98 research outputs found
Seasonal cycle and source analyses of aerosol optical properties in a semi-urban environment at Puijo station in Eastern Finland
We introduce a four-year (in 2006–2010) continuous data set of aerosol optical properties at Puijo in Kuopio, Finland. We study the annual and diurnal variation of the aerosol scattering and absorption coefficients, hemispheric backscattering fraction, scattering Ångström exponent, and single scattering albedo, whose median values over this period were 7.2 Mm<sup>−1</sup> (at 550 nm), 1.0 Mm<sup>−1</sup> (at 637 nm), 0.15, 1.93 (between 450 and 550 nm), and 0.85, respectively. The scattering coefficient peaked in the spring and autumn, being 2–4 times those in the summer and winter. An exception was the summer of 2010, when the scattering coefficient was elevated to ~300 Mm<sup>−1</sup> by plumes from forest fires in Russia. The absorption coefficient peaked in the winter when soot-containing particles derived from biomass burning were present. The higher relative absorption coefficients resulted in lower single scattering albedo in winter. The optical properties varied also with wind direction and time of the day, indicating the effect of the local pollutant sources and the age of the particles. Peak values in the single scattering albedo were observed when the wind blew from a paper mill and from the sector without local pollutant sources. These observations were linked, respectively, to the sulphate-rich aerosol from the paper mill and the oxygenated organics in the aged aerosol, which both are known to increase the scattering characteristics of aerosols. Decreases in the single scattering albedo in the morning and afternoon, distinct in the summertime, were linked to the increased traffic density at these hours. The scattering and absorption coefficients of residential and long-range transported aerosol (two separate cloud events) were found to be decreased by clouds. The effect was stronger for the scattering than absorption, indicating preferential activation of the more hygroscopic aerosol with higher scattering characteristics
Cognitive Outcome in Childhood-Onset Epilepsy: A Five-Decade Prospective Cohort Study
Objectives: Little is known about the very long-term cognitive outcome in patients with childhood-onset epilepsy. The aim of this unique prospective population-based cohort study was to examine cognitive outcomes in aging participants with childhood-onset epilepsy (mean onset age = 5.3 years) five decades later (mean age at follow-up = 56.5 years). Methods: The sample consisted of 48 participants with childhood-onset epilepsy and 48 age-matched healthy controls aged 48-63 years. Thirty-six epilepsy participants were in remission and 12 continued to have seizures. Cognitive function was examined with 11 neuropsychological tests measuring language and semantic function, episodic memory, and learning, visuomotor function, executive function, and working memory. Results: The risk of cognitive impairment was very high in participants with continuing seizures; odds ratio (OR) = 11.7 (95% confidence interval [CI] (2.8, 49.6), p = .0008). They exhibited worse performances across measures of language and semantic function, and visuomotor function compared to participants with remitted epilepsy and healthy controls. In the participants with remitted epilepsy, the risk of cognitive impairment was somewhat elevated, but not statistically significant; OR = 2.6 (95% CI [0.9, 7.5], p = .08).Conclusions: Our results showed that the distinction of continued versus discontinued seizures was critical for determining long-term cognitive outcome in childhood-onset epilepsy. Few participants in remission exhibited marked cognitive impairment compared to age-matched peers. However, a subgroup of participants with decades long active epilepsy, continuous seizure activity and anti-epileptic drug (AED) medication, showed clinically significant cognitive impairment and are thus in a more precarious position when entering older age.</div
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One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa
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%
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Characterization of satellite-based proxies for estimating nucleation mode particles over South Africa
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
VVER-1000 SFAT : Final Report on Task FIN A 1073 of the Finnish Support Programme to the IAEA Safeguards
Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis
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
South African EUCAARI measurements: seasonal variation of trace gases and aerosol optical properties
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 cm−3 and the estimated volume of sub-10 μm particles 9.3 μm3 m−3. The aerosol absorption and scattering coefficients at 637 nm were 8.3Mm−1 and 49.5Mm−1, respectively. The mean single-scattering albedo at 637 nm was 0.84 and the A° ngstro¨m 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 southeastern 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.JRC.H.7-Climate Risk Managemen
Spectral dependence of birch and pine pollen optical properties using a synergy of lidar instruments
Active remote sensors equipped with the capability to detect polarization, a shape-relevant parameter, are essential to aerosol particle identification in the vertical domain. Most commonly, the linear particle depolarization ratio has been available at the shorter wavelengths of 355 and/or 532 nm. Recently, linear particle depolarization ratios at longer wavelengths (910, 1064, and 1565 nm) have emerged in lidar aerosol research. In this study, a synergy of three lidars, namely a PollyXT lidar, a Vaisala CL61 ceilometer, and a HALO Photonics StreamLine Pro Doppler lidar, as well as in situ aerosol and pollen observations have been utilized to investigate the spectral dependence of birch and pine pollen particles. We found that, regardless of the pollen type, the linear particle depolarization ratio was subject to the amount of pollen and its relative contribution to the aerosol mixture in the air. More specifically, during birch pollination, characteristic linear particle depolarization ratios of 5 ± 2 % (355 nm), 28 ± 6 % (532 nm), 23 ± 6 % (910 nm), and 33 ± 4 % (1565 nm) were retrieved at the pollen layer. Regarding the pine-dominant period, characteristic linear particle depolarization ratios of 6 ± 2 %, 43 ± 11 %, 22 ± 6 %, and 26 ± 3 % were determined at wavelengths of 355, 532, 910, and 1565 nm, respectively. For birch, the linear particle depolarization ratio at 1565 nm was the highest, followed by the 532 and 910 nm wavelengths, respectively. A sharp decrease at 355 nm was evident for birch pollen. For pine pollen, a maximum at the 532 nm wavelength was observed. There was no significant change in the linear particle depolarization ratio at 910 nm for the pollen types considered in this study. Given the low concentration of pollen in the air, the inclusion of the longer wavelengths (910 and 1565 nm) for the detection of birch and pine can be beneficial due to their sensitivity to trace large aerosol particles.</p
Atomic Layer Deposition of Aluminum Phosphate Based on the Plasma Polymerization of Trimethyl Phosphate
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The AeroCom evaluation and intercomparison of organic aerosol in global models
This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models.
The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition.
Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern.
Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately
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