Browsing by Author "Tiitta, P."
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- ItemAtmospheric 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.
- ItemCharacterization of satellite-based proxies for estimating nucleation mode particles over South Africa(München : European Geopyhsical Union, 2015) Sundström, A.-M.; Nikandrova, A.; Atlaskina, K.; Nieminen, T.; Laakso, L.; Vakkari, V.; Baars, H.; Engelmann, R.; Beukes, J.P.; Van Zyl, P.G.; Josipovic, M.; Tiitta, P.; Chiloane, K.; Piketh, S.; Lihavainen, H.; Lehtinen, K.E.J.; Komppula, M.Proxies for estimating nucleation mode number concentrations and further simplification for their use with satellite data have been presented in Kulmala et al. (2011). In this paper we discuss the underlying assumptions for these simplifications and evaluate the resulting proxies over an area in South Africa based on a comparison with a suite of ground-based measurements available from four different stations. The proxies are formulated in terms of sources (concentrations of precursor gases (NO2 and SO2) and UVB radiation intensity near the surface) and a sink term related to removal of the precursor gases due to condensation on pre-existing aerosols. A-Train satellite data are used as input to compute proxies. Both the input data and the resulting proxies are compared with those obtained from ground-based measurements. In particular, a detailed study is presented on the substitution of the local condensation sink (CS) with satellite aerosol optical depth (AOD), which is a column-integrated parameter. One of the main factors affecting the disagreement between CS and AOD is the presence of elevated aerosol layers. Overall, the correlation between proxies calculated from the in situ data and observed nucleation mode particle number concentrations (Nnuc) remained low. At the time of the satellite overpass (13:00–14:00 LT) the highest correlation is observed for SO2/CS (R2 = 0.2). However, when the proxies are calculated using satellite data, only NO2/AOD showed some correlation with Nnuc (R2 = 0.2). This can be explained by the relatively high uncertainties related especially to the satellite SO2 columns and by the positive correlation that is observed between the ground-based SO2 and NO2 concentrations. In fact, results show that the satellite NO2 columns compare better with in situ SO2 concentration than the satellite SO2 column. Despite the high uncertainties related to the proxies calculated using satellite data, the proxies calculated from the in situ data did not better predict Nnuc. Hence, overall improvements in the formulation of the proxies are needed.
- ItemOne year of Raman lidar observations of free-tropospheric aerosol layers over South Africa(München : European Geopyhsical Union, 2015) Giannakaki, E.; Pfüller, A.; Korhonen, K.; Mielonen, T.; Laakso, L.; Vakkari, V.; Baars, H.; Engelmann, R.; Beukes, J.P.; Van Zyl, P.G.; Josipovic, M.; Tiitta, P.; Chiloane, K.; Piketh, S.; Lihavainen, H.; Lehtinen, K.E.J.; Komppula, M.Raman lidar data obtained over a 1 year period has been analysed in relation to aerosol layers in the free troposphere over the Highveld in South Africa. In total, 375 layers were observed above the boundary layer during the period 30 January 2010 to 31 January 2011. The seasonal behaviour of aerosol layer geometrical characteristics, as well as intensive and extensive optical properties were studied. The highest centre heights of free-tropospheric layers were observed during the South African spring (2520 ± 970 m a.g.l., also elsewhere). The geometrical layer depth was found to be maximum during spring, while it did not show any significant difference for the rest of the seasons. The variability of the analysed intensive and extensive optical properties was high during all seasons. Layers were observed at a mean centre height of 2100 ± 1000 m with an average lidar ratio of 67 ± 25 sr (mean value with 1 standard deviation) at 355 nm and a mean extinction-related Ångström exponent of 1.9 ± 0.8 between 355 and 532 nm during the period under study. Except for the intensive biomass burning period from August to October, the lidar ratios and Ångström exponents are within the range of previous observations for urban/industrial aerosols. During Southern Hemispheric spring, the biomass burning activity is clearly reflected in the optical properties of the observed free-tropospheric layers. Specifically, lidar ratios at 355 nm were 89 ± 21, 57 ± 20, 59 ± 22 and 65 ± 23 sr during spring (September–November), summer (December–February), autumn (March–May) and winter (June–August), respectively. The extinction-related Ångström exponents between 355 and 532 nm measured during spring, summer, autumn and winter were 1.8 ± 0.6, 2.4 ± 0.9, 1.8 ± 0.9 and 1.8 ± 0.6, respectively. The mean columnar aerosol optical depth (AOD) obtained from lidar measurements was found to be 0.46 ± 0.35 at 355 nm and 0.25 ± 0.2 at 532 nm. The contribution of free-tropospheric aerosols on the AOD had a wide range of values with a mean contribution of 46%.
- ItemOrganic 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.
- ItemOrganic aerosol concentration and composition over Europe: Insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis(München : European Geopyhsical Union, 2014) Fountoukis, C.; Megaritis, A.G.; Skyllakou, K.; Charalampidis, P.E.; Pilinis, C.; van der Gon, H.A.C. Denier; Crippa, M.; Canonaco, F.; Mohr, C.; Prévôt, A.S.H.; Allan, J.D.; Poulain, L.; Petäjä, T.; Tiitta, P.; Carbone, S.; Kiendler-Scharr, A.; Nemitz, E.; O'Dowd, C.; Swietlicki, E.; Pandis, S.N.A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.
- ItemSouth African EUCAARI measurements: Seasonal variation of trace gases and aerosol optical properties(München : European Geopyhsical Union, 2012) Laakso, L.; Vakkari, V.; Virkkula, A.; Laakso, H.; Backman, J.; Kulmala, M.; Beukes, J.P.; van Zyl, P.G.; Tiitta, P.; Josipovic, M.; Pienaar, J.J.; Chiloane, K.; Gilardoni, S.; Vignati, E.; Wiedensohler, A.; Tuch, T.; Birmili, W.; Piketh, S.; Collett, K.; Fourie, G.D.; Komppula, M.; Lihavainen, H.; de Leeuw, G.; Kerminen, V.-M.In this paper we introduce new in situ observations of atmospheric aerosols, especially chemical composition, physical and optical properties, on the eastern brink of the heavily polluted Highveld area in South Africa. During the observation period between 11 February 2009 and 31 January 2011, the mean particle number concentration (size range 10–840 nm) was 6310 cm3 and the estimated volume of sub-10 μm particles 9.3 μm3 m−3. The aerosol absorption and scattering coefficients at 637 nm were 8.3 Mm−1 and 49.5 Mm−1, respectively. The mean single-scattering albedo at 637 nm was 0.84 and the Ångström exponent of scattering was 1.5 over the wavelength range 450–635 nm. The mean O3, SO2, NOx and H2S-concentrations were 37.1, 11.5, 15.1 and 3.2 ppb, respectively. The observed range of concentrations was large and attributed to the seasonal variation of sources and regional meteorological effects, especially the anticyclonic re-circulation and strong winter-time inversions. In a global context, the levels of gases and particulates were typical for continental sites with strong anthropogenic influence, but clearly lower than the most polluted areas of south-eastern Asia. Of all pollutants observed at the site, ozone is the most likely to have adverse environmental effects, as the concentrations were high also during the growing season. The measurements presented here will help to close existing gaps in the ground-based global atmosphere observation system, since very little long-term data of this nature is available for southern Africa.