Application of regression and machine learning approaches in the analysis of mass absorption cross section of black carbon aerosols

The model described in the manuscript “Application of regression and machine learning approaches in the analysis of mass absorption cross section of black carbon aerosols. 1: Model development and evaluation” can be implemented using Python. Our model utilizes multi-wavelength light absorption _­and scattering as well as aerosol size distribution as input variables to predict MAC_BC. The investigated data analytical approaches include different multivariate regressions, support vector machine, and neural networks.

We provide a detailed user’s guide for Windows users to implement our model. The model requires a list of Python and R packages. While users can install them separately, we recommend using an “Anaconda” environment to recreate the environmental setting that we used for model development. This virtual environment contains all the required packages (the packages will be installed automatically).