Characterizing two distinct biomass burning regimes over Southeast Asia and their impacts on regional air quality

Author(s):  
Margaret Marvin ◽  
Paul Palmer ◽  
Fei Yao ◽  
Barry Latter ◽  
Richard Siddans ◽  
...  

<p>Mainland and maritime Southeast Asia is home to more than 655 million people, representing nearly 10% of the global population. The dry season in this region is typically associated with intense biomass burning activity, which leads to a significant increase in surface air pollutants that are harmful to human health, including ozone (O<sub>3</sub>) and fine (radii smaller than 2.5 microns) particulate matter (PM<sub>2.5</sub>). Latitude-based differences in dry season timing and land use distinguish two regional biomass burning regimes: (1) agricultural waste burning on the peninsular mainland from February through April and (2) coastal peat burning across the equatorial islands in September and October. The type and amount of material burned determines the chemical composition of emissions and subsequently their impact on regional air quality. Understanding the individual and collective roles of these biomass burning regimes is a crucial step towards developing effective air quality mitigation strategies for Southeast Asia. Here, we use the nested GEOS-Chem atmospheric chemistry transport model (horizontal resolution of 0.25° x 0.3125°) to simulate fire-atmosphere interactions over Southeast Asia during March and September of 2014, when emissions peak from the two regional burning seasons. Based on our analysis of model output, we report how these two distinct biomass burning regimes impact the photochemical environment over Southeast Asia and what the resulting consequences are for surface air quality. We will also present a critical evaluation of our model using ground-based and satellite observations of atmospheric composition across the region.</p>

2015 ◽  
Vol 15 (1) ◽  
pp. 363-373 ◽  
Author(s):  
B. Aouizerats ◽  
G. R. van der Werf ◽  
R. Balasubramanian ◽  
R. Betha

Abstract. Smoke from biomass and peat burning has a notable impact on ambient air quality and climate in the Southeast Asia (SEA) region. We modeled a large fire-induced haze episode in 2006 stemming mostly from Indonesia using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). We focused on the evolution of the fire plume composition and its interaction with the urbanized area of the city state of Singapore, and on comparisons of modeled and measured aerosol and carbon monoxide (CO) concentrations. Two simulations were run with WRF-Chem using the complex volatility basis set (VBS) scheme to reproduce primary and secondary aerosol evolution and concentration. The first simulation referred to as WRF-FIRE included anthropogenic, biogenic and biomass burning emissions from the Global Fire Emissions Database (GFED3) while the second simulation referred to as WRF-NOFIRE was run without emissions from biomass burning. To test model performance, we used three independent data sets for comparison including airborne measurements of particulate matter (PM) with a diameter of 10 μm or less (PM10) in Singapore, CO measurements in Sumatra, and aerosol optical depth (AOD) column observations from four satellite-based sensors. We found reasonable agreement between the model runs and both ground-based measurements of CO and PM10. The comparison with AOD was less favorable and indicated the model underestimated AOD, although the degree of mismatch varied between different satellite data sets. During our study period, forest and peat fires in Sumatra were the main cause of enhanced aerosol concentrations from regional transport over Singapore. Analysis of the biomass burning plume showed high concentrations of primary organic aerosols (POA) with values up to 600 μg m−3 over the fire locations. The concentration of POA remained quite stable within the plume between the main burning region and Singapore while the secondary organic aerosol (SOA) concentration slightly increased. However, the absolute concentrations of SOA (up to 20 μg m−3) were much lower than those from POA, indicating a minor role of SOA in these biomass burning plumes. Our results show that about 21% of the total mass loading of ambient PM10 during the July–October study period in Singapore was due to biomass and peat burning in Sumatra, but this contribution increased during high burning periods. In total, our model results indicated that during 35 days aerosol concentrations in Singapore were above the threshold of 50 μg m−3 day−1 indicating poor air quality. During 17 days this was due to fires, based on the difference between the simulations with and without fires. Local pollution in combination with recirculation of air masses was probably the main cause of poor air quality during the other 18 days, although fires from Sumatra and probably also from Kalimantan (Indonesian part of the island of Borneo) added to the enhanced PM10 concentrations. The model versus measurement comparisons highlighted that for our study period and region the GFED3 biomass burning aerosol emissions were more in line with observations than found in other studies. This indicates that care should be taken when using AOD to constrain emissions or estimate ground-level air quality. This study also shows the need for relatively high resolution modeling to accurately reproduce the advection of air masses necessary to quantify the impacts and feedbacks on regional air quality.


2020 ◽  
Author(s):  
Margaret R. Marvin ◽  
Paul I. Palmer ◽  
Barry G. Latter ◽  
Richard Siddans ◽  
Brian J. Kerridge ◽  
...  

Abstract. Mainland and maritime Southeast Asia are home to more than 655 million people, representing nearly 10 % of the global population. The dry season in this region is typically associated with intense biomass burning activity, which leads to a significant increase in surface air pollutants that are harmful to human health, including ozone (O3). Latitude-based differences in dry season and land use distinguish two regional biomass burning regimes: (1) burning on the peninsular mainland peaking in March and (2) burning across Indonesia peaking in September. The type and amount of material burned in each regime impacts the emissions of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOCs), which combine to produce ozone. Here, we use the nested GEOS-Chem atmospheric chemistry transport model (horizontal resolution of 0.25° × 0.3125°), in combination with satellite observations from the Ozone Monitoring Instrument (OMI) and ground-based observations from Malaysia, to investigate ozone photochemistry over Southeast Asia in 2014. Seasonal cycles of tropospheric ozone columns from OMI and GEOS-Chem peak with biomass burning emissions. Compared to OMI, the model has a mean annual bias of −11 % but tends to overestimate tropospheric ozone near areas of seasonal fire activity. We find that outside of these burning areas, the underlying photochemical environment is generally NOx-limited, dominated by anthropogenic NOx and biogenic non-methane VOC emissions. Pyrogenic emissions of NOx play a key role in photochemistry, shifting towards more VOC-limited ozone production and contributing about 30 % of the regional ozone formation potential during both biomass burning seasons. Using the GEOS-Chem model, we find that biomass burning activity coincides with widespread ozone exposure at levels that exceed world public health guidelines, resulting in 272 premature deaths on mainland Southeast Asia in March of 2014 and another 273 deaths across Indonesia in September. Despite a positive model bias, hazardous ozone levels are confirmed by surface observations during both burning seasons.


2014 ◽  
Vol 14 (7) ◽  
pp. 9345-9400 ◽  
Author(s):  
T. Amnuaylojaroen ◽  
M. C. Barth ◽  
L. K. Emmons ◽  
G. R. Carmichael ◽  
J. Kreasuwun ◽  
...  

Abstract. In order to improve our understanding of air quality in Southeast Asia, the anthropogenic emissions inventory must be well represented. In this work, we apply different anthropogenic emission inventories in the Weather Research and Forecasting Model with Chemistry (WRF-Chem) version 3.3 using MOZART gas-phase chemistry and GOCART aerosols to examine the differences in predicted carbon monoxide (CO) and ozone (O3) surface mixing ratios for Southeast Asia in March and December 2008. The anthropogenic emission inventories include the Reanalysis of the TROpospheric chemical composition (RETRO), the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), the MACCity emissions (adapted from the Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment projects), the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS) emissions, and a combination of MACCity and SEAC4RS emissions. Biomass burning emissions are from the Fire Inventory from NCAR (FINNv1) model. WRF-chem reasonably predicts the 2 m temperature, 10 m wind, and precipitation. In general, surface CO is underpredicted by WRF-Chem while surface O3 is overpredicted. The NO2 tropospheric column predicted by WRF-Chem has the same magnitude as observations, but tends to underpredict NO2 column over the equatorial ocean and near Indonesia. Simulations using different anthropogenic emissions produce only a slight variability of O3 and CO mixing ratios, while biomass burning emissions add more variability. The different anthropogenic emissions differ by up to 20% in CO emissions, but O3 and CO mixing ratios differ by ~4.5% and ~8%, respectively, among the simulations. Biomass burning emissions create a substantial increase for both O3 and CO by ~29% and ~16%, respectively, when comparing the March biomass burning period to December with low biomass burning emissions. The simulations show that none of the anthropogenic emission inventories are better than the others and any of the examined inventories can be used for air quality simulations in Southeast Asia.


2021 ◽  
Vol 21 (3) ◽  
pp. 1917-1935
Author(s):  
Margaret R. Marvin ◽  
Paul I. Palmer ◽  
Barry G. Latter ◽  
Richard Siddans ◽  
Brian J. Kerridge ◽  
...  

Abstract. Mainland and maritime Southeast Asia is home to more than 655 million people, representing nearly 10 % of the global population. The dry season in this region is typically associated with intense biomass burning activity, which leads to a significant increase in surface air pollutants that are harmful to human health, including ozone (O3). Latitude-based differences in the dry season and land use distinguish two regional biomass burning regimes: (1) burning on the peninsular mainland peaking in March and (2) burning across Indonesia peaking in September. The type and amount of material burned in each regime impact the emissions of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOCs), which combine to produce ozone. Here, we use the nested GEOS-Chem atmospheric chemistry transport model (horizontal resolution of 0.25∘ × 0.3125∘), in combination with satellite observations from the Ozone Monitoring Instrument (OMI) and ground-based observations from Malaysia, to investigate ozone photochemistry over Southeast Asia in 2014. Seasonal cycles of tropospheric ozone columns from OMI and GEOS-Chem peak with biomass burning emissions. Compared to OMI, the model has a mean annual bias of −11 % but tends to overestimate tropospheric ozone near areas of seasonal fire activity. We find that outside these burning areas, the underlying photochemical environment is generally NOx-limited and dominated by anthropogenic NOx and biogenic non-methane VOC emissions. Pyrogenic emissions of NOx play a key role in photochemistry, shifting towards more VOC-limited ozone production and contributing about 30 % of the regional ozone formation potential during both biomass burning seasons. Using the GEOS-Chem model, we find that biomass burning activity coincides with widespread ozone exposure at levels that exceed world public health guidelines, resulting in about 260 premature deaths across Southeast Asia in March 2014 and another 160 deaths in September. Despite a positive model bias, hazardous ozone levels are confirmed by surface observations during both burning seasons.


2017 ◽  
Vol 200 ◽  
pp. 693-703 ◽  
Author(s):  
Jos Lelieveld

In atmospheric chemistry, interactions between air pollution, the biosphere and human health, often through reaction mixtures from both natural and anthropogenic sources, are of growing interest. Massive pollution emissions in the Anthropocene have transformed atmospheric composition to the extent that biogeochemical cycles, air quality and climate have changed globally and partly profoundly. It is estimated that mortality attributable to outdoor air pollution amounts to 4.33 million individuals per year, associated with 123 million years of life lost. Worldwide, air pollution is the major environmental risk factor to human health, and strict air quality standards have the potential to strongly reduce morbidity and mortality. Preserving clean air should be considered a human right, and is fundamental to many sustainable development goals of the United Nations, such as good health, climate action, sustainable cities, clean energy, and protecting life on land and in the water. It would be appropriate to adopt “clean air” as a sustainable development goal.


2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.


2017 ◽  
Vol 10 (2) ◽  
pp. 585-607 ◽  
Author(s):  
William J. Collins ◽  
Jean-François Lamarque ◽  
Michael Schulz ◽  
Olivier Boucher ◽  
Veronika Eyring ◽  
...  

Abstract. The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.


2006 ◽  
Vol 25 (S1) ◽  
pp. 221-222 ◽  
Author(s):  
Rajasekhar Balasubramanian ◽  
Siao Wee See

2014 ◽  
Vol 14 (23) ◽  
pp. 12983-13012 ◽  
Author(s):  
T. Amnuaylojaroen ◽  
M. C. Barth ◽  
L. K. Emmons ◽  
G. R. Carmichael ◽  
J. Kreasuwun ◽  
...  

Abstract. In order to improve our understanding of air quality in Southeast Asia, the anthropogenic emissions inventory must be well represented. In this work, we apply different anthropogenic emission inventories in the Weather Research and Forecasting Model with Chemistry (WRF-Chem) version 3.3 using Model for Ozone and Related Chemical Tracers (MOZART) gas-phase chemistry and Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosols to examine the differences in predicted carbon monoxide (CO) and ozone (O3) surface mixing ratios for Southeast Asia in March and December 2008. The anthropogenic emission inventories include the Reanalysis of the TROpospheric chemical composition (RETRO), the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), the MACCity emissions (adapted from the Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment projects), the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS) emissions, and a combination of MACCity and SEAC4RS emissions. Biomass-burning emissions are from the Fire Inventory from the National Center for Atmospheric Research (NCAR) (FINNv1) model. WRF-Chem reasonably predicts the 2 m temperature, 10 m wind, and precipitation. In general, surface CO is underpredicted by WRF-Chem while surface O3 is overpredicted. The NO2 tropospheric column predicted by WRF-Chem has the same magnitude as observations, but tends to underpredict the NO2 column over the equatorial ocean and near Indonesia. Simulations using different anthropogenic emissions produce only a slight variability of O3 and CO mixing ratios, while biomass-burning emissions add more variability. The different anthropogenic emissions differ by up to 30% in CO emissions, but O3 and CO mixing ratios averaged over the land areas of the model domain differ by ~4.5% and ~8%, respectively, among the simulations. Biomass-burning emissions create a substantial increase for both O3 and CO by ~29% and ~16%, respectively, when comparing the March biomass-burning period to the December period with low biomass-burning emissions. The simulations show that none of the anthropogenic emission inventories are better than the others for predicting O3 surface mixing ratios. However, the simulations with different anthropogenic emission inventories do differ in their predictions of CO surface mixing ratios producing variations of ~30% for March and 10–20% for December at Thai surface monitoring sites.


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