Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3579-2024
https://doi.org/10.5194/gmd-17-3579-2024
Model evaluation paper
 | 
03 May 2024
Model evaluation paper |  | 03 May 2024

Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec

Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou

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Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global land cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959–1977, https://doi.org/10.1080/01431160412331291297, 2005. a
Batisse, E., Goudreau, S., Baumgartner, J., and Smargiassi, A.: Socio-economic inequalities in exposure to industrial air pollution emissions in Quebec public schools, Can. J. Publ. He., 108, e503–e509, https://doi.org/10.17269/CJPH.108.6166, 2017. a
Boutahar, J., Lacour, S., Mallet, V., Quélo, D., Roustan, Y., and Sportisse, B.: Development and validation of a fully modular platform for numerical modelling of air pollution: POLAIR, Int. J. Environ. Pollut., 22, 17–28, 2004. a
Brand, A., McLean, K. E., Henderson, S. B., Fournier, M., Liu, L., Kosatsky, T., and Smargiassi, A.: Respiratory hospital admissions in young children living near metal smelters, pulp mills and oil refineries in two Canadian provinces, Environ. Int., 94, 24–32, https://doi.org/10.1016/j.envint.2016.05.002, 2016. a
Buteau, S., Shekarrizfard, M., Hatzopolou, M., Gamache, P., Liu, L., and Smargiassi, A.: Air pollution from industries and asthma onset in childhood: A population-based birth cohort study using dispersion modeling, Environ. Res., 185, 109180, https://doi.org/10.1016/j.envres.2020.109180, 2020. a
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Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
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