Emission factors of PAHs, methoxyphenols, levoglucosan, elemental carbon and organic carbon from simulated wheat and Kentucky bluegrass stubble burns

Dhammapala, Ranil; Claiborn, Candis; Jiménez, Jorge; Corkill, Jeffrey A.; Gullett, Brian K.; Simpson, Christopher D.; Paulsen, Michael

doi:10.1016/j.atmosenv.2006.11.023

Cited by 89 publications

(66 citation statements)

References 32 publications

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“…The EC / CO ratio for the selected agricultural burning episode is 14.3 ± 4.4 ng m −3 ppb −1 , comparable to values reported for prescribed field fires by Pan et al (2012), Zhang et al (2015), and Li et al (2007) but higher than those derived during chamber combustion experiments (Dhammapala et al, 2007b;Hayashi et al, 2014) (Table 3). It should be noted that in combustion experiments the emission factor for different carbon species strongly depends on the type of residue combusted, initial moisture content, burning phase, and analytical instrument used for EC analysis.…”

Section: Polluted Air In the Transition Seasonssupporting

confidence: 64%

“…Wet deposition can affect aged EC Verma et al, 2011;Kanaya et al, 2016) but not CO, while CO can be removed from the atmosphere by oxidation with OH radicals (Hamilton et al, 2014). In addition, as noted above, CO can be produced from the oxidation of methane and non- Meadow-grass straw, wheat straw 10.9 ± 1.5 (F) 5.4 ± 4.3 (F) Dhammapala et al (2007b) a TOT (TOR) -thermal-optical transmittance (reflectance). b NCP -North China Plain.…”

Section: Characterisation Of Polluted Airmentioning

confidence: 99%

“…In the growing season, forested boreal regions emit biogenic volatile organic compounds (BVOCs) (isoprene, terpenes and sesquiterpenes) into the atmosphere (Kourtchev et al, 2005;Ehn et al, 2012;Noe et al, 2012;Ebben et al, 2011;Vestenius et al, 2014), and their oxidation products contribute to SOA formation or condense onto already 14382 E. F. Mikhailov et al: Long-term measurements (2010-2014 formed particles during transport, increasing aerosol sizes and mass (Tunved et al, 2006;Hallquist et al, 2009;Liao et al, 2014). Since the emission of the organic particle precursors depends on air temperature (Isidorov et al, 1985;Lappalainen et al, 2009), the SOA mass concentration also positively correlates with temperature (Leaitch et al, 2011;Corrigan et al, 2013;Liao et al, 2014).…”

Section: Near-pristine Airmentioning

confidence: 99%

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Long-term measurements (2010–2014) of carbonaceous aerosol and carbon monoxide at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia

et al. 2017

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Abstract. We present long-term (5-year) measurements of particulate matter with an upper diameter limit of ∼ 10 µm (PM 10 ), elemental carbon (EC), organic carbon (OC), and water-soluble organic carbon (WSOC) in aerosol filter samples collected at the Zotino Tall Tower Observatory in the middle-taiga subzone (Siberia). The data are complemented with carbon monoxide (CO) measurements. Air mass back trajectory analysis and satellite image analysis were used to characterise potential source regions and the transport pathway of haze plumes. Polluted and background periods were selected using a non-parametric statistical approach and analysed separately. In addition, near-pristine air masses were selected based on their EC concentrations being below the detection limit of our thermal-optical instrument. Over the entire sampling campaign, 75 and 48 % of air masses in winter and in summer, respectively, and 42 % in spring and fall are classified as polluted. The observed background concentrations of CO and EC showed a sine-like behaviour with a period of 365 ± 4 days, mostly due to different degrees of dilution and the removal of polluted air masses arriving at the Zotino Tall Tower Observatory (ZOTTO) from remote sources. Our analysis of the near-pristine conditions shows that the longest periods with clean air masses were observed in summer, with a frequency of 17 %, while in wintertime only 1 % can be classified as a clean. Against a background of low concentrations of CO, EC, and OC in the near-pristine summertime, it was possible to identify pollution plumes that most likely came from crude-oil production sites located in the oil-rich regions of Western Siberia. Overall, our analysis indicates that most of the time the Siberian region is impacted by atmospheric pollution arising from biomass burning and anthropogenic emissions. A relatively clean atmosphere can be observed mainly in summer, when polluted species are removed by precipitation and the aerosol burden returns to near-pristine conditions.

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Section: Polluted Air In the Transition Seasonssupporting

confidence: 64%

Section: Characterisation Of Polluted Airmentioning

confidence: 99%

Section: Near-pristine Airmentioning

confidence: 99%

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Long-term measurements (2010–2014) of carbonaceous aerosol and carbon monoxide at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia

et al. 2017

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“…The method of levoglucosan extraction from the particulate samples was developed from Dhammapala et al (2007). The sampling filters were spiked with 20 µL of 1000 mg L -1 methyl β-D-xylopyranoside (internal standard for levoglucosan) sonicated in 15 mL ethyl acetate for 30 minutes at a controlled temperature (~10°C).…”

Section: Extraction and Analysis Of Levoglucosanmentioning

confidence: 99%

Investigation of Biomass Burning Chemical Components over Northern Southeast Asia during 7-SEAS/BASELInE 2014 Campaign

Khamkaew

Chantara

Janta

et al. 2016

Aerosol Air Qual. Res.

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This study investigates the chemical components of biomass burning (BB) aerosols obtained from Doi Ang Khang (DAK; near BB source) and Chiang Mai University (CMU; an urban location) over northern Southeast Asia in dry season (March to mid-April) 2014. PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm) samples were collected over a 24-h sampling period as a part of the Seven South East Asian Studies ) and CMU (90.7-93.1 µg m -3 ) were not significantly different (p > 0.05) and well correlated (r = 0.8), and likely originated from similar source origins. The number of fire hotspots was particularly high during 20-21 March (greater than 200) and, consequently, peaks of PM 2.5 were recorded at both sites. The most abundant elements at both sampling sites were K (49-50% of total elements), Al (26-31%), Mg (16%) and Zn (4-7%), whereas SO 4 2-(30-38% of total ions), NO 3 -(13-20%), Na + (16-20%) and NH 4 + (14-15%) were the most abundant ions. Concentrations of levoglucosan and K + (BB tracers) were well correlated (r = 0.5 for CMU and 0.7 for DAK) confirming that the PM 2.5 detected in these areas were mainly influenced by BB activity. Principal component analysis (PCA) revealed that BB, road traffic, agricultural activity and soil re-suspension were plausible sources of PM 2.5 over the study locations. Apart from local sources, the influence of long-range transport was also investigated by way of three-day backward trajectory analysis.

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“…PAH EFs for stationary sources that were published between 1999 and the present are not substantially different from those already being used in SMOKE. For example, recent literature on agricultural burning (e.g., Dhammapala et al, 2007;Hall et al, 2012) reported EFs that were close (within a factor of 205 two) to those already in the inventory. Only emissions from iron and steel production were updated to those in Odabasi et al (2009) for electric arc furnaces, as the values used in Galarneau et al (2007) were derived from literature published before 1990, and were 1-2 orders of magnitude larger (hence likely represented outdated (or absent) pollution control equipment).…”

Section: Gas-particle Partitioningmentioning

confidence: 99%

GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American PAHs and benzene

Whaley

Galarneau

Makar

et al. 2018

Preprint

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Abstract. Environment and Climate Change Canada's online air quality forecasting model, GEM-MACH, was extended to simulate atmospheric concentrations of benzene and seven polycyclic aromatic hydrocarbons (PAHs): phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, and benzo(a)pyrene. In the expanded model, benzene and PAHs are emitted from major point, area, and mobile sources, with emissions based on recent emission factors. Modelled PAHs 5 undergo gas-particle partitioning (whereas benzene is only in the gas phase), atmospheric transport, oxidation, cloud processing, and dry and wet deposition. To represent PAH gas-particle partitioning, the Dachs-Eisenreich scheme was used, and we have improved gas-particle partitioning parameters based on an empirical analysis to get significantly better gas-particle partitioning results than the previous North American PAH model, AURAMS-PAH. Other added process parameterizations in-10 clude the particle phase benzo(a)pyrene reaction with ozone via the Kwamena scheme and gas-phase scavenging of PAHs by snow via vapor sorption to the snow surface.The resulting GEM-MACH-PAH model was used to generate the first online model simulations of PAH emissions, transport, chemical transformation and deposition for a high resolution domain (2.5-km grid cell spacing) in North America, centered on the PAH-data-rich region of southern On-15 tario, Canada and the north-eastern United States. Model output for two seasons was compared to measurements from three monitoring networks spanning Canada and the U.S. Average summertime model results were found to be statistically indistinguishable from measurements of benzene and all seven PAHs. The same was true for the winter seasonal mean, except for benzo(a)pyrene (BaP), which had a statistically significant positive bias. We present evidence that the benzo(a)pyrene results 20 may be ameliorated via further improvements to PM and oxidant processes and transport. Our analysis focused on four key components to the prediction of atmospheric PAH levels: spatial variability; sensitivity to mobile emissions; gas-particle partitioning; and wet deposition. Spatial variability of 1 Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-324 Manuscript under review for journal Geosci. Model Dev. Discussion started: 31 January 2018 c Author(s) 2018. CC BY 4.0 License. PAHs/PM 2.5 at 2.5-km resolution was found to be comparable to measurements. Predicted ambient surface concentrations of benzene and the PAHs were found to be critically dependent on mobile 25 emission factors, indicating the mobile emissions sector has a significant influence on ambient PAH levels in the study region. PAH wet deposition was overestimated due to additive precipitation biases in the model and the measurements. Our overall performance evaluation suggests that GEM-MACH-PAH can provide seasonal estimates for benzene and PAHs and be suitable for emissions scenario simulations. 30

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Emission factors of PAHs, methoxyphenols, levoglucosan, elemental carbon and organic carbon from simulated wheat and Kentucky bluegrass stubble burns

Cited by 89 publications

References 32 publications

Long-term measurements (2010–2014) of carbonaceous aerosol and carbon monoxide at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia

Long-term measurements (2010–2014) of carbonaceous aerosol and carbon monoxide at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia

Investigation of Biomass Burning Chemical Components over Northern Southeast Asia during 7-SEAS/BASELInE 2014 Campaign

GEM-MACH-PAH (rev2488): a new high-resolution chemical transport model for North American PAHs and benzene

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