The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1
Open accessAbstract
Abstract. The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2. 5 bias (PM2. 5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2. 5 on average in January and July. Overall, the seasonal variation in simulated PM2. 5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2. 5 concentrations decrease in the winter (when PM2. 5 is generally overestimated by CMAQ) and increase in the summer (when PM2. 5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low); however, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NOx (NO + NO2), VOC and SOx (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Description of the Advanced Research WRF Version 3
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D., Barker, D. M., Wang, W., Huang, X., & Duda, M. (2008) · UCAR/NCAR · doi:10.5065/d68s4mvh · Cited by 8,925
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., & Collins, W. D. (2008) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2008jd009944 · Cited by 5,738
The Kain–Fritsch Convective Parameterization: An Update
Kain, J. S. (2004) · Journal of Applied Meteorology · doi:10.1175/1520-0450(2004)043<0170:tkcpau>2.0.co;2 · Cited by 4,964
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., & Geron, C. (2006) · Atmospheric Chemistry and Physics · doi:10.5194/acp-6-3181-2006 · Cited by 4,603
Light Absorption by Carbonaceous Particles: An Investigative Review
Bond, T. C., & Bergstrom, R. W. (2006) · Aerosol Science and Technology · doi:10.1080/02786820500421521 · Cited by 2,980
Optical Properties of Aerosols and Clouds: The Software Package OPAC
Hess, M., Koepke, P., & Schult, I. (1998) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1998)079<0831:opoaac>2.0.co;2 · Cited by 2,909
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., & Schultz, M. G. (2001) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2001jd000807 · Cited by 2,486
Byun, D., & Schere, K. L. (2006) · Applied Mechanics Reviews · doi:10.1115/1.2128636 · Cited by 2,413
Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models
Wesely, M. L. (1989) · Atmospheric Environment (1967) · doi:10.1016/0004-6981(89)90153-4 · Cited by 2,304
WESELY, M. (2007) · Atmospheric Environment · doi:10.1016/j.atmosenv.2007.10.058 · Cited by 1,873
Cited by
Nolte, C. G., Spero, T. L., Bowden, J. H., Mallard, M. S., & Dolwick, P. D. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-18-15471-2018 · Cited by 55
Self-citation
Metadata
- Authors
- Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., & Young, J. O.
- Venue
- Geoscientific Model Development
- Publisher
- Copernicus GmbH
- Published
- 2017-04-21
- Volume
- 10
- Issue
- 4
- Pages
- 1703-1732
- ISSN
- 1991-959X (ISSN-L)
- 1991-9603
- OpenAlex
- W2606357855
- Cited by
- 336
- References
- 57
- FWCI
- 20.33
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1. https://app.cochat.ai/papers/10.5194/gmd-10-1703-2017
- The paper
- Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., . . . Young, J. O. (2017). Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1. Geoscientific Model Development. https://doi.org/10.5194/gmd-10-1703-2017
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.