Article

PM2.5 of ambient origin: estimates and exposure errors relevant to PM epidemiology.

Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, New Jersey 08901, USA.
Environmental Science and Technology (Impact Factor: 5.48). 08/2005; 39(14):5105-12. DOI: 10.1021/es048226f
Source: PubMed

ABSTRACT Epidemiological studies routinely use central-site particulate matter (PM) as a surrogate for exposure to PM of ambient (outdoor) origin. Below we quantify exposure errors that arise from variations in particle infiltration to aid evaluation of the use of this surrogate, rather than actual exposure, in PM epidemiology. Measurements from 114 homes in three cities from the Relationship of Indoor, Outdoor and Personal Air (RIOPA) study were used. Indoor PM2.5 of outdoor origin was calculated as follows: (1) assuming a constant infiltration factor, as would be the case if central-site PM were a "perfect surrogate" for exposure to outdoor particles; (2) including variations in measured air exchange rates across homes; (3) also incorporating home-to-home variations in particle composition, and (4) calculating sample-specific infiltration factors. The final estimates of PM2.5 of outdoor origin take into account variations in building construction, ventilation practices, and particle properties that result in home-to-home and day-to-day variations in particle infiltration. As assumptions became more realistic (from the first, most constrained model to the fourth, least constrained model), the mean concentration of PM2.5 of outdoor origin increased. Perhaps more importantly, the bandwidth of the distribution increased. These results quantify several ways in which the use of central site PM results in underestimates of the ambient PM2.5 exposure distribution bandwidth. The result is larger uncertainties in relative risk factors for PM2.5 than would occur if epidemiological studies used more accurate exposure measures. In certain situations this can lead to bias.

0 Bookmarks
 · 
102 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Personal exposure studies of air pollution generally use self-reported diaries to capture individuals' time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants' locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies.
    Environmental health : a global access science source. 05/2014; 13(1):33.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: h i g h l i g h t s g r a p h i c a l a b s t r a c t First source apportionment of indoor PM 2.5 conducted at Santiago, Chile. Outdoor and indoor sources each contribute half of the measured in-door PM 2.5 . Traffic and indoor cooking are the strongest sources of indoor PM 2.5 . Indoor concentrations of PM 2.5 were affected by socioeconomic status.: Indoor air quality PM 2.5 Sustainable urban development Household infiltration Source apportionment a b s t r a c t Indoor and outdoor PM 2.5 sampling campaigns were carried out at Santiago, Chile (6 million inhabitants, 33.5 S, 70.6 W) in spring 2012. A pair of samplers was placed inside each household studied and an additional pair of samplers was placed at a fixed outdoor location for measuring trace elements and elemental (EC) and organic carbon (OC) in Teflon and quartz filters, respectively. A total of 47 households in downtown Santiago were included in this study. Mean outdoor and indoor PM 2.5 concentrations were 19.2 and 21.6 mg/m 3 , respectively. Indoor concentrations of PM 2.5 were affected by socioeconomic status (p ¼ 0.048) but no such evidence was found for PM 2.5 species, except lead (p ¼ 0.046). Estimated species infiltration factors were 0. for PM 2.5 , OC, EC and sulfur, respectively. Estimated household infiltration factors had a median of 0.75, mean of 0.78, standard deviation of 0.18 and interquartile range (IQR) 0.67e0.86. For the very first time, Positive Matrix Factorization (PMF3) was applied to an indoor PM 2.5 chemical composition data set measured at Santiago. Source identification was carried out by inspection of key species and by comparison with published source profiles; six sources were identified. Three of them were outdoor contributions: motor vehicles with 5.6 (±0.7) mg/m 3 , street dust with 2.9 (±0.5) mg/m 3 and secondary sulfates with 3.4 (±0.5) mg/m 3 . The indoor sources were: indoor dust with 1.6 (±0.3) mg/m 3 , cleaning and cooking with 2.3 (±0.3) mg/m 3 and cooking and environmental tobacco smoke with 6.1 (±0.7) mg/m 3 . There is potential for further reducing PM 2.5 population exposure in the short term dby improving ventilation of indoor air and controlling indoor sources d and in the long term d with filtration of outdoor air and household improvements to reduce air change rates.
    Atmospheric Environment 05/2014; 80:692. · 3.11 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Polycyclic aromatic hydrocarbons (PAHs) are among the most toxic air pollutants in China. However, because there are unsubstantial data on indoor and outdoor particulate PAHs, efforts in assessing inhalation exposure and cancer risk to PAHs are limited in China. This study measured 12 individual PAHs in indoor and outdoor environments at 36 homes during the non-heating period and heating period in 2009. Indoor PAH concentrations were comparable with outdoor environments in the non-heating period, but were lower in the heating period. The average indoor/outdoor ratios in both sampling periods were lower than 1, while the ratios in the non-heating period were higher than those in the heating period. Correlation analysis and coefficient of divergence also verified the difference between indoor and outdoor PAHs, which could be caused by high ventilation in the non-heating period. To support this conclusion, linear and robust regressions were used to estimate the infiltration factor to compare outdoor PAHs to indoor PAHs. The calculated infiltration factors obtained by the two models were similar in the non-heating period but varied greatly in the heating period, which may have been caused by the influence of ventilation. Potential sources were distinguished using a diagnostic ratio and a mixture of coal combustion and traffic emission, which are major sources of PAHs.This article is protected by copyright. All rights reserved.
    Indoor Air 07/2014; · 3.30 Impact Factor

Full-text (2 Sources)

Download
32 Downloads
Available from
Jun 2, 2014