This study presents a comprehensive three year trend analysis of the indoor gaseous pollutants in public transit buses running on bio-diesel (B20) and ultra low sulfur diesel (ULSD) in the city of Toledo. Additionally, mass balance modeling of carbon dioxide pollutant inside the public transport buses has been conducted. The pollutants monitored in this study are carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxide (NO), and nitrogen dioxide (NO2). Two comfort level parameters of the passengers: temperature and relative humidity are also measured inside the buses.
Yearly variations of the five gaseous pollutants are studied and the accumulation of pollutant concentrations inside the bus was observed to be a result of variation in different parameters and not due to variation of a single parameter. The in-vehicle pollutant concentration trends are observed to be highly influenced by heavy traffic on the road. Over the three study period, relatively higher pollutant levels are observed for all the pollutants during winter season. Regression analysis has been used to identify the various factors that influence pollutant concentrations inside the bus. It was found that the pollutant levels are affected mainly by ventilation conditions of the bus, passenger activity inside the bus, vehicular traffic around the bus, and ambient meteorological conditions. The study identifies the important variables that affect in-vehicle pollutants in each season across different years. For example, ambient temperature, wind speed, passengers, trucks, and run/close are identified as influential factors affecting the in-vehicle CO2 concentrations in winter 2009.
A mass balance approach was used in modeling the levels of carbon dioxide (CO2) inside buses running on B20 and ULSD fuels. The model was tested over different seasons for one year period. The mixing factors for the model were calculated for both B20 and ULSD buses using a reverse approach on a seasonal basis. The infiltration rate, outdoor concentrations, and source emission rate were estimated from the literature review when developing the mass balance model. The model evaluation showed that the proposed mass balance model is capable of predicting the CO2 levels in both B20 and ULSD fueled buses in all the seasons with limited accuracy. The predictions of the proposed model heavily depend on the accurate knowledge of ambient CO2 levels.