Grantee Research Project Results
2006 Progress Report: Source-Apportionment of Primary Organic Carbon in the Eastern United States Combining Receptor-Models, Chemical Transport Models, and Laboratory Oxidation Experiments
EPA Grant Number: R832162Title: Source-Apportionment of Primary Organic Carbon in the Eastern United States Combining Receptor-Models, Chemical Transport Models, and Laboratory Oxidation Experiments
Investigators: Robinson, Allen , Donahue, Neil , Adams, Peter
Institution: Carnegie Mellon University
EPA Project Officer: Chung, Serena
Project Period: November 1, 2004 through October 31, 2007
Project Period Covered by this Report: November 1, 2005 through October 31, 2006
Project Amount: $450,000
RFA: Source Apportionment of Particulate Matter (2004) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
Objective:
- To measure oxidation kinetics of organic molecular markers in actual emissions (diesel engine, wood smoke, meat cooking) exposed to O3 and OH across a wide range of atmospheric conditions in a smog chamber.
- To apply receptor models (CMB, PMF) to molecular marker data collected by the Supersites to apportion ambient organic carbon in the Eastern United States to sources of primary organic aerosol.
- To evaluate existing emission inventories for primary organic carbon by comparing predictions of photochemical transport models to receptor modeling results.
- To combine receptor and chemical transport to quantify the contribution of different source classes and geographic sub-regions to primary organic carbon in the Eastern United Sates.
- To assess the importance of photochemical aging on primary organic aerosol composition in the Eastern US and its effects on source apportionment estimates.
Progress Summary:
The past year has been transformative for our understanding of organic particle behavior in the atmosphere, with major findings published in a recent article in the journal Science (1). Most primary organic particulate emissions are semivolatile; they thus partially evaporate with atmospheric dilution, creating significant amounts of low-volatility gas-phase material. Laboratory experiments show that photo-oxidation of diesel emissions rapidly generates organic aerosol, greatly exceeding the contribution from known secondary organic aerosol precursors. We attribute this unexplained secondary organic aerosol production to oxidation of low volatility gas-phase species. Accounting for both gas-particle partitioning and photochemical processing of primary emissions creates a regional aerosol and brings model predictions into better agreement with observations. This finding has important implications for how we measure and simulate organic aerosol, blurring the dual notion of secondary and primary organic aerosol.
The practical implications of these results include:
- The semivolatile character of primary emissions means that instead of measuring fixed primary organic aerosol emissions factors, we must measure the volatility distribution of the emissions.
- Models and inventories must account for these distributions and their evolution with photochemical age.
- Low volatility organics are an important source of secondary organic aerosol that are poorly accounted for in current models and inventories.
- Except for people living close to sources, the majority of the population, even in urban areas, is exposed mostly to SOA.
Objective 1: Laboratory Measurements of Oxidation Kinetics of Organic Molecular Markers
Ongoing experiments are addressing oxidation of molecular markers in organic aerosols exposed to both O3 and OH. As part of this work we have developed a relative kinetics framework for interpretation of data on the heterogeneous oxidation of multicomponent organic aerosols. Common accommodation, diffusion, and deposition terms cancel in this formulation, and rate constants may be determined for many compounds simultaneously within an aerosol with a realistic composition. Finally, cross-phase relative rate constants with a gas-phase reference compound and a condensed-phase target compound provide effective rate constants for use in atmospheric models. The relative rate approach is described in detail by Donahue et al. (2).
Another key component of our approach is to conduct the aging experiments in a smog chamber. This allows us to expose the aerosol to atmospherically relevant oxidant concentrations for time periods of hours. This avoids the potentially artificial mass transfer limitations of short duration and high oxidant concentration conditions typically used in aerosol flow tubes. A challenge with all smog chamber experiments is wall loss. In our relative rates approach, we handle wall losses by analyzing ratios of species concentrations. This assumes that the aerosols are internally mixed; we have demonstrated this assumption with control experiments. Additional details on our experimental technique can be found in Huff-Hartz et al. (3).
To evaluate the relative rate technique, we have performed a series of experiments using model meat cooking emission aerosols (3). The experiments were conducted using five different organic aerosols, varying in complexity from three to twelve components. These mixtures include alkenoic acids, alkanoic acids, alkanedioic acids, n-alkanes, and sterols. The mixtures were designed to simulate meat cooking emissions. Significant decay was observed for all species (except for the n-alkanes) in at least one of the experimental systems. By relating the decomposition of condensed-phase alkenoic acids to gas-phase alkenes, we show that the reaction rate constants of oleic acid and palmitoleic acid evolve as the aerosol is processed, decreasing by a factor of ~10 over the course of a four-hour experiment. The decay rate constants of cholesterol, oleic acid, and palmitic acid all depend strongly on aerosol composition, with more than an order of magnitude change in the effective rate constants depending on mixture composition. Effects of aerosol composition are likely to be even more significant in atmospheric aerosol, where particle compositions are highly variable. Our data indicate that mixture effects are complicated, making it difficult to extrapolate from simple laboratory systems to atmospherically relevant conditions.
In order to understand the oxidation kinetics of molecular markers in more realistic aerosols, we have been conducting a series of experiments with aerosolized hamburger grease. The composition of this grease is similar to previously published speciation data for meat cooking aerosols. Our experiments show surprisingly rapid oxidation oxidation of cholesterol and other cooking markers in hamburger grease. For example, our most conservative reaction rate for cholesterol, a molecular marker for meat cooking emissions, indicate a half-life of two days at modest ambient ozone concentrations of 30ppb. This rate is comparable to that measured as part of the validation experiments performed with a 12-component mixture. We are currently investigating the effects of relative humidity and secondary organic aerosol coatings on the oxidation kinetics of molecular markers in hamburger grease.
Since many molecular markers are saturated (no double bonds), OH could be a more important oxidant than O3. We have begun to study oxidation of motor vehicle markers (hopanes and steranes) in motor oil. The first step of this work was to develop a new method for production of OH radicals because of shortcomings of existing techniques in the context of heterogeneous oxidation (4). Existing methods typically require some combination of hard UV, high NOx, or extensive radical cycling. The new OH source is based on alkene ozonolysis. We use 2,3-dimethyl-2-butene (tetramethylethylene, TME) because TME ozonolysis results in an OH yield near unity. This OH source can consistently produce radicals in the range of (4−8) × 106 molec cm−3; these levels can also be easily sustained over experimental time scales of many hours. The main disadvantage to our method of OH production is that it requires high ozone concentrations so studying the chemistry of species that are reactive towards both OH radicals and ozone is impractical. As a proof of concept we present preliminary results from oxidation of n-hexacosane aerosol observed with an Aerodyne Aerosol Mass Spectrometer (AMS). The extent of hexacosane oxidation is sufficient to significantly change the AMS organic aerosol mass spectrum by virtue of fast heterogeneous uptake of OH radicals at the particle surface, with a calculated uptake coefficient γ = 1.04 ±0.21.
We have initiated a series of experiment to investigate aging of molecular markers in motor vehicle exhaust. The basic experiment involves flash vaporizing motor oil to generate an aerosol that is then exposed to our OH source. Initial experiments indicate reveal substantial oxidation of steranes in motor oil exposed to typical summertime levels of OH. Future experiments will investigate the changes in molecular composition due to this oxidation across a wider range of atmospheric conditions.
The practical implications of this work are that compounds used as molecular markers rapidly oxidize in simple systems, but that the oxidation rates strongly depend on mixture composition. Data in realistic systems (hamburger grease and motor oil) show significant decay of markers at atmospherically relevant oxidant concentrations. Therefore, aging of molecular markers likely presents a substantial complication to linear source apportionment techniques such as the Chemical Mass Balance model, especially in areas strongly influenced by regional transport.
Objective 2: Application of Receptor Models to Apportion Ambient Organic Aerosol to Primary Sources in the Eastern United States
A major focus of the project has been using ambient concentrations of molecular markers to estimate sources of organic aerosol. We have written a series of papers that utilize a large dataset of ambient molecular marker concentrations recently developed as part of the Pittsburgh Air Quality Study. The unprecedented size of the dataset provides a unique opportunity to critically evaluate the use of molecular markers for source apportionment. Each paper seeks to answer a set of questions for small groups of compounds associated with specific source classes (e.g., levoglucosan, resin acids, and syringols as markers for biomass combustion). Are the ambient molecular marker data organized in a fashion that implies the existence of a well-defined source profile or set of profiles? Which published profiles or combinations of published profiles can explain the ambient data? How well is the amount of ambient OC apportioned to a source class constrained by CMB analysis given the set of viable profile combinations? Is there evidence of photochemical oxidation of molecular markers?
The first paper in the series (5) describes a methodology to visualize the organization of ambient molecular marker data, to compare the data to source profiles, and to better understand CMB solutions. The methodology can also be used to assess chemical stability and aging. The core of the technique involves construction of plots of ratios of species concentrations (ratio-ratio plots) in which source profiles appear as points connected by linear mixing lines. The approach has been illustrated using ambient measurements made in Pittsburgh, PA over a one-year period of five, large polycyclic aromatic hydrocarbons (PAH) commonly used as molecular markers in CMB: benzo(b+j+k)fluoranthene, benzo(e)pyrene, benzo[g,h,i]perylene, coronene, and indeno(1,2,3-cd)pyrene. In Pittsburgh, the ambient concentrations of these PAH are strongly correlated suggesting a single dominant source. These correlations underscore the significant source information contained in molecular marker concentrations. Ratio-ratio plots are then used to evaluate the potential contribution of gasoline exhaust, diesel exhaust, wood smoke, and coke production emissions to the ambient concentrations of the target PAHs. Coke production is the dominant source of these large PAHs in Pittsburgh. Ambient concentrations of these large PAH provide little information on the gasoline-diesel split because of the strong influence of local emissions from coke production combined with potential photochemical decay of PAH in the regional air mass. Decay of PAHs will bias estimates of the gasoline-diesel split towards diesel emissions.
Companion papers consider source-specific sets of molecular markers for important source classes: cooking, biomass burning, and motor vehicles (6-8). Each paper illustrates different strengths and challenges of using molecular markers for source apportionment and provides additional case studies of the ratio-ratio approach. A consistent theme throughout the other papers is how source profile variability can be the main source of error in CMB analyses.
Ambient data of the cooking markers (cholesterol, palmitoleic acid, oleic acid, palmitic acid, and stearic acid) form reasonably well-organized ratio-ratio plots, implying the existence of a well-defined source profile (7). However, significant inconsistencies exist between the ambient data and published source profiles. Most notably, the ambient ratio of palmitoleic-acid-to-oleic-acid is more than a factor of ten greater than essentially all published source profiles. This problem is not unique to Pittsburgh. The reason for this discrepancy is not known but it means that both acids cannot be fit simultaneously by CMB. CMB analysis is performed using three different combinations of food cooking source profiles and molecular makers. Although all three solutions have high statistical quality, the amount of OC apportioned to food cooking emissions varies by a factor of nine. Differences in fitting species and source profile marker-to-organic-carbon ratios cause most of the large systematic biases between the different solutions. The best CMB model includes two alkanoic acids as fitting species in addition to other cooking markers, which helps constrain the source contribution estimates. It also includes two meat cooking source profiles to account for the variability in the ambient data. This model apportions an average of 320 ± 140 ng-C m-3 or 10% of the study average ambient organic carbon to food cooking emissions. Although these results illustrate the significant challenges created by source profile variability, the strong correlations in the ambient dataset underscore the significant promise that molecular markers hold for source apportionment analysis.
Motor vehicle markers (hopanes and EC) also form well-organized ratio-ratio plots, but the data exhibit a distinct seasonal pattern (8). The ambient winter data cluster on a hopanes/EC ratio-ratio plot, and a large number of different source profile combinations can explain the ambient data. In contrast, the widely varying summer ambient ratios can be explained by a limited number of source profile combinations. We present results for a number of different CMB scenarios, all of which perform equally well on the different statistical tests used to establish the quality of a CMB solution. The results illustrate how OC apportionment depends critically on the marker-to-OC ratios of the source profiles. The vehicular contribution in the winter is bounded between 13% and 20% of the ambient OC (274 ± 56 to 416 ± 72 ng-C/m3). However, variability in the diesel profiles creates uncertainty in the gasoline-diesel split on an OC basis; one set of scenarios suggests gasoline dominance while a second set indicates a more even split. On a PM2.5 mass basis, all solutions indicate diesel emissions as the dominant contributor. The summer CMB solutions do not present a consistent picture given the seasonal shift in the ambient hopanes-to-EC ratios relative to the source profiles. Consequently, if a consistent set of source profiles is applied to the entire dataset, gasoline vehicles dominate vehicular OC in the winter but diesel dominates in the summer, driven by a reduction of the gasoline contribution in the summer. The seasonal pattern in the hopanes-to-EC ratios may be caused by photochemical decay of hopanes in the regional air mass in the summer or by seasonal changes in vehicle emission profiles. This seasonality causes unexpected shifts in the gasoline-diesel split and therefore points to photochemical aging.
Unlike molecular markers for other primary sources, the biomass burning markers (levoglucosan, syringols, and resin acids) are not well organized in the ratio-ratio plots (6). We analyze the fall and winter data were analyzed with fireplace and woodstove source profiles while open burning profiles were used to analyze the spring and summer data. At the upper limit, biomass smoke is estimated to contribute on average 520 ± 140 ng-C m-3 or 14.5% of the ambient OC in the fall, 210 ± 85 ng-C m-3 or 10% of the ambient OC in the winter, and 60 ± 21 ng-C/m-3 or 2% of the ambient OC in the spring and summer. In the fall and winter, there is large day-to-day variability in the amount of OC apportioned to biomass smoke. The levels of biomass smoke in Pittsburgh are much lower than in some other areas of the United States, indicating significant regional variability in the importance of biomass combustion as a source of fine particulate matter. The calculations face two major sources of uncertainty. First, the ambient ratios of levoglucosan, resin acids, and syringhaldehyde concentrations are highly variable implying that numerous sources with distinct source profiles contribute to ambient marker concentrations. In contrast to previous CMB analyses, we find that at least three distinct biomass smoke source profiles must be included in the CMB model to explain the variability in the ambient dataset. Second, the marker-to-OC ratios of available biomass smoke profiles are highly variable. This variability introduces uncertainty of more than a factor of two in the amount of ambient OC apportioned to biomass smoke by different statistically acceptable CMB solutions.
The final paper in the series of CMB papers combines our earlier results with estimates for other primary sources to evaluate the overall OC budget and to examine the relative importance of local and regional primary sources (9). The model accounts for emissions from eight primary source classes, including major anthropogenic sources such as motor vehicles, cooking, and biomass combustion as well as some primary biogenic emissions (leaf abrasion products). We consider uncertainty associated with selection of source profiles and fitting species, sampling artifacts, photochemical aging, and unknown sources. In the context of the overall organic carbon (OC) mass balance, the contributions of diesel, wood-smoke, debris, and coke-oven emissions are all small and well-constrained; however, estimates for the contributions of gasoline-vehicle and cooking emissions can vary by an order of magnitude. A best-estimate solution is presented that represents the vast majority of our CMB results; it indicates that primary OC only contributes 27±8% and 50±14% (average ± standard deviation of daily estimates) of the ambient OC in the summer and winter respectively. Approximately two-thirds of the primary OC is transported into Pittsburgh as part of the regional air mass. The ambient OC that is not apportioned by the CMB model is well correlated with secondary organic aerosol (SOA) estimates based on the EC-tracer method as well as ambient concentrations of organic species associated with SOA. Therefore, SOA appears to the major component of OC, not only in the summer, but potentially in all seasons. Primary OC does dominate the OC mass balance on a small number of non-summer days with high OC concentrations; these events are associated with specific metrological conditions such as local inversions. Primary particulate emissions only contribute a small fraction of the ambient fine-particle mass, especially in the summer.
We have also used Positive Matrix Factorization (PMF) to analyze the Pittsburgh dataset. The source-specific nature of molecular markers greatly aids the selection of the number of factors and rotations, the association of factors with specific sources, and the identification of solutions that mix emissions from a specific source across multiple factors. PMF was performed using different combinations of species to investigate the stability of the results. The exact number of factors depends on the specific combination of input species; however, all solutions had the same core set of 7 factors. Six of these factors appear related to primary emissions and one to secondary organic aerosol. The amount of OC associated with these 7 core factors was, for the most part, well constrained across 21 different PMF solutions. However comparisons with source profiles and previously published chemical mass balance (CMB) analysis indicate that PMF does not cleanly differentiate between different sources. On a seasonal average basis there is better agreement between the PMF and CMB results in the summer than the winter. Both approaches imply that secondary organic aerosol is dominant in the summer, contributing between 60% and 70% of the OC. Both PMF and CMB analysis of molecular markers data indicate that motor vehicles are a relatively minor source, contributing only 10% of the annual-average OC.
The practical implications of this work are that even in a location strongly influenced by regional transport molecular markers concentrations contain significant source information. However, the combination of photochemistry and variability in source profiles create uncertainties for source apportionment analyses. Both PMF and CMB analysis of molecular marker data indicate that secondary organic aerosol contributes ~ 75% of ambient organic aerosol in the summer.
Objective 3: Evaluation of Emission Inventories Used by Chemical Transport Models
A source-resolved has been developed to predict the contribution of eight different sources to primary organic aerosol concentrations (10). The model was applied to the eastern United States during a seventeen day pollution episode beginning on July 12, 2001. Primary organic matter (OM) and elemental carbon (EC) concentrations are tracked for eight different sources: gasoline vehicles, non-road diesel vehicles, on-road diesel vehicles, biomass burning, wood burning, natural gas combustion, road dust, and all other sources. Individual emission inventories are developed from a modified version of the NEI 1999 for each source and a three-dimensional chemical transport model (PMCAMx+) is used to predict the primary OM and EC concentrations from each source. The source-resolved model is simple to implement and is faster than the existing source-oriented models.
The predictions of the source-resolved model are compared to measurements from the STN and IMPROVE networks. Reasonably agreement is observed in the predicted total OM and the ambient data, but the model predicts EC concentrations 3 times higher than measurements from STN. Significant discrepancies exist if one compares the source-resolved predictions to the results of chemical mass balance models (CMB) for Pittsburgh and Atlanta. Significant discrepancies exist between the source-resolved model predictions and the CMB model predictions for some of the sources. For EC, Non-road diesel, according to the emission inventory, is predicted to contribute more to EC in urban areas than on-road diesel. This overprediction suggests that the non-road diesel emission inventory is currently too high. While the non-road diesel inventory should be reduced, the on-road diesel emission inventory may also need to be reduced.
Natural gas, wood burning and biomass burning are other sources that have emission inventory problems. The most striking problems are observed for natural gas; the primary OM emission inventory for natural gas should be reduced by at least 50 times the current value.
The practical consequence of this work will be critical evaluation of emissions inventories for chemical transport models used for SIP development.
Objective 5: To Assess the Importance of Photochemical Aging on Primary Organic Aerosol Composition
An analysis of ambient molecular marker data found evidence that condensed-phase organic compounds are significantly oxidized in regional air masses and in locations affected by regional transport, especially during the summer (11). The core of the analysis involves examination of a large data set of ambient organic aerosol concentrations for removal of reactive compounds relative to less-reactive compounds. The approach allows visualization of both photochemistry and mixing of emissions from multiple sources in order to differentiate between the two phenomena. The focus is on hopanes and alkenoic acids, important markers for motor vehicle and cooking emissions. Ambient data from Pittsburgh, PA and the Southeastern United States contain evidence for significant photochemical oxidation of these compounds in the summertime. There is a strong seasonal pattern in the ratio of different hopanes to elemental carbon consistent with oxidation. In addition, measurements at rural sites indicate that hopanes are severely depleted in the regional air mass during the summer. Alkenoic acids also appear to be photochemically oxidized during the summertime; however, the oxidation rate appears to be much slower than that inferred from laboratory experiments. The significance of photochemistry is supported by rudimentary calculations which indicate substantial oxidation by OH radicals and ozone on a time scale of a few days or so, comparable to time scales for regional transport. Oxidation is non-linear; therefore it represents a very substantial complication to linear source apportionment techniques such as the Chemical Mass Balance model.
The strong seasonal pattern in the hopanes-to-EC ratios causes a seasonal shift in the relative importance of primary emissions from gasoline vehicles to ambient OC. In the summer when hopanes-to-EC ratios are small and most CMB solution indicate negligible amounts of primary OC from gasoline vehicles. In contrast, CMB predicts substantial amounts of gasoline vehicle OC predicted by CMB in the winter. Therefore, photooxidation of molecular marker maybe influencing critical first order source apportionment questions such as the net contribution of motor vehicle emissions and the gasoline-diesel split. For example, assuming that molecular markers are conserved in the winter indicates that oxidation may reduce the contribution of primary emissions from motor vehicles by about a factor of 2. Alternative explanations include seasonally shifting emissions profiles.
The practical implications of these findings are that oxidation likely alters source apportionment estimates using molecular markers in locations with significant regional transport. Assessing the extent of these problems will require the laboratory data being developed as part of Objective 1.
References:
1. Robinson AL, Donahue NM, Shrivastava M, Weitkamp EA, Sage AM, Grieshop AP, Lane TE, Pierce JR, Pandis SN. Rethinking organic aerosol: semivolatile emissions and photochemical aging. Science 2007;315:1259-1262.
2. Donahue NM, Robinson AL, Huff Hartz KE, Sage AM, Weitkamp E. Competitive oxidation in atmospheric aerosols: the case for relative kinetics. Geophysical Research Letters 2005;32(16):Art. No. L16805.
3. Huff-Hartz KE, Weitkamp EA, Sage AM, Donahue NM, Robinson AL. Laboratory measurements of the oxidation kinetics of organic aerosol mixtures using a relative rate constants approach. Journal of Geophysical Research 2007;112:(D04204), doi:10.1029/2006JD007526.
4. Lambe AT, Zhang J, Sage AM, Donahue NM. Controlled OH radical production via ozone-alkene reactions for use in aerosol aging studies. Environmental Science & Technology 2007;41:2357-2363.
5. Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF. Source apportionment of molecular markers and organic aerosol – 1. polycyclic aromatic hydrocarbons and methodology for data visualization. Environmental Science & Technology 2006;40(24):7803-7810.
6. Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF. Source apportionment of molecular markers and organic aerosol – 2. Biomass smoke. Environmental Science & Technology 2006;40(24):7811-7819.
7. Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF. Source apportionment of molecular markers and organic aerosol – 3. food cooking emissions. Environmental Science & Technology 2006;40(24):7820-7827.
8. Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF, Robinson AL. Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: effects of varying source profiles and seasonal trends in ambient marker concentrations. Atmospheric Environment 2006;40(40):8002-8019.
9. Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF, Robinson AL. Insights into the primary-secondary and regional-local contributions to ambient organic aerosol in Pittsburgh, Pennsylvania. Atmospheric Environment (submitted, 2007).
10. Lane TE, Pinder RW, Shrivastava M, Robinson AL, Pandis SN. Source contributions to primary organic aerosol: comparison of the results of a source-resolved model and the chemical mass balance approach. Atmospheric Environment (in press, 2007).
11. Robinson AL, Donahue NM, Rogge WF. Photochemical oxidation and changes in molecular composition of organic aerosol in the regional context. Journal of Geophysical Research 2006;111:(D03302), doi:10.1029/2005JD006265.
Future Activities:
During the upcoming 12 months we shall focus on the following objectives:
- Conducting laboratory aging experiments using motor oil and meat cooking grease to measure oxidation kinetics of important molecular markers across a range of atmospheric conditions.
- Estimate the biases associated with heterogeneous oxidation on source apportionment estimates.
- Conduct source resolved simulations using PMCAMx and the NEI 2002 emission inventory for July 2001, October 2001, January 2002, and April 2002. Compare predictions with receptor modeling (CMB and PMF) results from the Pittsburgh supersite and other related studies.
Journal Articles on this Report : 12 Displayed | Download in RIS Format
Other project views: | All 75 publications | 26 publications in selected types | All 26 journal articles |
---|
Type | Citation | ||
---|---|---|---|
|
Donahue NM, Robinson AL, Huff Hartz KE, Sage AM, Weitkamp EA. Competitive oxidation in atmospheric aerosols: the case for relative kinetics. Geophysical Research Letters 2005;32:L16805. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit |
|
Donahue NM, Robinson AL, Stanier CO, Pandis SN. Coupled partitioning, dilution, and chemical aging of semivolatile organics. Environmental Science & Technology 2006;40(8):2635-2643. |
R832162 (2005) R832162 (2006) R832162 (Final) R831081 (2005) R831081 (Final) |
Exit Exit Exit |
|
Huff Hartz KE, Weitkamp EA, Sage AM, Donahue NM, Robinson AL. Laboratory measurements of the oxidation kinetics of organic aerosol mixtures using a relative rate constants approach. Journal of Geophysical Research-Atmospheres 2007;112(D4):D04204 (13 pp.). |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit |
|
Lambe AT, Zhang J, Sage AM, Donahue NM. Controlled OH radical production via ozone-alkene reactions for use in aerosol aging studies. Environmental Science & Technology 2007;41(7):2357-2363. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
|
Lane TE, Pinder RW, Shrivastava M, Robinson AL, Pandis SN. Source contributions to primary organic aerosol:Comparison of the results of a source-resolved model and the chemical mass balance approach. Atmospheric Environment 2007;41(18):3758-3776. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
|
Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricke A, Rogge WF. Source apportionment of molecular markers and organic aerosol--1. Polycyclic aromatic hydrocarbons and methodology for data visualization. Environmental Science & Technology 2006;40(24):7803-7810. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
|
Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF. Source apportionment of molecular markers and organic aerosol. 2. Biomass smoke. Environmental Science & Technology 2006;40(24):7811-7819. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit |
|
Robinson AL, Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF. Source apportionment of molecular markers and organic aerosol. 3. Food cooking emissions. Environmental Science & Technology 2006;40(24):7820-7827. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
|
Robinson AL, Donahue NM, Rogge WF. Photochemical oxidation and changes in molecular composition of organic aerosol in the regional context. Journal of Geophysical Research-Atmospheres 2006;111(D3):D03302 (15 pp.). |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit |
|
Robinson AL, Donahue NM, Shrivastava MK, Weitkamp EA, Sage AM, Grieshop AP, Lane TE, Pierce JR, Pandis SN. Rethinking organic aerosols: semivolatile emissions and photochemical aging. Science 2007;315(5816):1259-1262. |
R832162 (2006) R832162 (Final) R831081 (Final) |
Exit Exit Exit |
|
Shrivastava MK, Lipsky EM, Stanier CO, Robinson AL. Modeling semivolatile organic aerosol mass emissions from combustion systems. Environmental Science & Technology 2006;40(8):2671-2677. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
|
Subramanian R, Donahue NM, Bernardo-Bricker A, Rogge WF, Robinson AL. Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania:effects of varying source profiles and seasonal trends in ambient marker concentrations. Atmospheric Environment 2006;40(40):8002-8019. |
R832162 (2005) R832162 (2006) R832162 (Final) |
Exit Exit Exit |
Supplemental Keywords:
RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Air Quality, Environmental Chemistry, Monitoring/Modeling, Environmental Monitoring, Environmental Engineering, particulate organic carbon, atmospheric dispersion models, atmospheric measurements, model-based analysis, source apportionment, chemical characteristics, emissions monitoring, environmental measurement, airborne particulate matter, air quality models, air quality model, air sampling, speciation, particulate matter mass, analytical chemistry, modeling studies, chemical transport models, real-time monitoring, aerosol analyzers, chemical speciation sampling, particle size measurement, atmospheric chemistryRelevant Websites:
http://airquality.web.cmu.edu Exit
Progress 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.