In Situ Tropical Peatland Fire Emission Factors and Their Variability, as Determined by Field Measurements in Peninsula Malaysia

Abstract

Fires in tropical peatlands account for >25% of estimated total greenhouse gas emissions from deforestation and degradation. Despite significant global and regional impacts, our understanding of specific gaseous fire emission factors (EFs) from tropical peat burning is limited to a handful of studies. Furthermore, there is substantial variability in EFs between sampled fires and/or studies. For example, methane EFs vary by 91% between studies. Here we present new fire EFs for the tropical peatland ecosystem; the first EFs measured for Malaysian peatlands, and only the second comprehensive study of EFs in this crucial environment. During August 2015 (under El Niño conditions) and July 2016, we embarked on field campaigns to measure gaseous emissions at multiple peatland fires burning on deforested land in Southeast Pahang (2015) and oil palm plantations in North Selangor (2016), Peninsula Malaysia. Gaseous emissions were measured using open‐path Fourier transform infrared spectroscopy. The IR spectra were used to retrieve mole fractions of 12 different gases present within the smoke (including carbon dioxide and methane), and these measurements used to calculate EFs. Peat samples were taken at each burn site for physicochemical analysis and to explore possible relationships between specific physicochemical properties and fire EFs. Here we present the first evidence to indicate that substrate bulk density affects methane fire EFs reported here. This novel explanation of interplume, within‐biome variability, should be considered by those undertaking greenhouse gas accounting and haze forecasting in this region and is of importance to peatland management, particularly with respect to artificial compaction.

Review of emissions from smouldering peat fires and their contribution to regional haze episodes

“…Uncertainties in peat fire EF determination and total emission estimates Theoretically, EFs can be calculated by using species mass flux and dry fuel mass loss rate (Eqn 2); however, the mass loss rate is difficult to obtain under most measurement conditions, especially for field measurements (Huijnen et al 2016;Stockwell et al 2016;Smith et al 2018). As a result, a carbon mass balance approach is widely used to calculate the EFs from peat fires.…”

“…The EMR of X is often denoted by 'DX' : DCO 2 is the EMR of CO 2 ; DCO is the EMR of CO. Yokelson et al (1997) Boreal and temperate peat fire MCE data source: Yokelson et al (1997);Stockwell et al (2014);Black et al (2016); Wilson et al (2015); Chakrabarty et al (2016). Tropical peat fire MCE data source: Christian et al (2003); Stockwell et al (2014);Stockwell et al (2016);Smith et al (2018). It is noticeable that Geron and Hays (2013) reported MCE in the smouldering ground fire field measurement at Green Swamp (MCE ranged from 65 to 80%).…”

“…Meyer et al (2012) found that for tropical savanna fires with a larger range of MCE (,0.7 to 0.99), an exponential relationship provides a better empirical description (R 2 ¼ 0.74) between MCE and CH 4 EFs. However, during the measurements of smouldering fires, little or no dependence of EFs on MCE was observed Burling et al 2011;Stockwell et al 2016;Smith et al 2018).…”

Dominant contribution of oxygenated organic aerosol to haze particles from real-time observation in Singapore during an Indonesian wildfire event in 2015

“…The BBOA concentration increased at noontime, although no significant local source of biomass burning was available during the P2 period. The BBOA enhancement at noontime could be due to the transport of biomass burning plume event from Peninsula Malaysia that 25 might occur during the short P2 period (Miettinen et al, 2017;Smith et al, 2017). The PBOA concentration did not vary significantly during the P2 period, suggesting that it might not be produced locally.…”

“…The BBOA contribution was relatively similar (~14%) during both periods, although the average BBOA concentration was three-time higher during the P1 period than the P2 period. The consistent contribution of BBOA during both periods might indicate an influence of other sources of BBOA (e.g., wildfires in Peninsular Malaysia (Miettinen et al, 2017;Smith et al, 2017)) in addition to wildfires in Indonesia. 10…”