Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Aug 20.
Published in final edited form as: J Occup Environ Hyg. 2017 Sep;14(9):739–748. doi: 10.1080/15459624.2017.1326700

Lung function measures following simulated wildland firefighter exposures

Matthew D Ferguson 1, Erin O Semmens 1, Emily Weiler 1, Joe Domitrovich 2, Mary French 1, Christopher Migliaccio 1, Charles Palmer 3, Charles Dumke 3, Tony Ward 1,*
PMCID: PMC6101969  NIHMSID: NIHMS1501997  PMID: 28609218

Abstract

Across the world, biomass smoke is a major source of air pollution and is linked with a variety of adverse health effects. This is particularly true in the western US where wood smoke from wildland forest fires are a significant source of PM2.5. Wildland firefighters are impacted as they experience elevated PM2.5 concentrations over extended periods of time, often occurring during physical exertion. Various epidemiological studies have investigated wood smoke impacts on human health, including occupational field exposures experienced by wildland firefighters. As there are numerous challenges in carrying out these field studies, having the ability to research the potential health impacts to this occupational cohort in a controlled setting would provide important information that could be translated to the field setting.

To this end, we have carried out a simulated wildland firefighter exposure study in a wood smoke inhalation facility. Utilizing a randomized crossover trial design, we exposed 10 participants once to clean filtered-air, 250 μg/m3, and 500 μg/m3 wood stove-generated wood smoke PM2.5. Participants exercised on a treadmill at an absolute intensity designed to simulate wildland firefighting for 1.5 hours. In addition to measured PM2.5 smoke concentrations, mean levels of CO2, CO, and % relative humidity were continuously monitored and recorded and were representative of occupational ‘real-world’ exposures. Pulmonary function was measured at three time points: before, immediately after, and 1-hour post-exposure. Although there were some reductions in FVC, FEV1, and FVC:FEV1 measures, results of the spirometry testing did not show significant changes in lung function. The development of this wood smoke inhalational facility provides a platform to further address unique research questions related to wood smoke exposures and associated adverse health effects.

Keywords: wood, smoke, wildland, firefighting, inhalation, spirometry

INTRODUCTION

Air pollution has a major impact on human health throughout the world, and is a leading cause of premature mortality (13). Both globally and throughout the US, urban areas with large populations often have elevated levels of air pollution, including airborne particulate matter (PM). This is also true for rural areas of the northern Rocky Mountain region of the US, where biomass burning (e.g., wildland fires, wood stoves, etc.) is a major source of elevated ambient and indoor PM2.5 concentrations throughout the year (416).

Globally, smoke from wildland fires partly attribute to around 339,000 deaths a year (17). Tens of thousands of wildland fires burn between 3 million and 10 million acres of land depending on year in the US alone. These fires are predicted to continue or worsen in many regions throughout the world (18). During these wildland fire events, emissions of wood smoke PM2.5 can impact ambient air quality in communities thousands of kilometers downwind (20). It can also infiltrate homes resulting in indoor PM concentrations similar to levels observed outside (2124).

With predicted increases in forest fires (18), the number of wildland firefighter crews deployed to fight these fires will also increase. These crews have been shown to experience smoke PM levels up to 2,930 μg/m3 with average levels of exposure during wildland firefighting activities ranging from 509–558 μg/m3, and average CO levels of exposure ranging from 1.3–1.7 ppm (25). When working on project fires or prescribed burns, firefighters can experience average concentrations ranging from 500–630 μg/m3 throughout an entire work shift (26). Related health studies conducted in the field have found an overall general decrease in lung function following wildland firefighting activities (2729).

Given the many sources of biomass smoke exposures leading to a variety of exposure scenarios, there is a need to study the health effects following similar smoke exposures in a controlled environment. Wildland firefighter exposures are unique due to sustained and elevated PM2.5 wood smoke concentrations while also enduring considerable physical exertion. The objective of this study was to deliver wood smoke PM2.5 (generated in wood stove) in a controlled facility to 10 human participants and determine respiratory impacts under simulated conditions typically experienced (i.e., physical and atmospheric) by wildland firefighters. Below we describe the design and methods utilized in carrying out the exposure trials and present exposure and lung function results.

METHODS

The Inhalation and Pulmonary Physiology Core within the Center for Environmental Health Sciences at the University of Montana was originally developed to conduct wood smoke exposure trials using mice, but was modified in this application to conduct human exposure trials. The study described herein is a 10-participant pilot project simulating occupational wood smoke exposures encountered by wildland firefighters. Following recruitment into the study and initial entry level measurements (Day 1), 10 individuals participated in three experimental trials, each one occurring one week apart (i.e., Day 2, Day 3, and Day 4). Each participant was blinded to his exposure assignment and was exposed, while exercising, once to either clean filtered-air (0 μg/m3), 250 μg/m3, or 500 μg/m3 wood smoke PM2.5, in random order for 1.5 hours. Throughout each exposure, PM2.5, CO, CO2, and % relative humidity levels were continuously monitored and recorded. Spirometry measures were collected prior to, immediately after, and 1-hour post each exposure.

Inhalation Facility and Exposure Levels

Wood smoke for these exposure trials was generated using an older-model wood stove (Englander, England Stove Works, Inc., Monroe, VA) and routed through dilution chambers before ultimate delivery to the participant through a breathing mask. The wood used in this study was cured (~15% moisture content) western larch (Larix occidentalis Nutt.), which is a common species in western Montana. The technique for building and maintaining the fire was uniform throughout each exposure. Prior to each exposure trial, some remaining ash from previous burns was removed for a consistent starting ash depth (~0.5–1” deep). Each fire started with about 1 kg of wood as well as kindling (1–2 pages of newspaper). About 300 g of wood was then added every 15–20 minutes over a two-hour period, with each fire started 25–30 minutes prior to each exposure trial.

During each exposure trial, smoke pulled from the wood stove chimney was routed through dilution chambers where filtered air (Cambridge Absolute Filter, Cambridge Filter Corp., Syracuse NY) was introduced in an effort to dilute the smoke (FIGURE 1). Wood smoke was then delivered from the dilution and mixing chambers to the participant via a modified mask respirator (Hans Rudolph, Inc., Shawnee, Kansas). The major pump pulling air from the wood stove chimney and through the dilution chambers was placed in line between the chambers and the mask. This allowed air to be ‘pushed’ through the mask at rates (~90–100 L/min) appropriate for an individual to comfortably breath while exercising on a treadmill.

FIGURE 1.

FIGURE 1.

A simplified schematic showing the path of wood smoke through the inhalation system

En route to the mask and following the pump, wood smoke PM first passed through 2.5 feet of flex tubing before coming to a T-valve that directed the wood smoke PM to both the mask and to a fume hood where excess wood smoke PM was exhausted. Tubing to the mask included 108” of Clean-Bor tubing (VacuMed, Ventura, CA) made of ethylene vinyl acetate. The mask utilized was a Rudolph Nasal & Mouth Breathing Face Mask with a two-way non-rebreathing T-valve. Another hose exited the mask and was directed to the fume hood for exhaust.

The exposure room (11’10” × 5’10” × 8’) contained a treadmill (Model Q65, Quinton Instrument Company, Bothell, WA) attached to a control station (Model Q4000, Quinton Instrument Company, Bothell, WA), and other items intended for participant comfort. This included a fan to improve air circulation in the room. A stand within arm’s reach and at eye level was also placed in front of the treadmill providing a platform for the participant to set a magazine, book, tablet, or phone. If desired, participants were also allowed to listen to music throughout their exposure trial. For comfort, the mask and tubes were suspended from the ceiling by adjustable straps. This allowed the mask to be placed at an appropriate height, reducing the burden of mask and tubing weight on the participant’s head and face, and allowed the mask to move and shift with the participant while they were exercising on the treadmill.

Two PM2.5 monitors (DustTrak, TSI, Model 8530 and Model 8534, Shoreview, MN) were used during the exposures to measure continuous readings of real-time and average PM2.5 concentrations directly routed to the mask (see Figure 1). The first DustTrak (Model 8534) was used to adjust wood smoke PM2.5 concentrations delivered through the dilution chambers. The second DustTrak (Model 8530) measured continuous PM2.5 concentrations delivered to the mask just prior to inhalation. All PM2.5 concentrations reported in this manuscript were obtained from this second DustTrak. Carbon monoxide (CO), carbon dioxide (CO2), and % relative humidity at the mask were also monitored with a Q-Trak (TSI, Model 7565, Shoreview, MN) and collocated to the second DustTrak. This CO measurement was especially important to ensure low levels of CO during each exposure trial.

Inclusion Criteria and Recruitment

This study included 10 healthy, non-smoking males, aged 18–40 years, with no pre-existing chronic lung diseases. Participants did not have wood smoke exposures at home or work (via cigarettes or wood stoves), and had to complete a moderate physical exercise protocol three times during the study. Due to the small size of this pilot study, and to remove the potentially confounding impact of gender on findings, only males were included. Additional inclusion criteria described in more detail below under ‘Day 1’ included answering ‘No’ to all questions on a Physical Activity Readiness Questionnaire (PARQ), as well as having a VO2 max > 40 ml/kg/min.

Following study approval from the University of Montana’s Institutional Review Board, participants were recruited from the University of Montana student, faculty, and staff population. Flyers were posted throughout the campus. Upon the initial meeting with participants, enrolled volunteers were administered oral and written informed consent, and then scheduled for Day 1 measures. Participants received a stipend upon completion of each of the three exposure trials (Days 2–4, respectively).

Day 1

Day 1 of the study was used to determine eligibility for the Days 2–4 exposure trials, with inclusion/exclusion criteria intended to reduce the risk of adverse response occurrences throughout each exposure. Participants were reminded to fast for three hours before presenting. They were then asked to complete a personal information questionnaire and PARQ, and undergo a test to verify their maximum level of oxygen uptake (VO2 max) was greater than 40 ml/kg/min. The percentage of body fat for each participant was also determined via an underwater weighing test. Personal information collected included age, height, weight, percentage of body fat, VO2 max, and illnesses and medications taken during the study period. If participants met all the inclusion criteria, scheduling was initiated for Days 2, 3, and 4. The entire process for Day 1 took approximately 1.25 hours/participant.

Day 2–4 Exposure Trials

Following the Day 1 evaluations, participants participated in three exposure trials, each one occurring one-week apart (i.e., Day 2, Day 3, and Day 4). During the study, each participant was exposed once to either clean filtered air, 250 μg/m3, or 500 μg/m3 wood smoke PM2.5 in a double-blind randomized crossover design. During smoke exposure, participants were asked to walk on a treadmill at a set rate and incline (3.5 mph and 5.7% grade) for 1.5 hours to simulate working on a fireline, with a short (e.g., 20–30 seconds) break every 15 minutes to evaluate perceived stress and drink a predetermined amount of water. A researcher was constantly monitoring both the CO and PM2.5 concentrations to the mask and signs of participant discomfort at all times during the exposure trials. Each of the three experimental trials took approximately 3 hours.

Pulmonary Function

Spirometry is the most widely used assessment of pulmonary function for diagnosis and prognosis of pulmonary status and disease, including chronic obstructive pulmonary disease (COPD) and other restrictive diseases (3033). Evaluated spirometry measures used in this study include the volume of exhaled breath during the first second of forced expiratory air following maximum inhalation (FEV1), the vital capacity (FVC; the maximum volume of air forced out of the lungs following maximum inhalation), and the ratio FEV1/FVC (also known as the Tiffeneau-Pinelli index). For each of the three trials, spirometry measurements were collected from the participants before, immediately post-exposure, and 1-hour after each exposure. Each assessment was conducted by having the participant blow air rapidly and forcefully into the mouthpiece of a Koko Legend Spirometer (Ferraris Respiratory, Louisville, CO). To ensure accurate and reliable results during the pulmonary function test, a strict protocol was followed that included both specific participant instructions as well as quality control measures (34).

Quality Assurance / Quality Control

The DustTrak was zero calibrated prior to each exposure trial. The tubes connecting the flex tubing to the mask were replaced following each exposure trial, and the mask was thoroughly cleansed after each exposure. This was done by disassembling the mask, with each part thoroughly washed in warm water with mild detergent. This ensured that participants were equipped with a clean mask at the start of each exposure. The building of each fire was consistent using standardized procedures (e.g., starting mass, stoking mass, etc.). To further reduce source variability, the same people conducted the fire loading and stoking throughout the entire study.

Data Analysis

Each participant was randomly assigned an identification number at the start of the study, with all samples, questionnaire responses, physiological measurements, and other data collection forms labeled with this number. We define exposure as 1) filtered-air, 2) 250 μg/m3 wood smoke PM2.5, or 3) 500 μg/m3 wood smoke PM2.5. Due to skewness in the distributions, the presence of outliers, and the small sample size for pulmonary function measures in this pilot project, we utilized the Skillings-Mack test, a nonparametric analog to a repeated measures ANOVA that allows for unbalanced data, to evaluate if observed pre- to post-exposure changes in lung function differed significantly by wood smoke exposure condition. Comparisons were also made using Dunnett’s test. These tests were performed using Excel and Prism (GraphPad, v.5.0a).

RESULTS

Environmental conditions and spirometry results are reported below. Also, due to fatigue in one participant and another participant dropping out before their final exposure, two individuals did not complete all spirometry measures.

Day 1 Measures

The participants had an average age of 26.4 (± 3.7). Average height (in inches) of all participants was 70.13 (± 3.1). The body weight (kg) and percent body fat outcomes were 79.03 (± 12.2) and 14.16 (± 2.6), respectively. All participants showed acceptable VO2 max levels (ml/kg/min) following Day 1 test measures at 53.53 (± 7.2). No illnesses or medications were reported prior to Day 1 measures.

Exposure Concentrations

We were able to successfully deliver consistent, reproducible exposures in the wood smoke inhalation facility. FIGURE 2 presents an example of a participant’s delivered smoke PM2.5 concentrations at the mask throughout the 250 μg/m3 and 500 μg/m3 exposure trials. Across all trials, the average measured concentrations of PM2.5 from filtered-air, 250 μg/m3, and 500 μg/m3 exposures were 5.2 (±4.9) μg/m3, 253.9 (± 5.8) μg/m3, and 506.2 (± 4.8) μg/m3, respectively. Greater than 99% of PM2.5 mass measured in the dilution chamber was in the PM1 fraction (as measured by the DustTrak Model 8534, data not shown). The average levels of CO from all filtered-air, 250 μg/m3, and 500 μg/m3 exposures were 0.003 (± 0.007) ppm, 0.87 (± 0.28) ppm, and 1.87 (± 0.65) ppm, respectively. Mean levels of CO2 from all filtered-air, 250 μg/m3, and 500 μg/m3 exposures were 443 (± 22) ppm, 464 (± 28) ppm, and 482 (± 21) ppm, respectively. From all filtered-air, 250 μg/m3, and 500 μg/m3 exposures, relative humidity was 14.1 (± 8.4) %, 12.1 (± 5.3) %, and 13.1 (± 2.7) %, respectively.

FIGURE 2.

FIGURE 2.

Continuous PM2.5 concentrations and averages plotted for a 250 μg/m3 (top) and 500 μg/m3 (bottom) 90-minute exposure trial, respectively.

Lung Function

As presented in TABLE I, calculated “change from pre-exposure values” included normalizing each participant’s post- and 1-hour post-exposure spirometry values (FVC, FEV1, and FVC:FEV1) to their perspective pre-exposure levels, for each of the three exposures. This included subtracting pre-exposure values from post- and 1-hour post-exposure, for each individual exposure. This normalization decreases within-participant day-to-day variation, as well as between-participant variation.

TABLE I.

Measured Spirometry Outcomes as Averages and as Change from Pre-Exposure Levels.

Pre-exposure (n=9) Post-exposure (n=9) 1-hr Post-exposure (n=10)

Filtered-air 250 μg/m3 500 μg/m3 Filtered-air 250 μg/m3 500 μg/m3 Filtered-air 250 μg/m3 500 μg/m3
Measurement category Mean (sd) Mean (sd) Mean (sd) Mean (sd) Mean (sd) Mean (sd) Mean (sd) Mean (sd) Mean (sd)

FVC
Unadjusted values (liters) 5.41 (0.53) 5.58 (0.82) 5.61 (0.93) 5.37 (0.61) 5.62 (0.79) 5.69 (0.96) 5.37 (0.46) 5.51 (0.77) 5.57 (0.94)
change from pre-exposure levelsA −0.04 (0.30) 0.04 (0.21) 0.08 (0.28) 0.00 (0.33) −0.07 (0.27) −0.04 (0.21)
FEV1
Unadjusted values (liters) 4.37 (0.34) 4.55 (0.64) 4.44 (0.67) 4.41 (0.46) 4.35 (0.90) 4.64 (0.64) 4.42 (0.42) 4.27 (0.89) 4.39 (0.62)
change from pre-exposure levelsA 0.04 (0.31) −0.19 (1.00) 0.20 (0.36) 0.05 (0.48) −0.27 (1.03) −0.05 (0.33)
FVC:FEV1
Unadjusted values (ratio) 81.11 (6.34) 81.26 (6.44) 79.72 (8.10) 82.37 (6.97) 77.86 (14.0) 81.85 (7.29) 82.89 (7.90) 78.24 (15.3) 79.43 (8.54)
change from pre-exposure levelsA 1.26 (2.39) −3.40 (14.2) 2.13 (3.33) 1.78 (5.66) −3.02 (15.5) −0.29 (4.32)
A

Estimated changes from pre-exposure to immediate post-exposure and change from pre-exposure to 1-hour post-exposure.

Overall, spirometry results showed no significant changes following wood smoke PM2.5 exposures (TABLE I). The mean pre-exposure FVC results ranged from 5.41 (0.53) - 5.61 (0.93) liters. There was no impairment in lung function measured at the post-exposure time point, but there were slight reductions in FVC for the 250 μg/m3 and 500 μg/m3 exposures at the 1-hour post time point (−0.07 and −0.04 liters, respectively). This same trend is observed in the FEV1 measures. Pre-exposure baseline FEV1 measures ranged from 4.37 (0.34) - 4.55 (0.64) liters. Following the exposures, there was a post-exposure reduction at the 250 μg/m3 trial (−0.19 liters), and reductions of −0.27 liters (250 μg/m3) and −0.05 liters (500 μg/m3) measured in the 1-hour post exposure spirometry tests. Consistent with the FEV1 measures, we saw insignificant reductions in the ratio of FVC:FEV1 post-exposure at the 250 μg/m3 trial (−3.40), and insignificant reductions in 1-house post exposure measures for 250 μg/m3 (−3.02) and 500 μg/m3 (−0.29) exposure trials.

DISCUSSION

One goal of this pilot project was to deliver specific concentrations of PM2.5 wood smoke that simulated occupational exposures encountered by wildland firefighters. As demonstrated in FIGURE 2, the measured concentrations of PM2.5 were consistent with (and representative of) field research studies where PM levels (and CO concentrations) were recorded during wildland firefighting activities (25). Exposure concentrations are also representative of exposures encountered in other settings, providing future opportunities to investigate other exposure scenarios. The lower concentration of wood smoke PM2.5 exposure in this study (250 μg/m3) is comparable to concentrations recorded when biomass is burned for cooking or heating purposes in homes without ventilation (35), and consistent with concentrations used in other European human/biomass smoke exposure studies (3643). The higher level of exposure (500 μg/m3) is comparable to human exposure studies conducted by the Environmental Protection Agency’s Ghio et al. (44), where participants were exposed to an average concentration of 485 μg/m3 over a 2-hour period. Similarly, occupational studies have reported average wood smoke PM exposures (i.e., wildland fire firefighters) in the range of 500–800 μg/m3 (25, 26, 45). These same studies reported average CO and CO2 levels ranging about 1–7 ppm and 400–500 ppm, respectively.

Health Effects Associated with Wood Smoke Exposure

Most of the current knowledge regarding the adverse health effects (both acute and chronic detriments) following wood smoke exposures have come from epidemiologal studies. Ambient wildland fire PM levels exceeding 40 μg/m3, relative to concentrations less than 10 μg/m3 are associated with more than a doubling of observed asthmatic presentations (46). Other observations following similar events included increased risk of allergic respiratory disease, as well as bronchial asthma, exacerbation of type II diabetes (47) and cardiovascular disease (48, 49). Significant decreases in lung function were reported in several studies following occupational exposures (e.g. wildland firefighting) to wood smoke PM (27, 45, 50). Additional studies have shown a general increase in emergency room and outpatient visits during and following smoke events (49, 51-54).

Human Exposure Wood Smoke Studies

The limited number of studies involving human exposures to wood smoke PM in controlled environments show varying results. TABLE II presents a summary of human wood smoke studies that have been conducted in a variety of settings. Throughout the literature, PM levels in the human exposure studies ranged from around 150 to 1000 μg/m3, with durations of exposures from 1 to 4 hours. Studies reported a varying degree of physical activity throughout the trials, from sedentary 3-hour exposures (55) to riding an exercise bike at light effort (~70 W) for two 25-minute periods during a 4-hour exposure [PM2.5 concentrations 243–279 μg/m3 (43)]. The majority of the parameters (e.g., PM concentrations, duration of exposure, etc.) used in the present pilot study were within the range of those outlined in TABLE II. The route of exposure (using a mask to deliver the exposure) and the exercise component (briskly walking on a treadmill at a set rate and incline (3.5 mph and 5.7% grade) for 1.5 hours) are notable differences between our study and those summarized in TABLE II.

TABLE II.

Summary of Controlled Human Exposure Studies.

References N Exercise duration Exposure concentration(s) Wood smoke exposure
Hunter et al. 2014 16 adult males bike every 15 minutes 1-hour filtered-air and ~1 mg/m3
Bønløkke et al. 2014 24 adult males and females at rest 3.5 hours filtered-air (13), 222, and 385 μg/m3
Unosson et al. 2013 14 adult males and females bike every 15 minutes 3 hours filtered-air and 214 μg/m3
Stockfelt et al. 2013 16 adult males and females at rest 3 hours filtered-air, 146, and 295 μg/m3
Ghio et al. 2012 10 healthy individualsA bike every 15 minutes 2 hours filtered-air and 485 μg/m3
Stockfelt et al. 2012 16 adult males and females at rest 3 hours filtered-air, 146, and 295 μg/m3
Forchhammer et al. 2012 20 adult males and females at rest 3 hours filtered-air (14), 220, and 354 μg/m3
Riddervold et al. 2012 20 adult males and females at rest 3.5 hours filtered-air, 200, and 400 μg/m3
Riddervold et al. 2011 20 adult males and females at rest 3.5 hours filtered-air, 200, and 400 μg/m3
Sehlstedt et al. 2010 19 adult males and females bike every 15 minutes 3 hours filtered-air and 224 μg/m3
Danielsen et al. 2008 13 adult males and females 25 minute bike ride, 2x 4 hours filtered-air and 243–279μg/m3
Barregard et al. 2008 13 adult males and females 25 minute bike ride, 2x 4 hours filtered-air and 243–279 μg/m3
Sällsten et al. 2006 13 adult males and females 25 minute bike ride, 2x 4 hours filtered-air and 250 μg/m3
Barregard et al. 2006 13 adult males and females 25 minute bike ride, 2x 4 hours filtered-air and 243–279 μg/m3
A

Gender details of participating individuals not outlined in manuscript

Spirometry results from our study are consistent with previous studies (44, 56, 39) where, in healthy individuals, no significant changes in lung function were observed following controlled acute wood smoke exposures. Previous field studies investigating the influence of wildland fire smoke on wildland firefighter lung function, on the other hand, have shown significant effects from smoke inhalation (27, 28). Liu et al. (28) gathered spirometry data from sixty-three “seasoned” firefighters before and after a full season of fighting wildland fires. Significant declines in mean FVC and FEV1 values were observed post-season (0.09 and 0.15 L/s, respectively). In a comparable study, Betchley et al. (27) observed similar declines in FVC and FEV1 in a cohort of seventy-six volunteers following a full season of fighting wildland fires. Compared to our study conducted in a controlled environment, these field studies had much longer exposure durations and higher wood smoke concentrations generated from multiple fuel types.

Study Limitations and Next Steps

The results of both epidemiological studies and the controlled human studies presented in TABLE II have demonstrated that there are a variety of adverse health effects following exposure to wood smoke. These studies have reported conflicting results and outcomes. Several of these studies found no significant pro-inflammatory responses (38, 39, 55), whereas increases were observed in others (42, 44, 56,). Differences such as exposure levels, durations of exposure, varying physical activities, even biological media type (e.g. blood, EBC, etc.) and time of sample collection can partly explain these disparities. Also, the different lung function outcomes between short duration controlled exposures versus those following chronic exposures (i.e. wildland firefighters) suggest a possible role in exposure durations and recurrences. These outcomes should be considered in subsequent research trials.

As we designed this study to simulate exposures and environmental conditions experienced by wildland firefighters, exercise during the exposure trials was an important component of this study. As presented in TABLE II, about half of the aforementioned controlled human wood smoke exposure studies did not participate in an activity that might increase breathing and heart rate. In the studies where exercise was included, it was generally intermittent and non-strenuous. Importantly, the majority of observed effects occurred in participants that exercised intermittently during exposures. Also, due to the small size of this pilot study, only males were included. However, about 12%−16% of the wildland firefighter community is female (57). We intend to incorporate both genders in future occupational studies.

CONCLUSION

As rising temperatures and shrinking snow pack have both been impacted by climate change, it is hypothesized that the frequency, magnitude, and intensity of wildland fires will increase during future summers. In a 2008 commissioned report, it was concluded that “the most important research question with respect to wildland fire particle emissions is the relationship between emission, acute and chronic exposure, and health effects” (58). These factors point to more research needed for wildland firefighters who are exposed to wood smoke PM2.5 during occupational activities, as well as members of the public who are exposed to wildland and prescribed fire smoke in downwind populations.

Given the complexities (and dangers) of studying wood smoke exposures/health effects during actual wildland fire scenarios, our inhalational facility is novel in that it provides an opportunity to investigate human health effects following exposures to a range of relevant wood smoke PM concentrations during physical stress (including increased breathing rate) that simulates absolute intensity of a wildland firefighter. While focusing on firefighting activities, this study will also provide meaningful data on how wood smoke PM exposures might influence general and susceptible populations. In summary, this pilot study offers a unique method for delivering wood smoke PM at specific concentrations in a closed system. Controlling the physical exertion of our participants provides another innovative aspect of this study. The fire type, fuel type, mixing of filtered air with smoke effluent, and having direct control of those levels entering the mask provides a unique tool to answer important questions regarding human health impacts from wood smoke exposures. Future directions include evaluating systemic and pulmonary effects from these exposures, and investigating inflammatory outcomes and oxidative stress, including biomarkers of cardiovascular disease risk.

ACKNOWLEDGEMENTS

The authors thank Jed Syrenne, Britton Postma, Matthew Dorton, Kyle Cochrane, Emily Simpson, and Laura Porisch for data collection efforts. We are also grateful to Leon Washut and the Washut Endowment for Graduate Student Support in Biomedical Sciences at the University of Montana, as well as the study participants for the considerable time and effort put into this investigation. This research was supported by NCRR (COBRE P20RR 017670).

REFERENCES

  • 1.Pope IC, Burnett RT, Thun MJ, et al. : Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287(9): 1132–1141 (2002). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Cohen AJ, Ross Anderson H, Ostro B, Pandey KD, Krzyzanowski M, Kunzli N et al. : The Global Burden of Disease Due to Outdoor Air Pollution. Journal of Toxicology and Environmental Health, Part A 68(13–14): 1301–1307 (2005). [DOI] [PubMed] [Google Scholar]
  • 3.World Health Organization (WHO): 7 million premature deaths annually linked to air pollution. World Health Organization; (2014). [Google Scholar]
  • 4.U.S. Department of Energy: Space Heating in U.S. Homes, By Census Region, by U.S Energy Information Administration (EIA) Washington, D.C. (2009). [Google Scholar]
  • 5.Air Quality Management Work Group: Recommendations to the Clean Air Act Advisory Committee: Phase I and Next Steps. Washington, D.C: Air Quality Management Work Group, USEPA; 2005. [Google Scholar]
  • 6.Ward TJ, and Lange T: The impact of wood smoke on ambient PM2.5 in northern Rocky Mountain valley communities. Environmental Pollution 158(3): 723–729 (2010). [DOI] [PubMed] [Google Scholar]
  • 7.Naeher LP, Brauer M, Lipsett M, Zelikoff JT, Simpson CD, Koenig JQ et al. : Woodsmoke health effects: A review. Inhalation Toxicology 19(1): 67–106 (2007). [DOI] [PubMed] [Google Scholar]
  • 8.Larson T, Gould T, Simpson C, Liu LJS, Claiborn C, and Lewtas J: Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington, using positive matrix factorization. Journal of the Air & Waste Management Association 54(9): 1175–1187 (2004). [DOI] [PubMed] [Google Scholar]
  • 9.Ward TJ, and Smith GC: The 2000/2001 Missoula Valley PM2.5 chemical mass balance study, including the 2000 wildfire season - seasonal source apportionment. Atmospheric Environment 39(4): 709–717 (2005). [Google Scholar]
  • 10.Noonan CW, Ward TJ, Navidi W, Sheppard L, Bergauff M, and Palmer C: Assessing the impact of a wood stove replacement program on air quality and children’s health. Research report (162): 3–37; discussion 39–47 (2011). [PubMed] [Google Scholar]
  • 11.Ward T, and Noonan C: Results of a residential indoor PM(2.5) sampling program before and after a woodstove changeout. Indoor Air 18(5): 408–415 (2008). [DOI] [PubMed] [Google Scholar]
  • 12.Ward T, Boulafentis J, Simpson J, Hester C, Moliga T, Warden K et al. : Lessons learned from a woodstove changeout on the Nez Perce Reservation. Science of The Total Environment 409(4): 664–670 (2011). [DOI] [PubMed] [Google Scholar]
  • 13.Allen RW, Leckie S, Millar G, and Brauer M: The impact of wood stove technology upgrades on indoor residential air quality. Atmospheric Environment 43(37): 5908–5915 (2009). [Google Scholar]
  • 14.Noonan CW, Navidi W, Sheppard L, Palmer CP, Bergauff M, Hooper K et al. : Residential indoor PM2.5 in wood stove homes: follow-up of the Libby changeout program. Indoor Air 22(6): 492–500 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Semmens EO, Noonan CW, Allen RW, Weiler EC, and Ward TJ: Indoor particulate matter in rural, wood stove heated homes. Environmental Research 138: 93–100 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Jenkins PL, Phillips TJ, Mulberg EJ, and Hui SP: Activity Patterns of Californians - Use of and Proximity to Indoor Pollutant Sources. Atmospheric Environment Part a-General Topics 26(12): 2141–2148 (1992). [Google Scholar]
  • 17.Johnston FH, Henderson SB, Chen Y, Randerson JT, Marlier M, Defries RS et al. : Estimated global mortality attributable to smoke from landscape fires. Environmental Health Perspectives 120(5): 695–701 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.McKenzie D, Shankar U, Keane RE, Stavros EN, Heilman WE, Fox DG et al. : Smoke consequences of new wildfire regimes driven by climate change. Earth’s Future 2(2): 35–59 (2014). [Google Scholar]
  • 19.Westerling A, Brown T, Schoennagel T, Swetnam T, Turner M, and Veblen T: Briefing: Climate and wildfire in western U.S. forests. In Forest conservation and management in the Anthropocene: Conference proceedings Proceedings. RMRS-P-71. Fort Collins, CO, Sample VAB, Patrick R(ed.), pp. p. 81–102: US Department of Agriculture, Forest Service. Rocky Mountain Research Station, 2014. [Google Scholar]
  • 20.Le GE, Breysse PN, McDermott A, Eftim SE, Geyh A, Berman JD et al. : Canadian forest fires and the effects of long-range transboundary air pollution on hospitalizations among the elderly. ISPRS International Journal of Geo-Information 3(2): 713–731 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Barn P, Larson T, Noullett M, Kennedy S, Copes R, and Brauer M: Infiltration of forest fire and residential wood smoke: an evaluation of air cleaner effectiveness. Journal of Exposure Science and Environmental Epidemiology 18(5): 503–511 (2008). [DOI] [PubMed] [Google Scholar]
  • 22.Henderson DE, Milford JB, and Miller SL: Prescribed burns and wildfires in Colorado: Impacts of mitigation measures on indoor air particulate matter. Journal of the Air & Waste Management Association 55(10): 1516–1526 (2005). [DOI] [PubMed] [Google Scholar]
  • 23.Phuleria HC, Fine PM, Zhu YF, and Sioutas C: Air quality impacts of the October 2003 Southern California wildfires. Journal of Geophysical Research-Atmospheres 110(D7)(2005). [Google Scholar]
  • 24.Sapkota A, Symons JM, Kleissl J, Wang L, Parlange MB, Ondov J et al. : Impact of the 2002 Canadian forest fires on particulate matter air quality in Baltimore City. Environmental Science & Technology 39(1): 24–32 (2005). [DOI] [PubMed] [Google Scholar]
  • 25.Adetona O, Simpson CD, Onstad G, and Naeher LP: Exposure of wildland firefighters to carbon monoxide, fine particles, and levoglucosan. The Annals of occupational hygiene 57(8): 979–991 (2013). [DOI] [PubMed] [Google Scholar]
  • 26.Reinhardt TE, and Ottmar RD: Baseline measurements of smoke exposure among wildland firefighters. Journal of Occupational and Environmental Hygiene 1(9): 593–606 (2004). [DOI] [PubMed] [Google Scholar]
  • 27.Betchley C, Koenig JQ, van Belle G, Checkoway H, and Reinhardt T: Pulmonary function and respiratory symptoms in forest firefighters. American Journal of Industrial Medicine 31(5): 503–509 (1997). [DOI] [PubMed] [Google Scholar]
  • 28.Liu D, Tager IB, Balmes JR, and Harrison RJ: The effect of smoke inhalation on lung function and airway responsiveness in wildland fire fighters. The American review of respiratory disease 146(6): 1469–1473 (1992). [DOI] [PubMed] [Google Scholar]
  • 29.Rothman N, Ford DP, Baser ME, Hansen JA, O’Toole T, Tockman MS et al. : Pulmonary function and respiratory symptoms in wildland firefighters. Journal of occupational medicine. : official publication of the Industrial Medical Association 33(11): 1163–1167 (1991). [DOI] [PubMed] [Google Scholar]
  • 30.Halbert RJ, Natoli JL, Gano A, Badamgarav E, Buist AS, and Mannino DM: Global burden of COPD: systematic review and meta-analysis. European Respiratory Journal 28(3): 523–532 (2006). [DOI] [PubMed] [Google Scholar]
  • 31.Buffels J, Degryse J, Heyrman J, and Decramer M: Office spirometry significantly improves early detection of copd in general practice*: The didasco study. Chest 125(4): 1394–1399 (2004). [DOI] [PubMed] [Google Scholar]
  • 32.Nowak RM, Gordon KR, Wroblewski DA, Tomlanovich MC, and Kvale PA: Spirometric evaluation of acute bronchial asthma. JACEP 8(1): 9–12 (1979). [DOI] [PubMed] [Google Scholar]
  • 33.Celli BR: The importance of spirometry in COPD and asthma: effect on approach to management. Chest 117(2 Suppl): 15S–19S (2000). [DOI] [PubMed] [Google Scholar]
  • 34.Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, et al. : Standardisation of Spirometry. European Respiratory Journal. 26(2): 319–338 (2005) [DOI] [PubMed] [Google Scholar]
  • 35.Dills RL, Paulsen M, Ahmad J, Kalman DA, Elias FN, and Simpson CD: Evaluation of urinary methoxyphenols as biomarkers of woodsmoke exposure. Environmental Science & Technology 40(7): 2163–2170 (2006). [DOI] [PubMed] [Google Scholar]
  • 36.Riddervold IS, Bønløkke JH, Molhave L, Massling A, Jensen B, Gronborg TK et al. : Wood smoke in a controlled exposure experiment with human volunteers. Inhalation Toxicology 23(5): 277–288 (2011). [DOI] [PubMed] [Google Scholar]
  • 37.Stockfelt L, Sallsten G, Olin AC, Almerud P, Samuelsson L, Johannesson S et al. : Effects on airways of short-term exposure to two kinds of wood smoke in a chamber study of healthy humans. Inhalation Toxicology 24(1): 47–59 (2012). [DOI] [PubMed] [Google Scholar]
  • 38.Forchhammer L, Moller P, Riddervold IS, Bønløkke J, Massling A, Sigsgaard T et al. : Controlled human wood smoke exposure: oxidative stress, inflammation and microvascular function. Particle and fibre toxicology 9(2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Sehlstedt M, Dove R, Boman C, Pagels J, Swietlicki E, Londahl J et al. : Antioxidant airway responses following experimental exposure to wood smoke in man. Particle and fibre toxicology 7(2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Danielsen PH, Brauner EV, Barregard L, Sallsten G, Wallin M, Olinski R et al. : Oxidatively damaged DNA and its repair after experimental exposure to wood smoke in healthy humans. Mutation Research-Fundamental and Molecular Mechanisms of Mutagenesis 642(1–2): 37–42 (2008). [DOI] [PubMed] [Google Scholar]
  • 41.Barregard L, Saellsten G, Andersson L, Almstrand AC, Gustafson P, Andersson M et al. : Experimental exposure to wood smoke: effects on airway inflammation and oxidative stress. Occupational and Environmental Medicine 65(5): 319–324 (2008). [DOI] [PubMed] [Google Scholar]
  • 42.Sällsten G, Gustafson P, Johansson L, Johannesson S, Molnar P, Strandberg B et al. : Experimental wood smoke exposure in humans. Inhalation Toxicology 18(11): 855–864 (2006). [DOI] [PubMed] [Google Scholar]
  • 43.Barregard L, Sallsten G, Gustafson P, Andersson L, Johansson L, Basu S et al. : Experimental exposure to wood-smoke particles in healthy humans: Effects on markers of inflammation, coagulation, and lipid peroxidation. Inhalation Toxicology 18(11): 845–853 (2006). [DOI] [PubMed] [Google Scholar]
  • 44.Ghio AJ, Soukup JM, Case M, Dailey LA, Richards J, Berntsen J et al. : Exposure to wood smoke particles produces inflammation in healthy volunteers. Occupational and Environmental Medicine 69(3): 170–175 (2012). [DOI] [PubMed] [Google Scholar]
  • 45.Slaughter JC, Koenig JQ, and Reinhardt TE: Association between lung function and exposure to smoke among firefighters at prescribed burns. Journal of Occupational and Environmental Hygiene 1(1): 45–49 (2004). [DOI] [PubMed] [Google Scholar]
  • 46.Johnston FH, Kavanagh AM, Bowman DM, and Scott RK: Exposure to bushfire smoke and asthma: an ecological study. The Medical journal of Australia 176(11): 535–538 (2002). [DOI] [PubMed] [Google Scholar]
  • 47.Filho MAP, Pereira LAA, Arbex FF, Arbex M, Conceicao GM, Santos UP et al. : Effect of air pollution on diabetes and cardiovascular diseases in Sao Paulo, Brazil. Brazilian Journal of Medical and Biological Research 41(6): 526–532 (2008). [DOI] [PubMed] [Google Scholar]
  • 48.Park SK, Auchincloss AH, O’Neill MS, Prineas R, Correa JC, Keeler J et al. : Particulate air pollution, metabolic syndrome, and heart rate variability: the multi-ethnic study of atherosclerosis (MESA). Environmental Health Perspectives 118(10): 1406–1411 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Mott JA, Mannino DM, Alverson CJ, Kiyu A, Hashim J, Lee T et al. : Cardiorespiratory hospitalizations associated with smoke exposure during the 1997, Southeast Asian forest fires. International Journal of Hygiene and Environmental Health 208(1–2): 75–85 (2005). [DOI] [PubMed] [Google Scholar]
  • 50.Tepper A, Comstock GW, and Levine M: A longitudinal study of pulmonary function in fire fighters. American Journal of Industrial Medicine 20(3): 307–316 (1991). [DOI] [PubMed] [Google Scholar]
  • 51.Duclos P, Sanderson LM, and Lipsett M: The 1987 forest fire disaster in California: assessment of emergency room visits. Archives of Environmental Health: An International Journal 45(1): 53–58 (1990). [DOI] [PubMed] [Google Scholar]
  • 52.Emmanuel SC: Impact to lung health of haze from forest fires: the Singapore experience. Respirology 5(2): 175–182 (2000). [DOI] [PubMed] [Google Scholar]
  • 53.Kunzli N, Jerrett M, Mack WJ, Beckerman B, LaBree L, Gilliland F et al. : Ambient air pollution and atherosclerosis in Los Angeles. Environmental Health Perspectives 113(2): 201–206 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Chen L, Verrall K, and Tong S: Air particulate pollution due to bushfires and respiratory hospital admissions in Brisbane, Australia. International Journal of Environmental Health Research 16(3): 181–191 (2006). [DOI] [PubMed] [Google Scholar]
  • 55.Stockfelt L, Sallsten G, Almerud P, Basu S, and Barregard L: Short-term chamber exposure to low doses of two kinds of wood smoke does not induce systemic inflammation, coagulation or oxidative stress in healthy humans. Inhalation Toxicology 25(8): 417–425 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Riddervold IS, Bønløkke JH, Olin AC, Gronborg TK, Schlunssen V, Skogstrand K et al. : Effects of wood smoke particles from wood-burning stoves on the respiratory health of atopic humans. Particle and fibre toxicology 9: 12 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.National Wildland Firefighter, N.W.F.: National Wildland Firefighter (NWFF) Workforce Assessment - Final Report. Washington, D.C. : United States Forest Service, 2010. [Google Scholar]
  • 58.Austin C: “Wildland Firefighter Health Risks and Respiratory Protection” Montréal: IRSST, 2008 [Google Scholar]

RESOURCES