Development and application of a methodology to identify and rank the important factors affecting in-vehicle particulate matter

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• 作者：Akhil Kadiyala ; Ashok Kumar ; ^{akumar@utnet.utoledo.edu}
• 关键词：Indoor air quality ; Particulate matter ; Regression trees ; Public transport buses ; Biodiesel ; Sensitivity analysis
• 刊名：Journal of Hazardous Materials
• 出版年：2012
• 期刊代码：50_03043894
• 类别：ce
• 出版时间：30 April, 2012
• 卷：213-214
• 期：Complete
• 页码：140-146
• 文件大小：240 K

摘要

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 PM_2.5 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.