a transdisciplinary approach to understanding the health
TRANSCRIPT
University of WollongongResearch Online
Faculty of Science, Medicine and Health - Papers Faculty of Science, Medicine and Health
2016
A transdisciplinary approach to understanding thehealth effects of wildfire and prescribed fire smokeregimesG WilliamsonUniversity of Tasmania, [email protected]
David M. J. S BowmanUniversity of Tasmania
Owen F. PriceUniversity of Wollongong, [email protected]
S HendersonBritish Columbia Centre For Disease Control, Vancouver
Fay JohnstonUniversity of Tasmania
Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library:[email protected]
Publication DetailsWilliamson, G. J., Bowman, D. M. J. S., Price, O. F., Henderson, S. B. & Johnston, F. H. (2016). A transdisciplinary approach tounderstanding the health effects of wildfire and prescribed fire smoke regimes. Environmental Research Letters, 11 (12),125009-1-125009-11.
A transdisciplinary approach to understanding the health effects of wildfireand prescribed fire smoke regimes
AbstractPrescribed burning is used to reduce the occurrence, extent and severity of uncontrolled fires in manyflammable landscapes. However, epidemiologic evidence of the human health impacts of landscape fire smokeemissions is shaping fire management practice through increasingly stringent environmental regulation andpublic health policy. An unresolved question, critical for sustainable fire management, concerns thecomparative human health effects of smoke from wild and prescribed fires. Here we review current knowledgeof the health effects of landscape fire emissions and consider the similarities and differences in smoke fromwild and prescribed fires with respect to the typical combustion conditions and fuel properties, the qualityand magnitude of air pollution emissions, and the potential for dispersion to large populations. We furtherexamine the interactions between these considerations, and how they may shape the longer term smokeregimes to which populations are exposed. We identify numerous knowledge gaps and propose a conceptualframework that describes pathways to better understanding of the health trade-offs of prescribed and wildfiresmoke regimes.
Publication DetailsWilliamson, G. J., Bowman, D. M. J. S., Price, O. F., Henderson, S. B. & Johnston, F. H. (2016). Atransdisciplinary approach to understanding the health effects of wildfire and prescribed fire smoke regimes.Environmental Research Letters, 11 (12), 125009-1-125009-11.
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A transdisciplinary approach to understanding the health effects of wildfire and prescribed fire
smoke regimes
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2016 Environ. Res. Lett. 11 125009
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Environ. Res. Lett. 11 (2016) 125009 doi:10.1088/1748-9326/11/12/125009
LETTER
A transdisciplinary approach to understanding the health effects ofwildfire and prescribed fire smoke regimes
GJWilliamson1, DM J SBowman1, O FPrice2, S BHenderson3 and FH Johnston4,5
1 School of Biological Sciences, University of Tasmania, Hobart, Tasmania, Australia2 School of Biological Sciences, University ofWollongong,Wollongong, New SouthWales, Australia3 British ColumbiaCentre forDisease Control, Vancouver, BritishColumbia, Canada4 Menzies Research Institute, University of Tasmania,Hobart, Tasmania, Australia5 Author towhomany correspondence should be addressed.
E-mail: [email protected]
Keywords: smoke, prescribed fire, wildfire, health, review,management
AbstractPrescribed burning is used to reduce the occurrence, extent and severity of uncontrolled fires inmanyflammable landscapes. However, epidemiologic evidence of the human health impacts of landscapefire smoke emissions is shaping firemanagement practice through increasingly stringent environ-mental regulation and public health policy. An unresolved question, critical for sustainablefiremanagement, concerns the comparative human health effects of smoke fromwild and prescribedfires. Here we review current knowledge of the health effects of landscape fire emissions and considerthe similarities and differences in smoke fromwild and prescribed fires with respect to the typicalcombustion conditions and fuel properties, the quality andmagnitude of air pollution emissions, andthe potential for dispersion to large populations.We further examine the interactions between theseconsiderations, and how theymay shape the longer term smoke regimes towhich populations areexposed.We identify numerous knowledge gaps and propose a conceptual framework that describespathways to better understanding of the health trade-offs of prescribed andwildfire smoke regimes.
Introduction
Landscape fire smoke is a complex and dynamic mixof energy, water vapour, gases, and aerosols. Gaseousemissions affect climate forcing and biogeochemicalcycling, while aerosols affect rainfall distribution andwarming of the troposphere (Langmann et al 2009)and transport of plant nutrients. The public healthimpacts of air pollution, including landscape firesmoke, have become more clearly characterised overrecent decades (Reid et al 2016a, 2016b). Globally, anestimated three million deaths each year are attribu-table to outdoor air pollution (Lim et al 2013), while anestimated 340 000 annual deaths are attributable tosmoke from landscape fires (Johnston et al 2012). Evenwhen fires do not cause loss of infrastructure or directhuman injury, large human populations can beexposed to smoke pollution causing measurableincreases in mortality and morbidity (Hendersonet al 2011, Faustini et al 2015, Adetona et al 2016), such
that including the health impacts of smoke changesthe overall economic burden of wildfire events(Johnston andBowman 2014).
Fire is an inevitable feature of many environmentson Earth, yet humans are able tomanipulate landscapefire activity for a diversity of reasons (Bowmanet al 2011). A key technique is intentionally burninglandscapes to reduce fuel loads and hence the occur-rence, extent, and severity of uncontrolled wildfires(Fernandes and Botelho 2003). When appropriatelyplanned, escape of prescribed fires from intendedboundaries occurs in less than 1%of cases (Dether andBlack 2006), but when escapes occur they can result insignificant damage to homes and infrastructure(Smith 2012). In many jurisdictions, smoke manage-ment is an important constraint on prescribed burn-ing (Sneeuwjagt et al 2013) leading to an unresolvedpolicy debate about human health trade-offs betweensmoke from wildfire and prescribed fires. This pro-blem involves numerous disciplines including
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epidemiology, meteorology, atmospheric chemistry,fire ecology and management, but few researchers orpractitioners have such transdisciplinary expertise.Our objective is to provide a succinct review of thiscomplex problem and to propose a conceptual trans-disciplinary framework that can be used to guide fur-ther research.
Smoke impacts on humanhealth
The health impacts of landscape fire smoke are drivenby: (1) chemical composition and concentrations ofpollutants in the smoke plume; (2) the intensity andduration of the smoke exposure during an event; (3)the extent to which individuals can protect themselvesfrom the exposure and (4) the number of individualswho are exposed and their underlying health status.
The epidemiologic literature has focussed on con-centrations of particulate matter less than 2.5 micronsin diameter (PM2.5), which is routinely measured andhas been widely studied (Pope and Dockery 2006).Exposure to PM2.5 from many different sources has arange of impacts on human physiology, including:promotion of inflammation and blood coagulation;impairment of the respiratory, cardiovascular, andautonomic nervous systems; and increased risk ofgenetic mutations (Brook et al 2004, Barregardet al 2006, Berhane et al 2011, Danielsen et al 2011).Although the composition of PM2.5 can vary widely,there is insufficient evidence to quantify the relativeinfluence different chemical compositions on healthoutcomes at this time (Levy et al 2012). In a healthyperson, short term physiological changes in responseto PM2.5 are unlikely to be of clinical importance, yetthey can pose significant risk to unhealthy people. Forinstance, increased concentrations of PM2.5 may pre-cipitate heart attack or stroke in a person who alreadyhas cardiovascular disease, potentially leading to death(Brook et al 2004). Likewise, smoke exposure mightcause minor irritation of the eyes or throat in healthypeople, but could precipitate severe breathing diffi-culty in a person with asthma or other respiratory dis-ease (Johnston et al 2006). Positive associationsbetween forest fire smoke and mortality have beendocumented in a range of settings including Europe(Faustini et al 2015), Russia (Shaposhnikov et al 2014),south-eastern Australia (Johnston et al 2011a, 2011b)and Malaysia (Sastry 2002). The population healthimpacts of PM2.5 are observed across all PM2.5 con-centrations with no safe threshold, which highlightsthe potential impacts of prescribed fires, even thoughthey produce comparatively less smoke thanwildfires.
Although serious health outcomes are relativelyrare, the absolute number of people who suffer seriousimpacts from smoke events can be substantial whenlarge populations are exposed. The health impacts ofair pollution are tied to the prevalence of risk factors inthe population, such as cardiovascular and lung
diseases, diabetes, older or younger age, and lowersocioeconomic backgrounds (Eze et al 2015, Popeet al 2011). The same is likely true for fire smoke,although there has been less research on the topic(Reid et al 2016a, 2016b). Smoke exposure is known todisproportionately affect people with lung diseases(Henderson and Johnston 2012) and the evidenceconcerning impacts on heart diseases is emerging(Rappold et al 2012, Haikerwal et al 2015a, 2015b). Afew studies have also demonstrated adverse impactson infants and unborn babies (Jayachandran 2009,Holstius et al 2012), and on people with lower socio-economic status (Reid et al 2016a, 2016b Environ-mental Research, Rappold et al 2012). Higher adversehealth outcomes from smoke exposure have also beendocumented for Indigenous Australians who haveworse population health outcomes compared withnon-Indigenous people (Johnston et al 2007, Haniganet al 2008).
Some of the adverse health effects of smoke can bemitigated through preventative medication (Bhogalet al 2006). By definition, preventive medication mustbe taken in advance to reduce the likelihood of dete-rioration in symptoms (National Asthma CouncilAustralia 2015), and this requires advanced notice ofpossible smoke impacts. Similarly, short-term reduc-tion of personal exposure to smoke in homes can beachieved if doors and windows are closed before asmoke event. In an open house, indoor air quality willrapidly reflect outdoor conditions (Dix-Cooperet al 2014). There is evidence that creating clean airrefuges using mechanical air filtration substantiallyreduces wildfire smoke exposure (Barn et al 2008,2016). However, such devices have not been widelyadopted. Moving people to areas unaffected by smokeis logistically challenging and stressful for the affectedpopulations. The only evaluation of evacuation duringsevere smoke events concluded that it was protectivein only 30% of cases (Krstic and Henderson 2015).Specialised face-masks can be effective in occupationalsettings for personal protection, however there is noevidence these are helpful as a public health protectionmeasure forwildfire smoke episodes (Sbihi et al 2014).
Wild and prescribed fires generally result in differ-ent smoke exposures to human populations. Wildfiresare unpredictable and, in temperate forest ecosystems,can occur at a low frequency (decades) whereas pre-scribed burning is more predictable and can occur at agreater frequency. Thus wildfire smoke affects largeareas and potentially large populations, contrastedwith the potential for severe local impacts of pre-scribed fire smoke (Haikerwal et al 2015a, 2015b). Therelative health effects of these contrasting smoke expo-sures remain unknown. An additional research chal-lenge lies in understanding the contribution ofbackground air pollution from other sources, whichcomplicates resolving the relative effects of wildfireand prescribedfire smoke.
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Biomass combustion and smokeproduction
Differences infire intensity, area burnt, fuel availabilityand type, and duration of fires all affect smoke volume,composition and dispersion. Large wildfires tend tooccur during drought periods and in severe fireweather, driven by high temperatures, low relativehumidity, and strong winds (Meyn et al 2007). Thisresults in the combustion of larger fuels, with thepotential to spread to the canopies ofwoody vegetation(Wagner 1977). By contrast, prescribed fires aretypically lit duringmilder weather, which results in thecombustion offine surface fuels and limited damage toforest canopies (Agee and Skinner 2005). Complexphysiochemical processes of pyrolysis and combustioninvolving the breakdown of hydrocarbons drive quali-tative and quantitative differences between wild andprescribedfire smoke.
Pyrolysis involves heating fuel to enable the endo-thermic reactions that break up long chain hydro-carbons to produce solids and gases, and vaporise themoisture in the fuel (Sullivan and Ball 2012). Many ofthe gaseous compounds are strong greenhouse gases(Jain et al 2006) and can be toxic to humans (Deml-ing 2008). Combustion is a rapid exothermic oxida-tion of the products of pyrolysis that releases energy inthe formof heat and light. Idealised complete combus-tion is a process where all hydrocarbons in the originalfuel, both gaseous and solid, combine with oxygen torelease energy and form carbon dioxide (CO2) andwater vapour (H2O) (Rein 2013). In all landscape fires,combustion is incomplete, producing a smoke thatincludes gases (CO2, CO, H2O, NOx, NH4, SOx, CH4,phenols, etc) and aerosols (elemental, organic, andinorganic carbon compounds)(Akagi et al 2011).While many of these species are also harmful tohuman health, the population level impacts are pri-marily driven by the concentrations of aerosols mea-sured as PM2.5 (Reisen et al 2015). The combustionprocess also liberates small quantities of macro andmicro plant nutrients and trace elements, includingheavy metals. Constituent compounds in the smokecan undergo further chemical transformation in theatmosphere after emission, while aging can also alteraerosol size, composition, and concentration (Cubi-son et al 2011). In general, the concentration of PM2.5
is thought to scale with the concentrations of the co-occurring organic and inorganic compounds (Wardet al 1996, Andreae andMerlet 2001).
The enormous variability in smoke composition isdue to the substrate burned and factors that determinethe completeness of oxidation during combustion,including the fuel moisture content, temperature ofcombustion, and amount of oxygen available (Hobbset al 1996). Combustion is often divided into high-temperature flaming and low-temperature smoulder-ing types to differentiate the chemical processes andthe smoke emissions. Flaming is produced by the
combustion of gases, which is rapid and involves morecomplete consumption of the original fuel. Smoulder-ing is produced by the combustion of solids, which isslower and less complete. Flaming versus smoulderingcombustion is one of the most important determi-nants of potential public health impacts, becausesmouldering and incomplete combustion greatlyincreases the emissions, the suite of toxic co-pollu-tants, and the burn duration (Bertschi et al 2003,Janhäll et al 2010, Reisen et al 2015). Many factorsaffect the relative proportions of flaming and smoul-dering combustion in a landscape fire, including thetemperature of combustion (Einfeld et al 1991), thefuel moisture, mass and composition of the fuel (suchas grass, wood, or peat), and the stage of the fire (Sur-awski et al 2015). In a fuel bed with highmoisture con-tent, the heat released by flaming combustion is oftenused to vaporise water in nearby fuel particles. In a fuelbed with low moisture content, combustion is morerapid and complete due to the maintenance of highertemperatures, promoting the combustion of the vola-tile compounds and gases. These factors are shaped bythe current and antecedent meteorological conditions(Weise andWright 2014).
Weather conditions have major influences on firebehaviour and smoke production, and fire weather isincreasingly studied at a global scale (Field et al 2015,Jolly et al 2015). Relative humidity and rainfall drivelandscape fuel moisture, while wind speed drives oxy-gen delivery and energy transport, which dictate thespeed and completeness of combustion, as well as therate of fire spread (Rothermal 1983, Dowdy et al 2010).The spatial arrangement of the fuel array also influ-ences oxygen availability, the completeness of thecombustion process, and hence the composition ofemissions (Weise and Wright 2014). Densely packedfuels allow little oxygen penetration and slower, lesscomplete combustion. Larger fuels, such as branchesand logs, have lower surface-area-to-volume ratiosthat reduce oxygen penetration. These fuel types oftenundergo extended smouldering combustion ratherthan rapid flaming combustion. For all of the abovereasons the leading fire front often features more effi-cient flaming combustion, while smouldering com-bustion dominates theflanks (Surawski et al 2015).
Assigning emissions factors to strict prescribed orwildfire categories is complicated by the range of vari-ables driving smoke production. For example, pre-scribed fires may be carried out in moister fuels,leading to less efficient and greater smouldering com-bustion. They are also less likely to burn heavy fuels,such as logs, that may smoulder for a long time (Bert-schi et al 2003). Wildfires typically have a mix of flam-ing fires (at the head of the fire) and smouldering fires(on the flank of the fire). Improved physical models ofpyrolysis, fuel consumption and spread dynamics maybe required to accurately establish smoke constituentsunder different burning conditions and firebehaviours.
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Smoke transport
Smoke transport is shaped by many complex interac-tions between landscape fire and meteorological con-ditions, with the most critical determinant being theinjection height, at which horizontal transport of theplume begins. Smoke plumes with low injectionheights will disperse within themixing layer, the lowerlayer of the atmosphere in contact with the Earth’ssurface, while smoke plumes with high injectionheights may be carried aloft over long distances bywinds in the upper atmosphere (figure 1). There is abroadly linear association between fire intensity (totalinstantaneous energy release) and plume height (ValMartin et al 2009, Raffuse et al 2012, Petersonet al 2014), because the rate of biomass consumptiondrives the rate of heat release. In turn, the rate of heatrelease drives the plume buoyancy, such that intense,hotfires create a convection column andhigh injectionheights (Fromm et al 2006). Intense wildfires areassociated with higher injection heights than lowerintensity prescribed fires, which are assumed toproduce lower smoke plumes, as is the case withagricultural fires that have low fuel loads (Kaskaoutiset al 2014). The locality of impact from different firetypes can be expected to be correlated with injection
height, and therefore fire intensity, with lower inten-sity fires more likely to impact local communities andhigh intensity fires resulting in broader long-range butmore diffuse population impacts.
The atmospheric stability and mixing height (theheight above ground in which turbulence produceswell-mixed air) also determines how well smoke canbe dispersed (figure 1). A stable atmosphere occurswhen air temperatures decrease slowly with height,whereas an unstable atmosphere occurs when tem-peratures decrease rapidly with height (Fergu-son 2001). For example, Boer et al (2009) foundincreased particulate pollution in cities surrounded byprescribed fires set under stable, low wind-speed con-ditions. Unstable atmospheric conditions can con-tribute to extremely intense and uncontrollable fires(Trentman et al 2006, Cruz et al 2012, McRaeet al 2015) and convection columns that can penetratepast the mixing layer, even reaching into the strato-sphere. This smoke often has minimal local impactsrelative to the size of the fire, but the aerosols in theupper atmosphere have a significant climate impact(Westphal and Toon 1991), and they can be trans-ported around the globe to have impacts in other areas(Sapkota et al 2005).
Figure 1.Examples of smoke dispersion under a variety of atmospheric conditions and fire intensities: (a) a low intensity fire in apronounced inversion or stable atmosphere produces smoke that is restricted to bottomof themixing layer; (b) a low intensity fire in awell-mixed atmosphere produces smoke that is transported regionally below themixing layer; (c) amoderately intense fire in awell-mixed atmosphere produces smoke that penetrate through themixing layer enabling long distance (100 kms) transport in the uppertroposphere; and (d) a high intensityfire in an unstable atmosphere produces smoke that penetrate the stratosphere and disperses at aglobal scale.
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The ability for the atmosphere to disperse smokecan be captured by the ventilation index (VI, Goodricket al 2013), whichmultiplies themixing height and themean wind speed. This index can be used to plan opti-mum conditions for prescribed fire to ensure smoketransport away from local communities, and is appliedin this capacity in British Columbia. High VI valuesindicate a high mixing height and wind speed, withgood smoke dispersion conditions. Low VI valuesindicate a low mixing height and still air, often result-ing in temperature inversions where pollution is trap-ped in a cold layer of air near the surface. Smokeimpacts are often highest during stable atmosphericconditions and temperature inversions that formunder meteorological conditions suited to prescribedburning (Price et al 2016). The atmospheric dispersionindex (ADI, Lavdas 1986, Goodrick et al 2013) buildson the ventilation index by adding a measure of atmo-spheric stability in predicting smoke dispersion cap-ability, and variants on this index is used in severaljurisdictions in the United States to inform plannedburn planning. Evaluation of these simple dispersionindices as an alternative to computationally intensivesmoke modelling is an important avenue for futureresearch.
Health and prescribed andwildfire ‘smokeregimes’
We suggest that smoke emissions from wild andprescribed fires can be conceptualised as a smokeregime in the same way that fire ecologists integratethe effects of recurrent fires under the rubric of the fireregime. Understanding the totality of the health effectsof a smoke regime from prescribed and wildfiresrequires considering numerous trade-offs. Theincreased fraction of fuel burnt in wildfires producesmore smoke emissions. Williamson et al (2013) foundthe mean horizontal footprint of wildfire plumes to besix times greater than those for prescribed fires insouth-eastern Australia. However, the higher intensityof wildfires means the greater likelihood of plumesreaching the upper atmosphere, where horizontaltransport can carry the smoke away from the localarea. Prescribed fires can be planned, to some extent,around optimal atmospheric conditions for smoketransport, but the lower intensity of the fire can resultin lower atmospheric injection heights and greaterlocal impacts on air quality. In particular, prescribedburns must avoid hot and windy conditions in favourof cool, still days to minimise the risk of fires escapingplanned boundaries. This inevitably means that pre-scribed fires often coincide with overnight temper-ature inversions that trap smoke in valleys wherepeople often live.
Prescribed burnsmay cause a negative feedback onsubsequent wildfire area and intensity, but the natureof this feedback can only be quantified over the long
term, via the influence of a prescribed burning pro-gram on the fire regime of an area. Empirical andsimulation studies have shown that prescribed burn-ing reduces the area of wildfire in the forests of south-ern Australia by a ratio of approximately one third,meaning each one-hectare reduction in wildfire arerequires a three-hectare area of treatment (Boeret al 2009, Price and Bradstock 2011, Bradstocket al 2012b). This ratio has been termed ‘leverage’(Loehle 2004, Price et al 2015). In non-forest regionswith lower fuel loads and less frequent wildfire, theleverage is even lower (Price et al 2012a, Priceet al 2015). Only in regions with particularly high firefrequency, such as savannas, can a 1:1 ratio beachieved (Vilen and Fernandes 2011, Priceet al 2012b). The implication is that prescribed burn-ing programs will increase the overall area burnt inmost regions. The inefficiency of prescribed fires atreducing wildfire area is because fuels recover quicklyand wildfires are rare, such that most fuel-reducedpatches are not encountered by a wildfire. If a wildfiredoes encounter a treated patch the intensity isreduced, which implies lower fuel consumption andsmoke emission but the effects have never been quan-tified with respect to intensity, fuel consumption orsmoke. Instead, studies have focussed on the reduc-tion of fire severity, a measure of crown scorch(Keely 2009), which can be mapped using post-fireremote sensing. These studies have demonstrated thatrecent prescribed burning reduces damage to the for-est crown, but the effect decreases as the time-since-fire increases and as the fire weather becomes moresevere (Bradstock et al 2010, Price and Bradstock 2012,Tolhurst and McCarthy 2016). To quantify the fulleffect of a prescribed burning program on smoke pol-lution requires the integration of the leverage effectand the reduction in intensity effect. Bradstock et al(2012a) explored this integration in the context of pre-dicting greenhouse gas emissions, concluding thatprescribed burning programs were unlikely to reduceemissions, while acknowledging that a definitiveanswer depends on gathering empirical evidence onfuel consumption by prescribed andwildfire.
Given the mechanisms of feedback between pre-scribed and wildfire, community smoke exposure canonly be compared by considering the smoke regimerather than emissions from individual fires, in otherwords, smoke frommore frequent and less severe firesversus smoke from less frequent more severe fires. Forexample, Schweizer and Cisneros (2016) argue thatsmoke regimes in the USA would be less harmful topublic health with a policy of regular prescribed burn-ing than with a policy of total fire suppression. Thecomparative population health impacts of smokeregimes will be driven mostly by the number and sus-ceptibility of people affected by smoke from eachregime. Smaller fires usually have more local impactswhile larger fires have greater capacity for long dis-tance transport. Although smoke generation and
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population exposure might be reduced by smallerfires, the public health costs may be borne by popula-tions that are repeatedly exposed to smoke from a localregime of prescribed fire. This may be further compli-cated by climate change, which is reducing thewindowof opportunity for prescribed burning each year andleading tomore fires being set when the conditions arefavourable. This compression can result in pollutionevents as severe as those associated with larger wild-fires, exemplified by the conditions in Sydney duringMay 2016 (figure 2).
Modelling population exposure to smoke
Modelling smoke production and transport is criticalfor predicting and modelling smoke exposure fromwild and prescribed fires. This is challenging becauseof the need to parameterise fuel type and mass, rate ofand type of consumption, and energy release andatmospheric conditions (Heilman et al 2014).
The direct measurement of smoke emissions isconstrained by the availability air monitoring stations,and a dense network is required for tracking andunderstanding dispersion. Routine monitoring isoften biased towards large urban or industrial centres,with a focus on mobile and industrial sources for reg-ulatory purposes (Johnston et al 2010). Increasingly,however, smoke monitoring networks based on largenumbers of inexpensive, spatially dispersed, real timeinstruments are being deployed. Such networkshelp to improve smoke dispersion models and toquantify community impacts more meaningfully.Examples include the Florida Air Quality System(FLAQS, www.dep.state.fl.us/Air/air_quality/airdata.htm) and the Base Line Air Network of EPA Tasma-nia (BLANkET, http://epa.tas.gov.au/epa/real-time-air-quality-data-for-tasmania). These networks canalso provide real-time data on smoke impacts to thepublic. An alternative to ground-based particle moni-tors are remote sensing platforms on satellites, whichcan measure atmospheric aerosol concentration overlarge geographic areas. Data products such as the aero-sol optical depth (AOD) or aerosol optical thickness(AOT)measure total atmospheric aerosol by compar-ing the scattering of light in a given pixel with its spec-tral signature under a low aerosol load. While AODmeasures particles throughout the atmospheric col-umn, there is often strong correlation with particulateconcentrations at ground level (van Donkelaaret al 2015). These measurements are available in areasoutside the ground-based monitoring network, allow-ing quantification of long-distance smoke transport.The polar-orbiting MODIS, AVHRR and VIIRSinstruments all provide AOD measurements at vary-ing resolutions and overpass frequencies, while geos-tationary satellites, including GOES satellites over the
Americas and the Himawari-8 satellite over east Asia,also provide continuous AOD coverage. Other instru-ments use LiDAR (e.g. CALIOP) or stereoscopic ima-gery (e.g. MISR) to provide three-dimensionalimagery of smoke plumes.
Goodrick et al (2013) provide an excellent reviewof the range of empirical and physical models availablefor smoke dispersal. Empirical models use statisticalrelationships to describe observed smoke concentra-tions with respect to a range of predictor variablesassociated with smoke emissions including land use,meteorology, satellite location of fire and estimates ofintensity. For example, Yao and Henderson (2014)developed a system for British Columbia, Canada thatincorporates MODIS AOD, atmospheric ventingindex, measured PM2.5, and MODIS fire radiativepower measurements to estimate smoke concentra-tions across the province. There was a correlationcoefficient of 0.84 between model estimates andobserved PM2.5 concentrations in training cells onhigh-smoke concentration days. These models aresimple to parameterise and require little computa-tional power, but are often only locally applicable andcan perform poorly in conditions outside the trainingenvironment. Physical models range in complexityfrom simple box models, such as the atmospheric dis-persion index (ADI), through to grid models with alattice of cells with pollutant concentrations andmeteorological variables (Goodrick et al 2013). Inbetween, there are Gaussian plume models, whichincorporate wind impacts on plume dispersion, puffmodels, which disperse independent puffs of smokewith defined pollutant concentrations, and particlemodels, which simulate the movement of individualparticles through the atmosphere. Each approach hasparticular strengths, weaknesses, and applications.
The most elaborate and potentially useful class ofmodels are gridded numerical chemical transportmodels, such as the Australian Air Quality ForecastingSystem (AAQFS, Cope et al 2004). These systemsincorporate ameteorological model to simulate atmo-spheric temperature profiles and wind, emissionssources parameterised with emissions factors for avariety of chemical species, and chemical models ableto account for changes in chemistry as the smoke ages.Increases in computing power and the greater avail-ability of data sources for validation and modelimprovement mean that physical models have thepotential to improve our prediction of smoke impactsfrom landscape fire over the coming years. A fusion ofmultiple approaches is likely to emerge, to develop sys-tems for accurate prediction and estimation of smokeemissions. Such models will not only be pivotal inresolving the trade-offs of wildfire and prescribed fire,but also for providing advanced public health warn-ings (Yuchi et al 2016).
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Figure 2.An example from the Sydney basin, which covers an area of∼25 000 km2 and has a population of approximately 5millionpeople. InMay 2016 prescibed fires were set under low danger conditions to reducefire hazard. The unintended consequence of thisinterventionwas a smoke pollution event equally as severe as those caused by extremewildfires in a validated record from1995 to 2014(Johnston et al 2011a, 2011b,Hanigan et al 2016). Panels are as follows: (a) an image of the pollution obscuring the iconic SydneyHarbour Bridge; (b)MODIS imagery from theAqua satellite onMay 22 2016 showing the extent of the smoke pollution from theprescribed fires to thewest of the Sydney Basin; (c) the locations of prescribe fires set duringMay 2016; (d) the daily average PM2.5
concentrations inMay 2016 showing exceedences of the the 25μgm−3 Australian air quality standard (NEPM—NationalEnvironment ProtectionMeasure), and long termmean concentration; (e) the daily forestfire danger index (FFDI) inMay 2016,showing low risk due tomildweather conditions—values never exceed 25, the ‘very high’fire danger category; (f) the daily ventingindex forMay 2016 showing periods of decreased venting during periods of increased burning (low values), which entrapped thesmoke; and (g) the PM2.5 during theMay 2016 event comparedwith smoke from some of themost intense wildfire episodes in theprevious 20 years, as described in a validated smoke event database for the region (Johnston et al 2011a, Hanigan et al 2016). Previousepidemiologic studies in the Sydney Basin have shown that smoke events of similarmagnitude are associatedwith additional deaths,admissions to hospital, and presentations to hospital emergency departments (Johnston et al 2011a, 2011b,Martin et al 2013, Johnstonet al 2014). Such impacts need to beweighed against the wider impacts and risks of avoiding prescribed burns altogether, ormodifyingtheir implementation to reduce the potential for severe smoke events.
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Framework for understanding smokehealth impacts of wild and prescribedfires
A range of research challenges in the fields of fire
ecology, epidemiology, and atmospheric sciences
must be resolved before the relative human health
costs of wild and prescribe fire smoke regimes can be
accurately estimated. A framework to understand the
interrelations among the many complex factors is
presented here (figure 3). To understand the full
impact of prescribed burning programs on human
health we must consider the risk factors for each fire
(the event), the feedbacks between prescribed and
wildfire over time (the fire and smoke regimes), howthis translates into the interaction between smoke and
populations (the exposure), and, ultimately the effects
of the exposure on the population as a function of its
size, vulnerability and preparedness (health impacts).This framework will be useful for developing predic-tive models of smoke exposure, because understand-ing exposure is essential for quantifying the healthcosts of both wild and prescribed fire smoke regimes.Predictive models are also crucial to enable firemanagers to reduce smoke exposures and providewarnings to susceptible people.
Conclusion
We have provided a transdisciplinary review of thehealth impacts of smoke from wild and prescribedfires. This problem demands understanding recentadvances in air pollution epidemiology generally, andthe specific effects of landscape fire smoke. Thecomposition of landscape fire smoke is extraordinarily
Figure 3. Framework to understand the causes and uncertainties of landscape fire effects on human health. The framework is brokendown into events, regimes, exposure, and impacts. Individual fire events have features that can either dampen or amplify smokeproduction (green and red lines). Smoke andfire regimes are the collective consequences of numerous events. Long-term smokeexposure is shaped by the interaction between fire and smoke regimes. The health impacts of smoke exposure aremodulated by thedistribution and demographic profile of human populations. The aggregate population health impacts are determined by the complexinteraction of all the factors denoted in the diagram. There is no current assessment that considers all factors that influence the healthoutcomes of prescribed andwildfires. Such analysis is required to better understand the humanhealth trade-offs inherent is the use ofplanned fire tomanagewildfire.
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Environ. Res. Lett. 11 (2016) 125009
complex, and we use PM2.5 concentrations as anepidemiologic proxy for the mixture because we haveonly incipient understanding of its overall toxicology.Modelling of smoke particle emissions demandsquantification of the type of fuel and prevailingmeteorological conditions, both of which influencethe combustion conditions. The likely human healthimpacts of this smoke depend on the size of popula-tions affected, the concentration and duration ofexposure, and the effectiveness of any public healthinterventions. Prescribed fires can reduce the inci-dence of wildfires, trading off frequent short-termlocal-scale smoke pollution events for reductions inlonger time-scale broader population exposures. Thistrade-off must be incorporated into any evaluation ofthe health impacts for specific smoke regimes but it isimpossible to understand the respective healthimpacts of prescribed and wildfires with the availabledata. Instead, we propose a structured framework thatoutlines the necessary steps to move towards resolu-tion of this critical public health issue.
Acknowledgments
The content of this work was based on presentationsby FHJ, DMJSB, GJW, and SBH at the symposium‘Finding the Balance’ held at the University of BritishColumbia, April 2016. This public forum aboutbalancing wildfire, prescribed fire, forest health, andpublic health was sponsored by Health Canada, WallInstitute for Advanced Studies, UBC School of Popu-lation and Public Health, UBCFaculty of Forestry, andthe British Columbia Centre for Disease Control. Wethank the other attendees for their contributions tothis work via scholarly dialogue and debate. Ourresearch is also supported by an Australian ResearchCouncil LinkageGrant (LLP130100146).
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