Atmospheric pollutants in fog and rain events at the northwestern mountains of the Iberian Peninsula

Science of the Total Environment 497–498 (2014) 188–199

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Atmospheric pollutants in fog and rain events at the northwestern mountains of the Iberian Peninsula Ricardo Fernández-González a, Iria Yebra-Pimentel a, Elena Martínez-Carballo a, Jesús Simal-Gándara a,⁎, Xabier Pontevedra-Pombal b,⁎⁎ a b

Nutrition and Bromatology Group, Analytical and Food Chemistry Department, Faculty of Food Science and Technology, University of Vigo, Ourense Campus, E32004 Ourense, Spain Soil Science and Agricultural Chemistry Department, Faculty of Biology, University of Santiago de Compostela, Santiago Campus, E15782 Santiago de Compostela, Spain

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• There is no work about both PAHs and PCBs in fog-rain events. • None of the existing works is about the case of the northwestern mountains of the Iberian Peninsula. • This is a summary of a 2-year research project drawing conclusions for future approaches. • It deals with all factors affecting the atmospheric deposition of PAHs and PCBs in fog-rain events. • It shows input routes and measures to reduce pollution.

a r t i c l e

i n f o

Article history: Received 28 May 2014 Received in revised form 9 July 2014 Accepted 24 July 2014 Available online xxxx Editor: P. Kassomenos Keywords: PAHs PCBs Rain Fog Grasshopper effect Atmospheric pollution

a b s t r a c t Atmospheric polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are persistent organic pollutants (POPs) and exist in gas and particle phases, as well as dissolved or suspended in precipitation (fog or rain). While the hydrosphere is the main reservoir for PAHs, the atmosphere serves as the primary route for global transport of PCBs. In this study, fog and rain samples were collected during fourteen events from September 2011 to April 2012 in the Xistral Mountains, a remote range in the NW Iberian Peninsula. PAH compounds [especially of low molecular weight (LMW)] were universally found, but mainly in the fogwater samples. The total PAH concentration in fog-water ranged from non-detected to 216 ng · L−1 (mean of 45 ng · L−1), and was much higher in fall than in winter. Total PAH levels in the rain and fog events varied from non-detected to 1272 and 33 ng · L−1 for, respectively, LMW and high molecular weight (HMW) PAHs. Diagnostic ratio analysis (LMW PAHs/HMW PAHs) suggested that petroleum combustion was the dominant contributor to PAHs in the area. Total PCB levels in the rain and fog events varied from non-detected to 305 and 91 ng · L−1 for, respectively, PCBs with 2–3 Cl atoms and 5–10 Cl atoms. PCBs, especially those with 5–10 Cl atoms, were found linked to rain events. The occurrence of the most volatile PCBs, PCBs with 2–3 Cl atoms, is related to wind transport from far away sources, whereas the occurrence of PCBs with 5–10 Cl atoms seems to be related with the increase of its deposition during rainfall at the end of summer and fall. The

⁎ Corresponding author. Tel.: +34 988 387000; fax: +34 988 387001. ⁎⁎ Corresponding author. Tel.: +34 881 813238; fax: +34 981 596904. E-mail addresses: [email protected] (J. Simal-Gándara), [email protected] (X. Pontevedra-Pombal).

http://dx.doi.org/10.1016/j.scitotenv.2014.07.093 0048-9697/© 2014 Elsevier B.V. All rights reserved.

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movement of this fraction of PCBs is facilitated by its binding to air-suspended particles, whose concentrations usually show an increase as the result of a prolonged period of drought in summer. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Atmospheric deposition occurs when substances are deposited on land or water surfaces from the air. Many forms of atmospheric pollution affect human health and the environment at levels from local to global, especially persistent organic pollutants (POPs). These contaminants are emitted from diverse sources, and their input to ecosystems is mainly the result of human activities (Harvey, 1998). Industrialized nations have made important progress toward controlling some pollutants in recent decades, e.g. in the EEA-32 region, emissions of polycyclic aromatic hydrocarbons (PAHs) have fallen by 52%, polychlorinated biphenyls (PCBs) by 74%, hexachlorobenzene (HCB) by 91%, hexachlorocyclohexane (HCH) by 93%, and dioxins and furans by 83% between 1990 and 2010 (EEA, 2013). Some pollutants, especially PCBs, experiment the so-called grasshopper effect. This is the geochemical process by which POPs are transported from warmer to colder regions of the Earth. This leads to a pattern where a pollutant is emitted from an original source, transported some distance, and deposited. Then, a portion is re-emitted, transported a further distance, and re-deposited. This pattern is indefinitely repeated, although there is evidence that these POPs tend to sorption/desorption processes until they reach northern climates or high elevations. With regard to the background levels of some representative PAHs in the air, there are reports that detected levels of 0.020–1.2 ng · m−3 in rural areas and 0.15–19 ng · m−3 in urban areas. So, humans may be exposed to PAHs in soil near areas where coal, wood, gasoline, or other products have been burned. Other sources for human exposure to PAHs could also be the soil at or near hazardous waste sites, such as former manufactured-gas factory sites and wood-preserving facilities (ATSDR, 1995). Accurate and complete information on the emissions of POPs are essential for interpreting historical, current, and future pollution levels in ecosystems (Breivik et al., 2006). This information could also be essential to accurately establish the transport and deposition fluxes of these environmental contaminants. Consequently, research needs to be primarily focused on the origin and determination of seasonal variations of atmospheric pollutants. Normally, the higher precipitation rates are located in mountains. Mountain regions serve as a water supply, both directly and indirectly, through provision of lowland surface water (Daly and Wania, 2005). In high latitudes and altitudes, such deposition is greatly influenced by low temperatures and in particular the phase transition of water at 0 °C. Precipitation occurs in the form of snow rather than rain, which often could be a more efficient scavenger than rain (Lei and Wania, 2004). Fog is also a common feature of mountain regions and groundbased clouds form when a decrease in temperature causes an increase in relative humidity beyond the dew point (Whiteman, 2000). Most relevant are up-slope fogs, whereby moist air is cooled by being lifted up-slope, and radiation fogs, which develop in valleys and mountain basins when outgoing long-wave radiation cools the near-surface air during the night-time and in the winter (Daly and Wania, 2005). Fog droplets are much smaller than rain droplets and have a much higher surface-to-volume ratio. This can lead to significant enrichment of surface-active organic chemicals in fog-water, when compared to the concentration expected from Henry's law (Capel et al., 1991; Goss, 1994; Simcik, 2004; Valsaraj et al., 1993). Therefore, this suggests that fog may be an important mechanism for POP deposition in mountain regions and this fact could explain the differences in POP levels within mountains if the occurrence and frequency of fogs are localized. However, studies on the atmospheric geochemistry of fog, and in particular of the POPs, are scarce.

Two of the most environmentally important POP groups are PCBs and PAHs, which share several characteristics such as origin (mostly anthropogenic), long-distance atmospheric transport capacity, low environmental degradability, and high impact on the health of biota (including humans). Therefore, the aim of this work is to measure the deposition of PCBs and PAHs in rain- and fog-water, and assess possible seasonal patterns of deposition associated with rain and fog events northwest of the Iberian Peninsula. This area has been shown to function as a sink to PAHs associated with its latitudinal position within the context of southern Europe and the properties of soils receiving atmospheric deposition (Pontevedra-Pombal et al., 2012; Rey-Salgueiro et al., 2009a). 2. Methodology 2.1. Sampling strategy The study area is located in the highest elevations of the Northwestern Iberian Peninsula (Fig. 1). The maximum altitude reached is 1060 m a.s.l., and most of the territory is between 700 and 900 m a.s.l. This area is the best example of wet-fresh environments of southern Europe, with a sharp ombrothermal gradient from the coast to the mountainous areas. At the summit, rainfall is between 1400 and 1800 mm, the effective fog-precipitation exceeds 5000 mm and the mean temperature ranges from 7 to 10 °C. These values define an ombrothermal environment that is cool and very humid. The rainfall gradient is close to 100 mm per 100 m altitude, and the thermometric gradient is of − 0.67 °C per 100 m altitude. The seasonal rainfall is very low, the lowest in the Iberian Peninsula. That is, the Northern Mountains are fully in control of mesothermal (not arid) climates, which includes all cold temperate climates, mainly characterized by having an average temperature in the coldest month that is below 6.0 °C. Another defining feature of the climatic conditions of this area is the abundant fogs above 600 m a.s.l. Especially during the summer, under the situations from the north, northeast component, and anticyclonic stability, these reliefs allow flows of oceanic origin generated surface air that allow the development of clouds of stagnation. These, together with the phenomena of radiation fogs, collaborate intensively to increase water input. Since September 2011, a station of climate monitoring was launched in the vicinity of the Chao de Veiga Mol mire (CVM), a raised bog located in the Northern Mountains (43°32′34,4″ N–7°30′13,41″ W), at 700 m a.s.l. and 15 km south of the Atlantic coast (Fig. 1a). This sector is located over 150 km away from any heavily industrialized and populated city, and is 40, 90, and 130 km away from the three largest coal mines and the largest coal-fired power plant in Spain. Moreover, this sector is located in the direction of the dominant winds coming from an incineration plant (Fig. 1b). This sector was selected because previous research proved useful in identifying temporal accumulation patterns of different atmospheric pollutants on a local, regional, and hemispheric scale (Kylander et al., 2005; Martínez-Cortizas et al., 1999; PontevedraPombal et al., 2012, 2013). The installation consisted of a meteorological station (rainfall, fog, temperature, humidity, atmospheric pressure, total, and photosynthetically active radiation) and two rain- and fog-water collectors protected from light and solar radiation. This installation was completed with temperature and soil moisture loggers. The rain- and fog-water samples were collected every 15 days, transported refrigerated to the laboratory, filtered (0.45 μm), and distributed in 4 aliquots. The first aliquot was intended for the determination of trace elements, another aliquot to

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R. Fernández-González et al. / Science of the Total Environment 497–498 (2014) 188–199

Fig. 1. (a) Location of the study area. (b) Prevailing winds in winter and summer in the north-northwest of the Iberian Peninsula [for more detailed information see Rasilla et al. (2004)]. CVM: Chao de Veiga Mol mire.

quantify cations and anions, pH, and conductivity, a third one to analyze POPs, and another one is kept in reserve. All samples were immediately frozen at −18 °C. In this article, we presented the results of the determination of PAHs and PCBs for various rainfall-fog events in the study area. 2.2. Determination of PAHs and PCBs 2.2.1. Chemicals, solutions, and materials For determining PAHs, 10 selected PAHs were studied: fluoranthene (F, 98%), pyrene (P, 98%), benzo[a]-anthracene (B[a]A, 98%), chrysene (Chr, 99%), benzo[b]fluoranthene (B[b]F, 98%), benzo[k]fluoranthene (B[k]F, 98%), benzo[a]pyrene (B[a]P, 97%), dibenzo[a,h]anthracene (DB[ah]A, 97%), benzo[ghi]perylene (B[ghi]P, 98%), and indeno[1,2,3cd]pyrene (I[1,2,3-cd]P, 98%) were purchased from Sigma-Aldrich (Madrid, Spain), and they were used as markers for the 15 PAHs of toxicological significance. F was selected as the representative of three benzenic ring-PAHs. P, Chr, B[a]A, B[b]F, and B[k]F were selected as markers of four benzenic ring-PAHs. B[a]P, DB[ah]A and I[1,2,3-cd]P were selected as representatives of the five benzenic ring group of PAHs. B[ghi]P and DB[al]P were selected as markers of the other six benzenic ring-PAHs. A mixture containing several PCB congeners in isooctane (PCB 28, PCB 52, PCB 101, PCB 138, PCB 153, PCB 180, and PCB 209, 10 μg · mL− 1) was obtained from Riedel de Haën (Seelze, Germany). PCB 30 and PCB 195 were supplied from Dr. Ehrenstorfer (Augsburg, Germany) and chosen as internal and volumetric standards, respectively. In addition, another mixture containing twelve DL-PCB congeners in isooctane (PCB 77, PCB 81, PCB 105, PCB 114, PCB 118, PCB 123, PCB 126, PCB 156, PCB 157, PCB 167, PCB 169, and PCB 189, 10 μg · mL−1 for each one) was also obtained from Dr. Ehrenstorfer (Augsburg, Germany). PCB 11 was purchased from Sigma-Aldrich (Madrid, Spain). Finally, PCB 14, PCB 65, and PCB 166 were employed as surrogate standards to monitor the performance of PCB extraction procedures and acquired from Dr. Ehrenstorfer (Augsburg, Germany). All reagents used for the analysis of PAHs and PCBs were of trace analysis grade and n-hexane, chloroform, acetone, isooctane were supplied from Sigma-Aldrich (Madrid, Spain). Analytical grade C-45

nitrogen was supplied by Carburos Metálicos (Vigo, Spain). Individual 100 mg · L− 1 stock solutions of PAHs were prepared by dissolving about 0.010 g of product in a small amount of acetonitrile or n-hexane and diluting to 100 mL with the same solvent, depending on the solubility of the PAHs. From these solutions, new solutions containing 10 and 0.10 mg · L−1 of the different PAHs in n-hexane were prepared. From these diluted individual solutions, mixed solutions with PAHs ranging from 10 to 700 μg · L−1 were prepared in acetonitrile following evaporation of the n-hexane. Standard stock solutions of PCBs (0.50 mg · L−1 of each PCB) were prepared in acetone. Standard mix solutions (0.50– 20 μg · L− 1) were made by dilution of standard stock solution with chloroform. PCB 30 was added as internal standard (17 μg · L−1) in each level of these standard mix solutions from a solution of 0.28 mg · L− 1 prepared in n-hexane. Working standard solutions used to construct the calibration line were prepared in acetonitrile by dilution to reach concentrations between 0.020 and 40 μg · L−1. These solutions were stored in amber flasks at 4 °C, being stable for at least 6 months. Additional equipment included an ultrasonic bath (Branson, Geneva, Switzerland), a Universal 320R centrifuge (Hettich, Germany), an oven (P-Selecta, Barcelona, Spain), an analytical precision scale (Sartorius, Madrid, Spain), and a vortex shaker (Heidolph, Barcelona, Spain). Disposables used were nylon filters (0.45 μm), micropipettes (200–1000 μL), and injection vials (2.0 mL) furnished with screw caps and PTFE-lined butyl rubber septa and inserts (150 μL and 0.35 mL) and a SGE syringe (250 μL). 2.2.2. Extraction, detection, and quantification The general pre-analytical treatment used was based on a procedure for the determination of PAHs in different samples previously reported by the present authors (García-Falcón and Simal-Gándara, 2005; Rey-Salgueiro et al., 2008a, 2008b, 2009a, 2009b). About 30 mL of a water sample was subjected to up-and-down shaking with 3 × 10 mL n-hexane for 15 min each. After separation of the organic phase, anhydrous sodium sulphate was added followed by vigorous shaking for 5 min. Then, the extract was evaporated until dryness under a stream of nitrogen in a TurboVap LV Concentration Workstation (Caliper Life

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Fig. 2. (a) Distribution of annual wet precipitation and (b) quantification and origin of the wet precipitation during the study period in the work area.

Sciences, Spain) and re-dissolved to a final volume of 300 μL ACN for LCFD analysis. Chromatographic conditions were based on the method developed by Rey-Salgueiro et al. (2008a, 2008b, 2009a, 2009b). Fig. S1 shows an example of a LC-FD chromatogram obtained for PAH determination in a rainwater sample. For the analysis of PCBs, aliquots of 10 mL water samples were placed in 15 mL conical-bottomed glass centrifuge tubes. Prior to extraction, PCB 14, PCB 65, and PCB 166 (prepared in acetone, 0.50 mg · L−1) were added to each sample as surrogate standards (0.20 μg · L−1 of each surrogate PCBs). Then, 100 μL of chloroform containing PCB 195 as volumetric standard (50 μg · L−1) were twice added as extractant solvent. The tube was immersed into an ultrasonic bath (Branson, Geneva, Switzerland) in such a way that the level of both liquids (bath and sample) was the same. Extractions were performed at 40 kHz of ultrasound frequency and 100 W of power for 10 min at 25 °C. As a result, oil-in-water (O/W) emulsions of chloroform (dispersed phase) in

water (continuous phase) were formed (Regueiro et al., 2008). These emulsions were disrupted by centrifugation at 5000 rpm for 10 min (20 °C) and the organic phase was sedimented at the bottom of the conical tube. Extractant was collected by using a SGE syringe (250 μL) and transferred to a 150 μL glass insert located in a 2.0 mL amber vial. Finally, the obtained extracts were spiked with internal standard (PCB 30) in the same level as standard mix solutions. All extracts were stored at −18 °C until analysis by GC/MS. GC/MS analysis was carried out on a Trace 1300 Thermo Scientific gas chromatograph (Rodano, Italy), coupled to a single quadrupole mass detector ISQ from Thermo Electron Corporation (Italy). Separation was performed by using a DB-XLB capillary GC column (30 m × 0.25 mm i.d., 0.50 μm film thickness) from Agilent Technologies (USA). Helium (purity 99.9999%) was employed as carrier gas at a constant flow of 1.5 mL · min−1. Chromatographic conditions were based on the method developed by FernándezGonzález et al. (2013, 2014). The target compounds were positively

Fig. 3. General physicochemical characteristics of the rain- and fog-water collected for the studied period. Black line: fog-water. Grey line: rainwater. E.C.: electric conductivity; Cl−: 2− chlorides; NO− 3 : nitrates; SO4 : sulphates.

192

(a) Sample code

Type

Month

Fortnight

Season

F

P

∑LMWPAHs

B[a]A

Chr

B[b]F

B[k]F

B[a]P

∑HMWPAHs

∑PAHs

F/P

F/F + P

LMW/ HMW

PCB11

PCB28

∑LMWPCBs

PCB105

PCB209

∑HMWPCBs

∑PCBs

P-S-21511 P-O-11511 P-O-21511 P-N-11511 P-N-21511 P-D-11511 P-D-21511 Average

Rain Rain Rain Rain Rain Rain Rain Rain

September October October November November December December –

Second First Second First Second First Second –

Fall Fall Fall Fall Fall Fall Fall Fall

11 n.d. n.d. n.d. 363 2.7 n.d. 54

27 n.d. 20 22 909 29 7.3 145

38. n.d. 20 22 1272 32 7.3 199

n.d. n.d. n.d. n.d. 9.2 n.d. n.d. 1.3

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. 19 n.d. n.d. 2.7

n.d. 0.50 n.d. n.d. 2.3 n.d. n.d. 0.38

1.2 1.5 0.99 0.76 1.9 n.d. 1.4 1.1

1.2 2.0 0.99 0.76 33 n.d. 1.4 5.6

39 2.0 21 23 1304 32 8.7 204

0.41

0.29

32

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. 71 91 n.d. 23

n.d. n.d. n.d. n.d. 71 91 n.d. 23

n.d. n.d. n.d. n.d. 71 91 n.d. 23

P-X-11512 P-X-21512 P-F-11512 P-F-21512 P-M-11512 P-M-21512 P-Ab-11512 Average

Rain Rain Rain Rain Rain Rain Rain Rain

January January February February March March April –

First Second First Second First Second First –

Winter Winter Winter Winter Winter Winter Winter Winter

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

12 6.9 n.d. n.d. n.d. n.d. n.d. 2.8

12 6.9 n.d. n.d. n.d. n.d. n.d. 2.8

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. 0.50 n.d. n.d. 0.071

1.1 n.d. n.d. n.d. 1.0 n.d. n.d. 0.30

1.1 n.d. n.d. n.d. 1.5 n.d. n.d. 0.37

14 6.9 n.d. n.d. 1.5 n.d. n.d. 3.1

9.8 n.d. n.d. n.d. n.d. 108 n.d. 20

n.d. 305 261 266 n.d. n.d. n.d. 139

9.8 305 261 266 n.d. 108 n.d. 136

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. 53 n.d. 42 n.d. 88 n.d. 31

n.d. 53 n.d. 42 n.d. 88 n.d. 26

9.8 358 261 308 n.d. 196 n.d. 162

N-S-21511 N-O-11511 N-O-21511 N-N-11511 N-N-21511 N-D-11511 N-D-21511 Average

Fog Fog Fog Fog Fog Fog Fog Fog

September October October November November December December –

Second First Second First Second First Second –

Fall Fall Fall Fall Fall Fall Fall Fall

54 32 18 134 11 n.d. n.d. 36

50 52 55 70 55 11 7.9 43

104 84 73 204 66 101 7.9 43

n.d. n.d. n.d. n.d. 1.2 n.d. n.d. 0.16

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. 10 1.4 n.d. n.d. 1.7

n.d. n.d. 0.61 0.55 0.70 n.d. n.d. 0.27

n.d. 1.1 1.0 1.2 1.7 1.2 0.78 1.0

n.d. 1.3 1.6 12 4.9 1.2 0.79 3.1

104 85 75 216 71 12 8.7 82

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

81 n.d. n.d. n.d. n.d. n.d. n.d. 12

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

81 n.d. n.d. n.d. n.d. n.d. n.d. 12

81 n.d. n.d. n.d. n.d. n.d. n.d. 12

N-X-11512 N-X-21512 N-F-11512 N-F-21512 N-M-11512 N-M-21512 N-Ab-11512 Average

Fog Fog Fog Fog Fog Fog Fog Fog

January January February February March March April –

First Second First Second First Second First –

Winter Winter Winter Winter Winter Winter Winter Winter

n.d. n.d. n.d. n.d. n.d. n.d. 4.2 0.59

21 n.d. 8.3 n.d. n.d. n.d. 5.7 4.9

21 n.d. 8.3 n.d. n.d. n.d. 9.9 5.6

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. 15 n.d. n.d. n.d. n.d. n.d. 2.1

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

1.9 n.d. 0.67 1.7 n.d. n.d. 2.1 0.91

1.2 n.d. n.d. n.d. n.d. n.d. 1.4 0.36

3.1 15 0.67 1.7 n.d. n.d. 3.5 3.4

24 15 8.9 1.7 n.d. n.d. 13 8.9

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. 246 211 n.d. n.d. n.d. 239 99

n.d. 246 211 n.d. n.d. n.d. 239 100

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

n.d. 73 n.d. n.d. n.d. n.d. n.d. 10

n.d. 73 n.d. n.d. n.d. n.d. n.d. 10

n.d. 319 211 n.d. n.d. n.d. 239 110

0.40 0.092

0.29 0.084

21 29 39 5.2 11

1.1 0.62 0.33 1.9 0.20

0.52 0.38 0.25 0.66 0.17

75 45 17 13 8.9 10 6.8 12

0.74

0.42

2.9

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Table 1 (a) PAH and PCB levels found (ng · L−1) and (b) ∑PAHs and ∑PCBs found converted to RPFs (ng · L−1) and TEQs (pg WHO-TEQ · g−1), respectively, together with pollution data obtained from other areas for (c) PAHs and (d) PCBs.

(b) Sample type

Season

∑PAHs

∑PCBs

Rainwater Rainwater Fog-water Fog-water

Fall Winter Fall Winter

7.9 0.30 5.2 0.65

0 0 0.00030 0

Geographical Area

Urban or Natural Zone

Fog or Rain

Concentration Range (ng · L−1)

Reference

(c) Dübendorf—near Zürich (Switzerland)

Urban

Natural Natural

Rieti (Central Italy) Gdansk (Poland) Lake Maggiore (Northern Italy) Mount Taishan (China) Toronto (Canada) Point Petre (Canada) Shanghai (China) Central Valley of California (USA) Northwestern Mountains (NW Spain)

Urban Urban Natural Natural Urban Natural Urban Urban Natural (but near an incineration plant)

11–1.06 62–450 n.d.–27 0.60–2.4 n.d.–1422 1525 43–1095 1.0–13 28–75 90–975 n.d.–254 n.d.–96 30–6670 n.d.–800 n.d.–1304 n.d.–216

Leuenberger et al. (1988)

Summit of the Greenland Ice Sheet Lake Balaton (Central Europe)

Snow Rain Fog Snow Rain Snow Rain Rain Rain Fog Rain Rain Fog Fog Rain Fog

(d) Zürich (Switzerland) New Jersey (USA) Southern Sweden Island of Crete (Greece) Lausanne and Geneva (Switzeland) France Sub-Alpine (Northern Italy) Beijing (China) Northwestern Mountains (NW Spain)

Urban Urban and Natural Urban and Natural Urban (but rather limited industry) Urban Urban Natural Urban Natural (but near an incineration plant)

Fog Rain Rain Rain Rain Rain Rain Rain Rain Fog

7000–22,000 0.35–13 1.2–81 0.70–5.3 0.11–403 3.1013 0.65–2.4 7.0–993 n.d.–358 n.d.–319

Capel et al. (1991) Van Ry et al. (2002) Backe et al. (2002) Mandalakis and Stephanou (2004) Rossi et al. (2004) Blanchard et al. (2006) Castro-Jiménez et al. (2009) Yang et al. (2012) This work

Guidotti et al. (2000) Polkowska et al. (2001) Olivella (2006) Li et al. (2010) Melymuk et al. (2011) Melymuk et al. (2011) Li et al. (2011) Ehrenhauser et al. (2012) This work

R. Fernández-González et al. / Science of the Total Environment 497–498 (2014) 188–199

n.d.: not detected.

Jaffrezo et al. (1994) Kiss et al. (1997)

193

194

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identified by comparison of their mass spectra and retention times to those of standard solutions. Retention times, quantification ions, and confirming ions for each compound are shown in Table S1a. Fig. S2 shows an example of a GC/ISQ-MS chromatogram obtained for PCB determination in a fog-water sample.

a)

2.3. Characterization of the analytical methods Linear calibration curves were fitted reasonably in a concentration scale of two or three orders of magnitude, depending on the compound. To verify the linearity range, a Mandel fitting test (P = 99%) was

tPAHs -rain (ng/L)

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biweekly Fig. 4. Temporal distribution of (a) total PAHs (tPAHs) and (b) total PCBs (tPCBs) in rainwater and fog-water in the Northern Mountains (NW Spain), expressed in total concentration (ng · L−1) and in total cumulative deposition rate (μg · m−2).

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performed and was satisfactory for all the selected compounds. PAH and PCB recoveries were determined by spiking blank samples (n = 6), which were stored at refrigeration in the dark for 24 hours to facilitate equilibration with the sample matrix (Tables S1a, S1b). The spiking level was at the same concentration of quantification limit (LQ) of the overall method. PCB recoveries were also studied in each sample by using surrogate standards (PCB 14, PCB 65, and PCB 166). Detection and quantification limits (LD and LQ) were based on the noise obtained with the analysis of unfortified samples (n = 6). LD and LQ were defined as the concentration of the analyte that produced a signal-to-noise ratio of 3 and 10, respectively (ACS, 1980). For PAHs, these limits are shown in Table S1b. For PCBs, LDs and LQs of about 3.1 ± 0.5 and 7.8 ± 0.8 ng · L−1 were obtained. Finally, the target compounds were tested experimentally by spiking blank samples at such levels. A comprehensive evaluation of signal suppression was performed for each analyte in order to assess its effect on the quantification. Two different types of calibration curves were studied: calibration curves prepared using n-hexane and calibration-set solutions prepared in the sample matrix. The data obtained from the analysis of each calibration set were fitted to straight lines by the least squares method and slopes of each calibration curve were compared calculating an F statistic. The slopes were not statistically different (p b 0.05) and it could be confirmed that the matrix content does not introduce a systematic bias in the analytical signals.

2.4. Statistical analysis Analysis of variance (ANOVA) or multi-factor analysis of variance (MANOVA) was carried out using the statistical package Statgraphics Centurion XV for Windows Version 15.2.06 (Statistical Graphics Corp., Herndon, VA, USA). Tukey HSD's test was used to discriminate among the mean values. The aim was to search for differences in pollutant concentrations by season (fall or winter) and pollutant types (depending on molecular weight), mainly. 3. Results and discussion 3.1. General physical and chemical properties of rain- and fog-water Environmental monitoring of the selected area showed that in the period studied, the contribution of fog-water to the wet precipitation was substantially higher than that of the rainwater (Fig. 2a), reaching 94% of the total, being slightly higher in fall (Fig. 2b). Throughout the period analyzed, rainwaters were less acidic (pH average = 6.47) and showed lower electrical conductivity (E.C. average = 76.7 μS · cm−1) than fog-waters, with average values of pH = 4.46 and E.C. = 250 μS · cm− 1, respectively. On average, the abundance of anions in rainwater followed the Cl− ≥ SO24 −N N NO− 3 sequence, and the 2− fog-water Cl−N N NO− 3 N SO4 . Both in the rain and the fog, an increase

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− in conductivity and concentrations of Cl−, SO2− 4 , and NO3 were detected in the winter months, with a first peak in January and the maximal values in February–March (Fig. 3).

3.2. Occurrence of PAHs and PCBs pollutants in rain and fog events in fall and winter 2011–2012 Table 1a shows the concentration of the target POPs from rain and fog events. The average values for the total PAHs in fall were higher in rain (204 ng · L−1) than fog (82 ng · L− 1), while these values were lower in rain (3.1 ng · L−1) than in fog (8.9 ng · L−1) in winter. These levels are lower than the maximum allowable concentration in surface waters of some PAHs (B[a]P, B[b]F, B[k]F, and B[ghi]P) established by Directive 2013/39/EU regarding priority substances in the field of water policy. Total PAH levels in the rain and fog events ranged from non-detected to 1272 and 33 ng · L−1 for low-molecular weight (LMW) PAHs (F and P) and high-molecular weight (HMW) PAHs (B[a]A, Chr, B[b]F, B[k]F, and B[a]P), respectively. Previous research showed that most LMW PAH compounds exist in the gas phase, while HMW PAHs prefer to attach to aerosol particles due to their higher hydrophobicity (Tian et al., 2009; Li et al., 2011). Another source identification of PAHs could be conducted by diagnostic ratios of PAHs. In this way, LMW PAHs/HMW PAHs ratios suggested that petroleum combustion was the dominant contributor to PAHs (LMW PAHs/HMW PAHs

ratio N 1 = petrogenic source; Table 1a) (Li et al., 2010). F/P, F/F + P (F/202), B[a]A/Chr and B[a]A/B[a]A + Chr (B[a]A/228) ratios are also commonly used (Budzinski et al., 1997; Tam et al., 2001; Yunker et al., 2002). The F/202 ratio covers the gaseous as well as the particletransported PAHs (Orecchio and Papuzza, 2009). Yunker et al. (2002) reported that the F/202 ratio was below 0.40 for unburned petroleum sources; a ratio from 0.4 to 0.5 implies liquid fossil fuel sources and higher than 0.50 suggest wood and coal combustion. F/P and B[a]A/ Chr ratios greater than 1.0 and 0.40, respectively, are related to pyrolytic origins (Sicre et al., 1987). B[a]A/228 ratios b0.20 indicate petroleum, while values N 0.35 indicate combustion (Lehndorff and Schwark, 2004). In the present work, only F/P and F/202 values were available (Table 1a) and only two fog samples collected in 2011 presented F/P and F/202 ratios greater than 1.0 and 0.50, respectively. Therefore, the PAH content of these samples should be related to wood and coal combustion sources. The rest of the samples presented F/P and F/202 ratios lower than 1.0 and 0.40, respectively. These results agree with Li et al. (2011) (Table 1c) and indicated that unburned petroleum combustion could be the dominant source of PAH in fog-water. HMW PAHs showed levels below the detection limits. This could indicate that PAH contribution associated with carbon combustion and their transport over long distances with subsequent deposition were low. This fact could be explained by the effect of the European Union programs for emissions control in the atmosphere, the change of the kind of carbons burned in

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these plants, and the transformation of these factories in others of combined cycle. In particular, the northeast of the Iberian Peninsula (where the main coal mines and power plants are located) has been determined as a significant input of organic pollutants from coal use. However, the last 15 years has shown a steady decline in the deposition of PAHs on the surface of the ecosystems of this sector (Ares et al., 2009; Pontevedra-Pombal et al., 2012). This recent decrease has also been reported in other studies (Rose and Rippey, 2002; Zaccone et al., 2009). This trend coincides with the results shown by the national air emission inventories in Spain (MAGRAMA, 2012, 2013), which monitors changes in the balance between different sources and the effectiveness of policies to protect the atmosphere. Moreover, monitoring of the composition of atmospheric particulate matter conducted by García-Gacio (2013), in a contemporary period and adjacent place to our study area, showed poor petrogenic contribution to POPs, being very mainstream of the combustion sources (diesel, biomass, and others). In this context, it is also remarkable that there has been an increase (by more than 4 times) in POP emissions associated with the incineration of domestic or municipal wastes in Spain over the past 25 years (MAGRAMA, 2012), although it would be desirable to explore this question given the lack of specific research on this. The total PCB concentrations ranged from non-detected to 358 ng · L− 1 and 319 ng · L−1 rain and fog, respectively. As observed in Table 1a, both in fall and winter, the average values for the sums of total PCBs were higher in rain (23 and 162 ng · L−1, respectively) than in fog (12 and 110 ng · L−1, respectively). Total levels observed ranged from non-detected to 305 and 91 ng · L−1 for PCBs with 2–3 Cl atoms and 5–10 Cl atoms, respectively (Table 1a). These spread results could be due to the different timing of pollutant inputs at the sampling site. Lammel and Stemmler (2012) studied the transport and fate of four PCB congeners covering a range of 3–7 Cl atoms, and observed that secondary emissions (re-volatilisation from surfaces) are, in the long-term, increasingly gaining importance over primary emissions. These secondary emissions are most important for the congeners with 5–6 chlorine atoms. The maximum levels of total PCBs were 358 ng · L−1 in rain and 319 ng · L−1 in fog. These results are similar to those detected in Lausanne and Geneva (403 ng · L−1) in rain (Rossi et al., 2004) and much lower than those detected in Zurich (22,000 ng · L−1) in fog (Capel et al., 1991) (Table 1d). Nevertheless, it is possible to assume that the levels found do not have a large impact on the accumulation of these contaminants in the mountains of the NW Iberian Peninsula. This fact may be due to the low rainfall intensity during the study (maximum daily rainfall: 19–40 L · m−2 for winter and 41–116 L · m−2 for fall). Wet deposition is a non-linear process. The first minutes of rain will clean up the atmosphere, and subsequent rain will be cleaner, so it is possible that the selected POP levels are lower for certain events, but the deposition flux may be higher. Fig. 4a showed that total PAHs (tPAHs) from fog deposition is higher than rain for the period studied, except for one event in late fall, while the contribution of total PCBs (tPCBs) is higher in rain deposition (Fig. 4b) during the middle of fall and winter. The total deposition flux values in wet precipitation [rain- and fog-water] (tDFw) were calculated in fall and winter for individual PAHs (Fig. 5a) and tPAHs (85 and 3.1 μg · m−2 · day−1, respectively), the higher tDFw values were observed in fall, especially for LMW PAHs. Olivella (2006) observed higher PAH concentrations in November and December, coinciding with the largest precipitation amounts (Table 1c). They postulated that wet deposition (0.083– 1.4 μg m−2 month−1) could be the main source of PAH contamination into the surface waters of Lake Maggiore, whereas PCBs (Fig. 5b) and tPCBs were about 10 and 71 μg · m−2 · day−1, respectively. The higher tDFw values were found in winter, especially for PCB 28 (with 3 Cl atoms) and PCB 209 (with 10 Cl atoms). These values were higher than those published by Van Ry et al. (2002) and Turgut et al. (2012) in rainwater from natural, rural, and urban areas with values of about

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0.17 and 28 μg · m− 2 · year− 1 and 0.50 and 340 ng · m− 2 · day−1, respectively. Nevertheless, the type of precipitation (rain, snow, sleet, mixed, etc.) at each site plays an important role in the magnitude of the wet deposition flux (Van Ry et al., 2002). A MANOVA statistical analysis was then performed on the selected POPs levels found in the samples to estimate the effect of the interaction between PCBs (with 2–3 Cl atoms and 5–10 Cl atoms) or PAHs (LMW and HMW), seasonal variation (fall and winter), and sample type (rain and fog). PAH inputs found were at average levels with no significant differences in fall and winter. PAHs (especially the LMW PAHs) were mainly associated with the fog events. As it was previously commented, some researchers showed that most LMW PAHs exist in the gas phase, while HMW PAHs prefer to attach to aerosol particles due to their higher hydrophobicity (Tian et al., 2009; Tsapakis and Stephanou, 2005). Moreover, LMW PAHs usually have significant acute toxicity, while HMW PAHs have a high carcinogenic and mutagenic potential (Park et al., 2001). Instead, PCBs, especially those with 5–10 Cl atoms, were found to be linked to rain events. In this way, Yang et al. (2012) determined the temporal trend of PCBs in precipitation of Beijing from February 2009 to March 2011. They found that levels of PCBs were dominated by dissolved phase (83% of the total PCBs in precipitation), implying PCBs enrichment in rainwater due to efficient scavenging of highly contaminated gas phase and non-filterable submicron particles. The only effect that was shown to be significant was PCBs × season interaction (F-ratio = 10, p = 0.0023). Levels for PCBs with 2–3 Cl atoms were found to be higher in winter than in fall. The occurrence of the most volatile PCBs should be related to wind transport from far away sources, and wind seems to be the main force driving the appearance of these pollutants at winter times. Such observed effects are still more evident when performing an ANOVA by using only the PCB data (with 2–3 Cl atoms and 5–10 Cl atoms) with total levels higher than the median value 0 ng · L−1. With this analysis, it was also found that PCBs with 5–10 Cl atoms presented higher levels during the fall (F-ratio = 4.8, p = 0.046). Then, PCB pollution in the fall could be produced by a nearby incineration facility (Fig. 5b). The occurrence of PCBs with 5–10 Cl atoms in rainwater samples seems to be related with the increase of its deposition during rainfall at the end of summer and fall (Lei and Wania, 2004). The movement of this fraction of PCBs is facilitated by its binding to air-suspended particles, whose concentration usually shows an increase as a result of a prolonged period of drought during the summer. Moreover, another factor controlling these concentrations is their higher persistence with regard to PCBs with 2–3 Cl atoms. Nevertheless, to provide a basis for estimating potential biological impact, rain-fog quality guideline pollutant values intended for screeninglevel hazard would be welcome. There is still a need for institutional support to develop long-term monitoring systems, which can provide information about local, regional, and global pollution trends. 3.3. PCBs and pahs toxicological indices defined in the NorthWestern Mountains PCBs are divided into dioxin-like PCBs (DL-PCBs), showing toxicological properties similar to dioxins, and non-dioxin-like PCBs (NDLPCBs), which do not share the dioxin's toxic mechanism. For PCBs, the use of the total toxic equivalent quantity (TEQ) approach for risk assessment and management purposes was formally adopted (Kutz et al., 1990). In fact, TEQ is often used for legislation and risk assessment and management. Table S1a shows toxicity equivalency factors (TEFs) for DL-PCBs. Nevertheless, EPA (1993) indicated that the data for PAHs did not meet the criteria for the development of TEFs. The EPA's current approach to assessing cancer risk for PAHs uses the relative potency factor (RPF) approach, which estimates the cancer risk relative to B[a]P. The EPA's Office of Research and Development developed RPFs for 24 PAHs (EPA, 2010). The specific values for the 10 PAHs studied in this work are reflected in Table S1b.

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PCB and PAH levels found in fog-water and rainwater samples (Table 1a) were transformed in TEQs and RPFs, respectively (Table 1b). Directive 2013/39/EU as regards priority substances in the field of water policy includes only data for TEQ related to fish for the sum of dioxins and dioxin-like compounds of about 6.5 ng WHO-TEQ/kg. It could be concluded that higher risks of fog-water and rainwater could be associated with PAHs, especially by a single event during the fall season, with average RPF values of 5.2 and 7.9 ng · L− 1, respectively. 4. Conclusions This article reported, for the first time, the deposition of PAHs and PCBs associated with rain and fog events northwest of the Iberian Peninsula. Concentrations of LMW PAHs were higher than HMW ones and were mainly associated with the fog events. LMW PAHs/HMW PAHs ratios greater than 1 suggested that petroleum combustion was the dominant contributor to PAHs, as well as F/P and F/202 values lower than 1.0 and 0.40, respectively. Levels for PCBs with 2–3 Cl atoms were found to be higher in winter than in fall. The occurrence of the most volatile PCBs should be related to wind transport from far away sources, and wind seems to be the main force driving the appearance of these pollutants at winter times. It was also found that PCBs with 5–10 Cl atoms presented higher levels during the fall and, therefore, PCB pollution at fall could be produced by a nearby incineration facility. For PAHs, the higher total deposition flux values in wet precipitation (tDFw) were observed in fall, especially for LMW; whereas for PCBs, the higher tDFw values were found in winter, especially for PCB 28 (with 3 Cl atoms) and PCB 209 (with 10 Cl atoms). The higher toxicological risks of fog-water and rainwater are associated with PAHs, especially by a single event during the fall season, with average RPF values of 5.2 and 7.9 ng · L−1, respectively. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2014.07.093. References ACS (American Chemical Society). Subcommittee on Environmental Analytical Chemistry. Guidelines for data acquisition and data quality evaluation in environmental chemistry. Anal Chem 1980;52:2242-9. Ares A, Aboal JR, Fernández JA, Real C, Carballeira A. Use of the terrestrial moss Pseudoscleropodium purum to detect sources of small scale contamination by PAHs. Atmos Environ 2009;43:5501–9. ATSDR (Agency for Toxic Substances, Disease Registry). Toxicological profile for Polycyclic Aromatic Hydrocarbons (PAHs). Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service; 1995 [http://www.atsdr.cdc.gov/toxprofiles/tp.asp? id=122&tid=25]. Backe C, Larsson P, Agrell C. Spatial and temporal variation of polychlorinated biphenyl (PCB) in precipitation in southern Sweden. Sci Total Environ 2002;285:117–32. Blanchard M, Teil MJ, Chevreuil M. The seasonal fate of PCBs in ambient air and atmospheric deposition in northern France. J Atmos Chem 2006;53:123–44. Breivik K, Vestreng V, Rozovskaya O, Pacyna JM. Atmospheric emissions of some POPs in Europe: a discussion of existing inventories and data needs. Environ Sci Policy 2006; 9:663–74. Budzinski H, Jones I, Bellocq J, Piérad C, Garrigues P. Evaluation of sediment contamination by polycyclic aromatic hydrocarbons in the Gironde estuary. Mar Chem 1997; 58:85–97. Capel PD, Leuenberger C, Giger W. Hydrophobic organic chemicals in urban fog. Atmos Environ Part A 1991;25:1335–46. Castro-Jiménez J, Dueri S, Eisenreich SJ, Mariani G, Skejo H, Umlauf G, et al. Polychlorinated biphenyls (PCBs) in the atmosphere of sub-alpine northern Italy. Environ Pollut 2009;157:1024–32. Daly GL, Wania F. Organic contaminants in mountains. Environ Sci Technol 2005;39: 385–98. EEA (European Environment Agency Website)http://www.eea.europa.eu, 2013. Ehrenhauser FS, Khadapkar K, Wang Y, Hutchings JW, Delhomme O, Kommalapati RR, et al. Processing of atmospheric polycyclic aromatic hydrocarbons by fog in an urban environment. J Environ Monit 2012;14:2566–79. EPA (Environmental Protection Agency). Provisional guidance for quantitative risk assessment of polycyclic aromatic hydrocarbons. Cincinnati, OH: Office of Health

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