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

基于大型代表性样本的车辆空气交换率预测模型

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Abstract

The in-vehicle microenvironment is an important route of exposure to traffic-related pollutants, particularly ultrafine particles. However, significant particle losses can occur under conditions of low air exchange rate (AER) when windows are closed and air is recirculating. AERs are lower for newer vehicles and at lower speeds. Despite the importance of AER in affecting in-vehicle particle exposures, few studies have characterized AER and all have tested only a small number of cars. One reason for this is the difficulty in measuring AER with tracer gases such as SF(6), the most common method. We developed a simplified yet accurate method for determining AER using the occupants' own production of CO(2), a convenient compound to measure. By measuring initial CO(2) build-up rates and equilibrium values of CO(2) at fixed speeds, AER was calculated for 59 vehicles representative of California's fleet. AER measurements correlated and agreed well with the largest other study conducted (R(2) = 0.83). Multivariable models captured 70% of the variability in observed AER using only age, mileage, manufacturer, and speed. These results will be useful to exposure and epidemiological studies since all model variable values are easily obtainable through questionnaire.

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