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

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.

SUBMITTER: Fruin SA

PROVIDER: S-EPMC4041012 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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

Fruin Scott A SA Hudda Neelakshi N Sioutas Constantinos C Delfino Ralph J RJ

Environmental science & technology 20110323 8

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 ...[more]

PMID: 21428392

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Project description:Ungulates, in particular the Central European roe deer Capreolus capreolus and the North American white-tailed deer Odocoileus virginianus, are economically and ecologically important. The two species are risk factors for deer-vehicle collisions and as browsers of palatable trees have implications for forest regeneration. However, no large-scale management systems for ungulates have been implemented, mainly because of the high efforts and costs associated with attempts to estimate population sizes of free-living ungulates living in a complex landscape. Attempts to directly estimate population sizes of deer are problematic owing to poor data quality and lack of spatial representation on larger scales. We used data on >74,000 deer-vehicle collisions observed in 2006 and 2009 in Bavaria, Germany, to model the local risk of deer-vehicle collisions and to investigate the relationship between deer-vehicle collisions and both environmental conditions and browsing intensities. An innovative modelling approach for the number of deer-vehicle collisions, which allows nonlinear environment-deer relationships and assessment of spatial heterogeneity, was the basis for estimating the local risk of collisions for specific road types on the scale of Bavarian municipalities. Based on this risk model, we propose a new "deer-vehicle collision index" for deer management. We show that the risk of deer-vehicle collisions is positively correlated to browsing intensity and to harvest numbers. Overall, our results demonstrate that the number of deer-vehicle collisions can be predicted with high precision on the scale of municipalities. In the densely populated and intensively used landscapes of Central Europe and North America, a model-based risk assessment for deer-vehicle collisions provides a cost-efficient instrument for deer management on the landscape scale. The measures derived from our model provide valuable information for planning road protection and defining hunting quota. Open-source software implementing the model can be used to transfer our modelling approach to wildlife-vehicle collisions elsewhere.

Dataset Information

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

Publications

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

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