Factors Influencing the Variability of SO2 Concentrations in Istanbul

ABSTRACT

The correlation between sulfur dioxide (SO₂) concentrations measured at the European and Asian sides of Istanbul and meteorological parameters is investigated using principal component analysis (PCA) and multiple regression analysis techniques. Several meteorological parameters are selected to represent the atmospheric conditions during two winter periods: 1993–1994 and 1994–1995. Six principal components are found to explain the majority of the observed meteorological variability. Surface pressure, 850-mb temperature, and surface zonal (east-west) and meridional (north-south) winds show high loadings on separate factors identified by PCA. We seek dominant meteorological parameters that control the SO₂ levels at each monitoring station. Several multiple regression analysis models are fitted to the data from each monitoring station using six principal components and previous day SO₂ concentrations as independent variables.

Results suggest that the most important parameters, highly correlated with SO₂ concentrations in the Istanbul metropolitan area, are atmospheric pressure and surface zonal and meridional winds. These components have more influence on the determination of the air pollution levels at the Asian side than at the European side.     

Variability of atmospheric dust loading over the central Tibetan Plateau based on ice core glaciochemistry

A Mt. Geladaindong (GL) ice core was recovered from the central Tibetan Plateau (TP) spanning the period 1940–2005 AD. High-resolution major ion (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄^2?, NO₃^?) time-series are used to investigate variations in atmospheric dust loading through time. The crustal source ions vary seasonally with peaks in dust concentrations occurring during the winter and spring which are consistent with atmospheric dust observations at local meteorological stations. However, both similarities and dissimilarities are displayed between the decadal variation of atmospheric dust in the GL core and dust observation records from meteorological stations, which can be attributed to local environmental effects at the stations. This paper compares the 1980s and 1970s as case periods for low and high atmospheric dust loading, respectively, two periods reflecting shifts in spring atmospheric circulation (a weakening of zonal and meridional winds) from the 1970s (a period of enhanced dust aerosol transportation to central TP) to the 1980s (a period of diminished dust aerosol transportation to central TP), especially a significant decrease of meridional wind speeds in the 1980s. GL ice core dust proxies (Ca²⁺ and K⁺) are correlated with Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data in spring over the TP and in the northwestern China (especially for K⁺). Thus variability of crustal ions in central TP ice core provides a proxy for reconstructing a history of atmospheric dust loading not only on the TP, but also in northwestern China.     

On the relationship between acid rain and cloud type

Spanish European Monitoring and Evaluation Programme (EMEP) stations were selected to relate acid rain episodes with the meteorological structure that caused the rainfall during a 5-year period. A principal component analysis (PCA) was used to determine the origin of major ions (SO4(2-), NO3-, Cl-, Ca2+, K+, Mg2+, and Na+) in the rainwater. In addition, the meteorological origin of the rain was identified. Previous works suggested a relationship between acid rain and storm convective clouds. However, statistical analyses of pH values show that only the short-lived convective phenomena may cause acid rain in Spain. In fact, rain generated by fronts and that related to long-lived convective systems is neutral or even slightly basic. Results suggest that the acid rain might be related to the meteorological time scale instead of to the cloud type.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Analysis of atmospheric conditions during air pollution episodes in Ankara, Turkey

This paper presents a detailed analysis of the meteorological conditions that are associated with strong air pollution episodes in Ankara, Turkey. Based on climatological and air quality data [SO2 and TSP (total suspended particulates)] obtained for the winter months during 1989-1994, the analysis showed that the presence of weak atmospheric pressure gradients and warm air advection were the most important factors leading to high SO2 and TSP concentrations. In addition, the onset of the high air pollution episodes was generally associated with a trend toward negative vorticity at the 850-hPa level.     

A mathematical modeling of sulphur dioxide pollution in Erzurum City

A non-linear simple air-quality model was developed by applying the continuity equation for the air control volume over Erzurum city center and tested using daily average values of SO2 and meteorological data obtained during the winter seasons in Erzurum, Turkey from 1994 to 1998. Model parameters are estimated by non-linear regression analysis. Agreement between model predictions and measured data was found very satisfactory with standard deviations less than 20 microg/m3.     

Operational ozone forecasts for the region of Copenhagen by the Danish Meteorological Institute

The Danish Meteorological Institute (DMI) has developed an operational forecasting system for ozone concentrations in the Atmospheric Boundary Layer; this system is called the Danish Atmospheric Chemistry FOrecasting System (DACFOS). At specific sites where real-time ozone concentration measurements are available, a statistical after-treatment of DACFOS’ results adjusts the next 48 h ozone forecasts. This post-processing of DACFOS’ forecasts is based on an adaptive linear regression model using an optimal state estimator algorithm. The regression analysis uses different linear combinations of meteorological parameters (such as temperature, wind speed, surface heat flux and atmospheric boundary layer height) supplied by the Numerical Weather Prediction model DMI-HIRLAM. Several regressions have been tested for six monitoring stations in Denmark and in England, and four of the linear combinations have been selected to be employed in an automatic forecasting system. A statistical study comparing observations and forecasts shows that this system yields higher correlation coefficients as well as smaller biases and RMSE values than DACFOS; the present post-processing thus improves DACFOS’ forecasts. This system has been operational since June 1998 at the DMI's monitoring station in the north of Copenhagen, for which a new ozone forecast is presented every 6 h on the DMI's internet public homepage.     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

Particulate and sulfur dioxide concentration measurements in Patras,Greece

The purpose of this study was to obtain a better assessment of the Patras, Greece, air quality, in terms of the primary pollutants total suspended particulates (TSPs) and sulfur dioxide (SO2), because limited and short-duration measurements have been conducted in the past. Installation and operation of a mobile air monitoring station at two different locations in the Patras downtown area and one location in the outskirts of the city was undertaken and covered the periods July 1, 1994-January 30, 1995; March 18-August 23, 1995; and April 19-July 27, 1996, respectively. For both pollutants measured at each location, the monthly average concentrations and typical weekly variation of daily averages, as well as the diurnal variations and frequency concentration distributions in each month of the monitoring periods, were calculated and are presented in bar diagrams. The annual and winter period medians and the annual 98th percentile were also calculated and are compared with the limit and guide values provided by the European Economic Community Council Directive 80/779/EEC. In addition, comparison of SO2 values is made with the limit values adopted by the more recent Directive 1999/30/EC. It was found that the TSP and SO2 levels at all locations were very low and were lower than the levels found in Thessaloniki and Athens, Greece. An attempt to explain what had been measured is also undertaken. The data presented are considered essential for future reference and comparison purposes.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), onemixed (alternating winds) and one onlyanticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), one mixed (alternating winds) and one only anticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

Climate simulations using the GCRC 2-D zonally averaged statistical dynamical climate model

The two-dimensional statistical dynamical climate model, recently developed at the Global Change Research Center (GCRC 2D climate model) is presented and discussed. The model solves the 2-D primitive equations in finite difference form (mass continuity, Newton's second law, and the first law of thermodynamics) for the prognostic variables zonal mean density, zonal mean zonal velocity, zonal mean meridional velocity, and zonal mean temperature on a grid that has 18 nodes in latitude and 9 vertical nodes (plus the surface). The equation of state, p = ρRT and an assumed hydrostatic atmosphere, δp = −ρgδz, are used to diagnostically calculate the zonal mean pressure and vertical velocity for each grid node, and the moisture balance equation is used to estimate the precipitation rate.

The performance of the model at simulating the two-dimensional temperature, zonal winds, and mass stream function is discussed here. The strengths and weaknesses of the model are highlighted and plans for future model experiments and improvements are given. The parameterization of the transient eddy fluxes of heat and momentum developed by Stone and Yao (1987 and 1990) are used with small modifications. These modifications are shown to improve the performance of the model at simulating the observed climate system as well as increase the model's computational stability.     

Urban atmospheric pollution: personal exposure versus fixed monitoring station measurements

We initiated the PETER (pedestrian environmental traffic pollutant exposure research) project to investigate pedestrians' exposure to traffic related atmospheric pollutants, based on data obtained with the collaboration of selected categories of pedestrian urban workers. We investigated relations between roadside personal exposure levels of volatile aromatic hydrocarbons (including benzene) and particulate matter <10 microm (PM10) among traffic police (n = 126) and parking wardens (n = 50) working in downtown Bologna, Italy. Data were collected from workshifts throughout four 1-week periods in different seasons of 2000-2001. For benzene and PM10, comparisons were made with measurements by fixed monitoring stations, and influence of localized traffic intensity and meteorological parameters was examined. Roadside personal exposure to benzene correlated more strongly with other volatile aromatic hydrocarbons (toluene, xylenes and ethylbenzene) than with PM10. Benzene and PM10 personal exposure levels were higher than fixed monitoring station values (both p<0.0001). At multivariate analysis, benzene and PM10 data from fixed monitoring stations both correlated with meteorological variables, and were also influenced by localized traffic intensity. Plausibly because of the downtown canyon-like streets, weather conditions (during a period of drought) only marginally affected benzene personal exposure, and moderately affected PM10 personal exposure. These findings reinforce the concept that urban atmospheric pollution data from fixed air monitoring stations cannot automatically be taken as indications of roadside exposures.     

Emissions into the Atmosphere Due to the Ceramic Salt Glazing Process

The techniques of Principal Component Analysis (PCA) and subsequent regression analysis were used in an attempt to describe local and upwind chemical and physical factors which affect the variability of SO₄ ^–2 concentrations observed in a rural area of the northeastern U.S. The data used in the analyses included upwind and local O₃ concentrations, temperature, relative humidity and other climatological information, SO₂, and meteorological information associated with backward trajectories. The investigation identified five principal components, three major (eigenvalues >1) and two minor (eigenvalues < one), which accounted for 52% (r = 0.72) of the variability in the SO₄ ^–2 regression model. These components can be described as representing local and upwind photochemistry, droplet growth, SO₂ emissions, and air mass characteristics. The study also indicated that in future studies it will be necessary to a priori select air pollution and meteorological variables for measurement to potentially increase the sensitivity of this type of receptor model.     

An assessment of spatial and temporal variation of sulfur dioxide levels over Istanbul, Turkey

Sulfur dioxide concentration levels are investigated in Istanbul to assess air pollution during the heating seasons in which the concentration of air pollutants reach high levels due to the consumption of low-quality fossil fuels. Results reveal that in the 1985-91 period there is an increasing trend in the concentrations of air pollutants. One reason for this increase is found to be the switching to use of low-quality fossil fuels instead of cleaner ones; the consumption ratio of coal/fuel-oil increased drastically in the 1980s from the ratio of 0.62 during 1980 to 3.09 by 1990. Linear regression analysis also indicated the similar variability of sulfur dioxide and particulate matter curves with a correlation coefficient R2=0.87. An optimum interpolation technique, kriging, is used to obtain the spatial distribution of sulfur dioxide over the area. Results indicated that the maximum concentration regions over the European side, exceeding 300 microg/m(3) monthly averages, are found to be the Fatih-Gaziosmanpa?a-Bayrampa?a, Beyo?lu-Si?li, and Emin?nü areas. On the Asian side, the G?ztepe-Kadik?y area received a major threat from sulfur dioxide pollution. Results also indicated that there was a considerable decrease in air pollution levels over Istanbul in the 1995-96 season compared with the previous two seasons. This can be explained by (1) the increase in ventilation, (2) switching to natural gas as a home and business heating fuel, and (3) treatment of coal before its entrance to the city. The variability in weather conditions is explained by the adoption of a ventilation index, which is the product of wind speed and inversion height.     

Synoptic conditions associated with high carbon monoxide episodes at a coastal station in Hong Kong

The effect of different synoptic environments and the associated meteorological conditions on the transport of CO to a coastal station located at the southeastern tip of Hong Kong are examined. Based on the 1994 data, we found that the appearance of a Siberia high pressure, the passage of a cold front, the passage of a trough, and the existence of a tropical cyclone to the east to southeast of Hong Kong frequently gave rise to continental outflow from a northeasterly to a northwesterly direction. This continental airstream, which is highly contaminated with anthropogenic air pollutants, raised the CO concentration at the station to a level significantly above the oceanic value (measured to be around 81 pbbv under persistent maritime flow conditions). We also identified 20 high CO episodes in which the CO concentration of at least two consecutive hourly means in a given month exceeded two standard deviations from the monthly mean. All these episodes were directly associated with one of the above four types of synoptic environments with the winds being moderate to light northwesterly to northeasterly.     

Long-term variation in surface ozone and its precursors in Athens,Greece

INTENTION, GOAL, SCOPE, BACKGROUND: Photochemical pollution is a very complex process involving meteorological, topographic, emission and chemical parameters. The most important chemical mechanisms involved in the atmospheric process have already been identified and studied. However, many unknown parameters still exist because of the large number of participating chemical reactions. OBJECTIVE: The present study investigates the processes involved in the photochemical pollution effect of an urban station located in the greater area of the Athens basin and gives a plausible explanation for the different seasonal ozone development between that station and another rural one. Furthermore, the distribution of the mean monthly surface ozone observed at the urban station during 1987-2001 is examined in order to create a relevant forecasting tool. METHODS: Averaged hourly data of O3 and NOx observations monitored at the above mentioned stations, during 1987-2001, have been used in order to derive the daytime (7:00-15:00) values. Trajectories calculated by using a 2D-trajectory code and meteorological data, during the period 1988-1996, have also been used. RESULTS AND DISCUSSION: At the urban station, the percentage negative trend of NO and NOx data in winter and summer is higher than that in spring and autumn, while the percentage ozone trend is maximum in the summer. On the contrary, the negative surface ozone trend at the rural station exhibits a minimum in summer and a maximum in autumn and winter. The mean seasonal wind-rose for the selected months shows that the northward wind flow dominates during June, the month of the lowest negative ozone trend in the rural station. Finally, the development of the forecasting tool shows that the mean monthly surface ozone data during the period (1987-2001) demonstrates a semi-log distribution. CONCLUSIONS: Air transport effect on the air pollution of the rural station (not blocked by mountains) is deduced as a possible reason for the different seasonal ozone development observed between the rural and the urban station. Finally, the discrepancies between the theoretical probabilities deduced by the model and the empirical ones appear to be very small, and the corresponding correlation coefficient is 0.99. RECOMMENDATION AND OUTLOOK: However, to interpret the aforementioned statistical results about the negative trends in ozone and its precursors, additional parameters can be taken into account. Changes in NOx concentrations, for instance, can result not only from changes in emissions or meteorological conditions. There might also be a contribution through changes in the atmospheric composition. A study of the contribution of changes in atmospheric composition to trends of observed NOx concentrations requires that a series of steps be taken (removal of meteorological influence in the time series, calculation of trends in OH concentrations, etc.).     

Relation between forest vegetation, atmospheric deposition and site conditions at regional and European scales

Several monitoring programs have been set up to assess effects of atmospheric deposition on forest ecosystems. The aim of the present study was to evaluate effects on the understorey vegetation, based on the first round of a regional (the Netherlands) and a European forest monitoring program. A multivariate statistical analysis showed surprisingly similar results for both data sets; the vegetation appeared to be largely determined by the ‘traditional’ factors soil, climate, and tree species, but there was a small but statistically significant effect of atmospheric deposition. The effects of deposition include a slight shift towards nitrophytic species at high N deposition in the European network, and towards acidophytic species at high S-deposition in the Dutch network. The relatively small effect of atmospheric deposition is understandable in view of the very large natural variation in environmental conditions. Time series of both vegetation and environment are needed to assess deposition effects in detail.     

Multivariate space analysis of the major precipitation ions over Europe, 1986-1997

The annual average concentrations (1986-1997) of the major ions SO4(2-), NO3-, Cl-, NH4+, Na+, Mg2+, Ca2+, and K+ in precipitation are analyzed for selected EMEP stations. The objective is to determine the ion patterns or typologies in precipitation by principal component analysis (PCA) combined with a cluster analysis. SO4(2-) and NO3- ions are predominant in central and eastern Europe. This area corresponds to high emissions of SO2 and NO2. Sea spray ions are predominant in coastal sites. The soil components show an important contribution in southern Europe, possibly due to the soil dust transported from northern Africa.