Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5883-2022
https://doi.org/10.5194/gmd-15-5883-2022
Model description paper
 | 
28 Jul 2022
Model description paper |  | 28 Jul 2022

TransClim (v1.0): a chemistry–climate response model for assessing the effect of mitigation strategies for road traffic on ozone

Vanessa Simone Rieger and Volker Grewe

Related authors

The contribution of transport emissions to ozone mixing ratios and methane lifetime in 2015 and 2050 in the Shared Socioeconomic Pathways (SSPs)
Mariano Mertens, Sabine Brinkop, Phoebe Graf, Volker Grewe, Johannes Hendricks, Patrick Jöckel, Anna Lanteri, Sigrun Matthes, Vanessa S. Rieger, Mattia Righi, and Robin N. Thor
Atmos. Chem. Phys., 24, 12079–12106, https://doi.org/10.5194/acp-24-12079-2024,https://doi.org/10.5194/acp-24-12079-2024, 2024
Short summary
An advanced method of contributing emissions to short-lived chemical species (OH and HO2): the TAGGING 1.1 submodel based on the Modular Earth Submodel System (MESSy 2.53)
Vanessa S. Rieger, Mariano Mertens, and Volker Grewe
Geosci. Model Dev., 11, 2049–2066, https://doi.org/10.5194/gmd-11-2049-2018,https://doi.org/10.5194/gmd-11-2049-2018, 2018
Short summary
Revisiting the contribution of land transport and shipping emissions to tropospheric ozone
Mariano Mertens, Volker Grewe, Vanessa S. Rieger, and Patrick Jöckel
Atmos. Chem. Phys., 18, 5567–5588, https://doi.org/10.5194/acp-18-5567-2018,https://doi.org/10.5194/acp-18-5567-2018, 2018
Short summary

Related subject area

Atmospheric sciences
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024,https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024,https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024,https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024,https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024,https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary

Cited articles

Dahlmann, K., Grewe, V., Frömming, C., and Burkhardt, U.: Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?, Transport. Res. D: Tr. E., 46, 40–55, https://doi.org/10.1016/j.trd.2016.03.006, 2016. a
Deckert, R., Jöckel, P., Grewe, V., Gottschaldt, K.-D., and Hoor, P.: A quasi chemistry-transport model mode for EMAC, Geosci. Model Dev., 4, 195–206, https://doi.org/10.5194/gmd-4-195-2011, 2011. a
Dietmüller, S., Jöckel, P., Tost, H., Kunze, M., Gellhorn, C., Brinkop, S., Frömming, C., Ponater, M., Steil, B., Lauer, A., and Hendricks, J.: A new radiation infrastructure for the Modular Earth Submodel System (MESSy, based on version 2.51), Geosci. Model Dev., 9, 2209–2222, https://doi.org/10.5194/gmd-9-2209-2016, 2016. a
Dodge, M.: Combined use of modeling techniques and smog chamber data to derive ozoneprecursor relationships, in: International Conference on Photochemical Oxidant Pollution and its Control: Proceedings, edited by: Dimitriades, B., U.S. Environmental Protection Agency, Environmental Sciences Research Laboratory, Research Triangle Park, N.C., Vol. II., 881–889, ePA/600/3-77-001b, 1977. a
Fouquart, Y. and Bonnel, B.: Computations of solar heating of the Earth's atmosphere: A new parameterization, Beitr. Phys. Atmos., 53, 35–62, 1980. a
Download
Short summary
Road traffic emissions of nitrogen oxides, volatile organic compounds and carbon monoxide produce ozone in the troposphere and thus influence Earth's climate. To assess the ozone response to a broad range of mitigation strategies for road traffic, we developed a new chemistry–climate response model called TransClim. It is based on lookup tables containing climate–response relations and thus is able to quickly determine the climate response of a mitigation option.