Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0

Pye, Havala O. T.; Place, Bryan K.; Murphy, Benjamin N.; Seltzer, Karl M.; D’Ambro, Emma L.; Allen, Christine; Piletic, Ivan R.; Farrell, Sara; Schwantes, Rebecca H.; Coggon, Matthew M.; Saunders, Emily; Xu, Lu; Sarwar, Golam; Hutzell, William T.; Foley, Kristen M.; Pouliot, George; Bash, Jesse O.; Stockwell, William R.

doi:10.5194/acp-2022-695

Cited by 9 publications

(20 citation statements)

References 129 publications

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“…Speciation factor of 0.52 was used to estimate the emission of alkanes from SAPRC07TC ALK5, which contains other non-aromatic compounds (i.e., alcohols, ethers, esters, and carboxylic acids) in addition to alkanes (Carter, 2015). The emission factor of alkanes that were not fully covered by ALK5 (i.e., alkanes longer than C19, (Carter, 2015)) was estimated using the HC emission recently reported by the US Environmental Protection Agency (US EPA) (Pye et al, 2022) and the study by Mcdonald et al (2018). In this study, 160 all types of alkanes including linear, branched, and cyclic alkanes were surrogated with linear alkanes based on a carbon number.…”

Section: The Camx-unipar Integrationmentioning

confidence: 99%

“…The reduction of NOx in the NOx-rich region dramatically decreases nighttime biogenic SOA yields owing to the reaction of biogenic HCs with decreased nitrate radicals, but the reduced NOx increases daytime biogenic SOA yields (Han and Jang, 2023). In particular, the formation of the low-volatile products formed via the autoxidation of ozonolysis products is an essential source of biogenic SOA as 420 discussed by Pye et al (2022). In polluted urban environments (NOx-rich), the elevation of SOA mass with lowering NOx might be more substantial in East Asia, where aromatic SOA is dominant than that in California, where terpene and alkane SOA are dominant.…”

Section: Atmospheric Implications and Uncertaintiesmentioning

confidence: 99%

“…In this model, the carbon balance between gas chemistry and the aerosol module, which is caused by consumption of carbon to form SOA, has not been addressed. Pye et al (2022) recently developed the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM v1.0), which employs explicit oxidized products to improve the carbon balance between gas mechanisms and the SOA model 440 (Pye et al, 2022). Interconnecting atmospheric gas-chemistry with SOA formation is essential because SOA formation is a dynamic process as a function of precursors HCs, NOx, SO2, and atmospheric oxidants.…”

Section: Atmospheric Implications and Uncertaintiesmentioning

confidence: 99%

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CAMx-UNIPAR Simulation of SOA Mass Formed from Multiphase Reactions of Hydrocarbons under the Central Valley Urban Atmospheres of California

Jo¹,

Jang²,

Han³

et al. 2023

Preprint

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Abstract. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model was established on the Comprehensive Air quality Model with extensions (CAMx) to process Secondary Organic Aerosol (SOA) formation by capturing multiphase reactions of hydrocarbons (HCs) in regional scales. SOA growth was simulated using a wide range of anthropogenic HCs including ten aromatics and linear alkanes with different carbon-lengths. The atmospheric processes of biogenic HCs (isoprene, terpenes, and sesquiterpene) were simulated for the major oxidation paths (ozone, OH radicals, and nitrate radicals) to predict day and night SOA formation. The UNIPAR model streamlined the multiphase partitioning of the lumping species originating from semi-explicitly predicted gas products and their heterogeneous chemistry to form non-volatile oligomeric species in both organic aerosol and inorganic aqueous phase. The CAMx-UNIPAR model predicted SOA formation at four ground urban sites (San Jose, Sacramento, Fresno, and Bakersfield) in California, United States during wintertime 2018. Overall, the simulated mass concentrations of the total organic matter, consisting of primary OA (POA) and SOA, showed a good agreement with the observations. The simulated SOA mass in the urban areas of California was predominated by alkane and terpene. During the daytime, low-volatile products originating from the autoxidation of long-chain alkanes considerably contributed to the SOA mass. In contrast, a significant amount of nighttime SOA was produced by the reaction of terpene with ozone or nitrate radicals. The spatial distributions of anthropogenic SOA associated with aromatic and alkane HCs were noticeably affected by the southward wind direction owing to the relatively long lifetime of their atmospheric oxidation, whereas those of biogenic SOA were nearly insensitive to wind direction. During wintertime 2018, the impact of inorganic aerosol hygroscopicity on the total SOA budget was not evident because of the small contribution of aromatic and isoprene products that are hydrophilic and reactive in the inorganic aqueous phase. However, an increased isoprene SOA mass was predicted during the wet periods, although its contribution to the total SOA was little.

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Section: The Camx-unipar Integrationmentioning

confidence: 99%

Section: Atmospheric Implications and Uncertaintiesmentioning

confidence: 99%

Section: Atmospheric Implications and Uncertaintiesmentioning

confidence: 99%

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CAMx-UNIPAR Simulation of SOA Mass Formed from Multiphase Reactions of Hydrocarbons under the Central Valley Urban Atmospheres of California

Jo¹,

Jang²,

Han³

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…For example, the Rapid Radiative Transfer Model for General Circulation Model (GCM) (RRTMG) has become the most widely used radiation scheme in weather and climate modeling studies at regional and global scales (Iacono, 2011). For air pollution modeling, in collaboration with other researchers, the United States Environmental Protection Agency (Pye et al., 2021) is leading the development of a new chemical mechanism, Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM), designed for the prediction of multiple endpoints including ozone (O 3 ), secondary organic aerosol, and toxics linked to cancer and respiratory diseases. The CRACMM will prioritize conservation of emitted mass, transparency in aggregation of species, and offer a platform to integrate contributions from partners.…”

Section: Introductionmentioning

confidence: 99%

Dry Deposition Methods Based on Turbulence Kinetic Energy: 1. Evaluation of Various Resistances and Sensitivity Studies Using a Single‐Point Model

et al. 2022

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Dry deposition is a two-step transport process of air pollutants from the lowest air layer into a thin air layer surrounding objects, and then via this thin layer to objects on the surface. The first and second transport processes are known respectively as aerodynamic transport and boundary layer (also known as quasi-laminar/viscous layer) transport. Surface uptake can cause changes in the physical and/or chemical state of the underlying objects (e.g., vegetation) depending upon the chemical and/or biological uptake capacity. Usually, the slowest process will determine the total rate of pollutant deposition. Thus, dry deposition plays an important role (e.g., Bash

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“…Currently, Carbon Bond version 6 (CB6r3 as of CMAQv5.3) is the most common mechanism used by the US EPA for predicting O3 (Appel et al, 2021). The Community Regional Atmospheric Chemistry Multiphase Mechanism version 1.0 (CRACMMv1.0) (Pye et al, 2022) is a next generation chemical mechanism that was distributed for the first time with the release of CMAQv5.4 in October 2022 (U.S. EPA Office of Research and Development, 2022). CRACMMv1.0 builds on the RACM2 framework (Goliff et al, 2013) and includes new representations of several organic systems, most notably monoterpenes and aromatics, and couples gas-phase with particle-phase products.…”

mentioning

confidence: 99%

Sensitivity of Northeast U.S. surface ozone predictions to the representation of atmospheric chemistry in CRACMMv1.0

Place

Hutzell

Appel

et al. 2023

Preprint

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Abstract. Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemical Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O3) across the Northeast U.S. during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3 predictions of hourly and maximum daily 8-hour average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemical Mechanism (RACM2_ae6), which better matched surface network observations in the Northeast US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated high sensitivity of O3 to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O3 predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NOx cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3 disbenefits. In contrast, semivolatile to intermediate volatility alkanes introduced in CRACMMv1.0 acted to suppress O3 formation across the regional background through the sequestration of nitrogen oxides (NOx) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the Northeast US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) and good model performance compared to recent modelling studies in the literature.

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Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0

Cited by 9 publications

References 129 publications

CAMx-UNIPAR Simulation of SOA Mass Formed from Multiphase Reactions of Hydrocarbons under the Central Valley Urban Atmospheres of California

CAMx-UNIPAR Simulation of SOA Mass Formed from Multiphase Reactions of Hydrocarbons under the Central Valley Urban Atmospheres of California

Dry Deposition Methods Based on Turbulence Kinetic Energy: 1. Evaluation of Various Resistances and Sensitivity Studies Using a Single‐Point Model

Sensitivity of Northeast U.S. surface ozone predictions to the representation of atmospheric chemistry in CRACMMv1.0

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