scholarly journals Importance of transboundary transport of biomass burning emissions to regional air quality in Southeast Asia during a high fire event

2015 ◽  
Vol 15 (1) ◽  
pp. 363-373 ◽  
Author(s):  
B. Aouizerats ◽  
G. R. van der Werf ◽  
R. Balasubramanian ◽  
R. Betha
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Ambient Air ◽  
Basis Set ◽  
Data Sets ◽  
Test Model ◽  
Air Masses ◽  
Fire Emissions ◽  
Regional Air Quality

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.

scholarly journals Importance of transboundary transport of biomass burning emissions to regional air quality in Southeast Asia

2014 ◽  
Vol 14 (8) ◽  
pp. 11221-11248 ◽  
Author(s):  
B. Aouizerats ◽  
G. R. van der Werf ◽  
R. Balasubramanian ◽  
R. Betha
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Ambient Air ◽  
Basis Set ◽  
Minor Role ◽  
Test Model ◽  
Air Masses ◽  
Airborne Measurements ◽  
Fire Emissions

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 the largest fire-induced haze episode in the past decade (2006) in Indonesia using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). We focused mainly 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 CO concentrations. Two simulations were run with the model 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 b iomass 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 datasets for comparison including airborne measurements of Particulate Matter with a diameter of 10 μm or less (PM10) in Singapore, CO measurements in Sumatra, and Aerosol Optical Depth (AOD) column observations from 4 satellite-based sensors. We found reasonable agreement of the model runs with 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 secondary organic aerosol (SOA) concentration slightly increased. The absolute values of SOA (up to 20 μg m−3) were much lower than those from POA, indicating a minor role of SOA in 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 Borneo added to the enhanced PM10 concentrations. The model vs. 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 air quality.

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

2020 ◽  
Author(s):  
Margaret Marvin ◽  
Paul Palmer ◽  
Fei Yao ◽  
Barry Latter ◽  
Richard Siddans ◽  
...  
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
Agricultural Waste ◽  
Critical Evaluation ◽  
Dry Season ◽  
Mitigation Strategies ◽  
Atmospheric Composition ◽  
Regional Air Quality

<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>

scholarly journals Ambient air quality in the Kathmandu Valley, Nepal, during the pre-monsoon: concentrations and sources of particulate matter and trace gases

2020 ◽  
Vol 20 (5) ◽  
pp. 2927-2951 ◽  
Author(s):  
Md. Robiul Islam ◽  
Thilina Jayarathne ◽  
Isobel J. Simpson ◽  
Benjamin Werden ◽  
John Maben ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Trace Gases ◽  
Ambient Air ◽  
Kathmandu Valley ◽  
Ambient Air Quality ◽  
Regional Air Quality

Abstract. The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the pre-monsoon season. Ambient concentrations of fine and coarse particulate matter (PM2.5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 93 non-methane volatile organic compounds; NMVOCs) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated origins primarily from poorly maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those 2 weeks, daily average PM2.5 concentrations ranged from 30 to 207 µg m−3, which exceeded the World Health Organization 24 h guideline by factors of 1.2 to 8.3. On average, the non-water mass of PM2.5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas–aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (averaging 1230±1154 ng m−3), 1,3,5-triphenylbenzene (0.8±0.6 ng m−3), cholesterol (2.9±6.6 ng m−3), stigmastanol (1.0 ±0.8 ng m−3), and cis-pinonic acid (4.5±1.9 ng m−3) indicate contributions from biomass burning, garbage burning, food cooking, cow dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18±5 %), biomass burning (17±10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18±9 %). Model sensitivity tests with newly developed source profiles indicated contributions from biomass burning within a factor of 2 of previous estimates but greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2.5 OC included those originating from anthropogenic precursors such as naphthalene (10±4 %) and methylnaphthalene (0.3±0.1 %) and biogenic precursors for monoterpenes (0.13±0.07 %) and sesquiterpenes (5±2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) and/or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil fuel combustion) were the greatest contributors to PM2.5 and, as such, should be considered primary targets for controlling ambient PM pollution.

scholarly journals Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

2017 ◽  
Author(s):  
Hsiang-He Lee ◽  
Oussama Iraqui ◽  
Yefu Gu ◽  
Hung-Lam Steve Yim ◽  
Apisada Chulakadabba ◽  
...  
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Fossil Fuel ◽  
Anthropogenic Sources ◽  
Fire Emissions ◽  
Fossil Fuel Burning ◽  
Fuel Burning ◽  
Particulate Pollutants ◽  
Low Visibility

Abstract. Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years, degrading air quality, threatening human health, and interrupting economic and societal activities. Widespread biomass burning activities are a major source of severe haze events in Southeast Asia. On the other hand, particulate pollutants from human activities other than biomass burning also play an important role in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus non-fire (including fossil fuel combustion, road and industrial dust, land use, and land change, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and were respectively driven by emissions from: (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. Across ASEAN 50 cities, these model results reveal that 39 % of observed low visibility days can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. The remaining 28 % of observed low visibility days remain unexplained, likely due to emissions sources that have not been accounted for. Further analysis of 24-hr PM2.5 Air Quality Index (AQI) indicates that comparing to the simulated result of the case with stand-alone non-fire emissions, the case with coexisting fire and non-fire PM2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 % to 34 %. The premature mortality among major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ~ 4110 per year in 2002 to ~ 6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An exploratory experiment of using machine learning algorithms to forecasting the occurrence of haze events in Singapore is also demonstrated in this study. All these results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia needs to consider controlling emissions from non-fire anthropogenic sources.

scholarly journals Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

2018 ◽  
Vol 18 (9) ◽  
pp. 6141-6156 ◽  
Author(s):  
Hsiang-He Lee ◽  
Oussama Iraqui ◽  
Yefu Gu ◽  
Steve Hung-Lam Yim ◽  
Apisada Chulakadabba ◽  
...  
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Fossil Fuel ◽  
Anthropogenic Sources ◽  
Pollution Level ◽  
Fire Emissions ◽  
Fossil Fuel Burning ◽  
Fuel Burning ◽  
Particulate Pollutants

Abstract. Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years. Widespread biomass burning occurrences and particulate pollutants from human activities other than biomass burning play important roles in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus non-fire (including fossil fuel combustion, and road dust, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and are driven by emissions from (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. The model results reveal that 39 % of observed low-visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. Analysis of an 24 h PM2.5 air quality index (AQI) indicates that the case with coexisting fire and non-fire PM2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 to 34 %. The premature mortality in major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from  ∼  4110 per year in 2002 to  ∼  6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore is also explored in this study. All of these results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia needs to consider controlling emissions from non-fire anthropogenic sources.

scholarly journals Ambient air quality in the Kathmandu Valley, Nepal during the pre-monsoon: Concentrations and sources of particulate matter and trace gases

2019 ◽  
Author(s):  
Md. Robiul Islam ◽  
Thilina Jayarathne ◽  
Isobel J. Simpson ◽  
Benjamin Werden ◽  
John Maben ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Trace Gases ◽  
Ambient Air ◽  
Kathmandu Valley ◽  
Ambient Air Quality ◽  
Regional Air Quality

Abstract. The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the pre-monsoon season. Ambient concentrations of fine and coarse particulate matter (PM2.5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 85 non-methane volatile organic compounds; NMVOC) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated that origins primarily from poorly-maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those two weeks, daily average PM2.5 concentrations ranged from 30 to 207 µg m−3, which exceeded the World Health Organization 24 hour guideline by factors of 1.2 to 8.3. On average, the non-water mass of PM2.5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas-aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (1230 ± 1153 ng m−3), 1,3,5-triphenylbenzene (0.8 ±0.5 ng m−3), cholesterol (3.0 ± 6.7 ng m−3), stigmastanol (1.4 ± 6.7 ng m−3), and cis-pinonic acid (4.5 ± 0.6 ng m−3) indicate contributions from biomass burning, garbage burning, food cooking, cow-dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18 ± 5 %), biomass burning (17 ± 10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18 ± 9 %). Model sensitivity tests with newly-developed source profiles indicated contributions from biomass burning within a factor of two of previous estimates, but relatively greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2.5 OC included those originating from anthropogenic precursors for naphthalene (10 ± 4 %) and methylnaphthalene (0.3 ± 0.1 %) and biogenic precursors for monoterpenes (0.13 ± 0.07 %) and sesquiterpenes (5 ± 2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil-fuel combustion) were the greatest contributors to PM2.5 and, as such, should be considered primary targets for controlling ambient PM pollution.

scholarly journals Emission Inventory Processing of Biomass Burning from A Global Dataset for Air Quality Modeling

2020 ◽  
Author(s):  
Ernesto Pino-Cortés ◽  
Samuel Carrasco ◽  
Luis A. Díaz-Robles ◽  
Francisco Cubillos ◽  
Fidel Vallejo ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Sparse Matrix ◽  
Local Level ◽  
Air Quality Modeling ◽  
Simulation Software ◽  
Atmospheric Pollutants ◽  
Fire Emissions ◽  
Quality Modeling

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emissions inventory for this activity is a challenge today, mainly to perform modeling of air quality. There are free available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were the black carbon, the organic carbon, fine and coarse particulate matter, respectively. The inputs were pre-formatted to enter to the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source.

Trace gases and organic aerosol at a rural site in Vietnam during large scale biomass burning

2021 ◽  
Author(s):  
Simone M. Pieber ◽  
Dac-Loc Nguyen ◽  
Hendryk Czech ◽  
Stephan Henne ◽  
Nicolas Bukowiecki ◽  
...  
Keyword(s):  
Air Quality ◽  
Chemical Composition ◽  
Biomass Burning ◽  
Large Scale ◽  
Trace Gases ◽  
Organic Aerosol ◽  
Trace Gas ◽  
Rural Site ◽  
Air Masses ◽  
Mixing Ratios

<p>Open biomass burning (BB) is a globally widespread phenomenon. The fires release pollutants, which are harmful for human and ecosystem health and alter the Earth's radiative balance. Yet, the impact of various types of BB on the global radiative forcing remains poorly constrained concerning greenhouse gas emissions, BB organic aerosol (OA) chemical composition and related light absorbing properties. Fire emissions composition is influenced by multiple factors (e.g., fuel and thereby vegetation-type, fuel moisture, fire temperature, available oxygen). Due to regional variations in these parameters, studies in different world regions are needed. Here we investigate the influence of seasonally recurring BB on trace gas concentration and air quality at the regional Global Atmosphere Watch (GAW) station Pha Din (PDI) in rural Northwestern Vietnam. PDI is located in a sparsely populated area on the top of a hill (1466 m a.s.l.) and is well suited to study the large-scale fires on the Indochinese Peninsula, whose pollution plumes are frequently transported towards the site [1]. We present continuous trace gas observations of CO<sub>2</sub>, CH<sub>4</sub>, CO, and O<sub>3</sub> conducted at PDI since 2014 and interpret the data with atmospheric transport simulations. Annually recurrent large scale BB leads to hourly time-scale peaks CO mixing ratios at PDI of 1000 to 1500 ppb around every April since the start of data collection in 2014. We complement this analysis with carbonaceous PM<sub>2.5 </sub>chemical composition analyzed during an intensive campaign in March-April 2015. This includes measurements of elemental and organic carbon (EC/OC) and more than 50 organic markers, such as sugars, PAHs, fatty acids and nitro-aromatics [2]. For the intensive campaign, we linked CO, CO<sub>2</sub>, CH<sub>4</sub> and O<sub>3</sub> mixing ratios to a statistical classification of BB events, which is based on OA composition. We found increased CO and O<sub>3</sub> levels during medium and high BB influence during the intensive campaign. A backward trajectory analysis confirmed different source regions for the identified periods based on the OA cluster. Typically, cleaner air masses arrived from northeast, i.e., mainland China and Yellow sea during the intensive campaign. The more polluted periods were characterized by trajectories from southwest, with more continental recirculation of the medium cluster, and more westerly advection for the high cluster. These findings highlight that BB activities in Northern Southeast Asia significantly enhances the regional OA loading, chemical PM<sub>2.5 </sub>composition and the trace gases in northwestern Vietnam. The presented analysis adds valuable data on air quality in a region of scarce data availability.</p><p> </p><p><strong>REFERENCES</strong></p><p>[1] Bukowiecki, N. et al. Effect of Large-scale Biomass Burning on Aerosol Optical Properties at the GAW Regional Station Pha Din, Vietnam. AAQR. 19, 1172–1187 (2019).</p><p>[2] Nguyen, D. L, et al. Carbonaceous aerosol composition in air masses influenced by large-scale biomass burning: a case-study in Northwestern Vietnam. ACPD., https://doi.org/10.5194/acp-2020-1027, in review, 2020.</p>

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

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 ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

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.

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