MALTE-BOX
MALTE–BOX is a zero–dimensional improved version of the one-dimensional model MALTE (Model to predict new Aerosol formation in the Lower TropospherE) (Boy et al.

, 2006). We either read in the measured parent organic gas concentrations from measurements or predict biogenic emissions from vegetation with MEGAN (Model of Emissions of Gases and Aerosols from Nature - Guenther et al., 2006). The concentrations of inorganic vapours are usually taken from measurements. The further faith of all vapours is calculated using the chemical reaction schemes from the Master Chemical Mechanism (http://mcm.leeds.ac.uk/MCM/) and the Kinetic PreProcessor (KPP) (Damian et al., 2002). Aerosol dynamical processes (nucleation, coagulation, condensation, and evaporation) are calculated using the model UHMA (University of Helsinki Multicomponent Aerosol model) (Korhonen et al., 2004). We are thereby able to predict size dependent aerosol number and mass concentration together with the specific composition of atmospheric aerosol particles. MALTE-BOX has been intensively used during the last years on several scientific topics including studies on new particle formation (e.g. Ristoviski et al., 2010; Ortega et al., 2009; Wang et al., 2011), SOA mass formation (e.g. Hermansson et al., 2014) or atmospheric chemistry (e.g. Boy et al., 2013 - see also Figure 1).

Figure 1: Cumulative percentage contribution of the different SO2 oxidation mechanisms for the field station SMEAR II at Hyytiälä, Finland. The “H2SO4 by SO2 and CIs” data were calculated by first running the model with scenario D and then subtracting the values predicted by a run with scenario B. In this case only the difference between the new and old reaction rate constants for the sCIs are considered as a source term for the concentrations of sulphuric acid (for more details on the scenarios B and D see Boy et al., 2013). (sCI = stabilised Criegee Intermediate radicals)

Figure 2: Relative contributions of precursor vapours to the growth of sub-100 nm particles at (a) SMEAR II (Hyytiälä, Finland) and (b) SORPES (Nanjing, China). More details see Qi et al., 2018;

References (Publications with MALTE / MALTE-box simulations are highlighted with bold)

  • Yang, S., Liu, Z., Clusius, P. S., Liu, Y., Zou, J., Yang, Y., Zhao, S., Zhang, G., Xu, Z., Ma, Z., Yang, Y., Sun, J., Pan, Y., Ji, D., Hu, B., Yan, C., Boy, M., Kulmala, M., Wang, Y.: Chemistry of new particle formation and growth events during wintertime in suburban area of Beijing: Insights from highly polluted atmosphere, Atmos. Research, 2055, 105553, 2021, https://doi.org/10.1016/j.atmosres.2021.105553
  • Xavier, C., Rusanen. A., Zhou, P., Dean, C., Pichelstofer, L., Roldin, P., and Boy, M.: Aerosol Mass yields of selected Biogenic Volatile Organic Compounds – a theoretical study with near explicit gas-phase chemistry, Atmos. Chem. Phys., 19, 13741-13758, 2019
  • Qi, X. M., Ding, A. J., Roldin, P., Xu, Z. N., Zhou, P. T., Sarnela, N., Nie, W., Huang, X., Rusanen, A., Ehn, M., Rissanen, M., Petäjä, T., Kulmala, M. and Boy, M.: Modelling studies of HOM and its contributions to growth of new particles: comparison of boreal forest in Finland and polluted environment in China, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-235, 2018
  • Huang, X., Zhou, L., Ding, A., Qi, X., Nie, W., Wang, M., Chi, X., Petäjä, T., Kerminen, V.-M., Roldin, P., Rusanen, A., Kulmala, M. and Boy, M.: Comprehensive modelling study on observed new particle formation at the SORPES station in Nanjing, China, Atm. Chem. Phys., 16, 2477-2492, 2016.
  • Hermansson, E., Roldin, P., Rusanen, A., Mogensen, D., Kivekäs, N., Boy, M. and Swietlicki, E.: Biogenic SOA formation through gas-phase oxidation and gas-to-particle partitioning – comparison between process models of varying complexity, Atmos. Chem. Phys., 14, 11853- 11869, 2014
  • Boy, M., Mogensen, D., Smolander, S., Zhou, L., Nieminen, T., Paasonen, P., Plass-Dülmer, C., Sipilä, M., Petäjä, T., Mauldin, L., Berresheim, H. and Kulmala, M.: Oxidation of SO2 by stabilized Criegee Intermediate (sCI) radicals as a crucial source for atmospheric sulphuric acid concentrations, Atmos. Chem. Phys., 13, 3865-3879, 2013.
  • Wang, Z. B., Hu, M., Yue, D. L., Zheng, J., Zhang, R. Y., Wiedensohler, A., Wu, Z. J., Nieminen, T. and Boy, M.: Evaluation on the role of sulfuric acid in the mechanisms of new particle formation for Beijing case, Atmos. Chem. Phys., 11, 12633-12671, 2011.
  • Ristovski, Z.D., Suni, T., Kulmala, M., Boy, M., Meyer, N.K., Duplissy, J., Turnipseed, A., Morawska, L. and Baltensperger, U.: The role of sulphates and organic vapours in new particle formation in a eucalypt forest, Atmos. Chem. Phys., 10, 2919-2926, 2010.
  • Ortega, I. K., Suni, T., Grönholm, T., Boy, M., Hakola, H., Hellén, H., Valmari, T., Arvela, H., Vehkamäki, H. & Kulmala, M.: Is eucalyptol the cause of nocturnal events observed in Australia? Boreal Env. Res. 14, 606–615, 2009.
  • Boy, M., Hellmuth, O., Korhonen, H., Nillson, D., ReVelle, D., Turnipseed, A., Arnold, F. and Kulmala, M.: MALTE – Model to predict new aerosol formation in the lower troposphere, Atmos. Chem. Phys., 6, 4499–4517, 2006.
  • Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181-3210, 2006.
  • Damian, 5 V., Sandu, A., Damian, M., Potra, F., and Carmichael, G. R.: The kinetic preprocessor KPP – a software environment for solving chemical kinetics, Comput. Chem. Eng., 26, 1567-1579, 2002.
  • Korhonen H., Lehtinen K.E.J. & Kulmala M. 2004. Multicomponent aerosol dynamics model UHMA: model development and validation. Atmos. Chem. Phys., 4, 757-771.