Regional Impact of Biomass Burning in Southeast Asia on Atmospheric Aerosols during the 2013 Seven South-East Asian Studies Project

Li, Jie; Zhang, Yuqia; Wang, Zifa; Sun, Yele; Fu, Pingqing; Yang, Yingchun; Huang, Huili; Li, Jianjun; Zhang, Qiang; Lin, Chuan-Yao; Lin, Neng Huei

doi:10.4209/aaqr.2016.09.0422

Cited by 19 publications

(22 citation statements)

References 31 publications

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“…Several studies have used a mix of models and observations to explore the impacts of fire on atmospheric aerosol properties, visibility, and/or air quality in Mainland Southeast Asia (Duc et al., 2016; K. Huang et al., 2013; Lee et al., 2017, 2018; Li et al., 2017; Lin et al., 2013; Vongruang & Pimonsree, 2020; Yin et al., 2019). However, studies quantifying the contribution of fire to particulate air pollution, population exposure and public health are lacking in this region (H. J. Johnston et al., 2019; Yadav et al., 2017), compared in particular to the large number of studies focused on Equatorial Asia (e.g., Crippa et al., 2016; Kiely et al., 2020; Koplitz et al., 2016; Marlier et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

“…However, studies quantifying the contribution of fire to particulate air pollution, population exposure and public health are lacking in this region (H. J. Johnston et al., 2019; Yadav et al., 2017), compared in particular to the large number of studies focused on Equatorial Asia (e.g., Crippa et al., 2016; Kiely et al., 2020; Koplitz et al., 2016; Marlier et al., 2012). Recent studies show that fire is the dominant cause of the variation of local ambient air quality in Mainland Southeast Asia (Yin et al., 2019); contributing 49% of ambient PM 10 (particulate matter with aerodynamic diameter ≤ 10 μm) concentrations during peak open burning in March 2012 (Vongruang & Pimonsree, 2020) and 70%–80% to aerosol optical depth in source regions during March‐April 2013 (Li et al., 2017). Preventing fire could yield substantial reductions in population‐weighted PM 2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) concentrations across Mainland Southeast Asia (Reddington, Conibear, et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

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Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

et al. 2021

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Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognised, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south-eastern China). We found that eliminating fire could substantially improve regional air quality across Southeast Asia by reducing the population exposure to fine particulate matter (PM2.5) concentrations by 7% and surface ozone concentrations by 5%. These reductions in PM2.5 exposures would yield a considerable public health benefit across the region; averting 59,000 (95% uncertainty interval (95UI): 55,200-62,900) premature deaths annually. Analysis of subnational infant mortality rate data and PM2.5 exposure suggested that PM2.5 from fires disproportionately impacts poorer populations across Southeast Asia. We identified two key regions in northern Laos and western Myanmar where particularly high levels of poverty coincide with exposure to relatively high levels of PM2.5 from fires. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

et al. 2021

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“…The BB contributions to PM 10 concentrations of the four simulation cases were 2%-12% at Bangkok and 75%-89% at Chiang Mai for each day that the maximum concentrations were observed. Li et al [12] reported that BB contributions to simulated PM 2.5 was 70%-80% in the BB source regions during March-April 2013 and the contributions were close to 75%-89% at Chiang Mai on 21 March 2014. Figure 6 shows simulated and observed wind speed, planetary boundary layer (PBL) height, and daily concentrations at Bangkok and Chiang Mai from March to April.…”

Section: Daily Concentrations Of Pm 10 At Observation Sitesmentioning

confidence: 97%

“…However, particulate matter was not evaluated in the simulations. Li et al [12] reported that BB contributed 70%-80% of simulated PM 2.5 in northern Myanmar, Laos, and Vietnam during March-April 2013.…”

Section: Introductionmentioning

confidence: 99%

Impacts of Biomass Burning Emission Inventories and Atmospheric Reanalyses on Simulated PM10 over Indochina

et al. 2020

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Biomass burning (BB) is a major source of atmospheric particles over Indochina during the dry season. Moreover, Indochina has convoluted meteorological scales, and regional meteorological conditions dominate the transport patterns of pollutants. This study focused on the impacts of BB emission inventories and atmospheric reanalyses on simulated PM10 over Indochina in 2014 using the Community Multiscale Air Quality (CMAQ) model. Meteorological fields to input to CMAQ were produced by using the Weather Research and Forecasting (WRF) model simulation with the United States National Centers for Environmental Prediction Final (NCEP FNL) Operational Global Analysis or European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-interim). The Fire INventory from NCAR (FINN) v1.5 or the Global Fire Emissions Database including small fires (GFED v4.1s) was selected for BB emissions for the air quality simulation. The simulation case with NCEP FNL and FINN v1.5 (FNL + FINN) performed best throughout 2014, including the season when BB activities were intensified. The normalized percentage difference for maximum daily mean PM10 concentrations at Chiang Mai for FNL + FINN and the two simulation cases applying GFED v4.1s for BB emissions (−53% to −27%) was much larger than that between the FNL + FINN and ERA + FINN cases (10%). BB emission inventories more strongly impacted PM10 simulation than atmospheric reanalyses in highly polluted areas by BB over Indochina in 2014.

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“…Biomass burning emission causes a significant perturbation to global atmospheric chemistry (Stocks et al, 2000;Akagi et al, 2011;Grell et al, 2011;Lin et al, 2017;Popovicheva et al, 2017;Pani et al, 2018;Liang et al, 2019). It has an impact of direct and indirect effects on the radiative forcing of atmospheric aerosol particles and climate change (Li et al, 2017;Martins et al, 2018;Bukowiecki et al, 2019;Huang et al, 2019). Chemical compounds in aerosol particles are used as tracers to determine the sources such as biomass burning emission (Decesari et al, 2006;Wang et al, 2009;Lee et al, 2016;Du et al, 2017;Cui et al, 2018;Popovicheva et al, 2019;Priyadharshini et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

High Loadings of Water-Soluble Oxalic Acid and Related Compounds in PM2.5 Aerosols in Eastern Central India: Influence of Biomass Burning and Photochemical Processing

Deshmukh

Kawamura

Gupta

et al. 2019

Aerosol Air Qual. Res.

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Water-soluble organic compounds are important constituents of atmospheric aerosols and have been recognized as unique fingerprints to identify atmospheric processes. Fine aerosol samples (PM 2.5) were collected at Ambikapur (23.1°N and 83.2°E) in eastern central India from March to June 2017. The samples were analyzed for water-soluble dicarboxylic acids (C 2-C 12), glyoxylic acid (ωC 2), glyoxal (Gly), methylglyoxal (MeGly), organic carbon (OC), elemental carbon (EC) and water-soluble OC (WSOC). Oxalic acid (C 2) was detected as the most abundant species, followed by succinic (C 4) and malonic (C 3) acids. Temporal variation in concentrations of C 2 diacid and related compounds was pronounced from early to late April when biomass burning (BB) was dominant in eastern central India. Strong positive correlations of C 2 diacid and related compounds with levoglucosan (r = 0.83-0.99) further demonstrate that organic aerosols (OAs) were affected by BB in eastern central India. Strong positive correlations of C 2 with saturated diacids (C 3-C 9 : r = 0.78-0.97), ωC 2 (r = 0.98), Gly (r = 0.96) and MeGly (r = 0.84) suggest that their sources and formation processes were similar and oxalic acid might be produced via the photochemical degradation of precursor compounds. The relatively high ratios of WSOC to OC (avg. 0.69) and C 3 to C 4 diacid (avg. 0.95) suggest that water-soluble OAs were photochemically processed during the campaign. The total water-soluble organic compounds detected in Ambikapur PM 2.5 samples accounted for an average of 1.9% (1.1-3.1%) of OC. Our results demonstrate that BB and photochemical processing caused high levels of water-soluble organic compounds over eastern central India.

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Regional Impact of Biomass Burning in Southeast Asia on Atmospheric Aerosols during the 2013 Seven South-East Asian Studies Project

Cited by 19 publications

References 31 publications

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

Impacts of Biomass Burning Emission Inventories and Atmospheric Reanalyses on Simulated PM10 over Indochina

High Loadings of Water-Soluble Oxalic Acid and Related Compounds in PM2.5 Aerosols in Eastern Central India: Influence of Biomass Burning and Photochemical Processing

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