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Chemical characterisation of PM episodes in NE Spain
Chemosphere 62 (2006) 947–956 www.elsevier.com/locate/chemosphere
Chemical characterisation of PM episodes in NE Spain M. Viana *, X. Querol, A. Alastuey Institute of Earth Sciences ‘‘Jaume Almera’’, C/Lluis Sole´ i Sabarı´s s/n, 08028 Barcelona, Spain Received 13 January 2005; received in revised form 17 May 2005; accepted 30 May 2005 Available online 3 August 2005
Abstract The chemical composition of ambient particulate matter (PM) varies widely as a function of its main emission sources and of the chemical reactions which take place in the atmosphere. The aim of this study is to obtain the chemical profile of PM10 and PM2.5 during peak PM episodes, thus identifying the main emission sources and/or atmospheric processes which originate the PM episodes. To this end, cluster analysis was applied to a set of PM10 and PM2.5 data collected throughout 2001 in two urban and industrialised areas in NE Spain. As a result of this analysis, five clusters were identified for each site, and the interpretation of their chemical profiles lead to the identification of five types of peak PM episodes for each site: industrial, traffic and regional re-circulation episodes at both sites, plus crustal episodes in Barcelona, and peak traffic and industrial episodes (T + I) in Tarragona. Traffic episodes are characterised by daily means of 23 and 10 lg/m3 of OM + EC in Barcelona and Tarragona in PM10. Levels of secondary inorganic aerosols reach average daily means of 19 and 11 lg/m3 in Barcelona and Tarragona in PM10 during industrial episodes. High levels of sulphate (>5 lg/m3) and ozone (up to 77 lg/m3 daily mean) are good tracers of regional re-circulation episodes. During crustal episodes daily means of crustal elements reach up to 34 lg/m3 in Barcelona. Special attention has been drawn to the composition of the mineral matter during the different PM episodes. 2005 Published by Elsevier Ltd. Keywords: Cluster analysis; Source contribution; Chemical profile; Sahara dust; Mineral matter
1. Introduction Particulate matter (PM) is a complex mixture of substances suspended in the atmosphere in solid or liquid state with different properties (e.g. size distribution or chemical composition amongst others) and origins (anthropogenic and natural). Owing to this mixture of substances the chemical composition of PM may vary widely as a function of its major emission sources and the subsequent chemical reactions which take place in the atmosphere.
*
Corresponding author. Fax: +34 934110012. E-mail address: [email protected] (M. Viana).
0045-6535/$ - see front matter 2005 Published by Elsevier Ltd. doi:10.1016/j.chemosphere.2005.05.048
The study of this atmospheric pollutant has increased in the past years due to the understanding of its adverse effects on health (Dockery and Pope, 1996; Ku¨nzli et al., 2000; WHO, 2003) and the consequent implementation in the year 2001 of the European directive 1999/30/ EU, which establishes annual and daily limit values for PM10 (the PM mass which passes through a size selective impactor inlet with a 50% efficiency cut-off at 10 lm aerodynamic diameter). The chemical mass balance is the most commonly used method for assessing particulate matter source contributions (Wilson et al., 2002), and statistical methods such as factor analysis and multi-linear regression (Thurston and Spengler, 1985) have also produced interesting results regarding source identification. The results
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obtained from the use of these techniques are usually expressed as the contributions (in % and/or lg/m3) of the sources to the PM mass. However, the main objective of the present study is not to identify the contributions of the sources but to obtain the chemical profile of PM during peak concentration episodes in the North-Eastern Iberian Peninsula, and thus a different approach has been chosen: the use of cluster analysis. Statistical clustering of the PM samples classifies the samples in a straightforward manner according to their chemical profiles, and yields a number of clusters characterised by their specific chemical composition (Pen˜a and Rivera, 1992). The resulting compositional profile is then a reflection of the major emission source and/or the atmospheric process involved in the production of the peak PM episodes.
2. Methodology Two urban monitoring sites were selected in Barcelona and Tarragona, on the North-Eastern coast of Spain (Fig. 1). The Barcelona site is located in a park, under the influence of dense road traffic (Meridiana Avenue, located 150 m to the North of the station) and a large industrial area including two fuel-oil power plants. The Tarragona site is an urban background site located on the rooftop of a seven-storey building, under the influence of PM emissions from road
traffic and a highly industrialised area (oil chemistry and transformation, fuel-oil power plant, chemical industries). The sampling of PM10 and PM2.5 was carried out from 09/01/2001 to 27/12/2001 by means of the EN1234-1 reference high volume method for PM10 (Andersen, 68 m3/h) and high volume (30 m3/h) MCV samplers for PM2.5. It is important to consider that this sampling technique may be subject to the loss of a certain fraction of carbonaceous species and NO 3 by volatilisation (Turpin et al., 2000; Eatough et al., 2003). Three PM10 and two PM2.5 samples were collected per week, and 2 PM10 and 1 PM2.5 samples per week were selected for chemical analysis. The methodology (Querol et al., 2001) is based on the acid digestion of 1/2 of the filter for the determination of major and trace elements by ICP-AES and ICP-MS, water leaching of 1/4 of the filter to determine soluble ion concentrations ðSO2 4 , NO3 , þ NH4 , Cl ) by ion chromatography and FIA colorimetry, and elemental analysis of total C in the remaining 1/4 of the filter. The results from these chemical analyses were then grouped into four main components: crustal ðCO2 3 , SiO2, Al2O3, Ca, K, Mg, Fe, P2O5), OM + EC (organic matter + elemental carbon), SIA (secondary þ inorganic aerosols, nonmarine SO2 4 , NO3 , NH4 Þ and 2 marine (Na, Cl , marine SO4 ). A variable percentage of undetermined mass was observed. Relative analytical errors were between 3% and 10% for the elements studied.
Fig. 1. Study area and location of monitoring sites Barcelona and Tarragona.
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Cluster analysis was applied to the PM10 samples by means of the software package STATISTICA 4.2. The algorithm selected was K-means clustering by single linkage, taking Euclidean distances as the distance measure. The total number of samples was 88 for each site, although the final clustering was reduced to 85 cases for Barcelona and 81 for Tarragona as any cases with missing variables were excluded from the analysis. The same analysis was then applied to the PM2.5 samples, but owing to the lower number of samples available (44 and 43 samples respectively) the results were not concluding.
3. Chemical profiles of PM episodes The cluster analysis performed on the chemical dataset produced five independent clusters of samples for each site (Tables 1 and 2). Main tracer species were identified in the resulting chemical composition of each cluster, and these tracers were compared to those presented in available source contribution literature (Pacyna, 1986; Chueinta et al., 2000; Kim and Henry, 2000; Querol et al., 2001; Rodrı´guez et al., 2002; Sternbeck et al., 2002; Pakkanen et al., 2003; Adachi and Tainosho, 2004; Rodrı´guez et al., 2004). As a result, the clusters obtained for Barcelona were identified as industrial, traffic, regional, crustal and undetermined (Table 1), whereas those obtained for Tarragona were identified as industrial, traffic, traffic and industrial peak episodes (T + I), regional and undetermined (Table 2). The tracer species which helped interpret the origin of each of the clusters are discussed in detail below. The undetermined cluster represents samples in which the PM mass results from a mixture of sources. Traffic and industrial episodes are considered to have a local origin, as they result from the impact of local emissions on PM levels under low dispersive atmospheric scenarios. The T + I cluster in Tarragona was identified as peak industrial and/or traffic episodes. The regional clusters refer to regional re-circulation episodes as defined by Milla´n et al. (1997), which are originated by the re-circulation and ageing of air masses during the summer months due to specific orographic and meteorological conditions in the Western Mediterranean basin. Finally, in the case of Barcelona a cluster defined as crustal was identified, whereas it was not identified in the Tarragona analysis. In Barcelona this cluster represents the contribution of mineral matter from a number of anthropogenic sources such as construction and demolition dust and re-suspension from the park in which the station is located. It sporadically includes dust transported during African dust outbreaks, although these cases only represent a minor percentage during the sampling period (3 days out of 10 in the cluster). The fact that this cluster is not present in Tarragona
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may be due to the location of the site at a considerable height (seven-storey building), which limits the influence of mineral dust sources such as road dust re-suspension. The local influence of the park is also absent in Tarragona. African dust contributions are not identified as an isolated cluster in Tarragona as the percentage of the variability of the dataset represented by these samples was too low for them to be isolated as one independent cluster by the statistical analysis (considering that the analysis identifies no other direct crustal sources). The average chemical composition of PM10 and PM2.5 for each cluster is summarised in Tables 1 and 2. It is important to note that the cluster identified as traffic in Barcelona in PM2.5 includes only one sample, and thus the results may not be fully representative. Out of the 88 PM10 samples and the 44 and 43 PM2.5 samples available for Barcelona and Tarragona respectively, 85 and 81 PM10 and 43 and 36 PM2.5 samples were considered for the cluster analysis. Industrial episodes: the number of cases in this cluster is similar in Barcelona (n = 15, 18% of the PM10 cases) and Tarragona (n = 20, 25%). The mean daily PM10 levels obtained during these episodes are 57.5 lg/m3 in Barcelona (9.9 lg/m3 standard deviation, s.d.) and 37.1 lg/m3 in Tarragona (9.6 lg/m3 s.d.), and they were mainly registered between April and May and in September, showing no specific seasonal trend. The main tracers of the industrial origin of these episodes are the secondary inorganic aerosols (SIA, Querol et al., 2001; Rodrı´guez et al., 2004), which present average values of 18.6 lg/m3 in Barcelona (6.5 lg/m3 s.d.) and 10.9 lg/m3 in Tarragona (5.4 lg/m3 s.d.). Due to the influence of traffic at both sites, the levels of the OM + EC and crustal fractions are also relatively high (13.7 lg/m3 and 17.0 lg/m3 in Barcelona, and 7.9 lg/m3 and 10.6 lg/m3 in Tarragona for OM + EC and the crustal fraction, respectively). The composition of the SIA fraction has also been analysed, with the result that in Tarragona 55% of the total SIA mass is constituted by nonmarine sulphate (6.0 lg/m3) and 31% by nitrate (3.4 lg/m3), whereas in Barcelona both species represent a similar fraction (39% nitrate, 7.2 lg/m3, and 40% sulphate, 7.4 lg/m3). The prevalence of sulphate over nitrate in Tarragona during industrial episodes responds to the higher relative weight of industrial emissions with respect to traffic emissions at this site, while in Barcelona the traffic and industrial influences seem to have a similar relative weight. Due to the fact that industrial emissions in the study areas generally do not affect the mineral load, the composition of this fraction is very similar to the annual average (Al2O3/Ca = 0.92 vs 0.91 annual mean in Barcelona, and 0.45 vs 0.43 in Tarragona). With respect to the trace elements, these episodes are characterised in Barcelona and Tarragona by high levels
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Table 1 Average chemical composition of PM10 and PM2.5 at a traffic site with industrial influence in Barcelona, as a function of the 5 PM episodes identified: industrial, traffic, regional re-circulation, crustal and mixed sources Industrial PM10 n = 15 (18%)
Traffic PM10 n=8 (9%)
Regional PM10 n = 26 (31%)
Crustal PM10 n = 10 (12%)
Mixed PM10 n = 26 (31%)
Industrial PM2.5 n=9 (21%)
Traffic PM2.5 n=1 (2%)
Regional PM2.5 n = 12 (28%)
Crustal PM2.5 n=8 (19%)
Mixed PM2.5 n = 13 (30%)
lg/m3 T SO2 NO NO2 O3 PM OM + EC CO2 3 SiO2 Al2O3 Ca K Na Mg Fe nmSO2 4 mSO2 4 NO 3 Cl NHþ 4
19 5 31 45 21 57.5 13.7 4.2 6.3 2.1 2.3 0.5 0.9 0.3 1.2 7.4 0.2 7.2 0.6 3.9
14 7 87 54 8 66.3 22.7 5.4 5.2 1.7 3.0 0.6 0.8 0.3 1.6 5.5 0.2 5.7 1.3 2.0
25 5 8 25 44 36.1 6.6 3.0 4.3 1.4 1.4 0.4 1.6 0.3 0.7 5.3 0.4 2.5 1.1 1.5
19 7 20 35 29 64.7 10.5 6.7 15.0 5.0 3.3 1.0 1.5 0.7 2.2 3.8 0.4 3.4 1.4 1.8
16 5 24 37 21 36.1 10.8 3.2 3.2 1.1 1.7 0.4 0.8 0.2 0.8 3.3 0.2 2.7 1.0 1.4
20 4 35 46 23 36.9 15.1 1.0 1.1 0.4 0.4 0.2 0.1 0.2 0.3 6.3 <0.1 5.2 0.3 3.7
13 5 89 45 6 48.0 26.2 0.4 0.4 0.1 0.2 0.3 0.2 <0.1 0.3 6.3 <0.1 6.4 0.9 4.1
24 4 7 21 46 18.8 7.5 0.7 0.8 0.3 0.3 0.1 0.3 0.1 0.2 3.9 0.1 0.5 0.3 1.4
16 4 21 34 19 38.1 14.1 2.0 4.1 1.4 0.9 0.4 0.3 0.2 0.5 4.0 0.1 3.1 0.4 2.0
15 2 32 39 16.4 24.7 13.6 0.7 1.0 0.3 0.4 0.2 0.2 0.1 0.2 3.4 0.1 2.0 0.5 1.7
%acc. Undet. Crustal Marine SIA OM + EC
89.7 6.0 17.0 1.8 18.6 13.7
86.4 9.1 18.0 2.4 13.3 22.7
86.5 5.1 11.6 3.2 9.3 6.6
89.3 7.3 34.0 3.3 8.9 10.5
87.6 4.9 10.7 2.0 7.4 10.8
93.0 3.0 3.6 0.5 15.2 15.1
95.8 2.0 1.9 1.0 16.8 26.2
88.0 3.8 2.4 0.7 5.8 7.5
90.6 5.5 9.6 0.7 9.2 14.1
101.6 1.2 3.0 0.7 7.1 13.6
83 25 12 0.5 13 67 122 2 1.9 7 0.8 6 12 50 95
92 24 13 0.5 11 87 180 1.9 2 8 1.5 7 21 74 107
51 11 6 0.3 5 34 60 1.0 1.3 5 0.5 4 6 25 29
229 16 9 0.7 7 42 104 2 5 11 0.5 3 10 57 69
64 11 7 0.3 6 45 96 1.2 1.3 5 0.7 4 8 38 46
18 19 4 0.3 9 36 61 1.9 0.6 1.5 0.9 6 4 6 60
7 13 1.9 0.1 6 48 67 1.1 0.5 1.0 1.2 8 8 8 54
15 5 2 0.3 3 26 42 0.7 0.5 1.2 0.3 2 3 4 20
69 9 3 0.2 4 24 61 0.9 1.4 3 0.5 4 4 11 49
19 7 3 0.3 4 37 55 0.8 0.5 2 0.7 4 4 14 42
ng/m3 Ti V Cr Co Ni Cu Zn As Rb Sr Cd Sn Sb Ba Pb
2 n: Number of samples; OM + EC: organic matter + elemental carbon; nmSO2 4 : nonmarine sulphate; mSO4 : marine sulphate; %acc.: PM mass recovery through analysis; undet.: undetermined; crustal: CO2 , SiO , Al O , Ca, K, Mg, Fe, P O ; SIA: secondary inorganic 2 2 3 2 5 3 2 þ aerosols (nmSO2 4 , NO3 , NH4 ); marine: Na, Cl , mSO4 ; T: temperature (C).
of Ni (13 ng/m3 and 6 ng/m3), V (25 ng/m3 and 10 ng/m3) and Cr (12 ng/m3 and 4 ng/m3). These tracers typically reflect the presence of fuel-oil power plant
and/or petroleum refinery emissions (Pacyna, 1986). Both PM sources are found in the study areas (one power plant and a refinery in Tarragona, two power
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Table 2 Average chemical composition of PM10 and PM2.5 at an urban background site with industrial influence in Tarragona, as a function of the 5 PM episodes identified: industrial, traffic, T + I (traffic + industrial peak episodes), regional re-circulation and mixed sources Industrial PM10 n = 20 (25%)
Traffic PM10 n = 20 (25%)
T+I PM10 n=8 (10%)
Regional PM10 n = 16 (20%)
Mixed PM10 n = 17 (21%)
Industrial PM2.5 n=8 (22%)
Traffic PM2.5 n=6 (17%)
T+I PM2.5 n=6 (17%)
Regional PM2.5 n=6 (17%)
Mixed PM2.5 n = 10 (28%)
lg/m3 T SO2 NO NO2 O3 PM OM + EC CO2 3 SiO2 Al2O3 Ca K Na Mg Fe nmSO2 4 mSO2 4 NO 3 Cl NHþ 4
23 4 33 38 55 37.1 7.9 3.9 2.7 0.9 2.0 0.3 1.3 0.3 0.4 6.0 0.3 3.4 0.8 1.5
15 4 63 42 28 42.6 10.4 3.0 2.2 0.8 1.7 0.4 0.9 0.3 0.4 4.7 0.2 6.0 0.8 2.2
18 8 136 49 19 47.1 14.2 4.6 3.3 1.2 2.8 0.4 0.9 0.4 0.6 4.3 0.2 4.9 0.6 1.2
26 3 11 31 77 31.1 6.4 2.5 1.5 0.5 1.2 0.2 1.5 0.3 0.3 5.7 0.4 2.3 0.9 1.3
18 2 16 27 49 29.5 6.6 2.9 1.9 0.7 1.8 0.3 1.3 0.3 0.3 3.3 0.3 2.2 1.2 0.9
18 4 36 44 52 27.3 8.1 0.9 0.8 0.3 0.4 0.2 0.6 0.1 0.1 6.3 0.1 1.7 0.2 2.5
17 4 67 40 26 26.9 8.3 0.5 0.2 0.1 0.3 0.2 0.3 0.1 0.1 3.4 0.1 3.8 0.3 1.6
17 7 131 47 18 24.5 11.3 0.6 0.2 0.1 0.4 0.2 0.3 0.1 0.1 3.1 0.1 3.2 0.3 1.6
18 1.9 11 24 75 19.6 5.2 0.5 0.5 0.2 0.2 0.1 0.3 0.1 0.1 4.9 0.1 0.5 0.1 1.9
16 1.8 16 27 48 16.2 6.0 0.4 0.3 0.1 0.2 0.1 0.2 <0.1 0.1 2.8 0.1 1.1 0.1 1.4
%acc. Undet. Crustal Marine SIA OM + EC
86.1 5.8 10.6 2.4 10.9 7.9
79.7 8.6 8.7 1.9 12.9 10.4
85.0 7.2 13.4 1.8 10.4 14.2
80.7 5.9 6.5 2.8 9.4 6.4
81.5 5.9 8.2 2.7 6.3 6.6
82.4 5.5 2.9 0.9 10.5 8.1
74.9 7.5 1.5 0.7 8.8 8.3
91.5 3.6 1.7 0.7 7.9 11.3
80.4 6.2 1.7 0.5 7.3 5.2
89.7 5.8 1.3 0.4 5.2 6.0
ng/m3 Ti V Cr Co Ni Cu Zn As Rb Sr Cd Sn Sb Ba Pb
22 10 4 0.2 6 25 31 0.7 0.9 6 0.3 1.7 4 13 19
23 8 2 0.2 4 34 44 1.0 0.9 4 0.4 2 5 12 36
35 12 3 0.3 6 44 50 1.1 1.3 6 0.3 2 7 17 40
16 6 1.9 0.2 3 22 24 0.4 0.6 4 0.1 2 2 9 13
22 4 1.8 0.1 2 23 22 0.5 0.7 5 0.2 1.2 3 10 17
8 9 4 0.1 5 40 19 0.4 0.6 2 0.2 1.3 1.7 3 15
4 6 1.9 0.1 3 40 24 0.6 0.4 1.0 0.4 1.5 1.8 4 26
6 6 3 0.1 5 39 30 0.7 0.4 0.9 0.4 0.9 5 4 23
6 4 2 0.1 3 22 14 0.2 0.2 1.0 0.2 0.7 0.9 2 10
5 3 0.8 0.1 1.7 18 12 0.3 0.2 0.6 0.1 0.4 4 3 12
2 n: Number of samples; OM + EC: organic matter + elemental carbon; nmSO2 4 : nonmarine sulphate; mSO4 : marine sulphate; % acc.: PM mass recovery through analysis; undet.: undetermined; crustal: CO2 , SiO , Al O , Ca, K, Mg, Fe, P O 2 2 3 2 5; SIA: secondary inorganic 3 2 þ aerosols (nmSO2 4 , NO3 , NH4 ); marine: Na, Cl , mSO4 ; T: temperature (C).
plants in Barcelona). The levels of gaseous pollutants do not show marked increases during these episodes. Traffic episodes: the number of cases in this cluster is higher in Tarragona (n = 20, 25% of the cases) than in
Barcelona (n = 8, 9%), despite the marked traffic influence at the latter site. The fact that the Tarragona traffic cluster is more populated than in Barcelona does not indicate that the number of traffic episodes is higher in
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Tarragona, but that the traffic contributions are not as clearly differentiated in Barcelona. The higher degree of mixture between emissions from different sources in Barcelona is probably related to the location of the main industrial and traffic sources in the same direction (NNE, Beso`s river valley and Meridiana Ave.) with respect to the monitoring site. The PM10 levels registered reach high levels at both sites (the highest for all clusters in Barcelona, 66.3 lgPM10/m3, 7.0 lg/m3 s.d. and 42.6 lgPM10/m3, 11.0 lg/m3 s.d. in Tarragona). These episodes are mainly registered from October to March, coinciding with lower atmospheric dispersive conditions. The chemical composition of PM during these episodes in Barcelona is mainly determined by OM + EC (22.7 lg/m3, 4.6 lg/m3 s.d.) as a result of the road traffic exhaust emissions, followed by the mineral fraction (18.0 lg/m3, 4.6 lg/m3 s.d.) originated from road dust erosion and re-suspension (Kim and Henry, 2000; Querol et al., 2001). Note that the mean OM + EC levels during traffic episodes double the annual average obtained in Barcelona (11 lg/m3). In Tarragona the strong influence of the industrial emissions generates high SIA background levels during all episodes. Thus, during traffic episodes the highest OM + EC levels are registered (10.4 lg/m3, except for peak T + I episodes) and in parallel high SIA levels are registered (12.9 lg/m3, 6.9 lg/m3 s.d.). During traffic episodes the nitrate fraction prevails over sulphate in Tarragona (47% nitrate, 36% sulphate) whereas in Barcelona the ratios are once again balanced (43% nitrate, 42% sulphate). The composition of the mineral road dust re-suspended by traffic is in both cases dominated by Ca (3.0 lg/m3 in Barcelona, 1.7 lg/m3 in Tarragona) with respect to Al2O3 (1.7 lg/m3 in Barcelona, 0.8 lg/m3 in Tarragona), indicating that construction work dust is a significant contributor to mineral dust deposited on roads at urban sites. The Ti/Fe ratio may constitute a good tracer of road dust re-suspension as the results obtained for Barcelona (Ti/Fe = 59) and Tarragona (Ti/Fe = 53) are significantly different to that obtained in Barcelona for the crustal cluster (Ti/Fe = 106). The emissions from road traffic are typically characterised by high levels of Ba, Sb, Cd, Pb, Zn and Cu (Sternbeck et al., 2002; Pakkanen et al., 2003; Adachi and Tainosho, 2004). These results are confirmed during traffic episodes in Barcelona, where the average concentrations of these trace elements reach levels of Cu (87 ng/ m3), Zn (180 ng/m3), Cd (1.5 ng/m3), Sb (21 ng/m3), Ba (74 ng/m3) and Pb (107 ng/m3) which are maximal when compared to the other clusters. In the case of Tarragona the most outstanding elements are Cu (34 ng/m3), Zn (43 ng/m3), Sb (5 ng/m3) and Pb (36 ng/m3), although it must be noted that the traffic cluster in Tarragona does not include the peak traffic episodes, included in the T + I cluster. Finally, traffic episodes are also characterised by the highest levels of gaseous compounds such as NO
(87 lg/m3, 63 lg/m3 in Barcelona and Tarragona) and NO2 (54 lg/m3, 42 lg/m3 in Barcelona and Tarragona). Consequently, O3 levels are relatively low (8 lg/m3 and 28 lg/m3, respectively). Traffic + Industrial peak episodes (T + I): this cluster was only identified in the Tarragona analysis, and includes 8 PM10 samples (10% of the PM10 cases). The meteorological analysis of these days showed that the synoptic scale scenario was dominated by high pressure systems, mainly in winter, which favoured the stagnation of the air masses and the increase of pollutants emitted by local sources. The mean chemical composition of these local anthropogenic pollution episodes is dominated by OM+EC (14.2 lg/m3, 3.0 lg/m3 s.d.) and crustal components (13.4 lg/m3, 6.6 lg/m3 s.d.) as a result of the traffic influence, but also by SIA (10.4 lg/m3, 5.5 lg/m3 s.d.) originating from the industrial emissions. As a result of the source mixture present in this cluster, the chemical composition is characterised by high levels of elements such as V (12 ng/m3) and Ni (6 ng/m3), tracers of oil combustion emissions, but also by Cu (44 ng/m3), Ba (17 ng/m3) or Sb (7 ng/m3), tracers of road traffic emissions. Furthermore, levels of mineral trace elements such as Ti (35 ng/m3) or Sr (6 ng/m3) are also found in relatively high concentrations during these episodes. Regarding gaseous compounds, these episodes present the highest mean concentrations of SO2 (8 lg/m3), NO (136 lg/m3) and NO2 (49 lg/m3) and the lowest of O3 (19 lg/m3) in Tarragona. Crustal episodes: crustal episodes (n = 10, 12% of the PM10 cases) were only detected in Barcelona, and they include a number of anthropogenic sources such as construction and demolition dust and re-suspension from the park in which the station is located, and sporadically mineral dust transported during African dust outbreaks (3 out of 10 cases in the cluster). In Tarragona the station is located at a higher altitude than the Barcelona site, and this may account for a reduced influence of anthropogenic re-suspended dust. These episodes were detected in Barcelona in February–April, October and November, showing no seasonal trend. Average PM10 levels obtained in Barcelona are the second highest after the traffic episodes (64.7 lg/m3). As expected, the chemical composition is dominated by the levels of crustal components (34.0 lg/m3, 10.4 lg/m3 s.d., Chueinta et al., 2000; Kim and Henry, 2000; Querol et al., 2001), but it is important to note that in this fraction the levels of Al2O3 are predominant (5.0 lg/m3) with respect to Ca (3.3 lg/m3). This composition contrasts with that obtained during traffic episodes in which Ca prevailed both in Barcelona and Tarragona. Apart from the higher Al2O3/Ca ratio (1.5) during crustal episodes with respect to traffic episodes (Al2O3/Ca = 0.6 in Barcelona, 0.4 in Tarragona), the Al2O3 levels are also higher in this cluster (5.0 lg/m3 vs 1.7 lg/m3 during traffic episodes in Barcelona), evidencing the influence of
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clay minerals from African dust. This influence may also be observed regarding trace elements such as Ti (229 ng/m3) Rb (5 ng/m3) or Sr (11 ng/m3), which present maximal concentrations during crustal episodes. Regional re-circulation episodes: the mean daily PM10 levels obtained during regional re-circulation episodes at both study sites are lower than under crustal, traffic or industrial episodes. On average, PM10 levels reach 36.1 lg/m3 in Barcelona (n = 26, 31%) and 31.1 lg/m3 in Tarragona (n = 16, 20%). The main PM10 constituents during these days are SIA and crustal components in Barcelona (9.3 lg/m3, 4.0 lg/m3 s.d. and 11.6 lg/m3, 3.0 lg/m3 s.d.) and Tarragona (9.3 lg/m3, 5.1 s.d. and 6.5 lg/m3, 2.4 s.d.). As defined by Milla´n et al. (1997) regional re-circulation episodes are characterised by the ageing of air masses and they mainly occur during the spring and summer months, and it is a process which favours the formation of secondary aerosols (Rodrı´guez et al., 2002). Thus, owing to the high atmospheric stability of ammonium sulphate with respect to ammonium nitrate in warm periods, 57–61% of the SIA mass in PM10 is comprised of sulphate in Barcelona and Tarragona (mean levels of 5.3 lg/m3 and 5.7 lg/m3), and only 25–27% by nitrate (2.4–2.5 lg/m3). Furthermore, the summer convective circulations increase the re-suspension of soil particles and thus result in an increase of the crustal load in PM10 (mainly made up of Ca compounds, especially in Tarragona). The composition of PM10 during these episodes is not significantly characterised by the levels of any of the trace elements analysed, which are usually found in lower concentrations than under the other clusters identified. Conversely, gaseous pollutants are very good tracers of this type of episode as O3 levels reach the highest values (77 lg/m3 in Tarragona and 44 lg/m3 in Barcelona) and NO the lowest (11 lg/m3 and 8 lg/m3, respectively). Owing to the fact that these episodes mainly occur in summer (>80% in this study), temperature may constitute another good indicator of the occurrence of regional re-circulation episodes (highest mean levels of 25 C and 26 C registered in Barcelona and Tarragona for this type of episode, respectively). Undetermined (mixed) episodes: these clusters group the samples in which a mixture of sources was identified, and thus do not present a specific chemical profile or gaseous tracers. They consist of 26 cases (31%) in Barcelona and 17 (21%) in Tarragona for PM10, and are detected throughout the year. The cluster analysis was also applied to PM2.5, but the results were not representative due to the low number of cases available for each site (36 in Tarragona, 43 in Barcelona). However, in order to characterise the chemical composition of the finer grain size fraction the clustering obtained for PM10 was applied to the PM2.5 samples. For this approach it was assumed that the same sources which dominate in PM10 have a signif-
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icant influence on the finer fractions. This assumption may only be considered valid if all the sources identified in this study (industry, traffic, regional re-circulation, crustal material) have an impact on the levels of both PM10 and PM2.5, even though this impact may be clearly distinct for each fraction. The results here presented for PM2.5 (extrapolated from PM10) should thus not be considered as fully conclusive. This approach for PM2.5 has implications mainly for the days in which coarser sized emission sources dominate in PM10 (e.g., crustal material). Taking into account that the impact of this source is lower in PM2.5 than in PM10 (although not negligible), the resulting PM2.5 chemical profile would overestimate the contribution of the finer grain size sources, as their relative weight would be higher than that of the coarser grain size sources. A minimum number of 80–100 cases would be necessary for the optimal differentiation of independent clusters. PM2.5 levels under traffic episodes reach mean daily values of 48.0 lg/m3 in Barcelona (n = 1, 2%) and 27.0 lg/m3 in Tarragona (n = 6, 17%). Owing to the fine grain size distribution of OM + EC, it is this component that predominates in the composition of this PM fraction (26.2 lg/m3 in Barcelona, 8.3 lg/m3 in Tarragona). The relative weight of the mineral fraction decreases significantly in PM2.5 (20–27% in PM10 to 4–6% in PM2.5 at both sites). In absolute values the levels are very similar in Barcelona (1.9 lg/m3) and Tarragona (1.5 lg/m3), although higher levels were expected in Barcelona as the PM2.5 crustal fraction is significantly influenced by road traffic (Querol et al., 2004). This might be due to the fact that there is only one PM2.5 sample available in Barcelona. Levels of PM2.5 are maximal during industrial episodes in Tarragona (27.3 lgPM2.5/m3, n = 8, 22%) and high in Barcelona (36.9 lgPM2.5/m3, n = 9, 21%). The major contributor to the PM2.5 mass are the SIA, with 15.2 lg/m3 in Barcelona and 10.5 lg/m3 in Tarragona. The OM + EC contribution is also significant (15.1 lg/m3 in Barcelona and 8.1 lg/m3 in Tarragona). During regional re-circulation episodes PM2.5 levels reach 18.8 lg/m3 in Barcelona (n = 12, 28%) and 19.6 lg/m3 in Tarragona (n = 6, 17%), and the main components are OM + EC and SIA (7.5 lg/m3 and 5.8 lg/m3 respectively in Barcelona and 5.2 lg/m3 and 7.3 lg/m3 in Tarragona). The prevalence of sulphate with respect to nitrate and ammonia observed in PM10 is even more evident in PM2.5, as 67–68% of the SIA mass is made up of nonmarine sulphate (3.9 lg/m3 and 4.9 lg/m3 in Barcelona and Tarragona) whereas nitrate constitutes only 7–9% (0.5 lg/m3 at both sites). The composition of the crustal load is determined by Ca in Tarragona (Al2O3/Ca = 0.7) owing to the geology of the area, whereas in Barcelona the ratio is higher (Al2O3/Ca = 1.1). These results were also observed for PM10.
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Fig. 2. Chemical composition of PM10 and PM2.5 in Barcelona and Tarragona as a function of the different PM episodes identified.
Finally, the mean daily PM2.5 values registered during crustal episodes reach 38.1 lg/m3 in Barcelona (n = 8, 19%), with a mineral load of 9.6 lg/m3. This result is significantly high, as it represents 35% of the PM2.5 mass. The influence of clay minerals is still evident in the PM2.5 fraction, as the Al components prevail over Ca (Al2O3/Ca = 1.4). Accordingly to the results described above, Fig. 2 summarises the mean chemical composition of PM10 and PM2.5 during the different PM episodes identified in Barcelona and Tarragona. The figure shows how the percentages of OM + EC and SIA increase in PM2.5 with respect to PM10 at both sites, whereas the mineral and the marine fractions decrease significantly due to their coarser grain size distributions.
4. Composition of the crustal load The chemical composition of the crustal load may vary as a function of the different PM episodes. These variations are presented in Table 3, expressed as the relative weight of Al2O3, Ca, Fe and K with P respect to the sum of these elements and compounds [ (Al2O3, Ca, Fe, K)]. This group of elements has been selected because they are major components of the mineral fraction and their concentrations were determined by chemical analyses (direct measurements).
The largest variations are observed at the Barcelona site. For this station, Ca is the dominant element in PM10 and PM2.5 during industrial and traffic episodes (37% and 44% for PM10 and 29% and 24% for PM2.5, respectively), mainly due to the re-suspension of road dust by traffic. Road dust may contain high levels of Ca originated from construction works in the city area and/or from road pavement and paint (Adachi and Tainosho, 2004). During crustal episodes, on the other hand, the Al2O3 component prevails (44% in PM10 and 42% in PM2.5) as the African and local soil dust is made up by a relatively high proportion of clay materials. Regional re-circulation episodes favour the transport of regional as well as local dust, and thus the resulting chemical composition of the mineral fraction is balanced between Al2O3 (36% in PM10, 33% in PM2.5) and Ca (37% in PM10, 32% in PM2.5). The relative weight of Fe and K is rather constant in the PM10 fraction for all PM episodes (18–23% and 8–9%, respectively), but it presents larger variations in PM2.5. In the fine fraction, maximal levels of these elements are detected during traffic episodes (29% Fe, 32% K), indicating that they are directly linked to road traffic emissions, probably to abrasion of brake lining. The presence of high levels of Fe in road dust has been observed by a number of authors (Sternbeck et al., 2002; Adachi and Tainosho, 2004). The results obtained for Tarragona are much more constant, as the Ca component is the highest for all of
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Table 3 P Relative weight of Al2O3, Ca, Fe and K with respect to the sum of the same elements and compounds [ (Al2O3, Ca, Fe, K)] for each of the clusters identified at the Barcelona and Tarragona study sites Industrial PM10 Barcelona Al2O3 35 Ca 37 Fe 20 K 8
Traffic
PM10
Crustal
Mixed
Average
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
29 29 24 18
25 44 23 9
15 24 29 32
36 37 18 9
33 32 20 15
44 29 19 9
42 29 16 12
27 43 20 9
27 34 20 19
33 38 20 9
29 30 22 19
Traffic
Tarragona Al2O3 24 Ca 52 Fe 13 K 11
Regional
PM2.5
Industrial
T+I
Regional
Mixed
Average
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
11 41 15 33
26 55 12 8
27 41 13 19
24 55 13 9
12 48 17 24
23 53 13 10
27 42 15 16
23 58 11 8
20 48 15 17
24 55 12 9
19 44 15 22
the PM episodes in PM10 and PM2.5, ranging from 52– 58% in PM10 and from 41–48% in PM2.5. The relative weights of the remaining elements are also rather constant in PM10 (Al2O3 23–26%, Fe 11–13%, K 8–11%), but not in PM2.5. As in Barcelona, the relative weights of Fe and K increase significantly in the fine fraction (Fe 17% during peak traffic episodes, K 33% during traffic episodes). On average, in PM10 Ca has a stronger relative weight within the crustal load in Tarragona than in Barcelona, even though it is dominant at both sites (38% in Barcelona, 55% in Tarragona). Road traffic emissions are the main cause of the higher relative weight of Fe in Barcelona (traffic site, 20%) than in Tarragona (urban background, 12%), and the results obtained for K are the same at both sites (9%). As regards PM2.5, at both sites the fine fraction is enriched in Fe and K with respect to PM10 (22% and 19% respectively in Barcelona, 15% and 22% in Tarragona) and depleted in Ca (30% in Barcelona, 44% in Tarragona). Al2O3 also shows a decrease in PM2.5 at both sites (29% in Barcelona, 19% in Tarragona), although it is not as marked as in the case of Ca. The coarser Ca particles are originated from pavement abrasion and road dust re-suspension, whereas the Fe and K particles result from finer grain size sources such as brake lining abrasion. These results coincide with CE (2004), where it is stated that PM10 particles are mainly produced by pavement abrasion whereas when automobile parts such as brake lining are worn out, finer grain size particles (PM2.5) are produced.
5. Conclusions The main objective of the present study is to identify the chemical profiles of PM10 and PM2.5 episodes in the
industrialised urban areas of North-Eastern Spain. To this end, a cluster analysis was performed on PM10 and PM2.5 samples. The differentiation between clusters in Tarragona was relatively more complicated than in Barcelona due to the high industrial background in this city, which results in high SIA levels during all episodes. Thus, the variations of the levels of OM + EC and gaseous pollutants (NO, SO2) played a key role in the identification of traffic and T + I episodes. • Traffic episodes are characterised by mean daily values of 22.7 lg/m3 of OM + EC in Barcelona and 14.2 lg/m3 of OM + EC in Tarragona in PM10. Good tracers of traffic emissions are Cu, Zn, Sb and Pb as a result of exhaust emissions and break lining abrasion. • During industrial episodes the composition of the PM10 mass is determined by the secondary inorganic aerosols (SIA), as they add up to daily mean levels of 18.6 lg/m3 in Barcelona and 10.9 lg/m3 in Tarragona. Due to the fact that the main industrial activities at both sites are power generation by fuel-oil and oil transformation (in Tarragona), the levels of Ni and V are good tracers of industrial emissions. • Regional re-circulation episodes, typical of the Western Mediterranean (Milla´n et al., 1997; Rodrı´guez et al., 2002), are characterised by high levels of O3 and SIA, especially sulphates (5.3 lg/m3 in Barcelona, 5.7 lg/m3 in Tarragona) as a consequence of the enhanced photochemistry of the aged air masses. • Crustal episodes are only identified at the Barcelona site, as they mainly represent the influence from different anthropogenic sources (construction, demolition, re-suspension from a nearby park) and sporadically African dust contributions. The composition of this
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mineral dust (Al2O3/Ca = 1.5) differs clearly from that of city road dust (Al2O3/Ca = 0.6). • T + I episodes are only observed in Tarragona, and represent peak PM episodes registered under strong anticyclonic conditions. The chemical profile of these episodes is characterised by high levels of OM + EC (14.2 lg/m3), SIA (10.4 lg/m3) and gaseous pollutants (136 lgNO/m3, 8 lgSO2/m3). The composition of the mineral load in PM10 varies as a function of the PM episodes. On average, Ca has a stronger relative weight in Tarragona than in Barcelona, even though it is dominant at both sites (38% of P (Al2O3, Ca, Fe, K) in Barcelona, 55% in Tarragona). Road traffic emissions are the main cause of the higher relative weight of Fe in Barcelona (traffic site, 20%) than in Tarragona (urban background, 12%). At both sites the fine fraction is enriched in Fe and K with respect to PM10 and depleted in Ca and Al2O3 as the Fe and K particles result from finer grain size sources such as brake lining abrasion. The coarser Ca particles are originated from pavement abrasion and road dust resuspension.
Acknowledgements The authors would like to thank the Spanish Ministries of Education and Science and Technology (CGL2004-05984-C07-02/CLI) and the Autonomous Government of Catalonia for their funding. The data on gaseous pollutants were kindly provided by the Environmental Department of the Autonomous Government of Catalonia. The authors would like to acknowledge Ferra´n Clua and Joan Miro´ for performing the Tarragona sampling.
References Adachi, K., Tainosho, Y., 2004. Characterization of heavy metal particles embedded in tire dust. Environ. Int. 30 (8), 1009–1017. CE, 2004. II Position Paper on PM, CAFE Programme, Environment D.G., European Commission, 214 pp. Chueinta, W., Hopke, P.K., Paatero, P., 2000. Investigation of sources of atmospheric aerosol at urban and suburban residential areas in Tailand by positive matrix factorization. Atmos. Environ. 34, 3319–3329. Dockery, D., Pope, A., 1996. Epidemiology of acute health effects: Summary of time-series studied. In: Spengler, J.D., Wilson, R. (Eds.), Particles in Our Air: Concentration and Health Effects. Harvard University Press, pp. 123–147. Eatough, D.J., Long, R.W., Modey, W.K., Eatough, N.L., 2003. Semi-volatile secondary organic aerosol in urban
atmospheres: meeting a measurement challenge. Atmos. Environ. 37, 1277–1292. Kim, B.M., Henry, R.C., 2000. Application of SAFER model to the Los Angeles PM10 data. Atmos. Environ. 34, 1747– 1759. Ku¨nzli, N., Kaier, R., Medina, S., Studnicka, M., Chanel, O., Filliger, P., Herry, M., Jr, F.H., Puybonnieux-Texier, V., Que´nel, P., Schneider, J., Seethaler, R., Vergnaud, J.C., Sommer, H., 2000. Public health impact of outdoor and traffic related air pollution: a European assessment. The Lancet 356, 795–801. Milla´n, M., Salvador, R., Mantilla, E., Kallos, G., 1997. Photooxidant dynamics in the Mediterranean basin in summer: results from European research projects. J. Geophys. Res. 102, 8811–8823. Pacyna, J.M., 1986. Emission factors of atmospheric elements. In: Nriagu, J.O., Davidson, C.I. (Eds.), Toxic Metals in the Atmosphere. Wiley, New York, pp. 33–52. Pakkanen, T.A., Kerminen, V., Loukkola, K., Hillamo, R.E., Aarnio, P., Koskentalo, T., Maenhaut, W., 2003. Size distributions of mass and chemical components in streetlevel and rooftop PM1 particles in Helsinki. Atmos. Environ. 37, 1673–1690. Pen˜a, D., Rivera, G.S.D., 1992. Estadı´stica. Modelos y me´todos. 1. Fundamentos. Alianza Universidad Textos. Querol, X., Alastuey, A., Rodrı´guez, S., Plana, F., Ruiz, C.R., Cots, N., Massague´, G., Puig, O., 2001. PM10 and PM2.5 source apportionment in the Barcelona Metropolitan Area, Catalonia, Spain. Atmos. Environ. 35–36, 6407–6419. Querol, X., Alastuey, A., Viana, M.M., Rodrı´guez, S., Artı´n˜ano, B., Salvador, P., Santos, S.G.D., Patier, R.F., Ruiz, C.R., Rosa, J.D.L., Campa, A.S.D.L., Menedez, M., Gil, J.I., 2004. Speciation and origin of PM10 and PM2.5 in Spain. J. Aerosol. Sci. 35 (9), 1151–1152. Rodrı´guez, S., Querol, X., Alastuey, A., Mantilla, E., 2002. Origin of high summer PM10 and TSP concentrations at rural sites in Eastern Spain. Atmos. Environ. 36 (19), 3101– 3112. Rodrı´guez, S., Querol, X., Alastuey, A., Viana, M.M., Alarco´n, M., 2004. Comparative PM10–PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain. Sci. Total Environ. 328, 95–113. Sternbeck, J., Sjo¨din, A., Andre´asson, K., 2002. Metal emissions from road traffic and the influence of resuspension— results from two tunnel studies. Atmos. Environ. 36, 4735– 4744. Thurston, G.D., Spengler, J.D., 1985. A quantitative assessment of source contribution to inhalable particulate matter pollution in Metropolitan Boston. Atmos. Environ. 19 (1), 9–25. Turpin, B.J., Saxena, P., Andrews, E., 2000. Measuring and simulating particulate organics in the atmosphere: problems and prospects. Atmos. Environ. 34, 2983–3013. WHO, 2003. Health aspects of air pollution with particulate matter, ozone and nitrogen dioxide. World Health Organization, 98 pp. Wilson, W.E., Chow, J.C., Claiborn, C., Fusheng, W., Engelbrecht, J., Watson, J.G., 2002. Monitoring of particulate matter outdoors. Chemosphere 49, 1009–1043.
Chemical characterisation of PM episodes in NE Spain M. Viana *, X. Querol, A. Alastuey Institute of Earth Sciences ‘‘Jaume Almera’’, C/Lluis Sole´ i Sabarı´s s/n, 08028 Barcelona, Spain Received 13 January 2005; received in revised form 17 May 2005; accepted 30 May 2005 Available online 3 August 2005
Abstract The chemical composition of ambient particulate matter (PM) varies widely as a function of its main emission sources and of the chemical reactions which take place in the atmosphere. The aim of this study is to obtain the chemical profile of PM10 and PM2.5 during peak PM episodes, thus identifying the main emission sources and/or atmospheric processes which originate the PM episodes. To this end, cluster analysis was applied to a set of PM10 and PM2.5 data collected throughout 2001 in two urban and industrialised areas in NE Spain. As a result of this analysis, five clusters were identified for each site, and the interpretation of their chemical profiles lead to the identification of five types of peak PM episodes for each site: industrial, traffic and regional re-circulation episodes at both sites, plus crustal episodes in Barcelona, and peak traffic and industrial episodes (T + I) in Tarragona. Traffic episodes are characterised by daily means of 23 and 10 lg/m3 of OM + EC in Barcelona and Tarragona in PM10. Levels of secondary inorganic aerosols reach average daily means of 19 and 11 lg/m3 in Barcelona and Tarragona in PM10 during industrial episodes. High levels of sulphate (>5 lg/m3) and ozone (up to 77 lg/m3 daily mean) are good tracers of regional re-circulation episodes. During crustal episodes daily means of crustal elements reach up to 34 lg/m3 in Barcelona. Special attention has been drawn to the composition of the mineral matter during the different PM episodes. 2005 Published by Elsevier Ltd. Keywords: Cluster analysis; Source contribution; Chemical profile; Sahara dust; Mineral matter
1. Introduction Particulate matter (PM) is a complex mixture of substances suspended in the atmosphere in solid or liquid state with different properties (e.g. size distribution or chemical composition amongst others) and origins (anthropogenic and natural). Owing to this mixture of substances the chemical composition of PM may vary widely as a function of its major emission sources and the subsequent chemical reactions which take place in the atmosphere.
*
Corresponding author. Fax: +34 934110012. E-mail address: [email protected] (M. Viana).
0045-6535/$ - see front matter 2005 Published by Elsevier Ltd. doi:10.1016/j.chemosphere.2005.05.048
The study of this atmospheric pollutant has increased in the past years due to the understanding of its adverse effects on health (Dockery and Pope, 1996; Ku¨nzli et al., 2000; WHO, 2003) and the consequent implementation in the year 2001 of the European directive 1999/30/ EU, which establishes annual and daily limit values for PM10 (the PM mass which passes through a size selective impactor inlet with a 50% efficiency cut-off at 10 lm aerodynamic diameter). The chemical mass balance is the most commonly used method for assessing particulate matter source contributions (Wilson et al., 2002), and statistical methods such as factor analysis and multi-linear regression (Thurston and Spengler, 1985) have also produced interesting results regarding source identification. The results
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obtained from the use of these techniques are usually expressed as the contributions (in % and/or lg/m3) of the sources to the PM mass. However, the main objective of the present study is not to identify the contributions of the sources but to obtain the chemical profile of PM during peak concentration episodes in the North-Eastern Iberian Peninsula, and thus a different approach has been chosen: the use of cluster analysis. Statistical clustering of the PM samples classifies the samples in a straightforward manner according to their chemical profiles, and yields a number of clusters characterised by their specific chemical composition (Pen˜a and Rivera, 1992). The resulting compositional profile is then a reflection of the major emission source and/or the atmospheric process involved in the production of the peak PM episodes.
2. Methodology Two urban monitoring sites were selected in Barcelona and Tarragona, on the North-Eastern coast of Spain (Fig. 1). The Barcelona site is located in a park, under the influence of dense road traffic (Meridiana Avenue, located 150 m to the North of the station) and a large industrial area including two fuel-oil power plants. The Tarragona site is an urban background site located on the rooftop of a seven-storey building, under the influence of PM emissions from road
traffic and a highly industrialised area (oil chemistry and transformation, fuel-oil power plant, chemical industries). The sampling of PM10 and PM2.5 was carried out from 09/01/2001 to 27/12/2001 by means of the EN1234-1 reference high volume method for PM10 (Andersen, 68 m3/h) and high volume (30 m3/h) MCV samplers for PM2.5. It is important to consider that this sampling technique may be subject to the loss of a certain fraction of carbonaceous species and NO 3 by volatilisation (Turpin et al., 2000; Eatough et al., 2003). Three PM10 and two PM2.5 samples were collected per week, and 2 PM10 and 1 PM2.5 samples per week were selected for chemical analysis. The methodology (Querol et al., 2001) is based on the acid digestion of 1/2 of the filter for the determination of major and trace elements by ICP-AES and ICP-MS, water leaching of 1/4 of the filter to determine soluble ion concentrations ðSO2 4 , NO3 , þ NH4 , Cl ) by ion chromatography and FIA colorimetry, and elemental analysis of total C in the remaining 1/4 of the filter. The results from these chemical analyses were then grouped into four main components: crustal ðCO2 3 , SiO2, Al2O3, Ca, K, Mg, Fe, P2O5), OM + EC (organic matter + elemental carbon), SIA (secondary þ inorganic aerosols, nonmarine SO2 4 , NO3 , NH4 Þ and 2 marine (Na, Cl , marine SO4 ). A variable percentage of undetermined mass was observed. Relative analytical errors were between 3% and 10% for the elements studied.
Fig. 1. Study area and location of monitoring sites Barcelona and Tarragona.
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Cluster analysis was applied to the PM10 samples by means of the software package STATISTICA 4.2. The algorithm selected was K-means clustering by single linkage, taking Euclidean distances as the distance measure. The total number of samples was 88 for each site, although the final clustering was reduced to 85 cases for Barcelona and 81 for Tarragona as any cases with missing variables were excluded from the analysis. The same analysis was then applied to the PM2.5 samples, but owing to the lower number of samples available (44 and 43 samples respectively) the results were not concluding.
3. Chemical profiles of PM episodes The cluster analysis performed on the chemical dataset produced five independent clusters of samples for each site (Tables 1 and 2). Main tracer species were identified in the resulting chemical composition of each cluster, and these tracers were compared to those presented in available source contribution literature (Pacyna, 1986; Chueinta et al., 2000; Kim and Henry, 2000; Querol et al., 2001; Rodrı´guez et al., 2002; Sternbeck et al., 2002; Pakkanen et al., 2003; Adachi and Tainosho, 2004; Rodrı´guez et al., 2004). As a result, the clusters obtained for Barcelona were identified as industrial, traffic, regional, crustal and undetermined (Table 1), whereas those obtained for Tarragona were identified as industrial, traffic, traffic and industrial peak episodes (T + I), regional and undetermined (Table 2). The tracer species which helped interpret the origin of each of the clusters are discussed in detail below. The undetermined cluster represents samples in which the PM mass results from a mixture of sources. Traffic and industrial episodes are considered to have a local origin, as they result from the impact of local emissions on PM levels under low dispersive atmospheric scenarios. The T + I cluster in Tarragona was identified as peak industrial and/or traffic episodes. The regional clusters refer to regional re-circulation episodes as defined by Milla´n et al. (1997), which are originated by the re-circulation and ageing of air masses during the summer months due to specific orographic and meteorological conditions in the Western Mediterranean basin. Finally, in the case of Barcelona a cluster defined as crustal was identified, whereas it was not identified in the Tarragona analysis. In Barcelona this cluster represents the contribution of mineral matter from a number of anthropogenic sources such as construction and demolition dust and re-suspension from the park in which the station is located. It sporadically includes dust transported during African dust outbreaks, although these cases only represent a minor percentage during the sampling period (3 days out of 10 in the cluster). The fact that this cluster is not present in Tarragona
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may be due to the location of the site at a considerable height (seven-storey building), which limits the influence of mineral dust sources such as road dust re-suspension. The local influence of the park is also absent in Tarragona. African dust contributions are not identified as an isolated cluster in Tarragona as the percentage of the variability of the dataset represented by these samples was too low for them to be isolated as one independent cluster by the statistical analysis (considering that the analysis identifies no other direct crustal sources). The average chemical composition of PM10 and PM2.5 for each cluster is summarised in Tables 1 and 2. It is important to note that the cluster identified as traffic in Barcelona in PM2.5 includes only one sample, and thus the results may not be fully representative. Out of the 88 PM10 samples and the 44 and 43 PM2.5 samples available for Barcelona and Tarragona respectively, 85 and 81 PM10 and 43 and 36 PM2.5 samples were considered for the cluster analysis. Industrial episodes: the number of cases in this cluster is similar in Barcelona (n = 15, 18% of the PM10 cases) and Tarragona (n = 20, 25%). The mean daily PM10 levels obtained during these episodes are 57.5 lg/m3 in Barcelona (9.9 lg/m3 standard deviation, s.d.) and 37.1 lg/m3 in Tarragona (9.6 lg/m3 s.d.), and they were mainly registered between April and May and in September, showing no specific seasonal trend. The main tracers of the industrial origin of these episodes are the secondary inorganic aerosols (SIA, Querol et al., 2001; Rodrı´guez et al., 2004), which present average values of 18.6 lg/m3 in Barcelona (6.5 lg/m3 s.d.) and 10.9 lg/m3 in Tarragona (5.4 lg/m3 s.d.). Due to the influence of traffic at both sites, the levels of the OM + EC and crustal fractions are also relatively high (13.7 lg/m3 and 17.0 lg/m3 in Barcelona, and 7.9 lg/m3 and 10.6 lg/m3 in Tarragona for OM + EC and the crustal fraction, respectively). The composition of the SIA fraction has also been analysed, with the result that in Tarragona 55% of the total SIA mass is constituted by nonmarine sulphate (6.0 lg/m3) and 31% by nitrate (3.4 lg/m3), whereas in Barcelona both species represent a similar fraction (39% nitrate, 7.2 lg/m3, and 40% sulphate, 7.4 lg/m3). The prevalence of sulphate over nitrate in Tarragona during industrial episodes responds to the higher relative weight of industrial emissions with respect to traffic emissions at this site, while in Barcelona the traffic and industrial influences seem to have a similar relative weight. Due to the fact that industrial emissions in the study areas generally do not affect the mineral load, the composition of this fraction is very similar to the annual average (Al2O3/Ca = 0.92 vs 0.91 annual mean in Barcelona, and 0.45 vs 0.43 in Tarragona). With respect to the trace elements, these episodes are characterised in Barcelona and Tarragona by high levels
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Table 1 Average chemical composition of PM10 and PM2.5 at a traffic site with industrial influence in Barcelona, as a function of the 5 PM episodes identified: industrial, traffic, regional re-circulation, crustal and mixed sources Industrial PM10 n = 15 (18%)
Traffic PM10 n=8 (9%)
Regional PM10 n = 26 (31%)
Crustal PM10 n = 10 (12%)
Mixed PM10 n = 26 (31%)
Industrial PM2.5 n=9 (21%)
Traffic PM2.5 n=1 (2%)
Regional PM2.5 n = 12 (28%)
Crustal PM2.5 n=8 (19%)
Mixed PM2.5 n = 13 (30%)
lg/m3 T SO2 NO NO2 O3 PM OM + EC CO2 3 SiO2 Al2O3 Ca K Na Mg Fe nmSO2 4 mSO2 4 NO 3 Cl NHþ 4
19 5 31 45 21 57.5 13.7 4.2 6.3 2.1 2.3 0.5 0.9 0.3 1.2 7.4 0.2 7.2 0.6 3.9
14 7 87 54 8 66.3 22.7 5.4 5.2 1.7 3.0 0.6 0.8 0.3 1.6 5.5 0.2 5.7 1.3 2.0
25 5 8 25 44 36.1 6.6 3.0 4.3 1.4 1.4 0.4 1.6 0.3 0.7 5.3 0.4 2.5 1.1 1.5
19 7 20 35 29 64.7 10.5 6.7 15.0 5.0 3.3 1.0 1.5 0.7 2.2 3.8 0.4 3.4 1.4 1.8
16 5 24 37 21 36.1 10.8 3.2 3.2 1.1 1.7 0.4 0.8 0.2 0.8 3.3 0.2 2.7 1.0 1.4
20 4 35 46 23 36.9 15.1 1.0 1.1 0.4 0.4 0.2 0.1 0.2 0.3 6.3 <0.1 5.2 0.3 3.7
13 5 89 45 6 48.0 26.2 0.4 0.4 0.1 0.2 0.3 0.2 <0.1 0.3 6.3 <0.1 6.4 0.9 4.1
24 4 7 21 46 18.8 7.5 0.7 0.8 0.3 0.3 0.1 0.3 0.1 0.2 3.9 0.1 0.5 0.3 1.4
16 4 21 34 19 38.1 14.1 2.0 4.1 1.4 0.9 0.4 0.3 0.2 0.5 4.0 0.1 3.1 0.4 2.0
15 2 32 39 16.4 24.7 13.6 0.7 1.0 0.3 0.4 0.2 0.2 0.1 0.2 3.4 0.1 2.0 0.5 1.7
%acc. Undet. Crustal Marine SIA OM + EC
89.7 6.0 17.0 1.8 18.6 13.7
86.4 9.1 18.0 2.4 13.3 22.7
86.5 5.1 11.6 3.2 9.3 6.6
89.3 7.3 34.0 3.3 8.9 10.5
87.6 4.9 10.7 2.0 7.4 10.8
93.0 3.0 3.6 0.5 15.2 15.1
95.8 2.0 1.9 1.0 16.8 26.2
88.0 3.8 2.4 0.7 5.8 7.5
90.6 5.5 9.6 0.7 9.2 14.1
101.6 1.2 3.0 0.7 7.1 13.6
83 25 12 0.5 13 67 122 2 1.9 7 0.8 6 12 50 95
92 24 13 0.5 11 87 180 1.9 2 8 1.5 7 21 74 107
51 11 6 0.3 5 34 60 1.0 1.3 5 0.5 4 6 25 29
229 16 9 0.7 7 42 104 2 5 11 0.5 3 10 57 69
64 11 7 0.3 6 45 96 1.2 1.3 5 0.7 4 8 38 46
18 19 4 0.3 9 36 61 1.9 0.6 1.5 0.9 6 4 6 60
7 13 1.9 0.1 6 48 67 1.1 0.5 1.0 1.2 8 8 8 54
15 5 2 0.3 3 26 42 0.7 0.5 1.2 0.3 2 3 4 20
69 9 3 0.2 4 24 61 0.9 1.4 3 0.5 4 4 11 49
19 7 3 0.3 4 37 55 0.8 0.5 2 0.7 4 4 14 42
ng/m3 Ti V Cr Co Ni Cu Zn As Rb Sr Cd Sn Sb Ba Pb
2 n: Number of samples; OM + EC: organic matter + elemental carbon; nmSO2 4 : nonmarine sulphate; mSO4 : marine sulphate; %acc.: PM mass recovery through analysis; undet.: undetermined; crustal: CO2 , SiO , Al O , Ca, K, Mg, Fe, P O ; SIA: secondary inorganic 2 2 3 2 5 3 2 þ aerosols (nmSO2 4 , NO3 , NH4 ); marine: Na, Cl , mSO4 ; T: temperature (C).
of Ni (13 ng/m3 and 6 ng/m3), V (25 ng/m3 and 10 ng/m3) and Cr (12 ng/m3 and 4 ng/m3). These tracers typically reflect the presence of fuel-oil power plant
and/or petroleum refinery emissions (Pacyna, 1986). Both PM sources are found in the study areas (one power plant and a refinery in Tarragona, two power
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Table 2 Average chemical composition of PM10 and PM2.5 at an urban background site with industrial influence in Tarragona, as a function of the 5 PM episodes identified: industrial, traffic, T + I (traffic + industrial peak episodes), regional re-circulation and mixed sources Industrial PM10 n = 20 (25%)
Traffic PM10 n = 20 (25%)
T+I PM10 n=8 (10%)
Regional PM10 n = 16 (20%)
Mixed PM10 n = 17 (21%)
Industrial PM2.5 n=8 (22%)
Traffic PM2.5 n=6 (17%)
T+I PM2.5 n=6 (17%)
Regional PM2.5 n=6 (17%)
Mixed PM2.5 n = 10 (28%)
lg/m3 T SO2 NO NO2 O3 PM OM + EC CO2 3 SiO2 Al2O3 Ca K Na Mg Fe nmSO2 4 mSO2 4 NO 3 Cl NHþ 4
23 4 33 38 55 37.1 7.9 3.9 2.7 0.9 2.0 0.3 1.3 0.3 0.4 6.0 0.3 3.4 0.8 1.5
15 4 63 42 28 42.6 10.4 3.0 2.2 0.8 1.7 0.4 0.9 0.3 0.4 4.7 0.2 6.0 0.8 2.2
18 8 136 49 19 47.1 14.2 4.6 3.3 1.2 2.8 0.4 0.9 0.4 0.6 4.3 0.2 4.9 0.6 1.2
26 3 11 31 77 31.1 6.4 2.5 1.5 0.5 1.2 0.2 1.5 0.3 0.3 5.7 0.4 2.3 0.9 1.3
18 2 16 27 49 29.5 6.6 2.9 1.9 0.7 1.8 0.3 1.3 0.3 0.3 3.3 0.3 2.2 1.2 0.9
18 4 36 44 52 27.3 8.1 0.9 0.8 0.3 0.4 0.2 0.6 0.1 0.1 6.3 0.1 1.7 0.2 2.5
17 4 67 40 26 26.9 8.3 0.5 0.2 0.1 0.3 0.2 0.3 0.1 0.1 3.4 0.1 3.8 0.3 1.6
17 7 131 47 18 24.5 11.3 0.6 0.2 0.1 0.4 0.2 0.3 0.1 0.1 3.1 0.1 3.2 0.3 1.6
18 1.9 11 24 75 19.6 5.2 0.5 0.5 0.2 0.2 0.1 0.3 0.1 0.1 4.9 0.1 0.5 0.1 1.9
16 1.8 16 27 48 16.2 6.0 0.4 0.3 0.1 0.2 0.1 0.2 <0.1 0.1 2.8 0.1 1.1 0.1 1.4
%acc. Undet. Crustal Marine SIA OM + EC
86.1 5.8 10.6 2.4 10.9 7.9
79.7 8.6 8.7 1.9 12.9 10.4
85.0 7.2 13.4 1.8 10.4 14.2
80.7 5.9 6.5 2.8 9.4 6.4
81.5 5.9 8.2 2.7 6.3 6.6
82.4 5.5 2.9 0.9 10.5 8.1
74.9 7.5 1.5 0.7 8.8 8.3
91.5 3.6 1.7 0.7 7.9 11.3
80.4 6.2 1.7 0.5 7.3 5.2
89.7 5.8 1.3 0.4 5.2 6.0
ng/m3 Ti V Cr Co Ni Cu Zn As Rb Sr Cd Sn Sb Ba Pb
22 10 4 0.2 6 25 31 0.7 0.9 6 0.3 1.7 4 13 19
23 8 2 0.2 4 34 44 1.0 0.9 4 0.4 2 5 12 36
35 12 3 0.3 6 44 50 1.1 1.3 6 0.3 2 7 17 40
16 6 1.9 0.2 3 22 24 0.4 0.6 4 0.1 2 2 9 13
22 4 1.8 0.1 2 23 22 0.5 0.7 5 0.2 1.2 3 10 17
8 9 4 0.1 5 40 19 0.4 0.6 2 0.2 1.3 1.7 3 15
4 6 1.9 0.1 3 40 24 0.6 0.4 1.0 0.4 1.5 1.8 4 26
6 6 3 0.1 5 39 30 0.7 0.4 0.9 0.4 0.9 5 4 23
6 4 2 0.1 3 22 14 0.2 0.2 1.0 0.2 0.7 0.9 2 10
5 3 0.8 0.1 1.7 18 12 0.3 0.2 0.6 0.1 0.4 4 3 12
2 n: Number of samples; OM + EC: organic matter + elemental carbon; nmSO2 4 : nonmarine sulphate; mSO4 : marine sulphate; % acc.: PM mass recovery through analysis; undet.: undetermined; crustal: CO2 , SiO , Al O , Ca, K, Mg, Fe, P O 2 2 3 2 5; SIA: secondary inorganic 3 2 þ aerosols (nmSO2 4 , NO3 , NH4 ); marine: Na, Cl , mSO4 ; T: temperature (C).
plants in Barcelona). The levels of gaseous pollutants do not show marked increases during these episodes. Traffic episodes: the number of cases in this cluster is higher in Tarragona (n = 20, 25% of the cases) than in
Barcelona (n = 8, 9%), despite the marked traffic influence at the latter site. The fact that the Tarragona traffic cluster is more populated than in Barcelona does not indicate that the number of traffic episodes is higher in
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Tarragona, but that the traffic contributions are not as clearly differentiated in Barcelona. The higher degree of mixture between emissions from different sources in Barcelona is probably related to the location of the main industrial and traffic sources in the same direction (NNE, Beso`s river valley and Meridiana Ave.) with respect to the monitoring site. The PM10 levels registered reach high levels at both sites (the highest for all clusters in Barcelona, 66.3 lgPM10/m3, 7.0 lg/m3 s.d. and 42.6 lgPM10/m3, 11.0 lg/m3 s.d. in Tarragona). These episodes are mainly registered from October to March, coinciding with lower atmospheric dispersive conditions. The chemical composition of PM during these episodes in Barcelona is mainly determined by OM + EC (22.7 lg/m3, 4.6 lg/m3 s.d.) as a result of the road traffic exhaust emissions, followed by the mineral fraction (18.0 lg/m3, 4.6 lg/m3 s.d.) originated from road dust erosion and re-suspension (Kim and Henry, 2000; Querol et al., 2001). Note that the mean OM + EC levels during traffic episodes double the annual average obtained in Barcelona (11 lg/m3). In Tarragona the strong influence of the industrial emissions generates high SIA background levels during all episodes. Thus, during traffic episodes the highest OM + EC levels are registered (10.4 lg/m3, except for peak T + I episodes) and in parallel high SIA levels are registered (12.9 lg/m3, 6.9 lg/m3 s.d.). During traffic episodes the nitrate fraction prevails over sulphate in Tarragona (47% nitrate, 36% sulphate) whereas in Barcelona the ratios are once again balanced (43% nitrate, 42% sulphate). The composition of the mineral road dust re-suspended by traffic is in both cases dominated by Ca (3.0 lg/m3 in Barcelona, 1.7 lg/m3 in Tarragona) with respect to Al2O3 (1.7 lg/m3 in Barcelona, 0.8 lg/m3 in Tarragona), indicating that construction work dust is a significant contributor to mineral dust deposited on roads at urban sites. The Ti/Fe ratio may constitute a good tracer of road dust re-suspension as the results obtained for Barcelona (Ti/Fe = 59) and Tarragona (Ti/Fe = 53) are significantly different to that obtained in Barcelona for the crustal cluster (Ti/Fe = 106). The emissions from road traffic are typically characterised by high levels of Ba, Sb, Cd, Pb, Zn and Cu (Sternbeck et al., 2002; Pakkanen et al., 2003; Adachi and Tainosho, 2004). These results are confirmed during traffic episodes in Barcelona, where the average concentrations of these trace elements reach levels of Cu (87 ng/ m3), Zn (180 ng/m3), Cd (1.5 ng/m3), Sb (21 ng/m3), Ba (74 ng/m3) and Pb (107 ng/m3) which are maximal when compared to the other clusters. In the case of Tarragona the most outstanding elements are Cu (34 ng/m3), Zn (43 ng/m3), Sb (5 ng/m3) and Pb (36 ng/m3), although it must be noted that the traffic cluster in Tarragona does not include the peak traffic episodes, included in the T + I cluster. Finally, traffic episodes are also characterised by the highest levels of gaseous compounds such as NO
(87 lg/m3, 63 lg/m3 in Barcelona and Tarragona) and NO2 (54 lg/m3, 42 lg/m3 in Barcelona and Tarragona). Consequently, O3 levels are relatively low (8 lg/m3 and 28 lg/m3, respectively). Traffic + Industrial peak episodes (T + I): this cluster was only identified in the Tarragona analysis, and includes 8 PM10 samples (10% of the PM10 cases). The meteorological analysis of these days showed that the synoptic scale scenario was dominated by high pressure systems, mainly in winter, which favoured the stagnation of the air masses and the increase of pollutants emitted by local sources. The mean chemical composition of these local anthropogenic pollution episodes is dominated by OM+EC (14.2 lg/m3, 3.0 lg/m3 s.d.) and crustal components (13.4 lg/m3, 6.6 lg/m3 s.d.) as a result of the traffic influence, but also by SIA (10.4 lg/m3, 5.5 lg/m3 s.d.) originating from the industrial emissions. As a result of the source mixture present in this cluster, the chemical composition is characterised by high levels of elements such as V (12 ng/m3) and Ni (6 ng/m3), tracers of oil combustion emissions, but also by Cu (44 ng/m3), Ba (17 ng/m3) or Sb (7 ng/m3), tracers of road traffic emissions. Furthermore, levels of mineral trace elements such as Ti (35 ng/m3) or Sr (6 ng/m3) are also found in relatively high concentrations during these episodes. Regarding gaseous compounds, these episodes present the highest mean concentrations of SO2 (8 lg/m3), NO (136 lg/m3) and NO2 (49 lg/m3) and the lowest of O3 (19 lg/m3) in Tarragona. Crustal episodes: crustal episodes (n = 10, 12% of the PM10 cases) were only detected in Barcelona, and they include a number of anthropogenic sources such as construction and demolition dust and re-suspension from the park in which the station is located, and sporadically mineral dust transported during African dust outbreaks (3 out of 10 cases in the cluster). In Tarragona the station is located at a higher altitude than the Barcelona site, and this may account for a reduced influence of anthropogenic re-suspended dust. These episodes were detected in Barcelona in February–April, October and November, showing no seasonal trend. Average PM10 levels obtained in Barcelona are the second highest after the traffic episodes (64.7 lg/m3). As expected, the chemical composition is dominated by the levels of crustal components (34.0 lg/m3, 10.4 lg/m3 s.d., Chueinta et al., 2000; Kim and Henry, 2000; Querol et al., 2001), but it is important to note that in this fraction the levels of Al2O3 are predominant (5.0 lg/m3) with respect to Ca (3.3 lg/m3). This composition contrasts with that obtained during traffic episodes in which Ca prevailed both in Barcelona and Tarragona. Apart from the higher Al2O3/Ca ratio (1.5) during crustal episodes with respect to traffic episodes (Al2O3/Ca = 0.6 in Barcelona, 0.4 in Tarragona), the Al2O3 levels are also higher in this cluster (5.0 lg/m3 vs 1.7 lg/m3 during traffic episodes in Barcelona), evidencing the influence of
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clay minerals from African dust. This influence may also be observed regarding trace elements such as Ti (229 ng/m3) Rb (5 ng/m3) or Sr (11 ng/m3), which present maximal concentrations during crustal episodes. Regional re-circulation episodes: the mean daily PM10 levels obtained during regional re-circulation episodes at both study sites are lower than under crustal, traffic or industrial episodes. On average, PM10 levels reach 36.1 lg/m3 in Barcelona (n = 26, 31%) and 31.1 lg/m3 in Tarragona (n = 16, 20%). The main PM10 constituents during these days are SIA and crustal components in Barcelona (9.3 lg/m3, 4.0 lg/m3 s.d. and 11.6 lg/m3, 3.0 lg/m3 s.d.) and Tarragona (9.3 lg/m3, 5.1 s.d. and 6.5 lg/m3, 2.4 s.d.). As defined by Milla´n et al. (1997) regional re-circulation episodes are characterised by the ageing of air masses and they mainly occur during the spring and summer months, and it is a process which favours the formation of secondary aerosols (Rodrı´guez et al., 2002). Thus, owing to the high atmospheric stability of ammonium sulphate with respect to ammonium nitrate in warm periods, 57–61% of the SIA mass in PM10 is comprised of sulphate in Barcelona and Tarragona (mean levels of 5.3 lg/m3 and 5.7 lg/m3), and only 25–27% by nitrate (2.4–2.5 lg/m3). Furthermore, the summer convective circulations increase the re-suspension of soil particles and thus result in an increase of the crustal load in PM10 (mainly made up of Ca compounds, especially in Tarragona). The composition of PM10 during these episodes is not significantly characterised by the levels of any of the trace elements analysed, which are usually found in lower concentrations than under the other clusters identified. Conversely, gaseous pollutants are very good tracers of this type of episode as O3 levels reach the highest values (77 lg/m3 in Tarragona and 44 lg/m3 in Barcelona) and NO the lowest (11 lg/m3 and 8 lg/m3, respectively). Owing to the fact that these episodes mainly occur in summer (>80% in this study), temperature may constitute another good indicator of the occurrence of regional re-circulation episodes (highest mean levels of 25 C and 26 C registered in Barcelona and Tarragona for this type of episode, respectively). Undetermined (mixed) episodes: these clusters group the samples in which a mixture of sources was identified, and thus do not present a specific chemical profile or gaseous tracers. They consist of 26 cases (31%) in Barcelona and 17 (21%) in Tarragona for PM10, and are detected throughout the year. The cluster analysis was also applied to PM2.5, but the results were not representative due to the low number of cases available for each site (36 in Tarragona, 43 in Barcelona). However, in order to characterise the chemical composition of the finer grain size fraction the clustering obtained for PM10 was applied to the PM2.5 samples. For this approach it was assumed that the same sources which dominate in PM10 have a signif-
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icant influence on the finer fractions. This assumption may only be considered valid if all the sources identified in this study (industry, traffic, regional re-circulation, crustal material) have an impact on the levels of both PM10 and PM2.5, even though this impact may be clearly distinct for each fraction. The results here presented for PM2.5 (extrapolated from PM10) should thus not be considered as fully conclusive. This approach for PM2.5 has implications mainly for the days in which coarser sized emission sources dominate in PM10 (e.g., crustal material). Taking into account that the impact of this source is lower in PM2.5 than in PM10 (although not negligible), the resulting PM2.5 chemical profile would overestimate the contribution of the finer grain size sources, as their relative weight would be higher than that of the coarser grain size sources. A minimum number of 80–100 cases would be necessary for the optimal differentiation of independent clusters. PM2.5 levels under traffic episodes reach mean daily values of 48.0 lg/m3 in Barcelona (n = 1, 2%) and 27.0 lg/m3 in Tarragona (n = 6, 17%). Owing to the fine grain size distribution of OM + EC, it is this component that predominates in the composition of this PM fraction (26.2 lg/m3 in Barcelona, 8.3 lg/m3 in Tarragona). The relative weight of the mineral fraction decreases significantly in PM2.5 (20–27% in PM10 to 4–6% in PM2.5 at both sites). In absolute values the levels are very similar in Barcelona (1.9 lg/m3) and Tarragona (1.5 lg/m3), although higher levels were expected in Barcelona as the PM2.5 crustal fraction is significantly influenced by road traffic (Querol et al., 2004). This might be due to the fact that there is only one PM2.5 sample available in Barcelona. Levels of PM2.5 are maximal during industrial episodes in Tarragona (27.3 lgPM2.5/m3, n = 8, 22%) and high in Barcelona (36.9 lgPM2.5/m3, n = 9, 21%). The major contributor to the PM2.5 mass are the SIA, with 15.2 lg/m3 in Barcelona and 10.5 lg/m3 in Tarragona. The OM + EC contribution is also significant (15.1 lg/m3 in Barcelona and 8.1 lg/m3 in Tarragona). During regional re-circulation episodes PM2.5 levels reach 18.8 lg/m3 in Barcelona (n = 12, 28%) and 19.6 lg/m3 in Tarragona (n = 6, 17%), and the main components are OM + EC and SIA (7.5 lg/m3 and 5.8 lg/m3 respectively in Barcelona and 5.2 lg/m3 and 7.3 lg/m3 in Tarragona). The prevalence of sulphate with respect to nitrate and ammonia observed in PM10 is even more evident in PM2.5, as 67–68% of the SIA mass is made up of nonmarine sulphate (3.9 lg/m3 and 4.9 lg/m3 in Barcelona and Tarragona) whereas nitrate constitutes only 7–9% (0.5 lg/m3 at both sites). The composition of the crustal load is determined by Ca in Tarragona (Al2O3/Ca = 0.7) owing to the geology of the area, whereas in Barcelona the ratio is higher (Al2O3/Ca = 1.1). These results were also observed for PM10.
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Fig. 2. Chemical composition of PM10 and PM2.5 in Barcelona and Tarragona as a function of the different PM episodes identified.
Finally, the mean daily PM2.5 values registered during crustal episodes reach 38.1 lg/m3 in Barcelona (n = 8, 19%), with a mineral load of 9.6 lg/m3. This result is significantly high, as it represents 35% of the PM2.5 mass. The influence of clay minerals is still evident in the PM2.5 fraction, as the Al components prevail over Ca (Al2O3/Ca = 1.4). Accordingly to the results described above, Fig. 2 summarises the mean chemical composition of PM10 and PM2.5 during the different PM episodes identified in Barcelona and Tarragona. The figure shows how the percentages of OM + EC and SIA increase in PM2.5 with respect to PM10 at both sites, whereas the mineral and the marine fractions decrease significantly due to their coarser grain size distributions.
4. Composition of the crustal load The chemical composition of the crustal load may vary as a function of the different PM episodes. These variations are presented in Table 3, expressed as the relative weight of Al2O3, Ca, Fe and K with P respect to the sum of these elements and compounds [ (Al2O3, Ca, Fe, K)]. This group of elements has been selected because they are major components of the mineral fraction and their concentrations were determined by chemical analyses (direct measurements).
The largest variations are observed at the Barcelona site. For this station, Ca is the dominant element in PM10 and PM2.5 during industrial and traffic episodes (37% and 44% for PM10 and 29% and 24% for PM2.5, respectively), mainly due to the re-suspension of road dust by traffic. Road dust may contain high levels of Ca originated from construction works in the city area and/or from road pavement and paint (Adachi and Tainosho, 2004). During crustal episodes, on the other hand, the Al2O3 component prevails (44% in PM10 and 42% in PM2.5) as the African and local soil dust is made up by a relatively high proportion of clay materials. Regional re-circulation episodes favour the transport of regional as well as local dust, and thus the resulting chemical composition of the mineral fraction is balanced between Al2O3 (36% in PM10, 33% in PM2.5) and Ca (37% in PM10, 32% in PM2.5). The relative weight of Fe and K is rather constant in the PM10 fraction for all PM episodes (18–23% and 8–9%, respectively), but it presents larger variations in PM2.5. In the fine fraction, maximal levels of these elements are detected during traffic episodes (29% Fe, 32% K), indicating that they are directly linked to road traffic emissions, probably to abrasion of brake lining. The presence of high levels of Fe in road dust has been observed by a number of authors (Sternbeck et al., 2002; Adachi and Tainosho, 2004). The results obtained for Tarragona are much more constant, as the Ca component is the highest for all of
M. Viana et al. / Chemosphere 62 (2006) 947–956
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Table 3 P Relative weight of Al2O3, Ca, Fe and K with respect to the sum of the same elements and compounds [ (Al2O3, Ca, Fe, K)] for each of the clusters identified at the Barcelona and Tarragona study sites Industrial PM10 Barcelona Al2O3 35 Ca 37 Fe 20 K 8
Traffic
PM10
Crustal
Mixed
Average
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
29 29 24 18
25 44 23 9
15 24 29 32
36 37 18 9
33 32 20 15
44 29 19 9
42 29 16 12
27 43 20 9
27 34 20 19
33 38 20 9
29 30 22 19
Traffic
Tarragona Al2O3 24 Ca 52 Fe 13 K 11
Regional
PM2.5
Industrial
T+I
Regional
Mixed
Average
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
PM10
PM2.5
11 41 15 33
26 55 12 8
27 41 13 19
24 55 13 9
12 48 17 24
23 53 13 10
27 42 15 16
23 58 11 8
20 48 15 17
24 55 12 9
19 44 15 22
the PM episodes in PM10 and PM2.5, ranging from 52– 58% in PM10 and from 41–48% in PM2.5. The relative weights of the remaining elements are also rather constant in PM10 (Al2O3 23–26%, Fe 11–13%, K 8–11%), but not in PM2.5. As in Barcelona, the relative weights of Fe and K increase significantly in the fine fraction (Fe 17% during peak traffic episodes, K 33% during traffic episodes). On average, in PM10 Ca has a stronger relative weight within the crustal load in Tarragona than in Barcelona, even though it is dominant at both sites (38% in Barcelona, 55% in Tarragona). Road traffic emissions are the main cause of the higher relative weight of Fe in Barcelona (traffic site, 20%) than in Tarragona (urban background, 12%), and the results obtained for K are the same at both sites (9%). As regards PM2.5, at both sites the fine fraction is enriched in Fe and K with respect to PM10 (22% and 19% respectively in Barcelona, 15% and 22% in Tarragona) and depleted in Ca (30% in Barcelona, 44% in Tarragona). Al2O3 also shows a decrease in PM2.5 at both sites (29% in Barcelona, 19% in Tarragona), although it is not as marked as in the case of Ca. The coarser Ca particles are originated from pavement abrasion and road dust re-suspension, whereas the Fe and K particles result from finer grain size sources such as brake lining abrasion. These results coincide with CE (2004), where it is stated that PM10 particles are mainly produced by pavement abrasion whereas when automobile parts such as brake lining are worn out, finer grain size particles (PM2.5) are produced.
5. Conclusions The main objective of the present study is to identify the chemical profiles of PM10 and PM2.5 episodes in the
industrialised urban areas of North-Eastern Spain. To this end, a cluster analysis was performed on PM10 and PM2.5 samples. The differentiation between clusters in Tarragona was relatively more complicated than in Barcelona due to the high industrial background in this city, which results in high SIA levels during all episodes. Thus, the variations of the levels of OM + EC and gaseous pollutants (NO, SO2) played a key role in the identification of traffic and T + I episodes. • Traffic episodes are characterised by mean daily values of 22.7 lg/m3 of OM + EC in Barcelona and 14.2 lg/m3 of OM + EC in Tarragona in PM10. Good tracers of traffic emissions are Cu, Zn, Sb and Pb as a result of exhaust emissions and break lining abrasion. • During industrial episodes the composition of the PM10 mass is determined by the secondary inorganic aerosols (SIA), as they add up to daily mean levels of 18.6 lg/m3 in Barcelona and 10.9 lg/m3 in Tarragona. Due to the fact that the main industrial activities at both sites are power generation by fuel-oil and oil transformation (in Tarragona), the levels of Ni and V are good tracers of industrial emissions. • Regional re-circulation episodes, typical of the Western Mediterranean (Milla´n et al., 1997; Rodrı´guez et al., 2002), are characterised by high levels of O3 and SIA, especially sulphates (5.3 lg/m3 in Barcelona, 5.7 lg/m3 in Tarragona) as a consequence of the enhanced photochemistry of the aged air masses. • Crustal episodes are only identified at the Barcelona site, as they mainly represent the influence from different anthropogenic sources (construction, demolition, re-suspension from a nearby park) and sporadically African dust contributions. The composition of this
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mineral dust (Al2O3/Ca = 1.5) differs clearly from that of city road dust (Al2O3/Ca = 0.6). • T + I episodes are only observed in Tarragona, and represent peak PM episodes registered under strong anticyclonic conditions. The chemical profile of these episodes is characterised by high levels of OM + EC (14.2 lg/m3), SIA (10.4 lg/m3) and gaseous pollutants (136 lgNO/m3, 8 lgSO2/m3). The composition of the mineral load in PM10 varies as a function of the PM episodes. On average, Ca has a stronger relative weight in Tarragona than in Barcelona, even though it is dominant at both sites (38% of P (Al2O3, Ca, Fe, K) in Barcelona, 55% in Tarragona). Road traffic emissions are the main cause of the higher relative weight of Fe in Barcelona (traffic site, 20%) than in Tarragona (urban background, 12%). At both sites the fine fraction is enriched in Fe and K with respect to PM10 and depleted in Ca and Al2O3 as the Fe and K particles result from finer grain size sources such as brake lining abrasion. The coarser Ca particles are originated from pavement abrasion and road dust resuspension.
Acknowledgements The authors would like to thank the Spanish Ministries of Education and Science and Technology (CGL2004-05984-C07-02/CLI) and the Autonomous Government of Catalonia for their funding. The data on gaseous pollutants were kindly provided by the Environmental Department of the Autonomous Government of Catalonia. The authors would like to acknowledge Ferra´n Clua and Joan Miro´ for performing the Tarragona sampling.
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