Occurrence and seasonal distribution of polycyclic aromatic hydrocarbons and legacy and current-use pesticides in air from a Mediterranean coastal lagoon (Mar Menor, SE Spain)

Chemosphere 167 (2017) 382e395

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Occurrence and seasonal distribution of polycyclic aromatic hydrocarbons and legacy and current-use pesticides in air from a Mediterranean coastal lagoon (Mar Menor, SE Spain)
a, R. Moreno-Gonza
lez b, V.M. Leo
n b, * A. Carratala a b

Departamento de Ingeniería Química, Universidad de Alicante, Spain
fico de Murcia, Apdo. 22, C/ Varadero 1, 30740 San Pedro del Pinatar, Murcia, Spain ~ ol de Oceanografía, Centro Oceanogra Instituto Espan

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


PAHs, legacy and CUPs were analyzed in air using active and passive sampling devices.
28 compounds (PAHs, PCBs and pesticides) were found in coastal air samples.
Chlorpyrifos, chlorpyrifos-methyl and phenanthrene were the most commonly detected.
The highest concentrations for PAHs and some herbicides were found in winter.
The highest concentrations for insecticides were found in autumn.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 29 July 2016 Received in revised form 21 September 2016 Accepted 30 September 2016

The occurrence and seasonal distribution of polycyclic aromatic hydrocarbons (PAHs) and legacy and current-use pesticides (CUPs) in air were characterized around the Mar Menor lagoon using both active and passive sampling devices. The seasonal distribution of these pollutants was determined at 6 points using passive samplers. Passive sampler sampling rates were estimated for all detected analytes using an active sampler, considering preferentially winter data, due to probable losses in active sampling during summer (high temperatures and solar irradiation). The presence of 28 compounds (14 CUPs, 11 PAHs and 3 organochlorinated pesticides) were detected in air by polyurethane passive sampling. The most commonly detected contaminants (>95% of samples) in air were chlorpyrifos, chlorpyrifos-methyl and phenanthrene. The maximum concentrations corresponded to phenanthrene (6000 pg m3) and chlorpyrifos (4900 pg m3). The distribution of contaminants was spatially and seasonally heterogeneous. The highest concentrations of PAHs were found close to the airport, while the highest concentrations of pesticides were found in the influence area of agricultural fields (western stations). PAH and herbicide concentrations were higher in winter than in the other seasons, although some insecticides such as chlorpyrifos were more abundant in autumn. The presence of PAHs and legacy and current-use pesticides in air confirmed their transference potential to marine coastal areas such as the Mar Menor lagoon. © 2016 Elsevier Ltd. All rights reserved.

Handling Editor: R Ebinghaus Keywords: PAHs Pesticides Active sampling Passive air sampling Seasonal distribution

* Corresponding author.
n). E-mail address: [email protected] (V.M. Leo http://dx.doi.org/10.1016/j.chemosphere.2016.09.157 0045-6535/© 2016 Elsevier Ltd. All rights reserved.


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

1. Introduction A significant fraction of organic pollutants access the environment directly or indirectly by air and can be transported far from their sources associated with particulate material or gas fraction (Hapeman et al., 2013; Messing et al., 2011). This long-range transport is especially significant for polycyclic aromatic hydrocarbons (PAHs) and persistent organic pollutants (polychlorinated biphenyls (PCBs), organochlorinated pesticides (OCPs), etc.) (Pozo
nez et al., 2012), et al., 2006; Primbs et al., 2008; Castro-Jime which consequently are present in all environmental compartments. PAHs mainly occur in the atmosphere due to the incomplete combustion of oil, petrol, coal, wood and natural sources (Wild and Jones, 1995), and pesticides mainly by droplet and vapor drift during application (Bache and Johnstone, 1992), post-application vapor losses from treated surfaces (Glotfelty et al., 1984; Waite et al., 2002; Ferrari et al., 2003) and wind erosion of treated soil (Cessna et al., 2006). The hydrophobic character of many of these compounds favour their sorption on particulate material, being relevant their presence in gas and particulate phases as it has been confirmed in a number of studies (Pozo et al., 2006, 2011; Bozlaker et al., 2009; He and Balasubramanian, 2010; Estellano et al., 2012; Melymuk et al., 2012). Aerial transport is also relevant for other contaminants such as current-use pesticides, CUPs, (organophosphorus pesticides, triazines, etc.), for which the distribution distance increases with persistence. The occurrence of CUPs in air has been determined in rural and urban areas (Coupe et al., 2000;  et al., 2010; Moussaoui et al., 2012; Bozlaker et al., 2009; Coscolla
s et al., 2011; Estellano et al., 2015), mainly in the particuBorra late fraction (Yao et al., 2006, 2008; Gouin et al., 2008; Hart et al., 2012; Koblizkova et al., 2012; Coscoll a et al., 2013a,b; 2014). Active sampling is the traditional method used to determine semi-volatile organic compounds, including PCBs, PAHs and pesticides, in air (Yao et al., 2006, 2008; Chaemfa et al., 2008, 2009a;
nez et al., 2011). Passive sampling, which is based on Castro-Jime molecular diffusion, is the alternative procedure; no pumps and power are needed and the equipment is made with inexpensive components. Therefore large-scale field studies at remote, industrial or rural places can be done at a reasonable cost, making this technique appropriate for sampling over long periods of time (Lenoir et al., 1999; Eckhardt et al., 2007; Moussaoui et al., 2012). On the other hand, there is some uncertainness about the sampling rate because it has to be calculated from several approaches such as the use of performance reference compounds (PRCs) or calibrating passive samplers through the simultaneous use of an active sampler. Passive sampling is dependent on meteorological parameters, especially wind speed (Zhang et al., 2013) and is specific for each analyte. In fact, due to the effects of breakthrough, degradation, particle fractions and sampler uptake periods, some passive and active sampler configuration can underestimate semivolatile organic compounds (Melymuk et al., 2014). Several types of passive air sampler (PAS) techniques are currently being used for semi-volatile organic compounds, the polyurethane foam (PUF) disk (Pozo et al., 2006; Shoeib and Harner, 2002), the XAD-resin (Wania et al., 2003), semipermeable membrane devices and others (Shoeib and Harner, 2002). These techniques are semiquantitative since air concentrations can only be derived using estimated sampling rates (Bartkow et al., 2005). Coastal areas are under the influence of a large number of organic pollutant sources as a consequence of the intensive human activities taking place in these areas (urban, industrial, agricultural, etc.). The relevance of atmospheric deposition has been confirmed for PAHs in the Mediterranean Sea, where atmospheric inputs were higher than riverine ones (Lipiatou et al., 1997). These depositions
nez are dominated by low molecular weight PAHs (Castro-Jime

383

et al., 2012). Studies of persistent organic pollutant (POPs) levels in air in Spain are rather scarce and come mostly from specific
rez et al., 2003) studies conducted over short sampling periods (Pe with the objectives of identifying or evaluating possible sources or
lez et al., 2004; Mari improving analytical procedures (Egea-Gonza et al., 2008; Vilavert et al., 2013). Seasonal variation of PAHs was found to be related to the effect of temperature and solar irradiation, which favours their photo
s et al., 2011). oxidation in summer (Borra Seasonal trends in most CUPs were also observed in previous studies (Yao et al., 2008), showing the highest concentrations during application period (spring and summer) (Scheyer et al.,  et al., 2013b, 2014). However, no 2007; Hart et al., 2012; Coscolla previous information is available from other relevant intensive agriculture areas such as the Murcia Region, which consumes 10.9% of pesticides used in Spain (AEPLA, 2010) and where intensive agriculture takes place all year long, especially in coastal areas such as Campo de Cartagena. This area is therefore sensitive to the impact of organic pollutants, although there are no previous data of the levels of pesticides and PAHs concentrations in air. An estimation of organic pollutant levels in air, water and sediments is thus necessary to understand and model their behavior in the basin (Hafner and Hites, 2003; Gambaro et al., 2004). Moreover, the presence of pesticides in air can affect human health (Alavanja et al., 2003), and in particular male fertility is being affected by organophosphorus pesticides in the Murcia Region (Melgarejo et al., 2015). This study aims to characterize spatial and seasonal distribution of PAHs, PCBs and pesticides in air from Mar Menor lagoon using passive samplers previously calibrated with an active sampler, in order to identify their main sources in each season. Active samplers supply additional information about organic pollutant gas/particle partition and allow assessment of the daily variability of the particulate fraction. 2. Material and methods 2.1. Materials Polyurethane foam Bassic ZJ (mean density, 0.0295 g cm3, mean volume 952 cm3) was supplied by BITMAX. Quartz analytical filters supplied by Whatman were used in the active sampler, whilst HPLC grade methanol, n-hexane, dichloromehane, acetonitrile and water (Lichrosolv) were supplied by Merck (Darmstadt, Germany). All standards (mixed or individual, see complete compound list in Supplementary Material section) included in this study (organochlorinated pesticides, PCBs, PAHs, triazines, other pesticides and tributylphosphate) were purchased from Dr. Ehrenstorfer GmH (Augsburg, Germany), except for the organophosphorus pesticides mix, which was purchased from Ultra Scientific (Rhode Island, USA). Atrazine-D5, deuterated PAH mix (acenaphthene-D10, phenanthrene-D10, chrysene-D12 and perylene-D12), PCB-155 and chlorpyrifos-D10 were obtained from Dr. Ehrenstorfer (Augsburg, Germany), and were used as internal standards for triazines, PAHs, PCBs and the remaining pesticides respectively. 2.2. Study area The Mar Menor lagoon is the end point of drainages from a large intensive agricultural area (Campo de Cartagena) where a variety of pesticides are used all year round (several crop campaigns). This lagoon is surrounded by several small towns with a total population of 150,000 inhabitants and intense tourist activity, especially in

384


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

summer (the total population increases to more than 600,000 inhabitants in August) (CARM, 2010). In addition, there is a military airport close to the lagoon (Murcia-San Javier airport) which is also used for civil flights, and the area is influenced by a highly industrialized hub located 20 km to the south. During 2010 the most common winterespring crops in Campo de Cartagena area were lettuce (4600 ha), artichoke (3000 ha) and broccoliecauliflower (3000 ha). Pepper (1300 ha of greenhouses) and melon (3600 ha) were the predominant crops during spring and summer (data supplied by the Region of Murcia's Department for Agriculture and Water). Citrus and almond tree (rainfed) crops were also relevant, with 8700 ha and 5500 ha respectively. The input through surface
lez et al., 2013a) and the distribution watercourses (Moreno-Gonza of regulated and emerging pollutants have been characterized in the Mar Menor lagoon (Moreno-Gonz
alez et al., 2013b).


zares) were located in the main urban nuclei; the population in Alca these two towns rose from 24,000 and 16,000 in winter to 80,000 and 100,000 inhabitants in summer, respectively (INE, 2009). Sites A4 and A5 corresponded to agricultural and summer residential areas, respectively. Site A6 was located on a narrow fringe between the Mediterranean Sea and the lagoon called La Manga del Mar Menor (100e300 m), some distance from the main summer residential area. Sampling point A2 was in a natural area close to a combined military-civilian airport. Sampling points A2 and A4 were located at few hundred meters from crops and the rest ones were sited at longer distances from them. The periods sampled, the number of replicates in each point and the existence of simultaneous active sampling are shown in Table 1.

2.3. Active sampling: calibration of passive samplers

Polyurethane (PUF) disks for passive samplers and PUF cylinders for active samplers and respective blanks were measured, weighed and cleaned by several extractions with n-hexane prior to sampling. Quartz filters were ashed at 500  C for 8 h and weighed prior to sampling. After exposure, PUF samples and quartz filters were extracted with n-hexane using the pressurized liquid extractor (Dionex AS100) into 100 mL cells, at 1500 psi and 100  C using a 2-cycle program (5 min pre-heat; 5 min-static time; 120 s purge; flushing volume 50%). Extracts were evaporated to about 1.5 mL at 50  C in a rotary evaporator, spiked with 10 mL of 50 mg L1 of deuterated mix of PAH and pesticides, conducted to a final volume of 2 mL, stored in solvent rinsed amber glass containers and kept in the fridge until analysis. Other solvents (DCM/hexane and MeOH) were previously tested, but lower extractions or precipitates were obtained in the second case and consequently n-hexane was used for PUF and filter extraction. The hexane extract was concentrated using a gentle stream of N2 to 1.5 mL and analyzed by gas chromatography coupled with mass spectrometry (GC 6890N coupled with an Agilent 5975 inert XLD quadrupole mass spectrometer) using full-scan mode (slightly lower sensitivity but useful for screening new pollutants in real samples). Separation of compounds was achieved using a Supelco SLB-5MS capillary column, 60 m  0.25 mm I.D.  0.25 mm film thickness and helium as the carrier gas at 1 mL min1. Quantitative analysis was performed using an external standard calibration curve. The calibration curve samples were prepared in hexane (HPLC grade, Merck, Darmstadt, Germany) from 5 to 100 mg L1 for all considered analytes. The extraction efficiency was evaluated spiking PUF and filters directly in extraction cells with standard solution in methanol (all considered analytes at similar concentration). The extraction efficiency of target compounds using pressurized liquid extraction was higher than 90% in all cases. The limits of detection (LOD) were also determined for this procedure considering a signal/noise ratio of 3 and varied between 0.3 and 10 pg m3 for all studied analytes, except for heptachlors, endosulfans, drins and some triazines that shown LOD higher than 10 pg m3.

The active sampler used was a standard DIGITEL-80 high volume sampler (sampling flow 30 m3 h1), equipped with a PUF module located after the filter module with a retention efficiency of 99.95% of 0.3 mm particulate. It allows daily particle sampling (automatic filter exchanger) and global gas sampling in the PUF foam (manual). The gas fraction sample (PUF cylinder) obtained represented an integrated value of the full exposure period (13 days), while the particulate fraction (quartz filters) was characterized daily. Two sampling campaigns were conducted, in summer 2009 and winter 2010, in order to evaluate the effect of different meteorological conditions on passive sampling rates and to ensure full-screening of the organic pollutants present in air from the study area using a high sampling volume. The distribution between gas and particulate phase of the organic pollutants can be affected by changes in retention in the polyurethane foams at different atmospheric conditions. Calibration of passive samplers (sampling rates estimation of each compound detected) was performed through the simultaneous use of 3 passive samplers and the active sampler. More specifically, two sampling campaigns with both samplers were performed at sampling points A1 (13 days in summer) and A3 (13 days in winter) (Fig. 1, Table 1). 2.4. Passive sampling The passive samplers contained a PUF disk (Bassic ZJ) (average dimensions 10.9 cm diameter and 1.35 cm thick) with a surface area of 232 cm2, a volume of 126 cm3 and a density of 0.0295 g cm3. They were placed in a stainless chamber consisting of two domes with diameters of 30 cm and 25 cm respectively allowing air to flow through a 2.5 cm gap between the two domes, as previously used by Harner et al. (2006). This sampler housing protects the foam disk from precipitation, sunlight and particle deposition. The derived air concentrations for passive sampling, not including PRCs, should be considered semi-quantitative because specific meteorological parameter effects on sampling rates are not included (Tuduri et al., 2006). The passive sampler device works reasonably well up to an outside wind speed of 4 m s1, although sampling rates increase sharply at higher wind speeds (Zhang et al., 2013). Passive samplers were installed at 6 sampling points at 2.5 m above ground level (Fig. 1) around the Mar Menor lagoon for one month in each season (Table 1). At three of the sampling points (points A1, A3 in red, and A6, in green) replicates were used to assess the sampling variability/reproducibility and to improve the confidence of the determinations. Sampling points A1 (San Pedro del Pinatar) and A3 (Los

2.5. Extraction and analysis of organic pollutants

2.6. Quality control Quality assurance of the data obtained was determined using limit of quantification, linearity, procedural blanks, etc. During each sampling campaign field blanks were used (filter and PUF disks). In fact, trace amounts of naphthalene, fluorene and phenanthrene were detected in the blanks, which were used to correct real concentrations from sample extracts. Mean recoveries higher than 85% for the whole analytical procedure (PUF spiked with standards mix) were obtained and consequently no correction was applied to the


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

385

Fig. 1. Map of the Mar Menor lagoon indicating the location of sampling points, where 1, 2 or 3 passive samplers were simultaneously used, and the main urban nuclei in this area.

Table 1 Sampling schedule applied for passive and active samplers in the six sites around Mar Menor lagoon, indicating number of passive samplings, sampling periods, replicates (in brackets) and main meteorological characteristics at nearby stations. Campaigns

Calibration

Spatial

Active + passive samplers

Passive samplers

Site (n replicates)

A1 (1)

A3 (3)

A1 (3) + A2 + A3(3) + A4 + A5 + A6 (2)

Season

Summer

Winter

Winter

Spring

Summer

Autumn

Year

2009

2010

2010

2010

2010

2010

Period

19/08e01/09

19/02e04/03

18/02e22/03

21/5e21/6

3/8e3/09

18/10e18/11

22.4 30.0 17.0 1.2 3.6 0.2 2.8 6.0 0

15.1 25.0 7.0 1.2 4.0 0 3.7 14.0 0

13.4 25.0 3.0 1.2 4.0 0 3.3 14.0 0

23.8 36.0 17.0 1.3 4.0 0 2.7 8.0 0

26.4 38.0 19.0 1.2 4.0 0 3.2 11.0 0

16.6 24.0 8.0 1.2 5.0 0 3.7 13.0 0

T ºC (Aljorra)

Wind Speed m s1 (Aljorra)

Wind Speed m s1 (Alicante airport)

avg max min avg max min avg max min

final concentrations. Control calibration samples spiked with internal standards were measured regularly to check instrument performance during analysis. The reproducibility of air sampling data was evaluated by simultaneous exposures to 2e3 PUF disks (Fig. 1) deployed at the same height but with slightly different orientations. The mass

accumulated was affected by the orientation of the passive sampling devices, particularly in one of the replicates, which showed a higher accumulation than the others for some analytes (a more detailed explanation is provided in the results and discussion section). However, considering the two more similar passive sampling replicates the variability was lower than 25%.

386


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2.7. Meteorological and statistical analysis In order to relate levels of organic pollutants with possible sources or dispersion processes, the most relevant meteorological variables were considered: wind speed, wind direction and temperature, data being obtained from nearby meteorological stations. Two meteorological stations were located close to the study area: La Aljorra station, which is the nearest regional air quality station, at 18 km inland and the San Javier station located in the military airport, close to the lagoon and to the A2 sampling point. A third coastal meteorological tower located 58 km north at Alicante airport was used for comparison, filling in data gaps and possible artifacts in wind speed. Temperature ranges during the different calibration and sampling periods were similar in the three meteorological stations. Average temperature and range (min-max) hourly temperatures from the La Aljorra station, which was considered the reference station for temperature and wind direction, are shown in Table 1. La Aljorra station presented lower hourly wind speed compared with the stations at San Javier and Alicante airports. The San Javier station measured only in daylight hours and had a daily mean wind speed during the summer active sampling period ranging from 2.2 to 4.7 m s1 (total period mean 3.35 m s1), with wind gusts between 5.8 and 8.9 m s1. In the winter period the daily mean wind speed varied between 1.4 and 8.6 m s1 (total period mean 4.7 m s1), showing wind gusts between 6.1 and 19.7 m s1. Wind speed at Alicante airport (Table 1) showed a similar structure to that at San Javier airport, reaching the highest values in winter and fall. The availability of hourly data for all periods and coastal character was the reason for selecting this station for wind speed reference in the area. Fig. 1S shows dominant wind provenance in calibration and spatial campaigns (data from La Aljorra station). The area has a mild Mediterranean coastal climate. In winter westerly winds alternate with more stagnant conditions and westerly winds predominate in autumn. In spring and summer the area is almost outside northwesterly circulation and thermal sea-breeze circulations govern air mass circulation (Santacatalina et al., 2011). Air mass circulation has a diurnal cycle (land-sea) in which winds in the study area come from the east at warmer times of day and from the northwest at cooler ones. Statistical analyses were carried out using the SPSS statistical package (SPSS v. 15.0). Normality of data was tested by the ShapiroeWilk test and homogeneity of variances was tested using Levene's test. Mean data were compared between seasons when mean concentrations were higher than LOQ, with Tukey-b (equal variance) or T2 Tamhane (different variance) tests being used to analyse the seasonal differences applying a p < 0.05 significance level. 3. Results and discussion 3.1. Organic pollutants in air (active sampling): gas and particulate phase PAHs and pesticides were detected using active sampling in both phases (gas and particulate), confirming the presence of urban transport and agricultural sources in this system. More specifically, 32 out of 82 compounds analyzed were detected in air by active sampling, of which 22 and 32 were found in the gas and particulate phases, respectively. Most of these compounds were detected in both phases, with the exception of p,p’-DDE and acenaphthene, which were only detected in the gas phase. On the other hand, trichloronate, cyprodinil, procymidone, oxyfluorfen, desethylterbuthylazine and alachlor were only found in the particulate phase. Concentrations of PAHs, organochlorine pesticides (OCPs),

organophosphorus pesticides (OPPs) and other pesticides were higher in the gaseous phase than in the particulate phase. However, propyzamide, terbuthylazine, tributylphosphate and the heaviest PAHs (benzo(e)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, benzo(g,h,i)perylene and dibenzo(a,h) anthracene) were mainly associated to particles (Fig. 2). In general, there was a high degree of concordance between the compounds detected in both seasons (Fig. 2), although more compounds were found in winter than in summer. Higher temperatures and solar irradiation in summer can reduce the persistence of some pollutants (Borr
as et al., 2011) and differential wind patterns could affect pollutant transport and levels but the presence of CUPs is also related to their applications (urban, agriculture, etc.). In fact, the herbicides pendimethalin, propyzamide, oxyfluorfen and alachlor and the fungicide procymidone were only found in winter. The most abundant contaminants in the gas phase in winter were phenanthrene, chlortal-dimethyl, fluoranthene, naphthalene, pendimethalin, pyrene and chlorpyrifos, which were detected at concentrations higher than 200 pg m3 (Fig. 2). Pendimethalin, was also detected in 94e100% of spring-summer samples in German Bight and North Sea (Mai et al., 2013). However, the predominant contaminants found in summer were chlorpyrifos, fluoranthene, pyrene, phenanthrene and p,p’-DDE, at concentrations higher than 100 pg m3. The concentrations in the gas phase were higher in winter than in summer for all analytes with the exception of p,p’-DDE and chlorpyrifos. The presence of pollutants in the particulate phase depends on the physicochemical properties of each compound, the type of particulate material and the environment. In the case of low molecular weight PAHs, their particulate fraction ranged between 20% and 50% of total air concentration in summer; their gas fraction, however, was the predominant one in winter. The most abundant pollutants (concentration higher than 100 pg m3) found using active sampling were terbuthylazine and tributylphosphate in summer and propyzamide and pendimethalin in winter (Fig. 2). The concentrations found for cyprodinil and pendimethalin (0.04e0.4 ng m3) were similar to those found in particles of different size range in the rural atmosphere in France  et al., 2013a). Chlorpyrifos, chlorpyrifos-methyl and (Coscolla diazinon were also found in PM10 particles of the Valencia Region (Hart et al., 2012), the chlorpyrifos concentrations observed in the Mar Menor lagoon being similar to the mean values observed in Morella, Sant Jordi and Valencia. However, the concentrations detected in the lagoon for chlorpyrifos-methyl were four times higher than the maximum values found in Alzira (Hart et al., 2012). Terbuthylazine concentrations in particles were similar to those previously found in France (Sauret et al., 2008) and similar to the  et al., 2013b). mean value detected in the Valencia Region (Coscolla Daily variability (n ¼ 13) in the winter campaign (Fig. 3) was below 90% for the PAHs which were detected systematically in all daily samples (pyrene, fluoranthene, acenaphthene naphthalene, acenaphthylene, phenanthrene, chrysene, benzo(e)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, indeno-pyrene), and also for several pesticides (chlorpyrifos, pendimethalin, cyprodinil). Diazinon, terbuthylazine, tributylphosphate and chlorthaldimethyl were detected most of the days (>25%) and showed a daily variability of up to 150%. The lower variability of PAHs in relation to pesticides was probably related to a greater variability in agricultural applications compared to classic anthropogenic sources such as traffic, which are more closely related to PAH emissions. The PM10 average for the studied period was 23 mg m3 while the sum of POP (SPOP) average was 1.1 ng m3 and consequently represented a small fraction of PM10. This reflects the fact that the major constituents of PM10 (in mass) were inorganic (crustal, marine or secondary ions) and also elemental carbon (Santacatalina


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

387

Concentration (pg m-3)

800 700 600

A)

particle gas

500 400 300 200 100

Chlorthal-dimethyl

Propizamide

Pendimethalin

Tributylphosphate

Chlorpyrifos-methyl

Diazinon

Chlorpyrifos

Indeno-pyrene

Terbuthylazine

Benzo(a)pyrene

Benzo(k)fluoranthene

Chrysene

Benzo(b)fluoranthene

Pyrene

Benzo(a) anthracene

Fluoranthene

Anthracene

Fluorene

Phenanthrene

Acenaphthene

Naphthalene

Acenaphthylene

p,p-DDE

0

Concentration (pg m-3)

800 700

B)

particle

600

gas

500 400 300 200 100

Chlorthal-dimethyl

Pendimethalin

Propizamide

Tributylphosphate

Chlorpyrifos

Chlorpyrifos-methyl

Diazinon

Terbuthylazine

Indeno-pyrene

Benzo(a)pyrene

Benzo(k)fluoranthene

Benzo(b)fluoranthene

Chrysene

Benzo(a) anthracene

Pyrene

Fluoranthene

Anthracene

Fluorene

Phenanthrene

Acenaphthene

Naphthalene

Acenaphthylene

p,p-DDE

0

Fig. 2. Gas and particulate concentrations of contaminants (13 days approximately) in summer (A, site A1) and winter (B, site A3) using an active sampler.

Fig. 3. Daily variation of PM10, in mg m3(A left) and daily wind speed average in m s1 (A, right). Daily variation of sum of PAHs and sum of pesticides in PM10 particulate fraction (B right) and also (B left) for fluoranthene and terbuthylazine.

et al., 2012). However, the levels of PM10 and the sum of both pesticides and PAHs showed certain parallels in their evolution (no significant correlation), due to the fact that dispersion processes and anthropogenic emissions affect most pollutants in a similar
n et al., 2000; Yubero et al., 2011). The lowest way (Milla levels were related to the lowest emissions and the highest dispersion processes. For example, in Fig. 3, the minimum recorded on 23/2/2010 (Monday) was related to better dispersion (sustained high winds) and that of 28/02/2010 (Sunday) to lower anthropogenic emissions.

3.2. Passive sampler calibration: estimation of sampling rates using an active sampler The period-average data from passive and active samplers was used to calculate specific sampling rates (dX) for passive samplers in summer and winter. Passive samplers (by passive diffusion) accumulate different amounts of organic pollutants (mg X or mg X d1) at a theoretical and specific sampling rate for each organic pollutant (m3 d1). The specific sampling rates (dX) were estimated by adjusting air concentrations in both sampling methods (active/passive).

388


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  mgXd1 passive 3 1
¼ dX m d mgXm3 active In general passive samplers showed a good match with active samplers. Table 1S summarizes average results in both sampling systems for summer (19/8/2009e1/9/2009) and winter (19/2/ 2010e4/3/2010) periods respectively (Fig. 4). Sampling rates were estimated using the gas phase air concentration and the addition of gas and particle concentrations. Some studies suggest similar PUF sampling rates for gas- and particle-phase compounds, others show lower sampling rates for particle associated compounds (Melymuk et al., 2014 and references therein). The capability of passive samplers to capture particles should be lower than that of active samplers, but unfortunately the proportion of particles captured by passive samplers has not been estimated in this study. Both estimations were compared, and the total air concentration (gas þ particle) was selected as a reference because PUF disks were confirmed as samplers capable of accumulating compounds present in both gas and particle phases (Chaemfa et al., 2009b; Melymuk et al., 2011; Bohlin et al., 2014). Sampling rates were similar for terbuthylazine, chlorpyrifos and several PAHs (acenaphthylene, benzo(a)pyrene) in both seasons. However, in other cases, such as the majority of PAHs, sampling rates were higher in summer than in winter. Daily flow rates (pg d1) were similar for the 23 compounds found in summer and winter (Fig. 4). These results indicate that air concentrations should not be different from those derived from active samplers. However, lower levels were detected for these PAHs in active sampling in summer. These lower levels could be due to some losses (breakthrough) in active sampling (desorption from the dry fraction and drag from the gas fraction) as a result of the high temperatures found in this region in summer (max 30e38  C, Table 1), which favour volatilization and degradation of these compounds. This produced higher sampling rates in summer than winter. However, taking this factor into account we are more confident using the winter sampling rates. In previous studies the variability of sampling rates was attributed to site-specific meteorology, showing stronger wind dependency above 1 m s1 and increasing sharply to 40 m3 d1 at 1.75 m s1 (Tuduri et al., 2006). In fact, Pozo et al. (2006) found exceptionally high sampling rates in August (14 m3 d1 in Barcelona and Las Palmas de Gran Canaria and 24 m3 d1 in Alaska), attributable to high winds at these coastal sites. The physicochemical properties of each compound also affect the sampling rate. In this regard, other studies have reported wide ranges of sampling rates

(2e8.3 m3 d1) for different PCBs (Shoeib and Harner, 2002) and PAHs homologues (0.2 and 5.5 m3 d1 and 31 m3 d1 for naphthalene) (Bohlin et al., 2014). In many locations there was a seasonal dependence on wind speed and air mass origin, the greatest amount of air sampled being related to wind speed and direction (Melymuk et al., 2011). An increase in the gas-phase proportion of the least volatile PAHs as temperature increased was also observed (Melymuk et al., 2011), as was a slight trend of sampling rates increasing with temperature (Armstrong et al., 2014). The average uptake rates of selected PCBs and PBDEs over the 12 weeks of deployment ranged from 1.2 to 11 m3 d1 for high density PUFs and 1.4e12 m3 d1 for low density foams (Chaemfa et al., 2009c), also reflecting a higher uptake rate during the first 2 weeks in comparison to that in weeks 3e12. Sampling rates for chlorpyrifos varied from 2.1 to 7.5 m3 d1 (Armstrong et al., 2014) using depurating compounds and from 2.5 to 4.4 m3 d1 using active air sampling. Sampling rates estimated in passive samplers for some analytes (naphthalene, phenanthrene, fluoranthene, pyrene, chrysene, p,p’-DDE, chlorpyrifos, propyzamide, chlorpyrifosmethyl and terbuthylazine) were similar to those found in previous studies (2.5e12 m3 d1, Harner et al., 2006). The majority of these studies applied sampling rates of between 3 and 5 m3 d1 (Pozo et al., 2004, 2006, 2009, 2011; Gouin et al., 2005; Tuduri et al., 2006). However, recent studies have recommended the use of specific sampling rates in preference to generic ones (Melymuk et al., 2011; Bohlin et al., 2014). In fact, mean sampling rates obtained by Melymuk et al. (2011) varied from 4.9 ± 0.9 m3 d1 for 3ring PAHs to 8.0 ± 3.8 m3 d1 for 4-ring PAHs, which were in the same order as those detected in our study. In order to calculate air concentrations from passive samplers in our study, mean sampling rates (including particulate phase) were adopted for compounds with similar physicochemical characteristics. More specifically, four sampling rates were used to calculate air concentration from passive samplers for different analytes: 3 m3 d1 (propyzamide, pendimethalin and chlortal-dimethyl), 6 m3 d1 (triazines and the heaviest PAHs), 9 m3 d1 (p,p’-DDE) and 12 m3 d1 (light PAHs, organophosphorus pesticides and tributylphosphate) (Table 1S). If a flat sampling rate were applied (i.e.: 4 m3 d1) air concentrations should be higher than using the proposed specific rates for all cases, except for propyzamide, pendimethalin and chlortal-dimethyl. 3.3. Seasonal occurrence and distribution of organic pollutants by passive sampling 28 out of 82 analyzed compounds were detected in air by

Fig. 4. Daily flow rates obtained from passive samplers in winter and summer campaigns.


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

passive sampling (11 PAHs, 4 OPPs, 3 OCPs, 3 triazines and 7 from other groups), a similar number to those detected by active sampling (32 compounds). However, some pesticides were only detected by passive sampling at specific points and in certain seasons (b-HCH at A6 in autumn and secbumeton and prometon at A3 in winter). On the other hand, several PAHs (anthracene, benzo(k) fluoranthene, benzo(b)fluoranthene and indeno-pyrene), myclobutanil, desethyl-terbuthylazine and procymidone were previously found by active sampling but not detected by passive sampling. Sampling variability was evaluated using replicates at several points for all considered seasons. The orientation of passive sampling devices affected the pollutant mass accumulated, particularly in the replicate which showed highest accumulation of analytes. The variability between the two replicates in the sampling device located at point A6 (oriented to north and south and surrounded by the lagoon to the west and the Mediterranean Sea to the east) was below 25%, because neither of the two samplers vies with the other for preferential winds. However, in the case of devices with three replicates, cross-conformation led to one preferential sampling orientation and two less favoured orientations depending on preferential winds, except in winter when the three replicates were similar. In autumn and spring, the replicate with W or N orientation was more exposed to NW winds and systematically accumulated a higher pollutant mass than the other two. In summer the replicates E (in A3) and N (in A1) were more exposed to East winds than the other two and thus accumulated more mass. The sampling variability discarding the replicate with preferential mass accumulation was lower than 30% for all cases. Surprisingly, some pollutants were only found in one of the replicates at low concentrations, which led to standard deviations between replicates being higher than 25% in these specific cases.

3.4. OCPs p,p’-DDE was detected in the majority of samples at lower

389

concentrations than in previous studies performed in Las Palmas (Canary Islands) and California (Pozo et al., 2006), confirming its current input to coastal areas from the agricultural soils where it was applied. Mean concentrations of p,p’-DDE were lower than  et al., 2010). those found in France (Coscolla Several organochlorinated pesticide residues were detected, confirming their previous use in the surrounding area, which continues to act as a source. The degradation intermediate of p,p’DDT, p,p’DDE, was detected in all seasons showing similar mean concentrations and maximum values at A2 and A4 (Table 3). However, b-HCH and alachlor were only detected in one sample in autumn, this also being true for the herbicides secbumeton and
zares, A3). Surprisingly b-HCH was the prometon in winter (Los Alca unique HCH isomer found at concentrations higher than LOD, probably due to its higher persistence in the environment (Bachmann et al., 1988).

3.5. OPPs Chlorpyrifos was detected in all samples, as also observed in the Tuscan atmosphere (Estellano et al., 2015), in the Mississipi River (Majewski et al., 1998) and Brazilian mountains (Meire et al., 2012), showing its continuous use throughout the whole year. This insecticide is used to treat a variety of insects infesting the most common crops in the Campo de Cartagena area, being used in all seasons. In fact, chlorpyrifos was the most widely used insecticide in the Murcia Region in 2006 (Sanz-Navarro, 2008). Chlorpyrifos was also detected in all stations in particulate matter (PM10) in the Valencia Region (Hart et al., 2012). However, the detection frequency of this compound (47 and 42% respectively) in the Central Region of France (Coscoll a et al., 2010) was lower than at the Mar Menor lagoon. The second most frequently detected OPPs (95.8% samples) was chlorpyrifos-methyl (Table 2), which was also found in the majority of air samples from the Tuscany region (Estellano et al., 2015). Their regular presence in air favours their transfer to

Table 2 Estimated mean (n ¼ 24) annual air concentrations (pg$m3) considering all data available (one month in each season). Minimum value was b.q.l. (concentration below quantification limit) for all analytes. Group

Compound

>LOD (%)

Concentration (pg$m3) Mean

S.D.

Minimum

Maximum

Median

OCPs

b-HCH

4.2 87.5 4.2 12.5 37.5 37.5 79.2 95.8 87.5 25.0 12.5 8.3 8.3 16.7 75.0 16.7 100.0 95.8 12.5 29.2 50.0 4.2 87.5 29.2 25

b.q.l. 10.9 b.q.l. 4.1 19.8 127.6 253.4 808.3 205.9 67.7 3.4 b.q.l. b.q.l. 32.0 41.9 b.q.l. 1492.6 288.0 16.8 410.4 479.5 6.6 537.0 15.7 29.1

e 8.5 e 18.9 32.7 333.6 527.2 1517.7 275.4 126.8 14.0 e e 105.9 51.2 6.1 1489.0 380.5 54.2 816.5 793.2 32.5 797.7 28.5 60.2

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. 73.2 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

27.8 33.8 16.6 92.6 101.1 1592.9 2237.6 6041.6 1183.2 371.0 68.8 23.2 23.6 472.5 202.3 27.3 4902.4 1428.5 241.0 3207.7 3309.2 159.2 3134.2 101.8 187.5

n.d. 9.5 n.d. n.d. n.d. n.d. 32.6 125.2 111.2 n.d. n.d. n.d. n.d. n.d. 25.5 n.d. 955.6 112.4 n.d. n.d. 54.8 n.d. 220.4 n.d. n.d.

PAHs

Triazines OPPs

Other pesticides

Other compounds

p,p’-DDE Alachlor Naphthalene Acenaphthylene Acenaphthene Fluorene Phenanthrene Fluoranthene Pyrene Benzo(a)anthracene Chrysene Benzo(a)pyrene Dibenzo(a,h)anthracene Terbuthylazine Diazinon Chlorpyrifos Chlorpyrifos-methyl Propoxur Propyzamide Pendimethalin Oxyfluorfen Chlortal-dimethyl Cyprodinil Tributylphosphate

n.d.: not detected (concentration below the limit of detection).


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

390

Table 3 Concentrations higher than the limit of detection (LOD, %), seasonal mean concentrations (pg$m3, n ¼ 6) and other statistical parameters for the most abundant contaminants detected in the Mar Menor lagoon area using passive samplers (PUF), indicating when the seasonal differences were statistically significant (a,b superscripts). The corresponding data for the rest of analytes found are shown in Tables 2S and 3S. Compound

Season

>LOD (%)

Mean

S.D.

Minimum

Maximum (site)

Median

Fluorene

Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn Winter

83 33 100 100 100 83 100 100 50 100 100 100 83 83 100 83 67 33 100 100 100 100 100 100 83 100 100 100 0 0 100 17 0 0 100 100 100 50 100 100

57.7 41.7 287.7 626.7 596.6 340.8 1107.2 1188.5 57.1 a 48.9 a 154.3 a 563.4 b 8.3 7.5 10.1 17.7 15.5 a bql a 42.6 a 105.2 b 2355.0 a 821.0 ab 2530.6 a 263.7 b 59.3 147.6 781.5 163.6 n.d. n.d. 1609.9 a 31.8 b n.d. n.d. 1359.5 558.4 47.8 9.4 722.8 1368.1

136.9 93.6 594.4 793.4 1338.6 674.6 2419.4 1378.0 101.9 49.8 128.0 326.8 5.0 6.9 4.3 12.7 13.1 7.7 26.7 61.4 1583.7 787.9 1576.7 213.8 46.1 154.6 471.9 141.9 e e 870.6 77.9 e e 1093.8 457.9 25.3 18.8 577.8 1049.1

0.0 n.d. 29.0 170.2 26.1 n.d. 4.8 378.6 n.d. 5.0 39.5 240.4 n.d. n.d. 3.8 n.d. n.d. n.d. 23.9 29.7 449.1 142.5 519.9 73.2 n.d. 26.4 338.8 35.9 n.d. n.d. 632.7 n.d. n.d. n.d. 472.7 109.7 19.2 n.d. 346.5 513.9

337.2 (A2) 232.3 (A2) 1500.4 (A2) 2237.6 (A2) 3328.4 (A2) 1704.0 (A2) 6041.6 (A2) 3981.9 (A2) 261.1 (A2) 122.5 (A2) 402.9 (A2) 1183.2 (A2) 14.2 (A2) 19.8 (A4) 14.8 (A4) 33.8 (A2) 31.6 (A4) 18.9 (A1) 95.2 (A2) 202.3 (A4) 4410.5 (A2) 2044.6 (A4) 4902.4 (A2) 568.4 (A4) 115.4 (A3) 422.1 (A4) 1428.5 (A4) 332.1 (A4) n.d. n.d. 3207.7 (A4) 190.9 (A3) n.d. n.d. 3309.2 (A4) 1369.8 (A4) 94.3 (A4) 47.5 (A4) 1889.5 (A4) 3134.2 (A4)

1.7 n.d. 44.6 353.6 53.7 38.9 125.2 658.9 18.1 24.0 124.0 467.0 9.0 6.0 10.1 16.1 17.6 n.d. 35.1 90.9 2130.5 527.8 2392.4 208.5 53.0 80.2 573.4 119.3 n.d. n.d. 1491.9 n.d. n.d. n.d. 967.3 440.8 42.8 1.7 528.8 944.4

Phenanthrene

Fluoranthene

p,p’-DDE

Terbuthylazine

Chlorpyrifos

m-Chlorpyrifos

Propyzamide

Pendimethalin

Chlortal-dimethyl

n.d.: not detected (concentration below the limit of detection). bql: below quantification limit.

the waters of the Mar Menor lagoon, as suggested in a previous
lez et al., 2013b) to explain the homogeneous study (Moreno-Gonza distribution found in seawater for some pesticides in this system. The highest mean annual concentration was found for chlorpyrifos (1493 pg m3), which was similar to those detected in South China (Li et al., 2014) and Iowa (Peck and Hornbuckle, 2005) but  et al., 2010) and Italy lower than those found in France (Coscolla (Estellano et al., 2015). The highest concentration of chlorpyrifos (4902 pg m3) was higher than the maximum values detected in Algeria (Moussaoui et al., 2012), Brazil (Meire et al., 2012), Czech Republic (Koblizkova et al., 2012) and China (Li et al., 2014), but lower than those found (97,770 pg m3) in the Central Region of  et al., 2010) and in Spain (Borra
s et al., 2011). France (Coscolla Chlorpyrifos and chlorpyrifos-methyl were the most ubiquitous OPPs and were found in all seasons, as was also observed in Tuscan air (Estellano et al., 2015). However, diazinon was only detected in spring and winter, and trichloronate only in winter. Chlorpyrifos concentrations were significantly lower in winter than in the remaining seasons (Table 3), as was also observed in urban and rural sites from the Tuscany region (Estellano et al., 2015) and with the active sampler in our study. The lowest input through El
n watercourse to the Mar Menor lagoon also occurred in Albujo winter (Moreno-Gonz
alez et al., 2013a). Therefore, a certain similarity was confirmed between surface water input of contaminants

and their potential air deposition in the lagoon. The maximum concentrations of this insecticide were found at A2 and A4, which are the rural stations closest to agricultural crops. 3.6. PAHs The most frequently detected PAHs (>79% samples) were fluoranthene, fluorene and particularly phenanthrene (95.8%) (Table 2). The highest concentration of all considered analytes of this study was found for phenanthrene (6041.6 pg m3), a value corresponding to the lower ranges detected in other areas (Birgül et al., 2011; Bozlaker et al., 2009). The highest concentrations for the majority of PAHs homologues were found at A2 (San Javier-Murcia Airport) in all seasons (Tables 3 and 2S and Fig. 5), showing the relevance of this source of PAHs in the Mar Menor area, the effective dilution of the airport source and the lower relevance of other anthropogenic sources. Naphthalene and pyrene were the exception, their maximum concentrations being found at A6 and A4 respectively. Acenaphthene, fluorene, phenanthrene and fluoranthene were detected in all seasons. However, the remaining PAHs were mainly detected in winter despite the high population density during summer, probably due to the high solar irradiation and temperatures, which could favour their photodegradation and volatilization, even in the sorbed PUF


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

391

Fig. 5. Seasonal distribution of phenanthrene and fluoranthene in air at six different sampling points located on the perimeter of the Mar Menor lagoon.

fraction. A second factor may be the greater width of the planetary boundary layer in summer and spring due to the thermal turbulence that favours dispersion and dilution in air (Santacatalina et al., 2012; Yubero et al., 2011). It is also necessary to consider that air mass circulation in summer and spring is of preferentially eastern origin (from the sea and away from point sources), representing 50% of all winds in this period. In winter north-western circulation alternates with stagnant conditions allowing all terrestrial sources to feed air mass composition (see Fig. 1S). Concentrations of acenaphthylene and fluoranthene were significantly higher in winter than in the other seasons (Tables 3 and 2S). Phenanthrene concentrations in Mar Menor seawater were also higher in winter than
lez et al., 2013b), conin the remaining seasons (Moreno-Gonza firming their highest presence in this period in both environmental compartments. The highest concentrations of the most abundant PAHs (phenanthrene and fluoranthene) were found in winter at all sampling points (Fig. 5), except for phenanthrene close to the airport (A2) which reached its maximum value in autumn. 3.7. Triazines Terbuthylazine was the most commonly detected triazine (>75% of samples) (Table 2), being found in all autumn and winter samples (Table 3). Terbuthylazine is a commonly-used herbicide in lemon tree crops, one of the most relevant in Campo de Cartagena (4300 ha), and uncultivated areas (Sanz-Navarro, 2008). This pesticide revealed greater persistence in comparison with other triazine herbicides (Navarro et al., 2004), showing half-lives in seawater of 76 and 68 days at 20 and 40  C respectively. As was the case for PAHs, terbuthylazine showed higher concentrations in winter than in the other seasons at all sites as a consequence of the higher application of herbicides to control herbal growth in the agricultural areas than in other seasons. The highest concentration found was similar to that detected in German Bight (Mai et al.,


n 2013). The predominant input of this triazine through El Albujo watercourse was also found in winter (64% of annual input) (Moreno-Gonz
alez et al., 2013a). Prometon and secbumeton were also detected but only in winter at A3 station. 3.8. Other pesticides The herbicide chlortal-dimethyl was detected in 87.5% of samples (Table 2), being found in all seasons for the most common crops in the area (lettuce, broccoli, potato, tomato and melon). Pendimethalin, propyzamide, cyprodinil, propoxur and oxyfluorfen were also detected preferentially in winter and autumn but only in 50%, 29%, 29%, 12% and 4% of samples, respectively (Tables 2 and 3). As was the case for PAHs and terbuthylazine the highest concentrations for chlortal dimethyl were found in winter at all sites. However, the maximum values for the herbicides propyzamide and pendimethalin were obtained in autumn (Fig. 6). These results are
n in agreement with the seasonal inputs observed through El Albujo
lez et al., watercourse for the same compounds (Moreno-Gonza 2013a). The proximity of the agricultural fields on the east coast of the lagoon led to higher pesticide concentrations at these sampling points as a result of the prevailing winds, especially when the sampling site is not located in an urban area. Propyzamide, pendimethalin and chlortal-dimethyl showed maximum concentrations slightly over 3 ng m3. The concentration of chlortal-dimethyl was higher than the maximum concentration found in Sydney (Koblizkova et al., 2012). The concentration of pendimethalin was similar to the maximum concentration found in the Mississippi River area (Majewski et al., 1998), lower than that  et al., 2010) and higher than those refound in France (Coscolla ported in Ontario, the North Sea and the Tuscany region (Gouin et al., 2008; Mai et al., 2013; Estellano et al., 2015). Propyzamide was not detected in other areas (Coscoll a et al., 2010); to the best of our knowledge this study is the first in which this herbicide was detected in air, it having previously been detected in rainwater

392


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

Fig. 6. Seasonal distribution of current use pesticides (terbuthylazine, chlortal dimethyl, chlorpyrifos, propyzamide and pendimethalin) in air at six different sampling points located on the perimeter of the Mar Menor lagoon.

(Asman et al., 2005) and surface and seawaters (Moreno-Gonz
alez et al., 2013a,b). Propyzamide was only detected in autumn and winter in all sites (Tables 3 and 2S). This herbicide is commonly used in lettuce (3332 ha), brocculi, cauliflower (2955 ha) and endive (330 ha) crops (www.carm.es), which are the most widely planted in autumn and winter in the Campo de Cartagena area. Mean concentrations of propyzamide were higher in autumn than

in winter (p < 0.05). The predominant input of propyzamide
n watercourse also occurred in both seasons and through El Albujo the highest concentrations for this herbicide were found in winter
lez et al., 2013a). Other compounds were also (Moreno-Gonza detected, but only in one or two seasons, such as propoxur, oxyfluorfen and cyprodinil in winter. The fungicide cyprodinil was commonly used in the main greenhouse crops (pepper, cucumber,


et al. / Chemosphere 167 (2017) 382e395 A. Carratala

zucchini, etc.) and outdoor lettuce crops from autumn to spring. Mean concentrations of diazinon and cyprodinil were also lower than those found in France (Coscoll a et al., 2010). No significant seasonal variations were found for the other pesticides considered in this study. Tributylphosphate was also present because of its use as a solvent in fungicide and herbicide concentrates and other uses. Pesticides showed the highest concentrations close to the extensive crop areas (A2 and A4), in particular for chlorpyrifos, chlorpyrifos-methyl and pendimethalin (Fig. 6). The levels were within the upper ranges detected in Galveston Bay (Park et al., 2001) but lower than those detected in another intensive agricul
lez et al., 2004). tural area in Spain, Almería (Egea-Gonza A heterogeneous distribution of organic pollutants in air was observed around the Mar Menor lagoon, showing concentrations from below detection limit to 20e3000 pg m3 for the majority of analytes. The high variability of air concentrations observed for organic pollutants is in all probability a consequence of the specific analyte uses, their physicochemical properties, the predominant meteorological conditions, the sampling point and the season of the year (seasonal applications of some pesticides). The high spatial and seasonal variability observed for organic pollutants was related to pollutant physicochemical properties, their seasonal application pattern, the proximity of pollutant sources and the effect of the predominant meteorological conditions (wind intensity and direction, temperature, etc.) during the period studied. In this sense sea breeze (eastern circulation) could transport local emissions away from the lagoon in spring and summer, while those emissions could be concentrated in winter and autumn due to more stagnant conditions and to their transport to the lagoon by the prevailing NW wind. Despite the great analytical effort made, only a small fraction of all organic pollutants potentially present in air samples was determined, confirming the seasonal exposure of population to PAHs and pesticides, as has been also shown in other urban and rural areas. In fact the adverse effect of OPPs has been recently confirmed in a fertility study developed in Murcia Region (Melgarejo et al., 2015). The implementation of good agricultural practices (e.g. avoiding pesticide treatments on windy days) can contribute to reduce population exposure. Furthermore, this study has confirmed the input of PAHs and pesticides through air deposition to the Mar Menor lagoon and surrounding coastal areas. 4. Conclusions This study reveals the influence of the intensive agriculture areas and urban nuclei surrounding the Mar Menor lagoon on seasonal air concentrations. The measured concentrations reported reflect characteristic local sources rather than background atmospheric contamination: the majority of pesticides found in this study were related to vegetables and fruit crops from the surrounding area, except for organochlorine pesticides, which have remained in soils as a result of their previous use. The presence of 32 organic contaminants (PAHs, PCBs and pesticides) determined by active sampling was confirmed in the particulate phase, but more particularly in the gas phase, with the exception of certain herbicides and the heaviest PAHs. The concentrations determined in this study were similar to those detected in other agricultural areas. The sampling rates of passive samplers were determined for all analytes detected, considering preferentially winter data due to the probability of losses (breakthrough) in active sampling during summer (higher temperatures and solar irradiation). Furthermore, active and passive samplers detected a similar number of contaminants (32 and 28 respectively). The most commonly detected contaminants (>95% of samples) in air were chlorpyrifos, chlorpyrifos-methyl and phenanthrene, and the

393

maximum concentrations corresponded to phenanthrene (6000 pg m3), chlorpyrifos (4900 pg m3) and several pesticides at 3000 pg m3 (propyzamide, pendimethalin and chlortal-dimethyl). The distribution of contaminants was spatially and seasonally heterogeneous, showing the highest concentrations of PAHs close to the airport and those of pesticides in the influence area of agricultural fields (western stations). PAH and herbicide concentrations were higher in winter than in the other seasons, although some insecticides such as chlorpyrifos were more abundant in autumn. The high temperatures, solar irradiation and greater atmospheric dispersion in summer reduced the potential effect of the ten-fold increase in population during this period. The observed spatial heterogeneity in air confirmed that dry deposition should also be heterogeneous in the lagoon, being higher close to the main pollutant sources. This study demonstrates the high spatial and seasonal variability of air deposition for PAHs and pesticide in coastal areas, which should be considered as significant source for these contaminants, and confirmed the continuous population exposure to few ng m3 concentrations for some of these chemicals. Acknowledgements This research has been supported by the Spanish InterMinisterial Science and Technology Commission “DECOMAR” (CICYT, CTM2008-01832) and IMPACTA (CTM2013-48194-C3-1-R) projects, and by the European Union through the European
n Moreno-Gonza
lez Regional Development Fund (ERDF). Rube wishes to thank the Spanish Ministry of Science and Innovation for the FPI grant (BES 2009-014713). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.chemosphere.2016.09.157. References
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