Predictive model for vehicle air exchange rates based on a large, representative sample

Area of Science:

• Environmental Health
• Occupational Health
• Air Quality Science

Background:

• In-vehicle microenvironments are significant exposure routes for traffic-related pollutants, especially ultrafine particles.
• Particle loss within vehicles is influenced by air exchange rate (AER), which is lower in newer vehicles and at lower speeds.
• Previous AER characterization in vehicles is limited due to the difficulty of traditional measurement methods.

Purpose of the Study:

• To develop and validate a simplified method for determining in-vehicle air exchange rate (AER).
• To assess the relationship between vehicle characteristics, speed, and AER.
• To provide a practical method for estimating AER for exposure and epidemiological studies.

Main Methods:

• Developed a novel method to calculate AER using occupants' carbon dioxide (CO2) production.
• Measured initial CO2 build-up rates and equilibrium values in 59 representative California vehicles at fixed speeds.
• Validated the new method against a previous large-scale study, showing good correlation (R² = 0.83).

Main Results:

• The CO2-based method provided accurate AER measurements that correlated well with existing studies.
• Multivariable models explained 70% of AER variability using vehicle age, mileage, manufacturer, and speed.
• Vehicle age, mileage, manufacturer, and speed were significant predictors of AER.

Conclusions:

• The developed CO2-based method offers a simplified and accurate approach to measure in-vehicle AER.
• Vehicle characteristics and driving conditions significantly influence in-vehicle air quality.
• This method provides easily obtainable variables for future exposure and epidemiological research.