Quantification of in-vehicle gaseous contaminants of carbon dioxide and carbon monoxide under varying climatic conditions

摘要

This study quantifies the monitored in-vehicle contaminants of carbon dioxide (CO2) and carbon monoxide (CO) under varying climatic conditions using advanced statistical methods of regression trees and analysis of variance (ANOVA). The independent influential variables affecting vehicular CO2 and CO are first identified by using regression trees after considering meteorology, monitoring periods, indoor sources, on-road vehicles, and ventilation. Next, ANOVA is used as a complementary analysis to regression tree results to determine the statistical significance of the identified influential variables and to prioritize the statistically significant variables based on the F value. Passenger ridership and month are observed to have a predominant influence on in-vehicle CO2, while month and sky conditions showed a predominant influence on vehicular CO levels. High passenger ridership on a warm/hot day with good ventilation resulted in high CO2 buildup inside the vehicle. High levels of CO are observed inside the vehicle during fall, spring, and summer months on overcast days, with low to medium indoor temperatures, moderate to good ventilating conditions, low indoor relative humidity, and low wind speeds.