The present study adopted a two-step approach in the development of a methodology to identify and rank the important factors affecting in-vehicle particulate matter (PM). Firstly, the important factors affecting the monitored vehicular PM were identified using regression trees, considering several factors (meteorology, time-related, indoor sources, on-road, and ventilation) that could impact the vehicular indoor air quality. Secondly, the analysis of variance was used as a complementary sensitivity analysis to the regression tree results to rank the significant factors affecting vehicular PM. In-vehicle PM concentrations and sub-micron particle numbers were mainly influenced by the monthly/seasonal changes. Visibility and ambient PM2.5 additionally influenced the sub-micron particles. Furthermore, this study emphasized the variation of the monitored vehicular PM levels under different combinations of the ranked influential factors. (C) 2012 Elsevier B.V. All rights reserved.