Fraction of PM2.5 Personal Exposure Attributable to Urban Traffic: A Modeling Approach

Abstract

Personal exposure to fine particles (PM2.5) in a nonsmoking adult population has been characterized in Grenoble, France, in the framework of the European EXPOLIS study. The objective of this paper is to assess the fraction of the PM2.5 personal exposure attributable to urban traffic emissions. Volunteers (n = 40) carried a personal exposure monitoring case and filled in questionnaires on their outdoor and indoor environments, as well as time-activity diaries (15 min resolution), during 48 h (working days). Workplaces and places of residence were classified in two categories using a Geographic Information System (GIS): the atmospheric environment of some volunteers is best represented by PM ambient air monitors located in urban background sites, and others by monitors situated close to high traffic density sites (proximity sites). A partial least-squares regression model estimated the PM2.5 personal exposure (average = 36.6 μg/m3 ; standard deviation = 23.4 μg/m3) as a function of time spent in proximity (at work, home, or commuting), PMIO ambient air levels during the same days, and several confounders (passive smoking and indoor sources of particles). Six scenarios of “proximity” and “background” environments were accommodated, according to traffic intensity and road distance, in a sensitivity analysis; the best fitted model had R2 = .7. Personal PM2.5 exposures predicted by this model for different segments of the study population were compared to the background personal exposure, thus providing an estimate of the additional contribution of time spent near traffic sources. On average (percent time spent in proximity = 16.3; proximity scenario defined as the area located less than 50 m from a street with a traffic intensity greater than 20,000 vehicles/day), the PM2.5 personal exposure attributable to traffic equals 30%. For the lower tercile of the population, this contribution is 26%; for the upper tercile, it is 45%. A very influential parameter of this modeling estimation is the proportion of background ambient air particulate concentrations associated with traffic emissions. Based on local nighttime/daytime concentration ratios, a 20% proportion has been derived and used for these results. In the literature, this parameter ranges from 10% to 60%, yielding a proportion of personal exposure attributable to traffic proximity between 20% and 60%, and high-exposure situations reaching 60 to 75%. While these estimates are based only on winter data, they are in agreement with other results published in the literature. This modeling approach might be applied to other metropolitan situations, insofar as local data are used to assess the influence of traffic emissions on background ambient air PM 10 concentrations.