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Influence of African dust on the levels of atmospheric particulates in the Canary Islands air quality network
Atmospheric Environment 36 (2002) 5861–5875
Influence of African dust on the levels of atmospheric particulates in the Canary Islands air quality network M. Vianaa,*, X. Querola, A. Alastueya, E. Cuevasb, S. Rodr!ıgueza a b
Institute of Earth Sciences ‘‘Jaume Almera’’, CSIC, Lluis Sol!e i Sabar!ıs s/n, 08028 Barcelona, Spain Observatorio Atmosf!erico de Izana, * INM, C/ La Marina, 20, 6a Planta, 38001, S/C de Tenerife, Spain Received 25 March 2002; received in revised form 28 May 2002; accepted 26 June 2002
Abstract Time series of levels of atmospheric particulate matter (TSP and PM10) were studied at 19 air quality monitoring stations in the islands of Tenerife and Gran Canaria (Canary Islands) during the period 1998–2000. After analysing seasonal variations, attention was focused on the detection of high TSP and PM10 events and on the identification of their natural or anthropogenic origins. Back-trajectory analysis and TOMS-NASA aerosol index as well as satellite imagery (SeaWIFS-NASA) were used to identify three types of African dust outbreaks differing in seasonal occurrence, source origin and impact on TSP/PM10 levels. Mean annual and daily TSP and PM10 levels were compared with the forthcoming limit values of the EU Air Quality Directive EC/30/1999, and the results showed that the annual and daily limit values established for 2010 would only be met at rural stations. PM levels at urban background, urban and industrial sites would exceed the 2010 objectives. Only the levels at the urban-background stations would meet the requirements for 2005 despite the fact that the trade winds result in lower levels of atmospheric pollutants in the Canary Islands than in continental environments. The results highlight the role of African dust contributions when implementing the limit values of the EU directive. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: PM10; TSP; Saharan dust; Air quality monitoring; Canary Islands
1. Introduction Investigations on atmospheric aerosols and their role in global climate, atmospheric chemistry and human health have recently become a primary topic in air pollution research. A number of studies (Schwartz et al., 1996; Dockery and Pope, 1996) have demonstrated the impact of atmospheric particulate matter (PM) on human health, in particular that of thoracic (PM10) and alveolar (PM2.5) particles. As regards climate change and visibility, light extinction has been found to depend on the cross-section, extinction efficiency and size distribution of particles (M!esz!aros, 1999). Furthermore, PM is responsible for the cooling of the atmo-
*Corresponding author. E-mail address: [email protected] (M. Viana).
sphere by energy loss, estimated by Coakley et al. (1983) as a direct global cooling of 2–3 K. In the light of these studies, the European Commission has established PM10 limit values for PM monitoring in the new air quality directive (EC/30/ 1999). This directive will be implemented in two phases (years 2005 and 2010), at the end of which annual PM10 limit values will be 40 and 20 mg/m3, respectively. A daily limit value of 50 mg PM10/m3 has also been established, which may only be exceeded 35 days/year in 2005 and 7 days/year in 2010. In order to focus on emissions strictly related to anthropogenic activity, the directive specifies that these limits are not to be applied to events defined as natural (volcanic eruptions, geothermal and seismic activities, resuspension of particles, long range transport from arid zones, etc.). One of the most characteristic sources of natural PM affecting Southern Europe is the dust transported from
1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 4 6 3 - 6
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M. Viana et al. / Atmospheric Environment 36 (2002) 5861–5875
North Africa (Sahara and Sahel deserts, Carlson and Prospero, 1972; Bergametti et al., 1989a; Chester et al., 1993; Chiapello et al., 1995; Querol et al., 1998; Rodr!ıguez et al., 2001). The dry climate and the scarcity of precipitation in the Mediterranean basin favour a long residence time of PM in the atmosphere with the consequent impact on the air quality. This source is far less significant in the Northern latitudes owing to the increasing distance and the characteristic meteorology of these areas. The opposite situation is observed in the Canary Islands, as the proximity to the African coast and the regional atmospheric circulation result in an ideal scenario for the transport of African dust towards the islands. However, although studies have been published on the atmospheric scenarios giving rise to these events of African dust outbreaks (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Rodr!ıguez and Guerra, 2001; Torres et al., 2001), there is little information on the impact of these natural PM contributions on ambient PM10 levels registered by the Canary Air Quality Monitoring Network. The present study aims to explore this subject by accomplishing the following tasks: *
*
*
Study and interpretation of time series of TSP and PM10 for selected air quality monitoring stations during the period 1998–2000. Characterisation of Saharan dust intrusions over the Canary Islands and evaluation of their impact on PM time series. Comparison of PM levels with the annual and daily limit values established by the EU directive EC/30/ 1999 for 2005 and 2010.
1.1. The study area The Canary Islands constitute one of the 17 autonomous regions of Spain and are located off the Western
coast of Morocco, at approximately 100 km from the coastline (Fig. 1). Major urban and industrial development is centred on the Tenerife and Gran Canaria islands, and it is consequently these islands that host the Air Quality Monitoring Network (CAC, 1999). The meteorology of the area is highly influenced by the North Atlantic anticyclone, which varies in strength and position throughout the year. Meteorological scenarios favouring the transport of North African dust have already been thoroughly studied by a number of authors (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Torres et al., 2001). The low troposphere over the Canary islands is strongly stratified. Quasi-permanent subsidence conditions in the free troposphere together with frequent trade winds flow in the lowest troposphere result in a strong and stable temperature inversion (located at 1400 m a.s.l. in average) that separates a dry free troposphere from a relatively fresh and humid oceanic boundary layer. The thickness and the temperature gradient of the inversion layer reach a maximum in summer (July–August), when this layer is located at 800 m a.s.l, attaining an average thickness of 500 m and an average temperature gradient of 51C (Rodr!ıguez, 1999; Torres et al., 2001). The predominance of the trade winds (NE) in the oceanic boundary layer plays a key role in the atmospheric dynamics of the islands as it favours the dispersion of pollutants from urban and industrial sites over the ocean. Consequently, the levels of atmospheric pollutants in the Canary Islands are often lower than those in regions with a similar urban and industrial development in continental environments (Rodr!ıguez and Guerra, 2001). Taking into account all the above considerations, the composition of atmospheric aerosols in the study area could vary as a function of local anthropogenic emissions, trade winds intensity, Saharan dust contributions and, in a minor proportion, sea spray.
Fig. 1. Location of the study area and monitoring stations.
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1998). Fig. 2A and 2B show two examples of peak PM events. In Fig. 2A, TSP levels describe marked anthropogenic cycles with peaks (75 mg TSP/m3) during the week days and lows (40 mg TSP/m3) at the weekends. These cycles are easily identified at heavy traffic and ! industrial sites (such as Mesa y Lopez and Ne! stor ! Alamo), but not at urban-background and rural stations where TSP levels remain relatively constant below 25 mg TSP/m3. The correlation with levels of gaseous pollutants simultaneously recorded at the monitoring stations (NOx, SO2, O3, CO) helped the identification of these anthropogenic episodes. Conversely, in Fig. 2B, PM levels recorded at all stations increased simultaneously during an African dust outbreak, reaching daily means of 400 mg TSP/m3. During African episodes, dust contributions overcome the local emission scenarios with the result that similar PM levels are recorded at industrial, urban and rural sites. During these events, much higher PM levels are reached when compared with anthropogenic PM peaks, and may also last for longer periods, reaching up to 20– 25 days. The use of aerosol maps, images and backtrajectory analysis mentioned above is especially useful in the identification of natural events, and only the combination of all the four tools enables us to describe these events with precision. Attention was then focused on the specific days when the forthcoming EU daily limit value (50 mg PM10/m3) was exceeded and on the cause of the exceedances. Given that the majority of the stations measured PM as TSP, the PM10 fraction was assumed to constitute approximately 70% of TSP (Barrero, 2001; Querol et al., 2001). Finally, the results were compared with the limit values established by the EU directive and the number of the exceedances as well as the proportion of these due to African natural contributions was evaluated.
2. Methodology In order to study the time series of levels of PM10 and TSP for 1998–2000, 19 sampling stations were selected from the Gran Canaria and Tenerife Air Quality Monitoring Networks. Preliminary comparisons between the time series resulted in a final selection of 10 sites (five from Gran Canaria, five from Tenerife, see Table 1 and Fig. 1). Selection criteria were based on data availability, geographical location and degree of pollution and type of emission sources influencing the monitoring stations. Data availability before 1997 was too low to be included in the study. According to the averaged annual PM concentrations and emission sources in the area, the sampling stations were classified as rural, urban and industrial sites (Table 1). In the examples given in the present paper, stations of ! El R!ıo, Playa del Ingl!es, Mesa y Lopez and N!estor ! Alamo were selected to, respectively, represent the rural, urban background, heavy traffic and industrial environments. NCEP meteorological maps (Kalnay et al., 1996) were studied and back-trajectories were calculated daily with the HYSPLIT model (Draxler, 1995) in order to interpret the different source regions of the air masses reaching the study area. Isentropic back-trajectories were calculated at midday for five back day periods at 500, 1500 and 2500 m a.s.l., with a 6 h step for every day in 1998–2000. By means of the inter-correlation of time series of PM levels from the selected stations, peak and low PM events were identified and analysed in an attempt to determine their natural or anthropogenic origin. To this end, the back-trajectory interpretations were coupled with the information obtained from the evaluation of TOMS-NASA aerosol index maps (TOMS, http:// jwocky.gsfc.nasa.gov, Herman et al., 1997) and satellite imagery provided by NASA SeaWIFS project (http:// seawifs.gsfc.nasa.gov/SEAWIFS.html, McClain et al.,
Table 1 ! Monitoring stations selected for the study (T: heavy traffic; UB: urban background). Station Mesa y Lopez was relocated to Mercado Central in October 1999 No.
Name
1 1B 2 3 4 5 6 7 8 9 10
! Mesa y Lopez Mercado Central a ! N!estor Alamo Polideportivo T.C.a Gladiolosa Arinaga Sardina Playa del Ingl!es El M!edano Galletas El R!ıo
a
Location a
0
00
28108 04 N 281080 0600 N 281020 0000 N 281270 4900 N 281270 3700 N 271520 0700 N 271500 1200 N 271450 4000 N 281020 2000 N 281000 2500 N 281080 3500 N
PM measured as PM10 after July 1999.
0
00
15124 49 W 151250 5200 W 151240 2900 W 161150 3700 W 161160 0200 W 151230 1700 W 151270 4000 W 151340 0800 W 161320 2000 W 161390 2000 W 161390 2000 W
Type
Height (m)
PM measure
Urban/T Urban/UB Industrial Urban Urban Urban/UB Urban Urban/UB Urban Urban/UB Rural
14 20 48 68 95 190 190 17 5 3.5 500
Beta At.(TSP) Beta At.(PM10) Beta At.(TSP) Beta At.(TSP) Beta At.(TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP)
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M es a y López
Nés tor Á lam o
P l.Ingles
S ardina
Galletas
E l Rio
1 50
TSP (µg/m3)
1 25 1 00
W eek-end
W eek-end
W eek-end
75 50 25 0
(A)
1 0/01 /9 9
1 4/01 /9 9
1 8/01 /9 9
2 2/01 /9 9
2 6/01 /9 9
3 0/01 /9 9
TS P (µg/m 3 )
8 00 6 00
4 00 2 00 0
(B)
0 5/02 /9 8
1 2/02 /9 8
1 9/02 /9 8
2 6/02 /9 8
0 5/03 /9 8
Fig. 2. (A) Peak TSP events of anthropogenic origin as deduced from the difference in TSP levels recorded at background and urban/ industrial sites and from the weekly cycle of concentrations. (B) Peak TSP event of natural origin.
In order to quantify the mineral load in the bulk PM10 levels, eight 24 h PM10 samples were collected on 15 cm quartz fibre filters (QF20 Schleicher and Schuell) at the Mercado Central station during selected African dust events (winter: 10–11 February 2001; summer: 1–2 June 2001) and on days without significant atmospheric influence from Africa (26 February, 21 March, 17 May and 21 August 2001), by means of an Andersen Graseby PM10 high volume sampler (68 m3/h). PM10 samples were analysed for major and trace elements according to the procedure described in Querol et al. (2001).
3. Results and discussion 3.1. TSP and PM10 levels and EU standards Mean annual PM10 and TSP levels were obtained for the four types of emission scenarios identified: urbanindustrial, heavy traffic, urban background and rural (Table 2). The number of exceedances of the forthcoming EU daily limit value (n > 50 mg/m3) was also added and averaged for the study period (Table 3). The highest mean annual PM10 levels and number of exceedances of the forthcoming EU directive were measured at sites under a stronger anthropogenic
! influence (N!estor Alamo: 56 mg/m3, n ¼ 143; Mesa y ! Lopez: 46 mg/m3, n ¼ 88; Table 2), whereas minimum values for both parameters were registered at El R!ıo (16 mg/m3, n ¼ 17). Both PM10 levels and number of exceedances decrease progressively from industrial to rural stations, thereby implying a strong dependence on anthropogenic emissions. Mean annual PM10 levels may be classified into four categories: o20 mg PM10/m3 (rural); 20–30 mg PM10/m3 (urban background), 30–45 mg PM10/m3 (urban) and >50 mg PM10/m3 (urban-industrial). The number of yearly exceedances also range from 17 (rural), 24–30 (urban background), 30–90 (urban including heavy traffic) and over 90 (urban-industrial). In the light of these results, all of the stations would exceed the forthcoming EU daily and annual limit values for Phase II (year 2010, 20 mg PM10/m3, n ¼ 7), and only rural and urban-background stations would not exceed them in Phase I (year 2005, 40 mg PM10/m3, n ¼ 35). 3.2. Seasonal variation The seasonal variation of PM10 levels and n for 1998– 2000 presents a common pattern for all the stations (Fig. 3), which is defined by local emission cycles and the
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Table 2 Mean annual PM10 values (mg/m3) and number of annual exceedances of the EU daily limit value (LV, daily mean >50 mg PM10/m3) for the period 1998–2000 PM10 (mg/m3)
Industrial
Urban/T
Urban
Urban
Urban
Urban
UB
UB
UB
Rural
! N. Alamo
! M. y Lopez
Polidep.
Gladiolos
M!edano
Sardina
Arinaga
pl.Ingl!es
Galletas
El R!ıo
48 101 72 50 47 58 53 54 43 57 51 38
51 77 52 47 39 45 39 42 32 33 43 49
34 73 63 28 26 33 35 43 31 43 50 34
35 71 57 27 26 34 36 43 28 38 43 32
30 55 50 30 24 33 36 37 25 32 38 29
25 49 39 21 21 30 24 30 24 29 29 19
27 53 46 25 19 23 22 23 19 23 37 25
20 44 40 20 20 25 27 35 27 28 31 20
23 43 33 21 18 18 20 26 18 22 23 16
11 38 35 12 11 13 11 16 9 12 15 13
Annual mean
56
46
41
39
35
28
28
28
23
16
n>LV Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
7 14 17 11 10 16 15 17 6 12 12 6
12 11 14 13 5 9 2 5 3 1 6 7
4 11 12 3 0 3 3 9 3 6 8 4
4 10 11 2 1 3 5 7 1 5 6 3
4 10 9 3 1 4 4 5 0 4 5 3
4 7 7 1 0 1 0 3 1 3 3 1
4 8 8 0 0 1 0 1 0 1 4 2
2 6 5 0 1 1 1 5 2 2 4 2
4 7 6 0 0 1 0 1 0 1 3 1
1 6 6 0 0 0 0 2 0 1 1 0
143
88
66
58
52
31
29
31
24
17
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
Annual sum
UB: Urban background. T: heavy traffic.
Table 3 Averaged PM10 levels recorded for air mass source areas defined PM10 (mg/m3)
AN
ANW
AW
ASW
NAF
ME
EU
El Rio Galletas Arinaga Pl.Ingles Sardina Medano Gladiolos Polidep. M. y Lopez N. Alamo
10 19 14 21 22 28 26 27 35 45
9 17 20 21 21 26 24 26 35 40
9 18 20 19 19 25 25 26 39 42
14 19 43 34 34 31 36 41 50 64
34 38 49 42 46 57 64 72 65 77
14 24 24 24 30 36 39 41 40 53
17 26 28 29 29 39 34 36 44 55
AN: Nothern Atlantic; ANW: North Western Atlantic; AW: Western Atlantic; NAF: Northern Africa; ME: Mediterranean; EU: Europe.
overlap of these by Saharan/Sahelian dust contributions, local resuspension processes and sea spray input. The seasonal trend is characterised by three annual maxima: February–March, June–August and October– November. The maximal PM10 and n values are recorded in February–March, with the only exception ! of N!estor Alamo where the number of exceedances in this period is very similar to that of the summer months (Table 2). In the October–November maximum the only station which does not follow this seasonal trend is El R!ıo, scarcely affected by this increase owing to its location at 500 m a.s.l. As will be discussed, its location prevents this station from receiving the impact of low altitude Saharan dust outbreaks at the end of autumn. 3.3. Air mass source The back-trajectory analysis (Fig. 4) enabled us to conclude that the most frequent source area of the air
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Mes a y López
Nés tor Á lamo
A rinaga
PlIngles
Sardina
Polideportiv o
Gladiolos
El Médano
Galletas
El Río
120 PM10 (g/m3 )
100 80 60 40 20 0 Jan
Feb
Mar
A pr
May
Jun
Jul
A ug
Sep
Oc t
Nov
Dec
Jan
Feb
Mar
A pr
May
Jun
Jul
A ug
Sep
Oc t
Nov
Dec
n > 50 g/m3
20 15 10 5 0
Fig. 3. Monthly PM10 levels and number of exceedances of EU daily limit value (n) for the period 1998–2000.
mean PM10 levels obtained for North African air masses reached the highest mean values (34 mg PM10/ ! m3 in El R!ıo and 77 mg PM10/m3 in N!estor Alamo). Consequently, even though the occurrence of African air mass incursions over the Canary Islands is not the most frequent long-range transport scenario in the study area, it may be concluded that their impact on PM10 levels is the highest. Once again, an increase in the PM10 levels is observed for each source area from rural to industrial stations. Fig. 4. Distribution of source areas of air masses which reached the study area during the period 1998–2000.
3.4. Origin of exceedances of the EU daily limit value
masses reaching the Canary Islands was the Atlantic Ocean, especially the North and Northwest Atlantic (62% of the days studied). The next most frequent source area was the African continent (25%), and finally Europe and the Mediterranean basin only represent 13% of the days. Therefore, Atlantic air masses have the strongest influence on Canarian atmospheric dynamics. Mean PM10 concentrations for each source area were also determined. Table 3 shows how the lowest mean PM10 concentrations were recorded for days under the influence of Atlantic masses (El R!ıo: 9–10 mg PM10/m3; ! N!estor Alamo: 40–45 mg PM10/m3). Conversely, the
In order to identify the origin (natural or non-natural) of exceedances of the forthcoming EU daily limit values, exceedances classified as ‘‘natural’’ have been defined as those induced by African dust contributions. ‘‘Nonnatural’’ exceedances include mainly anthropogenic contributions although local dust resuspension, sea spray and long range transport from Europe and the Mediterranean basin are also considered. The number of natural exceedances is higher at urban and industrial stations than at urban background and rural sites. This is due to the addition of contributions from different sources, as the African dust load is added to the local background PM10 levels. Therefore, PM levels are
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situation would arise at urban-background stations for Phase I but not for Phase II given that the number of non-natural exceedances (n ¼ 10) would still surpass the EU limit for 2010 (Phase II, n ¼ 7). Heavy traffic and urban-industrial stations would not meet the requirements for any of the phases. The seasonal trend of the annual number of exceedances of the forthcoming EU daily limit value presents two clearly differentiated patterns for natural and nonnatural exceedances (Fig. 5). In the case of non-natural exceedances, there is no common seasonal pattern for the four emission scenarios studied. The different emission rates and sources and ventilation conditions at the four sites account for these differential seasonal patterns. Given that the occurrence of African dust episodes presents a marked seasonal trend, a common pattern of exceedances may be found regarding natural sources.
bound to exceed the limit value more often at urban and industrial sites (higher anthropogenic background levels) than at rural sites (low anthropogenic background levels). Mean annual exceedances range from 17 (El R!ıo) to ! 143 (Ne! stor Alamo), from which 4 to 87 are non-natural in origin and 13 to 56 caused by African dust contributions (Table 4). As the degree of anthropogenic influence decreases, so does the number of non-natural exceedances. Thus, at urban and industrial sites anthropogenic emissions may be considered to be the main contributor to the number of exceedances of the EU daily limit value, while at urban-background and rural stations North African contributions have a greater significance. At rural stations both requirements of the directive for Phases I (2005) and II (2010) would be met if natural exceedances were not taken into account. The same
Table 4 Interpretation of natural or non-natural origin of exceedances of the forthcoming EU daily limit value ! N. Alamo
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
! M. y Lopez Non-nat
3 4 7 10 6 13 13 13 5 6 5 2
4 10 10 1 4 3 2 4 1 6 7 4
7 5 9 11 3 7 2 2 3 0 0 3
5 6 5 2 2 2 0 3 0 1 6 4
1 5 4 2 0 2 2 7 2 2 2 0
3 6 8 1 0 1 1 2 1 5 6 4
0 5 3 1 1 2 4 3 0 1 2 0
4 5 8 1 0 1 1 4 1 4 4 3
1 4 3 2 0 3 3 4 0 1 2 1
3 6 5 1 0 1 1 2 0 3 3 2
87
56
52
36
29
37
23
36
25
27
Pl. Ingl!es Nat
Non-nat
Non-nat
Nat
Sardina Nat
Non-nat
Non-nat
M!edano
Nat
Non-nat
Nat
Gladiolos
Non-nat
Arinaga
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
Polideportivo
Nat
Galletas Nat
Non-nat
Non-nat
Nat
El R!ıo Nat
Non-nat
Nat
1 2 2 0 1 0 0 0 0 0 0 1
3 6 6 0 0 1 0 1 0 1 4 1
0 2 1 0 1 1 0 2 2 0 1 0
2 4 4 0 0 0 1 3 0 2 3 2
1 2 2 0 0 0 0 1 1 0 1 0
3 5 5 1 0 1 0 2 0 3 2 1
1 3 1 0 0 1 0 0 0 0 1 0
3 4 5 0 0 0 0 1 0 1 2 1
0 2 1 0 0 0 0 1 0 0 0 0
1 4 5 0 0 0 0 1 0 1 1 0
7
23
10
21
8
22
9
15
4
13
Nat: Natural origin; Non-nat: Non-natural origin.
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No. days PM10 > 50 g/m
3
12 12
NÉSTOR ÁLAMO
Non Nat (87)
3
MESA Y LÓPEZ
10
Nat (36)
8
Non Nat (52)
8 6
6
4
4
2
2 0
0 JAN
No. days PM10 > 50 g/m
Nat (56)
10
MAR
MAY
JUL
SEPT
NOV
12
JAN
MAR
MAY
JUL
SEPT
NOV
12 PLAYA DEL INGLÉS
EL RíO
10
10
Nat (21) Non Nat (10)
8 6
6
4
4
2
2
0
Nat (13)
8
Non Nat (4)
0 JAN
MAR
MAY
JUL
SEPT
NOV
JAN
MAR
MAY
JUL
SEPT
NOV
Fig. 5. Monthly natural and non-natural exceedances of the forthcoming EU daily limit value period 1998–2000.
This pattern is characterised by a strong February– March increase, followed by secondary maxima in June– August and in October–December. This seasonal trend coincides with the occurrence of Saharan/Sahelian dust outbreaks over the Canary Islands reported by Cuevas (1995), Bustos et al. (1998), Rodr!ıguez (1999), Torres et al. (2001). The impact of these episodes on PM10 levels, and their characterisation will be discussed below. 3.5. Sahara/Sahel dust contributions Earlier studies (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Torres et al., 2001) have described two main types of African dust outbreaks over the Canary Islands: low altitude atmospheric intrusions in winter and high altitude intrusions during summer. The study and interpretation of PM10 time series allow us to identify three scenarios where the influence of Saharan dust on ambient PM levels is observed on a regular basis over the years. These scenarios are consistent with the two types described by the aforementioned authors. 3.5.1. Winter (February–March) Sahelian events Sahel dust outbreaks in February–March are key factors when implementing the EU limit values owing to their high intensity. In these episodes, daily means of 600–700 mg PM10/m3 may be reached (Fig. 6). The frequency of these events ranges from 2 to 7 times per year, lasting from 2 to 22 days per episode. They are usually detected by all of the tools described above (TOMS, SeaWIFS, back-trajectories, Fig. 6), and their importance is such that in February and March 2000
more than 20 exceedances of the EU limit were registered at most stations. The meteorological scenario giving rise to winter episodes is characterised by the dominant presence of an anticyclone over North Africa, which shifts longitudinally and may be found off the Atlantic coast or in the proximity of the Mediterranean basin (Fig. 6). The dust from the Sahel desert is transported by anticyclonic circulations and the high dust concentrations may be registered up to the low troposphere (E2 km). However, certain unusual episodes have been described where the dust layer is limited to the lowest levels of the mixing layer and in these cases aerosol index maps (TOMS) do not register the intrusion (Herman et al., 1997). The African origin of these events may be demonstrated only by back-trajectory analysis and satellite imagery. 3.5.2. Summer (June–August) Saharan episodes The occurrence of these events is limited to the summer period (June–August), and is reflected in the PM10 time series as persistent high background PM10 levels. The incidence of these events on PM10 levels is especially evident at rural background sites, but it is also detectable at urban and industrial sites. An increase in background levels of 10–15 mg/m3 may persist from 15 to 30 days (Fig. 7), at the rate of 1 to 4 times per year. Consequently, summer intrusions may be clearly differentiated from winter episodes by their lower intensity (usually daily levels o75 mg PM10/m3) and frequency, but longer duration. During these events the North African anticyclone is relocated above 850 hPa (E1500 m a.s.l.) as a consequence of the thermal low which develops at surface
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Fig. 6. Example of a winter Sahelian dust outbreak (26 February–15 March 2000) on ambient PM10 levels in the Canary Islands (* measured as TSP). Satellite image (SeaWIFS) and aerosol index map (TOMS) corresponding to 26 February 2000, and backtrajectory analysis at 850 hPa. Dominant meteorological scenario during the winter Sahelian dust outbreaks, altitude of the 925 and 850 hPa pressure levels for 26 February 2000 at 12 h.
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Fig. 7. Example of a summer Saharan dust outbreak (March 2000–June 2000) on ambient PM10 levels in the Canary Islands (* measured as TSP). Meteorological scenario during the summer period over North Africa (surface temperature indicating thermal low and pressure at 700 hPa for 06 June 2000 at 12 h), and back-trajectory analysis for the same date, showing the African origin of air masses only above 850 hPa. Satellite image (SeaWIFS) and aerosol index map (TOMS).
M. Viana et al. / Atmospheric Environment 36 (2002) 5861–5875
level (Fig. 7). Thus, sea level back-trajectory analysis reflects only the influence of the trade winds, with no clear patterns of transport from Africa. Conversely, back-trajectories calculated at 2500 m a.s.l. show a defined African origin for the air masses (Fig. 7). These results agree with Torres et al. (2001), who affirm that in the summertime Saharan outbreaks never intrude the oceanic boundary layer but take place at higher levels. Because these episodes are relatively frequent, a semipermanent dust layer known as the Saharan Air Layer (Prospero and Carlson, 1981) is formed. This is clearly detected on TOMS maps and SeaWIFS images (Fig. 7). In addition to the continuous westward flow of dust, minor downward transport fluxes affect the underlying layer in a continuous and uniform manner. This vertical transport results in an increase in background PM10 levels during long periods (1–3 weeks) at all monitoring stations. 3.5.3. Autumn–winter events (October–November) These events occur mainly in October and November, and may be occasionally detected in December. Autumn intrusions are characterised by the shortest duration (2– 5 days), a frequency of 2–4 times per year and a strong intensity (daily PM levels up to 400–500 mg PM10/m3). This period is associated with a lack of relevant atmospheric processes which inject dust into the lower troposphere over the Sahara or Sahel deserts. However, given the proximity of the islands to the continent, local phenomena such as dust storms may influence the PM10 ambient levels. Thus, during October and November PM10 time series usually present certain abrupt peaks at all stations (Fig. 8). The detection of these episodes must be carried out by back-trajectory analysis and satellite imagery since TOMS aerosol maps do not detect low altitude dust storms (Herman et al., 1997) (Fig. 8). The characteristic meteorological scenario is once again dominated by the North African anticyclone, located at surface level during the winter period (Fig. 8). At this time of the year the surface of the Sahel desert is cooled owing to the lower ambient temperatures and the higher frequency of rain events with the result that dust injection processes are inhibited.
can dust outbreaks extremely high values of crustal components were determined. Winter levels of SiO2 and Al2O3 exceeded the levels reached without the influence of African dust by a factor of 46. This factor ranged from 14–25 for K, Ti, Ca, Fe, Mn, Mg and Ba. Summer levels of the same components were reduced compared with winter (only 1–2 times higher than levels without African dust contributions) owing to the minor intensity of events and the dilution induced in summer by vertical transport. The winter and summer ranges of concentrations of crustal components recorded are similar to those reported by Coud!e-Gaussen et al. (1987), Bergametti et al. (1989b), Prospero et al. (1995), Chiapello et al. (1997), and Tomza et al. (2001) for Saharan episodes. Fig. 9 shows the source contribution of the selected samples, where the predominance of the crustal fraction during African episodes is again evident (76–78% of bulk PM10 during winter, accounting for 129–191 mg/ m3, and 23–28% of PM10 in summer, accounting for 9– 12 mg/m3). Non-mineral carbon and secondary PM + (anthropogenic SO2 4 , NO3 and NH4 ) loads range 3 from 3–14% of PM10 (4–7 mg/m ) and 2–36% of PM10 (3–14 mg/m3), respectively. The marine load (Na, Cl and sea salt SO2 4 ) varies from 3–12% of PM10 (3–20 mg/ m3). Conversely, during days with no African dust contributions the crustal fraction accounts for a maximum of 26% of bulk PM10 (6–8 mg/m3), whereas nonmineral carbon ranges from 18–25% (5–9 mg/m3). The marine and secondary loads increase relatively (8–19% and 20–26%, respectively, accounting for 3–5 mg/m3 and 6–9 mg/m3).
4. Conclusions After the interpretation of the PM10 and TSP time series from nineteen stations belonging to two air quality monitoring networks in the Canary Islands during the period 1998–2000, the following conclusions may be drawn: *
3.6. Chemical characterisation The chemical composition of the eight PM10 samples collected during African episodes and during days without African dust influence is shown in Table 5. The chemical determinations accounted for 73–87% of bulk PM10 levels. Higher PM loads registered during African episodes with respect to non-African events are mainly due to the crustal load (Al2O3, SiO2, Ca, CO2 3 , Ti, Sr, K, Mg, Mn, Fe and P), and they are especially significant during winter episodes. During winter Afri-
5871
*
Three types of African dust contributions in the Canary Islands were identified and characterised. These episodes are dependent on the dominant meteorological scenarios at different times of the year, and have different impacts on PM time series. These events have been defined as winter, summer and autumn–winter dust outbreaks. These episodes are characterised by the daily PM values reached, duration and frequency (Table 6). The comparison of measured PM10 levels with the forthcoming limit values established by the EU directive EC/30/1999 reveals that only the rural station (El R!ıo) would meet the requirements for Phase II (2010), which would be clearly exceeded at urban background, urban and industrial sites even if
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Fig. 8. Example of two autumn–winter Saharan intrusions (November 1999) on ambient PM10 levels in the Canary Islands (*PM measured as TSP). Back-trajectory analysis, NASA-SeaWIFS image and TOMS map for 24 November 1999, and altitude of the 925 and 850 hPa pressure levels for 24 November 1999 at 12 h.
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Table 5 Chemical characterisation of five samples collected under African (February and June samples) and non-African (March, May and August samples) transport scenarios
PM10 Ctotal Corg
Sahara Feb.-01
Sahara Feb.-01
Sahel Jun.-01
Sahel Jun.-01
Non-Afr. Feb.-01
Non-Afr. Mar.-01
Non-Afr. May-01
Non-Afr. ago-01
244 14 7
169 11 7
43 6 6
38 5 4
36 9 9
30 6 5
31 7 7
26 7 7
CO2 3 SiO2 Al2O3 Ca K Na Mg Fe P SO2 4-anthrop:
35 82 27 15 4 6 5 8 0.5 6
19 60 20 8 3 4 3 5 0.1 3
3 5 1.5 1.0 0.4 2 0.4 0.7 0.02 10
2.0 3.2 1.1 0.6 0.3 3 0.4 0.5 0.02 9
2.0 2.8 0.9 0.7 0.3 1.9 0.4 0.6 0.0 3
1.9 1.8 0.6 0.8 0.2 1.7 0.3 0.4 0.0 2
2.0 1.9 0.6 0.9 0.2 1.6 0.3 0.4 0.0 4
2.0 2.0 0.7 0.7 0.2 2.6 0.4 0.4 0.0 3
SO2 4-marine NO 3 Cl NH+ 4
1.6 1.4 12 1.0
1.0 0.9 7.6 0.6
0.5 1.6 0.6 2
0.6 1.5 1.5 3
0.5 4.6 0.7 1.5
0.4 1.9 1.9 1.7
0.4 2.1 1.4 1.4
0.7 2.5 1.7 0.8
Mn Ti V Ba Pb
123 700 39 108 51
98 511 29 73 38
10 45 5 15 7
7 29 4 8 5
9 42 17 15 71
7 33 19 8 21
7 33 3 10 8
9 38 9 12 2
Total PM10 %
213 244 87
123 169 73
34 43 79
31 38 81
29 36 81
22 30 72
24 31 77
25 26 96
All concentrations in mg/m3 except for Mn, Ti, V, Ba and Pb (ng/m3).
Fig. 9. Source contribution of 8 samples analysed. N.A.(W): no African dust influence, winter. N.A.(S): no African dust influence, summer.
exceedances caused by African dust contributions are excluded (Table 7). The mean annual PM10 value and the mean number of exceedances of the daily limit value for 1998–2000 recorded at El R!ıo (16 mg/ m3, n ¼ 4) are very close to the limit values
established for 2010 (20 mg/m3, n ¼ 7) with the result that the values recorded at the remaining stations exceed the final objectives of the directive for 2010. It should be borne in mind that the rural station (El R!ıo), owing to its location at 500 m a.s.l., is often
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Table 6 Main characteristics of the North African dust outbreaks studied Dates
Winter Summer Autumn– winter
Feb.–Mar. Jun.–Aug. Oct.–Dec.
Max. daily PM10 (mg/m3)
Duration (days)
o700 o75 o400
2–22 15–30 2–5
Frequency (times/yr)
Acknowledgements 2–7 1–4 2–4
Table 7 Evaluation of the accomplishment of the requirements established by the EU directive regarding the daily and annual limit values, excluding natural exceedances of the daily limit value Phase I (2005)
Rural Urban background Urban and Industrial
*
*
*
3–14% and (b) SiO2, Al2O3, Ca, K, Fe, Ti, V, Mn and Ba concentrations are excellent tracers of African origin.
Phase II (2010)
Annual limit value
Daily limit value
Annual limit value
Daily limit value
Yes Yes No
Yes Yes No
Yes No No
Yes No No
above the marine boundary layer and therefore outside the direct influence of anthropogenic emission sources. The anthropogenic PM levels in the Canary Islands should be lower than those in continental environments in the EU given that the atmospheric dynamics of the islands favour the dispersion of pollutants over the ocean. As regards the limit values established for 2005 (Phase I, 40 mg/m3, n ¼ 35), they would only be exceeded at industrial and heavy traffic sites (Table 7). At these sites, more than 50 exceedances of the daily limit value are recorded. The number of exceedances of the daily limit value due to Saharan/Sahelian dust contributions is only decisive at rural stations when considering the 2010 EU requirements given that 76% of the exceedances registered at these sites have a natural origin. Sixtyeight percent of the exceedances may be considered natural at urban-background stations and approximately 40% at urban and industrial sites. The chemical analysis of samples collected with and without African dust influence proved that: (a) for the intensive winter African dust outbreaks (daily PM10 levels up to 191 mg/m3) at least 76% of the bulk PM10 levels may be attributable to dust load, whereas the anthropogenic input accounts for only
! InterminisThis study was financed by the Comision terial de Ciencia y Tecnolog!ıa (REN2001-0659-C03-03) and by the Spanish Ministry of the Environment. The authors would like to thank the Autonomous Govern! General de Salud ment of the Canary Islands (Direccion ! General de Industria y Energ!ıa) ! Publica and Direccion for their cooperation providing PM10 and TSP time series, NASA/Goddard Space Flight Center, NOAAARL and SeaWIFS-NASA Project for their contribution with TOMS, HYSPLIT model and meteorological database and satellite images, respectively. Meteorological analysis was provided by the NOAA-CIRES Climate Diagnostics Center Boulder Colorado from their Web site at http://www.cdc.noaa.gov/.
References Barrero, M.A., 2001. Estudio de la composici!on org!anica natural y contaminante de los aerosoles urbanos y su variabilidad temporal. Tesis Doctoral, Universidad Pa!ıs Vasco, Departamento Qu!ımica Aplicada, SanSebasti!an. 255pp. Bergametti, G., Dutot, A.L., Buat-Menard, P., Losno, R., Remoudaki, E., 1989a. Seasonal variability of the elemental composition of atmospheric aerosol particles over the NW Mediterranean. Tellus 41B, 353–361. Bergametti, G., Gomes, L., Coud!e-Gaussen, G., Rognon, P., Le Coustumer, M.N., 1989b. African dust observed over Canary Islands: source regions identification and transport pattern for some summer situation. Journal of Geophysical Research 94, 14855–14864. Bustos, J.J., Cuevas, E., Marrero, C., Alonso, S., 1998. ! de las masas de aire en la troposfera libre Caracterizacion y en la capa de mezcla en Canarias. In: Proceedings of the IX Asamblea Geodesia y Geof!ısica, Aguadulce (Almer!ıa), pp. 9–13. CAC, 1999. Calidad del Aire en Canarias: 1992–1998. Direcci! General de Salud Publica, ! on Gobierno de Canarias. Carlson, T.N., Prospero, J.M., 1972. The large scale movement of Saharan air outbreaks over the northern equatorial Atlantic. Journal of Applied Meteorology 11, 283–297. Chester, R., Nimmo, M., Alarc!on, M., Saydam, C., Murphy, K.J.T., Sanders, G.S., Corcoran, P., 1993. Defining the chemical character of aerosols from the atmosphere in the Mediterranean sea and surrounding regions. Oceanographica Acta 16, 231–246. Chiapello, I., Bergametti, G., Gomes, L., Chatenet, B., 1995. An additional low layer transport of Sahelian and Saharan dust over the North-Eastern Tropical Atlantic. Geophysical Research Letters 22 (23), 3191–3194.
M. Viana et al. / Atmospheric Environment 36 (2002) 5861–5875 Chiapello, I., Bergametti, G., Chatenet, B., 1997. Origins of African dust transported over the northeastern tropical Atlantic. Journal of Geophysical Research 102 (D12), 13701–13709. Coakley Jr., J.A, Cess, R.L., Yurevich, F.B., 1983. The effects of tropospheric aerosol on the Earth’s radiation budget. A paremetrization for climate models. Journal of Aerosol Science 40, 116–138. Coud!e-Gaussen, G., Rognon, P., Bergametti, G., Gomes, L., Strauss, B., Gros, J.M., Le Coustumer, M.N., 1987. Saharan dust over Fuerteventura Island (Canaries), Chemical and mineralogical characteristics, air mass trajectories and probable sources. Journal of Geophysical Research 92, 9753–9811. Cuevas, E., 1995. Estudio del Comportamiento del Ozono * (Tenerife) y su Troposf!erico en el Observatorio de Izana ! con la Din!amica Atmosf!erica, Ph.D. Thesis, Relacion Facultad de Ciencias F!ısicas, Universidad Complutense de Madrid, available on CD under request, ISBAN 84-6690399-2, 1995. Dockery, D., Pope, A., 1996. Epidemiology of acute health effects: summary of time-series studied. In: Wilson, R., Spengler, J.D. (Eds.), Particles in Our Air: Concentration and Health Effects. Harvard University Press, Cambridge MA, USA, pp. 123–147. Draxler, R.R., 1995. Hybrid Single-Particle Lagrangian Integrated Trajectories, Version 3.2, NOAA-ARL. Herman, J.R., Bhartia, P.K., Torres, O., Hsu, C., Seftor, C., Celarier, E., 1997. Global distribution of UV-absorbing aerosols from Nimbus7/TOMS data. Journal of Geophysical Research 201, 16911–16922. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., Joseph, D., 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorlogical Society 77, 437–471. McClain, C.R., Cleave, M.L., Feldman, G.C., Gregg, W.W., Hooker, S.B., Kuring, N., 1998. Science Quality SeaWiFS data for global biosphere research. Sea Technology 39 (9), 10–15. M!esz!aros, E., 1999. Fundamentals of Atmospheric Aerosol Chemistry. Akad!emiai Kiado, Budapest.
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Prospero, J.M., Carlson, T.N., 1980/1981. Saharan air outbreaks over the tropical North Atlantic. Pure and Applied Physics 119, 667–691. Prospero, J.M., Schmitt, R., Cuevas, E., Savoie, D.L., Graustein, W.C., Turekian, K.K., Volz-Thomas, A., D!ıaz, A., Oltmans, S.J., Levy II, H., 1995. Temporal variability of summer-time ozone and aerosols in the free troposphere over the eastern North Atlantic. Geophysical Research Letters 22 (21), 2925–2928. ! Querol, X., Alastuey, A., Puicercus, J.A., Mantilla, E., Miro, ! * J.V., Lopez-Soler, A., Plana, F., Art!ınano, B., 1998. Seasonal evolution of suspended particles around a large coal-fired power station: particle levels and sources. Atmospheric Environment 32, 1963–1978. Querol, X., Alastuey, A., Rodr!ıguez, S., Plana, F., Ruiz, C.R., Cots, N., Massagu!e, G., Puig, O., 2001. PM10 and PM2.5 source apportionment in the Barcelona Metropolitan Area, Catalonia, Spain. Atmospheric Environment 35, 6407–6419. ! de la variaciones de ozono Rodr!ıguez, S., 1999. Comparacion superficial asociadas a procesos de transporte sobre y bajo ! temperatura subtropical en Tenerife. Tesis la inversion de Licenciatura, Universidad de La Laguna, Tenerife, Canarias. Rodr!ıguez, S., Guerra, J.C., 2001. Monitoring of ozone in a marine environment in Tenerife (Canary Islands). Atmospheric Environment 35, 1829–1841. Rodr!ıguez, S., Querol, X., Alastuey, A., Kallos, G., Kakaliagou, O., 2001. Saharan dust contributions to PM10 and TSP levels in Southern and E. Spain. Atmospheric Environment 35, 2433–2447. Schwartz, J., Dochery, D.W., Neas, L.M., 1996. Is daily mortality associated specifically with fine particles? Journal of Air and Waste Management Association 46, 927–939. Tomza, U., Arimoto, R., Ray, B.J., 2001. Color-related differences in the chemical composition of aerosol-laden filters. Atmospheric Environment 35, 1703–1709. * Torres, C.J., Cuevas, E., Guerra, J.C., Carreno, V., 2001. ! de las Masas de Aire en la Region ! Caracterizacion Subtropical. In: Proceedings of the V Simposio Nacional ! de Prediccion; available on CD under request, ISBN 84-8320-192-5, Instituto Nacional de Meteorolog!ıa, Madrid.
Influence of African dust on the levels of atmospheric particulates in the Canary Islands air quality network M. Vianaa,*, X. Querola, A. Alastueya, E. Cuevasb, S. Rodr!ıgueza a b
Institute of Earth Sciences ‘‘Jaume Almera’’, CSIC, Lluis Sol!e i Sabar!ıs s/n, 08028 Barcelona, Spain Observatorio Atmosf!erico de Izana, * INM, C/ La Marina, 20, 6a Planta, 38001, S/C de Tenerife, Spain Received 25 March 2002; received in revised form 28 May 2002; accepted 26 June 2002
Abstract Time series of levels of atmospheric particulate matter (TSP and PM10) were studied at 19 air quality monitoring stations in the islands of Tenerife and Gran Canaria (Canary Islands) during the period 1998–2000. After analysing seasonal variations, attention was focused on the detection of high TSP and PM10 events and on the identification of their natural or anthropogenic origins. Back-trajectory analysis and TOMS-NASA aerosol index as well as satellite imagery (SeaWIFS-NASA) were used to identify three types of African dust outbreaks differing in seasonal occurrence, source origin and impact on TSP/PM10 levels. Mean annual and daily TSP and PM10 levels were compared with the forthcoming limit values of the EU Air Quality Directive EC/30/1999, and the results showed that the annual and daily limit values established for 2010 would only be met at rural stations. PM levels at urban background, urban and industrial sites would exceed the 2010 objectives. Only the levels at the urban-background stations would meet the requirements for 2005 despite the fact that the trade winds result in lower levels of atmospheric pollutants in the Canary Islands than in continental environments. The results highlight the role of African dust contributions when implementing the limit values of the EU directive. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: PM10; TSP; Saharan dust; Air quality monitoring; Canary Islands
1. Introduction Investigations on atmospheric aerosols and their role in global climate, atmospheric chemistry and human health have recently become a primary topic in air pollution research. A number of studies (Schwartz et al., 1996; Dockery and Pope, 1996) have demonstrated the impact of atmospheric particulate matter (PM) on human health, in particular that of thoracic (PM10) and alveolar (PM2.5) particles. As regards climate change and visibility, light extinction has been found to depend on the cross-section, extinction efficiency and size distribution of particles (M!esz!aros, 1999). Furthermore, PM is responsible for the cooling of the atmo-
*Corresponding author. E-mail address: [email protected] (M. Viana).
sphere by energy loss, estimated by Coakley et al. (1983) as a direct global cooling of 2–3 K. In the light of these studies, the European Commission has established PM10 limit values for PM monitoring in the new air quality directive (EC/30/ 1999). This directive will be implemented in two phases (years 2005 and 2010), at the end of which annual PM10 limit values will be 40 and 20 mg/m3, respectively. A daily limit value of 50 mg PM10/m3 has also been established, which may only be exceeded 35 days/year in 2005 and 7 days/year in 2010. In order to focus on emissions strictly related to anthropogenic activity, the directive specifies that these limits are not to be applied to events defined as natural (volcanic eruptions, geothermal and seismic activities, resuspension of particles, long range transport from arid zones, etc.). One of the most characteristic sources of natural PM affecting Southern Europe is the dust transported from
1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 4 6 3 - 6
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North Africa (Sahara and Sahel deserts, Carlson and Prospero, 1972; Bergametti et al., 1989a; Chester et al., 1993; Chiapello et al., 1995; Querol et al., 1998; Rodr!ıguez et al., 2001). The dry climate and the scarcity of precipitation in the Mediterranean basin favour a long residence time of PM in the atmosphere with the consequent impact on the air quality. This source is far less significant in the Northern latitudes owing to the increasing distance and the characteristic meteorology of these areas. The opposite situation is observed in the Canary Islands, as the proximity to the African coast and the regional atmospheric circulation result in an ideal scenario for the transport of African dust towards the islands. However, although studies have been published on the atmospheric scenarios giving rise to these events of African dust outbreaks (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Rodr!ıguez and Guerra, 2001; Torres et al., 2001), there is little information on the impact of these natural PM contributions on ambient PM10 levels registered by the Canary Air Quality Monitoring Network. The present study aims to explore this subject by accomplishing the following tasks: *
*
*
Study and interpretation of time series of TSP and PM10 for selected air quality monitoring stations during the period 1998–2000. Characterisation of Saharan dust intrusions over the Canary Islands and evaluation of their impact on PM time series. Comparison of PM levels with the annual and daily limit values established by the EU directive EC/30/ 1999 for 2005 and 2010.
1.1. The study area The Canary Islands constitute one of the 17 autonomous regions of Spain and are located off the Western
coast of Morocco, at approximately 100 km from the coastline (Fig. 1). Major urban and industrial development is centred on the Tenerife and Gran Canaria islands, and it is consequently these islands that host the Air Quality Monitoring Network (CAC, 1999). The meteorology of the area is highly influenced by the North Atlantic anticyclone, which varies in strength and position throughout the year. Meteorological scenarios favouring the transport of North African dust have already been thoroughly studied by a number of authors (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Torres et al., 2001). The low troposphere over the Canary islands is strongly stratified. Quasi-permanent subsidence conditions in the free troposphere together with frequent trade winds flow in the lowest troposphere result in a strong and stable temperature inversion (located at 1400 m a.s.l. in average) that separates a dry free troposphere from a relatively fresh and humid oceanic boundary layer. The thickness and the temperature gradient of the inversion layer reach a maximum in summer (July–August), when this layer is located at 800 m a.s.l, attaining an average thickness of 500 m and an average temperature gradient of 51C (Rodr!ıguez, 1999; Torres et al., 2001). The predominance of the trade winds (NE) in the oceanic boundary layer plays a key role in the atmospheric dynamics of the islands as it favours the dispersion of pollutants from urban and industrial sites over the ocean. Consequently, the levels of atmospheric pollutants in the Canary Islands are often lower than those in regions with a similar urban and industrial development in continental environments (Rodr!ıguez and Guerra, 2001). Taking into account all the above considerations, the composition of atmospheric aerosols in the study area could vary as a function of local anthropogenic emissions, trade winds intensity, Saharan dust contributions and, in a minor proportion, sea spray.
Fig. 1. Location of the study area and monitoring stations.
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5863
1998). Fig. 2A and 2B show two examples of peak PM events. In Fig. 2A, TSP levels describe marked anthropogenic cycles with peaks (75 mg TSP/m3) during the week days and lows (40 mg TSP/m3) at the weekends. These cycles are easily identified at heavy traffic and ! industrial sites (such as Mesa y Lopez and Ne! stor ! Alamo), but not at urban-background and rural stations where TSP levels remain relatively constant below 25 mg TSP/m3. The correlation with levels of gaseous pollutants simultaneously recorded at the monitoring stations (NOx, SO2, O3, CO) helped the identification of these anthropogenic episodes. Conversely, in Fig. 2B, PM levels recorded at all stations increased simultaneously during an African dust outbreak, reaching daily means of 400 mg TSP/m3. During African episodes, dust contributions overcome the local emission scenarios with the result that similar PM levels are recorded at industrial, urban and rural sites. During these events, much higher PM levels are reached when compared with anthropogenic PM peaks, and may also last for longer periods, reaching up to 20– 25 days. The use of aerosol maps, images and backtrajectory analysis mentioned above is especially useful in the identification of natural events, and only the combination of all the four tools enables us to describe these events with precision. Attention was then focused on the specific days when the forthcoming EU daily limit value (50 mg PM10/m3) was exceeded and on the cause of the exceedances. Given that the majority of the stations measured PM as TSP, the PM10 fraction was assumed to constitute approximately 70% of TSP (Barrero, 2001; Querol et al., 2001). Finally, the results were compared with the limit values established by the EU directive and the number of the exceedances as well as the proportion of these due to African natural contributions was evaluated.
2. Methodology In order to study the time series of levels of PM10 and TSP for 1998–2000, 19 sampling stations were selected from the Gran Canaria and Tenerife Air Quality Monitoring Networks. Preliminary comparisons between the time series resulted in a final selection of 10 sites (five from Gran Canaria, five from Tenerife, see Table 1 and Fig. 1). Selection criteria were based on data availability, geographical location and degree of pollution and type of emission sources influencing the monitoring stations. Data availability before 1997 was too low to be included in the study. According to the averaged annual PM concentrations and emission sources in the area, the sampling stations were classified as rural, urban and industrial sites (Table 1). In the examples given in the present paper, stations of ! El R!ıo, Playa del Ingl!es, Mesa y Lopez and N!estor ! Alamo were selected to, respectively, represent the rural, urban background, heavy traffic and industrial environments. NCEP meteorological maps (Kalnay et al., 1996) were studied and back-trajectories were calculated daily with the HYSPLIT model (Draxler, 1995) in order to interpret the different source regions of the air masses reaching the study area. Isentropic back-trajectories were calculated at midday for five back day periods at 500, 1500 and 2500 m a.s.l., with a 6 h step for every day in 1998–2000. By means of the inter-correlation of time series of PM levels from the selected stations, peak and low PM events were identified and analysed in an attempt to determine their natural or anthropogenic origin. To this end, the back-trajectory interpretations were coupled with the information obtained from the evaluation of TOMS-NASA aerosol index maps (TOMS, http:// jwocky.gsfc.nasa.gov, Herman et al., 1997) and satellite imagery provided by NASA SeaWIFS project (http:// seawifs.gsfc.nasa.gov/SEAWIFS.html, McClain et al.,
Table 1 ! Monitoring stations selected for the study (T: heavy traffic; UB: urban background). Station Mesa y Lopez was relocated to Mercado Central in October 1999 No.
Name
1 1B 2 3 4 5 6 7 8 9 10
! Mesa y Lopez Mercado Central a ! N!estor Alamo Polideportivo T.C.a Gladiolosa Arinaga Sardina Playa del Ingl!es El M!edano Galletas El R!ıo
a
Location a
0
00
28108 04 N 281080 0600 N 281020 0000 N 281270 4900 N 281270 3700 N 271520 0700 N 271500 1200 N 271450 4000 N 281020 2000 N 281000 2500 N 281080 3500 N
PM measured as PM10 after July 1999.
0
00
15124 49 W 151250 5200 W 151240 2900 W 161150 3700 W 161160 0200 W 151230 1700 W 151270 4000 W 151340 0800 W 161320 2000 W 161390 2000 W 161390 2000 W
Type
Height (m)
PM measure
Urban/T Urban/UB Industrial Urban Urban Urban/UB Urban Urban/UB Urban Urban/UB Rural
14 20 48 68 95 190 190 17 5 3.5 500
Beta At.(TSP) Beta At.(PM10) Beta At.(TSP) Beta At.(TSP) Beta At.(TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP) TEOM (TSP)
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M es a y López
Nés tor Á lam o
P l.Ingles
S ardina
Galletas
E l Rio
1 50
TSP (µg/m3)
1 25 1 00
W eek-end
W eek-end
W eek-end
75 50 25 0
(A)
1 0/01 /9 9
1 4/01 /9 9
1 8/01 /9 9
2 2/01 /9 9
2 6/01 /9 9
3 0/01 /9 9
TS P (µg/m 3 )
8 00 6 00
4 00 2 00 0
(B)
0 5/02 /9 8
1 2/02 /9 8
1 9/02 /9 8
2 6/02 /9 8
0 5/03 /9 8
Fig. 2. (A) Peak TSP events of anthropogenic origin as deduced from the difference in TSP levels recorded at background and urban/ industrial sites and from the weekly cycle of concentrations. (B) Peak TSP event of natural origin.
In order to quantify the mineral load in the bulk PM10 levels, eight 24 h PM10 samples were collected on 15 cm quartz fibre filters (QF20 Schleicher and Schuell) at the Mercado Central station during selected African dust events (winter: 10–11 February 2001; summer: 1–2 June 2001) and on days without significant atmospheric influence from Africa (26 February, 21 March, 17 May and 21 August 2001), by means of an Andersen Graseby PM10 high volume sampler (68 m3/h). PM10 samples were analysed for major and trace elements according to the procedure described in Querol et al. (2001).
3. Results and discussion 3.1. TSP and PM10 levels and EU standards Mean annual PM10 and TSP levels were obtained for the four types of emission scenarios identified: urbanindustrial, heavy traffic, urban background and rural (Table 2). The number of exceedances of the forthcoming EU daily limit value (n > 50 mg/m3) was also added and averaged for the study period (Table 3). The highest mean annual PM10 levels and number of exceedances of the forthcoming EU directive were measured at sites under a stronger anthropogenic
! influence (N!estor Alamo: 56 mg/m3, n ¼ 143; Mesa y ! Lopez: 46 mg/m3, n ¼ 88; Table 2), whereas minimum values for both parameters were registered at El R!ıo (16 mg/m3, n ¼ 17). Both PM10 levels and number of exceedances decrease progressively from industrial to rural stations, thereby implying a strong dependence on anthropogenic emissions. Mean annual PM10 levels may be classified into four categories: o20 mg PM10/m3 (rural); 20–30 mg PM10/m3 (urban background), 30–45 mg PM10/m3 (urban) and >50 mg PM10/m3 (urban-industrial). The number of yearly exceedances also range from 17 (rural), 24–30 (urban background), 30–90 (urban including heavy traffic) and over 90 (urban-industrial). In the light of these results, all of the stations would exceed the forthcoming EU daily and annual limit values for Phase II (year 2010, 20 mg PM10/m3, n ¼ 7), and only rural and urban-background stations would not exceed them in Phase I (year 2005, 40 mg PM10/m3, n ¼ 35). 3.2. Seasonal variation The seasonal variation of PM10 levels and n for 1998– 2000 presents a common pattern for all the stations (Fig. 3), which is defined by local emission cycles and the
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Table 2 Mean annual PM10 values (mg/m3) and number of annual exceedances of the EU daily limit value (LV, daily mean >50 mg PM10/m3) for the period 1998–2000 PM10 (mg/m3)
Industrial
Urban/T
Urban
Urban
Urban
Urban
UB
UB
UB
Rural
! N. Alamo
! M. y Lopez
Polidep.
Gladiolos
M!edano
Sardina
Arinaga
pl.Ingl!es
Galletas
El R!ıo
48 101 72 50 47 58 53 54 43 57 51 38
51 77 52 47 39 45 39 42 32 33 43 49
34 73 63 28 26 33 35 43 31 43 50 34
35 71 57 27 26 34 36 43 28 38 43 32
30 55 50 30 24 33 36 37 25 32 38 29
25 49 39 21 21 30 24 30 24 29 29 19
27 53 46 25 19 23 22 23 19 23 37 25
20 44 40 20 20 25 27 35 27 28 31 20
23 43 33 21 18 18 20 26 18 22 23 16
11 38 35 12 11 13 11 16 9 12 15 13
Annual mean
56
46
41
39
35
28
28
28
23
16
n>LV Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
7 14 17 11 10 16 15 17 6 12 12 6
12 11 14 13 5 9 2 5 3 1 6 7
4 11 12 3 0 3 3 9 3 6 8 4
4 10 11 2 1 3 5 7 1 5 6 3
4 10 9 3 1 4 4 5 0 4 5 3
4 7 7 1 0 1 0 3 1 3 3 1
4 8 8 0 0 1 0 1 0 1 4 2
2 6 5 0 1 1 1 5 2 2 4 2
4 7 6 0 0 1 0 1 0 1 3 1
1 6 6 0 0 0 0 2 0 1 1 0
143
88
66
58
52
31
29
31
24
17
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
Annual sum
UB: Urban background. T: heavy traffic.
Table 3 Averaged PM10 levels recorded for air mass source areas defined PM10 (mg/m3)
AN
ANW
AW
ASW
NAF
ME
EU
El Rio Galletas Arinaga Pl.Ingles Sardina Medano Gladiolos Polidep. M. y Lopez N. Alamo
10 19 14 21 22 28 26 27 35 45
9 17 20 21 21 26 24 26 35 40
9 18 20 19 19 25 25 26 39 42
14 19 43 34 34 31 36 41 50 64
34 38 49 42 46 57 64 72 65 77
14 24 24 24 30 36 39 41 40 53
17 26 28 29 29 39 34 36 44 55
AN: Nothern Atlantic; ANW: North Western Atlantic; AW: Western Atlantic; NAF: Northern Africa; ME: Mediterranean; EU: Europe.
overlap of these by Saharan/Sahelian dust contributions, local resuspension processes and sea spray input. The seasonal trend is characterised by three annual maxima: February–March, June–August and October– November. The maximal PM10 and n values are recorded in February–March, with the only exception ! of N!estor Alamo where the number of exceedances in this period is very similar to that of the summer months (Table 2). In the October–November maximum the only station which does not follow this seasonal trend is El R!ıo, scarcely affected by this increase owing to its location at 500 m a.s.l. As will be discussed, its location prevents this station from receiving the impact of low altitude Saharan dust outbreaks at the end of autumn. 3.3. Air mass source The back-trajectory analysis (Fig. 4) enabled us to conclude that the most frequent source area of the air
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Mes a y López
Nés tor Á lamo
A rinaga
PlIngles
Sardina
Polideportiv o
Gladiolos
El Médano
Galletas
El Río
120 PM10 (g/m3 )
100 80 60 40 20 0 Jan
Feb
Mar
A pr
May
Jun
Jul
A ug
Sep
Oc t
Nov
Dec
Jan
Feb
Mar
A pr
May
Jun
Jul
A ug
Sep
Oc t
Nov
Dec
n > 50 g/m3
20 15 10 5 0
Fig. 3. Monthly PM10 levels and number of exceedances of EU daily limit value (n) for the period 1998–2000.
mean PM10 levels obtained for North African air masses reached the highest mean values (34 mg PM10/ ! m3 in El R!ıo and 77 mg PM10/m3 in N!estor Alamo). Consequently, even though the occurrence of African air mass incursions over the Canary Islands is not the most frequent long-range transport scenario in the study area, it may be concluded that their impact on PM10 levels is the highest. Once again, an increase in the PM10 levels is observed for each source area from rural to industrial stations. Fig. 4. Distribution of source areas of air masses which reached the study area during the period 1998–2000.
3.4. Origin of exceedances of the EU daily limit value
masses reaching the Canary Islands was the Atlantic Ocean, especially the North and Northwest Atlantic (62% of the days studied). The next most frequent source area was the African continent (25%), and finally Europe and the Mediterranean basin only represent 13% of the days. Therefore, Atlantic air masses have the strongest influence on Canarian atmospheric dynamics. Mean PM10 concentrations for each source area were also determined. Table 3 shows how the lowest mean PM10 concentrations were recorded for days under the influence of Atlantic masses (El R!ıo: 9–10 mg PM10/m3; ! N!estor Alamo: 40–45 mg PM10/m3). Conversely, the
In order to identify the origin (natural or non-natural) of exceedances of the forthcoming EU daily limit values, exceedances classified as ‘‘natural’’ have been defined as those induced by African dust contributions. ‘‘Nonnatural’’ exceedances include mainly anthropogenic contributions although local dust resuspension, sea spray and long range transport from Europe and the Mediterranean basin are also considered. The number of natural exceedances is higher at urban and industrial stations than at urban background and rural sites. This is due to the addition of contributions from different sources, as the African dust load is added to the local background PM10 levels. Therefore, PM levels are
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situation would arise at urban-background stations for Phase I but not for Phase II given that the number of non-natural exceedances (n ¼ 10) would still surpass the EU limit for 2010 (Phase II, n ¼ 7). Heavy traffic and urban-industrial stations would not meet the requirements for any of the phases. The seasonal trend of the annual number of exceedances of the forthcoming EU daily limit value presents two clearly differentiated patterns for natural and nonnatural exceedances (Fig. 5). In the case of non-natural exceedances, there is no common seasonal pattern for the four emission scenarios studied. The different emission rates and sources and ventilation conditions at the four sites account for these differential seasonal patterns. Given that the occurrence of African dust episodes presents a marked seasonal trend, a common pattern of exceedances may be found regarding natural sources.
bound to exceed the limit value more often at urban and industrial sites (higher anthropogenic background levels) than at rural sites (low anthropogenic background levels). Mean annual exceedances range from 17 (El R!ıo) to ! 143 (Ne! stor Alamo), from which 4 to 87 are non-natural in origin and 13 to 56 caused by African dust contributions (Table 4). As the degree of anthropogenic influence decreases, so does the number of non-natural exceedances. Thus, at urban and industrial sites anthropogenic emissions may be considered to be the main contributor to the number of exceedances of the EU daily limit value, while at urban-background and rural stations North African contributions have a greater significance. At rural stations both requirements of the directive for Phases I (2005) and II (2010) would be met if natural exceedances were not taken into account. The same
Table 4 Interpretation of natural or non-natural origin of exceedances of the forthcoming EU daily limit value ! N. Alamo
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
! M. y Lopez Non-nat
3 4 7 10 6 13 13 13 5 6 5 2
4 10 10 1 4 3 2 4 1 6 7 4
7 5 9 11 3 7 2 2 3 0 0 3
5 6 5 2 2 2 0 3 0 1 6 4
1 5 4 2 0 2 2 7 2 2 2 0
3 6 8 1 0 1 1 2 1 5 6 4
0 5 3 1 1 2 4 3 0 1 2 0
4 5 8 1 0 1 1 4 1 4 4 3
1 4 3 2 0 3 3 4 0 1 2 1
3 6 5 1 0 1 1 2 0 3 3 2
87
56
52
36
29
37
23
36
25
27
Pl. Ingl!es Nat
Non-nat
Non-nat
Nat
Sardina Nat
Non-nat
Non-nat
M!edano
Nat
Non-nat
Nat
Gladiolos
Non-nat
Arinaga
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
Polideportivo
Nat
Galletas Nat
Non-nat
Non-nat
Nat
El R!ıo Nat
Non-nat
Nat
1 2 2 0 1 0 0 0 0 0 0 1
3 6 6 0 0 1 0 1 0 1 4 1
0 2 1 0 1 1 0 2 2 0 1 0
2 4 4 0 0 0 1 3 0 2 3 2
1 2 2 0 0 0 0 1 1 0 1 0
3 5 5 1 0 1 0 2 0 3 2 1
1 3 1 0 0 1 0 0 0 0 1 0
3 4 5 0 0 0 0 1 0 1 2 1
0 2 1 0 0 0 0 1 0 0 0 0
1 4 5 0 0 0 0 1 0 1 1 0
7
23
10
21
8
22
9
15
4
13
Nat: Natural origin; Non-nat: Non-natural origin.
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No. days PM10 > 50 g/m
3
12 12
NÉSTOR ÁLAMO
Non Nat (87)
3
MESA Y LÓPEZ
10
Nat (36)
8
Non Nat (52)
8 6
6
4
4
2
2 0
0 JAN
No. days PM10 > 50 g/m
Nat (56)
10
MAR
MAY
JUL
SEPT
NOV
12
JAN
MAR
MAY
JUL
SEPT
NOV
12 PLAYA DEL INGLÉS
EL RíO
10
10
Nat (21) Non Nat (10)
8 6
6
4
4
2
2
0
Nat (13)
8
Non Nat (4)
0 JAN
MAR
MAY
JUL
SEPT
NOV
JAN
MAR
MAY
JUL
SEPT
NOV
Fig. 5. Monthly natural and non-natural exceedances of the forthcoming EU daily limit value period 1998–2000.
This pattern is characterised by a strong February– March increase, followed by secondary maxima in June– August and in October–December. This seasonal trend coincides with the occurrence of Saharan/Sahelian dust outbreaks over the Canary Islands reported by Cuevas (1995), Bustos et al. (1998), Rodr!ıguez (1999), Torres et al. (2001). The impact of these episodes on PM10 levels, and their characterisation will be discussed below. 3.5. Sahara/Sahel dust contributions Earlier studies (Cuevas, 1995; Bustos et al., 1998; Rodr!ıguez, 1999; Torres et al., 2001) have described two main types of African dust outbreaks over the Canary Islands: low altitude atmospheric intrusions in winter and high altitude intrusions during summer. The study and interpretation of PM10 time series allow us to identify three scenarios where the influence of Saharan dust on ambient PM levels is observed on a regular basis over the years. These scenarios are consistent with the two types described by the aforementioned authors. 3.5.1. Winter (February–March) Sahelian events Sahel dust outbreaks in February–March are key factors when implementing the EU limit values owing to their high intensity. In these episodes, daily means of 600–700 mg PM10/m3 may be reached (Fig. 6). The frequency of these events ranges from 2 to 7 times per year, lasting from 2 to 22 days per episode. They are usually detected by all of the tools described above (TOMS, SeaWIFS, back-trajectories, Fig. 6), and their importance is such that in February and March 2000
more than 20 exceedances of the EU limit were registered at most stations. The meteorological scenario giving rise to winter episodes is characterised by the dominant presence of an anticyclone over North Africa, which shifts longitudinally and may be found off the Atlantic coast or in the proximity of the Mediterranean basin (Fig. 6). The dust from the Sahel desert is transported by anticyclonic circulations and the high dust concentrations may be registered up to the low troposphere (E2 km). However, certain unusual episodes have been described where the dust layer is limited to the lowest levels of the mixing layer and in these cases aerosol index maps (TOMS) do not register the intrusion (Herman et al., 1997). The African origin of these events may be demonstrated only by back-trajectory analysis and satellite imagery. 3.5.2. Summer (June–August) Saharan episodes The occurrence of these events is limited to the summer period (June–August), and is reflected in the PM10 time series as persistent high background PM10 levels. The incidence of these events on PM10 levels is especially evident at rural background sites, but it is also detectable at urban and industrial sites. An increase in background levels of 10–15 mg/m3 may persist from 15 to 30 days (Fig. 7), at the rate of 1 to 4 times per year. Consequently, summer intrusions may be clearly differentiated from winter episodes by their lower intensity (usually daily levels o75 mg PM10/m3) and frequency, but longer duration. During these events the North African anticyclone is relocated above 850 hPa (E1500 m a.s.l.) as a consequence of the thermal low which develops at surface
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Fig. 6. Example of a winter Sahelian dust outbreak (26 February–15 March 2000) on ambient PM10 levels in the Canary Islands (* measured as TSP). Satellite image (SeaWIFS) and aerosol index map (TOMS) corresponding to 26 February 2000, and backtrajectory analysis at 850 hPa. Dominant meteorological scenario during the winter Sahelian dust outbreaks, altitude of the 925 and 850 hPa pressure levels for 26 February 2000 at 12 h.
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Fig. 7. Example of a summer Saharan dust outbreak (March 2000–June 2000) on ambient PM10 levels in the Canary Islands (* measured as TSP). Meteorological scenario during the summer period over North Africa (surface temperature indicating thermal low and pressure at 700 hPa for 06 June 2000 at 12 h), and back-trajectory analysis for the same date, showing the African origin of air masses only above 850 hPa. Satellite image (SeaWIFS) and aerosol index map (TOMS).
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level (Fig. 7). Thus, sea level back-trajectory analysis reflects only the influence of the trade winds, with no clear patterns of transport from Africa. Conversely, back-trajectories calculated at 2500 m a.s.l. show a defined African origin for the air masses (Fig. 7). These results agree with Torres et al. (2001), who affirm that in the summertime Saharan outbreaks never intrude the oceanic boundary layer but take place at higher levels. Because these episodes are relatively frequent, a semipermanent dust layer known as the Saharan Air Layer (Prospero and Carlson, 1981) is formed. This is clearly detected on TOMS maps and SeaWIFS images (Fig. 7). In addition to the continuous westward flow of dust, minor downward transport fluxes affect the underlying layer in a continuous and uniform manner. This vertical transport results in an increase in background PM10 levels during long periods (1–3 weeks) at all monitoring stations. 3.5.3. Autumn–winter events (October–November) These events occur mainly in October and November, and may be occasionally detected in December. Autumn intrusions are characterised by the shortest duration (2– 5 days), a frequency of 2–4 times per year and a strong intensity (daily PM levels up to 400–500 mg PM10/m3). This period is associated with a lack of relevant atmospheric processes which inject dust into the lower troposphere over the Sahara or Sahel deserts. However, given the proximity of the islands to the continent, local phenomena such as dust storms may influence the PM10 ambient levels. Thus, during October and November PM10 time series usually present certain abrupt peaks at all stations (Fig. 8). The detection of these episodes must be carried out by back-trajectory analysis and satellite imagery since TOMS aerosol maps do not detect low altitude dust storms (Herman et al., 1997) (Fig. 8). The characteristic meteorological scenario is once again dominated by the North African anticyclone, located at surface level during the winter period (Fig. 8). At this time of the year the surface of the Sahel desert is cooled owing to the lower ambient temperatures and the higher frequency of rain events with the result that dust injection processes are inhibited.
can dust outbreaks extremely high values of crustal components were determined. Winter levels of SiO2 and Al2O3 exceeded the levels reached without the influence of African dust by a factor of 46. This factor ranged from 14–25 for K, Ti, Ca, Fe, Mn, Mg and Ba. Summer levels of the same components were reduced compared with winter (only 1–2 times higher than levels without African dust contributions) owing to the minor intensity of events and the dilution induced in summer by vertical transport. The winter and summer ranges of concentrations of crustal components recorded are similar to those reported by Coud!e-Gaussen et al. (1987), Bergametti et al. (1989b), Prospero et al. (1995), Chiapello et al. (1997), and Tomza et al. (2001) for Saharan episodes. Fig. 9 shows the source contribution of the selected samples, where the predominance of the crustal fraction during African episodes is again evident (76–78% of bulk PM10 during winter, accounting for 129–191 mg/ m3, and 23–28% of PM10 in summer, accounting for 9– 12 mg/m3). Non-mineral carbon and secondary PM + (anthropogenic SO2 4 , NO3 and NH4 ) loads range 3 from 3–14% of PM10 (4–7 mg/m ) and 2–36% of PM10 (3–14 mg/m3), respectively. The marine load (Na, Cl and sea salt SO2 4 ) varies from 3–12% of PM10 (3–20 mg/ m3). Conversely, during days with no African dust contributions the crustal fraction accounts for a maximum of 26% of bulk PM10 (6–8 mg/m3), whereas nonmineral carbon ranges from 18–25% (5–9 mg/m3). The marine and secondary loads increase relatively (8–19% and 20–26%, respectively, accounting for 3–5 mg/m3 and 6–9 mg/m3).
4. Conclusions After the interpretation of the PM10 and TSP time series from nineteen stations belonging to two air quality monitoring networks in the Canary Islands during the period 1998–2000, the following conclusions may be drawn: *
3.6. Chemical characterisation The chemical composition of the eight PM10 samples collected during African episodes and during days without African dust influence is shown in Table 5. The chemical determinations accounted for 73–87% of bulk PM10 levels. Higher PM loads registered during African episodes with respect to non-African events are mainly due to the crustal load (Al2O3, SiO2, Ca, CO2 3 , Ti, Sr, K, Mg, Mn, Fe and P), and they are especially significant during winter episodes. During winter Afri-
5871
*
Three types of African dust contributions in the Canary Islands were identified and characterised. These episodes are dependent on the dominant meteorological scenarios at different times of the year, and have different impacts on PM time series. These events have been defined as winter, summer and autumn–winter dust outbreaks. These episodes are characterised by the daily PM values reached, duration and frequency (Table 6). The comparison of measured PM10 levels with the forthcoming limit values established by the EU directive EC/30/1999 reveals that only the rural station (El R!ıo) would meet the requirements for Phase II (2010), which would be clearly exceeded at urban background, urban and industrial sites even if
5872
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Fig. 8. Example of two autumn–winter Saharan intrusions (November 1999) on ambient PM10 levels in the Canary Islands (*PM measured as TSP). Back-trajectory analysis, NASA-SeaWIFS image and TOMS map for 24 November 1999, and altitude of the 925 and 850 hPa pressure levels for 24 November 1999 at 12 h.
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Table 5 Chemical characterisation of five samples collected under African (February and June samples) and non-African (March, May and August samples) transport scenarios
PM10 Ctotal Corg
Sahara Feb.-01
Sahara Feb.-01
Sahel Jun.-01
Sahel Jun.-01
Non-Afr. Feb.-01
Non-Afr. Mar.-01
Non-Afr. May-01
Non-Afr. ago-01
244 14 7
169 11 7
43 6 6
38 5 4
36 9 9
30 6 5
31 7 7
26 7 7
CO2 3 SiO2 Al2O3 Ca K Na Mg Fe P SO2 4-anthrop:
35 82 27 15 4 6 5 8 0.5 6
19 60 20 8 3 4 3 5 0.1 3
3 5 1.5 1.0 0.4 2 0.4 0.7 0.02 10
2.0 3.2 1.1 0.6 0.3 3 0.4 0.5 0.02 9
2.0 2.8 0.9 0.7 0.3 1.9 0.4 0.6 0.0 3
1.9 1.8 0.6 0.8 0.2 1.7 0.3 0.4 0.0 2
2.0 1.9 0.6 0.9 0.2 1.6 0.3 0.4 0.0 4
2.0 2.0 0.7 0.7 0.2 2.6 0.4 0.4 0.0 3
SO2 4-marine NO 3 Cl NH+ 4
1.6 1.4 12 1.0
1.0 0.9 7.6 0.6
0.5 1.6 0.6 2
0.6 1.5 1.5 3
0.5 4.6 0.7 1.5
0.4 1.9 1.9 1.7
0.4 2.1 1.4 1.4
0.7 2.5 1.7 0.8
Mn Ti V Ba Pb
123 700 39 108 51
98 511 29 73 38
10 45 5 15 7
7 29 4 8 5
9 42 17 15 71
7 33 19 8 21
7 33 3 10 8
9 38 9 12 2
Total PM10 %
213 244 87
123 169 73
34 43 79
31 38 81
29 36 81
22 30 72
24 31 77
25 26 96
All concentrations in mg/m3 except for Mn, Ti, V, Ba and Pb (ng/m3).
Fig. 9. Source contribution of 8 samples analysed. N.A.(W): no African dust influence, winter. N.A.(S): no African dust influence, summer.
exceedances caused by African dust contributions are excluded (Table 7). The mean annual PM10 value and the mean number of exceedances of the daily limit value for 1998–2000 recorded at El R!ıo (16 mg/ m3, n ¼ 4) are very close to the limit values
established for 2010 (20 mg/m3, n ¼ 7) with the result that the values recorded at the remaining stations exceed the final objectives of the directive for 2010. It should be borne in mind that the rural station (El R!ıo), owing to its location at 500 m a.s.l., is often
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Table 6 Main characteristics of the North African dust outbreaks studied Dates
Winter Summer Autumn– winter
Feb.–Mar. Jun.–Aug. Oct.–Dec.
Max. daily PM10 (mg/m3)
Duration (days)
o700 o75 o400
2–22 15–30 2–5
Frequency (times/yr)
Acknowledgements 2–7 1–4 2–4
Table 7 Evaluation of the accomplishment of the requirements established by the EU directive regarding the daily and annual limit values, excluding natural exceedances of the daily limit value Phase I (2005)
Rural Urban background Urban and Industrial
*
*
*
3–14% and (b) SiO2, Al2O3, Ca, K, Fe, Ti, V, Mn and Ba concentrations are excellent tracers of African origin.
Phase II (2010)
Annual limit value
Daily limit value
Annual limit value
Daily limit value
Yes Yes No
Yes Yes No
Yes No No
Yes No No
above the marine boundary layer and therefore outside the direct influence of anthropogenic emission sources. The anthropogenic PM levels in the Canary Islands should be lower than those in continental environments in the EU given that the atmospheric dynamics of the islands favour the dispersion of pollutants over the ocean. As regards the limit values established for 2005 (Phase I, 40 mg/m3, n ¼ 35), they would only be exceeded at industrial and heavy traffic sites (Table 7). At these sites, more than 50 exceedances of the daily limit value are recorded. The number of exceedances of the daily limit value due to Saharan/Sahelian dust contributions is only decisive at rural stations when considering the 2010 EU requirements given that 76% of the exceedances registered at these sites have a natural origin. Sixtyeight percent of the exceedances may be considered natural at urban-background stations and approximately 40% at urban and industrial sites. The chemical analysis of samples collected with and without African dust influence proved that: (a) for the intensive winter African dust outbreaks (daily PM10 levels up to 191 mg/m3) at least 76% of the bulk PM10 levels may be attributable to dust load, whereas the anthropogenic input accounts for only
! InterminisThis study was financed by the Comision terial de Ciencia y Tecnolog!ıa (REN2001-0659-C03-03) and by the Spanish Ministry of the Environment. The authors would like to thank the Autonomous Govern! General de Salud ment of the Canary Islands (Direccion ! General de Industria y Energ!ıa) ! Publica and Direccion for their cooperation providing PM10 and TSP time series, NASA/Goddard Space Flight Center, NOAAARL and SeaWIFS-NASA Project for their contribution with TOMS, HYSPLIT model and meteorological database and satellite images, respectively. Meteorological analysis was provided by the NOAA-CIRES Climate Diagnostics Center Boulder Colorado from their Web site at http://www.cdc.noaa.gov/.
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