Biomass burning aerosol emissions from vegetation fires: particle number and mass emission factors and size distributions

Janhäll, Sara; Pöschl, Ulrich

doi:10.5194/acpd-9-17183-2009

Cited by 59 publications

(97 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…), in contrast to much higher ΔNCN,10/ΔcCO levels for urban (100 -300 cm -3 ppb -1 ) and power plant emissions (up to 900 cm -3 ppb -1 ) (Janhaell et al, 2010;Kuhn et al, 2010; 15 Andreae et al, 2012). Furthermore, the ratios of excess NCCN(S) to excess cCO, ΔNCCN(S)/ΔcCO, for the individual S levels range between 6.7 ± 0.5 cm -3 ppb -1 for the lowest S = 0.11 % and values around 18.0 ± 1.3 cm -3 ppb -1 for higher S (see Table S1 and ), 'swamping' the Aitken mode DAit = 70 ± 1 nm, NAit = ~140 cm -3 ) almost completely, giving the entire distribution a monomodal appearance.…”

mentioning

confidence: 98%

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

Pöhlker

Ditas

Saturno

et al. 2017

Preprint

View full text Add to dashboard Cite

Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014 -Feb 2015. In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different para-5 metrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et. al. 2016b).The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere: ), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range. Atmos. Chem. Phys. Discuss., https://doi

show abstract

mentioning

confidence: 98%

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

Pöhlker

Ditas

Saturno

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…The dry particle size distribution is determined by an accumulation mode with a count median or geometric mean diameter of D g =120 nm, a geometric standard deviation of σ g =1.5 (Reid et al, 2005;Janhäll et al, 2009), and the hygroscopic properties are described by an effective hygroscopicity parameter of 0.2 (Andreae and Rose et al, 2008b;. The effects of variations in hygroscopicity will be addressed below (Sect.…”

Section: Different Regimes Of Ccn Activationmentioning

confidence: 99%

“…In another set of model simulations we added a coarse particle mode with D g,c =5 µm and σ g,c =1.3, and we assigned different fractions of N CN to this mode (f N,c =10 −5 to 10 −3 ; Reid et al, 2005;Liu et al, 2008;Janhäll et al, 2009). With f N,c =10 −5 and in the aerosol-limited regime, the coarse particle mode had practically no influence on N CD ( N CD /N CD ≈0).…”

Section: Hygroscopicity Effectsmentioning

confidence: 99%

“…Hjelmfelt et al, 1978;Hegg, 1999;Nenes et al, 2001;Feingold, 2003;Lance et al, 2004;Lohmann et al, 2004;Ervens et al, 2005;Segal and Khain, 2006;Kivekas et al, 2008;Cubison et al, 2008;Altaratz et al, 2008). This is realistic for regions with low or moderate air pollution, but in biomass burning plumes the aerosol particle number concentrations can reach up to ∼10 5 cm −3 Reid et al, 2005;Janhäll et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN)

et al. 2009

Self Cite

View full text Add to dashboard Cite

Abstract.We have investigated the formation of cloud droplets under pyro-convective conditions using a cloud parcel model with detailed spectral microphysics and with the κ-Köhler model approach for efficient and realistic description of the cloud condensation nucleus (CCN) activity of aerosol particles. Assuming a typical biomass burning aerosol size distribution (accumulation mode centred at 120 nm), we have calculated initial cloud droplet number concentrations (N CD ) for a wide range of updraft velocities (w=0.25-20 m s −1 ) and aerosol particle number concentrations (N CN =200-10 5 cm −3 ) at the cloud base. Depending on the ratio between updraft velocity and particle number concentration (w/N CN ), we found three distinctly different regimes of CCN activation and cloud droplet formation:(1) An aerosol-limited regime that is characterized by high w/N CN ratios (>≈10 −3 m s −1 cm 3 ), high maximum values of water vapour supersaturation (S max >≈0.5%), and high activated fractions of aerosol particles (N CD /N CN >≈90%). In this regime N CD is directly proportional to N CN and practically independent of w.(2) An updraft-limited regime that is characterized by low w/N CN ratios (<≈10 −4 m s −1 cm 3 ), low maximum values of water vapour supersaturation (S max <≈0.2%), and low activated fractions of aerosol particles (N CD /N CN <≈20%). In this regime N CD is directly proportional to w and practically independent of N CN .Correspondence to: H. Su (hsu@mpch-mainz.mpg.de) (3) An aerosol-and updraft-sensitive regime (transitional regime), which is characterized by parameter values in between the two other regimes and covers most of the conditions relevant for pyro-convection. In this regime N CD depends non-linearly on both N CN and w.In sensitivity studies we have tested the influence of aerosol particle size distribution and hygroscopicity on N CD . Within the range of effective hygroscopicity parameters that is characteristic for continental atmospheric aerosols (κ≈0.05-0.6), we found that N CD depends rather weakly on the actual value of κ. A compensation of changes in κ and S max leads to an effective buffering of N CD . Only for aerosols with very low hygroscopicity (κ<0.05) and also in the updraft-limited regime for aerosols with higher than average hygroscopicity (κ>0.3) did the relative sensitivities ∂lnN CD /∂lnκ≈ ( N CD /N CD )/( κ/κ) exceed values of ∼0.2, indicating that a 50% difference in κ would change N CD by more than 10%.The influence of changing size distribution parameters was stronger than that of particle hygroscopicity. Nevertheless, similar regimes of CCN activation were observed in simulations with varying types of size distributions (polluted and pristine continental and marine aerosols with different proportions of nucleation, Aitken, accumulation, and coarse mode particles). In general, the different regimes can be discriminated with regard to the relative sensitivities of N CD against w and N CN (∂lnN CD /∂lnw and ∂lnN CD /∂lnN CN ). We propose to separate the different regimes by rel...

show abstract

“…Lognormal functions are generally used to describe aerosol particle dimensions (William C. Hinds, 1999), and also in specific cases such as marine aerosol (Smith et al, 1993) or biomass burning aerosol emissions from vegetation fires (Janhäll et al, 2009). Multi-modal lognormal fitting was performed using OriginPro 8.5 software (OriginLab®, Northampton, MA, USA), and each mode was described following Equation 1.…”

Section: Scanning Electron Microscopy and Energy-dispersive X-ray Spementioning

confidence: 99%

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

Sgrigna

Baldacchini

Esposito

et al. 2016

Science of The Total Environment

View full text Add to dashboard Cite

This study reports application of monitoring and characterization protocol for particulate matter (PM) deposited on tree leaves, using Quercus ilex as a case study species. The study area is located in the industrial city of Terni in central Italy, with high PM concentrations. Four trees were selected as representative of distinct pollution environments based on their proximity to a steel factory and a street. Wash off from leaves onto cellulose filters were characterized using scanning electron microscopy and energy dispersive X-ray spectroscopy, inferring the associations between particle sizes, chemical composition, and sampling location.Modeling of particle size distributions showed a tri-modal fingerprint, with the three modes centered at 0.6 (factory related), 1.2 (urban background), and 2.6 μm (traffic related). Chemical detection identified 23 elements abundant in the PM samples. Principal component analysis recognized iron and copper as sourcespecific PM markers, attributed mainly to industrial and heavy traffic pollution respectively. Upscaling these results on leaf area basis provided a useful indicator for strategic evaluation of harmful PM pollutants using tree leaves.

show abstract

Biomass burning aerosol emissions from vegetation fires: particle number and mass emission factors and size distributions

Cited by 59 publications

References 72 publications

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN)

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

Contact Info

Product

Resources

About