmospheres 2008;113(D18):D18301 (16 pp.). |
R833748 (2008) R833748 (2009) R833748 (2010) R833748 (Final) R831081 (Final) R832162 (Final) |
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Supplemental Keywords:
airborne particulate matter, aerosol, emission characterization, atmospheric chemistry, regional modeling, source/receptor analysis, photochemistryProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.