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End date: 2019 × Start date: 2019 × Has files: Yes × Version: publishedVersion × Subject: atmospheric modeling × Subject: particulate matter ×

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Now showing 1 - 4 of 4
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    Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach
    (München : European Geopyhsical Union, 2014) Crippa, M.; Canonaco, F.; Lanz, V.A.; Äijälä, M.; Allan, J.D.; Carbone, S.; Capes, G.; Ceburnis, D.; Dall'Osto, M.; Day, D.A.; DeCarlo, P.F.; Ehn, M.; Eriksson, A.; Freney, E.; Hildebrandt Ruiz, L.; Hillamo, R.; Jimenez, J.L.; Junninen, H.; Kiendler-Scharr, A.; Kortelainen, A.-M.; Kulmala, M.; Laaksonen, A.; Mensah, A.A.; Mohr, C.; Nemitz, E.; O'Dowd, C.; Ovadnevaite, J.; Pandis, S.N.; Petäjä, T.; Poulain, L.; Saarikoski, S.; Sellegri, K.; Swietlicki, E.; Tiitta, P.; Worsnop, D.R.; Baltensperger, U.; Prévôt, A.S.H.
    Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.
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    Comparing two years of Saharan dust source activation obtained by regional modelling and satellite observations
    (München : European Geopyhsical Union, 2013) Tegen, I.; Schepanski, K.; Heinold, B.
    A regional-scale dust model is used to simulate Saharan dust emissions and atmospheric distributions in the years 2007 and 2008. The model results are compared to dust source activation events compiled from infrared dust index imagery from the geostationary Meteosat Second Generation (MSG) satellite. The observed morning maximum in dust source activation frequencies indicates that the breakdown of nocturnal low level jets is an important mechanism for dust source activation in the Sahara. The comparison shows that the time of the day of the onset of dust emission is delayed in the model compared to the observations. Also, the simulated number of dust emission events associated with nocturnal low level jets in mountainous regions is underestimated in the model. The MSG dust index observations indicate a strong increase in dust source activation frequencies in the year 2008 compared to 2007. The difference between the two years is less pronounced in the model. Observations of dust optical thickness, e.g. at stations of the sunphotometer network AERONET, do not show such increase, in agreement with the model results. This indicates that the number of observed dust activation events is only of limited use for estimating actual dust emission fluxes in the Sahara. The ability to reproduce interannual variability of Saharan dust with models remains an important challenge for understanding the controls of the atmospheric dust load.
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    Atmospheric boundary layer top height in South Africa: Measurements with lidar and radiosonde compared to three atmospheric models
    (München : European Geopyhsical Union, 2014) Korhonen, K.; Giannakaki, E.; Mielonen, T.; Pfüller, A.; Laakso, L.; Vakkari, V.; Baars, H.; Engelmann, R.; Beukes, J.P.; Van Zyl, P.G.; Ramandh, A.; Ntsangwane, L.; Josipovic, M.; Tiitta, P.; Fourie, G.; Ngwana, I.; Chiloane, K.; Komppula, M.
    Atmospheric lidar measurements were carried out at Elandsfontein measurement station, on the eastern Highveld approximately 150 km east of Johannesburg in South Africa throughout 2010. The height of the planetary boundary layer (PBL) top was continuously measured using a Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended). High atmospheric variability together with a large surface temperature range and significant seasonal changes in precipitation were observed, which had an impact on the vertical mixing of particulate matter, and hence, on the PBL evolution. The results were compared to radiosondes, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) space-borne lidar measurements and three atmospheric models that followed different approaches to determine the PBL top height. These models included two weather forecast models operated by ECMWF (European Centre for Medium-range Weather Forecasts) and SAWS (South African Weather Service), and one mesoscale prognostic meteorological and air pollution regulatory model TAPM (The Air Pollution Model). The ground-based lidar used in this study was operational for 4935 h during 2010 (49% of the time). The PBL top height was detected 86% of the total measurement time (42% of the total time). Large seasonal and diurnal variations were observed between the different methods utilised. High variation was found when lidar measurements were compared to radiosonde measurements. This could be partially due to the distance between the lidar measurements and the radiosondes, which were 120 km apart. Comparison of lidar measurements to the models indicated that the ECMWF model agreed the best with mean relative difference of 15.4%, while the second best correlation was with the SAWS model with corresponding difference of 20.1%. TAPM was found to have a tendency to underestimate the PBL top height. The wind speeds in the SAWS and TAPM models were strongly underestimated which probably led to underestimation of the vertical wind and turbulence and thus underestimation of the PBL top height. Comparison between ground-based and satellite lidar shows good agreement with a correlation coefficient of 0.88. On average, the daily maximum PBL top height in October (spring) and June (winter) was 2260 m and 1480 m, respectively. To our knowledge, this study is the first long-term study of PBL top heights and PBL growth rates in South Africa.
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    EARLINET: Potential operationality of a research network
    (München : European Geopyhsical Union, 2015) Sicard, M.; D'Amico, G.; Comerón, A.; Mona, L.; Alados-Arboledas, L.; Amodeo, A.; Baars, H.; Baldasano, J.M.; Belegante, L.; Binietoglou, I.; Bravo-Aranda, J.A.; Fernández, A.J.; Fréville, P.; García-Vizcaíno, D.; Giunta, A.; Granados-Muñoz, M.J.; Guerrero-Rascado, J.L.; Hadjimitsis, D.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R.E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.
    In the framework of ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated in the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time, the single calculus chain (SCC) – the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products – was used. All stations sent in real-time measurements of a 1 h duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC, while the optical processing was performed in near-real time after the exercise ended. 98 and 79 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on the lidar data. The paper draws present and future SCC users' attention to the most critical parameters of the SCC product configuration and their possible optimal value but also to the limitations inherent to the raw data. The continuous use of SCC direct and derived products in heterogeneous conditions is used to demonstrate two potential applications of EARLINET infrastructure: the monitoring of a Saharan dust intrusion event and the evaluation of two dust transport models. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modeling, climate research and calibration/validation activities of spaceborne observations.