Multipollutant modeling of ozone, reactive nitrogen and HAPs across the continental US with CMAQ-CB6

Luecken, Deborah; Yarwood, Greg; Hutzell, William T.

doi:10.1016/j.atmosenv.2018.11.060

Cited by 106 publications

(59 citation statements)

References 33 publications

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“…The chlorine chemistry in the CB6r3 chemical mechanism (Yarwood et al, 2014;Luecken, et al, 2019) An updated Euler Backward Iterative (EBI) solver was also developed for the revised mechanisms. Model sensitivity simulations show that including the ClNO3 chemistry decreases monthly mean O3 by 0.1 -0.5 parts per billion by volume (ppbv).…”

Section: Updates To the Chlorine Chemistrymentioning

confidence: 99%

The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation

Appel¹,

Bash²,

Fahey³

et al. 2020

Preprint

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Abstract. The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry; updated chlorine chemistry; updated detailed bromine/iodine chemistry; updated simple halogen chemistry; addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism; updated M3Dry bi-directional deposition model; and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bi-directional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model’s hybrid vertical coordinate (HVC) system was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ53 was performed by comparing monthly and seasonal mean daily 8-hr average (MDA8) O3 and PM2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O3, CMAQ531 has higher O3 in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O3 bias. MDA8 O3 is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O3 from the lateral boundary conditions (BCs), which generally increases MDA8 O3 bias in spring and fall. For daily 24-hr average PM2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter as CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons isolating updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used, were also performed. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O3 mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O3 dry deposition to snow in CMAQ53) and lower O3 mixing ratios in mid and lower latitudes year-round (due to reduced O3 over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC system resulted in consistently higher (1.0–1.5 ppbv) MDA8 O3 mixing ratios and higher PM2.5 concentrations (0.1–0.25 µg m−3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O3 is generally higher with M3Dry outside of summer, while PM2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to some surfaces between the two models. For ambient NH3, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias, but larger error and lower correlation, in the summer.

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Section: Updates To the Chlorine Chemistrymentioning

confidence: 99%

The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation

Appel¹,

Bash²,

Fahey³

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…ESX allows for the investigation of for example chemistry and deposition processes within the lowest tens of metres of the atmosphere (similar in concept to e.g. Makar et al, 1999;Ashworth et al, 2015). The most recent version of the ESX model also allows for Lagrangian trajectory simulations, which will enable the exploration of detailed chemical analysis as air masses traverse perhaps hundreds of kilometres (similar to e.g.…”

Section: Introductionmentioning

confidence: 99%

GenChem v1.0 – a chemical pre-processing and testing system for atmospheric modelling

et al. 2020

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Abstract. This paper outlines the structure and usage of the GenChem system, which includes a chemical pre-processor GenChem.py) and a simple box model (boxChem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the Meteorological Synthesizing Centre – West of the European Monitoring and Evaluation Programme (EMEP MSC-W) CTM and related systems, boxChem can be run as a stand-alone chemical solver, enabling for example easy testing of chemical mechanisms against each other. This paper presents an outline of the usage of the GenChem system, explaining input and output files, and presents some examples of usage. The code needed to run GenChem is released as open-source code under the GNU license.

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“…Listed models were developed in whole or in part by EPA, except the Pacific Northwest National Laboratory's Salish Sea Model. Model references: VELMA (Abdelnour et al 2011(Abdelnour et al , 2013McKane et al 2014b); SMURF (Snyder et al 2019); CORESET (Melbourne-Thomas et al 2011a, b); HexSim (Schumaker et al 2014); EPA H2O (Russell et al 2015); HWBI (Orlando et al 2017); Salish Sea Model (Khangaonkar et al 2018(Khangaonkar et al , 2019; CMAQ (Luecken et al 2019); BenMAP-CE (Davidson et al 2007;Berman et al 2012) decision makers in balancing ecological, economic and social criteria over timescales relevant to immediate needs and long-term planning goals. A major challenge in modeling coastal ecosystems is the establishment of a coupled human-natural modeling framework capable of addressing transfers of terrestrial nutrients and toxic chemicals to marine waters, and consequent impacts on marine life and ecosystem goods and services.…”

Section: Potential Additional Envision Plug-ins For Coastal Ecosystemmentioning

confidence: 99%

An Integrated Multi-Model Decision Support Framework for Evaluating Ecosystem-Based Management Options for Coupled Human-Natural Systems

McKane

Brookes

Djang

et al. 2020

Ecosystem-Based Management, Ecosystem Services and Aquatic Biodiversity

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Simulation models offer a way to achieve a comprehensive understanding of the consequences of alternative community planning scenarios. For example, a community might want to understand how a particular decision-such as expanding an urban growth boundary into lands zoned for agriculture-will result in ecological, economic, and social tradeoffs for various stakeholder groups. This chapter explores the utility of ENVISION, a spatially-explicit decision support framework that integrates various ecological and human systems model "plug-ins" for informing Ecosystem-Based Management (EBM) options. While ENVISION already has a reasonably large tool box of such plug-ins, its usefulness could be further extended to address a wider range of community and ecosystem types. We specifically examine how a suite of existing U.S. Environmental Protection Agency decision support tools (VELMA, HexSim, CORESET, Coral PF and others) could significantly extend ENVISION's plug-in toolbox for coastal ecosystem EBM, inclusive of terrestrial-marine interactions and restoration goals of coastal communities dependent on marine ecosystem services.

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Multipollutant modeling of ozone, reactive nitrogen and HAPs across the continental US with CMAQ-CB6

Cited by 106 publications

References 33 publications

The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation

The Community Multiscale Air Quality (CMAQ) Model Versions 5.3 and 5.3.1: System Updates and Evaluation

GenChem v1.0 – a chemical pre-processing and testing system for atmospheric modelling

An Integrated Multi-Model Decision Support Framework for Evaluating Ecosystem-Based Management Options for Coupled Human-Natural Systems

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