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Additional resources for Aerosols: Science and Case Studies
Debry, B. Sportisse, and B. Jourdain, A stochastic approach for the numerical simulation of the general dynamics equation for aerosols, J. Comput. , vol. 184, no. 2, pp. 649–669, 2003.  W. J. Menz, J. Akroyd, and M. Kraft, Stochastic solution of population balance equations for reactor networks, J. Comput. , vol. 256, pp. 615–629, 2014.  S. L. Rani, R. Dhariwal, and D. L. Koch, A stochastic model for the relative motion of high Stokes number particles in isotropic turbulence, J. , vol. 756, pp.
Nagpure, and R. M. Harrison, Preliminary estimates of nanoparticle number emissions from road vehicles in megacity Delhi and associated health impacts, Environ. Sci. , vol. 45, no. 13, pp. 5514–5521, 2011.  J. Kirkby, J. Duplissy, K. Sengupta, C. Frege, H. Gordon, C. Williamson, M. Heinritzi, M. Simon, C. Yan, J. Almeida, J. Tröstl, T. Nieminen, I. K. Ortega, R. Wagner, A. Adamov, A. Amorim, A. K. Bernhammer, F. Bianchi, M. Breitenlechner, S. Brilke, X. Chen, J. Craven, A. Dias, S. Ehrhart, R.
9 çè m12 ÷ø In theory, once the PBE was converted to forms such as Eq. (7), in which unresolved moments are involved, it can be further numerically solved together with Eq. (10). 4. Quadrature method of moments The QMOM and its variants such as DQMOM are regarded as the mostly used method of moments in the implementation of the PBM [47, 48]. This method achieves great success in that it has no any physical assumptions and has no requirement for the form of dynamics kernels. Thus, this method can deal with all relevant aerosol dynamics problems.
Aerosols: Science and Case Studies by Konstantin Volkov