空气中PM2.5的动态扩散及宏观预测

以PM2.5扩散、衰减模式为研究对象,分析探究了PM2.5的扩散规律、危机治理及其后5年的治理问题.首先通过主成分分析法,建立了PM2.5与其它污染物之间的多元非线性对数模型.同时引入相对湿度的影响因素对模型进行再度优化,提高了模型的拟合优度.运用统计学原理,得出采集点之间的PM2.5具有较高的协同性.另外分析了静态下PM2.5污染物颗粒的受力和漂移模式和从点源、面源两方面分析了PM2.5动态扩散模式,建立了PM2.5的扩散偏微分方程模型.根据建立的扩散模型,对突变的污染物浓度确定安全区域的范围.最后建立综合费用和专项费用的多目标优化模型,利用贝叶斯支持向量机方法对PM2.5进行宏观预测,并运用系统动力学理论对目标值进一步优化,并对不同治理模式进行对比分析.

Dynamic Diffusion and Macro Forecasts of PM2.5 Air

This paper is focused on the PM2.5 diffusion and decay mode,analysis itsdiffusion rule,crisis governance and governance after 5 years.We first established the multivariate nonlinear logarithmic model between PM2.5 and other pollutants by principal component analysis.Meanwhile,introduce the relative humidity factors to re-optimization the model,improves the goodness of fit of the model.Then apply the statistical principles and come to the conclusion that the PM2.5 collection point has a high synergistic.In addition,we analysis the force and drift mode of PM2.5 particulate pollutants under static condition,and the dynamic diffusion mode of PM2.5 from point and non-point source.Then,we established a diffusion partial differential equation model of PM2.5.Based on the diffusion model,we determine the safety range of the mutationalpollutant concentration.Last,we build the multi-objective optimization model about comprehensive cost and special cost,make a macroscopic prediction of PM2.5 by using Bayes support vector machines method,further optimize the target value by system dynamics theory andcompare and analyze the different governance models.