Biomass Burning and Haze in Indonesia, Long-Term Climate Perspective, and Impact on Regional Air Quality

Author(s):  
Sheila Dewi Ayu Kusumaningtyas ◽  
Edvin Aldrian ◽  
Sunaryo Sunaryo ◽  
Roni Kurniawan
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.


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 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>


2007 ◽  
Vol 41 (10) ◽  
pp. 2083-2097 ◽  
Author(s):  
M. van Loon ◽  
R. Vautard ◽  
M. Schaap ◽  
R. Bergström ◽  
B. Bessagnet ◽  
...  

2017 ◽  
Vol 122 (4) ◽  
pp. 2304-2324 ◽  
Author(s):  
Yonghua Wu ◽  
Yong Han ◽  
Apostolos Voulgarakis ◽  
Tijian Wang ◽  
Mengmeng Li ◽  
...  

2017 ◽  
Vol 227 ◽  
pp. 414-427 ◽  
Author(s):  
Ishwar Chandra Yadav ◽  
Ningombam Linthoingambi Devi ◽  
Jun Li ◽  
Jabir Hussain Syed ◽  
Gan Zhang ◽  
...  

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