GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American PAHs and benzene

Abstract. Environment and Climate Change Canada’s online air quality forecasting model, GEMMACH, was extended to simulate atmospheric concentrations of benzene and seven polycyclic aromatic hydrocarbons (PAHs): phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, and benzo(a)pyrene (BaP). In the expanded model, benzene and PAHs are emitted from major point, area, and mobile sources, with emissions based on recent emission factors. Modelled PAHs undergo gas-particle partitioning (whereas benzene is only in the gas phase), atmospheric transport, oxidation, cloud processing, and dry and wet deposition. To represent PAH gas-particle partitioning, the Dachs-Eisenreich scheme was used, and we have improved gas-particle partitioning parameters based on an empirical analysis to get significantly better gas-particle partitioning results than the previous North American PAH model, AURAMS-PAH. Other added process parameterizations include the particle phase benzo(a)pyrene reaction with ozone via the Kwamena scheme and gas-phase scavenging of PAHs by snow via vapor sorption to the snow surface. The resulting GEM-MACH-PAH model was used to generate the first online model simulations of PAH emissions, transport, chemical transformation and deposition for a high resolution domain (2.5-km grid cell spacing) in North America, centered on the PAH-data-rich region of southern Ontario, Canada and the north-eastern United States. Model output for two seasons was compared to measurements from three monitoring networks spanning Canada and the U.S. Average summertime model results were found to be statistically indistinguishable from measurements of benzene and all seven PAHs. The same was true for the winter seasonal mean, except for BaP, which had a statistically significant positive bias.We present evidence that the benzo(a)pyrene results may be ameliorated via further improvements to PM and oxidant processes and transport. Our analysis focused on four key components to the prediction of atmospheric PAH levels: spatial variability; sensitivity to mobile emissions; gas-particle partitioning; and wet deposition. Spatial variability of PAHs/PM2.5 at 2.5-km resolution was found to be comparable to measurements. Predicted ambient surface concentrations of benzene and the PAHs were found to be critically dependent on mobile emission factors, indicating the mobile emissions sector has a significant influence on ambient PAH levels in the study region. PAH wet deposition was overestimated due to additive precipitation biases in the model and the measurements. Our overall performance evaluation suggests that GEM-MACHPAH can provide seasonal estimates for benzene and PAHs and be suitable for emissions scenario simulations.

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GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American polycyclic aromatic hydrocarbons and benzene

Geoscientific Model Development ◽

10.5194/gmd-11-2609-2018 ◽

2018 ◽

Vol 11 (7) ◽

pp. 2609-2632 ◽

Cited By ~ 7

Author(s):

Cynthia H. Whaley ◽

Elisabeth Galarneau ◽

Paul A. Makar ◽

Ayodeji Akingunola ◽

Wanmin Gong ◽

...

Keyword(s):

Polycyclic Aromatic Hydrocarbons ◽

High Resolution ◽

Spatial Variability ◽

Gas Phase ◽

Aromatic Hydrocarbons ◽

North American ◽

Wet Deposition ◽

Emission Factors ◽

Mobile Emissions ◽

Polycyclic Aromatic

Abstract. Environment and Climate Change Canada's online air quality forecasting model, GEM-MACH, was extended to simulate atmospheric concentrations of benzene and seven polycyclic aromatic hydrocarbons (PAHs): phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, and benzo(a)pyrene. In the expanded model, benzene and PAHs are emitted from major point, area, and mobile sources, with emissions based on recent emission factors. Modelled PAHs undergo gas–particle partitioning (whereas benzene is only in the gas phase), atmospheric transport, oxidation, cloud processing, and dry and wet deposition. To represent PAH gas–particle partitioning, the Dachs–Eisenreich scheme was used, and we have improved gas–particle partitioning parameters based on an empirical analysis to get significantly better gas–particle partitioning results than the previous North American PAH model, AURAMS-PAH. Added process parametrizations include the particle phase benzo(a)pyrene reaction with ozone via the Kwamena scheme and gas-phase scavenging of PAHs by snow via vapour sorption to the snow surface. The resulting GEM-MACH-PAH model was used to generate the first online model simulations of PAH emissions, transport, chemical transformation, and deposition for a high-resolution domain (2.5 km grid cell spacing) in North America, centred on the PAH data-rich region of southern Ontario, Canada and the northeastern US. Model output for two seasons was compared to measurements from three monitoring networks spanning Canada and the US Average spring–summertime model results were found to be statistically unbiased from measurements of benzene and all seven PAHs. The same was true for the fall–winter seasonal mean, except for benzo(a)pyrene, which had a statistically significant positive bias. We present evidence that the benzo(a)pyrene results may be ameliorated via further improvements to particulate matter and oxidant processes and transport. Our analysis focused on four key components to the prediction of atmospheric PAH levels: spatial variability, sensitivity to mobile emissions, gas–particle partitioning, and wet deposition. Spatial variability of PAHs ∕ PM2.5 at a 2.5 km resolution was found to be comparable to measurements. Predicted ambient surface concentrations of benzene and the PAHs were found to be critically dependent on mobile emission factors, indicating the mobile emissions sector has a significant influence on ambient PAH levels in the study region. PAH wet deposition was overestimated due to additive precipitation biases in the model and the measurements. Our overall performance evaluation suggests that GEM-MACH-PAH can provide seasonal estimates for benzene and PAHs and is suitable for emissions scenario simulations.

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Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

10.5194/acp-2017-193 ◽

2017 ◽

Author(s):

Benjamin N. Murphy ◽

Matthew C. Woody ◽

Jose L. Jimenez ◽

Ann Marie G. Carlton ◽

Patrick L. Hayes ◽

...

Keyword(s):

United States ◽

Gas Phase ◽

Transport Model ◽

Organic Aerosol ◽

Uncertain Parameters ◽

Northern California ◽

Monitoring Networks ◽

Modest Improvement ◽

Organic Vapor ◽

Combustion Emissions

Abstract. Mounting evidence from field and laboratory observations coupled with atmospheric model analyses show that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality (CMAQ) Model v5.2 accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the SOA from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: 1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, 2) multigenerational aging of organic vapor products from known SOA precursors (e.g. toluene, alkanes, etc), 3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and 4) reversible organic-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially-averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 % and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 km and 12 km), gas-phase chemical mechanisms, seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May–June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g. correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g. bias at Pasadena from −5.62 to −2.42 μg m−3). Daily-averaged predictions of observations at routine monitoring networks from simulations over the continental U.S. (CONUS) in 2011 show modest improvement during winter with mean biases reducing from 1.14 to 0.73 μg m−3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

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The effect of dry and wet deposition of condensable vapors on secondary organic aerosols concentrations over the continental US

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-13731-2014 ◽

2014 ◽

Vol 14 (9) ◽

pp. 13731-13767 ◽

Cited By ~ 8

Author(s):

C. Knote ◽

A. Hodzic ◽

J. L. Jimenez

Keyword(s):

Gas Phase ◽

Dry Deposition ◽

Wet Deposition ◽

Water Solubility ◽

Transport Model ◽

Chemistry Transport Model ◽

Dry And Wet Deposition ◽

Modeling Systems ◽

Sensitivity Studies ◽

Wet Removal

Abstract. The effect of dry and wet deposition of semi-volatile organic compounds (SVOC) in the gas-phase on the concentrations of secondary organic aerosol (SOA) is reassessed using recently derived water solubility information. The water solubility of SVOCs was implemented as a function of their volatility distribution within the regional chemistry transport model WRF-Chem, and simulations were carried out over the continental United States for the year 2010. Results show that including dry and wet removal of gas-phase SVOCs reduces annual average surface concentrations of anthropogenic and biogenic SOA by 48% and 63% respectively over the continental US Dry deposition of gas-phase SVOCs is found to be more effective than wet deposition in reducing SOA concentrations (−40% vs. −8% for anthropogenics, −52% vs. −11% for biogenics). Reductions for biogenic SOA are found to be higher due to the higher water solubility of biogenic SVOCs. The majority of the total mass of SVOC + SOA is actually deposited via the gas-phase (61% for anthropogenics, 76% for biogenics). A number of sensitivity studies shows that this is a robust feature of the modeling system. Other models that do not consider dry and wet removal of gas-phase SVOCs would hence overestimate SOA concentrations by roughly 50%. Assumptions about the water solubility of SVOCs made in some current modeling systems (H* = 105 M atm−1; H* = H* (HNO3)) still lead to an overestimation of 25% / 10% compared to our best estimate. A saturation effect is observed for Henry's law constants above 108 M atm−1, suggesting an upper bound of reductions in surface level SOA concentrations by 60% through removal of gas-phase SVOCs. Considering reactivity of gas-phase SVOCs in the dry deposition scheme was found to be negligible. Further sensitivity studies where we reduce the volatility of organic matter show that consideration of gas-phase SVOC removal still reduces average SOA concentrations by 31% on average. We consider this a lower bound for the effect of gas-phase SVOC removal on SOA concentrations.

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Inconsistency of ammonium–sulfate aerosol ratios with thermodynamic models in the eastern US: a possible role of organic aerosol

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-5107-2017 ◽

2017 ◽

Vol 17 (8) ◽

pp. 5107-5118 ◽

Cited By ~ 33

Author(s):

Rachel F. Silvern ◽

Daniel J. Jacob ◽

Patrick S. Kim ◽

Eloise A. Marais ◽

Jay R. Turner ◽

...

Keyword(s):

Gas Phase ◽

Ammonium Sulfate ◽

Wet Deposition ◽

Transport Model ◽

Organic Aerosol ◽

Sulfate Aerosol ◽

Chemical Transport Model ◽

Thermodynamic Models ◽

So2 Emissions ◽

Mass Transfer Limitation

Abstract. Thermodynamic models predict that sulfate aerosol (S(VI) ≡ H2SO4(aq) + HSO4−+ SO42−) should take up available ammonia (NH3) quantitatively as ammonium (NH4+) until the ammonium sulfate stoichiometry (NH4)2SO4 is close to being reached. This uptake of ammonia has important implications for aerosol mass, hygroscopicity, and acidity. When ammonia is in excess, the ammonium–sulfate aerosol ratio R =  [NH4+] ∕ [S(VI)] should approach 2, with excess ammonia remaining in the gas phase. When ammonia is in deficit, it should be fully taken up by the aerosol as ammonium and no significant ammonia should remain in the gas phase. Here we report that sulfate aerosol in the eastern US in summer has a low ammonium–sulfate ratio despite excess ammonia, and we show that this is at odds with thermodynamic models. The ammonium–sulfate ratio averages only 1.04 ± 0.21 mol mol−1 in the Southeast, even though ammonia is in large excess, as shown by the ammonium–sulfate ratio in wet deposition and by the presence of gas-phase ammonia. It further appears that the ammonium–sulfate aerosol ratio is insensitive to the supply of ammonia, remaining low even as the wet deposition ratio exceeds 6 mol mol−1. While the ammonium–sulfate ratio in wet deposition has increased by 5.8 % yr−1 from 2003 to 2013 in the Southeast, consistent with SO2 emission controls, the ammonium–sulfate aerosol ratio decreased by 1.4–3.0 % yr−1. Thus, the aerosol is becoming more acidic even as SO2 emissions decrease and ammonia emissions stay constant; this is incompatible with simple sulfate–ammonium thermodynamics. A tentative explanation is that sulfate particles are increasingly coated by organic material, retarding the uptake of ammonia. Indeed, the ratio of organic aerosol (OA) to sulfate in the Southeast increased from 1.1 to 2.4 g g−1 over the 2003–2013 period as sulfate decreased. We implement a simple kinetic mass transfer limitation for ammonia uptake to sulfate aerosols in the GEOS-Chem chemical transport model and find that we can reproduce both the observed ammonium–sulfate aerosol ratios and the concurrent presence of gas-phase ammonia. If sulfate aerosol becomes more acidic as OA ∕ sulfate ratios increase, then controlling SO2 emissions to decrease sulfate aerosol will not have the co-benefit of suppressing acid-catalyzed secondary organic aerosol (SOA) formation.

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The effect of dry and wet deposition of condensable vapors on secondary organic aerosols concentrations over the continental US

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-1-2015 ◽

2015 ◽

Vol 15 (1) ◽

pp. 1-18 ◽

Cited By ~ 55

Author(s):

C. Knote ◽

A. Hodzic ◽

J. L. Jimenez

Keyword(s):

Gas Phase ◽

Dry Deposition ◽

Wet Deposition ◽

Water Solubility ◽

Transport Model ◽

Dry And Wet Deposition ◽

Modeling Systems ◽

Sensitivity Studies ◽

Made In ◽

Wet Removal

Abstract. The effect of dry and wet deposition of semi-volatile organic compounds (SVOCs) in the gas phase on the concentrations of secondary organic aerosol (SOA) is reassessed using recently derived water solubility information. The water solubility of SVOCs was implemented as a function of their volatility distribution within the WRF-Chem regional chemistry transport model, and simulations were carried out over the continental United States for the year 2010. Results show that including dry and wet removal of gas-phase SVOCs reduces annual average surface concentrations of anthropogenic and biogenic SOA by 48 and 63% respectively over the continental US. Dry deposition of gas-phase SVOCs is found to be more effective than wet deposition in reducing SOA concentrations (−40 vs. −8% for anthropogenics, and −52 vs. −11% for biogenics). Reductions for biogenic SOA are found to be higher due to the higher water solubility of biogenic SVOCs. The majority of the total mass of SVOC + SOA is actually deposited via the gas phase (61% for anthropogenics and 76% for biogenics). Results are sensitive to assumptions made in the dry deposition scheme, but gas-phase deposition of SVOCs remains crucial even under conservative estimates. Considering reactivity of gas-phase SVOCs in the dry deposition scheme was found to be negligible. Further sensitivity studies where we reduce the volatility of organic matter show that consideration of gas-phase SVOC removal still reduces average SOA concentrations by 31% on average. We consider this a lower bound for the effect of gas-phase SVOC removal on SOA concentrations. A saturation effect is observed for Henry's law constants above 108 M atm−1, suggesting an upper bound of reductions in surface level SOA concentrations by 60% through removal of gas-phase SVOCs. Other models that do not consider dry and wet removal of gas-phase SVOCs would hence overestimate SOA concentrations by roughly 50%. Assumptions about the water solubility of SVOCs made in some current modeling systems (H* = H* (CH3COOH); H* = 105 M atm−1; H* = H* (HNO3)) still lead to an overestimation of 35%/25%/10% compared to our best estimate.

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