Articles | Volume 12, issue 4
Geosci. Model Dev., 12, 1403–1422, 2019
https://doi.org/10.5194/gmd-12-1403-2019

Special issue: The PALM model system 6.0 for atmospheric and oceanic boundary-layer...

Geosci. Model Dev., 12, 1403–1422, 2019
https://doi.org/10.5194/gmd-12-1403-2019
Model description paper
11 Apr 2019
Model description paper | 11 Apr 2019

Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation

Mona Kurppa et al.

Related authors

Technical note: Dispersion of cooking-generated aerosols from an urban street canyon
Shang Gao, Mona Kurppa, Chak K. Chan, and Keith Ngan
Atmos. Chem. Phys., 22, 2703–2726, https://doi.org/10.5194/acp-22-2703-2022,https://doi.org/10.5194/acp-22-2703-2022, 2022
Short summary
The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-1079,https://doi.org/10.5194/acp-2021-1079, 2022
Revised manuscript accepted for ACP
Short summary
Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021,https://doi.org/10.5194/gmd-14-7411-2021, 2021
Short summary
Sensitivity analysis of the PALM model system 6.0 in the urban environment
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021,https://doi.org/10.5194/gmd-14-4443-2021, 2021
Short summary
Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air Quality in Beijing, China
Benjamin Foreback, Lubna Dada, Kaspar Dällenbach, Chao Yan, Lili Wang, Biwu Chu, Ying Zhou, Tom V. Kokkonen, Mona Kurppa, Rosaria E. Pileci, Yonghong Wang, Tommy Chan, Juha Kangasluoma, Lin Zhuohui, Yishou Guo, Chang Li, Rima Baalbaki, Joni Kujansuu, Xiaolong Fan, Zemin Feng, Pekka Rantala, Shahzad Gani, Federico Bianchi, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, Yongchun Liu, and Pauli Paasonen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-192,https://doi.org/10.5194/acp-2021-192, 2021
Revised manuscript accepted for ACP
Short summary

Related subject area

Atmospheric sciences
A machine learning methodology for the generation of a parameterization of the hydroxyl radical
Daniel C. Anderson, Melanie B. Follette-Cook, Sarah A. Strode, Julie M. Nicely, Junhua Liu, Peter D. Ivatt, and Bryan N. Duncan
Geosci. Model Dev., 15, 6341–6358, https://doi.org/10.5194/gmd-15-6341-2022,https://doi.org/10.5194/gmd-15-6341-2022, 2022
Short summary
Large-eddy simulations with ClimateMachine v0.2.0: a new open-source code for atmospheric simulations on GPUs and CPUs
Akshay Sridhar, Yassine Tissaoui, Simone Marras, Zhaoyi Shen, Charles Kawczynski, Simon Byrne, Kiran Pamnany, Maciej Waruszewski, Thomas H. Gibson, Jeremy E. Kozdon, Valentin Churavy, Lucas C. Wilcox, Francis X. Giraldo, and Tapio Schneider
Geosci. Model Dev., 15, 6259–6284, https://doi.org/10.5194/gmd-15-6259-2022,https://doi.org/10.5194/gmd-15-6259-2022, 2022
Short summary
Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework
Joshua Chun Kwang Lee, Javier Amezcua, and Ross Noel Bannister
Geosci. Model Dev., 15, 6197–6219, https://doi.org/10.5194/gmd-15-6197-2022,https://doi.org/10.5194/gmd-15-6197-2022, 2022
Short summary
OpenIFS/AC: atmospheric chemistry and aerosol in OpenIFS 43r3
Vincent Huijnen, Philippe Le Sager, Marcus O. Köhler, Glenn Carver, Samuel Rémy, Johannes Flemming, Simon Chabrillat, Quentin Errera, and Twan van Noije
Geosci. Model Dev., 15, 6221–6241, https://doi.org/10.5194/gmd-15-6221-2022,https://doi.org/10.5194/gmd-15-6221-2022, 2022
Short summary
Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022,https://doi.org/10.5194/gmd-15-6143-2022, 2022
Short summary

Cited articles

Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: development and first applications, Atmos. Environ., 32, 2981–2999, https://doi.org/10.1016/S1352-2310(98)00006-5, 1998. a
Albriet, B., Sartelet, K., Lacour, S., Carissimo, B., and Seigneur, C.: Modelling aerosol number distributions from a vehicle exhaust with an aerosol CFD model, Atmos. Environ., 44, 1126–1137, https://doi.org/10.1016/j.atmosenv.2009.11.025, 2010. a, b, c
Ankilov, A., Baklanov, A., Colhoun, M., Enderle, K.-H., Gras, J., Julanov, Y., Kaller, D., Lindner, A., Lushnikov, A., Mavliev, R., McGovern, F., Mirme, A., O'Connor, T., Podzimek, J., Preining, O., Reischl, G., Rudolf, R., Sem, G., Szymanski, W., Tamm, E., Vrtala, A., Wagner, P., Winklmayr, W., and Zagaynov, V.: Intercomparison of number concentration measurements by various aerosol particle counters, Atmos. Res., 62, 177–207, https://doi.org/10.1016/S0169-8095(02)00010-8, 2002. a
Antoniou, N., Montazeri, H., Wigo, H., Neophytou, M. K.-A., Blocken, B., and Sandberg, M.: CFD and wind-tunnel analysis of outdoor ventilation in a real compact heterogeneous urban area: Evaluation using “air delay”, Build. Environ., 126, 355–372, https://doi.org/10.1016/j.buildenv.2017.10.013, 2017. a
Anttila, T., Kerminen, V.-M., and Lehtinen, K. E.: Parameterizing the formation rate of new particles: The effect of nuclei self-coagulation, J. Aerosol Sci., 41, 621–636, https://doi.org/10.1016/j.jaerosci.2010.04.008, 2010. a
Download
Short summary
This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM model system 6.0. The first evaluation study shows excellent agreements with measurements. Furthermore, we show that ignoring the dry deposition of aerosol particles can overestimate aerosol number concentrations by 20 %, whereas condensation and dissolutional growth increase the total aerosol mass by over 10 % in this specific urban environment.