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Article, 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%., published version, http://purl.org/eprint/status/PeerReviewed

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.

Absorption Ångström exponents (AAEs) calculated from filter-based absorption measurements are often used to give information on the origin of the ambient aerosol, for example, to distinguish between urban pollution and biomass burning aerosol. Filter-based absorption measurements are widely used and are common at aerosol monitoring stations globally. Several correction algorithms are used to account for artefacts associated with filter-based absorption techniques. These algorithms are of profound importance when determining the absolute amount of absorption by the aerosol. However, this study shows that there are substantial differences between the AAEs calculated from these corrections. Depending on the used correction, AAEs can change by as much as 46%. The study also highlights that the difference between AAEs calculated using different corrections can lead to conflicting conclusions on the type of aerosol when using the same data set. The AAE ranged between 1.17 for non-corrected data to 1.96 for the correction that gave the greatest values. Furthermore, the study implies that the AAEs reported for a site depend on at which filter transmittance the filter is changed. In this work, the AAEs were calculated from data measured with a three-wavelength particle soot absorption photometer (PSAP) at Elandsfontein on the South African Highveld for 23 months. The sample air of the PSAP was diluted to prolong filter change intervals, by a factor of 15. The correlation coefficient between the dilution-corrected PSAP and a non-diluted Multi-Angle Absorption Photometer (MAAP) was 0.9. Thus, the study also shows that the applicability of the PSAP can be extended to remote sites that are not often visited or suffer from high levels of pollution.

Atmospheric lidar measurements were carried out at Elandsfontein measurement station, on the eastern Highveld approximately 150 km east of Johannesburg in South Africa (SA) 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 (PM), and hence, on the PBL evolution. The results were compared to radio soundings, 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. Comparison of lidar measurements to the models indicated that the ECMWF model agreed the best with mean absolute 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 SAWS operated 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. 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 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) were 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 the Southern Hemisphere. Only a few studies have been performed in Europe and Asia, most of them with less data coverage.