Articles | Volume 16, issue 16
https://doi.org/10.5194/gmd-16-4659-2023
https://doi.org/10.5194/gmd-16-4659-2023
Development and technical paper
 | 
18 Aug 2023
Development and technical paper |  | 18 Aug 2023

Dynamic Meteorology-induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis

Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo

Related authors

Quantifying Forest Canopy Shading and Turbulence Effects on Boundary Layer Ozone over the United States
Chi-Tsan Wang, Patrick C. Campbell, Paul Makar, Siqi Ma, Irena Ivanova, Bok H. Baek, Wei-Ting Hung, Zachary Moon, Youhua Tang, Barry Baker, Rick Saylor, and Daniel Tong
EGUsphere, https://doi.org/10.5194/egusphere-2025-485,https://doi.org/10.5194/egusphere-2025-485, 2025
Short summary
Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region
Chi-Tsan Wang, Bok H. Baek, William Vizuete, Lawrence S. Engel, Jia Xing, Jaime Green, Marc Serre, Richard Strott, Jared Bowden, and Jung-Hun Woo
Earth Syst. Sci. Data, 15, 5261–5279, https://doi.org/10.5194/essd-15-5261-2023,https://doi.org/10.5194/essd-15-5261-2023, 2023
Short summary
Quantifying the importance of vehicle ammonia emissions in an urban area of northeastern USA utilizing nitrogen isotopes
Wendell W. Walters, Madeline Karod, Emma Willcocks, Bok H. Baek, Danielle E. Blum, and Meredith G. Hastings
Atmos. Chem. Phys., 22, 13431–13448, https://doi.org/10.5194/acp-22-13431-2022,https://doi.org/10.5194/acp-22-13431-2022, 2022
Short summary
The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model
Bok H. Baek, Rizzieri Pedruzzi, Minwoo Park, Chi-Tsan Wang, Younha Kim, Chul-Han Song, and Jung-Hun Woo
Geosci. Model Dev., 15, 4757–4781, https://doi.org/10.5194/gmd-15-4757-2022,https://doi.org/10.5194/gmd-15-4757-2022, 2022
Short summary
Evaluating wildfire emissions projection methods in comparisons of simulated and observed air quality
Uma Shankar, Donald McKenzie, Jeffrey P. Prestemon, Bok Haeng Baek, Mohammed Omary, Dongmei Yang, Aijun Xiu, Kevin Talgo, and William Vizuete
Atmos. Chem. Phys., 19, 15157–15181, https://doi.org/10.5194/acp-19-15157-2019,https://doi.org/10.5194/acp-19-15157-2019, 2019
Short summary

Related subject area

Atmospheric sciences
Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025,https://doi.org/10.5194/gmd-18-4667-2025, 2025
Short summary
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025,https://doi.org/10.5194/gmd-18-4625-2025, 2025
Short summary
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025,https://doi.org/10.5194/gmd-18-4571-2025, 2025
Short summary
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025,https://doi.org/10.5194/gmd-18-4499-2025, 2025
Short summary
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025,https://doi.org/10.5194/gmd-18-4417-2025, 2025
Short summary

Cited articles

Andrade, M. d. F., Kumar, P., de Freitas, E. D., Ynoue, R. Y., Martins, J., Martins, L. D., Nogueira, T., Perez-Martinez, P., de Miranda, R. M., Albuquerque, T., Gonçalves, F. L. T., Oyama, B., and Zhang, Y.: Air quality in the megacity of São Paulo: Evolution over the last 30 years and future perspectives, Atmos. Environ., 159, 66–82, https://doi.org/10.1016/j.atmosenv.2017.03.051, 2017. 
Baek, B. H.: The Integration approach of MOVES and SMOKE models, the 19th Emissions Inventory Conference, San Antonio, TX, https://gaftp.epa.gov/air/nei/ei_conference/EI20/session2/baek.pdf (last access: 28 July 2023), 2010. 
Baek, B.: CMAQ-MetEmis: Development of Dynamic Meteorology-Induced Emissions Coupler (MetEmis) for Onroad Mobile Sources in the Community Multiscale Air Quality (CMAQ) (version 1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.7150000, 2022. 
Baek, B. H. and Seppanen, C.: CEMPD/SMOKE: SMOKE v4.8.1 Public Release (January 29, 2021), Zenodo [data set], https://doi.org/10.5281/zenodo.4480334, 2021. 
Baek, B. H., Seppanen, C., Houyoux, M., Eyth, A., and Mason, R.: Installation Guide for the SMOKE-MOVES Integration Tool, https://www.cmascenter.org/smoke/documentation/0*moves_tool/SMOKE_MOVES_Tool_Installation_Guide.pdf (last access: 28 July 2023), 2010. 
Download
Short summary
To enable the direct feedback effects of aerosols and local meteorology in an air quality modeling system without any computational bottleneck, we have developed an inline meteorology-induced emissions coupler module within the U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system to dynamically model the complex MOtor Vehicle Emission Simulator (MOVES) on-road mobile emissions inline without a separate dedicated emissions processing model like SMOKE.
Share