Book Description

Travel is an everyday necessity for many people, making the environment of a passenger vehicle a place where they spend a significant amount of time. Previous studies have indicated that more than 100 volatile organic compounds (VOCs) are present in ambient air within the cabins of new cars, some of which have been found to have adverse health effects. While previous VOC models have been produced, there is still uncertainty in these models with respect to changing variables such as temperature, sunlight, and the presence of multiple VOCs. An accurate and reliable model, capable of determining the concentration of different VOCs in a car cabin as a function of time, is the focus of this research. Using data from VOC determinations in environmental test chambers emitted from polymethylpentene (PMP) films, and previous chamber modeling studies, models for VOC air concentration were produced. These models were programmed using Python, an open-source programming language that can easily be used for scientific studies. Current models give accurate estimations for chambers with and without airflow. An equation to predict the surface temperature, based on incident solar irradiance, of materials was used to adjust the VOC emission models to account for sunlight. This theoretical adjustment, while still needing to be tested, provides a good foundation for accounting for sunlight in the interior of vehicles. Overall, this work builds a better understanding of vehicle indoor air quality (VIAQ) and exposes the difficulties of modeling the complicated interior environments of passenger vehicles.