Trends in atmospheric new-particle formation : 16 years of observations in a boreal-forest environment

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Airborne measurements of aerosols and carbon dioxide during a prescribed fire experiment at a boreal forest site

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Characteristics of new particle formation events and cluster ions at K-puszta, Hungary

Atmospheric new particle formation events were analyzed based on particle size distributions measured with a Differential Mobility Particle Sizer (DMPS) and an Air Ion Spectrometer (AIS) during the BIOSOL (Formation mechanisms, marker compounds, and source apportionment for biogenic atmospheric aerosols) campaign on 22 May-29 June 2006 at the K-puszta measurement site in Hungary. The particle size distribution data were classified into different new particle event classes and growth and formation rates of the particles were calculated. New particle formation was observed on almost all days and the median diameter growth rates of nucleation mode particles increased with increasing particle size. The observed formation rate of 10 nm particles was typically somewhat larger than 1 cm(-3) s(-3) (median 1.2), and the growth rate for sub 3 nm particles was 1.7 nm h(-1) and for nucleation mode 6 nm h(-1). The ambient concentrations of gases or meteorological data were not able to explain the differences in the growth and formation rates or in the particle formation between the days. However, 0.3-1.8 nm cluster ion concentrations correlated negatively with wind speed

Laboratory verification of a new high flow differential mobility particle sizer, and field measurements in Hyytiälä

Measurement of atmospheric sub-10 nm nanoparticle number concentrations has been of substantial interest recently, which, however, is subject to considerable uncertainty. We report a laboratory characterization of a high flow differential mobility particle sizer (HFDMPS), which is based on the Half-mini type differential mobility analyzer (DMA) and nano condensation nuclei counter (A11), and show the first results from atmospheric observations. The HFDMPS utilizes the state-of-the-art aerosol technology, and is optimized for sub-10 nm particle size distribution measurements by a moderate resolution DMA, optimized and characterized low-loss particle sampling line and minimal dilution in the detector. We present an exhaustive laboratory calibration to the HFDMPS and compare the measured size data to the Hyytiala long-term DMPS and Neutral cluster and ion spectrometer. The HFDMPS detects about two times higher 3-10 nm particle concentrations than the long-term DMPS, and the counting uncertainties are halved as compared to the long-term DMPS. The HFDMPS did not observe any sub-2.5 nm particles in Hyytiala, and the reason for that was shown to be the inability of diethylene glycol to condense on such small biogenic particles. Last, we discuss the general implications of our results to the sub-10 nm DMPS based measurements.Peer reviewe

Airborne measurements over the boreal forest of southern Finland during new particle formation events in 2009 and 2010

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Estimating cloud condensation nuclei number concentrations using aerosol optical properties : role of particle number size distribution and parameterization

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS 4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (N-CCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating N-CCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between N-CCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Angstrom exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (sigma(sp)) of PM10 particles. The analysis first showed that the dependence of N-CCN on supersaturation (SS) can be described by a logarithmic fit in the range SS 4. At SS > 0 :4% the average bias ranged from similar to 0.7 to similar to 1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, similar to 1.4-1.9. In other words, at SS > 0:4% N-CCN was estimated with an average uncertainty of approximately 30% by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Angstrom exponent (SAE). The squared correlation coefficients between the AOP-derived and measured N-CCN varied from similar to 0.5 to similar to 0.8. To study the physical explanation of the relationships between N-CCN and AOPs, lognormal unimodal particle size distributions were generated and N-CCN and AOPs were calculated. The simulation showed that the relationships of N-CCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of N-CCN and AOPs were similar to those of the observed ones.Peer reviewe

Biomass-burning smoke episodes in Finland from eastern European wildfires

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