Pollution sources detection via principal component analysis and rotation

Abstract

Air pollution is a widely preoccupation which needs the development of control strategies. To reach this goal, pollution sources have to be precisely identified. Principal component analysis is a possible response to this problem. Indeed this factorial method enables to detect sources, that is to have a qualitative description of them. In this work, techniques of rotation are a useful help for the association of variables with factors. We highlight the fact that the rotation must be applied to the standardized principal components, so as to keep good interpretation properties. This methodology has then been applied to a problem of air pollution on a french site