摘要
Brownian coagulation is the most important inter-particle mechanism affecting the size distribution of aerosols. Analytical solutions to the governing population balance equation （PBE） remain a challenging issue. In this work, we develop an analytical model to solve the PBE under Brownian coagulation based on the Taylor-expansion method of moments. The proposed model has a clear advantage over conventional asymptotic models in both precision and efficiency. We first analyze the geometric standard deviation （GSD） of aerosol size distribution. The new model is then implemented to determine two analytic solu- tions, one with a varying GSD and the other with a constant GSD, The varying solution traces the evolution of the size distribution, whereas the constant case admits a decoupled solution for the zero and second moments, Both solutions are confirmed to have the same precision as the highly reliable numerical model, implemented by the fourth-order Runge-Kutta algorithm, and the analytic model requires significantly less computational time than the numerical approach. Our results suggest that the proposed model has great potential to replace the existing numerical model, and is thus recommended for the study of physical aerosol characteristics, especially for rapid predictions of haze formation and evolution,
Brownian coagulation is the most important inter-particle mechanism affecting the size distribution of aerosols. Analytical solutions to the governing population balance equation （PBE） remain a challenging issue. In this work, we develop an analytical model to solve the PBE under Brownian coagulation based on the Taylor-expansion method of moments. The proposed model has a clear advantage over conventional asymptotic models in both precision and efficiency. We first analyze the geometric standard deviation （GSD） of aerosol size distribution. The new model is then implemented to determine two analytic solu- tions, one with a varying GSD and the other with a constant GSD, The varying solution traces the evolution of the size distribution, whereas the constant case admits a decoupled solution for the zero and second moments, Both solutions are confirmed to have the same precision as the highly reliable numerical model, implemented by the fourth-order Runge-Kutta algorithm, and the analytic model requires significantly less computational time than the numerical approach. Our results suggest that the proposed model has great potential to replace the existing numerical model, and is thus recommended for the study of physical aerosol characteristics, especially for rapid predictions of haze formation and evolution,
基金
the Alexander von Humboldt Foundation(Grant No.1136169)
the Open Foundation of State Key Laboratory of Loess and Quaternary Geology for financial supports
the joint support of the National Natural Science Foundation of China(Grant Nos.11372299 and 11132008)
the Sino-German Research Project (Grant No.GZ971)
ZJNSF(Grant No.LY13E080007)
