Global_Environmental_Research_Vol.27No.1
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5.1 Key Indicators of Peatland Fire Aerosols A time-of-flight aerosol chemical speciation monitor (ToF-ACSM) provides continuous online size and non-refractory (NR) chemical composition data on individual sub-micron aerosol particles without filter sampling It produces ensemble-average mass spectra for organic and inorganic species, and organic aerosol (OA) mass spectra can be deconvolved in combination with different statistical techniques sources, composition and atmospheric processing of OAs (e.g., Chen et al., 2020). In recent years, a research group based at Nanyang Technological University (hereafter “the Singapore group”) used ToF-ACSM to characterize the physical and chemical properties of organic aerosols during the 2015 haze episode in Singapore 65, 73, 74. However, there are no field studies of IPF aerosol using ToF-ACSM in other ASEAN countries or at peatland fire sites in our dataset. Laboratory experiments are a powerful approach for determining in-depth chemical compositions of fresh and aged peat-burning aerosols and their influencing factors using ToF-ACSM under controlled environmental conditions. Laboratory experiments on aerosols from Indonesian-peat and other biomass combustion have been 65, 66, 69, 81, 82, 86, 102, 109, 112 investigated by the Singapore group using a flow-type reactor with ToF-ACSM, and by Ahern et al.81 using batch-type dual chambers with an Aerodyne high‐resolution AMS and a proton transfer reaction mass 44 4. Aerosol Mass Spectra Analysis for Chemical Characterization 5. Source Apportionment of PM during Haze Episodes PM2.5 collected in Kuala Lumpur during different monsoon seasons88, and PM0.1, PM1 and PM2.5 collected in southern Thailand during normal, partial and strong haze periods in 2019119. Bivariate plots of Flt/(Flt+Pyr) versus Ind/(Ind+BgP) indicated that the major sources of PM during strong haze periods were predominantly from biomass burning in the case of Thailand119. Two other studies indicated different sources without specifying a definite source of the Supplementary Information shows three bivariate plots of PAH ratios for haze and non-haze periods using our dataset. In Fig. S6 (A), the three blue circles in the upper right region (biomass burning region) are clearly distinguished from the other data. The data are from samples collected at three sites in Riau, Indonesia during the 2015 fire episode28, and the sampling sites were 100 m, 60 km and 220 km away from the fire source. However, no definite sources of haze were identified for the other data. Moreover, contributions from local sources can IPF-derived haze15. dominate Unfortunately, the concentration of each PAH congener is either indicated only as graphical data (Thailand data119 mentioned above) or not available in some reports. More quantitative data may improve source identification of IPF-derived haze. the contribution of (Fröhlich et al., 2013). to estimate the haze. Figure S6 Y. FUJII and S. TOHNO spectrometer (PTR-MS) for volatile organic compound measurement. Detailed in Several indicators for IPFs have been suggested from the diagnostic ratios of chemical species based on field observation data (source and/or receptor sites) and laboratory burning experiments. OC/EC, WSOC/OC and HULIS-C/WSOC in PM provide a rough indication of origins or characteristics of carbonaceous aerosols (Cao et al., 2005; Frka et al., 2018; Shen et al., 2014). The OC/EC source-dominated field observations28, 44, 63, 77, 106 and laboratory burning experiments17, 26, 66, 83, 90, 95 were 2.42–223 and 14 –163, respectively. The discrepancy among these data can be attributed to differences in combustion conditions such as load, moisture content (Chen et al., 2010), fuel smoldering kinetics and the reaction-zone structure of the IPF (Huang and Rein, 2014). In addition, the use of different protocols such as NIOSH and IMPROVE for OC/EC determination may also lead to uncertainties (Wu et al., 2016). Thus, to show the representative OC/EC for an IPF is extremely difficult, as mentioned in Fujii et al.106. At the receptor sites, obvious increases in OC/EC during haze periods were consistently observed compared to during non-haze periods in Malaysia2, 50, 56, Singapore16, 25, 43, 89 and Thailand120. WSOC/OC obtained from source-dominated field observations77,106 and laboratory burning experiments23, 26, 66, 83, 90 was 0.085 – 0.16 and 0.0093 – 0.87, respectively. WSOC/OC obtained from certain laboratory burning experiments23, 26 differed significantly field observations. These laboratory burning systems may not accurately represent real-world IPFs. Fujii et al.105 showed WSOC/OC in TSP collected in Bangi, Malaysia during a haze period (strong haze: 0.34, light-haze: 0.39 ± 0.034) was slightly lower than that during a non-haze period (0.41 ± 0.064). Based on these data, Δ(WSOC/OC) was calculated by subtracting the average concentrations of OC and WSOC during the non-haze period from those of the haze period106. The resulting Δ(WSOC/OC) was 0.36 ± 0.055, which is higher than the WSOC/OC obtained at the IPF source77, 106, suggesting secondary WSOC formation during transport from IPF sources to receptor sites. As an indicator, WSOC/OC is not useful for IPFs. Regarding HULIS-C/WSOC, only one set of field observation data is available105. Regarding that report, although HULIS-C/WSOC during the haze period in analyses of chemical from obtained those obtained from compositions, secondary aerosol formation and the relationship between chemical compositions and physical properties are provided with additional documents in the Supplementary Information. through

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