The sentiment that woodsmoke, being a natural substance, must be benign to humans is still sometimes heard. It is now well established, however, that wood-burning stoves and fireplaces as well as wildland and agricultural fires emit significant quantities of known health-damaging pollutants, including several carcinogenic compounds. Two of the principal gaseous pollutants in woodsmoke, CO and NOx, add to the atmospheric levels of these regulated gases emitted by other combustion sources. Health impacts of exposures to these gases and some of the other woodsmoke constituents (e.g., benzene) are well characterized in thousands of publications. As these gases are indistinguishable no matter where they come from, there is no urgent need to examine their particular health implications in woodsmoke. With this as the backdrop, this review approaches the issue of why woodsmoke may be a special case requiring separate health evaluation through two questions. The first question we address is whether woodsmoke should be regulated and/or managed separately, even though some of its separate constituents are already regulated in many jurisdictions. The second question we address is whether woodsmoke particles pose different levels of risk than other ambient particles of similar size. To address these two key questions, we examine several topics: the chemical and physical nature of woodsmoke; the exposures and epidemiology of smoke from wildland fires and agricultural burning, and related controlled human laboratory exposures to biomass smoke; the epidemiology of outdoor and indoor woodsmoke exposures from residential woodburning in developed countries; and the toxicology of woodsmoke, based on animal exposures and laboratory tests. In addition, a short summary of the exposures and health effects of biomass smoke in developing countries is provided as an additional line of evidence. In the concluding section, we return to the two key issues above to summarize (1) what is currently known about the health effects of inhaled woodsmoke at exposure levels experienced in developed countries, and (2) whether there exists sufficient reason to believe that woodsmoke particles are sufficiently different to warrant separate treatment from other regulated particles. In addition, we provide recommendations for additional woodsmoke research.

Recent studies have associated short-term exposure to respirable particulate matter (PM10) exposure with peak flow decrements, increased symptoms of respiratory irritation, increased use of asthma medications, and increased hospitalization for asthma. Increased mortality from chronic respiratory disease has also been reported. To help confirm whether PM10 exposure is a risk factor for the exacerbation of asthma, we compiled daily records of asthma emergency room visits from eight hospitals in the Seattle area. In Poisson regressions controlling for weather, season, time trends, age, hospital, and day of the week, the daily counts of emergency room visits for persons under age 65 were significantly associated with PM10 exposure on the previous day. The mean of the previous 4 days' PM10 was a better predictor (p < 0.005). The relative risk for a 30 micrograms/m3 increase in PM10 was 1.12 (95% confidence interval 1.20 to 1.04). Daily PM10 concentrations never exceeded 70% of the current ambient air quality standards during the period. The consistency of investigations of the health effects of PM10 suggest that increased attention should be given to the control of particulate matter air pollution.

Investigators in the Inner-City Asthma Study are listed in the Appendix. We thank the participants for making their homes available to us for 2-week periods. We also thank our excellent staff for performing the many tasks involved in a multiyear, multicity field study.

We measured fractional exhaled nitric oxide (FENO), spirometry, blood pressure, oxygen saturation of the blood (SaO2), and pulse rate in 16 older subjects with asthma or chronic obstructive pulmonary disease (COPD) in Seattle, Washington. Data were collected daily for 12 days. We simultaneously collected PM10 and PM2.5 (particulate matter ≤10 μm or ≤2.5 μm, respectively) filter samples at a central outdoor site, as well as outside and inside the subjects’ homes. Personal PM10 filter samples were also collected. All filters were analyzed for mass and light absorbance. We analyzed within-subject associations between health outcomes and air pollution metrics using a linear mixed-effects model with random intercept, controlling for age, ambient relative humidity, and ambient temperature. For the 7 subjects with asthma, a 10 μg/m3 increase in 24-hr average outdoor PM10 and PM2.5 was associated with a 5.9 [95% confidence interval (CI), 2.9–8.9] and 4.2 ppb (95% CI, 1.3–7.1) increase in FENO, respectively. A 1 μg/m3 increase in outdoor, indoor, and personal black carbon (BC) was associated with increases in FENO of 2.3 ppb (95% CI, 1.1–3.6), 4.0 ppb (95% CI, 2.0–5.9), and 1.2 ppb (95% CI, 0.2–2.2), respectively. No significant association was found between PM or BC measures and changes in spirometry, blood pressure, pulse rate, or SaO2 in these subjects. Results from this study indicate that FENO may be a more sensitive marker of PM exposure than traditional health outcomes and that particle-associated BC is useful for examining associations between primary combustion constituents of PM and health outcomes.

Most particulate matter (PM) health effects studies use outdoor (ambient) PM as a surrogate for personal exposure. However, people spend most of their time indoors exposed to a combination of indoor-generated particles and ambient particles that have infiltrated. Thus, it is important to investigate the differential health effects of indoor- and ambient-generated particles. We combined our recently adapted recursive model and a predictive model for estimating infiltration efficiency to separate personal exposure (E) to PM2.5 (PM with aerodynamic diameter ≤2.5 μm) into its indoor-generated (Eig) and ambient-generated (Eag) components for 19 children with asthma. We then compared Eig and Eag to changes in exhaled nitric oxide (eNO), a marker of airway inflammation. Based on the recursive model with a sample size of eight children, Eag was marginally associated with increases in eNO [5.6 ppb per 10-μg/m3 increase in PM2.5; 95% confidence interval (CI), −0.6 to 11.9; p = 0.08]. Eig was not associated with eNO (−0.19 ppb change per 10μg/m3). Our predictive model allowed us to estimate Eag and Eig for all 19 children. For those combined estimates, only Eag was significantly associated with an increase in eNO (Eag: 5.0 ppb per 10-μg/m3 increase in PM2.5; 95% CI, 0.3 to 9.7; p = 0.04; Eig: 3.3 ppb per 10-μg/m3 increase in PM2.5; 95% CI, −1.1 to 7.7; p = 0.15). Effects were seen only in children who were not using corticosteroid therapy. We conclude that the ambient-generated component of PM2.5 exposure is consistently associated with increases in eNO and the indoor-generated component is less strongly associated with eNO.