Real-time and time-integrated PM2.5 and CO from prescribed burns in chipped and non-chipped plots: firefighter and community exposure and health implications

Designing a conceptual framework for strategic selection of Bushfire mitigation approaches

Fires are an important aspect of environmental ecology; however, they are also one of the most widespread destructive forces impacting natural ecosystems as well as property, human health, water and other resources. Urban sprawl is driving the construction of new homes and facilities into fire-vulnerable areas. This growth, combined with a warmer climate, is likely to make the consequences of wildfires more severe. To reduce wildfires and associated risks, a variety of hazard reduction practices are implemented, such as prescribed burning (PB) and mechanical fuel load reduction (MFLR). PB can reduce forest fuel load; however, it has adverse effects on air quality and human health, and should not be applied close to residential areas due to risks of fire escape. On the other hand, MFLR releases less greenhouse gasses and does not impose risks to residential areas. However, it is more expensive to implement. We suggest that environmental, economic and social costs of various mitigation tools should be taken into account when choosing the most appropriate fire mitigation approach and propose a conceptual framework, which can do it. We show that applying GIS methods and life cycle assessment we can produce a more reasonable comparison that can, for example, include the benefits that can be generated by using collected biomass for bioenergy or in timber industries. This framework can assist decision makers to find the optimal combinations of hazard reduction practices for various specific conditions and locations.

Spatial distribution of particulate matter 2.5 released from surface fuel combustion of Pinus koraiensis - A laboratory simulation study

High concentration particulate matter 2.5 released from forest fires, in addition to direct burns and asphyxia, PM_2.5 is one of the main pollutants which threaten the safety of forest fire fighter. Therefore, to assess spatial distribution of PM_2.5, a simulation study was conducted. Fuel beds with different moisture contents and loads were constructed. 144 times burning experiments were carried out under different wind speeds by using wind tunnel device. PM_2.5 particles at different spatial points were collected and calculated. The results show that, in the two of three variables interaction between wind speed, fuel load, and, except fuel moisture content, wind speed and fuel load are positively correlated with the PM_2.5 concentrations. From PM_2.5 concentration which collected at each point in the horizontal and vertical directions, the overall trend is that PM_2.5 concentration increases along the horizontal downwind direction (C and D higer than A and B) and the vertical upward direction (A and C higer than B and D) Based on BP neural network, the spatial distribution model of PM_2.5 concentration with single hidden layer was established. The prediction accuracy of modeling samples and validation samples is balanced when hidden layer node is 5. This study will help to make reference for PM_2.5 occupational exposure standards, forest fire smoke management and forest fire management in China.

African American Exposure to Prescribed Fire Smoke in Georgia, USA

Our project examines the association between percent African American and smoke pollution in the form of prescribed burn-sourced, fine particulate matter (PM_2.5) in the U.S. state of Georgia for 2018. (1) Background: African Americans constitute 32.4% of Georgia's population, making it the largest racial/ethnic minority group in the state followed by Hispanic Americans at 9.8%. African Americans, Hispanic Americans, and lower wealth groups are more likely than most middle and upper income White Americans to be exposed to environmental pollutants. This is true because racial and ethnic minorities are more likely to live in urban areas where pollution is more concentrated. As a point of departure, we examine PM_2.5 concentrations specific to prescribed fire smoke, which typically emanates from fires occurring in rural or peri-urban areas. Two objectives are specified: a) examine the association between percent African American and PM_2.5 concentrations at the census tract level for Georgia, and b) identify emitters of PM_2.5 concentrations that exceed National Ambient Air Quality Standards (NAAQS) for the 24-h average, i. e., >35 µg/m³. (2) Methods: For the first objective, we estimate a spatial Durbin error model (SDEM) where pollution concentration (PM_2.5) estimates for 1683 census tracts are regressed on percent of the human population that is African American or Hispanic; lives in mobile homes; and is employed in agriculture and related occupations. Also included as controls are percent evergreen forest, percent mixed evergreen/deciduous forest, and variables denoting lagged explanatory and error variables, respectively. For the second objective, we merge parcel and prescribed burn permit data to identify landowners who conduct prescribed fires that produce smoke exceeding the NAAQS. (3) Results: Percent African American and mobile home dweller are positively related to PM_2.5 concentrations; and government and non-industrial private landowners are the greatest contributors to exceedance levels (4) Conclusions: Reasons for higher PM_2.5 concentrations in areas with higher African American and mobile home percent are not clear, although we suspect that neither group is a primary contributor to prescribed burn smoke but rather tend to live proximate to entities, both public and private, that are. Also, non-industrial private landowners who generated prescribed burn smoke exceeding NAAQS are wealthier than others, which suggests that African American and other environmental justice populations are less likely to contribute to exceedance levels in the state.

Impacts of prescribed fires and benefits from their reduction for air quality, health and visibility in the Pacific Northwest of the United States

Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and local air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios - 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho and western Montana where most prescribed fires occur. Prescribed burning contributes to visibility impairment and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 work day losses can be attributed to prescribed fires and these health impacts decrease by 25-30% when a 30% fire emission scenario is considered. Implications This study assesses the potential regional and local air quality, public health and visibility impacts from prescribed burning activities as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts and improved visibility.

The impact of the 2016 Fort McMurray Horse River Wildfire on ambient air pollution levels in the Athabasca Oil Sands Region, Alberta, Canada

An unprecedented wildfire impacted the northern Alberta city of Fort McMurray in May 2016 causing a mandatory city wide evacuation and the loss of 2,400 homes and commercial structures. A two-hectare wildfire was discovered on May 1, grew to ~157,000ha by May 5, and continued to burn an estimated ~590,000ha by June 13. A comprehensive air monitoring network operated by the Wood Buffalo Environmental Association (WBEA) in and around Fort McMurray provided essential health-related real-time air quality data to firefighters during the emergency, and provided a rare opportunity to elucidate the impact of gaseous and particulate matter emissions on near-field communities and regional air pollution concentrations. The WBEA network recorded 188 fire-related exceedances of 1-hr and 24-hr Alberta Ambient Air Quality Objectives. Two air monitoring sites within Fort McMurray recorded mean/maximum 1-hr PM2.5 concentrations of 291/5229μgm-3 (AMS-6) and 293/3259μgm-3 (AMS-7) during fire impact periods. High correlations (r2=0.83-0.97) between biomass combustion related gases (carbon monoxide (CO), non-methane hydrocarbons (NMHC), total hydrocarbons (THC), total reduced sulfur (TRS), ammonia) and PM2.5 were observed at the sites. Filter-based 24-hr integrated PM2.5 samples collected every 6 days showed maximum concentrations of 267μgm-3 (AMS-6) and 394μgm-3 (AMS-7). Normalized excess emission ratios relative to CO were 149.87±3.37μgm-3ppm-1 (PM2.5), 0.274±0.002ppmppm-1 (THC), 0.169±0.001ppmppm-1 (NMHC), 0.104±0.001ppmppm-1 (CH4), 0.694±0.007ppbppm-1 (TRS), 0.519±0.040ppbppm-1 (SO2), 0.412±0.045ppbppm-1 (NO), 1.968±0.053ppbppm-1 (NO2), and 2.337±0.077ppbppm-1 (NOX). A subset of PM2.5 filter samples was analyzed for trace elements, major ions, organic carbon, elemental carbon, and carbohydrates. Sample mass reconstruction and fire specific emission profiles are presented and discussed. Potential fire-related photometric ozone instrument positive interferences were observed and were positively correlated with NO and NMHC.

Improving estimation of real-time concentration for inhalable particles < 10 microm from a light scattering monitor

This study evaluated the relationship between the real-time concentration measurements of inhalable particles whose diameters were less than 10 microm, from a light scattering monitor and a beta gauge monitor, at various instantaneous relative humidities. This work demonstrated that the mean inhalable particle concentrations as measured by the light scattering monitor were higher than those of the manual sampler, such that a factor of 0.74 was employed to adjust the light scattering monitor for inhalable particle concentration measurements. The mean inhalable particle concentrations determined by the beta gauge monitor at a low relative humidity setpoint correlated well with those obtained by the manual sampler. The real-time inhalable particle concentration of the adjusted light scattering monitor was further compared to those of the beta gauge monitor to investigate the effect of instantaneous relative humidity on the mass readings of the automatic monitors. The results demonstrated that the estimated concentration measurements by the adjusted light scattering monitor should be re-calibrated in real-time to improve the accuracy of the inhalable particle concentrations at various instantaneous relative humidities.

Biological monitoring of smoke exposure among wildland firefighters: a pilot study comparing urinary methoxyphenols with personal exposures to carbon monoxide, particular matter, and levoglucosan

Urinary methoxyphenols (MPs) have been proposed as biomarkers of woodsmoke exposure. However, few field studies have been undertaken to evaluate the relationship between woodsmoke exposure and urinary MP concentrations. We conducted a pilot study at the US Forest Service-Savannah River Site, in which carbon monoxide (CO), levoglucosan (LG), and particulate matter (PM(2.5)) exposures were measured in wildland firefighters on prescribed burn days. Pre- and post-shift urine samples were collected from each subject, and cross-shift changes in creatinine-corrected urinary MP concentrations were calculated. Correlations between exposure measures and creatine-adjusted urinary MP concentrations were explored, and regression models were developed relating changes in urinary MP concentrations to measured exposure levels. Full-shift measurements were made on 13 firefighters over 20 work shifts in winter 2004 at the US Forest Service Savannah River site, a National Environmental Research Park. The average workshift length across the 20 measured shifts was 701+/-95 min. LG and CO exposures were significantly correlated for samples where the filter measurement captured at least 60% of the work shift (16 samples), as well as for the smaller set of full-shift exposure samples (n=9). PM(2.5) and CO exposures were not significantly correlated, and LG and PM(2.5) exposures were only significantly correlated for samples representing at least 60% of the work shift. Creatinine-corrected urinary concentrations for 20 of the 22 MPs showed cross-shift increases, with 14 of these changes showing statistical significance. Individual and summed creatinine-adjusted guaiacol urinary MPs were highly associated with CO (and, to a lesser degree, LG) exposure levels, and random-effects regression models including CO and LG exposure levels explained up to 80% of the variance in cross-shift changes in summed creatinine-adjusted guaiacol urinary MP concentrations. Although limited by the small sample size, this pilot study demonstrates that urinary MP concentrations may be effective biomarkers of occupational exposure to wood smoke among wildland firefighters.