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Wildland Fire Emission Factors in North America: Synthesis of Existing Data, Measurement Needs and Management Applications

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Wildland Fire Emission Factors in North America: Synthesis of Existing Data, Measurement Needs and Management Applications CSIRO PUBLISHING International Journal of Wildland Fire 2020, 29, 132–147 https://doi.org/10.1071/WF19066 Wildland fire emission factors in North America: synthesis of existing data, measurement needs and management applications Susan J. PrichardA,E, Susan M. O’NeillB, Paige EagleA, Anne G. AndreuA, Brian DryeA, Joel DubowyA, Shawn UrbanskiC and Tara M. StrandD AUniversity of Washington School of Environmental and Forest Sciences, Box 352100, Seattle, WA 98195-2100, USA. BPacific Wildland Fire Sciences Laboratory, US Forest Service Pacific Northwest Research Station, 400 N. 34th Street, Seattle, WA 98103, USA. CMissoula Fire Sciences Laboratory, US Forest Service Rocky Mountain Research Station, 5775 W Broadway Street, Missoula, MT 59808, USA. DScion Research, Te Papa Tipu Innovation Park, 49 Sala Street, Rotorua 3010, Private Bag 3020, Rotorua 3046, New Zealand. ECorresponding author. Email: [email protected] Abstract. Field and laboratory emission factors (EFs) of wildland fire emissions for 276 known air pollutants sampled across Canada and the US were compiled. An online database, the Smoke Emissions Repository Application (SERA), was created to enable analysis and summaries of existing EFs to be used in smoke management and emissions inventories. We evaluated how EFs of select pollutants (CO, CO2,CH4,NOx, total particulate matter (PM), PM2.5 and SO2) are influenced by combustion phase, burn type and fuel type. Of the 12 533 records in the database, over a third (n ¼ 5637) are represented by 23 air pollutants, most designated as US Environmental Protection Agency criteria air pollutants, greenhouse gases, hazardous air pollutants or known air toxins. Among all pollutants in the database, including the most common pollutants PM, CO, CO2 and CH4, records are unevenly distributed with a bias towards flaming combustion, prescribed burning and laboratory measurements. Across all EFs, records are most common for south-eastern and western conifer forests and western shrubland types. Based on identified data gaps, we offer recommendations for future studies, including targeting underrepresented air pollutants, smouldering combustion phases and improved source characterisation of wildland fire emissions. Additional keywords: air quality, greenhouse gas emissions, particulate matter, prescribed fire emissions, smoke management, wildfire emissions. Received 24 April 2019, accepted 26 October 2019, published online 7 January 2020 Introduction fire management, smoke modelling and emission inventories in Over the past decade, field and laboratory studies have made North America. substantial progress in characterising the chemical composition The Smoke Emissions Repository Application (SERA) pre- of wildland fire smoke and quantifying emission factors (EFs) in sented here is a searchable online database of existing EFs of 276 North America. EFs are defined as the mass of a gas or aerosol known air pollutants in standardised units (g kgÀ1) (https://depts. pollutant per dry weight unit mass of consumed fuel (Urbanski washington.edu/nwfire/sera, accessed 26 November 2019). 2014). Since the seminal review of Andreae and Merlet (2001), EF records include modified combustion efficiency (MCE, several reviews have summarised existing EFs by vegetation Yokelson et al. 1996), fuel type, study type (laboratory or field), type or region (Akagi et al. 2011; Yokelson et al. 2013; Urbanski measurement platform (ground, tower or air-based), geographic 2014), and studies were compiled into a summary dataset using location and source reference. The database was created to enable unpublished and published data from the 1960s to 2011 (Lincoln analysis and summaries of existing EFs, and creation of average et al. 2014). These developments, including several more recent EFs to be used in decision support tools for smoke management, studies, represent a large advancement in emissions character- including Consume (Prichard 2007), FOFEM (Reinhardt et al. isation and justify the creation of a master repository of EFs that 1997) and the BlueSky Smoke Modelling Framework (Larkin can be used to produce consistent values applicable for wildland et al. 2009), as well as future updates to national emissions Journal compilation Ó IAWF 2020 Open Access CC BY-NC-ND www.publish.csiro.au/journals/ijwf Wildland fire emission factors in North America Int. J. Wildland Fire 133 inventories (e.g. US EPA 2017). Prior to updates provided by generally associated with marginally combustible fuels such as Urbanski (2014), models that predict wildland fire emissions such coarse wood (i.e. stumps and downed logs .7.6 cm in diameter) as Consume, FOFEM and BlueSky used EFs published within the and duff that generally have incomplete combustion and smoulder 2001 Smoke Management Guide (Hardy et al. 2001) and sup- for extended periods (Ottmar 2014). ported a relatively small list of pollutants, including particulate Smoke management guides have traditionally summarised matter (PM), carbon monoxide (CO), carbon dioxide (CO2), EFs by major vegetation or fuel type. For example, the 2001 methane (CH4), non-methane organic compounds (NMOCs) Smoke Management Guide (Hardy et al. 2001) compiled and sulfur dioxide (SO2). SERA was designed to provide a pollutant EFs from existing studies of prescribed burns, includ- synthesis of existing EFs and summary values for emissions ing EFs summarised from broadcast burned slash of Douglas fir, modelling that can facilitate more rapid incorporation of EFs than juniper and ponderosa pine forests (Ward et al. 1989), broadcast was previously available through a relational database main- burned brush (Hardy et al. 1996) and wildfires (Hardy et al. tained by the US Forest Service Pacific Wildland Fire Sciences 1992). Hardy et al. (2001) also provided EFs by flaming, short- Laboratory (Seattle, WA). term smouldering and long-term residual smouldering phases of For many air pollutants, selecting the most appropriate EFs combustion. Summarising EFs by combustion phase is gener- to represent emissions from biomass burning needs to consider ally useful for fire managers to inform smoke reduction techni- the combustion of fuels that burn in smouldering combustion ques, such as finding optimal burn windows that maximise and low-heat pyrolysis phases (e.g. coarse wood and organic flaming combustion and minimise long-term smouldering soils). Modified combustion efficiency (MCE ¼ DCO2/ (MACTEC Federal Programs 2004), which can contribute to (DCO2 þ DCO)) is a measure of the relative fraction of flaming greater overall pollutant emissions of PM and CO and nighttime and smouldering combustion, and has been demonstrated to intrusions into communities (Miller et al. 2019). be highly correlated with EFs for pollutant emissions (such as Since the original smoke management guide was published in CO, CH4 and NMOCs) that are more concentrated in smoul- 2001, a large number of prescribed burn studies and a relatively dering combustion phases (Urbanski 2014). Emissions studies small number of wildfire emissions studies have been conducted. often include a measure of MCE to characterise source com- Urbanski (2014) synthesised fire-average EFs for major pollutant bustion phase (Yokelson et al. 1996; Urbanski 2014). For species by burn type (i.e. prescribed burns and wildfires) and example, Urbanski (2013) found that Rocky Mountain wildfire region and/or vegetation type. Fire-average flaming and smoul- emissions from prescribed fires in moderate to heavy coarse dering EFs and their estimated uncertainty were summarised wood had a much lower MCE than that observed in studies of based on six prescribed fire groupings in the US, including prescribed fires in the south-east, from where the majority of south-eastern (SE) conifer, south-western (SW) conifer and the EFs reported in the literature for NMOCs and PM2.5 north-western (NW) conifer forests, western shrublands and have been derived. More recently, Sekimoto et al. (2018) western grasslands, and two wildfire categories including W examined relationships between high- and low-temperature conifer wildfires and boreal wildfires. Additional residual pyrolysis and found that these two variables explained most of smouldering EFs were included for coarse wood, temperate forest the variability in non-methane organic gas emissions and organic soils and boreal forest organic soils (referred to hereafter outperformed MCE. The relationship between wildland fire as duff). More recently, sampled plumes from western US emissions and combustion highlights the need to develop wildfires suggest that the quantity and composition of fuels algorithms for extrapolating EFs to broadly representative burned in summer (May–October) wildfires may substantially fuel types and burning conditions (e.g. flaming v. smouldering increase estimates of pollutant emissions, including greenhouse and prescribed underburn v. crown fire). Because many gases (e.g. CO2 and CH4) and particulate matter (Liu et al. 2017). smoke management issues associated with wildland fire The objectives of this study were to develop a centralised emissions are from residual long-term smouldering sources, repository for evaluating and synthesising emissions factor characterising the fuels and EFs associated with these burning datasets for major fuel types in North America and to provide conditions is critical for fire management applications updates to best-estimate EFs for major pollutant species. (Urbanski 2013; Yokelson et al. 2013; Hu et al. 2018; Peterson Because wildland fire emissions
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