| 1. |
- Kulmala, M., et al.
(författare)
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General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) - integrating aerosol research from nano to global scales
- 2011
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 11:24, s. 13061-13143
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.
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| 2. |
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| 3. |
- Vuollekoski, H., et al.
(författare)
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A numerical comparison of different methods for determining the particle formation rate
- 2012
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 12:5, s. 2289-2295
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Tidskriftsartikel (refereegranskat)abstract
- Different methods of determining formation rates of 3 nm particles are compared, basing on analysis of simulated data, but the results are valid for analyses of experimental particle size distribution data as well, at least within the accuracy of the applied model. The study shows that the method of determining formation rates indirectly from measured number concentration data of 3-6 nm particles is generally in good agreement with the theoretical calculation with a systematic error of 0-20%. While this accuracy is often enough, a simple modification to the approximative equation for the formation rate is recommended. A brief study on real atmospheric data implied that in some cases the accuracy gain may be significant.
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| 4. |
- Vuollekoski, H., et al.
(författare)
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MECCO : A method to estimate concentrations of condensing organics-Description and evaluation of a Markov chain Monte Carlo application
- 2010
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Ingår i: Journal of Aerosol Science. - : Elsevier BV. - 0021-8502 .- 1879-1964. ; 41:12, s. 1080-1089
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Tidskriftsartikel (refereegranskat)abstract
- The development of a new method to estimate concentrations of condensing organics (MECCO) is described. A Markov chain Monte Carlo method is applied, and by using measured particle size distribution and random vapor concentrations as input, the predicted changes in particle population by an aerosol dynamics model are utilized. The method provides the ambient vapor concentrations required for the observed particle growth in particle number size distribution data, assuming all growth can be attributed to net condensation of super-saturated vapors. In this paper, MECCO was coupled with the UHMA box-model to provide aerosol dynamics. With few changes, MECCO could be applied to study other input parameters, and coupled with other dynamics models as well. Evaluation of the method was carried out with simulated output from the UHMA model using the assumption of three organic vapors, and MECCO-UHMA was able to estimate their concentrations with great accuracy. However, the condensation of vapors is currently considered irreversible, since the used particle size distribution data do not provide information on the composition of particles. The distinguishing between the vapors is based on few vapor parameters, which limits the possibilities of identifying actual vapors. An example of atmospheric application is also presented. This revealed the importance of quality control of the input particle concentrations: instrumental noise and changes in the observed air mass pose challenges for the presented method. Data need to be smoothed in a reasonable way so that the point-like measurements can be utilized, but also so that the important information on particle growth is conserved. MECCO is a useful tool to approximate vapor concentrations and may be applied to estimate vapor properties as well. However, a computationally efficient and physically accurate aerosol dynamics model is essential for MECCO's performance.
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