Size distribution and chemical composition of primary particles emitted during open biomass burning processes: Impacts on cloud condensation nuclei activation

2019 ◽  
Vol 674 ◽  
pp. 179-188 ◽  
Author(s):  
Li Chen ◽  
Qing Li ◽  
Di Wu ◽  
Hao Sun ◽  
Yaqi Wei ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Size Distribution ◽  
Biomass Burning ◽  
Cloud Condensation Nuclei ◽  
Condensation Nuclei ◽  
Primary Particles

scholarly journals Physical properties of the sub-micrometer aerosol over the Amazon rain forest during the wet-to-dry season transition - comparison of modeled and measured CCN concentrations

2004 ◽  
Vol 4 (8) ◽  
pp. 2119-2143 ◽  
Author(s):  
J. Rissler ◽  
E. Swietlicki ◽  
J. Zhou ◽  
G. Roberts ◽  
M. O. Andreae ◽  
...  
Keyword(s):  
Size Distribution ◽  
Biomass Burning ◽  
Time Resolution ◽  
Large Scale ◽  
Transition Period ◽  
Cloud Condensation Nuclei ◽  
Particle Diameter ◽  
Hygroscopic Growth ◽  
Condensation Nuclei ◽  
Number Size Distribution

Abstract. Sub-micrometer atmospheric aerosol particles were studied in the Amazon region, 125 km northeast of Manaus, Brazil (-1°55.2'S, 59°28.1'W). The measurements were performed during the wet-to-dry transition period, 4-28 July 2001 as part of the LBA (Large-Scale Biosphere Atmosphere Experiment in Amazonia) CLAIRE-2001 (Cooperative LBA Airborne Regional Experiment) experiment. The number size distribution was measured with two parallel differential mobility analyzers, the hygroscopic growth at 90% RH with a Hygroscopic Tandem Mobility Analyzer (H-TDMA) and the concentrations of cloud condensation nuclei (CCN) with a cloud condensation nuclei counter. A model was developed that uses the H-TDMA data to predict the number of soluble molecules or ions in the individual particles and the corresponding minimum particle diameter for activation into a cloud droplet at a certain supersaturation. Integrating the number size distribution above this diameter, CCN concentrations were predicted with a time resolution of 10 min and compared to the measured concentrations. During the study period, three different air masses were identified and compared: clean background, air influenced by aged biomass burning, and moderately polluted air from recent local biomass burning. For the clean period 2001, similar number size distributions and hygroscopic behavior were observed as during the wet season at the same site in 1998, with mostly internally mixed particles of low diameter growth factor (~1.3 taken from dry to 90% RH). During the periods influenced by biomass burning the hygroscopic growth changed slightly, but the largest difference was seen in the number size distribution. The CCN model was found to be successful in predicting the measured CCN concentrations, typically within 25%. A sensitivity study showed relatively small dependence on the assumption of which model salt that was used to predict CCN concentrations from H-TDMA data. One strength of using H-TDMA data to predict CCN concentrations is that the model can also take into account soluble organic compounds, insofar as they go into solution at 90% RH. Another advantage is the higher time resolution compared to using size-resolved chemical composition data.

scholarly journals Air mass physiochemical characteristics over New Delhi: impacts on aerosol hygroscopicity and cloud condensation nuclei (CCN) formation

2020 ◽  
Vol 20 (11) ◽  
pp. 6953-6971 ◽  
Author(s):  
Zainab Arub ◽  
Sahil Bhandari ◽  
Shahzad Gani ◽  
Joshua S. Apte ◽  
Lea Hildebrandt Ruiz ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Size Distribution ◽  
Cloud Condensation Nuclei ◽  
Chemical Properties ◽  
Industrial Emissions ◽  
Condensation Nuclei ◽  
Aerosol Composition ◽  
Time Resolved ◽  
Air Mass ◽  
Air Masses

Abstract. Delhi is a megacity subject to high local anthropogenic emissions and long-range transport of pollutants. This work presents for the first time time-resolved estimates of hygroscopicity parameter (κ) and cloud condensation nuclei (CCN), spanning for more than a year, derived from chemical composition and size distribution data. As a part of the Delhi Aerosol Supersite (DAS) campaign, the characterization of aerosol composition and size distribution was conducted from January 2017 to March 2018. Air masses originating from the Arabian Sea (AS), Bay of Bengal (BB), and southern Asia (SA) exhibited distinct characteristics of time-resolved sub-micron non-refractory PM1 (NRPM1) species, size distributions, and CCN number concentrations. The SA air mass had the highest NRPM1 loading with high chloride and organics, followed by the BB air mass, which was more contaminated than AS, with a higher organic fraction and nitrate. The primary sources were identified as biomass-burning, thermal power plant emissions, industrial emissions, and vehicular emissions. The average hygroscopicity parameter (κ), calculated by the mixing rule, was approximately 0.3 (varying between 0.13 and 0.77) for all the air masses (0.32±0.06 for AS, 0.31±0.06 for BB, and 0.32±0.10 for SA). The diurnal variations in κ were impacted by the chemical properties and thus source activities. The total, Aitken, and accumulation mode number concentrations were higher for SA, followed by BB and AS. The mean values of estimated CCN number concentration (NCCN; 3669–28926 cm−3) and the activated fraction (af; 0.19–0.87), for supersaturations varying from 0.1 % to 0.8 %, also showed the same trend, implying that these were highest in SA, followed by those in BB and then those in AS. The size turned out to be more important than chemical composition directly, and the NCCN was governed by either the Aitken or accumulation modes, depending upon the supersaturation (SS) and critical diameter (Dc). af was governed mainly by the geometric mean diameter (GMD), and such a high af (0.71±0.14 for the most dominant sub-branch of the SA air mass – R1 – at 0.4 % SS) has not been seen anywhere in the world for a continental site. The high af was a consequence of very low Dc (25–130 nm, for SS ranging from 0.1 % to 0.8 %) observed for Delhi. Indirectly, the chemical properties also impacted CCN and af by impacting the diurnal patterns of Aitken and accumulation modes, κ and Dc. The high-hygroscopic nature of aerosols, high NCCN, and high af can severely impact the precipitation patterns of the Indian monsoon in Delhi, impact the radiation budget, and have indirect effects and need to be investigated to quantify this impact.

scholarly journals Physical properties of the sub-micrometer aerosol over the Amazon rain forest during the wet-to-dry season transition – comparison of modeled and measured CCN concentrations

2004 ◽  
Vol 4 (3) ◽  
pp. 3159-3225 ◽  
Author(s):  
J. Rissler ◽  
E. Swietlicki ◽  
J. Zhou ◽  
G. Roberts ◽  
M. O. Andreae ◽  
...  
Keyword(s):  
Size Distribution ◽  
Biomass Burning ◽  
Time Resolution ◽  
Large Scale ◽  
Transition Period ◽  
Cloud Condensation Nuclei ◽  
Particle Diameter ◽  
Hygroscopic Growth ◽  
Condensation Nuclei ◽  
Number Size Distribution

Abstract. We studied the sub-micrometer atmospheric aerosol particles in the Amazon region, 125 km northeast of Manaus (−1°55.2' S, 59°28.1' W). The measurements were performed during the wet-to-dry transition period, 4–28 July 2001 as part of the LBA (Large-Scale Biosphere Atmosphere Experiment in Amazonia) CLAIRE-2001 (Cooperative LBA Airborne Regional Experiment) experiment. The number size distribution was measured with two parallel differential mobility analyzers, the hygroscopic growth at 90% RH with a hygroscopic tandem mobility analyzer (H-TDMA) and the concentrations of cloud condensation nuclei (CCN) with a cloud condensation nuclei counter (CCNC). We developed a model to predict from H-TDMA data the number of soluble molecules or ions in the particles and the corresponding minimum particle diameter for activation to a cloud droplet at a certain supersaturation. Integrating the number size distribution above this diameter, CCN concentrations were predicted with a time resolution of 10 min and compared to the measured concentrations. During the study period, three different air masses were classified and compared: clean background, air influenced by aged biomass burning, and moderately polluted air from fresh local burning. For the clean period 2001, similar number size distributions and hygroscopic behavior were observed as during the wet season at the same site in 1998, with mostly internally mixed particles of low diameter growth factor (Gf~1.3 taken from dry to 90% RH). During the periods influenced by biomass burning the hygroscopic growth changed slightly, but the largest difference was seen in the number size distribution. The CCN model was found to be successful in predicting the measured CCN concentrations, typically within 25%. A sensitivity study showed relatively small dependence on the assumption of which model salt that was used to predict CCN concentrations from H-TDMA data. One strength of using H-TDMA data to predict CCN concentrations is that the model can also take into account the solubility of organic compounds, insofar as they go into solution at 90% RH. Another advantage is the higher time resolution compared to using size-resolved chemical composition data.

scholarly journals Measured and modelled cloud condensation nuclei number concentration at the high alpine site Jungfraujoch

2010 ◽  
Vol 10 (16) ◽  
pp. 7891-7906 ◽  
Author(s):  
Z. Jurányi ◽  
M. Gysel ◽  
E. Weingartner ◽  
P. F. DeCarlo ◽  
L. Kammermann ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Hydrological Cycle ◽  
Cloud Condensation Nuclei ◽  
Sensitivity Study ◽  
Research Station ◽  
Condensation Nuclei ◽  
Composition Data ◽  
Particle Mobility ◽  
Kohler Theory ◽  
Highly Correlated

Abstract. Atmospheric aerosol particles are able to act as cloud condensation nuclei (CCN) and are therefore important for the climate and the hydrological cycle, but their properties are not fully understood. Total CCN number concentrations at 10 different supersaturations in the range of SS=0.12–1.18% were measured in May 2008 at the remote high alpine research station, Jungfraujoch, Switzerland (3580 m a.s.l.). In this paper, we present a closure study between measured and predicted CCN number concentrations. CCN predictions were done using dry number size distribution (scanning particle mobility sizer, SMPS) and bulk chemical composition data (aerosol mass spectrometer, AMS, and multi-angle absorption photometer, MAAP) in a simplified Köhler theory. The predicted and the measured CCN number concentrations agree very well and are highly correlated. A sensitivity study showed that the temporal variability of the chemical composition at the Jungfraujoch can be neglected for a reliable CCN prediction, whereas it is important to know the mean chemical composition. The exact bias introduced by using a too low or too high hygroscopicity parameter for CCN prediction was further quantified and shown to be substantial for the lowest supersaturation. Despite the high average organic mass fraction (~45%) in the fine mode, there was no indication that the surface tension was substantially reduced at the point of CCN activation. A comparison between hygroscopicity tandem differential mobility analyzer (HTDMA), AMS/MAAP, and CCN derived κ values showed that HTDMA measurements can be used to determine particle hygroscopicity required for CCN predictions if no suitable chemical composition data are available.

scholarly journals Cloud activation properties of aerosol particles in a continental Central European urban environment

2021 ◽  
Vol 21 (14) ◽  
pp. 11289-11302
Author(s):  
Imre Salma ◽  
Wanda Thén ◽  
Máté Vörösmarty ◽  
András Zénó Gyöngyösi
Keyword(s):  
Chemical Composition ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Urban Aerosol ◽  
Condensation Nuclei ◽  
Frequency Distributions ◽  
Remote Locations ◽  
Cloud Activation

Abstract. Collocated measurements using a condensation particle counter, differential mobility particle sizer and cloud condensation nuclei counter were realised in parallel in central Budapest from 15 April 2019 to 14 April 2020 to gain insight into the cloud activation properties of urban aerosol particles. The median total particle number concentration was 10.1 × 103 cm−3. The median concentrations of cloud condensation nuclei (CCN) at water vapour supersaturation (S) values of 0.1 %, 0.2 %, 0.3 %, 0.5 % and 1.0 % were 0.59, 1.09, 1.39, 1.80 and 2.5 × 103 cm−3, respectively. The CCN concentrations represented 7–27 % of all particles. The CCN concentrations were considerably larger but the activation fractions were systematically substantially smaller than observed in regional or remote locations. The effective critical dry particle diameters (dc,eff) were derived utilising the CCN concentrations and particle number size distributions. Their median values at the five supersaturation values considered were 207, 149, 126, 105 and 80 nm, respectively; all of these diameters were positioned within the accumulation mode of the typical particle number size distribution. Their frequency distributions revealed a single peak for which the geometric standard deviation increased monotonically with S. This broadening indicated high time variability in the activating properties of smaller particles. The frequency distributions also showed fine structure, with several compositional elements that seemed to reveal a consistent or monotonical tendency with S. The relationships between the critical S and dc,eff suggest that urban aerosol particles in Budapest with diameters larger than approximately 130 nm showed similar hydroscopicity to corresponding continental aerosol particles, whereas smaller particles in Budapest were less hygroscopic than corresponding continental aerosol particles. Only modest seasonal cycling in CCN concentrations and activation fractions was seen, and only for large S values. This cycling likely reflects changes in the number concentration, chemical composition and mixing state of the particles. The seasonal dependencies of dc,eff were featureless, indicating that the droplet activation properties of the urban particles remained more or less the same throughout the year. This is again different from what is seen in non-urban locations. Hygroscopicity parameters (κ values) were computed without determining the time-dependent chemical composition of the particles. The median values for κ were 0.15, 0.10, 0.07, 0.04 and 0.02, respectively, at the five supersaturation values considered. The averages suggested that the larger particles were considerably more hygroscopic than the smaller particles. We found that the κ values for the urban aerosol were substantially smaller than those previously reported for aerosols in regional or remote locations. All of these characteristics can be linked to the specific source composition of particles in cities. The relatively large variability in the hygroscopicity parameters for a given S emphasises that the individual values represent the CCN population in ambient air while the average hygroscopicity parameter mainly corresponds to particles with sizes close to the effective critical dry particle diameter.

scholarly journals Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model

2012 ◽  
Vol 12 (1) ◽  
pp. 623-689 ◽  
Author(s):  
G. W. Mann ◽  
K. S. Carslaw ◽  
D. A. Ridley ◽  
D. V. Spracklen ◽  
K. J. Pringle ◽  
...  
Keyword(s):  
Size Distribution ◽  
Transport Model ◽  
Cloud Condensation Nuclei ◽  
Particle Growth ◽  
Free Troposphere ◽  
Chemical Transport Model ◽  
Condensation Nuclei ◽  
Chemistry Transport Model ◽  
Surface Mass ◽  
Cloud Processing

Abstract. A global modal aerosol microphysics module (GLOMAP-mode) is evaluated and improved by comparing against a sectional version (GLOMAP-bin) and observations in the same 3-D global offline chemistry transport model. With both schemes, the model captures the main features of the global particle size distribution, with sub-micron aerosol approximately unimodal in continental regions and bi-modal in marine regions. Initial bin-mode comparisons showed that various size distribution parameter settings (mode widths and inter-modal separation sizes) resulted in clear biases compared to the sectional scheme. By adjusting these parameters in the modal scheme, much better agreement is achieved against the bin scheme and observations. Surface mass of sulphate, sea-salt, black carbon (BC) and organic carbon (OC) are, on the annual mean, within 25 % in the two schemes in nearly all regions. On the annual mean, surface level concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), surface area density and condensation sink also compare within 25 % in most regions. However, marine CCN concentrations between 30° N and 30° S are systematically higher in the modal scheme, by 25–60 %, which we attribute to differences in size-resolved particle growth or cloud-processing. Larger differences also exist in regions or seasons dominated by biomass burning and in free-troposphere and high-latitude regions. Indeed, in the free-troposphere, GLOMAP-mode BC is a factor 2–4 higher than GLOMAP-bin, likely due to differences in size-resolved scavenging. Nevertheless, in most parts of the atmosphere, we conclude that bin-mode differences are much less than model-observation differences, although some processes are missing in these runs which may pose a bigger challenge to modal schemes (e.g. boundary layer nucleation, ultra-fine sea-spray). The findings here underline the need for a spectrum of complexity in global models, with size-resolved aerosol properties predicted by modal schemes needing to be continually benchmarked and improved against freely evolving sectional schemes and observations.

scholarly journals Measured and modelled Cloud Condensation Nuclei (CCN) concentration in São Paulo, Brazil: the importance of aerosol size-resolved chemical composition on CCN concentration prediction

2013 ◽  
Vol 13 (12) ◽  
pp. 32353-32389 ◽  
Author(s):  
G. P. Almeida ◽  
J. Brito ◽  
C. A. Morales ◽  
M. F. Andrade ◽  
P. Artaxo
Keyword(s):  
Chemical Composition ◽  
Real Time ◽  
Cloud Condensation Nuclei ◽  
Bulk Composition ◽  
Sao Paulo ◽  
Aerosol Size Distribution ◽  
São Paulo ◽  
Condensation Nuclei ◽  
Aerosol Composition ◽  
The Impact

Abstract. Measurements of cloud condensation nuclei (CCN), aerosol size distribution and non-refractory chemical composition were performed from 16 to 31 October 2012 in the São Paulo Metropolitan Area (SPMA), Brazil. CCN measurements were performed at 0.2%, 0.4%, 0.6%, 0.8% and 1.0% water supersaturation and were subsequently compared with Köhler theory, considering the chemical composition. Real-time chemical composition has been obtained deploying for the first time in SPMA an Aerosol Chemical Ionization Monitor (ACSM). CCN closure analyses were performed considering internal mixture. Average aerosol composition during the studied period yielded 4.81 ± 3.05, 3.26 ± 2.10, 0.30 ± 0.27, 0.52 ± 0.32, 0.37 ± 0.21 and 0.04 ± 0.04 μg m−3 for organics, BC, NH4, SO4, NO3 and Cl, respectively. Particle number concentration was 12 813 ± 5350 cm−3, being a large fraction in the nucleation mode. CCN concentrations were on average 1090 ± 328 cm−3 and 3570 ± 1695 cm−3 at SS = 0.2% and SS = 1.0%, respectively. Results show an increase in aerosol hygroscopicity in the afternoon as a result of aerosol photochemical processing, leading to an enhancement of both organic and inorganic secondary aerosols in the atmosphere, as well as an increase in aerosol average diameter. Considering the bulk composition alone, CCN concentrations were substantially overpredicted (29.6 ± 45.1% at 0.2% supersaturation and 57.3 ± 30.0% at 1.0% supersaturation). Overall, the impact of composition on the calculated NCCN decreases with decreasing supersaturation, partially because using bulk composition introduces less bias for large diameters and lower critical supersaturations. Results suggest that the consideration of only inorganic fraction improves the calculated NCCN. Introducing a size-dependent chemical composition based on filter measurements from previous campaigns has considerably improved simulated values for NCCN (average overprediction error 3.0 ± 33.4% at 0.20% supersaturation and average under prediction error 2.4 ± 20.5% at 1.0% supersaturation). This study provides the first insight on aerosol real-time composition and hygroscopicity on a~site strongly impacted by emissions of a unique vehicular fleet due to the extensive biofuel usage.

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