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2004 Progress Report: Personal PM Exposure Assessment
EPA Grant Number: R827355C003Subproject: this is subproject number 003 , established and managed by the Center Director under grant R827355
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Airborne PM - Northwest Research Center for Particulate Air Pollution and Health
Center Director: Koenig, Jane Q.
Title: Personal PM Exposure Assessment
Investigators: Liu, Sally , Allen, Ryan , Claiborn, Candis , Compher, Michael , Gould, Timothy , Hallstrand, Teal , Kalman, Dave , Koenig, Jane Q. , Larson, Timothy V. , Simpson, Chris
Current Investigators: Liu, Sally , Allen, Ryan , Claiborn, Candis , Kalman, Dave , Koenig, Jane Q. , Larson, Timothy V. , Simpson, Chris
Institution: University of Washington
EPA Project Officer: Stacey Katz/Gail Robarge,
Project Period: June 1, 1999 through May 31, 2004 (Extended to May 31, 2006)
Project Period Covered by this Report: June 1, 2004 through May 31, 2005
Project Amount: Refer to main center abstract for funding details.
RFA: Airborne Particulate Matter (PM) Centers (1999)
Research Category: Particulate Matter
Description:
Objective:The objectives of this research project are to: (1) characterize the key factors influencing this relationship and develop models for predicting personal particulate matter (PM) exposures; and (2) provide exposure models for the concurrent epidemiologic study to reach an unbiased estimation of health effects.
Progress Summary:Sensitivity Analysis of the Recursive Model Approach for Estimating Residential Particle Infiltration Efficiencies From Light Scattering Data
This project involved the following tasks: (1) characterize and compare personal, indoor, and outdoor exposures to various components of PM10 and PM2.5 among three major susceptible subpopulations and one control healthy cohort; (2) determine the strength of the relationship of the particle exposures of the high-risk subpopulations to the concentrations measured by a central monitoring station; (3) characterize the key factors influencing this relationship and develop models for predicting personal PM exposures; (4) provide exposure models for the concurrent epidemiologic study to reach unbiased estimation of health effects; and (5) update the study design and analysis goals based on the new findings and new hypotheses.
Exposure Modeling
In our previous work, we described the application of a recursive form of the mass balance equation to hourly indoor and outdoor light scattering data to estimate fine particle infiltration efficiency (Finf), penetration efficiency (P), and deposition rate (k), as well as the air exchange rate (a), in individual residences. Because of space constraints and data limitations, we were unable to conduct a thorough sensitivity analysis of the recursive model technique. Thus, the two purposes of this analysis were to evaluate the reliability of the parameter estimates and to determine an approach to solving the RM that produced the most accurate estimates of Finf when using sulfur as a tracer of outdoor particles. The solution surfaces for P, a, and k were extremely flat, indicating large uncertainties in the point estimates, and the estimates were highly dependent on the goodness-of-fit criterion. In contrast, the solution surfaces for Finf showed much steeper gradients, and the estimates were not sensitive to different goodness-of-fit criteria, consistent with our previous results indicating that the estimates of Finf for individual residences are robust. Based on comparisons with the sulfur tracer technique, the RM provides a considerable improvement over the simple indoor-outdoor ratio approach for estimating Finf. Although the accuracy of the Finf estimates was fairly insensitive to the censoring approach and the presence or absence of an intercept term in the regression, the most accurate Finf estimates were obtained by censoring only the rising edge of indoor source peaks and solving the RM using an intercept term. Two likely causes of positive intercepts after censoring indoor sources are temporary changes in the light scattering efficiency of the indoor aerosol and a loss of semivolatile particle species caused by heating the inlet of the outdoor nephelometer. We conclude that the RM approach applied to light-scattering data provides accurate estimates of Finf in individual residences and represents a valid alternative to the more commonly used tracer technique.
Exposure and Health Assessments of the Effects of Agricultural Field Burning in Young Adults With Asthma Living in Pullman, Washington
Agricultural (Ag) burning is a cost-effective method of cleaning and preparing the field for the succeeding growth season. Smoke from Ag burning, however, may contain various air pollutants, which may cause or exacerbate respiratory disease. The short-duration excursions of Ag-burning smoke often do not violate the National Ambient Air Quality Standards, however, at locations where air quality monitors are situated. Although a limited number of studies documented potential health effects from Ag-burning smoke, there is a paucity of literature characterizing community residents’ exposure to Ag-burning smoke and the associated health effects.
In the past several years, Ag burning has been subject to intense public health debate and in several cases law suits were filed in eastern Washington and Idaho. This study, aimed to assess the short-term exposure and health effects of Ag burning.
The study was conducted in Pullman, Washington, during the fall of 2002 prescribed agricultural field burning season. The study consisted of 32 young adults with asthma (aged 18-52, median 24) and 2 randomly assigned monitoring sessions for each subject, including an active session and an on-call session. The active session required 16 participants to perform in-lab measures of on-line exhaled nitric oxide (eNO) (Sievers, Boulder CO), coached spirometry (microDL) and complete symptom questionnaires at the same time of day every Monday, Wednesday, and Friday during a 30-day period. The on-call session, occurred during the remaining 30-days of the 60-day monitoring session. During a declared episode, the on-call subjects would have all health measures performed with the active subjects over the 3 successive days from the initial called episode. During our study, there were one sham episode and four real episodes, defined as more than 3 consecutive 30-minute PM2.5 averages exceeding 40 µg/m3.
Air quality measurements at the central site included continuous PM2.5, PM10, carbon dioxide, nitrogen oxides, and meteorological conditions and 12-hour integrated PM2.5, elemental and organic carbon (EC/OC), and levoglucosan (LG), a marker for biomass combustion. The personal exposure measurements were collected from 16 subjects, inside of 12 residences, and outside of 6 residences. Exposure estimates included personal exposure measurements of PM2.5, EC/OC, LG, calculated exposure to PM2.5 of outdoor origin, and calculated exposure to PM2.5 from Ag burning.
Three manuscripts will report the results of this research. The first manuscript characterizes the air quality during Ag burning episode and nonepisode periods. Two source apportionment methods, including the Chemical Mass Balance (CMB-8) model and the Positive Matrix Factorization (PMF), were utilized to apportion the measured PM2.5 mass concentrations to major sources found in eastern Washington. The second manuscript investigates personal exposure to PM and utilizes the CMB-8 results in Chapter 1 to estimate personal exposure to PM originating from ambient sources and Ag-burning activities. The third manuscript utilizes air quality measurements and exposure estimates to assess acute health effects from exposure to PM2.5 originated from Ag-burning smoke.
During the study period, the observed 1-hour average PM2.5 concentrations ranged between 0.3 and 59.6 μg/m3, averaging 13.0±9.2 μg/m3. Major contributions of PM2.5 included soil (38%), vegetative burning (35%), and sulfate aerosol (20%) based on the CMB-8 analysis. The PMF-generated profiles were consistent with those selected for CMB-8 modeling. In addition, the PM2.5 mass concentration estimates from the two models were significantly correlated for individual sources. LG, PM2.5 from biomass combustion, and soil PM2.5 mass concentrations (both derived from receptor modeling) were significantly higher during the episodes than during non-episode days, whereas other measurements, including NOx, carbon dioxide (CO2), OC, and EC were relatively similar on episode and nonepisode days. Although we successfully identified Ag burning episodes with a higher contribution of PM2.5 from vegetative burning, an equal or higher contribution from airborne soil dust to the real-time PM2.5 measurements could not be ignored.
The observed mean personal exposure to PM2.5 was 13.8±11.1 µg/m3, which was on average 8.0 µg/m3 higher during the Ag burning episodes (19.0±11.8 µg/m3) than nonepisodes (11.0±9.7 µg/m3). The personal LG exposure also was higher during the episode than nonepisode periods. The ambient contribution fraction, which propagates central site measurements to personal exposure, ranged between 0.28 and 2.21. The correlation between the central-site and personal LG was 0.75. We combined the CMB-8 and total exposure modeling results in a model to predict PM2.5 exposure that originated from Ag burning for individual subjects (Eab). The estimated Eab ranged from 2.0 to 7.1 µg/m3 (mean=3.5±1.3 µg/m3) and correlated with personal LG measurements (r= 0.53). Uncertainties in the Eab estimates were caused in part by the dependence on the ambient contribution fraction for total PM2.5 as a surrogate for biomass burning related PM mass. We found significant between-subject variation between episodes and nonepisodes in both the Eab estimates and subjects’ activity patterns. This suggests that the LG measurements at the central sites may not be representative of individual exposure to Ag burning smoke.
We hypothesized that adults with mild-moderate asthma who are not using anti-inflammatory medication would show a positive association of eNO and negative association of FEV1 and maximal mid-expiratory flow (MMEF) with the peak 1-hour average of PM2.5 during the previous 24 hours. We further refined our health assessment by using individual specific exposure estimates originating from Ag burning. Health measures included 594 on-line eNO and 591 coached spirometry tests. These health effects were assessed with a GEE model that included fixed covariates for gender, age, body mass index (BMI), exposure estimates, an interaction term between medication use and exposure, and adjusted for temperature and relative humidity. There was no significant effect of peak 1-hour PM2.5 on measures of eNO among those not prescribed anti-inflammatory medications: -0.35 ppb (95% CI: -1.70, 1.01) per 10 μg/m3 increase in PM2.5 or those prescribed controller medications: 1.68 ppb (95% CI: -1.51, 4.87) per 10 μg/m3 increase of PM2.5. Similar null effects of peak PM2.5 exposure were noted for spirometric measures of MMEF and FEV1. Sensitivity analyses that assessed Ag burning related exposure using LG, indoor concentration of Ag burn-related PM, or estimated exposure to ambient or Ag burning originated PM did not change our null results.
Our study had several strengths that added to the validity of the results. These included repeated in-lab measures of subclinical effects (eNO and spirometry), inclusion of a sham Ag burn episode to control for nonagricultural PM-related changes in pulmonary measures and symptoms measures, detailed exposure measures that included residential indoor and personal measures in a community where agricultural burning represented a relatively high fraction of total PM2.5. Although the frequency and peak levels of Ag burn related PM2.5 were low, they were representative of the recent Ag burning-related PM. Since the 1999 Memorandum of Understanding between the wheat growers and the Washington Department of Ecology, and the subsequent implementation of Ag burn control strategies by Ecology, acreage burned and Ag-related PM emission have been decreasing. The low and infrequent exposures were observed in the present 2002 Ag burn study as well as in the previous 2 years (2000 and 2001).
Although the null results may be true, the following factors could have contributed to the absence of effect in our study: the selection of a relatively nonsusceptible study population, nonlinear effects of agricultural field burn PM on eNO and spirometric measures, timing of our health assessments, inability to accurately capture the spatial and temporal variation of PM, inability to accurately measure agricultural combustion contributions to the PM mass, and an equal or greater contribution to peak PM2.5 from airborne dust during the Ag-burning episodes.
In conclusion, the observed PM2.5 levels and excursions were typical of those of previous years. Although we did not find an association between peak PM2.5 from field burning and decrements in pulmonary function or increases in eNO in young adults with asthma, we cannot rule-out health effects from field burning in more susceptible populations or at higher PM concentrations. We recommend future studies that measure subclinical effects on children with asthma, older individuals with cardiac disease, or farm workers exposed to potentially greater agricultural PM concentrations.
Children’s Exposure to Diesel Exhaust While Riding School Buses With Different Diesel Engines
Objectives. The objective of this pilot study was to test the feasibility of monitoring PM during school bus trips, recruiting children with asthma to participate in such a study, and to examine the feasibility of measuring lung function and exhaled breath in the field in these children.
In this pilot study, we assessed the exposures of nine asthmatic and nonasthmatic children in Seattle while they rode to and from school in a variety of makes and models of diesel school buses, including two retrofitted with an oxidative catalyst to reduce emissions. Using validated portable instruments, on-bus exposures to fine and ultrafine particles, elemental carbon and organic carbon, sulfur dioxide (SO2), and nitrogen dioxide (NO2) were quantified during subjects’ commutes. We also measured personal exposure including real-time PM2.5 and integrated concentrations of SO2, NO2, and PM2.5, on each subject. We performed health measures immediately after the morning commute and before the afternoon ride to explore respiratory health effects including lung function, eNO, and oxidative stress makers in exhaled breath condensate (eBC). The commute to and from school on the bus may be the most substantial source of PM2.5 exposure that children regularly encounter during their daily activities. In-vehicle exposure to PM2.5 averaged 60 μg/m3 and was seven times higher than the concurrent ambient levels. Ultrafine particle counts on the buses averaged 67,727 particle counts/cm3, 2-fold greater than the concentrations of ultrafine particle measured at 60 μg/m3 PM2.5 in controlled chamber tests during equipment validation. For nonasthmatic children (n=4) and the asthmatic child not on medication, the eNO and hydrogen peroxide (H2O2) in eBC showed positive correlations with exposure to ultrafine particle counts during the morning commute. Nonasthmatic children (n=5) also showed significant decrements in FEV1 related to ultrafine PM during the morning commute. Our pilot study results suggest that health effects of PM and diesel exhaust are related to the magnitude of acute exposures, with nonasthmatic children being more responsive to diesel exhaust exposure than asthmatic children on anti-inflammatory medicine.
Future Activities:Exposure Assessment and the Exposure Core have published several papers examining sources of indoor, outdoor, and personal PM2.5. One of our papers estimated real-time contributions of personal PM2.5 exposure from ambient and nonambient sources. Year 6 work will perform sensitivity analyses of the modeling approach and assumptions that generated these estimates. We recently discovered that additional XRF elemental analyses are necessary to provide an adequate sample size for our sensitivity analysis. We initiated the additional XRF analyses and received the results in late January 2005. We are working on incorporating these results into our sensitivity analyses. Because of the availability of these data, we plan to use the 1-year no-cost extension period to conduct quality control and prepare manuscripts to address all problems.
In March 2005, we conducted additional NOx monitoring to examine spatial and traffic effects on air pollution levels related to PM2.5 in North Seattle. These traffic-related monitoring data will enhance our current spatial analysis on NO2/SO2 and the comparisons of on-bus and in-traffic analysis. A 1-year no-cost extension is necessary to incorporate the latest monitoring data in the analyses and to publish the adjusted model.
Journal Articles on this Report: 6 Displayed | Download in RIS Format
| Other subproject views: | All 65 publications | 25 publications in selected types | All 25 journal articles |
| Other center views: | All 191 publications | 97 publications in selected types | All 94 journal articles |
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Allen R, Wallace L, Larson T, Sheppard L, Liu L-JS. Estimated hourly personal exposures to ambient and nonambient particulate matter among sensitive populations in Seattle, Washington. Journal of the Air & Waste Management Association 2004;54(9):1197-1211. |
R827355 (2004) R827355 (Final) R827355C003 (2003) R827355C003 (2004) R827355C003 (Final) R827355C008 (Final) R827355C009 (Final) |
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Delfino RJ, Quintana PJE, Floro J, Gastañaga VM, Samimi BS, Kleinman MT, Liu L-JS, Bufalino C, Wu C-F, McLaren CE. Association of FEV1 in asthmatic children with personal and microenvironmental exposure to airborne particulate matter. Environmental Health Perspectives 2004;112(8):932-941. |
R827355 (2004) R827355 (Final) R827355C003 (2003) R827355C003 (2004) R827355C003 (Final) |
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Jimenez J, Wu C-F, Claiborn C, Gould T, Simpson CD, Larson T, Liu L-JS. Agricultural burning smoke in eastern Washington—Part I: Atmospheric characterization. Atmospheric Environment 2006;40(4):639-650. |
R827355 (Final) R827355C003 (2004) R827355C003 (Final) R827355C010 (Final) |
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Koenig JQ, Mar TF, Allen RW, Jansen K, Lumley T, Sullivan JH, Trenga CA, Larson TV, Liu L-JS. Pulmonary effects of indoor-and outdoor-generated particles in children with asthma. Environmental Health Perspectives 2005;113(4):499-503. |
R827355 (2004) R827355 (Final) R827355C002 (2003) R827355C002 (2004) R827355C002 (Final) R827355C003 (2004) R827355C003 (Final) R827355C009 (Final) |
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Simpson CD, Paulsen M, Dills RL, Liu L-JS, Kalman DA. Determination of methoxyphenols in ambient atmospheric particulate matter: tracers for wood combustion. Environmental Science & Technology 2005;39(2):631-637. |
R827355 (2004) R827355 (Final) R827355C003 (2004) R827355C003 (Final) R827355C010 (2003) R827355C010 (Final) R829584 (2004) |
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Wu C-F, Delfino RJ, Floro JN, Quintana PJ, Samimi BS, Kleinman MT, Allen RW, Liu L-JS. Exposure assessment and modeling of particulate matter for asthmatic children using personal nephelometers. Atmospheric Environment 2005;39(19):3457-3469. |
R827355 (Final) R827355C003 (2004) R827355C003 (Final) |
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ambient particles, fine particles, combustion, health, exposure, biostatistics, susceptibility, human susceptibility, sensitive populations, air toxics, genetic susceptibility, indoor air, indoor air quality, indoor environment, tropospheric ozone, California, CA, polyaromatic hydrocarbons, PAHs, hydrocarbons, acute cardiovascular effects, aerosols, air pollutants, air pollution, air quality, airborne pollutants, airway disease, airway inflammation, allergen, ambient aerosol, ambient aerosol particles, ambient air, ambient air quality, ambient particle health effects, animal model, assessment of exposure, asthma, atmospheric aerosols, atmospheric chemistry, biological markers, biological response, cardiopulmonary response, cardiovascular disease, children, children’s vulnerability, combustion, combustion contaminants, combustion emissions, epidemiology, exposure, exposure and effects, exposure assessment, harmful environmental agents, hazardous air pollutants, health effects, health risks, human exposure, human health effects, human health risk, incineration, inhalation, lead, morbidity, mortality, mortality studies, particle exposure, particle transport, particulates, particulate matter, PM, risk assessment,
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Air, Geographic Area, Scientific Discipline, Health, RFA, Susceptibility/Sensitive Population/Genetic Susceptibility, indoor air, Risk Assessments, genetic susceptability, Northwest, Health Risk Assessment, Epidemiology, air toxics, Atmospheric Sciences, Biochemistry, particulate matter, Environmental Chemistry, State, aerosols, exposure assessment, incineration, California (CA), PAHs, exposure and effects, ambient air quality, cardiovascular disease, health effects, hydrocarbons, indoor air quality, inhalation, mortality, allergens, air quality, ambient air, cardiopulmonary response, fine particles, hazardous air pollutants, atmospheric aerosols, cardiopulmonary responses, human health risk, particle exposure, mortality studies, air pollutants, biostatistics, human health effects, particulates, PM 2.5, sensitive populations, toxicology, ambient particle health effects, air pollution, atmospheric chemistry, children, PM10, stratospheric ozone, Seattle, Washington, exposure, human susceptibility, ambient aerosol, asthma, health risks, human exposure, Human Health Risk Assessment, morbidity, animal model, particle transport
Relevant Websites:
http://depts.washington.edu/pmcenter/
Progress and Final Reports:
1999 Progress Report
2000 Progress Report
2001 Progress Report
2002 Progress Report
2003 Progress Report
Original Abstract
Final Report
Main Center Abstract and Reports:
R827355 Airborne PM - Northwest Research Center for Particulate Air Pollution and Health
Subprojects under this Center:
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827355C001 Epidemiologic Study of Particulate Matter and Cardiopulmonary
Mortality
R827355C002 Health Effects
R827355C003 Personal PM Exposure Assessment
R827355C004 Characterization of Fine Particulate Matter
R827355C005 Mechanisms of Toxicity of Particulate Matter Using Transgenic Mouse Strains
R827355C006 Toxicology Project -- Controlled Exposure Facility
R827355C007 Health Effects Research Core
R827355C008 Exposure Core
R827355C009 Statistics and Data Core
R827355C010 Biomarker Core
R827355C011 Oxidation Stress Makers