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 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 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.

scholarly journals Better constraints on sources of carbonaceous aerosols using a combined <sup>14</sup>C – macro tracer analysis in a European rural background site

2011 ◽  
Vol 11 (1) ◽  
pp. 2503-2547 ◽  
Author(s):  
S. Gilardoni ◽  
E. Vignati ◽  
F. Cavalli ◽  
J. P. Putaud ◽  
B. R. Larsen ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Biomass Burning ◽  
Elemental Carbon ◽  
Fossil Fuel ◽  
Carbonaceous Aerosol ◽  
Po Valley ◽  
Fossil Fuel Burning ◽  
Potential Source ◽  
Fuel Burning ◽  
Source Contributions

Abstract. The source contributions to carbonaceous PM2.5 aerosol were investigated at a European background site at the edge of the Po Valley, in Northern Italy, during the period January–December 2007. Carbonaceous aerosol was described as the sum of eight source components: primary (1) and secondary (2) biomass burning organic carbon, biomass burning elemental carbon (3), primary (4) and secondary (5) fossil fuel burning organic carbon, fossil fuel burning elemental carbon (6), primary (7) and secondary (8) biogenic organic carbon. The concentration of each component was quantified using a set of macro tracers (organic carbon OC, elemental carbon EC, and levoglucosan), micro tracers (arabitol and mannitol), and 14C measurements. This was the first time that 14C measurements were performed on a long time series of data able to represent the entire annual cycle. This set of 6 tracers, together with assumed uncertainty ranges of the ratios of OC-to-EC, and the fraction of modern carbon in the 8 source categories, provides strong constraints to the source contributions to carbonaceous aerosol. The uncertainty of contributions was assessed with a Quasi-Monte Carlo (QMC) method accounting for the variability of OC and EC emission factors, and the uncertainty of reference fractions of modern carbon. During winter biomass burning composed 50% of the total carbon (TC) concentration, while in summer secondary biogenic OC accounted for 45% of TC. The contribution of primary biogenic aerosol particles was negligible during the entire year. Moreover, aerosol associated with fossil fuel burning represented 26% and 43% of TC in winter and summer, respectively. The comparison of source apportionment results in different urban and rural areas showed that the sampling site was mainly affected by local aerosol sources during winter and regional air masses from the nearby Po Valley in summer. This observation was further confirmed by back-trajectory analysis applying the Potential Source Contribution Function method to identify potential source regions. The contribution of secondary organic aerosol (SOA) to the organic mass (OM) was significant during the entire year. SOA accounted for 23% and 83% of OM during winter and summer, respectively. While the summer SOA was dominated by biogenic sources, winter SOA was mainly due to biomass and fossil fuel burning. This indicates that the oxidation of intermediate volatility organic compounds co-emitted with primary organics is a significant source of SOA, as suggested by recent model results and Aerosol Mass Spectrometer measurements in urban regions. Comparison with previous global model simulations, indicates a strong underestimate of wintertime primary aerosol emissions in this region.

scholarly journals XCO2 retrieved from IASI using KLIMA algorithm

2014 ◽  
Author(s):  
Samuele Del Bianco ◽  
Bruno Carli ◽  
Marco Gai ◽  
Lucia Maria Laurenza ◽  
Ugo Cortesi
Keyword(s):  
Carbon Dioxide ◽  
Land Use ◽  
Fossil Fuel ◽  
Land Use Changes ◽  
International Agreements ◽  
Reliable Estimate ◽  
Natural Sources ◽  
Sources And Sinks ◽  
Fossil Fuel Burning ◽  
Fuel Burning

Carbon dioxide (CO<sub>2</sub>) is the main greenhouse gas released into the Earth’s atmosphere by human activities. The concentration of CO<sub>2</sub> in the atmosphere depends on the balance of natural sources and sinks, which are being perturbed by anthropogenic forcing due to fossil fuel burning, uncontrolled urban development, deforestation and other land use changes. An improvement in our understanding of processes responsible for absorption of CO<sub>2</sub> is urgently needed both for a reliable estimate of future CO<sub>2</sub> levels, and for the enforcement of effective international agreements for its containment. [...]

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.

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