Peat fuels representing four biomes of boreal (western Russia and Siberia),
temperate (northern Alaska, USA), subtropical (northern and southern
Florida, USA), and tropical (Borneo, Malaysia) regions were burned in a
laboratory chamber to determine gas and particle emission factors (EFs).
Tests with 25 % fuel moisture were conducted with predominant smoldering
combustion conditions (average modified combustion efficiency (MCE) =0.82±0.08). Average fuel-based EFCO2 (carbon dioxide) are highest
(1400 ± 38 g kg-1) and lowest (1073 ± 63 g kg-1) for
the Alaskan and Russian peats, respectively. EFCO (carbon monoxide) and
EFCH4 (methane) are ∼12 %–15 % and ∼0.3 %–0.9 % of EFCO2, in the range of 157–171 and 3–10 g kg-1, respectively. EFs for nitrogen species are at the same magnitude
as EFCH4, with an average of 5.6 ± 4.8 and 4.7 ± 3.1 g kg-1 for EFNH3 (ammonia) and EFHCN (hydrogen cyanide); 1.9±1.1 g kg-1 for EFNOx (nitrogen oxides); and 2.4±1.4 and 2.0 ± 0.7 g kg-1 for EFNOy (total reactive
nitrogen) and EFN2O (nitrous oxide).
An oxidation flow reactor (OFR) was used to simulate atmospheric aging times
of ∼2 and ∼7 d to compare fresh (upstream)
and aged (downstream) emissions. Filter-based EFPM2.5 varied by
> 4-fold (14–61 g kg-1) without appreciable changes between
fresh and aged emissions. The majority of EFPM2.5 consists of EFOC
(organic carbon), with EFOC/ EFPM2.5 ratios in the range of 52 %–98 % for fresh emissions and ∼14 %–23 % degradation after
aging. Reductions of EFOC (∼7–9 g kg-1) after aging
are most apparent for boreal peats, with the largest degradation in low-temperature OC1 that evolves at < 140 ∘C, indicating the
loss of high-vapor-pressure semivolatile organic compounds upon aging. The
highest EFLevoglucosan is found for Russian peat (∼16 g kg-1), with ∼35 %–50 % degradation after aging. EFs for
water-soluble OC (EFWSOC) account for ∼20 %–62 % of
fresh EFOC.
The majority (> 95 %) of the total emitted carbon is in the
gas phase, with 54 %–75 % CO2, followed by 8 %–30 % CO. Nitrogen in
the measured species explains 24 %–52 % of the consumed fuel nitrogen, with an average of 35 ± 11 %, consistent with past studies that report
∼1/3 to 2/3 of the fuel nitrogen measured in biomass
smoke. The majority (> 99 %) of the total emitted nitrogen is
in the gas phase, with an average of 16.7 % as NH3 and 9.5 % as
HCN. N2O and NOy constituted 5.7 % and 2.9 % of consumed
fuel nitrogen. EFs from this study can be used to refine current emission
inventories.
Introduction
Globally, peatlands occupy ∼3 % of the Earth's land
surface, but they store as much as 610 gigatonnes (i.e., 610×1015 g) of carbon, representing 20 %–30 % of the planet's
terrestrial carbon (Page et al., 2011; Rein et al., 2009).
Peatland fires can persist for weeks to months and are dominated by the
smoldering phase as opposed to the flaming phase of biomass burning
(Stockwell et al., 2016; Hu et al., 2018). This results in lower
combustion efficiencies, increased particulate matter (PM) emissions, and
larger fractions of brown carbon (BrC) compared to black carbon (BC) or soot
(Pokhrel et al., 2016). Peat fires emit reduced nitrogen compounds (e.g.,
ammonia, NH3; and hydrogen cyanide, HCN); volatile and semivolatile
organic compounds (VOCs and SVOCs); and PM2.5 (PM with aerodynamic
diameters < 2.5 µm) (Akagi et al., 2011; Yokelson et al.,
2013). Peat smoke and ash affect ecosystem productivity, soil acidity,
biogeochemical cycling, atmospheric chemistry, Earth's radiation balance,
and human health. Warmer climates lower the water table in peatlands and
change the pattern, frequency, and intensity of the peatland fires causing
local- and regional-scale air pollution and visibility impairment (Page
et al., 2002; Turetsky et al., 2010, 2015a, b). For Southeast Asia,
fire-related regional air pollution and its effects on atmospheric
visibility, ecosystems, and human health have been addressed in many studies
(e.g., Behera et al., 2015; Betha et al., 2013; Bin Abas et al.,
2004; Engling et al., 2014; Heil and Goldammer, 2001; Kundu et al.,
2010; Levine, 1999; Hu et al., 2019; Tham et al., 2019; Fujii et al.,
2017; Dall'Osto et al., 2014).
Nitrogen, one of the most important plant nutrients, affects global carbon
and biogeochemical cycles (Crutzen and Andreae, 1990; Gruber and
Galloway, 2008). Deposition of oxidized and reduced nitrogen species from
biomass burning, such as gaseous nitric oxide (NO), nitrogen dioxide
(NO2), and NH3 as well as particulate nitrate (NO3-) and
ammonium (NH4+), alters terrestrial ecosystems (Chen
et al., 2010), while nitric acid (HNO3) contributes to soil
acidification and excessive nitrification that reduce plant resistance to
environmental stresses (Goulding et al., 1998). Gaseous
nitrogen oxides (NOx) affect atmospheric chemistry through (1) reactions with hydroxyl (OH) and peroxy (HO2+RO2) radicals; (2) conversion to nitrate radical (NO3), dinitrogen pentoxide
(N2O5), and acyl peroxy nitrates (particularly peroxyacetyl
nitrate, PAN), which are important NOx reservoirs; and (3) formation of
ozone (O3) and secondary organic aerosols (SOA) (Alvarado et al.,
2010; Cubison et al., 2011; Ng et al., 2007). While NH3 neutralizes
HNO3 to form particulate ammonium nitrate (NH4NO3), it may
also react with alkanoic acids to form alkyl amides, nitriles, and ammonium
salts that can also contribute to SOA formation (Na et al., 2007; Simoneit
et al., 2003; Zhao et al., 2013). In addition, NH3 interacts with SOA to form BrC that further influence the aerosol radiative forcing
(Updyke et al., 2012).
This study quantifies peat burning emission factors (EFs) for fresh and aged
multipollutant mixtures through controlled burns in a laboratory combustion
chamber with atmospheric aging simulated by an oxidation flow reactor (OFR).
These tests are applied to peat samples from diverse parts of the world.
Global distribution of peatlands (based on Yu et
al., 2010). Samples were obtained from Odintsovo, Russia; Pskov, Siberia;
black spruce forest, northern Alaska, USA; Putnam County Lakebed and
Everglades National Park, Florida, USA; Caohai and Gaopo, Guizhou, China;
and Borneo, Malaysia.
ExperimentFuel types
Peatlands are found all over the world, as illustrated in Fig. 1
(based on Yu et al., 2010), with large deposits found in the
northern USA and Canada, northern Europe, Russia/Siberia, and southeast
Asia. Eight types of peat fuels from different regions and climates were
collected for testing, including boreal (i.e., Odintsovo, Russia; and Pskov,
Siberia), temperate (i.e., black spruce forest, northern Alaska, USA),
subtropical (i.e., northern (Putnam County Lakebed) and southern (Everglades
National Park) Florida, USA; and Caohai and Gaopo, Guizhou, southern China),
and tropical (i.e., Borneo, Malaysia) peats.
Representative peat samples of 250–1150 g from the upper 20 cm of the
peatland surface were excavated for each region indicated in Fig. 1. As peat
is a heterogeneous mixture of decomposed plant material, it can be formed in
different wetlands under changing climates and nutrient contents
(Turetsky et al., 2015a). Supplement Fig. S1
shows that the appearance of peat fuels varies by region.
To quantify carbon (C), hydrogen (H), nitrogen (N), sulfur (S), and oxygen
(O) content, ∼2–3 g of each peat fuel was dried in a vacuum
oven (∼105∘C) for 2 h prior to elemental
analysis (Thermo Flash-EA 1112 CHNS/O Analyzer, Waltham, MA, USA).
Import and export regulations (USDA, 2010) require high-temperature heating
of soil/peat fuels as part of the sterilization process. Peat fuels were
heated to 90 ∘C and weighed every 24 h to achieve a stable dry
mass with ∼0.16 % moisture by weight content (after
∼96 h of heating). The low heating temperature (i.e.,
below the water boiling point) minimized VOC losses, although some compounds
with high volatilities could have been removed at 90 ∘C. To better
simulate the field conditions during peat fires, distilled–deionized water
(DDW) was added to rehydrate the dry peat and achieve a fuel moisture of
∼25 % (by weight) before each experiment
(Yatavelli et al., 2017). To examine the effects
of fuel moisture on emissions, additional experiments (n=3) were conducted
at 60 % fuel moisture content (by weight) for the Putnam (FL) peat.
Configuration for peat combustion experimental setup. (FTIR:
Fourier transform infrared spectrometer; OFR: oxidation flow reactor; OFR
lamps were operated at 2 and 3.5 V to simulate aging of ∼2 and 7 d, respectively.)
Experimental setup
The laboratory setup shown in Fig. 2 used a biomass combustion chamber with
a volume of ∼8 m3 (1.8 m (W) × 1.8 m (L) × 2.2 m (H))
(Tian et al., 2015). Instrument specifications
and operating principles are shown in Table S1 in the Supplement. The chamber is made of 3 mm thick aluminum to withstand high-temperature heating. A blower supplied
air filtered by a charcoal bed and a high-efficiency particulate air (HEPA)
filter near the bottom of the chamber to remove background gas and particle
contaminants. The ventilation rate was controlled by the blower and exhaust
fan at ∼2.65 m3 min-1, resulting in a smoke
residence time of ∼3 min in the chamber assuming a
well-stirred flow model.
For each test, ∼10–30 g of dried peat was placed in an
asbestos-insulated circular container on top of an induction heater that
provided heating during the first ∼5–10 min of combustion
(see Fig. S2). This method replaced a propane torch used in initial test
burns, thereby minimizing non-peat burning emissions. The smoldering process
is usually self-propagating and sustained by heat conduction and radiation,
with fuel mass continuously monitored by a scale underneath the induction
heater (Ohlemiller et al., 1979).
Continuous PM2.5 mass concentrations were monitored with a DustTrak
(TSI model 8532, Shoreview, MN, USA) (Wang et al.,
2009) (Table S1). When PM2.5 concentrations reached their maximum and
started to decline, the induction heater was turned off. The fuel was
consumed with diminished smoke emissions after ∼20 min.
Preliminary tests were conducted using ∼10–20 g of fuel and a
dilution ratio of ∼3 to 5, yielding sufficient particle
loadings on the filters (∼150–290 µg per 47 mm filter
disc). To achieve higher filter deposits of 300–600 µg per filter that
accommodate comprehensive organic speciation, additional fuels
(∼15–20 g) were added with the induction heater turned on for
another ∼10 min. Sampling continued until the
concentrations returned to background level.
Sampling ports for stack concentrations of carbon dioxide (CO2) and
multiple gases by Fourier transform infrared (FTIR; model DX 4015; Gasmet
Technologies Oy, Finland) spectroscopy were located ∼1 m
above the top of the chamber roof in the exhaust duct (Fig. 2). The FTIR
spectrometer measured gaseous emissions prior to dilution to obtain enhanced
signal-to-noise ratios for trace gases (Jaakkola et al.,
1998). An exhaust gas sample was drawn into the FTIR where the infrared (IR)
absorption spectra in the wave number range of 900–4200 cm-1 were
measured. The instrument software compares the measured absorption spectra
with reference gas absorption spectra in the calibration library to identify
gas species and calculate concentrations. Examples of reference gas spectra
and an Everglades (FL) peat sample spectrum are plotted in Fig. S3.
Smoke from the chamber was drawn through a dilution sampling manifold where
the exhaust was diluted with clean air to achieve cooling that allowed for
condensation of SVOCs. A portion of the exhaust was directed through a
potential aerosol mass (PAM)-OFR (Aerodyne Research Inc., Billerica, MA,
USA) to simulate atmospheric aging prior to quantification by the sampling
instruments shown in Fig. 2. The 185 and 254 nm (OFR185) ultraviolet (UV)
lamps in the OFR were operated at 2 and 3.5 V with 10 L min-1 flow
rate to simulate intermediate-aged (∼2 d) and well-aged
(∼7 d) emissions, assuming an average daily OH
concentration of 1.5×106 molecules cm-3. The estimated OH
exposures (OHexp) at 2 and 3.5 V were 2.6×1011 and 8.8×1011 molecules s cm-3 based on the measured decay of sulfur
dioxide (SO2) (Cao et al., 2019). Due to external OH reactivity from carbon monoxide (CO),
NOx, and other reactants, these OHexp levels represent upper
limits of the actual OH exposures inside the OFR (Peng et al., 2015; Li et
al., 2015).
Oxides of nitrogen were measured as NOx (the sum of NO and NO2)
and total reactive nitrogen (NOy, including NO, NO2,
N2O5, HNO3, HNO4, ClONO2, HONO, alkyl nitrates, and
PAN) by chemiluminescence NOx and NOy analyzers (Ballenthin et
al., 2003; Allen et al., 2018). The NOx analyzers placed upstream and
downstream of the OFR determined NOx changes with OHexp in the
OFR. There are known interferences for the nonselective catalytic converter
in the chemiluminescent NOx analyzer and for spectroscopic absorption
in the FTIR (Allen et al., 2018; Prenni et al., 2014; Villena et al.,
2012). The chemiluminescence monitor converts most nitrogenous compounds to
NO, with HNO3 and PAN being the most important potential interferents
(Winer et al., 1974). However, much of the available
HNO3 and PAN is removed by the tubing leading to the molybdenum
converter in the standard NOx analyzer, which is why the NOy
analyzer locates the converter at the inlet. Allen et al. (2018) found no
significant differences between NOx measurements of biomass burning
plumes when comparing a chemiluminescent analyzer with more specific UV
absorption measurements.
The following analyses are based on (1) the commercial NOx analyzers
for NO, NO2, and NOx (NO+NO2 as equivalent NO2); (2) the NOy analyzer for total reactive nitrogen; and (3) the FTIR
spectrometer for trace gas measurements of methane (CH4), NH3,
HCN, nitrous oxide (N2O), and 13 low-molecular-weight carbon compounds (C1–C6).
PM2.5 filter packs were sampled upstream and downstream
of the OFR to characterize fresh and aged emissions, respectively, with
MiniVol PM2.5 samplers (Airmetrics, Springfield, OR, USA) operated at
5 L min-1 flow rate per channel. PM2.5 mass, elements, carbon,
water-soluble organic carbon (WSOC), ions, carbohydrates, organic acids, and gaseous NH3 and HNO3 were obtained from the paired
upstream and downstream filter samples to examine changes in speciated EFs
and source profiles with photochemical aging. Average filter-based EFs are
examined by peat types and aging times (i.e., denoted as fresh 2 vs. aged 2
and fresh 7 vs. aged 7) (Chow et al., 2019).
The open face sampling manifold allows homogenous particle deposits on 47 mm
filters (Watson et al., 2017). To test the uniformity of
particle deposits, five individual punches were removed from the center and
each quadrant of the 47 mm quartz-fiber filter disc for carbon analyses.
Table S2 shows total carbon (TC = OC + EC) concentration variations of
1.7 % to 5 % across the filters for the five test burns, within the
overall uncertainty of the emission estimates.
Modified combustion efficiency and fuel-based emission factors
The modified combustion efficiency (MCE) is defined as the ratio of
background-subtracted CO2 to the sum of CO2 and CO (Ward
and Radke, 1993):
MCE=ΔCO2ΔCO2+ΔCO,
where ΔCO2 and ΔCO are CO2 and CO concentrations
above background. MCE provides a real-time indicator of the combustion
status (e.g., MCE > ∼0.9 for flaming and MCE
< ∼0.85 for smoldering).
Each burn was completed when concentrations of pollutants measured online
(i.e., CO, NOx, NOy, and PM2.5) returned to the
baseline/background levels. Dilution ratios ranging from 2.7 to 5 were taken
into account when calculating EFs. Fuel-based EFs are calculated based on
carbon mass balance, expressed as grams of emission per kilogram of dry fuel
(g kg-1) burned (Wang et al., 2012). For gaseous and particle
species i, the time-integrated EFi is
EFi=CMFfuelCiCCO2MCMCO2+CCOMCMCO+CCH4MCMCH4+∑jCothersjnj×MCMothersj+PMc×1000,
where CMFfuel is the carbon mass fraction of the fuel in kilograms of carbon per
kilogram of fuel; Ci, CCO2, CCO, CCH4, and Cothersj are the background-subtracted
concentrations for species i (e.g., nitrogen or PM2.5 species),
CO2, CO, CH4, and other carbon compound (C1–C6) species j in milligrams per cubic meter (mg m-3)
under standard conditions (temperature =293 K and pressure =1 atm),
respectively; PMc is the total carbon concentration of PM2.5 in milligrams per cubic meter (mg m-3); MC, MCO2, MCO, MCH4, and
Mothersj are the atomic or molecular weights of carbon,
CO2, CO, CH4, and carbon compound species j in milligrams per mole, respectively;
nj is the number of carbon atoms in carbon compound j; and the factor 1000
converts kilograms to grams. All concentrations are converted to stack concentration;
i.e., species measured after dilution are adjusted by the dilution ratio.
Equation (2) assumes that the carbon mass in unmeasured carbon compounds and other
emissions not listed above is negligible compared to that in CO2, CO,
CH4, measured carbon compounds (C1–C6), and PM2.5 carbon.
Estimation of wall losses
Gas and particle wall losses can result in some underestimation of measured
EFs, but it is well within the measurement uncertainties of ±15 %.
Losses can occur inside the combustion chamber, in the exhaust stack,
sampling lines, and inside the OFR. Due to the low surface-to-volume ratio
of the chamber (2.9 m-1) and short residence time (∼3 min) in this study, the gas and particle losses are expected to be low in
the combustion chamber. Grosjean (1985) estimated an NH3 loss
rate of 4–17×10-4 min-1 in a small Teflon chamber (3.9 m3) with a surface-to-volume ratio of 3.8 m-1, resulting in
< 0.5 % NH3 wall loss. Even though the NH3
accommodation coefficient might be higher for aluminum than Teflon
(Neuman et al., 1999), the chamber wall loss in this study
is expected to be < 5 % for NH3. To reduce wall losses of
sticky gases, the FTIR sampled exhaust gas from the stack without dilution,
as shown in Fig. 2. Approximately 9 % NH3 would encounter the stack
wall due to turbulent diffusion (Hinds, 1999). The maximum NH3
loss in the stack is < 9 %, and the maximum overall NH3 loss
is < 14 %. Losses of less sticky gases would be lower.
The particle wall loss rates by McMurry and Grosjean (1985) and
Wang et al. (2018) indicate < 5 % particle number losses for 10 nm–2.5 µm in a similar chamber.
Particle losses by turbulent diffusion in the stack are also low (< 0.5 %). For a 2 m long horizontal heated sampling line in this study
(Fig. 2), particle losses by diffusion and gravitational settling are
negligible (< 0.1 %) for 10 nm–1 µm particles and
∼6 % for 2.5 µm particles. Earlier measurements
showed that the dilution tunnel had ∼100 % penetration for
0.5–5 µm particles (Wang et al., 2012). Therefore,
maximum particle losses in this study are estimated to be < 5 %
for 10 nm–1 µm and < 10 % for 2.5 µm. Past
studies (Lambe et al., 2011; Bhattarai et al., 2018; Karjalainen et al.,
2016) showed that particle number losses through the OFR may be
∼50 % for 20 nm and < 10 % for > 100 nm particles, with a negligible effect on mass concentration.
Average peat composition* (dry weight percentage) for total
carbon (C), hydrogen (H), nitrogen (N), sulfur (S), and oxygen (O).
* Elemental analyses were performed using an elemental analyzer (Flash-EA1112 CHNS/O Analyzer, Thermo Fisher Scientific, Waltham, MA, USA). Each
dried peat sample (∼2–3 g) was submitted for combustion
analysis at 900 ∘C for C, H, N, and S in a helium/oxygen
atmosphere and at 1060 ∘C for O in a helium atmosphere. Three to
four replicate sample analyses were conducted for each type of peat to
obtain the average and standard deviations.
Results and discussionFuel composition
Table 1 shows that peat contains 44 % C–57 % C and 31 % O–39 % O with the
exception of the two Guizhou, China, peats (20 % C–30 % C and 21 % O–24 % O).
The carbon content (50.6 ± 2.5 % C) in the Borneo, Malaysia, peat is
within the range of carbon fractions reported for the Kalimantan and Sumatra,
Indonesia, peat (44 % C–60 % C) (Christian et al., 2003; Hatch et al.,
2015; Iinuma et al., 2007; May et al., 2014; Setyawati et al., 2017). The low
carbon content (20 % C–30 % C) of Guizhou peats is similar to the 28 % C–30 % C reported for two eastern North Carolina, USA, peats
(Black et al., 2016).
Hydrogen contents of 2 % H–7 % H in Table 1 are consistent with abundances
found elsewhere, including (1) ∼6 % H for northern
Minnesota, USA, peat (Yokelson et al., 1997); (2) ∼2 % H–3 % H for the eastern North Carolina peat
(Black et al., 2016); and (3) ∼5 % H–7 % H for Indonesian peats (Iinuma et al.,
2007; Christian et al., 2003; Hatch et al., 2015). Sulfur (S) contents are
below detection limits (< 0.01 %), and nitrogen contents are 1 % N–4 % N. Ratios of N/C are 0.02–0.08, consistent with the reported N/C ratios
of (1) 0.036 for Neustädter Moor, northern Germany
(Iinuma et al., 2007); (2) 0.017–0.04 for Ireland and
the United Kingdom (Wilson et al., 2015); (3) 0.02–0.03 for
Alberta and Ontario, Canada (Stockwell et al., 2014); (4) 0.062 for
Minnesota, USA (Yokelson et al., 1997); (5) 0.022–0.03 for
the eastern coast of North Carolina, USA
(Black et al., 2016); and (6) 0.036–0.039 for Kalimantan and Sumatra, Indonesia (Christian et al.,
2003; Hatch et al., 2015).
The sum of elements (i.e., C, H, N, S, and O) accounts for 91 %–98 % of
total mass except for the Guizhou peats (47 %–56 %). As Guizhou peats
appear to be a mixture of peat and soil, these samples may represent
degraded peats (Miettinen et al., 2017) or contain additional
minerals or high ash contents, similar to North Carolina peats
(44 %–62 % ash, Black et al., 2016).
Therefore, these peats were only used for preliminary testing of sample
ignition and heating to optimize burning conditions. Overall, the six other
peats in Table 1 represent biomes from different regions of the world.
Emission factors (EFs)
Table S3 summarizes the 40 peat combustion tests with the peat masses before
and after each burn. The afterburn residue may have contained unburned peat
as well as noncombustible ash. The residues were not analyzed for carbon
and nitrogen contents. A few samples were voided due to sampling
abnormalities. The following analyses are based on the 32 paired (fresh vs.
aged) samples at 25 % fuel moisture and 3 paired samples at 60 % fuel
moisture. The amount of fuel consumed per test ranged from 21 to 48 g for all
but Russian peat (14–15 g) due to limited supply.
PM2.5 mass concentrations, in the range of 328–2277 µg m-3,
are 1 to 2 orders of magnitude higher than those commonly measured at
ambient monitoring sites. Typical sample durations from ignition to
completion were ∼40–60 min, except for the Everglades
(FL) peats that took longer (up to 135 min). Similar particle loadings
(mostly within ±20 %) were found for downstream (aged) and
upstream (fresh) samples. The exception is Everglades (FL) peat, where
prolonged sample durations and 7 d aging times resulted in higher
downstream particle loadings with ratios of aged/fresh mass concentrations
ranging from 1.6 to 2.0.
Peat combustion emission factors (EFs) for CO2, CO, and
CH4a.
a Data acquired from this study are so designated.
b Only included number of samples reported.
c FM; fuel moisture content.
d FTIR: Fourier transform infrared spectroscopy. CH4 was acquired
by FTIR in this study.
e Obtained from Stockwell et al. (2014) as only the ratios of moles
compound/total moles carbon detected was reported in Yokelson
et al. (1997).
f NWR: National Wildlife Reserve.
g Reviews for atmospheric modeling and emission inventory development.
h From Ward and Hardy (1984); Yokelson et al. (1997, 2013).
i From Christian et al. (2003) for tropical peats.
j Detailed volatile organic gas emission factors for one of these
samples are reported by Koss et al. (2018).
Gaseous carbon emission factors
Individual and average carbonaceous gas EFs are summarized in Table S4. As
shown in Fig. S4, variations by biome are found among the different peats
with relative standard deviations ranging from 2 % to 27 %. The largest EFs
are found for CO2 (EFCO2), ranging from 994 to 1455 g kg-1,
which are 1 to 2 orders of magnitude higher than the corresponding EFCO
and EFCH4. Average EFCO2 varied by > 30 % among
biomes, ranging from 1073 ± 63 g kg-1 to 1400 ± 38 g kg-1 for the
Russian and Alaskan peats, respectively.
Muraleedharan et al. (2000) reported the first
laboratory-combustion EFs of 150–185 g kg-1 for EFCO2, 15–37 g kg-1 for EFCO, and 6–11 g kg-1 for EFCH4 on a wet mass
basis for Brunei peat with a 51.4 % moisture content. Table 2 shows
studies conducted over the past decade, with more field monitoring during
the 2015 El Niño–Southern Oscillation (ENSO) period in Indonesia. Open path (OP)-FTIR was commonly used to
acquire gaseous emissions with MCEs ranging from 0.77 to 0.86, consistent with
smoldering combustion. A limited number of burns (n of 1 to 6) were
conducted in laboratories using combustion chambers, whereas a larger number
of in situ field-burn samples (n of 17 to 35) were acquired for southeast
Asian peats (Wooster et al., 2018; Setyawati et al., 2017; Stockwell et
al., 2016).
Table 2 exhibits > 2-fold variations in EFCO2 among studies.
The highest EFCO2 with the lowest variability was found for tropical
peats (ranges 1331–1831 g kg-1 for smoldering). Average EFCO2
(1331 ± 78 g kg-1) for Malaysian peat (n=6) from this study is
∼16 % and ∼18 % lower than the 1579±58 and 1615 ± 184 g kg-1 for Peninsula, Malaysia
(Smith et al., 2018), and average boreal/temperate peats (Hu et al.,
2018), respectively. Malaysian peat EFCO2 measured in this study is 20 % lower than the 1681 ± 96 g kg-1, averaged from seven studies
of Kalimantan and Sumatra, Indonesia, peats (Christian et al.,
2003; Stockwell et al., 2014; Huijnen et al., 2016; Nara et al., 2017).
Overall average EFCO2 values (1269 ± 139 g kg-1, n=32)
from this study (Table S4) are ∼19 %–25 % lower than the
1563 ± 65 g kg-1 for peatland fires used in atmospheric models
(Akagi et al., 2011), 1550±130 g kg-1 in a recent review (Andreae, 2019), and 1703 g kg-1 (Christian et al., 2003) adopted by the 2014
Intergovernmental Panel on Climate Change (IPCC) for organic soil fire
inventories (IPCC, 2014). EFs derived from this study
cover four biomes which may improve global emission estimates.
Average EFCO is typically ∼12 %–15 % of
EFCO2 in the range of 157–171 g kg-1 for all but the two
Florida peats with 394 ± 46 g kg-1 (MCE =0.65±0.04)
and 93 ± 21 g kg-1 (MCE =0.90±0.03) for the Putnam and
Everglades peats, respectively (Tables S4 and 2). This is consistent
with a higher EFCO under lower MCEs reported by
Setyawati et al. (2017) – a 45-fold increase
from 3.1 ± 7.2 g kg-1 for flaming (MCE =0.998±0.005)
to 138 ± 72 g kg-1 for smoldering (MCE =0.894±0.055)
combustion.
Average EFCO values of 157–161 g kg-1 for boreal and temperate peats are
∼10 % lower than the 179 ± 61 g kg-1 from Hu et al. (2018). The overall average EFCO of 175 ± 92 g kg-1 from
this study is ∼4 % lower than the 182 ± 60 g kg-1 in Akagi et al. (2011), ∼30 % lower than the
250 ± 23 g kg-1 in Andreae (2019), and ∼15 %
lower than the 207–210 g kg-1 used in IPCC (2014).
Average EFCH4 is ∼0.3 %–0.9 % of EFCO2, lowest for
cold climates with 3.2–6.9 g kg-1 for the boreal and temperate peats
and 6.7–10.4 g kg-1 for the subtropical and tropical peats (Table S4).
Table 2 shows that EFCH4 values for Malaysian and Indonesian peats exceed
∼10 g kg-1 in five of the eight past studies. These EFs
are more in line with the 11.8 ± 7.8 g kg-1 in Akagi et al. (2011), 9.3 ± 1.5 g kg-1 in Andreae (2019), and 9–21 g kg-1
in IPCC (2014) but are higher than the average (6.6 ± 2.4 g kg-1) found in this study.
Emission factors depends on both fuel composition and combustion conditions.
Figure S5a shows that total measured gas and particle carbon increases with
fuel carbon content for the six types of peat. EFCO2 increases with
fuel carbon content (Fig. S5b) except for the Putnam (FL) peat, which has
the highest fuel carbon (56.6±0.37 %) but low EFCO2. It has high
EFCO and EFTC (Fig. S5c–d), consistent with its low MCE (0.65±0.04). EFCO and EFTC do not show a clear trend with fuel
carbon content; however, EFCH4 increases with fuel carbon (Fig. S5e)
but decreases with fuel oxygen content (Fig. S5f).
Gaseous nitrogen emission factors
Individual and average gaseous nitrogen species EFs are summarized in Table S5. EFNO and EFNO2 (Fig. S6b) are low in the range of 0.2–2.1 g kg-1. For fresh emissions, most of the NOx (NO+NO2) is
present as NO. After the OFR, NO decreased while NO2 increased, as
shown in Fig. S7. A low correlation coefficient (r=0.67) between the
downstream and upstream EFNOx suggests the changes of NO/NO2
ratios between the fresh and aged emissions as well as variabilities among
tests.
Peat combustion emission factors (EFs) for gaseous nitrogen
speciesa.
a Data acquired from this study are so designated.
b Data acquired from Fourier transform infrared (FTIR) spectroscopy for
this study.
c Data acquired from the NOx instrument upstream of the oxidation
flow reactor for this study.
d Data acquired from the NOy instrument for this study.
e Reported as NOx.
f The reported NOx as NO was converted to NOx as NO2 for
comparison.
g Reviews for atmospheric modeling and emission inventory development.
Table 3 shows that most studies do not report EFNO or EFNO2,
partially due to the low concentrations and large variabilities under
atmospheric aging. Stockwell et al. (2016, 2014) reported 0.31–1.85 g kg-1 EFNO and 2.31–2.36 g kg-1 EFNO2 for Indonesia
peats. These levels are much higher than the EFNOx (as NO2) of
0.75 ± 0.10 g kg-1 for Malaysian peat in this study.
Emissions for reactive nitrogen, EFNOy (as NO2), ranged from 0.61 to 6.3 g kg-1 with an average of 2.4 ± 1.4 g kg-1 (Table S5).
EFNOy > 2.5 g kg-1 are found for the two Florida peats
(Fig. S6c) with an average of 4.3 ± 1.1 g kg-1 for Everglades,
which reports the highest nitrogen content (3.93 ± 0.08 %) among
peats (Table 1). Figure S5g shows that EFNO increases with fuel
nitrogen content, while EFNO2 is not dependent on fuel nitrogen content
(Fig. S5h). Because EFNO is higher than EFNO2, EFNOx and
EFNOy increase with fuel nitrogen content (not shown). Figure S8 shows
that ∼74 % of the NOy is NOx with a high correlation coefficient (r=0.93). Nitrogen oxides are typically converted
to other oxidized nitrogen species within 24 h after emission
(Seinfeld and Pandis, 1998; Prenni et al., 2014). The ratio of
NOx/NOy has been used to infer photochemical aging (Kleinman et
al., 2003, 2007; Olszyna et al., 1994; Parrish et al., 1992).
The high NOx/NOy ratios suggest that NOx had not been converted to
other reactive nitrogen species in the diluted peat plume.
Nitrous oxide (N2O), an inert form of oxide from nitrogen with an
atmospheric lifetime of ∼110 years, commonly emitted from
fossil fuel, solid waste fertilizers, and biomass combustion, is a
greenhouse gas defined by the U.S. EPA (2016). Table S5 shows that EFN2O
are similar to EFNOy except for Everglades (FL) peat with low
EFN2O (1.5 ± 0.3 g kg-1), in the range of 1.1–4.4 g kg-1 and average of 2.0 ± 0.7 g kg-1. The highest average
EFN2O (3.6 ± 0.6 g kg-1) is found for Putnam (FL) peat (Fig. S6c).
Hydrogen cyanide (HCN), a known emission from biomass burning (Li et al.,
2000; Stockwell et al., 2014), exhibits > 7-fold differences
(1.8–14 g kg-1) in EFHCN (Table S5). The average EFHCN (11.5±2.3 g kg-1) for Putnam (FL) peat is 2- to 5-fold higher than
for the other biomes (Fig. S6a). Table 3 shows large EFHCN variations
among studies, from 0.73 ± 0.50 g kg-1
(Ireland, Wilson et al., 2015) to 5.75 ± 1.60 g kg-1 (Indonesia, Stockwell et al., 2016). More consistent EFHCN values
are found for tropical peats in the range of 3–6 g kg-1. Average
EFHCN values in this study, 4.7 ± 3.1 g kg-1, are in line with the
5.0 ± 4.9 and 4.4 ± 1.2 g kg-1 reported by Akagi et al. (2011) and Andreae (2019).
EFNH3 values (0.4–8.3 g kg-1) are of the same magnitude as EFHCN
(Fig. S6a) and independent of fuel nitrogen content (Fig. S5i) except for
the Everglades (FL) peat (9–18 g kg-1), which has the highest fuel
nitrogen content. Total reduced nitrogen emissions, EFNH3+
EFHCN, for the two Florida peats (12–25 g kg-1) are
∼2- to 3-fold higher than those for other regions. Table 3
also shows high variabilities in EFNH3 among studies (1–12 g kg-1). The overall average of 5.6 ± 4.8 g kg-1 in this study
is consistent with the 4.2 ± 3.2 g kg-1 in Andreae (2019) but
∼50 % of the 10.8 ± 12.4 g kg-1 in Akagi et al. (2011). The high standard deviations associated with these averages
signify large variabilities among experiments.
Figure S9a shows some difference in EFNH3 determined by FTIR and the
impregnated filter, especially at high concentrations. The regression slope
shows that EFNH3 by the FTIR was ∼22 % lower than
that of filters with a correlation coefficient of 0.76. Variable baselines
in the FTIR measurements along with some nitrogen content in the diluted air
and breath NH3 (Hibbard and Killard, 2011) in the testing
laboratory may have contributed to these variations. The impregnated filter
collects all of the NH3 over the sampling period, including amounts
that are below the FTIR detection limits, so it is probably better
representing the time-integrated EFNH3. Reduction of EFNH3 is most
apparent after atmospheric aging in Fig. S9b (slope of 0.11), with 2–14 g kg-1 in fresh emissions and reduced to ∼0.5–3 g kg-1 after aging.
PM2.5 mass and carbon emission factors
Continuous PM2.5 from the DustTrak with the factory calibration factor
yielded PM2.5 EFs 3 to 5 times higher than of those derived from
gravimetric analyses, higher than the 2-fold mass differences by Wooster
et al. (2018). This discrepancy is well known as the factory calibration
uses Arizona road dust with a size distribution that is much coarser than
that of biomass burning. Therefore, EFPM2.5 is calculated from the
filter samples. Chow et al. (2019) present the
species abundances in PM2.5 mass for this study based on the average
fresh and aged profiles, separated by 2 and 7 d photochemical aging times
simulated with the OFR (Aerodyne, 2019). The same approach is used
in Table S6 to compare fresh and aged particle EFs. Comparisons between
combined fresh vs. aged EFs for PM2.5 mass, carbon (OC, EC, and TC),
and levoglucosan for individual tests are shown in Table S7.
Figure S10 shows that EFPM2.5 varies > 4-fold (14–61 g kg-1) for different peats without large differences between fresh and
aged emissions. EFOC varied from 9 to 44 g kg-1 while EFEC
(0.00–2.2 g kg-1) were low (Table S7). The majority of EFPM2.5 values consist of EFOC, with average EFOC/ EFPM2.5 ratios of 52 %–98 % by peat type in fresh emissions, followed by ∼14 %–23 %
reductions after aging, with the exception of Putnam (FL) peats (remained at
69 %–70 %).
Reductions of EFOC after ∼7 d of photochemical aging
are most apparent (∼7–9 g kg-1) for the boreal peats,
with the largest degradation for low-temperature OC1 (evolved at
140 ∘C during carbon analysis), indicating losses of high-vapor-pressure SVOCs upon aging (Table S6). The two Florida peats exhibit an
initial EFOC decrease of ∼2 g kg-1 after 2 d
aging, but with an increase of 1.8–4.0 g kg-1 after 7 d. However,
these changes are less than the standard deviations associated with the
averages.
EFWSOC varies by 5-fold (3–16 g kg-1) with over a ∼50 % increase for the Putnam (FL) and Malaysian peats after 7 d.
Average EFWSOC by peat type accounts for ∼16 %–36 % and
∼20 %–62 % of fresh EFPM2.5 and EFOC,
respectively. From 2 to 7 d aging, Fig. S11 shows reduced correlation
coefficients (r from 0.86 to 0.76 for PM2.5, from 0.88 to 0.84 for OC,
and 0.94 to 0.68 for WSOC).
Peat combustion emission factors (EFs) for PM2.5 mass and
carbona.
Average emission factor (g kg-1) Sampling locationSampling methodModifiedCarbon analysisEFPM2.5cEFOCEFECRatio(reference)(no. of samples)combustionmethodb(PM size)(EFTC/ EFPM)efficiency(MCE)Indonesia (locationLab0.89TOF-AMS and SP234.934.50.010.99not specified)(PM1)k(OA)k(BC)kMay et al. (2014)ReviewslPeatlands fromNANANANA6.23 ± 3.60.2 ± 0.11NAtropical forestAkagi et al. (2011)SmolderingNANANA19.2 ± 6.88.38 ± 4.140.36 ± 0.280.46Boreal/temperateNANANA17.3 ± 6.08.8 ± 4.240.28 ± 0.180.52Smoldering tropicalHu et al. (2018)Peat firesNANANA17.312.40.190.73Andreae (2019)
a Data acquired from this study are so designated.
b The IMPROVE_A protocol reports OC and EC by
thermal/optical reflectance (TOR, Chow et al.,
2007); the NIOSH and NIOSH5040 reports OC and EC by thermal/optical
transmittance (NIOSH, 1999); VDI is the German Industrial Standard (VDI,
1999); TOF-MS: time-of-flight mass spectrometer
(Drewnick et al., 2005); and SP2: single-particle soot
photometer (DMT Inc., Boulder, CO, USA) measures black carbon (BC) by
laser-induced incandescence technique (Stephens et al.,
2003).
c Size fraction is PM2.5 except where otherwise noted.
d FM; fuel moisture.
e Includes averages of all fresh and all aged emission factors (EFs) for
the 25 % fuel moisture (i.e., grouped fresh 2 and fresh 7 vs. aged 2 and
aged 7 shown in Table S7).
f Comparisons between 25 % and 60 % fuel moisture content are only
made with fresh 2 vs. aged 2 of Putnam (FL) peats.
g Sum of five stages of Berner Impactor with 0.05–0.14, 0.14–0.42,
0.42–1.2, 1.2–3.5, and 3.5–10 µm size ranges.
h National Wildlife Refuge, eastern NC.
i From Jayarathne et al. (2018).
j BC by micro-Aethalometer (AE 51) (Cheng et al., 2013; Wooster et al.,
2018).
k PM1 and organic aerosol (OA) acquired from TOF-MS measurements (Drewnick et al.,
2005).
l Reviews for atmospheric modeling and emission inventory development.
As WSOC is part of the OC, the WSOC / OC ratio can be used to illustrate
atmospheric aging. Figure S12 shows that WSOC / OC ratios increased by 6 %–16 % after aging. This is attributed to a combination of oxygenation of the
aged organic emissions and the reduction of EFOC (Table S7). The
increase in WSOC / OC ratios may also be due to photochemical transformation
of primary OC to WSOC and/or formation of water-soluble SOA during
atmospheric aging (Aggarwal and Kawamura, 2009; Agarwal et al., 2010).
Table 4 compares filter-based PM mass and carbon from different studies.
Since different carbon protocols yield different fractions of OC and EC
(Watson et al., 2005), the analytical protocols are listed. Most studies
follow either IMPROVE_A TOR (Chow et al., 2007) or NIOSH
thermal/optical transmittance (TOT) protocols (NIOSH, 1999). As the
transmittance pyrolysis correction (i.e., TOT) accounts for charred OC both
on the filter surface and organic vapor within the filter substrate, lower
EFEC values are expected as compared to TOR (Chow et al., 2004). To remove the
OC and EC split uncertainty, TC to PM mass ratios are listed for comparison.
Two studies reported BC from a micro-Aethalometer (Wooster
et al., 2018) or a single-particle soot photometer (SP2; May et al.,
2014). As BC levels are very low, not many differences can be distinguished
between BC and EC.
Most studies report EFPM2.5 with a few exceptions for EFPM10
(Kuwata et al., 2018; Iinuma et al., 2007) and EFPM1 (May et al.,
2014). As most of the PM10 is in the PM2.5 fraction for biomass
combustion, particle size fractions have a minor effect on PM EFs (Geron
and Hays, 2013; Hu et al., 2018).
Table 4 shows that the majority of EFPM2.5 lies in the range of
∼20–50 g kg-1 with the exception of very low
EFPM2.5 values of 4–8 and 6–7 g kg-1 reported by
Bhattarai et al. (2018) and
Black et al. (2016). These are
probably due to low filter mass loadings and limited testing (n of 1 to 3),
which may result in large uncertainties in gravimetric mass.
Average carbonaceous species abundances in total emitted carbon
(the sum of carbon in CO2, CO, CH4, carbon compounds, and PM2.5 total
carbon (TC = OC + EC)). Numbers on top of the bars are average modified
combustion efficiencies (MCEs) and the number of samples in each average. The
carbon compounds include hydrogen cyanide (HCN), formaldehyde (CH2O),
methanol (CH3OH), formic acid (HCOOH), carbonyl sulfide (COS), ethylene
(C2H4), ethane (C2H6), acetaldehyde (C2H4O),
ethanol (C2H5OH), acetic acid (CH3COOH), propane
(C3H8), acrolein (C3H4O), acetone (C3H6O),
3-butadiene (C4H6), benzene (C6H6), hexane
(C6H14), phenol (C6H5OH), and chlorobenzene
(C6H5Cl) acquired by Fourier transform infrared spectrometry.
Ratio of emitted over consumed nitrogen for each type of peat
(emitted nitrogen is the sum of nitrogen in HCN, NH3, NO, NO2, and
NOz (NOy-NOx), N2O, HNO3, and PM2.5 ions
(NO2-+NO3-+NH4+); and the consumed
nitrogen is the product of percent fuel nitrogen content and mass of fuel
burned).
Despite different carbon analysis methods, most EFOC lies in the range
of ∼5–30 g kg-1 with the exception of EFOC (37 g kg-1) for Putnam (FL) and EFOA (organic aerosol, 34.5 g kg-1)
for Indonesian peat measured by a time-of-flight mass spectrometer (May
et al., 2014). Most studies show that EFTC accounts for ∼60 %–85 % of the EFPM2.5, with low EFEC (0.02–1.3 g kg-1).
EFWSOC values of 6–7 and 4–6 g kg-1 for the Alaskan and Malaysian peats
from this study are consistent with the 6.7 and 3.1 g kg-1 from German
and Indonesian peats in Iinuma et al. (2007),
respectively. EFLevoglucosan exhibits > 2 orders of
magnitude variabilities among the biomes with 0.24–16 and
0.24–9.6 g kg-1 in fresh and aged emissions, respectively.
Past studies show that the extent of levoglucosan degradation depends on OH
exposure in the OFR, organic aerosol composition, and vapor wall losses
(e.g., Bertrand et al., 2018a, b; Hennigan et al., 2010; Hoffmann et
al., 2010; May et al., 2012; Lai et al., 2014; Pratap et al., 2019). Potential
chemical pathways for the formation of organic species in biomass combustion
emissions were proposed by Gao et al. (2003) that suggested
the fragmentation of levoglucosan to C3–C5 diacids, followed by oxalic acid,
acetic acid, and formic acid. This is consistent with the increases in
EForganic acids after atmospheric aging, as shown in Table S6.
However, detailed chemical mechanisms need to be further investigated.
The highest EFLevoglucosan is found for the fresh Russian peats (15.8±2.9 g kg-1), and this is diminished by 45 % after 7 d
aging (8.8 ± 2.1 g kg-1). Few studies report EFLevoglucosan
and results are highly variable. The EFLevoglucosan of 0.57 g kg-1
in PM2.5 (converted from 46 mg g-1 OC) by Jayarathne et al. (2018) is
∼23 % of the 2.5 g kg-1 by Iinuma
et al. (2007), both for Indonesia peats. The EFLevoglucosan of 0.5–1.0 g kg-1 from fresh Malaysian peat in this study is comparable to 0.57 g kg-1 by Jayarathne et al. (2018). The 4.6 g kg-1 of
EFLevoglucosan for the northern German peat (Iinuma
et al., 2007) is higher than the 1.2–4.7 g kg-1 found for the average
Siberian and Alaskan peats in this study.
EFs for ionic nitrogen species are low (< 0.1 g kg-1) in fresh
emissions. Both EFNH4+ and EFNO3- increase with 7 d
aging – > 0.5 g kg-1 EFNH4+ for all peat and
> 1 g kg-1 EFNO3- for all but Russian (0.79±0.08 g kg-1) and Putnam (FL) peats (0.66 ± 0.08 g kg-1), consistent with the formation of secondary inorganic aerosol.
Effect of fuel moisture content on emission factors
Only a few studies examine the effects of fuel moisture on peat emissions
with inconsistent results. An early study by McMahon et al. (1980)
reported high emissions for total suspended particle (TSP, ∼ < 30–60 µm) of 30 ± 20 g kg-1 for dry (< 11 % moisture) as compared to 4.1 ± 3.8 g kg-1 (after the first
24 h) for wet (53 %–97 % moisture) organic soil. Rein et al. (2009) found higher CO2 (but not CO) yields while increasing
fuel moisture to 600 % for tests of boreal Scotland peats in a cone
calorimeter which continuously supplies heat to the fuel. Smoldering
combustion is possible with high in situ fuel moisture contents when surrounding
peat provides insulation and heat from combustion is available for drying
just before the advancing front, but such samples will not burn in the
laboratory. Watts (2013) sustained lab-based peat
smoldering from a cypress swamp (FL) at ∼250 % moisture
content, which appears to be a maximum.
Table 2 shows that increasing moisture content from ∼25 %
to ∼60 % for the three Putnam (FL) peats resulted in an 11 % increase in EFCO2 but reductions of 20 % EFCO and 12 %
EFCH4. No consistent variabilities are found for nitrogen species
(Table 3), with negligible changes in EFNH3 and EFHCN; a 13 %–30 % reduction in EFNO, EFNOx, and EFNOy; and
a 45 % increase in EFNO2 and 9 % increase in EFN2O. On the
other hand, a reduction of ∼30 % EFPM2.5 is found
(Table 4) as fuel moisture increased from 25 % to 60 %. Higher fuel
moisture contents typically result in less efficient burning conditions,
thereby increasing CO and reducing MCE (Chen et al., 2010).
However, an opposite trend is found with EFCO reduced from 394 ± 46 to 315 ± 10 g kg-1 and MCEs increased from 0.65 ± 0.04
to 0.72 ± 0.01. It is hypothesized that, at higher fuel moisture
contents, combustion residence time is slowed enough so that radiant heat
transfer from ignited particles to uncombusted areas of peat can be greater,
thus increasing the combustion efficiency. It is also possible that the
higher water content results in a water–gas shift reaction that converts CO
and water to CO2 and hydrogen. Overall, the EFs for ∼60 % moisture contents are comparable to EFs for the six other peats with
∼25 % moisture content.
Increased (∼25 % to 60 %) fuel moisture yields a
∼20 % reduction in fresh EFOC, much lower than the
35 %–43 % reduction (∼25 % to 50 % moisture) reported by
Chakrabarty et al. (2016) for the Siberian and Alaskan peats. By
increasing fuel moisture, Chakrabarty et al. (2016) also reported an increase
in EFCO2 by 20 % but a ∼75 % reduction and 35 %
increase in EFCO for Siberian and Alaskan peats, respectively, based on
a single sample.
Distribution of carbon and nitrogen species
Figure 3 shows the distribution of carbonaceous species. Because the EFs are
calculated based on the carbon mass balance method (Eq. 2), the total
emitted carbon is assumed to be the same as total consumed carbon. The
majority (> 90 %) of total emitted carbon is present in the
gas phase, with 54 %–75 % CO2, followed by 8 %–30 % CO. On average,
emitted carbon includes 69.8 ± 7.5 % CO2, 14.8 ± 6.5 % CO, 1.0 ± 0.3 % CH4, 9.6 ± 2.4 % volatile carbon
compounds, and 4.8 ± 1.3 % PM2.5 TC. The highest (30 ± 4 %) and lowest (8.4 ± 1.9 %) CO abundances for the Putnam (FL)
and Everglades (FL) peats are consistent with the lowest and highest average
MCEs of 0.65 and 0.90, respectively.
The nitrogen budget in Fig. 4 accounts for 24 %–52 % of nitrogen in the
consumed fuel. Since burn temperatures are below those at which NOx
forms from oxygen reactions with N2 in the air; most of the nitrogen in
emissions derives from the nitrogen content of the fuels.
Kuhlbusch et al. (1991) found N2 emissions constituted an
average of 31 ± 20 % of nitrogen in consumed grass, hay, pine
needle, clover, and wood fuels. Since N2 measurements require
combustion in N2-free atmosphere (e.g., a He-O2 mixture), N2
was not quantified here, but it was probably emitted in similar quantities.
Isocyanic acid (HNCO) is another important nitrogen-containing compound
found in biomass burning emissions (Roberts et al., 2011).
Koss et al. (2018) report a 0.16 g kg-1 nitrogen-equivalent EF (0.5 g kg-1 for HNCO) for a peat sample,
comparable to EFs for several of the measured nitrogen compounds summarized
in Table 3. Other nitrogen-containing gases reported by
Koss et al. (2018) with EFs
> 0.1 g kg-1 include acetonitrile (CH3CN), acetamide
(CH3CONH2), benzonitrile (C6H5CN), and pyridine +
pentadienenitriles (C5H5N), which could account for part of the
unmeasured nitrogen in emissions. Neff et al. (2002) found
that organic nitrogen formed from photochemical reactions of hydrocarbon
with NOx plays an important role in the global nitrogen cycle.
Approximately 30 ± 16 % of Neff et al.'s total nitrogen was from
organic nitrogen, similar to the 25 % of total nitrogen deposition flux
reported by Jickells et al. (2013). Alkaloids, dissolved organic
nitrogen, along with nitroaromatic compounds have been reported (e.g.,
Benitez et al., 2009; Laskin et al., 2009; Kuhlbusch et al., 1991; Koppmann et
al., 2005; Kopacek and Posch, 2011; Stockwell et al., 2015).
The majority (> 99 %) of the measured nitrogen in emissions is
in the gas phase. On average, 16.7 % of the fuel nitrogen was emitted as
NH3 and 9.5 % was emitted as HCN. N2O and NOy constituted
5.7 % and 2.9 % of nitrogen in the consumed fuel. NH3 emissions
accounted for 26 %–28 % of consumed nitrogen for Everglades (FL) and
Malaysian peats, while HCN emissions dominated fuel nitrogen(13 %–17 %) for
the Putnam (FL) and Malaysian peats. The fraction of N2O emissions in
Malaysian peat nitrogen (10.3 ± 1.1 %) was more than twice the
fractions found for the other regions, with reactive nitrogen (NOy) only
accounting for 2 %–4 % of the fuel nitrogen. The sum of NH3 and HCN
nitrogen ranged from 35 % to 39 % of consumed nitrogen for the Malaysian and
Everglades (FL) peats, which is about three times the fraction for Russian
peat.
Lobert et al. (1990) point out the importance of
nitrogen-containing gases in biomass burning for the atmospheric nitrogen
balance. On average, the emitted nitrogen includes 17 ± 10 %
NH3, 9.5 ± 3.8 % HCN, 5.7 ± 2.5 % N2O, 2.8±1.0 % NOy (including NOx), and 0.14 ± 0.18 %
of PM nitrogen (sum of NO2-, NO3-, and NH4+).
The average nitrogen budget accounts for 35 ± 11 % of the total
consumed nitrogen, consistent with past studies showing that around
one- to two-thirds of the fuel nitrogen is accounted for during biomass
combustion.
Summary and conclusions
This paper reports fuel composition and emission factors (EFs) from
laboratory chamber combustion of six types of peat fuels representing boreal
(Russia and Siberia), temperate (northern Alaska, USA), subtropical
(northern and southern Florida, USA), and tropical (Borneo, Malaysia)
climate regions. Dried peat fuel contains 44 %–57 % carbon (C), 31 %–39 %
oxygen (O), 5 %–6 % hydrogen (H), 1 %–4 % nitrogen (N), and < 0.01 % sulfur (S). The nitrogen to carbon ratios are low, in the range of
0.02–0.08, consistent with peat compositions reported in other studies.
Thirty-two tests with 25 % fuel moisture were reported with predominant
smoldering combustion conditions (MCE =0.82±0.08). Average
fuel-based EFs for CO2 (EFCO2) are highest (1400 ± 38 g kg-1) and lowest (1073 ± 63 g kg-1) for the Alaskan and
Russian peats, respectively. EFCO and EFCH4 are ∼12 %–15 % and ∼0.3 %–0.9 % of EFCO2 in the range of
∼157–171 and 3–10 g kg-1, respectively. The
exception is the two Florida peats, reporting the highest (394 ± 46 g kg-1) and lowest (93 ± 21 g kg-1) EFCO for Putnam and
Everglades, respectively.
Filter-based EFPM2.5 varied by > 4-fold (14–61 g kg-1)
without appreciable changes between fresh and aged emissions. The majority
of EFPM2.5 consists of EFOC, with average EFOC/ EFPM2.5
ratios by peat type in the range of 52 %–98 % in fresh emissions, followed
by ∼14 %–23 % reduction after aging with the exception of
Putnam (FL) peats (retained at 69 %–70 %). Reduction of EFOC
(∼7–9 g kg-1) are most apparent for boreal peats with
the largest decrease in low-temperature OC1 (evolved at 140 ∘C),
suggesting the loss of high-vapor-pressure semivolatile organic compounds
during aging. EFs for water-soluble OC (EFWSOC) account for
∼20 %–62 % of EFOC with ∼6 %–16 %
increase in EFWSOC/ EFOC ratios after aging. The highest
EFLevoglucosan is found for Russian peat (15.8 ± 2.9 g kg-1)
with a 45 % degradation after aging.
The majority (> 90 %) of the total emitted carbon is in the
gas phases with 54 %–75 % CO2, followed by 8 %–30 % CO. The nitrogen
budget only explains 24 %–52 % of the consumed nitrogen, with an average of
35 ± 11 %, consistent with past studies that around one-
to two-thirds of the total nitrogen is lost upon biomass combustion. The
majority (> 99 %) of the total emitted nitrogen is in the gas
phase, dominated by the two reduced nitrogen species with 16.7 % for
NH3 and 9.5 % for HCN. N2O and NOy are detectable at 5.7 % and 2.9 % abundance. EFs from this study can be used to refine
current emission inventories.
Data availability
The data of this study are available from the authors upon request.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-14173-2019-supplement.
Author contributions
JGW, JCC, JC, L-WAC, and XW jointly designed the study, performed the data
analyses, and prepared the manuscript. QW, JT, and SSHH carried out the peat
combustion experiments. SG conducted emission factor calculations. ACW
acquired peat fuels and provided technical advice on the peat fuel process.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This research was primarily supported by the National Science Foundation
(NSF, AGS-1464501 and CHE-1214163) as well as internal funding from both the
Desert Research Institute, Reno, NV, USA, and Institute of Earth
Environment, Chinese Academy of Sciences, Xi'an, China. The Caohai and Gaopo
peat samples were provided by Pinhua Xia of Guizhou Normal University,
Guizhou, China, and Chunmao Zhu of the Japan Agency for Marine-Earth
Science and Technology, Yokosuka, Japan.
Financial support
This research has been supported by the U.S. National Science Foundation (grant nos. AGS-1464501 and CHE-1214163) as well as the National Atmospheric Research Program (2017YFC0212200) and the National Research Program for Key Issues in Air Pollution Control (DQGG0105) in China.
Review statement
This paper was edited by James Roberts and reviewed by two anonymous referees.
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