Science of the Total Environment 473–474 (2014) 576–588

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Integrated assessment of air pollution using observations and modelling in Santa Cruz de Tenerife (Canary Islands) José M. Baldasano a,b,⁎, Albert Soret a, Marc Guevara a, Francesc Martínez a, Santiago Gassó a,b a b

Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS), Earth Sciences Department, Jordi Girona 29, Edificio Nexus II, 08034 Barcelona, Spain Environmental Modelling Laboratory, Technical University of Catalonia, Avda. Diagonal 647, Edificio H, Oficina 10.23, 08028 Barcelona, Spain

H I G H L I G H T S • • • • •

Integrated assessment of air pollution using observations and modelling Santa Cruz de Tenerife is affected by specific pollution episodes. Significant emission, meteorological and orographic conditions play a key role. The refinery plume plays an important role in the SO2 levels. Particulate matter episodes are caused by intrusions of Saharan dust.

a r t i c l e

i n f o

Article history: Received 26 August 2013 Received in revised form 12 December 2013 Accepted 12 December 2013 Available online 4 January 2014 Keywords: Air pollution High-resolution air quality modelling Atmospheric dynamics Anthropogenic emissions Santa Cruz de Tenerife (Canary Islands)

a b s t r a c t The present study aims to analyse the atmospheric dynamics of the Santa Cruz de Tenerife region (Tenerife, Canary Islands). This area is defined by the presence of anthropogenic emissions (from a refinery, a port and road traffic) and by very specific meteorological and orographic conditions—it is a coastal area with a complex topography in which there is an interaction of regional atmospheric dynamics and a low thermal inversion layer. These factors lead to specific atmospheric pollution episodes, particularly in relation to SO2 and PM10. We applied a methodology to study these dynamics based on two complementary approaches: 1) the analysis of the observations from the air quality network stations and 2) simulation of atmospheric dynamics using the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b and WRF-ARW/HYSPLIT modelling systems with a high spatial resolution (1 × 1 km2). The results of our study show that the refinery plume plays an important role in the maximum SO2 observed levels. The area of maximum impact of the refinery is confined to a radius of 3 km around this installation. A cluster analysis performed for the period: 1998–2011 identified six synoptic situations as predominant in the area. The episodes of air pollution by SO2 occur mainly in those with more limited dispersive conditions, such as the northeastern recirculation, the northwestern recirculation and the western advection, which represent 33.70%, 11.23% and 18.63% of the meteorological situations affecting the study area in the year 2011, respectively. In the case of particulate matter, Saharan dust intrusions result in episodes with high levels of PM10 that may exceed the daily limit value in all measurement station; these episodes occur when the synoptic situation is from the east (3.29% of the situations during the year 2011). © 2013 Elsevier B.V. All rights reserved.

1. Introduction The impact of air quality on human health has been widely studied (WHO, 2006, 2013). In Europe, atmospheric pollution is regarded as one of the environmental factors that has the greatest impact on human health (EEA, 2005). This conclusion has led to a significant increase and standardisation of network monitoring and modelling techniques for atmospheric pollution. The European Commission has shown great interest in the dynamics and transportation of pollutants to ensure

⁎ Corresponding author. E-mail address: [email protected] (J.M. Baldasano). 0048-9697/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scitotenv.2013.12.062

compliance with legislation and to inform the population about pollutant levels (EC, 2008). The legislation is particularly demanding when air pollution concentrations exceed certain thresholds and limit values, in which case a detailed diagnosis of territorial areas exceeding the pollution levels and a forecast of the evolution of the air quality levels are demanded. The articles 6, 7, 10 and 14 of the 2008/50/CE Directive (EC, 2008) recommend that analyses of air quality levels are supplemented with measurements that are based on the use of modelling techniques or objective estimations to assess the air quality. The maximum levels and corresponding allowable exceedances that have been established by legislation (EC, 2008) continue to be exceeded in Europe, particularly in Spain (de Leeuw and Vixseboxse, 2010). With

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respect to SO2, the urban population that is exposed to levels that are higher than the legal limits has declined significantly in recent decades (EEA, 2010). Nonetheless, in the Canary Islands (Fig. 1a), and more precisely in the city of Santa Cruz de Tenerife, SO2 levels remain high, surpassing legislative limits in 2011. This is the only area in Spain in which the hourly (350 μg m− 3) and daily limits (125 μg m−3) are exceeded (MAGRAMA, 2012). The interaction between the synoptic and local dynamics in areas of complex topography has a significant effect on air quality levels (Baldasano et al., 1994; Perez et al., 2004; Rodriguez et al., 2008; Flocas et al., 2009). The Canary Islands benefit from the dispersion and transport that involve trade winds (Morales and Perez, 2000). However, in the case of Santa Cruz de Tenerife, the combination of anthropogenic emission sources: refinery, port and road traffic, and the Islands' singular meteorological and orographic characteristics lead to specific pollution episodes. Those singular characteristics include the following: 1) The interaction between topography and prevailing winds. At a synoptic level, the prevailing winds in the area are the so-called trade winds, i.e., moderate to strong winds from the northeast. These

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winds interact with the complex topography of the island of Tenerife (Fig. 1b) (including the Mount Teide (3718 m amsl) in the centre of the island and the mountains of Anaga (992 m amsl) upwind of Santa Cruz de Tenerife (Fig. 1)), which results in the development of geographic effects in the lower layers of the atmosphere (Jorba et al., 2008). 2) The local winds present daily cycles marked by breezes due to the coastal location. This means that, during the day, the sea breeze favours the transport of pollutants from the coast (where the port and refinery are) to the town of Santa Cruz de Tenerife (Rodriguez et al., 2008). 3) The ocean current that bathes the Canary Islands is a cold current (the Canary Current). Therefore, surface air masses are cold and wet, which leads to the presence of thermal inversion approximately between 900 and 1200 m (Cuevas et al., 2012), that hinders convective motions. Saharan dust intrusions have a strong impact on air quality because of the proximity of the Canary Islands to the African continent (approximately 300 km) and the Azores anticyclone (CórdobaJabonero et al., 2011; Alonso-Pérez et al., 2011a, 2011b). The result

Fig. 1. Location of the Canary Islands (top left) and the major topographical features of Tenerife Island (top right). Details of the study area (5 km radius).

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of Alonso-Pérez et al. (2007) shows an average duration of the intrusion of approximately three days, with most significant events occurring in March. With respect to particulate matter from anthropogenic sources, Rodriguez et al. (2008) indicate that the main source of PM10 and PM2.5 (b10 and 2.5 μm in diameter, respectively) is the emission from road traffic and that photo-oxidation processes contribute significantly to the concentration of ultrafine particles. González and Rodríguez (2013) add that background levels of ultrafine particles are caused by traffic emissions and that elevated levels of photo-oxidation result from emissions from port activities and the refinery. Guerra et al. (2004) analysed O3 episodes in Tenerife and determined that the elevated levels recorded are caused by the long-distance transport of such pollutants from northern latitudes and from local emissions of primary pollutants that affect urban areas and downwind of major emission sources. Milford et al. (2008) present a statistical prediction system of Tenerife air quality based on measurements and a model based on analogue method obtaining the meteorological parameters from the global model ECMWF (25 × 25 km2 spatial resolution). The results highlight the need to work with a system consisting of a mesoscale meteorological model and a photochemical model (Limited Area Model) of higher spatial resolution that is particularly important in coastal areas and areas with complex topography. This finding led to the development of a high spatial resolution (2 × 2 km2) air quality forecasting system for the Canary Islands, CALIOPE-CAN (http://www.bsc.es/caliope-can) which uses the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b coupled model system (Baldasano, 2010). This study aims to analyse the atmospheric dynamics of the area affecting the city of Santa Cruz de Tenerife during 2011 to determine the impact of emissions (particularly from the oil refinery) on air quality, in particular SO2 and PM10. To achieve this goal, we employ a methodology that is based on two complementary approaches: the analysis of the observations from the network of air quality stations in the area, and the application of modelling techniques at high spatial resolution (1 × 1 km2). 2. Methodology This study analyses the atmospheric dynamics in the area of Santa Cruz de Tenerife in 2011. The work is based on: 1) Analysis of the observations from the network of air quality stations for the pollutants SO2, NO2, O3, PM10 and PM2.5, which provides timely information of air pollution in the locations of these stations. The study area has an extensive network of 11 air quality stations (Table 1) that are mostly concentrated in the urban area near the refinery and the port (Figs. 1c and 2). 2) A selection of six representative days of prevailing weather patterns and application of air quality modelling at high spatial (1 × 1 km2) and temporal (1 h) resolutions, which will help explain the

atmospheric dynamics and confirm the findings that result from the analysis of the observations. Prior to the application of the air quality modelling, the synoptic patterns affecting the study region were identified. A cluster analysis of back trajectories, calculated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) (Draxler and Rolph, 2013; Rolph, 2013), was performed following the methodology described in Jorba et al. (2004). Six-hourly atmospheric back trajectories of two days duration directed toward Santa Cruz de Tenerife at an altitude of 500 m above ground were used in the analyses. The backward trajectories were calculated at 12 UTC. The database was composed for the period: 1998–2011 from The National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). The cluster analysis was used to objectively identify the dominant synoptic patterns. Besides, for the selection of the representative day for each specific pattern was used the following information: Meteosat satellite images, data from air quality stations, the radio soundings in Tenerife, and the emissions from the refinery (see Appendix A). The representative days were simulated using the Eulerian air quality modelling system: WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b. In addition, main conclusions regarding the most significant point source of the area (the refinery) were confirmed by using a Lagrangian approach: the HYSPLIT model driven by the WRF-ARW meteorological model results. The WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b coupled modelling system represents the state-of-the-art in air quality modelling. The Weather Research and Forecasting (WRF) meteorological model (Michalakes et al., 2004; Skamarock and Klemp, 2008) provides weather information as an input to the photochemical Model-3 Community Multiscale Air Quality (CMAQ) model (Byun and Schere, 2006). The final working domain covers an area of 252 × 252 km2 with a high spatial (1 × 1 km2) resolution, temporal (1 h) resolution, and 33 σ vertical levels with 12 characterising the planetary boundary layer (PBL). The model top is defined at 50 hPa to resolve the troposphere–stratosphere exchanges properly. Tenerife Island is a coastal area characterised by a very complex terrain. Thus, simulations require the use of models with high spatial and temporal resolution to properly reproduce atmospheric dynamics (Baldasano et al., 2008a). In order to provide adequate boundary and initial conditions, the model system was run on three regional scales: D1 including Europe and northern Africa (12 × 12 km2); D2 including Canary Islands (4 × 4 km2), and D3 also including Canary Islands (2 × 2 km2) with hourly temporal resolutions (see Appendix B). A one-way nesting was performed from one domain to the other in order to retrieve the meteorological and air quality conditions to the final domain. Chemical boundary conditions for the parent domain were provided by the global climate chemistry model LMDz-INCA2 (Hauglustaine et al., 2004; Folberth et al., 2006). The Dust REgional Atmospheric Model (BSC-DREAM8b) (Basart et al., 2012) was designed to simulate and predict the atmospheric

Table 1 List of meteorological and air quality stations in the area of Santa Cruz de Tenerife and their pollution measurements. Stations

LAT (°)

LON (°)

Altitude (m)

SO2

NO2

PM10

PM2.5

O3

Casa Cuna Merca Tenerife Refinery Vuelta Los Pájaros Depósito Tristán García Escámez La Granja Park Los Gladiolos Tome Cano Tena Artigas Piscina Municipal

28.2704 28.2637 28.4540 28.4620 28.4582 28.4566 28.4630 28.4587 28.4622 28.4554 28.4580

−16.1640 −16.1643 −16.2664 −16.2770 −16.2787 −16.2719 −16.2649 −16.2684 −16.2619 −16.2768 −16.2633

178 125 79 158 197 120 78 93 67 167 66

x x x x x x x x x x x

x x

x x

x

x

x x x x x x x

x x

x x

x x x x

x

x x x x x x x

x x

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Fig. 2. Top: hourly SO2, daily PM10 and hourly NO2 air quality levels for all stations in the study area in 2011, arranged chronologically from January 1st to December 31th. Below: hourly levels of SO2, PM10 and NO2 arranged according to wind direction (from 0° to 360°) for the Piscina Municipal, Depósito Tristán and Casa Cuna stations.

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Table 2 Specific parameterisations of the CMAQ, WRF-ARW and BSC-DREAM8b models. Model

Meteorology

Chemistry

Mineral dust

Model version

WRF-ARW v3

CMAQ v4.5

BSC-DREAM8b

Dom. (Nx, Ny, Nz, km × km) (33 sigma vertical layers up to 50 hPa, with 12 under PBL

D1: 480, 400, 33, 12 ∗ 12 D2: 219, 117, 33, 4 ∗ 4 D3: 304, 204, 33, 2 ∗ 2 D4: 252, 252, 33, 1 ∗ 1 NCEP/FNL 1° × 1º

D1: 480, 400, 33, 12 ∗ 12 D2: 219, 117, 33, 4 ∗ 4 D3: 304, 204, 33, 2 ∗ 2 km D4: 252, 252, 33, 1 ∗ 1 D1: LMDz-INCA2 D2, D3 and D4: • IC: 24-h Spin-up • BC: parent domain Chemical Model: cb4 Aerosol Model: AERO4 (sea-salt: Gong, 2003; Zhang et al., 2005) Adv: Yamartino mass- conserving Dif: Eddy diffusivity theory Aerosol d.v.: aero-depv2 Dry d.r.: Models-3

D:196, 256, 24, 1/3° × 1/3°

IC/BC

Parameterisations

Boundary l.:YSU Microphysics: WSM3 Cumulus Scheme: KainFritsch Land Surf. Mod.: Noah Long Wave: RRTM Short Wave: Dudhia

cycle of mineral dust. The BSC-DREAM8b uses offline coupling and its outputs are then simply added to the CMAQ-calculated particulate matter. The specifications and parameterisations of the model system are summarised in Table 2. For further information see Appendix B. The HERMESv2 model (High Elective Resolution Emission Modelling System v2.0; Guevara et al., 2013) provides the emissions for the air quality model. HERMESv2 is an updated version of the original HERMES2004 model (Baldasano et al., 2008b) in terms of data and methods, which was specifically developed for the whole Spanish territory (including Canary Islands and Balearic Islands) and features a spatial resolution of 1 × 1 km2 and a temporal resolution of 1 h. It combines a comprehensive database with updated methodologies for estimating anthropogenic and biogenic emissions. In the present study, emissions from all sources ranked by the Sources Nomenclature for Sources of Air Pollution (SNAP) have been considered (Section 4.1). Given the main emissions sources of the area (refinery, road traffic and port), the specific modules for estimating these emissions are detailed: combustion in energy industries (SNAP01), road transport (SNAP07) and maritime (SNAP08). In the module on emissions from combustion processes in energy industries (SNAP01—power plants, refineries and coke industries), the emissions factors have been defined based on measured data provided by the Spanish National Office of Emission Control for Large Combustion Facilities (OCEM-CIEMAT), with 333 total plants in Spain. In the specific case of the Tenerife refinery, measured emissions (including height, exhaust gas temperature, etc.) on an hourly basis for the main 15 sources (Government of the Canary Islands, personal communication) were implemented in the emission model. Emissions from road transport (SNAP07) were estimated based on the method described in EEA TIER 3 (EEA, 2009), implemented to calculate Emissions from Road Transport 4 (COPERT 4). The digital traffic map contains specific traffic intensity (daily average traffic, [vehicles·day−1]), the average speed (km·h−1), and the vehicle fleet as adapted to the COPERT 4 categories (256 categories) for each track section. This information was obtained by post-processing information from the following: (1) traffic intensity at 755 points (based on traffic capacity provided by the Canarian Government), (2) statistical vehicular fleet composition by province (NUT 3) (DGT [General Directorate for Road Traffic], 2010) and (3) the digital Spanish road network (Tele Atlas® MultiNet®, 2011). Additionally, the model also considers the emissions of particulate matter caused by resuspension from paved road (Pay et al., 2011). The estimation of maritime emissions (SNAP0804) is based on the methodology described in Entec UK Limited (2007, 2010), which divides the activities of vessels into two main operations: manoeuvring

NCEP/FNL 1° × 1°

Nickovic et al., 2001 8-bin size distribution within the 0.1–10 μm radius range Long Wave: RRTM Pérez et al. (2006a, 2006b)

and hoteling. Information on the annual operations and Gross Tonnage (GT) by vessel type and port was obtained from the annual reports of each Spanish port authority (AAPP, 2009). Fuel consumption factors and EFs are based on Cooper and Gustafsson (2004). Finally, once the refinery was identified as the main source, HYSPLIT version 4 was used to produce forward dispersion pattern from the refinery in order to confirm the main findings from the analysis of the air quality data observations and WRF-ARW/HERMESv2/CMAQ/BSCDREAM8b results. The domain in HYSPLIT was the same as in WRFARW/HERMESv2/CMAQ/BSC-DREAM8b simulations with a spatial resolution of 1 × 1 km2 and a temporal resolution of 1 h. HYSPLIT model was implemented with meteorological fields derived from the WRFARW simulations. 3. Analysis of air quality observations The air quality levels measured at the stations in the Santa Cruz de Tenerife city in 2011 (Canary Government, 2009, 2012) were analysed for SO2, NO2, O3, PM10 and PM2.5. All these stations are located on an area with a 5 km radius that includes the city of Santa Cruz de Tenerife and its metropolitan area where an additional effort was made to provide a deeper analysis of the atmospheric and air quality dynamics (hereafter, the “study area”) (Fig. 1c). The hourly air quality levels of SO2 exceeded the legal maximum limit (350 μg m−3 not to be exceeded in more than 24 occasions) at four stations (Fig. 2a), including the Piscina Municipal (maximum of 1325 μg m− 3; legal limit exceeded on 46 occasions), the Refinery (707 μg m−3; 11 occasions), La Granja Park (463 μg m−3; 1 occasion) and Tomé Cano (1241 μg m−3; 5 occasions). It is noteworthy that the hourly levels differ significantly between the stations, although they are all close to one another geographically. Whereas the Piscina Municipal station registered a maximum hourly value of 1325 μg m−3 and the hourly legal limit was exceeded on 46 occasions, at Los Gladiolos station – located just 500 m away from the Piscina Municipal – the maximum recorded value was 307 μg m−3 and did not exceed the legal limit. An analysis of the hourly levels at different stations reveals that high levels do not coincide temporally (Fig. 2a), it may indicate the presence of a significant source of SO2, which affects areas differently depending on the specific atmospheric dynamics. This was also confirmed by the study of air quality levels as a function of wind direction and by a dynamic analysis based on the model results (Section 4). The Piscina Municipal station registered the highest SO2 levels, exceeding twice the threshold of public warning (500 μg m−3) during 2011. The Piscina Municipal station also recorded the highest maximum daily levels, exceeding the legal limit (125 μg m−3, not to be exceeded on

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more than 3 occasions) on 4 occasions. The Tomé Cano station exceeded this limit once. The second pollutant that implies air quality levels exceedances is the particulate matter (PM10 and PM2.5). All stations in the area exceeded the legal daily limit of PM10 between 3 and 25 times (50 μg m−3 not to be exceeded on more than 35 occasions) (Fig. 2b). The average annual levels for all the stations in the Santa Cruz de Tenerife city ranged between 20 and 24 μg m−3 (with an annual limit of 40 μg m−3) and between 7 and 10 μg m−3 for PM2.5 (annual limit of 25 μg m−3). The periods of high concentration of particulate material coincided in all the stations (Fig. 2b) and coincided with the 24 Saharan dust episodes identified by the CALIMA system in 2011 (http://www. calima.ws/). Regarding NO2, none of the stations in the study area exceeded the hourly (200 μg m− 3) or annual (40 μg m− 3) legal maximum value (Fig. 2c). The highest hourly value was registered in Los Gladiolos station (199 μg m−3), whereas Casa Cuna registered the highest annual mean value (27 μg m−3). The maximum hourly concentration for O3 was 133 μg m− 3 (Tena Artigas), and the threshold for public information (180 μg m−3) was not exceeded by any of the stations of the study area. The analysis of the hourly air quality levels of SO2, NO2, PM10 and PM2.5 according to wind direction (Fig. 2d–l) offers important information about local dispersion patterns. For this analysis, three stations with air quality and meteorological information were selected, including the Piscina Municipal, Depósito Tristán and Casa Cuna. Regarding SO2, for the 46 times of which the maximum hourly level (350 μg m−3) was exceeded at the Piscina Municipal station, the wind came from the south (Fig. 2f). At the Depósito Tristán station, the highest SO2 levels correspond to higher local southerly winds coming from the refinery (Fig. 2e), which suggests that the refinery plume has an effect on the SO2 levels of these stations. At the Casa Cuna station, the elevated SO2 levels correspond to northeastern winds (Fig. 2d). This station is constrained by its location, southwest of the city and the refinery, on the slope of a mountain, which results in orographic wind channelling. For particulate matter, the highest levels do not relate to any local wind direction pattern (Fig. 2g, h and i). At a synoptic level, particulate matter pollution in the study area is mainly caused by episodes of Saharan dust intrusion with synoptic winds from the east. In the Casa Cuna and Depósito Tristán stations (2 g and 2 h), there are three peaks that exceeded 300 μg m−3 of PM10. These levels correspond to three consecutive hours on December 9th, 2011 (02–04 UTC), synoptically characterised by the presence of an anticyclone over the Azores that involved the movement of Saharan dust toward the Canary Islands (east–west direction). Nonetheless, for those hours, the observed direction at the local level is northwest, which is related to recirculation caused by the breeze regime. In the remaining stations, high levels of particulate matter are observed for the same period because of the regional behaviour of mineral dust pollution (Pay et al., 2012). The registered increase in the levels of the finer fraction of particulate matter (PM2.5) and low levels of other pollutants is an additional evidence that indicates the contribution of mineral dust to particulate matter, it helps exclude the contributions of other sources (refinery, maritime and road traffic). With respect to NO2, the observed concentrations show a more homogeneous pattern for the whole annual period (Fig. 2j, k and l), and no peak above the legal hourly limit (200 μg m−3) was registered. For the Piscina Municipal station (Fig. 2l), the wind directions related to higher NO2 average levels are southern (caused by the refinery plume effect) and northwestern (caused by traffic emissions recirculated through night breezes in a land–sea direction). In Depósito Tristán station, the highest levels were recorded for the northwestern direction (Fig. 2k) related to road traffic emissions. Finally, in the case of Casa Cuna station, as in the case of SO2, orographic channelling facilitated higher levels coming from the northwest (Fig. 2j).

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4. Modelling results In this section, specific emissions in the study area will first be analysed. Next, the results of the cluster analysis are presented, through which the six patterns that define the synoptic meteorology of the study area have been obtained; following this analysis, the representative day of each of these patterns were selected and analysed. The analysis of simulations by the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b and WRF-ARW/HYSPLIT model systems are performed for each of the six synoptic patterns. The aim was to confirm the initial hypotheses through the analysis of the observations, i.e., that high levels of SO2 in the Santa Cruz de Tenerife area are caused by the refinery plume and that particulate matter episodes are caused by intrusions of Saharan dust. 4.1. Analysis of emissions in the area Emissions by pollutant and sector in the area of Santa Cruz de Tenerife city (5 × 5 km2) are analysed in order to determine the contribution of each source to the total emissions. Those emissions were estimated using the HERMES model v2. In Appendix C, the emissions inventory from HERMES v2 is compared to the Spanish Inventory System. The study area registers three main emission sources: the refinery, road traffic and maritime activities in ports (Table 3). Total SOx emissions are equal to 2723 Mg/year. The refinery emissions can be categorised as emissions from power generation (SNAP01) and emissions from torches (SNAP09). In general, refinery emissions represent 78% of total SOx emissions: 1769 and 347 Mg/year (SNAP01 and SNAP09, respectively). The second source of SOx emissions are from maritime activities in ports (SNAP08, 12%), which have been significantly reduced in recent years by reducing the sulphur content of marine fuels (EC, 2005). SOx emissions from road traffic (SNAP07) are also significantly lower, 21 Mg/year, primarily because of the reduction of sulphur content in fuels (EC, 2003). Road traffic is the main source of NOx, PM and CO. For NOx, 56.7% were traffic (SNAP07): 1632 of 2879 Mg/year; however, NOx emissions from the refinery are also significant, accounting for 40.3%. Regarding PM, road traffic accounts for 61.0% of total emissions: 250 to 410 Mg/year; the refinery contributes to 24.9% of emissions; and maritime activities in ports (SNAP08) is the third source with 13.2%. In the case of CO, emissions from road traffic (SNAP07) are the most significant (EEA, 2009), especially in urban areas like the Santa Cruz de Tenerife, the 92.6% of the emissions come from road traffic: 4401 of 4753 Mg/year. Finally NMVOC emissions are more scattered, the main source of emissions are maritime activities in ports (SNAP08), 29.8% of emissions: 1389 to 4657 Mg/year. 4.2. Trajectory calculations and cluster analysis, predominant synoptic meteorological situations To objectively characterise and quantify the atmospheric dynamics of the study area from a synoptic perspective, a cluster analysis of back trajectories for 2011 was performed and its results were compared to the corresponding climate analysis for the period 1998–2011. Subsequently, based on the results of this analysis, a representative day for each dynamic pattern was selected to be simulated and analysed (Section 4.3). The cluster analysis grouped the back trajectories directed toward Santa Cruz de Tenerife at 500 m agl into the six major groups shown in Fig. 3. In each group, trajectories are shown in blue for the winter and in red for the summer. The main synoptic situations identified were the following: 1. Fast advection from the NE, associated with trade winds. The presence of the anticyclone located over the Azores induces flows from the northeast on the Canary Islands. This situation is characterised by moderate to strong winds.

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Table 3 Emissions by SNAP sector (Mg/year) for Santa Cruz de Tenerife (5 × 5 km2). Mg/year

SOx

NOx

PST

CO

NMVOC

SNAP01: combustion in energy and transformation industries SNAP02: non-industrial combustion plants SNAP03_04: combustion in industry and production processes SNAP05: extraction and distribution of fossil fuels and geothermal energy SNAP06: solvents and other product use SNAP07: road transport SNAP08: port activities SNAP09: refinery's flare stacks SNAP10: agriculture SNAP11: biogenic TOTAL Total refinery (SNAP01 and SNAP09) % refinery % road transport % port activities % rest of sectors

1769 1 245 0 0 21 340 347 0 0 2723 2116 78% 1% 12% 9%

914 31 16 0 0 1632 41 243 0 1 2879 1158 40% 57% 1% 2%

101 2 1 0 0 250 54 1 1 0 410 102 25% 61% 13% 1%

83 18 43 0 0 4401 127 54 3 23 4753 137 3% 93% 3% 1%

38 5 588 839 683 890 1389 9 1 213 4657 47 1% 19% 30% 50%

2. Fast advection from the NW. These situations are characterised by strong entries associated with the cold and intense north-western winds. 3. Advection from E. These situations are characterised by a strong influence of the anticyclone over the Iberian Peninsula that induces eastern flows to the Canary Islands; they are associated with intrusions of Saharan dust over the archipelago that are typical of the winter period. 4. Advection from W. Advective situations involving a western component that are characterised by moderate to strong winds from the western Atlantic. 5. NE recirculation. These situations are characterised by a lowpressure gradient on the Canary Islands. Air masses evolve from the north to the archipelago with moderate to low speeds. 6. NW recirculation. These situations are characterised by atmospheric situations involving low-pressure gradients over the islands. The winds are weak with a variable component.

(US-EPA) developed model guidelines (US-EPA, 1991, 2005) defining several statistical goals for operational model performance. Although there is no criterion for a “satisfactory” model performance, US-EPA (1991, 2005) suggested values of ± 10–15% for the mean normalized bias error (MNBE), ±15–20% for the unpaired peak prediction accuracy (UPA) and 30–35% for the mean normalized gross error for concentrations above a prescribed threshold (MNGE) to be met by modelling simulations of O3, to be considered for regulatory applications. The statistical values obtained as a result of the evaluation (Table 4) (e.g. the average MNGE for selected air quality stations is 15% for O3 predictions, 24% for NO2, and 26% for SO2 and PM10) meet the criteria established in the US EPA Guidelines (US EPA, 1991, 2005) and the uncertainty objectives set by the European Directive (2008/50/EC). It confirms the need for working with fine grids for addressing air quality processes in urban and industrial areas in complex terrains.

4.4. Analysis and discussion of the simulation results Fig. 3 shows the occurrence of the identified groups on a monthly basis for year 2011 and the 1998–2011 period. Situations with a northeastern component (advections and recirculation) are the most significant, especially in summer. The northwestern advections, characterised by stronger winds, are less significant, particularly in summer. Situations with eastern and western winds are more typical of the winter period. The situations with low-pressure gradients (recirculation) are significant throughout the annual period. The results for the year 2011 are consistent with the period from 1998 to 2011 when the specific characteristics of each year are smoothed over the entire period. In 2011, the western winds are more prevalent than for the entire period, whereas the western component recirculation is less significant. Similarly, the northeastern advection is more significant in the summer of 2011 than for the 1998–2011 period. 4.3. Model validation The WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b model system has been extensively evaluated in the context of the CALIOPE_CAN project, both externally (Canary Government, 2010) and internally, through a near-real-time system (http://www.bsc.es/caliope-can/?q= node/71). In addition, in the framework of this work, hourly air quality data from the air quality stations have been used to evaluate the performance of WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b simulations explicitly. The European Directive 2008/50/CE (EC, 2008) defined an uncertainty of 50% as the maximum error of the measured and calculated concentration levels. Also, the US Environmental Protection Agency

When analysing the air quality levels measured in the air quality stations network, the main effect caused by emissions from the refinery is observed in the concentrations of SO2. Hence the present analysis based on model results has particularly emphasised this pollutant. To conduct a separate analysis of the refinery effect, two emission scenarios are simulated with the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b model system: WITH and WITHOUT. The WITH scenario considers all the emissions in the study area, while the WITHOUT scenario considers all the emissions except those related to the Tenerife refinery. Thus, the difference between the two scenarios determines the specific effect of that source. One of the conclusions drawn by analysing the measured levels of SO2 is that the effect of the refinery plume on the study area is localised. Thus, to determine the primary area of influence of the refinery, Fig. 4 shows modelled SO2 increases caused by the refinery plume in relation to the distance to the refinery for each of the six predominant weather patterns. The situations characterised by increased atmospheric stability present higher increases because of lower dispersive conditions. The highest modelled increase for SO 2 during western conditions (24/01/2011) is 105.8 μg m−3. The situations involving northeastern and northwestern recirculation register similar SO2 levels (02/07/ 2011 and 06/04/2011, respectively) and exceed 30 μg m−3. In the three northeastern, northwestern and eastern situations, the air quality levels are lower and do not exceed 30 μg m−3. With respect to distance, the highest SO2 increases are limited to a radius of 3 km around the installation. Beyond that distance, increases are below 30 μg m−3; for distances over 5 km, the increments are below 20 μg m−3.

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Year 2011

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Period 1998-2011

Fig. 3. Upper panel: Results of the cluster analysis of the back trajectories directed toward Santa Cruz de Tenerife at 500 m snt for 2011 (left), and for the 1998–2011 period (right) [Back winter trajectories: blue, back; summer trajectories: red]. Lower panel: Monthly occurrence of six clusters (in percentage) identified during the study period for 2011 (left) and the period from 1998 to 2011 (right).

With respect to NO2, the air quality increases due to the refinery plume are significantly lower. The modelled increases do not exceed 40 μg m−3 in any of the weather patterns analysed. The most significant increases are again observed for the western situations (24/01/2011),

Table 4 Summary of the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b model system evaluation for the days of study.

O3 NO2 SO2 PM10

MNBE (%)

MNGE (%)

UPA (%)

Correlation coefficient

−6.86 −17.86 −6.83 −18.84

14.77 23.52 25.98 25.44

−15.71 −24.83 −25.72 −22.46

0.75 0.73 0.68 0.63

with a maximum value of 38.85 μg m−3. In all other situations, the increments were below 20 μg m−3. Next subsections analyse the atmospheric dynamics and their influence on air quality levels for each of predominant weather patterns were analysed using the results from the models. First, we analyse those situations with favourable dispersive conditions, in which synoptic dynamics play a strong role that dominates local processes; those situations in which local dynamics play a larger role are analysed last. 4.4.1. NW and NE advection The northwestern and northeastern situations (represented by days July 23 and November 21, 2011) are similar in terms of atmospheric dynamics; therefore, these situations are considered together. At a synoptic level, both situations are characterised by the effect of the Azores anticyclone that leads to northerly winds in Santa Cruz de Tenerife.

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Fig. 4. Hourly increases in emission levels of SO2 (top) and NO2 (bottom) caused by the refinery plume for the 6 representative days of the study. WRF-ARW/HERMESv2/CMAQ model system.

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Northwestern situations are less common (7.95% compared to 25.21% for northeastern situations in 2011) and are associated with colder and stronger winds. The ridge of the island, where the Mount Teide stands, acts as an orographic barrier for air masses. Air masses split when they encounter and go around the obstacle (Fig. 5a). On the leeward side (south area), convergence zones occur that produce weaker flows in this area (3–4 m/s). At this point, eddies are formed, in the zone of convergence upward movements of air masses are observed, which may even lead to the emergence of orographic clouds. In the northern part of the island (Fig. 5b), northeastern winds particularly affect the Santa Cruz de Tenerife area. Humid air masses in contact with the ocean reach Tenerife. In their attempt to circumvent the Anaga mountain range, they ascend the mountainside and initiate a condensation process, which sometimes results in the formation of orographic clouds and precipitation (Foehn effect). On the opposite side, there is an abnormal elevation of the temperature, a decrease of the relative humidity and increase the speed and wind gusts. Such increases of wind speed downwind in the Anaga mountain range increase the dispersive conditions in the area, which are already favourable because of the synoptic situation; this causes relatively good air quality. The maximum levels remained below 40 μg m−3 SO2. Synoptic pattern day of study % 2011 % 1998-2011

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Fig. 5c and d depicts refinery plume at 10 UTC for the WRF-ARW/ HERMESv2/CMAQ/BSC-DREAM8b and WRF-ARW/HYSPLIT simulations, respectively. At 10 UTC, both simulations show how the plume flows to the south with levels below 5 μg m− 3 SO2. The maximum increases caused by the emissions from the Tenerife refinery were below 20 μg m−3 SO2 (Fig. 5e). Those increases are limited to a radius of 4 km south of the installation. Regarding the other pollutants, PM10 levels did not exceed 40 μg m−3, and NO2 levels did not exceed 25 μg m−3. 4.4.2. Advection from East The advection from East (represented by day December 23, 2011) shows moderate to strong eastern winds (Fig. 5f), which represents 3.29% of the situations in 2011. On the eastern side of the island, the air masses move parallel to the coast and avoid the obstacle presented by the ridge of the island. In the south of the island, the formation of eddies may be observed; in the convergence zone, air masses tend to rise because of orographic lifting. On the western side of the island, there are also areas of convergence that originate recirculation. In the northern part of the island (Fig. 5g), air masses are slowed by the ridge of the island when approaching the area of Santa Cruz de Tenerife. The speeds observed in the area are on the order of 3–4 m/s.

Wind streams Tenerife Island

Wind streams Northern Tenerife

Refineries plume (SO2) Northern Tenerife (SO2; µg m-3 )

Refineries plume (SO2) Northern Tenerife (SO2; µg m-3 )

Hourly maximum increase due to refinery emissions Studio area (SO2; µg m-3 )

WRF

WRF

WRF/HERMESv2/CMAQ

WRF/HYSPLIT

WRF/HERMESv2/CMAQ

Advection NE (NE) 23 July 2011 NE: 25.21% (2011) 28.82 (1998-2011) NW: 7.95% (2011) 9.64% (1998-2011)

a 15 UTC

b 10 UTC

c 10 UTC

d

e

i

j

n

o

t

u

y

z

10 UTC

East (E) 23 December 2011 3.29% (2011) 8.70% (1998-2011)

f 4 UTC

West (W) 24 January 2011 18.63% (2011) 5.72% (1998-2011)

g 13 UTC

k 2 UTC

Recirculation N-E (RNE) 2 July 2011 33.70% (2011) 31.92% (1998-2011)

l

p

Recirculation N-W (RNW) 6 April 2011 11.23% (2011) 15.14% (1998-2011)

10 UTC

9 UTC

10 UTC

s 9 UTC

w 14 UTC

13 UTC

m

r

v 13 UTC

13 UTC

10 UTC

10 UTC

h

9 UTC

x 14 UTC

14 UTC

Fig. 5. Wind streams and SO2 levels for the days of study, from left to right: wind streams (U10) over Tenerife Island; detail of wind streams (U10) at NE Tenerife; air quality levels of SO2 caused by refinery emissions (μg m−3) for a selected time step (WRF-ARW/HERMESv2/CMAQ model system); air quality levels of SO2 caused by refinery emissions (μg m−3) for a selected time step (WRF-ARW/HYSPLIT); and detail of the hourly maximum SO2 increase caused by refinery emissions.

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During the early hours of the day, the prevailing winds in the area move south along the coast and blow the plume of the refinery area away from the island. Beginning at 9 UTC, prevailing winds veer slightly, showing a more marked easterly component. As a result, in the area of Santa Cruz de Tenerife, the winds that moved south parallel to the coast ascend the slope of the ridge as katabatic winds (directed toward the west-northwest) and slow down (b3 m/s). This decrease in speed leads to increased levels of pollutants locally between 9 and 19 UTC. This behaviour enables the ascension of the refinery plume over the Aguere Valley, moving over the city of Santa Cruz de Tenerife. Fig. 5h and i shows refineries plume for the WRF-ARW/HERMESv2/CMAQ/ BSC-DREAM8b and WRF-ARW/HYSPLIT simulations at 13 UTC, respectively. The refinery plume affects the southern part of Santa Cruz de Tenerife. Observed hourly levels of SO2 were below 70 μg m− 3. The maximum hourly SO2 increases are registered along the coastline, south of the refinery (Fig. 5j). Although the eastern situation may be associated with mineral dust intrusion, as discussed above, there was no intrusion on this particular day. Hourly levels of PM10 and NO2 were lower than 40 and 90 μg m−3, respectively. 4.4.3. Advection from West The advection from West represents 18.63% in 2011 (represented by day January 24, 2011). The results from the meteorological model indicate that the island of Tenerife was affected by moderate western winds. Initially, the winds have a strong west-northwestern component (0–7 UTC) and as the day progresses, the winds veer slightly and show a west-southwestern component, beginning at 17 UTC. Such moderate winds, between 3 and 5 m/s, experience a reduction in speed when they come into contact with the orographic barrier of the Tenerife Island, which results in the formation of the so-called “barrier jets” parallel to the coastline and windward of the island. Such flows are formed when a surface flow hits an orographic barrier with a mountain pass on its left side. Because the winds are unable to lift over the obstacle (essentially the mountain range crowned by Mount Teide), they veer left and surround it. The “barrier jets” circulate parallel to the orographic barrier and always veer to the left in the northern hemisphere. Leeward of the island, there are convergence zones producing weaker flows and eddies (Fig. 5k). These eddies are of weak intensity (less than or equal to 3 m/s). As shown in detail in Fig. 5l, the Aguere Valley (which connects the Anaga with the Esperanza mountains on the dorsal side of the island) forms a corridor between the windward and leeward sides of the island. This situation produces a “Venturi effect” and intensifies the airstream as it passes through a narrowing in the terrain. Leeward of that narrowing is an increase in wind speed. Thus, although January 24, 2011, registered moderate winds from the west, the area of Santa Cruz de Tenerife experienced slightly stronger winds (4–7 m/s) and explains why the air quality levels in Santa Cruz de Tenerife are relatively good (b 20 μg SO2 m−3) during the early hours in the day. These low levels are caused by the dispersion produced by the channelisation of the Aguere Valley, which directs the emissions seaward. As the hours pass (10 UTC), synoptic winds veer to the north, which weakens the Venturi effect and the appearance of vortices downwind, locally, these have a clear effect in winds weaken. This results in the recirculation of air masses and the consequent decrease in the dispersive potential of the area. In this situation, the refinery emissions that were blown out to sea in the early morning hours are recirculated over the area. This implies a significant increase in SO2 levels, which exceed 120 μg m−3. Fig. 5m and n depict how the refinery plume affects Santa Cruz de Tenerife for the WRF-ARW/HERMESv2/CMAQ/BSC-DREAM8b and WRF-ARW/HYSPLIT simulations, respectively. The SO2 contribution of the refinery at its maximum impact exceeds 100 μg m−3. With their gradual turn toward the north (18 UTC), the winds, which hit the orographic barrier of the Mount Teide, form a jet barrier on the

left side of the southern coast of the island. The winds that move along the right side experience an increase in speed (5–6 m/s), which slows down when reaching the area surrounding Santa Cruz de Tenerife because of the proximity of the Anaga Mountains. Thus, during the last hours of the day, new vortices are formed in the area of Santa Cruz de Tenerife, causing a new recirculation of the main emissions in the area. Under these conditions, the plume of the refinery affects the study area (Fig. 5o), and the local recirculation of pollutants resulted in maximum SO2 levels around the Santa Cruz de Tenerife refinery area, which exceeds 100 μg m−3, and an SO2 contribution from the refinery that exceeds 75 μg m−3. However, the air quality levels of PM10 and NO2 are less than 30 and 100 μg m−3, respectively. 4.4.4. Northeastern recirculation The northeastern recirculation (represented by day July 2, 2011), shows weak winds from the northeast, which comprise 33.70% of the situations that occurred in 2011. This situation is similar to that of the northwestern and northeastern advections at a synoptic level but with more moderate winds. Air masses that approach the island are slowed because of the orographic obstacle. The incident flow is separated and flows around both sides of the island. On the western side, winds move parallel to the coast and swirl in the south of the island (Fig. 5p). In the north area of the island (Fig. 5r), the situation is complex. First, air masses that bypass the island on its eastern side travel at high speeds parallel to the coast. Second, the Foehn effect that is produced by the Anaga mountains leads to increased wind speeds and the appearance of streaks in the lee of these mountains. Third, the Aguere valley also channels the winds from the north of the island and increases their speed. The result is the emergence of convergence zones that create eddies in the area of Santa Cruz de Tenerife. Analysing the Santa Cruz de Tenerife area in detail shows that the Tenerife refinery plume is blown offshore by strong winds during the early hours. As convergence zones (and consequently eddies) form, winds weaken and do not maintain a specific direction. In addition, the boundary layer is below 600 m (12 UTC) and hinders convective movements. Under these dispersive conditions, which are reduced particularly between 9 and 15 UTC, the refinery plume (Fig. 5s and 5t) is recirculated inland and the air quality consequently deteriorates, exceeding 30 μg m−3 SO2 near the refinery (Fig. 5u). With respect to particulate matter, that day was preceded by a period of Saharan dust intrusion, which implies elevated PM10 concentrations (hourly levels b110 μg m−3). In the case of NO2, the hourly levels were below 70 μg m−3. 4.4.5. Northwestern recirculation The northwestern recirculation (represented by day April 6, 2011), accounts for 11.23% of the situations in 2011. The day is marked by a weak wind (2–3 m/s) with no marked synoptic direction. During the early hours of the day, the winds from the north are shielded in the north of the island because of the front formed by land breezes that disappear with the appearance of the first rays of the sun and the heating of the surface. Downwind of the ridge of the island, eddies are formed in convergence zones (Fig. 5v). Due to the recirculation meteorological situation, the winds did not show a marked synoptic direction and, as the day progressed, the wind veered and blew with a southern component (from 9 UTC). In the north of the island, the predominant direction change had a significant impact. The winds that affect the Santa Cruz area are trapped in the Anaga Mountains. This effect implies reduced speed in flowing over the obstacle (Fig. 5w). As a result, the refinery plume moves north and the greatest impact occurs on the city of Santa Cruz between 14 and 21 h (Fig. 5x and v). This situation results in increased daytime SO2 pollution values, which exceed the legal limit of 350 μg m−3 SO2. The maximum effect of the refinery plume takes place on the city of Santa Cruz de Tenerife (Fig. 5z). For PM10 and NO2, hourly levels do not exceed 40 μg m−3 and 110 μg m−3, respectively.

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5. Conclusions This study has analysed and evaluated the air quality in the area of Santa Cruz de Tenerife in 2011 to determine the impact of emissions in the area, especially those emissions caused by the oil refinery. This analysis has identified the main factors that lead to exceedances of air quality levels. These factors are very specific; meteorological and orographic conditions that hinder dispersive conditions in the area (i.e., coastal zone, interaction of regional atmospheric dynamics and complex terrain, low thermal inversion layer), and the presence of significant emission sources in the area. Two complementary approaches were used. First, the analysis of the observations measured by the air quality stations network provides timely air quality data at the specific locations. Second, selecting study days that represent the different dominant meteorological patterns and applying modelling techniques with high spatial (1 × 1 km2) and temporal (1 h) resolutions enable the analysis of the interaction of local atmospheric dynamics and dominant synoptic patterns with the topography of the area. The results show an important role for refinery emissions in the exceedances of the legal limits of SO2 levels. The oil refinery plume has a local effect in the vicinity of the installation, and the maximum area of influence of the refinery is located in a radius of 3 km surrounding the refinery. Air quality levels of NO2 do not exceed maximum legal levels; the main emission source is road traffic and is complemented by the refinery emissions. Six meteorological patterns synoptic situations – northwestern, northeastern, eastern, western, northeastern recirculations and northwestern recirculations – were identified. Episodes with high SO2 and NO2 air quality levels originate from meteorological situations with more limited dispersive conditions, i.e., the northeastern recirculation, the northwestern recirculation and the western advection, which represent a combined 64% of the situations from 2011. Conversely, trade winds situations (northeastern and northwestern) are characteristic of the area (33.16% of the situations, 2011) and lead to favourable dispersive conditions. With respect to particulate matter levels, the episodes of high concentration are related to episodes of Saharan dust intrusion. The synoptic pattern that favours these episodes is eastern, which is mainly registered during the winter and represents 3.29% of the situations from 2011. This methodology has allowed linking poor air quality levels with emission sources in an area of complex terrain. The methodology described herein may be applied to study the impact on air quality caused by different emission sources and also to the study of atmospheric dynamics in areas characterised by a complex topography, such as Santa Cruz de Tenerife. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2013.12.062. Acknowledgment Authors gratefully acknowledge the support given by the Canary Government, Ministry of Education, Universities and Sustainability and to the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and READY website (http://www.ready.noaa.gov) used in this publication. Simulations were carried out on the MareNostrum supercomputer of the Barcelona Supercomputing Center–Centro Nacional de Supercomputacion. References AAPP. Spanish Port Authorities. Annual reports; 2009 [http://www.puertos.es/sites/ default/files/memorias_anuales/2009/index.html, April 2012]. Alonso-Pérez S, Cuevas E, Querol X, Viana M, Guerra JC. Impact of the Saharan dust outbreaks on the ambient levels of total suspended particles (TSP) in the marine

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