New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

Oleg M. Melnik; Stephen A. Paskaluk; Mark Y. Ackerman; Katharine O. Melnik; Dan K. Thompson; Sara S. McAllister; Mike D. Flannigan

doi:10.3390/fire5010001

Melnik, Oleg M.;Paskaluk, Stephen A.;Ackerman, Mark Y.;Melnik, Katharine O.;Thompson, Dan K.;McAllister, Sara S.;Flannigan, Mike D.

2021-12-23 00:00:00

fire Article New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel 1 , 2 , 3 4 5 Oleg M. Melnik * , Stephen A. Paskaluk , Mark Y. Ackerman , Katharine O. Melnik , 6 , 7 8 1 Dan K. Thompson , Sara S. McAllister and Mike D. Flannigan Department of Renewable Resources, University of Alberta, Edmonton, AB T6G 2H1, Canada; mike.ﬂannigan@ualberta.ca Fire Operations, Forest Management Division, Department of Environment and Natural Resources, Government of the Northwest Territories, Fort Smith, NT X0E 0P0, Canada Department of Human Ecology, University of Alberta, Edmonton, AB T6G 2N1, Canada; stephen.paskaluk@ualberta.ca Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada; ackerman@ualberta.ca School of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8140, New Zealand; kmelnik@ualberta.ca Northern Forestry Centre, Canadian Forest Service, Edmonton, AB T6H 3S5, Canada; daniel.thompson@canada.ca Great Lakes Forestry Centre, Canadian Forest Service, Sault Ste. Marie, ON P6A 2E5, Canada Fire Sciences Laboratory, Rocky Mountain Research Station, USDA Forest Service, Missoula, MT 59808, USA; sara.mcallister@usda.gov * Correspondence: melnik@ualberta.ca Abstract: Improving the accuracy of ﬁre behavior prediction requires better understanding of live fuel, the dominant component of tree crowns, which dictates the consumption and energy release of the crown ﬁre ﬂame-front. Live fuel ﬂammability is not well represented by existing evaluation methods. High-ﬂammability live fuel, e.g., in conifers, may maintain or increase the energy release Citation: Melnik, O.M.; Paskaluk, of the advancing crown ﬁre ﬂame-front, while low-ﬂammability live fuel, e.g., in boreal deciduous S.A.; Ackerman, M.Y.; Melnik, K.O.; stands, may reduce or eventually suppress ﬂame-front energy release. To better characterize these Thompson, D.K.; McAllister, S.S.; fuel–ﬂame-front interactions, we propose a method for quantifying ﬂammability as the fuel’s net Flannigan, M.D. New In-Flame effect on (contribution to) the frontal ﬂame energy release, in which the frontal ﬂame is simulated using a Flammability Testing Method Applied to Monitor Seasonal methane diffusion ﬂame. The fuel’s energy release contribution to the methane ﬂame was measured Changes in Live Fuel. Fire 2022, 5, 1. using oxygen consumption calorimetry as the difference in energy release between the methane ﬂame https://doi.org/10.3390/fire5010001 interacting with live fuel and the methane ﬂame alone. In-ﬂame testing resulted in fuel ignition and consumption comparable to those in wildﬁres. The energy release contribution of live fuel was Academic Editor: Alistair M. S. Smith signiﬁcantly lower than its energy content measured using standard methods, suggesting better Received: 13 November 2021 sensitivity of the proposed metric to water content- and oxygen deﬁciency-associated energy release Accepted: 20 December 2021 reductions within the combustion zone. Published: 23 December 2021 Publisher’s Note: MDPI stays neutral Keywords: oxygen consumption calorimetry; oxygen bomb calorimetry; heat of combustion; energy with regard to jurisdictional claims in release; live fuel ﬂammability; foliar moisture content; FMC; white spruce; picea glauca published maps and institutional afﬁl- iations. 1. Introduction The efﬁciency of wildland ﬁre management in protecting values at risk and address- Copyright: © 2021 by the authors. ing emerging climate change-related environmental challenges depends on the ability to Licensee MDPI, Basel, Switzerland. predict wildﬁre behavior, which is controlled by the ﬁre environment [1]. Increasing the This article is an open access article understanding of the fuel component of the ﬁre environment, in particular, the ﬂammability distributed under the terms and of live plant material available for combustion (i.e., live fuel) can improve the accuracy conditions of the Creative Commons of ﬁre behavior predictions [2,3]. As a dominant component of crown fuel consumption, Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ live fuel drives crown ﬁres, which are difﬁcult to predict and control, and which make 4.0/). up the largest part of the area burned in the North American boreal forest [4]. Ever since Fire 2022, 5, 1. https://doi.org/10.3390/ﬁre5010001 https://www.mdpi.com/journal/ﬁre Fire 2022, 5, 1 2 of 29 the development of the ﬁrst operational ﬁre models in the 1970s, it was thought that the consumption of live fuel by a ﬂame-front and the resulting effects on the wildﬁre behavior were minor compared to those of dead fuel. However, by analyzing the consumption data from Stocks [5] and considering only the ﬂaming front [6], it was shown that live fuel constituted at least 48–60% of the mass consumed in a crown ﬁre [7] or likely even more, because the data analyzed only accounted for green foliage and did not include the fresh branchwood also consumed in the ﬂame-front [8]. The ﬂammability and overall proportion of available live fuel and its effects on crown ﬁre behavior will likely also increase in the future with increased drought [9] and wildﬁre intensities [10]. The ﬂammability of live fuel has been measured via numerous metrics, including time- to-ignition (ignitibility), combustion rate (combustibility), duration (sustainability) [11], and completeness (consumability) [12]. None of the above metrics are considered in the Canadian Forest Fire Behavior Prediction (FBP) System; instead, foliar moisture content (FMC) is used. The actual use of FMC is largely limited to determining the initiation of crowning because FMC is used for predicting the rate of crown ﬁre spread only in the conifer plantation fuel type (C-6) where sufﬁcient data are available. FMC is seasonally adjusted for conifer bud burst phenology, but it does not account for drought-induced increases in live fuel ﬂammability and crown ﬁre behavior. Along with extreme weather, drought is a primary driver of the occurrence, intensity, and difﬁculty of suppression of wildﬁres [13]. Both drought-induced relative plant water content loss, as a measure of physiological drought [14,15], and the associated increase in ﬂammable volatiles [16] raise live fuel ﬂammability [17–20]. However, the seasonal pattern of FMC in the FBP model is static year-to-year and, therefore, is insensitive to the level of drought and the drought-induced changes in live fuel ﬂammability during a particular ﬁre season. While the level of drought is accounted for by using the Drought Code from the Fire Weather Index System, which represents water content in the organic forest ﬂoor soil layer 10–20 cm deep [21], for live vegetation it should be evaluated by using the water availability in the soil layer penetrated by roots—on average 2 m deep for boreal forest tree species [22]. In the American National Fire Danger Rating System (NFDRS), FMC is sensitive to drought and used for predicting the ﬂammability of herbaceous material and shrubs, but not tree species [23]. FMC only accounts for the water content and ﬂammability of foliage, while crown ﬁre also consumes fresh branchwood [8,24] that has different ﬂammability [25] due to differences in water content [26], chemical composition, and spatial structure. FMC only partially represents live fuel ﬂammability, while dry matter content, density, and chemical composition are equally important [19,20,27–30]. Therefore, FMC alone can only partially explain live fuel ﬂammability, as well as the initiation, type [31,32], and spread rate of crown ﬁres [33]. While the effect of live fuel moisture content or FMC on ﬁre rate of spread is considered to be underestimated [3], FMC has not shown a statistically signiﬁcant relationship with the rate of ﬁre spread in ﬁeld-scale experimental ﬁres [34,35]. Consider- ing these issues and given the complexities of chemical and physiological measurements across the multiple interacting drivers of ﬂammability such as moisture (e.g., FMC), den- sity, and chemical composition, a simple experimental method for monitoring live fuel ﬂammability directly is needed to provide more adequate input into ﬁre behavior and ﬂame propagation modelling. Flame propagation is a chain of events where already burning fuel elements preheat and ignite subsequent elements. The propagation rate can be calculated as the ratio of the distance to the next fuel element to its time-to-ignition [36]. However, time-to- ignition alone does not provide a complete characterization of fuel ﬂammability or ﬂame propagation. Greater energy release results in more available energy to ignite the next fuel element, a shorter time-to-ignition [12], and a potentially higher rate of spread. If the energy release is less than that required to ignite the next fuel element, the ﬁre will not spread. To represent the mass-energy transfer processes during ﬂame propagation, ﬂammability should consider the fuel’s capacity to release energy. Babrauskas et al. [37] Fire 2022, 5, 1 3 of 29 considered the heat (energy) release rate to be the most important variable in determining ﬁre hazard. The available energy release per unit area within the ﬂaming front (energy release component) is an important output of the NFDRS [38]. The energy release from burning fuel into the unburned fuel ahead (horizontal propagating ﬂux) has been linked with the rate of ﬁre spread, the preheat ignition energy, and the fuel bulk density in the heat balance equation [39]. This relationship is used for calculating the rate of spread in the Rothermel surface ﬁre spread model within the NFDRS [40], predicting the initiation of crowning [31], and modifying crown ﬁre rate of spread [33] within the FBP. A ﬁre-front’s energy release rate, or ﬁre intensity, directly affects ﬁreﬁghter safety [41], the probability of initial attack success [42], and the range of adequate strategies and tactics for wildﬁre control [32]. Fire intensity in Byram’s [43] formula is calculated as a product of the dry mass of fuel consumed per unit area in the active ﬂaming zone, the rate of ﬁre spread, and heat of combustion (H) as a measure of fuel ﬂammability. Heat of combustion has been traditionally measured using oxygen bomb calorimetry as the gross (“high”) heat of combustion (H , kJ g ). By testing oven-dry plant material gross in a pure oxygen environment (e.g., [25]), H overestimates potential energy release. gross To evaluate a more realistic “lower” heat of combustion, or “heat yield”, H requires gross adjustment for losses and reductions in energy release that occur within real ﬂame-fronts and are related to the signiﬁcant and variable water content of live plants [43]. For instance, the FMC of white spruce ranges from 75% to 480% [44,45] or even 500% (as measured in this study) of dry mass. The combustion of live fuel occurs simultaneously with the evaporation of water present in substantial quantities [46,47] because high internal leaf pressure during burning allows live plant tissue to retain water within the temperature range of 160 C to 220 C, which is substantially higher than the normal boiling point (100 C) of water [48]. Additionally, the high heating rates of a typical ﬁre often create temperature gradients within the fuel, with surfaces reaching ignition temperatures while water is still being evaporating from the much cooler internal regions [27]. High energy losses for fuel preheating as well as for evaporation of water of the reaction and water contained in the fuel [43] in turn result in a reduction in reaction temperature and energy release. When compared with rehydrated dead foliage of similar moisture content, live foliage reaches a lower temperature during preheating and drying within an incoming ﬂame (175 C versus 200 C), exhibits a noticeably slower temperature increase, and takes longer to ignite (10 s versus 5 s) [48]. Further reductions in energy release are caused by the dilution of the gaseous products of pyrolysis and oxygen by water vapor [43,47,49], the oxygen deﬁciency due to increased oxygen consumption [47,50], and the ﬂow dynamic alteration of interacting ﬂames [50] resulting in an incomplete combustion and a substantial release of unburned hydrocarbons from high-intensity ﬁres [43]. The FBP System does not take all these factors into account, and instead applies a heat of combustion of 18 kJ g [51] estimated as H with a single 5–10% deduction for energy lost via the evaporation gross of only water of the reaction but not water contained in the fuel [52]. This can lead to a substantial error in ﬁre intensity estimation. The effective heat of combustion (H , kJ g ) [18] measured using oxygen consump- eff tion calorimetry better accounts for reductions associated with oxygen deﬁciency and water content by testing fresh plant material in an open-air environment (instead of pure oxygen). It also produces an “effective” value that accounts for incomplete char oxida- tion, which is observed in real wildﬁres due to the short duration of ﬂaming combustion during ﬁre front passage. Within the 80–170% range of moisture content typical for live conifers, Babrauskas’ method produced values of H at 7–12 kJ g (fresh mass basis), or eff approximately 19 kJ g dry mass basis (at an average of 100% shoot water content) for live fuel [18], which is close to that measured as H or assumed by the FBP model at gross 18 kJ g . The method only partially represents real ﬁres because it utilizes radiative-only heating, while fuels in a wildﬁre setting are exposed to both radiative and convective heat transfer. Convective heating has been considered [31,53,54] and has been shown to be Fire 2022, 5, 1 4 of 29 the dominant energy transfer mechanism in many cases [55], especially in the mid-upper portion of the canopy [56]. Additionally, H , as measured by Babrauskas [18], is insensitive to additional reduc- eff tions in energy release resulting from the interaction of the live fuel ﬂame (reacting ﬂammable gases emitted by the recently ignited live fuel element) with the incoming frontal ﬂame (the combined ﬂame comprised of reacting ﬂammable gases emitted by the already burning fuel elements) (Figure 1, left) within the ﬂames interaction zone (FIZ). This interaction of the ﬂames results in the creation of an oxygen-deﬁcient gaseous mixture caused by the increased oxygen consumption and ﬂow dynamic alteration for the live fuel ﬂame. There- fore, the energy release of the live fuel ﬂame within the FIZ (Figure 1, left) is most likely lower than the energy release of the live fuel ﬂame alone, tested traditionally as H using eff oxygen consumption calorimetry, in which oxygen deﬁciency is nearly absent because the fuel is surrounded by air due to the use of radiant only heating (Figure 1, right). Moreover, the energy release of the incoming frontal ﬂame itself (Figure 1, left) in the FIZ may also be reduced—both by oxygen deﬁciency and by the high water content of the live fuel. These reductions are not accounted for by the existing techniques due to the complexity of the multiple factors involved such as fuel water content, dry matter content, the rates of heating, pyrolysis, and water evaporation, as well as the concentrations of oxygen, pyrolysates, and water vapor. Thus, the net change in the energy release of the incoming frontal ﬂame resulting from its interaction with the live fuel element burning within the ﬂame, or the fuel’s net contribution to the frontal ﬂame energy release, may be substantially smaller than H or H . gross eff Figure 1. A conceptual diagram of the combustion environment. Left: combustion of a live fuel element in a real wildﬁre where the live fuel ﬂame interacts with the incoming frontal ﬂame. The region where these ﬂames interact—the ﬂames interaction zone (FIZ)—includes energy release reductions that are unaccounted for by current methods. The vertical direction of ﬂame propagation on the diagram, from bottom to top instead of forward-upward as in real crown ﬁre ﬂame-fronts, represents the experimental setup and apparatus. Right: combustion of a live fuel element in traditional tests out of a frontal ﬂame where the live fuel ﬂame is surrounded by atmospheric air as performed, for example, when measuring effective heat of combustion using standard oxygen consumption calorimetry test setup, e.g., [57]. Considering these issues, the main objective of this study was to introduce a new experimental methodology, developed by Melnik et al. [58] and Paskaluk et al. [59], which utilizes in-ﬂame ﬂammability testing (1) to better represent ignition heat transfer within Fire 2022, 5, 1 5 of 29 wildﬁres and (2) to physically represent and account for the additional energy release reductions resulting from the interaction of ﬂames within the FIZ discussed above. Instead of separately estimating the energy release reductions that exist in real ﬂame-fronts and subtracting them from the gross heat of combustion to evaluate “heat yield” [43], the proposed methodology directly measures the heat yield added to the ﬂame-front by the fuel element as the fuel element’s energy release contribution to the incoming frontal ﬂame. 2. Materials and Methods 2.1. Fuel Element’s Energy Release Contribution to the Incoming Frontal Flame The incoming frontal ﬂame was simulated using a non-premixed methane diffusion ﬂame. Although methane is one of the combustible gases released by wildland fuels, methane was used in the tests primarily due to being a readily available laboratory gas with a well-known and consistent composition and heat of combustion. The known ﬂow rate of methane in the tests allows to calculate its energy release potential to verify HRR values measured with oxygen consumption calorimetry. Importantly, using a non- premixed diffusion methane ﬂame facilitates the creation of exposure conditions similar in temperature and oxygen concentration to those encountered in the diffusion rate-limited wildﬁre ﬂame with a temperature typically around 1000 C. The ﬂame was produced by a 10 10 cm open burner that provided approximately 40 kW m total heat ﬂux measured at the bottom-center of the sample holder with radiative heating comprising about 35% of this value, which is higher than the 15–20% radiative heat fraction reported in the literature for smaller methane ﬂames [60,61]. The fuel element was represented in the tests by a live fuel sample. Therefore, the fuel element’s contribution to the energy release of the incoming frontal ﬂame De was measured using oxygen consumption calorimetry [57] as the net difference in energy release between the methane ﬂame interacting with the live fuel sample (Figure 2a) and the methane ﬂame alone (Figure 2b), as in Equation (1) below. De = Q Q (1) (incoming ﬂame + fuel) (incoming ﬂame alone) where: De is the fuel element’s/sample’s contribution to the energy release of the incoming ﬂame (kJ), Q is the total energy release of the methane ﬂame interacting (incoming ﬂame + fuel ) with the live fuel sample burning within it (kJ), and Q is the total energy (incoming ﬂame alone) release from the methane ﬂame alone (kJ). In a wildﬁre, live fuel interacts with the passing ﬂame-front and contributes to its energy release, propagation, and behavior only during the time in which the ﬂame-front is present and the fuel is exposed to it. This ﬂame-front exposure time includes fuel pre- heating/ignition time and ﬂame-front residence (ﬂaming combustion) time. By analyzing existing literature and ﬁre-front video recordings [56,62,63], the ﬂame-front exposure time is estimated to be on average 61 s, including 29 s of fuel preheating/ignition time and 32 s of ﬂame-front residence time (Table 1). The relevance of this analysis for the particular fuel type used in the present study (conifers) was conﬁrmed by our preliminary experimental results [59] showing that burning fuel contributes signiﬁcantly to the heat release rate (HRR) of the incoming methane ﬂame for only a short period (55–65 s). Therefore, to adequately represent the fuel element’s contribution to the energy release of the passing ﬂame-front, the duration of 60 s was chosen for the evaluation of the total energy release of the incoming methane ﬂame with the fuel sample burning within the ﬂame (Equation (1)) by integrat- ing its HRR measured with oxygen consumption calorimetry [57]. This 60-s integration window ensured that fuel ignition, ﬂaming combustion, and, partially, char oxidation phases were included in the evaluation. The total energy release of the methane ﬂame alone passing an empty sample holder was determined by integrating its measured HRR over the same time period. Methane-only tests were conducted both at the beginning and at the end of each day of testing, and these two results were averaged to provide a reference HRR over the 60 s period. This measurement was compared to the theoretical value calculated from the measured methane ﬂow rate to conﬁrm the result. Fire 2022, 5, 1 6 of 29 Fire 2022, 4, x FOR PEER REVIEW 6 of 31 (a) (b) Figure 2. The proposed test set-up for measuring the energy release contribution of the sample to Figure 2. The proposed test set-up for measuring the energy release contribution of the sample to the incoming flame using an oxygen consumption cone calorimeter. The energy release of (a) the the incoming ﬂame using an oxygen consumption cone calorimeter. The energy release of (a) the incoming methane flame interacting with live fuel was greater (even when only judged visually by incoming methane ﬂame interacting with live fuel was greater (even when only judged visually the volume of flames), compared with (b) the energy release of the methane flame alone. This dif- by the volume of ﬂames), compared with (b) the energy release of the methane ﬂame alone. This ference in energy release represents the fuel element’s/sample’s contribution to the energy release difference in energy release represents the fuel element’s/sample’s contribution to the energy release of the incoming methane flame ∆e (kJ) in Equation (1). From bottom to top in (a): load cell, a me- of thane burner, incoming methane fl the incoming methane ﬂame De ame, wir (kJ) in Equation e-mesh sample (1). Fr holder om bottom containing a live fuel sample to top in (a): load cell, a burning within incoming methane flame, and outgoing flame (methane flame mixed with the flame methane burner, incoming methane ﬂame, wire-mesh sample holder containing a live fuel sample of the burning live fuel sample). Vertical (upward) direction of flame propagation represented by burning within incoming methane ﬂame, and outgoing ﬂame (methane ﬂame mixed with the ﬂame the experimental setup of the apparatus is slightly different from that occurring in real crown fire of the burning live fuel sample). Vertical (upward) direction of ﬂame propagation represented by flame-fronts, where it is forward-upward. the experimental setup of the apparatus is slightly different from that occurring in real crown ﬁre ﬂame-fronts, where it is forward-upward. In a wildfire, live fuel interacts with the passing flame-front and contributes to its energy release, propagation, and behavior only during the time in which the flame-front Table 1. Flame-front exposure time documented for high-intensity wildland crown ﬁre-fronts during is present and the fuel is exposed to it. This flame-front exposure time includes fuel preheat- International ing/ignition t Cr ime an own Fir d efl Modeling ame-front Experiment residence ( in fthe lamin Northwest g combust Territories, ion) time. B Canada. y analyzing ex- isting literature and fire-front video recordings [56,62,63], the flame-front exposure time Preheating Start Flame-Front is estimated to be on average 61 s, including 29 s of fuel preheating/ignition time and 32 s Preheating/Ignition Flame-Front Recording ID Timestamp Residence Time Source of flame-front residenc Delay Te ime time (Tab (s) le 1). The relevance of t Exposure his an Time alysi (s) s for the particular (h:min:s or s) (s) fuel type used in the present study (conifers) was confirmed by our preliminary experi- Plot 3 Part II 03:10:40 19 53 72 [62] (video) mental results [59] showing that burning fuel contributes significantly to the heat release Video 3 04:32:47 23 35 58 [63] (video) rate (HRR) of the incoming methane flame for only a short period (55–65 s). Therefore, to Video 4 04:32:58 18 29 47 [63] (video) adequately represent the fuel element’s contribution to the energy release of the passing Video 5 04:32:53 21 29 50 [63] (video) flame-front, the duration of 60 s was chosen for the evaluation of the total energy release Video 6 04:32:51 13 38 51 [63] (video) Video 7 04:32:36 24 38 62 [63] (video) of the incoming methane flame with the fuel sample burning within the flame (Equation (1)) by integrating its HRR measured with oxygen consumption calorimetry [57]. This 60- s integration window ensured that fuel ignition, flaming combustion, and, partially, char Fire 2022, 5, 1 7 of 29 Table 1. Cont. Preheating Start Flame-Front Preheating/Ignition Flame-Front Recording ID Timestamp Residence Time Source Delay Time (s) Exposure Time (s) (h:min:s or s) (s) Sensor height 13.8 m 530 35 30 65 [56] Sensor height 12.3 m 520 50 25 75 [56] Sensor height 9.2 m 535 35 20 55 [56] Sensor height 6.2 m 540 35 30 65 [56] Sensor height 3.1 m 535 50 25 75 [56] Average 29 32 61 HRR calculations were performed as speciﬁed for oxygen consumption cone calorime- ter tests in [57], based on O and CO measurements using a Fire Testing Technology (East 2 2 Grinstead, West Sussex, UK) bench scale mass loss calorimeter instrumented with a Model 300 analyzer from California Analytical Instruments (Orange, CA, USA) with IR CO and CO detectors. The exhaust was sampled at 0.017 L s through the paramagnetic oxygen analyzer. Data were collected at 10 Hz per channel with a USB-2416 data acquisition device (Measurement Computing Corporation, Norton, MA, USA) and a PC using DASYLab 11 data acquisition software (Hoskin Scientiﬁc, Burnaby, BC, Canada). The mass loss of the fuel samples during the tests was measured using a 600 g load cell with a custom-made lightweight methane burner mounted on top. Methane ﬂow to the burner at 0.15 L s during testing was controlled with a rotameter to provide a diffusion ﬂame with a nominal heat release rate of 5.5 kW. During each test, after a wire-mesh sample holder containing a pre-weighed sample was placed on the methane burner, data acquisition was initiated, and the methane ﬂow was started and ignited using a gas lighter. Since data acquisition contin- ued for four minutes, the approximately 15 s delay between the start of data acquisition, ignition, and the gas analyzer sampling resulted in 225 s of test data. The measurement uncertainty for standard oxygen consumption calorimetry in an open system, where the products of combustion are diluted with ambient air, includes the uncertainty associated with oxygen concentration measurements (oxygen analyzer accuracy), the assumed heat of combustion (calorimetric coefﬁcient E), measurements of the mass ﬂow rate of the ex- haust products, and the assumed combustion expansion factor, which depends on oxygen depletion [64]. The total range of uncertainties in the measured heat release rate could be as high as 20% primarily due to analyzer uncertainty at low oxygen depletion levels, which decreases with moderate oxygen depletion and increases again from 12% to 15% with growth in oxygen depletion, ambient air dilution, and higher contribution of the assumed expansion factor [64]. The uncertainty of CO and soot corrections is lower when the composition of the fuel is known [64] and is expected to be 5% or lower for conven- tional organic fuels when the 13.1 kJ/g constant, widely accepted for oxygen-consumption calorimetry, is used [65]. Instead of focusing on measuring the heat release rate directly, this study rated the heat release rate of the combined ﬂame (methane plus forest fuels) relative to a methane ﬂame alone. Since most of the measurement uncertainties are the same for both measurements and are negated in the relative measurement, the uncertainty in this study can be expected to be even smaller than reported by Huggett [65]. More details on the apparatus, procedure, as well as data acquisition and analysis can be found in Paskaluk et al. [59]. The energy release contribution De in Equation (1) measures the difference in energy release for the incoming ﬂame that resulted from the interaction with the fuel element and, similarly to the effective heat of combustion H in [18], considers an “effective” value eff that accounts for incomplete char oxidation. Therefore, the fuel element’s/sample’s energy release contribution De (kJ) in Equation (1) will be referred to as the fuel’s differential effective heat of combustion (¶H , kJ g ) when expressed either on a mass loss basis or a fresh mass eff basis. Both of these metrics were compared to determine which one better represented and predicted the ﬂammability of live fuel. However, in the rest of the study, only fresh Fire 2022, 5, 1 8 of 29 mass basis ¶H was considered and used to investigate the differences in ﬂammability eff attributable to the age of the plant material, seasonal changes in live fuel ﬂammability, and factors affecting these changes, as well as to evaluate the substantiality of the energy release reductions within the ﬂames interaction zone. 2.2. Fuel Samples Previous studies varied in terms of what was consumed during the ﬂame-front pas- sage in crown ﬁres in coniferous forests—fresh foliage alone or with some fresh branch- wood [31], or fresh foliage with fresh branchwood of varying diameters (0–3 mm [66], 0–10 mm [24], and 0–30 mm [8]). The plant material tested in this study consisted of fresh twigs/branchwood 0–9 mm thick with the attached foliage, collectively referred to as shoots. The ﬂow of combustion gases around and through thin, sparsely distributed fuels, such as the live coniferous shoots consumed in a crown ﬁre, signiﬁcantly differs from the ﬂow above surface fuels such as the layer of needles/foliage on the forest ﬂoor. The arrangement of needles removed from branches and laid ﬂat in the sample holder is more representative of surface fuels than fuels consumed in a crown ﬁre, potentially resulting in very different preheating, ignition, and burning behavior. Consequently, it is important to preserve the fuel structure in tests as much as possible, as was achieved in this study by testing the ﬂammability and biophysical properties of the exact same live plant material as is consumed by crown ﬁre—fresh shoots rather than foliage alone. To emphasize the focus on shoots, the terms shoot ﬂammability and shoot water content (SWC) will be used in this study rather than the more traditional terms foliar ﬂammability and foliar moisture content (FMC) or fuel ﬂammability and fuel moisture content. To adequately represent the spatial structure and ﬂammability at a tree branch scale but to avoid variation in the results due to the irregular spatial distribution of shoots within the branch, fuel samples were standardized for fuel mass, spatial arrangement, and bulk density using the concept of “ﬂat” fuel sample of deﬁned bulk density introduced in this study. A plant canopy is a porous fuel where a fuel element of given mass burns within the average per fuel element combustion space of given volume, which determines fuel porosity and bulk density. The volume of the roughly 30 30 30 cm combustion/testing space was 0.027 m , which included an approximately 10 10 30 cm combined burner and sample ﬂame with some surrounding air space since the ﬂame is non-premixed (Figure 2). To standardize and represent in tests the typical canopy bulk density of full-density conifers at 3 3 0.2 kg m [31,66,67], the fuel sample mass within the 0.027 m space should be 0.0054 kg dry mass, or 0.011 kg fresh mass (at an average 100% shoot water content on a dry mass basis; see Section 2.5 below). These 11 g (mean value) samples were further used for ﬂammability testing. To prepare a ﬂat fuel sample of deﬁned bulk density, approximately 9–13 g of shoots were arranged in a single layer (instead of many layers as on an actual tree branch) and placed into a sample basket, ensuring that the spatial arrangement of plant material resembled that in a real tree branch of white spruce (Figure 3a) and was as consistent as possible from test to test. The design of the wire-mesh sample holder allowed for a constant distance (5 cm) from plant material to the base of the methane ﬂame and its unrestricted ﬂow through the sample (Figure 3b). 2.3. Field Sampling Sampling was performed in a 50 to 70-year-old mixed stand of white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx.) located in the ecological reserve of the University of Alberta Botanic Garden, 15 km SW of Edmonton, Canada. Eighteen white spruce trees 15–20 m tall were selected across the site to represent a variety of local soil moisture conditions. Sampling occurred between 12:00 and 16:00 during 11 sampling days without precipitation or visible moisture on the surface of the plants from May to October 2014. Each sampling day, three to ﬁve trees out of the 18 identiﬁed were randomly selected and one tree branch from each tree within lower-one-third outer south- facing part of the crown was harvested using a pole pruner (Figure A1). Tree branches Fire 2022, 4, x FOR PEER REVIEW 9 of 31 Fire 2022, 5, 1 9 of 29 of plant material resembled that in a real tree branch of white spruce (Figure 3a) and was as consistent as possible from test to test. The design of the wire-mesh sample holder al- were stored in resealable plastic bags in a refrigerator at 4 C before ﬂammability tests were lowed for a constant distance (5 cm) from plant material to the base of the methane flame performed. Full sampling protocols are described in [7]. and its unrestricted flow through the sample (Figure 3b). (a) (b) Figure 3. (a) Fuel sample (new shoots) in a 10 × 10 × 1 cm wire mesh sample holder placed on the Figure 3. (a) Fuel sample (new shoots) in a 10 10 1 cm wire mesh sample holder placed on the weight scale. (b) Side view of the empty sample holder. The design of the sample holder provided weight scale. (b) Side view of the empty sample holder. The design of the sample holder provided a a constant distance from the shoots to the ignition source and spatial uniformity (constant dimen- constant distance from the shoots to the ignition source and spatial uniformity (constant dimensions sions and controlled density) of the fuel sample. and controlled density) of the fuel sample. 2.3. Field Sampling 2.4. Test Sequence Sampling was performed in a 50 to 70-year-old mixed stand of white spruce (Picea Each fresh tree branch was separated into shoots of different ages, and their respective glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx.) located in the mass proportions in the branch composition were measured. Four sample types were ecological reserve of the University of Alberta Botanic Garden, 15 km SW of Edmonton, considered: new shoots (if present, N = 42), 1-year-old shoots (N = 48), 2+ year-old shoots Canada. Eighteen white spruce trees 15–20 m tall were selected across the site to represent (N = 48), and tree branch (made up of new, 1-year-old and 2+ year-old shoots according to a variety of local soil moisture conditions. Sampling occurred between 12:00 and 16:00 their respective mass proportions in the composition of a given branch, N = 47). For each during 11 sampling days without precipitation or visible moisture on the surface of the sample type, one fuel sample was prepared, and its differential effective heat of combustion plants from May to October 2014. Each sampling day, three to five trees out of the 18 (¶H ) was tested (185 fuel samples in total). The remaining shoots of a given age were eff identified were randomly selected and one tree branch from each tree within lower-one- subsampled to determine water content, dry matter content, and fresh mass basis energy third outer south-facing part of the crown was harvested using a pole pruner (Figure A1). content. For the tree branch sample, these biophysical characteristics were estimated as a Tree branches were stored in resealable plastic bags in a refrigerator at 4 °C before flam- weighted average of new, 1 year, and 2+ year shoots from the same branch according to mability tests were performed. Full sampling protocols are described in [7]. their proportions in the branch composition. Since three to ﬁve branches (one from each selected tree) were harvested on each sampling day, three to ﬁve individual measurements 2.4. Test Sequence of ¶H and biophysical characteristics were performed for each of the four sample types eff for any given sampling day. Daily average results were used for calculating the data points Each fresh tree branch was separated into shoots of different ages, and their respec- in the seasonal time series. tive mass proportions in the branch composition were measured. Four sample types were considered: new shoots (if present, N = 42), 1-year-old shoots (N = 48), 2+ year-old shoots 2.5. Biophysical Characteristics (N = 48), and tree branch (made up of new, 1-year-old and 2+ year-old shoots according Considering the fact that substantial seasonal variation in dry matter content can lead to their respective mass proportions in the composition of a given branch, N = 47). For to the misrepresentation of water content when measured on a dry mass basis [2] (e.g., each sample type, one fuel sample was prepared, and its differential effective heat of com- FMC), shoot water content SWC was calculated on a dry mass basis [68], fresh mass basis, bustion (∂Heff) was tested (185 fuel samples in total). The remaining shoots of a given age and volume basis [7] (see Nomenclature). Dry matter content was calculated on a fresh were subsampled to determine water content, dry matter content, and fresh mass basis mass basis. Gross heat of combustion H on a dry mass basis was measured using a gross energy content. For the tree branch sample, these biophysical characteristics were esti- model 1341 Plain Jacket Bomb Calorimeter (Parr Instrument Company, Moline, IL, USA) mated as a weighted average of new, 1 year, and 2+ year shoots from the same branch and the standard oxygen bomb calorimetry test method [69]. The H , when expressed gross according to their proportions in the branch composition. Since three to five branches (one on a fresh mass basis [19] is referred to in our study as fresh mass basis energy content (EC) from each selected tree) were harvested on each sampling day, three to five individual because, assuming that water content is an inert diluent [18], this metric represents the measurements of ∂Heff and biophysical characteristics were performed for each of the four theoretical maximum amount of energy that can be released by a unit of live fuel’s fresh mass with combustion in pure oxygen after it has been oven dried. Fire 2022, 5, 1 10 of 29 3. Results and Discussion 3.1. Heat Transfer In existing oxygen consumption calorimetry methods, a heat ﬂux of 25–50 kW m is within the range observed in wildland ﬁres: 13–140 kW m peak convective and 20–132 kW m peak radiative heat ﬂuxes for surface and mixed (surface/crown) ﬁres and 2 2 32–42 kW m peak convective and 120–300 kW m peak radiative heat ﬂuxes in crown ﬁres, with noticeably lower time-averaged values [55] (Table 2). In wildﬁres, heat transfer is both radiative and convective [55], and the direction of convective heating coincides with the direction of ﬂame propagation (tilted sideways-upward in crown ﬁre ﬂame-fronts). In contrast, in traditional oxygen consumption/cone calorimetry, heat transfer is practically radiative-only. Unlike in real ﬁres, the ﬂame in cone calorimetry tests propagates down- ward through the fuel sample because energy is emitted by a radiant source above the sample and is directly received only by the upward-facing outer portion of the sample, which ignites ﬁrst. The opposite direction of the upward ﬂow of hot combustion products from the already burning fuel results in only a slight contact with the unburned fuel in the lower portion of the sample and a negligible element of convective heat transfer. These test conditions result in the partial and variable consumption of fresh plant material due to in- consistent delayed ignition at 52–555 s versus 1–50 s in wildﬁre ﬂame-fronts [56,63,70]. The prolonged ignition leads to variability in test results largely driven by water evaporation and pyrolysis rather than combustion and, unlike within real ﬂame-fronts [46], substantially reduces fuel water content before ignition, therefore masking water content-related energy release reductions when the fuel ﬁnally ignites. In our study, these issues were resolved by using combined radiative and convective heating from the methane ﬂame where the direction of convective ﬂux coincided with the direction of ﬂame propagation (upward: the sample was ignited from below/sides). This is similar to real conditions in crown ﬁres where the direction of heat transfer and ﬂame propagation also coincides (though it is sideways-upward rather than upward, as in the tests). Although the heat ﬂux of 40 kW m we used was comparable to that of existing methods, the changes listed above resulted in rapid and consistent ignition times of 10–30 s and near-complete consumption (on average 87.1%) of tested fresh 0–9 mm thick branchwood with the attached foliage, which closely represents the live fuel consumed within real ﬂame-fronts [8,24,31,66]. Prince and Fletcher [48] achieved a similarly fast (~10 s) and consistent ignition of fresh live leaves by using a similar upward convective heating test setup. Table 2. Convective and radiative heat transfer in wildland ﬁres for different fuel and ﬁre types. It is important to note that convective heat ﬂux is usually inferred from measurements of a total heat ﬂux gauge, the geometry of which is not representative of wildland fuels, so these values must be considered with caution. Peak Peak Convective Flame- Total Radiative Heat Transfer Flame Front Heat Heat Transfer Location, Fire Figure 2 Fire Type Length Source Residence Transfer Name kW kW (m) Time (s) (kW m ) % % 2 2 m m Needle cast Surface 30 37 [71] Surface 0.83 42 22 20 Rombo 1 [55] Surface 0.39 4 13 24 Eglin 2 [55] Surface 1.59 12 107 115 Ichauway 1 [55] Mixed grasses, Surface 082 9 100 105 Ichauway 2 [55] needle cast Surface 0.84 22 140 90 Ichauway 3 [55] Surface 1.25 11 82 59 Ichauway 4 [55] Fire 2022, 5, 1 11 of 29 Table 2. Cont. Peak Peak Convective Flame- Total Radiative Flame Heat Transfer Front Heat Heat Transfer Location, Fire Figure 2 Fire Type Length Source Residence Transfer Name (m) kW kW Time (s) (kW m ) % % 2 2 m m 30–120 40–50 Mediterranean [71] 112 51 [72] Mixed 6.5 21 113 51 45 Experiment 1 [73] Shrubs, scrubs Mixed 6.8 31 120 62 52 Experiment 2 [73] Mixed 8.4 27 110 50 45 Experiment 3 [73] Mixed 5.1 25 83 36 43 Experiment 4 [73] Mixed 6.1 26 101 34 34 Experiment 5 [73] Surface 1.25 17 60 75 Eglin 1 [55] Needle cast, Brush 2.4 40 94 130 Rombo 2 [55] grass, shrubs, Brush 1.44 10 26 120 Leadore 1 [55] brush, or Brush 1.44 10 19 132 Leadore 2 [55] sagebrush 105–120 30–60 [71] 32–42 100–120 25–50 [71] Crown 30 42 300 Rat Creek [55] Forest Crown 20 50 32 189 Mill Creek [55] Crown 37 120–300 [71] 3.2. Energy Release Reductions The test method presented in this paper quantiﬁes ﬂammability as the differential effective heat of combustion (¶H ), which is an “effective” value that accounts for reduced eff energy release with incomplete char oxidation during the ﬂame-front passage. Due to the in-ﬂame testing setup, ¶H directly accounts for the energy release reductions caused eff by fuel water content [49] and oxygen deﬁciency [50] with the interaction of ﬂames in the ﬂames interaction zone as discussed in the last paragraph of the Introduction. The described method produced a considerably lower and broader range of values for live fuel ﬂammability compared with traditional methods, suggesting that the energy release reductions within the ﬂames interaction zone are substantial. The mean ¶H for new eff shoots measured with our method was 0.23 kJ g (Table 3), showing a 97% reduction in energy release compared to the more traditional fresh mass basis energy content (EC) measured here with a bomb calorimeter at 7.55 kJ g . With a 65% reduction in energy release compared to the EC of 9.70 kJ g , the combined mean ¶H for all ages of shoots eff measured with our method was 3.38 kJ g (on a fresh mass basis), or approximately 6.8 kJ g on a dry mass basis (at average 100% shoot water content). In contrast, the FBP model uses a constant of 18 kJg [51] for the “lower” heat of combustion [52], which is almost three times higher and likely substantially over-predicts ﬁre intensity and the resulting spotting distance in live fuels where convective energy is directly calculated [74], while also missing seasonal variation in live fuel conditions. Table 3. Seasonal variation in energy content and ﬂammability. Minimum, maximum, mean, and standard deviations of fresh mass basis energy content (EC, kJ g ) and ﬂammability measured as differential effective heat of combustion (¶H , kJ g ). eff Minimum Maximum Range Mean (Standard Sample Deviation) Plant Tissue Type Size EC ¶H EC ¶H EC ¶H EC ¶H eff eff eff eff Tree branch (mixed shoot) 8.64 0.24 11.93 10.63 3.29 10.87 10.27 (0.81) 4.39 (1.79) 47 New shoots 4.46 6.33 10.88 6.48 6.42 12.81 7.55 (2.07) 0.23 (3.68) 42 1 year shoots 9.27 1.98 11.51 7.10 2.24 5.12 10.37 (0.52) 4.75 (1.19) 48 2+ year shoots 9.54 2.61 12.06 6.49 2.52 3.88 10.92 (0.57) 4.76 (0.86) 48 All ages of shoots 4.46 6.33 12.06 7.10 7.60 13.43 9.70 (1.89) 3.38 (3.03) 138 combined Fire 2022, 5, 1 12 of 29 When measured as effective heat of combustion using oxygen consumption calorime- try in the open air with radiant-only heating [18], live fuel ﬂammability ranged from 1 1 7 kJ g to 12 kJ g , depending on water content within the 80–170% (dry mass basis) range typical for most live conifers. In contrast, the differential effective heat of combustion (¶H ), measured in our study using the same oxygen consumption calorimetry equip- eff ment, but with the added in-ﬂame testing setup, showed values for all ages of shoots that 1 1 were on average lower by 9 kJ g and ranged from a positive 7.10 kJ g to a negative 6.33 kJ g , depending on water content. For new shoots, ¶H similarly varied from eff 1 1 a positive 6.48 kJ g to a negative value of 6.33 kJ g . In some cases, the ¶H was eff negative for the whole tree branch (Table 3). Since the ¶H represents the energy release eff contribution of the fuel to the incoming ﬂame, its negative values indicated a reduction in the energy release of the incoming methane ﬂame resulting from the interaction with the live fuel sample of high water content and the associated substantial energy release reductions within the ﬂames interaction zone. New shoots had substantial negative ¶H at eff the beginning of the season in Figure 4a and suppressed the energy release of the methane ﬂame (Figure 5a), in contrast to the 1-year-old shoots (Figure 5b). Traditional measurements of energy content using oxygen bomb or radiant heating oxygen consumption calorime- try cannot be negative because they represent the fuel’s potential energy release and are insensitive to energy release reductions within the ﬂames interaction zone. Figure 4. Seasonal variation in live fuel ﬂammability expressed as differential effective heat of combustion (¶H ): (a) Time series. Red, blue, green, and orange lines represent tree branch, new, eff 1 year, and 2+ year-old shoots respectively. Standard error is shown as same-color shadow around each line. Flammability of new shoots stayed substantially negative from late-May until late-June; (b) Box plot of seasonal variation in ¶H for tree branch, new, 1 year, and 2+ year-old shoots. eff A horizontal line within the box (the interquartile range, IQR) indicates the median. Whiskers are shown at 1.5 IQR. Circles indicate observed values outside of the 1.5 IQR. Fire 2022, 5, 1 13 of 29 Fire 2022, 4, x FOR PEER REVIEW 14 of 31 (a) (b) Figure 5. Variation in energy release contribution depending on fuel properties. For (a) new shoots Figure 5. Variation in energy release contribution depending on fuel properties. For (a) new shoots with high water content, the combined energy release of the incoming methane flame interacting with high water content, the combined energy release of the incoming methane ﬂame interacting with burning live fuel was lower (both when measured and when judged visually by the volume of with burning live fuel was lower (both when measured and when judged visually by the volume flames) compared with the initial energy release of the incoming methane flame alone (indicated by of ﬂames) compared with the initial energy release of the incoming methane ﬂame alone (indicated white dashed line). Therefore, the live fuel sample’s contribution to the energy release of the incom- by white dashed line). Therefore, the live fuel sample’s contribution to the energy release of the ing methane flame expressed as ∂Heff was negative. In the case of (b) highly flammable 1 year-old incoming shoots, themethane ∂Heff was positiv ﬂame expr e, where the com essed as ¶H bined v was negative. olume (and hence In the case energy release) of (b) highly of t ﬂammable he incom- eff ing methane flame interacting with burning live fuel was larger compared to that of the incoming 1 year-old shoots, the ¶H was positive, where the combined volume (and hence energy release) of eff methane flame alone (indicated by white dashed line). the incoming methane ﬂame interacting with burning live fuel was larger compared to that of the incoming methane ﬂame alone (indicated by white dashed line). 3.3. Flammability Definition and Numerical Fuel Classification 3.3. Flammability Deﬁnition and Numerical Fuel Classiﬁcation Traditionally, flammability is always a positive quantity because it is defined as the Traditionally, ﬂammability is always a positive quantity because it is deﬁned as the fuel’s ability to burn as represented by the ease/time of ignition (ignitibility), as well as com- fuel’s ability to burn as represented by the ease/time of ignition (ignitibility), as well as bustion rate (combustibility), duration (sustainability) [11], and completeness (consuma- combustion rate (combustibility), duration (sustainability) [11], and completeness (consum- bility) [12]. As a contribution to this broad mostly time/mass-based set, we introduce an ability) [12]. As a contribution to this broad mostly time/mass-based set, we introduce an energy release-based criterion. Flammability in our study is defined as the ability of a fuel energy release-based criterion. Flammability in our study is deﬁned as the ability of a fuel or material to sustain flame propagation, or a fuel element’s energy release contribution to the or material to sustain ﬂame propagation, or a fuel element’s energy release contribution to the incoming flame ∆e expressed on a mass loss basis or fresh mass basis as the differential incoming ﬂame De expressed on a mass loss basis or fresh mass basis as the differential effective heat of combustion (∂Heff). Therefore, the observed variation from a positive effective heat of combustion (¶H ). Therefore, the observed variation from a positive value −1 −1 eff value of 7.10 kJ g to a negative −6.33 kJ g in ∂Heff clearly indicates that the contribution 1 1 of 7.10 kJ g to a negative 6.33 kJ g in ¶H clearly indicates that the contribution of the eff of the burning live fuel element to the incoming flame energy release can vary from high- burning live fuel element to the incoming ﬂame energy release can vary from high-positive positive to low-negative. The sensitivity of the ∂Heff to these positive or negative effects to low-negative. The sensitivity of the ¶H to these positive or negative effects allows for eff allows for the development of a numerical classification of materials and substances. Ra- the development of a numerical classiﬁcation of materials and substances. Rather than ther than arbitrarily classifying them into fuels, non-fuels, and suppressants, their flam- arbitrarily classifying them into fuels, non-fuels, and suppressants, their ﬂammability can mability can be directly measured using ∂Heff as the positive, neutral, or negative value of be directly measured using ¶H as the positive, neutral, or negative value of their contribu- eff their contribution to the energy release of the incoming flame. This is especially important tion to the energy release of the incoming ﬂame. This is especially important for evaluating for evaluating suppressants and fire chemicals as well as fuel-to-suppressant transitioning suppressants and ﬁre chemicals as well as fuel-to-suppressant transitioning materials such materials such as live fuel. Live plant tissue substantially changes the proportions of as live fuel. Live plant tissue substantially changes the proportions of “combustibles” (dry “combustibles” (dry matter) and “suppressants” (water) in its composition during the Fire 2022, 5, 1 14 of 29 matter) and “suppressants” (water) in its composition during the season depending on the phenophase and the level of physiological drought. During June, new shoots of white spruce showed the highest seasonal water content and the lowest fresh mass basis energy content (Figure 6) resulting in negative values of ¶H (Figure 4a) and actually suppressing eff the energy release of the incoming methane ﬂame (Figure 5a), in contrast to late summer, when the new shoots’ ﬂammability is similar to that of older growth (Figure 4a). Figure 6. Seasonal variation in shoot properties for white spruce in 2014: (a) shoot water content on a volume basis (SWC ); (b) shoot water content on a dry mass basis (SWC ); and (c) fresh vol dm mass basis energy content (EC). Solid red, blue, green, and orange lines represent tree branch, new, 1 year-, and 2+ year-old shoots, respectively. Standard error is shown as a same-color shadow around each line. 3.4. Energy Balance Through in-ﬂame testing, the fuel’s energy release contribution expressed as De (per fuel element) and the differential effective heat of combustion ¶H (per unit of fuel eff element’s fresh mass) better represent the processes and conditions within a ﬂame-front including fuel ignition and the interaction of ﬂames within the ﬂames interaction zone. By Fire 2022, 5, 1 15 of 29 Fire 2022, 4, x FOR PEER REVIEW 16 of 31 measuring the fuel element’s contribution to the energy release of the incoming ﬂame, De directly quantiﬁes the gain or reduction in energy release at a given fuel element, which may or may not be sufficient to compensate for the energy losses from that fuel element may or may not be sufﬁcient to compensate for the energy losses from that fuel element (∆e ) into the environment and into the horizontal propagation flux for preheating the (De ) into the environment and into the horizontal propagation ﬂux for preheating the next + + − next fuel elements. Higher, similar, or lower values of ∆e relative to /∆e / indicate in- fuel elements. Higher, similar, or lower values of De relative to /De / indicate increases, creases, no effect, or declines in the horizontal propagation flux for the preheating of the no effect, or declines in the horizontal propagation ﬂux for the preheating of the next fuel next fuel elements and, hence, the growth, steady propagation, or decline of the incoming elements and, hence, the growth, steady propagation, or decline of the incoming ﬂame + + fl (see ame (see Figur F ei7 gu for re 7 for det details). a Ther ils). efor Theref e, D ore e , and ∆e and ¶H ∂H mor eff more accur e accurately ate rly represent the epresent the ener en- gy eff ergy g generation eneration component of the energ component of the energy balance y balanc of the e ofincoming the incoming ﬂame flame at a fuel at a element fuel element scale sca and le can and c be an used be uas sed a as mor a e madequate ore adequa ﬂammability te flammabilinput ity inp for ut ﬂame for flam pre p opagation ropagation and and ﬁre fire behavior behavi modelling or modelling b based ased on on ener energ gy balance y balance ra ratherther tha than FMC n FMC or ti or time-to-ignition. me-to-ignition. Figure 7. The figure shows the energy balance and the state of the frontal flame determined by the Figure 7. The ﬁgure shows the energy balance and the state of the frontal ﬂame determined by energy balance at each separate fuel element (∆E), which is the sum of energy generation (∆e ) and + the energy balance at each separate fuel element (DE), which is the sum of energy generation (De ) energy losses (∆e ). Flame propagates from fuel element F1 to fuel element F4; flame from each and energy losses (De ). Flame propagates from fuel element F1 to fuel element F4; ﬂame from previous element represents incoming frontal flame. Vertical direction of flame propagation, from each previous element represents incoming frontal ﬂame. Vertical direction of ﬂame propagation, the bottom to the top (instead of tilted sideways-upward as in real crown fire flame-fronts) repre- from the bottom to the top (instead of tilted sideways-upward as in real crown ﬁre ﬂame-fronts) sents the experimental setup and the apparatus. Depending on the weather conditions, and the represents the experimental setup and the apparatus. Depending on the weather conditions, + and the physical, chemical, and spatial properties of the particular fuel bed, the value of ∆e may or may physical, chemical, and spatial properties of the particular fuel bed, the value of De may or may not not be sufficient to compensate for the energy losses from a fuel element ∆e to the environment and into the horizontal propagation flux for preheating the next fuel elements. The frontal flame be sufﬁcient to compensate for the energy losses from a fuel element De to the environment and into + − propagates steadily (middle image, equilibrium state) when ∆e = |∆e | because the horizontal the horizontal propagation ﬂux for preheating the next fuel elements. The frontal ﬂame propagates propagation flux for the preheating of the next fuel element + s (which is the “useful” part of ∆e ) is steadily (middle image, equilibrium state) when De = |De | because the horizontal propagation compensated by the sufficient part of energy generation ∆e . The frontal flame declines (left image) ﬂux for the preheating of the next fuel elements (which is the “useful” part of De ) is compensated + − + − if ∆e < |∆e | because lower values of ∆e relative to |∆e | indicate declines in the horizontal prop- + + by the sufﬁcient part of energy generation De . The frontal ﬂame declines (left image) if De < |De | agation flux for the preheating of the next fuel elements, which is now insufficiently compensated because lower values of De relative to |De | indicate declines in the horizontal propagation ﬂux + + − + by ∆e . The frontal flame grows (right image) when ∆e > |∆e | because higher values of ∆e rela- for the preheating of the next fuel elements, which is now insufﬁciently compensated by De . The tive to |∆e | indicate increases in the horizontal propagation flux for the preheating of the next + + frontal ﬂame grows (right image) when De > |De | because higher values of De relative to |De | fuel elements. indicate increases in the horizontal propagation ﬂux for the preheating of the next fuel elements. The characteristics of the spatial structure of live fuel can alter the complex boundary The characteristics of the spatial structure of live fuel can alter the complex boundary layer flow of hot combustion gases around and through thin fuels such as fresh live layer ﬂow of hot combustion gases around and through thin fuels such as fresh live shoots, shoots, thus affecting the heat transfer coefficients from combustion gases to the fuel ele- thus affecting the heat transfer coefﬁcients from combustion gases to the fuel element. This ment. This can shift the energy balance (∆E , shown in Figure 7, by affecting energy gen- can shift the energy balance (DE, shown in Figure 7, by affecting energy generation deﬁned eration defined in our study as the fuel’s energy release contribution ∆e as well as energy in our study as the fuel’s energy release contribution De as well as energy losses from a losses from a fuel element ∆e and the proportions of its two components—losses to the fuel element De and the proportions of its two components—losses to the environment environment and energy used for preheating the next fuel elements. The positive or neg- and energy used for preheating the next fuel elements. The positive or negative shift ative shift in energy balance will affect the propagation of flame from one fuel element to in energy balance will affect the propagation of ﬂame from one fuel element to the next the next and the resulting fire behavior. In addition, live fuels “burst” and shoot jets of gases [48] and burning needles (observed in our study) during combustion due to high Fire 2022, 5, 1 16 of 29 and the resulting ﬁre behavior. In addition, live fuels “burst” and shoot jets of gases [48] and burning needles (observed in our study) during combustion due to high internal leaf pressures [48], which potentially also changes the boundary layer ﬂow and may or may not contribute to the ignition of the neighbouring fuel elements and ﬂame propagation. Since no in-depth analysis of boundary layer ﬂuid motion was undertaken, and consequently the effects of fuel properties on heat transfer coefﬁcients are not known, live fuel ﬂammability testing should be phenology- and species-speciﬁc with a special attention to preserving the spatial structure of the fuel. 3.5. Stand-Scale Flammability Although energy release is directly related to the fuel mass loss [11] and, theoretically, the traditional mass loss basis approach should have an obvious advantage, the fresh mass basis approach introduced in this study was equally successful in predicting variation in ﬂammability measured as ¶H (Table 4).Therefore, the species-speciﬁc ¶H for live fuel eff eff can be predicted at the forest stand scale using remote sensing-derived predictor variables such as shoot water content and others in Table 4 (see also Figure 8). With further research on the effects of heat transfer intensity, this will allow for operationally predicting the potential energy release of live fuel for the forest stand. It can be calculated as the fresh mass of live fuel in the forest stand available for high-intensity crown ﬁre (typically fresh 0–9 mm thick branchwood with the attached foliage [8,24,31,66]) multiplied by its potential energy output—the fresh mass basis ¶H of the same live plant material determined eff using our method. The amount of live fuel available for crown ﬁre can be measured using standard fuel inventory protocols. This approach, when applied for live and dead fuel, allows for the operational calculations of a maximum possible energy release under extreme ﬁre-weather conditions or the potential net heat content (PNHC) of the forest stand. As a numerical measure of the potential forest stand ﬂammability, the PNHC can be further used in the development of a new numerical stand characteristics-based fuel classiﬁcation within a new generation of crown ﬁre models. The PNHC, when reduced from potential to actual value depending on the severity of ﬁre-weather conditions, represents the actual net heat content (ANHC) of the forest stand that can be further used as a numerical input of the actual forest stand ﬂammability for energy release-based ﬁre behavior modelling. Table 4. Adjusted R-squared values for the predictor variables in modelling ﬂammability as dif- ferential effective heat of combustion on a fresh mass basis (¶H ) using traditional and proposed eff approaches. The proposed fresh mass basis approach introduced in this study showed same or better results in predicting ﬂammability compared with the traditional mass loss basis approach. 2 2 R for Flammability R for Flammability Predictor (Predictand) as Fresh Mass (Predictand) as Mass Loss Basis ¶H , New Approach Basis ¶H , Old Approach eff eff Shoot water content, fresh 0.82 0.80 mass basis (SWC ) fm Shoot water content dry mass basis (SWC ) as analog of dm 0.79 0.78 FMC, but for shoots instead of just foliage Shoot dry matter content, 0.81 0.80 fresh mass basis (DM) Shoot fresh mass basis energy 0.80 0.77 content, (EC) Shoot gross heat of combustion dry mass basis 0.005 0.002 (H ), or caloriﬁc content gross Fire 2022, 5, 1 17 of 29 Figure 8. Factors affecting live fuel ﬂammability. Flammability as differential effective heat of combustion on a fresh mass basis (¶H ) for tree branch, new, 1 year-, and 2+ year-old shoots of white eff spruce in relation to (a) shoot water content on a fresh mass basis (SWC ), (b) shoot water content fm on a dry mass basis (SWC ) as analog of FMC, (c) dry matter content, (DM), and (d) fresh mass dm basis energy content (EC). Red, blue, green, and orange dots represent tree branch, new, 1 year-, and 2+ year-old shoots, respectively. 3.6. Seasonal Variation and Drivers of Flammability The seasonal trend of live fuel ﬂammability for white spruce observed in 2014 differs substantially from that assumed by the FBP model (Figure 9) and better matches the historical seasonality of extreme wildﬁre in Canada (see Figure A2 and data set in Table A1). According to the FBP, extreme crown ﬁre behavior can be expected around 1 June, during the “spring dip”, when the FMC is assumed to be the lowest [75] and the corresponding live fuel ﬂammability represented by FMC-derived Crown Spread Factor is the highest [33,76]. However, most extreme wildﬁres in Canada since 1825 started either substantially earlier Fire 2022, 5, 1 18 of 29 (early April to late May) or later (July-August and mid-fall). In this study, the ﬁrst seasonal peak in live fuel ﬂammability was observed in early May, three weeks earlier than was predicted by the FBP (Figure 9), and it closely matches the start of the 1989 Northern Manitoba, 1998 Swan Hills, 2011 Richardson Backcountry, 2011 Slave Lake, 2015 British Columbia, and 2016 Fort McMurray extreme wildﬁres (Table A1). The next three seasonal spikes in ﬂammability were observed in early July, early August, and September-October, corresponding well to the timing of the 1911 Porcupine, 2015 Northern Saskatchewan, and 2014 and 2017 British Columbia wildﬁres (early July), as well as the 1916 Matheson, 1998 British Columbia, and 2003 Okanagan Mountain Park ﬁres (early-mid August), and the 1825 Miramichi, 1922 Haileybury, 1938 Rainy River, and a major run of 1950 Chinchaga River extreme wildﬁres (September-October) (Figure A2). In contrast, at this time of the season, the FBP predicts the lowest seasonal values of live fuel ﬂammability represented by the Crown Spread Factor [33,76] for conifer stands common in Canada. Figure 9. Seasonal changes in live fuel ﬂammability as measured in our study as differential effective heat of combustion (¶H ) for 2014 (solid line) and as assumed by the FBP model when expressed eff as an FMC-derived Crown Spread Factor (dashed line). The FPB model assumes only one seasonal maximum in live fuel ﬂammability around 1 June. Flammability measured in this study indicates the ﬁrst seasonal maximum three weeks earlier, in early May, which closely matches the historical seasonality of extreme crown ﬁre behavior in Canada (Figure A2 and Table A1). In agreement with the historical seasonality of extreme crown ﬁre behavior, ﬂammability measured in this study indicates the second and the third seasonal maximums around 1 July and 1 August when the FBP model assumes lowest values of the season. Shoot age had a signiﬁcant effect on live fuel ﬂammability (ANOVA, p < 0.001, F = 60.081, n = 42). New shoots played an important role at the beginning of the sea- 1 1 1 son. Their ﬂammability was on average lower (0.23 kJ g against 4.75 kJ g or 4.76 kJ g for 1-year and 2+year old shoots respectively (Table 3)) and varied more widely compared with older growth (Figure 4). The timing and magnitude of the observed seasonal max- imums in live fuel ﬂammability for a tree branch (Figure 4a) were best explained by the opposite seasonal trend of the shoot water content volume basis (SWC , Figure 6a). The vol observed “early-August dip” in SWC and the simultaneous resulting spike in ﬂamma- vol bility were likely caused by a summer-fall drought [77]. The ﬁrst seasonal maximum in Fire 2022, 5, 1 19 of 29 ﬂammability, observed in early May, was less accurately compared with SWC , indicated vol by the corresponding minimum in the traditional shoot water content, on a dry mass basis, (SWC ) only in the end of June, which is almost three weeks later (Figure 6b). This dm suggests that SWC and its analog FMC alone cannot fully represent the ﬂammability of dm live fuel. Moreover, since substantial seasonal variation in dry matter content is a major issue in measuring two-variable water content on a dry mass basis [2], such as SWC dm and FMC, the use of single-variable shoot water content on a fresh mass basis (SWC ) or fm SWC may be advantageous. vol As in previous studies [17,18,29,78], the ﬂammability of live fuel was strongly inversely related to water content (SWC in Figure 8a and more traditional SWC in Figure 8b). fm dm The differential effective heat of combustion was negative for new shoots with SWC dm over 210%. Flammability was strongly directly related to dry matter content (Figure 8c). Conﬁrming the ﬁndings of [19], the traditional gross heat of combustion (dry mass basis, H ) was unable to satisfactorily explain variation in live fuel ﬂammability (adjusted gross R = 0.005 in Table 4). In contrast to their results, a non-standard fresh mass basis energy content (Figure 8d), measured in this study as H on a fresh mass basis, was as successful gross in explaining the variation in ﬂammability as water or dry matter content. Since fresh mass basis energy content is determined by both chemical composition and water content, this also supports the conclusions of [79] concerning the importance of these two variables in predicting live fuel ﬂammability. 3.7. Limitations and Future Research To improve the understanding of the effects of canopy spatial structure and ﬁre- weather conditions on wildﬁre behavior, the proposed method requires further exploration of the effects of the amount, arrangement, and bulk density of the tested plant material, the intensity and duration of the methane ﬂame exposure, and the distance from the ﬂame base to the sample. The oxygen consumption calorimetry method [57], which was used as a part of the experimental methodology for measuring differential effective heat of combustion in our study, is insensitive to direct energy losses with fuel preheating and water desorption and evaporation (latent heat). These losses need to be accounted for in further studies. The substantial differences between the seasonal pattern of live fuel ﬂammability assumed by the FBP model and that measured in 2014 suggest the necessity of further investigations over multiple seasons. Different regions, species, and age-classes should also be represented. The water content for some samples taken in May and early June was likely underestimated due to prolonged storage; close-to-real-time testing will improve the representation of seasonal changes in water content and ﬂammability. A greater ability to explain seasonal changes in ﬂammability and the higher sensitivity to drought of the shoot water content volume-basis metric, as compared with more traditional shoot water content metrics (on a dry mass basis), suggests the necessity of further studies on quantifying the ﬂammability of live fuel using a volumetric approach. 4. Conclusions The present study was the ﬁrst to use in-ﬂame ﬂammability testing for quantifying energy release; previously, in-ﬂame testing was only used for quantifying time-to-ignition, e.g., [46], and for studying increased oxygen consumption and ﬂow dynamic alteration within the ﬂames interaction zone of burning fuel elements [50]. An in-ﬂame test setup with upward convective heating similar to that in our study was also used by Borujerdi et al. and Prince and Fletcher [47,48] for testing live leaves; however, only combustion temperature was monitored, rather than energy release measured in the current study. Determining energy release in conditions similar to those within a ﬂame-front, i.e., directly in the ﬂame, allows for more realistic conditions of heat transfer, ignition, and combustion. The samples tested were representative of live fuel consumed by crown ﬁre ﬂame-front, and consisted of fresh branchwood 0–9 mm thick with attached foliage. Fast and consistent ignition and almost complete consumption of tested fuel reinforces the validity of the method. Fire 2022, 5, 1 20 of 29 By using in-ﬂame testing, the experimental methodology documented here directly accounts for the additional water content- and oxygen deﬁciency-associated energy release reductions caused by the interaction of the ﬂames. The values of live fuel ﬂammability measured in our study were almost three times lower compared with those currently used in the FBP System and on average 9 kJ g lower than the values measured tradition- ally, suggesting an important effect of the energy release reductions within the ﬂames interaction zone. The observed seasonal trend of live fuel ﬂammability for white spruce in 2014 sub- stantially differs from that assumed by the FBP model and better matches the historical seasonality of extreme wildﬁre in Canada. At the tree branch-scale, changes in live fuel ﬂammability were dictated by phenology-associated changes in the relative amount and ﬂammability of new shoots during spring and by drought-induced changes in ﬂammability of all ages of shoots throughout the season. Variation in live fuel ﬂammability was equally well explained using water content, dry matter content, and fresh mass basis energy content (the latter is not typically used in wildﬁre applications). Similar models developed for main forest species should provide stand-speciﬁc input of live fuel ﬂammability that can be directly linked with the existing FBP modules as a replacement of the ﬁxed seasonal pattern of variation in FMC. Using differential effective heat of combustion, ﬂammability in this study was quanti- ﬁed as the fuel’s net contribution to the energy release of the incoming ﬂame, that showed both positive and negative values. Therefore, rather than arbitrarily classifying materials and substances into fuels, non-fuels, or suppressants, their ﬂammability can be directly measured using the proposed method as a positive, neutral, or negative energy release contribution to the incoming ﬂame. This is especially important for characterization of sup- pressants, ﬁre chemicals, and fuel-to-suppressant transitioning materials such as live fuel. With in-ﬂame testing, our method more accurately measures the energy-generation component of energy balance at a fuel element scale because it better represents the pro- cesses and conditions within real ﬂame-fronts and directly quantiﬁes changes in the energy release of the incoming ﬂame. For instance, low and negative values for live crown fuels in leafed-out deciduous and mixedwood boreal stands will indicate a reduction in ﬁre intensity and the eventual suppression of the incoming crown ﬁre ﬂame-front. High values for live crown fuels in coniferous stands (e.g., during drought) will indicate growth in the intensity of the incoming crown ﬁre ﬂame-front, while low and negative values will suggest crown ﬁre weakening. Successful modelling of energy release on a fresh mass basis instead of a traditional mass loss basis, with further research, will allow for the operational prediction of the potential energy release of a whole forest stand as a measure of its ﬂammability. This variable, determined for extreme ﬁre-weather conditions, can be used in the development of a new numerical stand characteristics-based fuel classiﬁcation and—when reduced for the actual ﬁre-weather conditions—can be used in energy balance-based ﬁre behavior modelling. Using a more adequate value to represent the ﬂammability of live fuel and forest stand will contribute to improving the accuracy of ﬁre behavior predictions and increasing the efﬁciency of forest and wildﬁre management in the face of increasingly complex environmental challenges arising from changes in climate and ﬁre regimes. Author Contributions: Conceptualization, O.M.M., S.A.P., and M.Y.A.; methodology, O.M.M., S.A.P., M.Y.A., and D.K.T.; software, K.O.M., S.A.P., D.K.T., and O.M.M.; validation, M.Y.A., S.A.P., and D.K.T.; formal analysis, M.D.F., D.K.T., and S.S.M.; investigation, O.M.M., and S.A.P.; resources, M.D.F., M.Y.A., and D.K.T.; data curation, K.O.M., and O.M.M.; writing—original draft preparation, O.M.M.; writing—review and editing, O.M.M., K.O.M., M.Y.A., M.D.F., D.K.T., S.S.M., and S.A.P.; Visualization, K.O.M., and O.M.M.; Supervision, M.D.F., M.Y.A., D.K.T., and S.S.M.; project admin- istration, M.D.F.; funding acquisition, M.D.F. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Canadian Partnership for Wildland Fire Science (Canada Wildﬁre). Fire 2022, 5, 1 21 of 29 Data Availability Statement: The data presented in this study are openly available at https://doi. org/10.5281/zenodo.5687455. Acknowledgments: The authors thank Martin Alexander, Peter Murphy, Brian Stocks, Ralph Nelson, Xianli Wang, Cordy Tymstra, Richard Olsen, and Dan Perrakis for sharing their professional expertise and advice on this study and express sincere gratitude to Stavros Sakellariou, Mihails Melniks, and Larisa Melnic for assisting with ﬁeldwork and lab work. This study was supported by the Northern Forestry Centre of the Canadian Forest Service, Forest Management Division of the Department of Environment and Natural Resources of the Government of the Northwest Territories, and the Protective Clothing and Equipment Research Facility of the University of Alberta. Conﬂicts of Interest: The authors declare no conﬂict of interest. Nomenclature Energy-related variables and deﬁnitions H Heat of combustion, dry mass basis (kJ g ) H Gross heat of combustion, dry mass basis (caloriﬁc content) (kJ g ) gross EC Energy content, equivalent to H expressed on fresh mass basis (kJ g ) gross H Effective heat of combustion, mass loss basis (kJ g ) eff Flammability as fuel element’s contribution to the energy release of the incoming ﬂame, De per fuel element/sample (kJ) Flammability as differential effective heat of combustion, which represents De per unit ¶H eff fresh mass or mass loss of fuel element/sample (kJ g ) Other variables and deﬁnitions DM Dry matter content, fresh mass basis (%) FIZ Flames interaction zone FMC Foliar moisture content, dry mass basis (%) Shoots Twigs/branchwood 0–9 mm thick with the attached foliage SWC Shoot water content, fresh mass basis (%) fm Shoot water content, dry mass basis (analogous to FMC, but for shoots instead SWC dm of foliage alone) (%) SWC Shoot water content, volume basis (g cm ) vol Fire 2022, 5, 1 22 of 29 Fire 2022, 4, x FOR PEER REVIEW 23 of 31 Appendix A. Additional Figures Figure A1. Field sampling. Samples were harvested within lower-one-third outer south-facing Figure A1. Field sampling. Samples were harvested within lower-one-third outer south-facing part part of the crown using a pole pruner. of the crown using a pole pruner. Appendix B. Historical Seasonality of Extreme Crown Fire Behavior in Canada Appendix B. Historical Seasonality of Extreme Crown Fire Behavior in Canada The extreme wildfires (Table A1) that were used to determine timing and historical The extreme wildﬁres (Table A1) that were used to determine timing and historical seasonality of extreme crown fire behavior in Canada for 1825–2017 in Figure A2 (as the seasonality of extreme crown ﬁre behavior in Canada for 1825–2017 in Figure A2 (as the start time for extreme wildfires) were selected from [80,81] for the period from 1825 to the start time for extreme wildﬁres) were selected from [80,81] for the period from 1825 to the early 1900s and from the Canadian Disaster Database [82] for the period from the early early 1900s and from the Canadian Disaster Database [82] for the period from the early 1900s to 2016. The criteria for selecting extreme wildfires among the wildfire disasters 1900s to 2016. The criteria for selecting extreme wildﬁres among the wildﬁre disasters listed listedin in t the hesour sources ces above above wer were an e anyy o of fthe the fo following: llowing: (1 (1)) multiple multiplewildﬁr wildfir e-r e-re elated lated human human life losses, (2) area burned 100,000 ha or more, or (3) evacuation of 2000 people or over. life losses, (2) area burned 100,000 ha or more, or (3) evacuation of 2000 people or over. Additional Additional information information for for some some of t of these hes wildﬁr e wildes fires (if missing) (if missing) waswa retrieved s retrieved from fr[om [8 83–863– ]. 86]. All wildﬁres since the early 1900s documented in the literature and ofﬁcial web sources, which were classiﬁed by authors as extreme-intense or outstanding, but omitted All wildfires since the early 1900s documented in the literature and official web from Public Safety Canada (2020), were also included in this analysis. These are the 1950 sources, which were classified by authors as extreme-intense or outstanding, but omitted Chinchaga [87], 1968 Lesser Slave Lake [88], 1968 Inuvik [89], 1968 Vega [90], 1980 DND-4-80 from Public Safety Canada (2020), were also included in this analysis. These are the 1950 and DND-3-80 Cold Lake wildﬁres [88], the 1981 Hay River 36 [91], 2001 Chisholm [90], 2002 Chinchaga [87], 1968 Lesser Slave Lake [88], 1968 Inuvik [89], 1968 Vega [90], 1980 DND- House River [92], 2003 McLure [93], 2003 Okanagan Mountain Park [94], 2011 Richardson 4-80 and DND-3-80 Cold Lake wildfires [88], the 1981 Hay River 36 [91], 2001 Chisholm [90], 2002 House River [92], 2003 McLure [93], 2003 Okanagan Mountain Park [94], 2011 Richardson Backcountry [95], 2017 Kenow [96], and 2017 Verdant Creek wildfires [97], as Fire 2022, 5, 1 23 of 29 Backcountry [95], 2017 Kenow [96], and 2017 Verdant Creek wildﬁres [97], as well as the 2010 British Columbia, 2016 Peace Region BC, and 2017 British Columbia [86] wildﬁres. Figure A2. Historical seasonality of extreme crown ﬁre behavior in Canada for 1825–2017 compared with seasonal trend of live fuel ﬂammability measured in 2014 and that assumed by the FBP model. The FPB model represents live fuel ﬂammability expressed as a FMC-derived Crown Spread Factor (dashed line) at a rough temporal scale assuming only one seasonal maximum in live fuel ﬂamma- bility around 1 June. Live fuel ﬂammability measured in our study as differential effective heat of combustion ¶H for 2014 (solid line) showed seasonal trend of higher temporal resolution with eff three seasonal maximums that match the maximums in historical seasonality of extreme crown ﬁre behavior (gray histogram representing number of extreme ﬁres started during a given 5-day period) according to the dataset in Table A1: early May (three weeks earlier compared with the assumptions of the FBP), early July, and early August. By contrast, the Crown Spread Factor by the FBP model assumes close to the lowest values for the season in early July and early August. Table A1. List of extreme wildﬁres in Canada for 1825–2017. Data from the list were used to build a histogram of historical seasonality of extreme crown ﬁre behavior in Canada for 1825–2017 in Figure A2. When the information differed between two referenced sources, data from both were reported, separated by a slash (/). Wildﬁre Name and Year Start Date End Date Size (ha) Human Lives Lost Evacuated Reference Location 160+ Great Miramichi Fire, NB 1825 7 October - 1,200,000 [80] (500+ unofﬁcially) Saguenay–Lac-Saint-Jean 19 May/27 1870 19 May 400,000 7 [80,81] Fire, QC May The Great Fire, Ottawa 1870 1 August 28 August 51,200+ 20+ 8000+ [81] Valley, ON Fernie Fire, BC 1908 1 August 1 August 25,900 22+ [80] Baudette Fire/Rainy River 1910 7 October 7 October 121,500 42+ [80] Fire, MN and ON Fire 2022, 5, 1 24 of 29 Table A1. Cont. Wildﬁre Name and Year Start Date End Date Size (ha) Human Lives Lost Evacuated Reference Location 73+ Great Porcupine Fire, AB 200,000/ 1911 11 July 11 July (in the hundreds 200 [80,82] and ON 804,650 unofﬁcially) 223+ Great Matheson Fire, AB 3 August/29 1916 29 July 200,000 (as high as 400 8000 [80,82] and ON July unofﬁcially) Lac La Biche Fire, AB and 1919 19 May Early June 2,800,000 13+ [80,83] SK Great Fire of 1922 168,000/ 43+ (as high as 150 1922 30 September 5 October 11,000 [80,82] Haileybury, ON 518,000 unofﬁcially) Rainy River and Dance 30,355/ 1938 10 October 15 October 17+ 155 [80,82] Township Fire, ON 37,230 Gogama, ON 1941 14 May 15 June 133,827 [82] Mississagi, ON 1948 1 May 31 October 261,017 [82] Chinchaga River Fire (Wisp Major run 20 1950 October 1,400,000 [87] ﬁre), BC and AB September Major run Lesser Slave Lake Fire, AB 1968 133,550 [98] 23 May Vega ﬁre, AB 1968 23 May [90] Inuvik Fire, NWT 1968 8 August 18 August 35,000 [89] Cold Lake Fire (DND-3-80), 1980 1 May [98] AB and SK Cold Lake Fire (DND-4-80) 1980 2 May 177,813 [98] AB and SK Hay River Fire (HY-36-81), 1981 3 July 1009 [91] NWT Red Lake Fire, ON 1980 1 June 43,664 5000 [82] Fire Northeast of 1985 1 July 240,000+ [82] Vancouver, BC Northern Manitoba ﬁres 1989 11 May 20 September 3,280,000 25,000 [82,84] Betsiamites, Ragueneau 1991 29 June 29 June 7000 [82] and Baie-Comeau Fire, QC North Central 1995 29 May 29 May 160,000 3338 [82] Saskatchewan ﬁres Swan Hills Fire, AB 1998 5 May 21 May 155,000 2030 [82] Tibbet Lake Fire, NWT 1998 22 July 31 July 140,000 5 [82] British Columbia ﬁres 1998 1 August 31 August? 42,115 10,600 [82] Salmon Arm Fire, BC 1998 10 August 17 August 6300 7000 [82] Chisholm ﬁre (LWF-063), 2001 23 May 29 May 36,690 [90] AB 248,000/ House River Fire, AB 2002 17 May 7 June 1550 [82,92] 248,243 Manitoba ﬁres 2003 1 April 31 October 918,845 665 [82,85] Southeastern BC and 2003 1 July 31 August 48,501 [82] Southwestern AB ﬁres Okanagan Mountain Park 25,000/ 27,000/ [94]/ 2003 16 August 12 September Fire, BC 25,600 33,050 [86] 26,420/ [86]/ McLure Fire, BC 2003 30 July October 3800 26,000 [93] Mistissini Fire, QC 2006 16 June 18 June 3200 [82] Tumbler Ridge Fire, BC 2006 3 July 5 July 9100 4000 [82] South Indian Lake Fire, MB 2007 19 July 26 July 147,473 963 [82] Norway House and 2008 28 May 28 May 3330 [82] Sherridon Fire, MB Halifax Fire, NS 2008 13 June 13 June 5000 [82] Northern Saskatchewan 2008 30 June 30 June 2500 [82] ﬁres Fire 2022, 5, 1 25 of 29 Table A1. Cont. Wildﬁre Name and Human Lives Year Start Date End Date Size (ha) Evacuated Reference Location Lost Kelowna, Kamloops and 2009 1 May 31 August [82] Cariboo Fire, BC 1 20,000 West Kelowna wildﬁres, BC 2009 18 July 31 August [82] British Columbia ﬁres 2010 28 July 8 September [82] 330,000 2 1383 18 August (2nd Early British Columbia ﬁres 2010 [86] major run) September Richardson Backcountry 2011 15 May September 148,000+ [95] Fire, AB Slave Lake Wildﬁre, AB 2011 14 May 22 May 4900 1 12,055 [82] Northern Ontario ﬁres 2011 6 July 25 July 300,000 3300+ [82] Mackenzie County Fire, AB 2012 11 July 20 July 100,000 300 [82,99] Lethbridge and Coalhurst 2012 10 September 11 September 3000 [82] Fire, AB Northwest Territories ﬁres 2014 1 July 18 September 3,500,000+ 60 [82] British Columbia ﬁres 2014 1 July 30 September 360,000 4500 [82] British Columbia ﬁres 2015 9 May 11 September 300,000 1 3432 [82] Northern Saskatchewan 2015 1 July 18 July 1,800,000 13,000 [82] ﬁres Peace Region ﬁres, BC 2016 18 April Fall [86] Wood Buffalo (Fort 1 May/30 Mid June/ 589,000/ McMurray) Wildﬁre, AB 2016 2 88,000/96,000 [100]/[82] April 1 June 593,670 and SK Easterville and 2016 23 June 27 June 2070 [82] Chemawawin Fire, MB British Columbia ﬁres 2017 7 July 15 September 1,200,000+ 65,000 [86] Verdant Creek Fire, BC 2017 15 July October 18,017 [97] Kenow Fire, AB 2017 30 August 38,000 [96] References 1. 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New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

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Fire – Multidisciplinary Digital Publishing Institute

Published: Dec 23, 2021

Keywords: oxygen consumption calorimetry; oxygen bomb calorimetry; heat of combustion; energy release; live fuel flammability; foliar moisture content; FMC; white spruce; picea glauca

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New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

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New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

New In-Flame Flammability Testing Method Applied to Monitor Seasonal Changes in Live Fuel

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