Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city

Journal Pre-proof Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city E. Triantafyllou, E. Diapouli, Μ.Β. Korras-Carraca, M. Manousakas, C. Psanis, A.A. Floutsi, C. Spyrou, K. Eleftheriadis, G. Biskos PII:

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https://doi.org/10.1016/j.apr.2019.12.015

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Atmospheric Pollution Research

Received Date: 13 August 2019 Revised Date:

13 December 2019

Accepted Date: 16 December 2019

Please cite this article as: Triantafyllou, E., Diapouli, E., Korras-Carraca, Μ.Β., Manousakas, M., Psanis, C., Floutsi, A.A., Spyrou, C., Eleftheriadis, K., Biskos, G., Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city, Atmospheric Pollution Research, https://doi.org/10.1016/j.apr.2019.12.015. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.

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Contribution of locally-produced and transported air pollution to particulate matter in a small insular coastal city

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E. Triantafyllou1,*, E. Diapouli2, Μ.Β. Korras-Carraca1, M. Manousakas2, C. Psanis1, A.A. Floutsi3, C. Spyrou4, K. Eleftheriadis2, and G. Biskos3,5,*

9 10 11 12 13 14 15 16 17

1

2

3

Department of Environment, University of the Aegean, Mytilene 81100, Greece

Environmental Radioactivity Lab, I.N.Ra.S.T.E.S., N.C.S.R. Demokritos, 15310 Ag. Paraskevi, Attiki, Greece

Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft 2628-CN, The Netherlands

4

School of Physics, National and Kapodistrian, University of Athens, Athens, Greece 5

Energy Environment and Water Research Centre, The Cyprus Institute, Nicosia 2121, Cyprus

18

Submitted: August 2019

19

Revised: December 2019

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Atmospheric Pollution Research

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*To Whom Correspondence Should be Addressed

1

1

Abstract

2

The concentrations, size distributions, and elemental compositions of the atmospheric

3

aerosol over a small but representative (in terms of size, population, and geographical

4

characteristics) insular coastal city in the North Aegean Sea were measured during

5

winter and summer. Mean PM2.0 and PM1.0 concentrations at the city centre were

6

respectively 26 and 21 µg m-3 during the cold period, and 21 and 15 µg m-3 during the

7

warm period. Although these concentrations are considerably lower compared to

8

corresponding values of PM2.5 and PM1.0recorded in large cities in the region, they are

9

still very close to the mean annual standards set by the EU for PM2.5. Higher average

10

mass (by ca. 26-36% for Total Suspended Particles, PM2.0 and PM1.0) were observed

11

in the cold period compared to those in the warm period, due to the additional

12

emissions from domestic heating and the weaker atmospheric dilution. The elemental

13

composition measurements showed that crustal and anthropogenic elements (i.e., K,

14

Ca, Ti, Mg, Fe, As, S) in the collected particle samples were also enriched when

15

polluted air masses were transported from Northeastern Turkey. These measurements

16

also showed that natural sources contribute sea-salt and re-suspended soil to the

17

particulate matter load in the city’s atmosphere. Non-exhaust traffic emission sources

18

were also found to be an important contributor, as indicated by the good correlations

19

(R2 = 0.40 - 0.91) between crustal and traffic-related elements (i.e., Zn, Cr, Cu, and

20

Mn). Overall, PM measurements in the urban environment in the region are relatively

21

high, being influenced by both local sources and long-transported air masses.

22

Keywords: Air quality, PM pollution, Atmospheric aerosols, Northeastern

23

Mediterranean.

2

1

1. Introduction

2

Urban air quality is affected by natural and anthropogenic sources of particulate

3

matter (PM) and gaseous species that can cause adverse effects upon human health

4

(e.g., Lelieveld et al., 2015; Stafoggia et al., 2017). Although the concentrations of

5

main air pollutants has been decreasing in large European cities during the last decade

6

(Guerreiro et al., 2014), airborne particles having sizes smaller than 2.5 µm (i.e.,

7

PM2.5) often exhibit values above or close to the EU annual standard (25 µg m-3),

8

mainly due to the numerous and intense anthropogenic sources, including

9

transportation, domestic combustion processes and industrial activities (Manousakas

10

et al., 2015; Diapouli et al., 2017a; Mamali et al., 2018).

11

The air quality in small cities is believed to be better than that in large urban

12

agglomerations, whereas microclimate in urban areas can be greatly affected by the

13

local conditions and the densely constructed urban complex (Dimoudi et al., 2013).

14

Previous studies, however, have shown that small cities can be influenced by major

15

particle sources under certain meteorological conditions. In the small agricultural city

16

of Ciudad Real (75000 inhabitants) in Spain, for instance, high PM2.5 concentrations

17

are mostly influenced by crustal sources and transported air masses from the Sahara

18

desert, while vehicular traffic accounts for only 14% of those concentrations (Aranda

19

et al., 2015). In contrast, in Lycksele and Gundsømagle, two small Scandinavian

20

cities, the high concentrations of coarse and fine particles (PM10, PM2.5 and PM1.0)

21

that are typically observed in winter, are the result of local traffic and wood

22

combustion emissions in combination with low air temperatures and stable weather

23

conditions (Krecl et al., 2008).

24

Apart from local/regional sources, air quality in small cities may be significantly

25

affected by transported air pollution from distant sources under specific 3

1

meteorological conditions (i.e., wind direction and speed). A number of observations

2

at coastal sites in the region of the Eastern Mediterranean have shown that high PM

3

concentrations are in many cases linked to air masses transported from Africa and the

4

Middle East (e.g., Sciare et al., 2008; Floutsi et al., 2016). Especially for the region of

5

the Northern Aegean Sea (NAS), air quality at remote locations in the region can be

6

significantly affected by polluted air masses transported from Eastern Europe and the

7

Black Sea during summer (Bezantakos et al., 2013; Tombrou et al., 2015;

8

Triantafyllou et al., 2016). Despite this evidence, however, there is still insufficient

9

information on the quality of the air in coastal urban areas in this region and on the

10

influence of the local and distant sources during the warm, and cold period.

11

The aim of this work is to investigate the contribution of local and distant sources to

12

the air quality in small insular cities. To do so we characterize the atmospheric aerosol

13

and investigate the potential sources of PM pollution at a small, yet representative,

14

insular coastal city in the background marine environment of the NAS during winter

15

and summer. More specifically, we measured the concentrations, size distributions, as

16

well as the elemental composition of the atmospheric aerosol particles in the city of

17

Mytilene, and related them with transported air masses from different regions.

18

2. Methods

19

2.1. Study areas and meteorology

20

Measurement campaigns were conducted in the city of Mytilene (39° 10΄ N, 26° 20΄

21

E), which is the capital of the island of Lesvos. The island is located in the region of

22

the NAS, as shown in Fig. 1, and is very close to Turkey. In total, two campaigns

23

were carried out: one during the cold period from 27 January to24 February 2014 (27

4

1

– 55 day of year), and one during the warm period from 24 June to 15 July 2014 (175

2

– 195 day of year).

3

Mytilene is a small but densely populated city (ca. 1600 people/km2; 30000

4

inhabitants in total), which serves as the main port of the island of Lesvos. The main

5

air pollution sources in the city include the port activities, the thermal (fuel oil fired)

6

power plant located at the suburbs of the city, and the international airport, which is

7

located ca.8 km away from the city (cf. Psanis et al., 2017, for details).Another major

8

contributor to air pollution is traffic, which can be a significant source at many

9

locations of the city as a result of the narrow roads that cause high congestion,

10

especially during rush hours. PM concentrations were measured simultaneously at

11

two measurement sites installed at the centre (i.e., at Sapfous Square of Mytilene,

12

SSM) and at the port (i.e., at the Port Authorities of Mytilene, PAM) of the city, as

13

shown in Fig. 1.

14

Both sampling sites were located in an open area at ca. 10 m above sea level (a.s.l.).

15

Each site was selected to capture the impact of different sources on local air quality.

16

SSM can be considered as a representative site affected by everyday human activities

17

(transportation, heating, etc.) since it is less than 100 m from the city centre with direct

18

access to the sea, whereas PAM is mainly affected by all the activities related to the

19

port as it is at its centre and a few tens of metre from the port docks.

20

A number of meteorological parameters, including temperature, relative humidity,

21

wind speed and direction, were provided by the meteorological station located at the

22

airport of the island (at an elevation of about 4 m a.s.l.). To identify the origin of the

23

air masses reaching the measurement sites during the campaigns, we calculated back-

24

trajectories using the NOAA HYSPLIT model (Stein et al., 2015; Rolph et al., 2017).

25

Back trajectories were obtained at ground level and at a height of 500 and 2500 m 5

1

a.g.l. over the sampling sites in order to estimate the impact of long range transport of

2

anthropogenic air pollution and desert dust. In addition, days with desert dust episodes

3

were identified using the online NMMB/BSC-dust transport model (Pérez et al., 2011;

4

Haustein et al., 2012)and the SKIRON/Dust model (Spyrou et al., 2010). Finally, the

5

simulated boundary layer height was derived from ECMWF reanalysis data, with a

6

temporal resolution of 6h and a spatial resolution of 0.75° (Uppala et al., 2005).

7

Although the resolution of this model is not that high, it provides a good

8

approximation of the boundary layer height above our study region.

9

2.2. Measurements and analytical methods

10

Total Suspended Particle (TSP) samples were collected at both sites (SSM and PAM)

11

every 8h during the cold and warm periods of the campaign, using a custom-made

12

sampler (constructed according the Part 50 of the 40th Code of Federal Regulations;

13

US Environmental Protection Agency, 2006) operated at a flow rate of 13 lpm. The

14

TSP sampling periods were scheduled during the day (between 7:00 and 15:00), the

15

evening (between 15:00 and 23:00) and the night (between 23:00 and 7:00 the next

16

morning).These time periods corresponded to the rush hours of the traffic and of the

17

port activity. In addition to TSP samples, particle mass size distributions in the range

18

from 0.1 to 3.2 µm were measured at SSM using a Micro-Orifice Uniform Deposit

19

Impactor (MOUDI; Model 110R; MSP Corporation, Shoreview, MN) operated at a

20

flow rate of 30 lpm for 48 h continuously for each sample. The different stages of the

21

MOUDI had 50% particle cut sizes of 18, 10, 5.6, 3.2, 1.8, 1.0, 0.56, 0.32, 0.18, and

22

0.10 µm. Using these measurements we also determined the mass concentrations of

23

particles having sizes in the range 0.1µm
24

provide good approximations of PM2.0 and PM1.0, respectively (Robert et al., 2007;

25

Sun et al., 2015). All samplers operated simultaneously using a common inlet tube

6

1

(made of conductive silicone) that had a total length of ca. 6 m, and was kept straight

2

for most of its length to minimize particle losses.

3

A total of 47 TSP samples (27 during the campaign conducted in the winter and 20 in

4

the summer), as well as 19 PM2.0 and PM1.0 samples (9 during winter and 10 during

5

summer) were collected respectively every 8 and 48h on quartz filters (Whatman QM-

6

A quartz filters 47 mm in diameter, 2 µm pore size, Part No.Z675032).Prior to

7

sampling, the filters were heated at 450°C for 12 h to remove any organic residues.

8

An electronic microbalance with a resolution of 0.01 mg (Kern &Sohn Model 770)

9

was used to weigh the filters, which were conditioned under controlled temperature

10

and moisture conditions (20 ± 2 °C and 50 ± 5% RH) for 48 h before and after

11

sampling.

12

After collection and final weighing, the samples were wrapped in aluminium foils,

13

sealed in plastic containers and stored in a freezer at – 20 °C until analysed. The

14

majority of the TSP, PM2.0 and PM1.0 samples (35 out of 48 for TSP and 19 out of 19

15

for PM2.0 and PM1.0) collected during the two sampling periods were further analysed

16

for a number of elements (i.e., Na, Cl, S, Ca, Ti, K, Cr, Mg, Mn, Fe, Ni, Zn, Ba, Cu

17

and As) using a high resolution energy dispersive X-ray fluorescence spectrometer

18

(Model PANalytical Epsilon 5). Concentrations in field blanks were determined and

19

subtracted from every reported value of each sample. Calculated limits of detection

20

(LOD) for the above-mentioned elements ranged from1×10-5to 3×10-2µg m-3, with

21

precisions ranging from0.2 to 19%.Details of the XRF analysis and quantification are

22

described in Manousakas et al. (2017).

23

2.3. Data analysis

7

1

For the analysis of the chemical composition measurements and to serve the

2

comparison between the two seasons, we used a range of tools. Those include the

3

Student’s t-test (with a p-value of 0.05), correlation analysis of elemental

4

concentrations in the TSP as well as in PM2.0 and PM1.0 samples, and calculations of

5

the enrichment factor (EFs) for each element and season. The EF of an element X for

6

each PM sample is determined by (IAEA, 1992):

EF =

(/)   (1) (/)

7

where C is a reference element of crustal origin, which is usually chosen among Al,

8

Si, Sc, Mn, Ti, Fe (Reimann and Caritat, 2000; Sutherland, 2000). In all cases

9

presented here we used Ti as a reference element, because it exhibited the lowest

10

enrichment factors among the detected reference elements for all PM fractions during

11

both periods. The elemental composition of the Earth’s crust was taken from

12

Wedepohl (1995). EF values larger than 10 suggest that anthropogenic sources

13

dominate the investigated samples, while EF values lower than 5 indicate that

14

elements are of crustal origin. EF values between 5 and 10 correspond to elements

15

that originate from both natural and anthropogenic sources (IAEA, 1992).

16

3. Results and discussion

17

3.1. Particle mass concentrations

18

In general, particle mass concentrations were higher during cold compared to warm

19

period. As shown in Fig. 2a, the measured average concentrations of TSP, PM2.0 and

20

PM1.0 at SSM were higher by ca. 32%, 26% and 36%, respectively, during the cold

21

period than during the warm period. This observation is consistent with similar

22

measurements in other cities that are reported in the literature (Carbone et al., 2010;

23

Triantafyllou and Biskos, 2012), and can be attributed to i) the additional emissions 8

1

from domestic heating during winter, and ii) the lower dilution associated to the

2

weaker winds and the lower boundary layer heights (ca. 39%; i.e., average values

3

calculated by WRF - Chem model) in colder compared to warmer periods (cf. Table

4

1).

5

The prevailing winds in our study area during the cold period had mainly northeast

6

direction (50 % frequency) with low to medium wind speeds (reaching up to 5.7 m s-

7

1

8

strongly with speeds ranging from 2.0 to 9.3 m s-1. Weaker winds in cold period

9

compared to those in the warm period were observed over nearby areas (Odabasi et

10

al., 2002). During the cold period, 30% of the sampling days had calm conditions

11

(wind speed < 1 m s-1), during which the contribution of local sources to the quality of

12

the air is increased (Voutsa et al., 2002).

). In the warm period the prevailing winds were from the northwest and blew

13

TABLE 1

14

Average TSP concentrations at the two sampling sites observed during the warm

15

period were 61 µg m-3 at SSM and 79 µg m-3 at PAM (cf. dashed lines in Fig. S1a in

16

the supplement), with the difference being statistically significant as indicated by the

17

Student’s t-test using a p-value of 0.05. This difference can be attributed to the higher

18

emissions from the enhanced activities at PAM during the cold period (compared to

19

the warm), and the fact that ship emissions did not affect significantly the city centre

20

(i.e., SSM) due to the northern winds that prevailed (cf. Fig. S3).

21

In contrast, the respective values during the cold period were 80 and 84 µg m-3 (cf.

22

dashed lines in Fig. S2a), but those were not statistically significantly different,

23

suggesting that the two sampling sites are similarly affected by all the local sources in

24

this case. The PM2.0 and PM1.0 concentrations recorded at the SSM site had average

9

1

values of 26 and 21 µg m-3 during the cold period and 21 and 15 µg m-3 during the

2

warm period, respectively (cf. dashed lines in Figs. S1b and S2b). These

3

measurements are lower (by ca. 20 – 40% in the cold and 18 – 50% in the warm

4

period) compared to those observed in urban environments of larger cities in Greece,

5

such as Thessaloniki and Athens (Kassomenos et al., 2012; Voutsa et al., 2014; Tolis

6

et al., 2015) as a result of the lower anthropogenic activity (e.g., traffic and heating),

7

but still very close to the mean daily limit values set by the WHO for PM2.5 (WHO,

8

2006).

9

PM measurements are affected by local sources, but can also be attributed to long-

10

range transport of polluted air masses. As indicated by back trajectory calculations, in

11

ca. 57% of the cases during cold period campaign and 80% during the warm period

12

campaign, the observed air masses were in the polluted region of Northeastern Turkey

13

and the Black Sea ca. 30 h before reaching the measurement sites in our study (cf.

14

Fig. S4a and S4b). Consequently, the PM concentrations observed during the warm

15

period in the city are affected by the industrial and urban anthropogenic sources

16

(including traffic; Odabasi et al., 2010; Koçak et al., 2011) of the Eastern region of

17

Turkey and by the shipping emissions from the nearby waterways connecting the

18

Black Sea (Kesgin and Vardar, 2001; Deniz and Durmuşoğlu, 2008) to the

19

Mediterranean and from there to the rest of the globe.

20

Days with favourable synoptic conditions for Saharan Dust transport over the North

21

Aegean region were also observed (cf. periods identified by the gray-shaded areas in

22

Figs. S1 and S2 and results of back-trajectory analysis and of the SKIRON Model

23

shown respectively in Figs. S4 and S5). In all cases the transportation of natural dust

24

occurred over small-scale dust events (i.e., events during which the daily particle

10

1

concentrations reached values of 200–1000 µg m-3; Draxler et al., 2001; Escudero et

2

al., 2006). During days with desert dust transport, the TSP, PM2.0 and PM1.0

3

concentrations were in average ca.40% higher compared to the days when the air

4

quality was affected primarily by local emissions (cf. Fig. 2b).This is not surprising

5

given that the Eastern Mediterranean is frequently affected by long-range dust

6

transport (Gkikas et al., 2013; Floutsi et al., 2016), with reports showing that particle

7

concentrations can increase by up to 120 % at other rural/coastal sites of the region

8

(Gerasopoulos et al., 2006; Koçak et al., 2007; Lazaridis et al., 2008; Vasilatou et al.,

9

2017).

10

The contribution of the finest particle fraction to TSP and of PM1.0 to PM2.0, reflected

11

by the ratios of PM2.0/TSP and PM1.0/PM2.0, are shown in Table 2. Fine particles

12

comprise a small fraction of total particle mass (PM2.0/TSP) in both periods, with an

13

average value of 0.34 and a relatively small range, suggesting that natural sources

14

(i.e., desert dust transport, local soil dust re-suspension or sea-salt particles) contribute

15

significantly to the particulate matter load in the atmosphere over the city. This is

16

consistent with observations in other Mediterranean coastal cities (Alastuey et al.,

17

2005; Koçak et al., 2007; Galindo et al., 2013; Romano et al., 2016), corroborating

18

that this is a generalized regional pattern. Both periods exhibit relatively high average

19

PM1.0/PM2.0ratios (0.80 in the cold and 0.75 in the warm period), which is indicative

20

of the higher influence of the aerosol by anthropogenic sources as those tend to

21

produce sub-micrometre particles (Alastuey et al., 2005). Considering also that the

22

variability of this ratio is small for the entire period during both measuring campaigns,

23

the importance of anthropogenic sources in the atmosphere of Mytilene is in general

24

high in both cases.

25

TABLE 2 11

1

Fig. 3 shows the average mass distributions of particles having diameters from 0.1 to

2

3.2 µm measured by the MOUDI during the two seasons at SSM. In both cases the

3

size distributions can be devided in two regions: one in the submicron range with

4

particles having a mean size between 0.18 and 1.0 µm, and one corresponding to

5

coarser particles with sizes > 1.0 µm. The mean size of the particles derived from

6

these measurements is smaller (ca.0.6µm) during the cold and larger (ca. 1.2µm)

7

during the warm period, with more particles residing in the submicron region during

8

the cold period. This corroborates the higher importance of anthropogenic combustion

9

sources (that produce smaller particles compared to natural sources) during the cold

10

period, which is also supported by the elemental analysis of the PM samples discussed

11

in section 3.2 below.

12

3.2. PM chemical composition

13

Variation in the chemical composition of TSP, PM2.0 and PM1.0 samples collected at

14

the two measurement sites (SSM and PAM) during the warm and cold periods are

15

provided in Tables 3 and 4. Average values of all elements in both periods are much

16

lower than those reported from measurements at urban sites in larger cities in the

17

region (i.e., Thessaloniki and Athens; Karanasiou et al., 2007; Terzi et al., 2010), with

18

Na, S, Ca, Fe, K and Cl being the most abundant elements at both sites and seasons.

19

TABLE 3

20

TABLE 4

21

In all cases presented here we used Ti as a reference element, because it exhibited the

22

lowest enrichment factors among the detected reference elements for all PM fractions

23

during both periods. The elementary composition of the Earth’s crust was taken from

24

Wedepohl (1995). The EF values for each element in the samples collected at the two

12

1

measurement sites (SSM and PAM) are shown in Fig.4. The results of the analyses

2

suggested that the main PM sources were the marine environment (sea-salt particles),

3

re-suspension of polluted soil particles and road dust, as well as emissions from traffic

4

and residential heating. More detailed discussion on each of these sources is provided

5

below.

6

3.2.1 Sea-salt

7

Sea-salt was an important fraction of atmospheric aerosol sampled in the marine

8

coastal environment of Mytilene. The abundant presence of marine elements (Na and

9

Cl) were mainly found in TSP, as expected, due to the coarse size of sea-salt particles,

10

which yields relatively low mean PM2.0/TSP ratios (ranging from 0.15 to 0.18; cf.

11

Tables 3 and 4) obtained for these elements during both seasons. The higher

12

concentrations of Na and Cl at the PAM (p-value of 0.05) suggest that this site is

13

more affected by the sea spray in comparison to SSM, which can be explained by its

14

closer proximity to the open sea. This is also supported by the stronger correlations

15

between Na and K in the TSP samples collected at the PAM compared to those at

16

SSM (Fig. 5c and 5d).

17

The seasonal contribution of sea salt to the samples collected at the two stations

18

differs. During the warm period, the mean Cl/Na concentration ratio (ca. 1.2) at PAM

19

was close to the typical seawater ratio of 1.8 (Bowen, 1979), indicating that fresh sea-

20

salt aerosol impacted the site. However, the Cl/Na ratios were very low at SSM in the

21

warm period and at both sites in the cold period (0.15 at SSM and 0.19 at PAM).

22

These low values can be explained by the depletion of Cl by the chemical reaction of

23

sea-salt particles with gaseous pollutants (such as nitric and sulfuric acid), leading to

24

the removal of Cl and the formation of particulate nitrate or sulfate species (i.e.,

25

NaNO3, Na2SO4; Eleftheriadis et al., 1998). More recently, in a source apportionment 13

1

study conducted in two Greek urban centres (Athens and Thessaloniki), Diapouli et al.

2

(2017a) have reported Cl depletion and significant contribution from secondary

3

species in the sea-salt chemical profiles.

4

While we cannot provide evidence for these reactions here due to the absence of

5

sulfate and nitrate measurements, the observed low Cl/Na ratios indicate that marine

6

Na is combined with nitric acid. The low temperatures and high relative humidity

7

prevailing during the cold period favour the formation of secondary nitrate (Dassios

8

and Pandis, 1999), leading to aging of the marine aerosol at both sites. Here, Na

9

concentrations displayed a good correlation (R2 ranging from 0.50 to 0.99) with Fe,

10

Zn, Cr, Cu, Mn at both sites during the cold period (Table 5). This observation

11

suggests the presence of aged sea-salt, as it is associated with trace elements of

12

anthropogenic origin having spent considerable time mixed with marine air(Ogunsola

13

et al., 1994; Visser et al., 2015).

14

3.2.2 Soil re-suspension

15

Enhanced re-suspension of polluted soil particles and road dust is another important

16

source suggested by the elemental composition of the TSP samples collected at both

17

sites. High concentrations of Ca, Mg, Fe, and Ti were observed in both seasons, with

18

concentrations during the warm period being significantly higher compared to those

19

in the cold period (p-value of 0.05), as a result of the more dry conditions (Petaloti et

20

al., 2006; Minguillón et al., 2012b) and of the stronger (by ca. 78%) warm period

21

winds. This is in line with the mean PM2.0/TSP ratios for these elements, which

22

exhibited lower values in warm period (up to 0.18), and the elemental size distribution

23

of the total mass for the most crustal elements, like Ti, which are shifted towards the

24

coarser sizes (1.0 – 1.8µm; Fig. 5), indicating that these elements were related more to

25

the natural sources during this period. This is also supported by the lower EFs 14

1

(exhibiting values < 5) of Ca, Mg, and Fe in the TSP samples collected at both

2

seasons and for K in warm period (Fig. 4a and 4b), as well as by the good correlations

3

among almost all these elements (i.e., Ca, Mg, Fe, K and Ti) measured in the TSP

4

samples at both sites during winter (R2 ranging from 0.40 to 0.80; Table 5c and 5d).

5

The fine and coarse modes (0.32-0.56 µm and above 1 µm, respectively) of K

6

concentrations in the warm period are of similar magnitude (cf. Fig. 5), indicating

7

significant contribution from soil re-suspension under dry atmospheric conditions or

8

from the sea-salt. Mn concentrations during both seasons are partly linked to natural

9

sources and specifically to the re-suspension of road dust as indicated by the good

10

correlations with Ca and Mg (R2from 0.42 to 0.87; Table 5) and the EF values that are

11

lower than 10. The important contribution of road dust re-suspension was further

12

exhibited by good correlations between Ca and Mg (R2 ranging from 0.40 to 0.87;

13

Table 6), with most of the traffic-related elements (i.e., Cr, Cu and Mn) being in the

14

fine fractions at the SSM site. It should be noted here that Ca and Mg has been linked

15

to the re-suspension of natural dust, but Mg can be also related to the re-suspension of

16

soil dust and sea-salt particles by vehicular traffic (Viana et al., 2008; Wawer et al.,

17

2015).

18

3.3.3 Traffic

19

Traffic-related PM elements such as Cr, V and Mn were detected in all three PM

20

fractions (TSP, PM2.0 and PM1.0) and Ba in TSP, with the concentrations being

21

significantly higher (p-value of 0.05) in the warm period compared to the cold period

22

(Tables 3 and 4). This is not surprising since the thermal power plant is in general an

23

important source of airborne particles, together with traffic that has a stronger

24

influence during the summer holiday season (Massas et al., 2009). In addition,

25

correlations among Fe, Zn, Cr, Cu, and Mn were stronger in the TSP rather than the

15

1

fine fractions, as a result of the contribution of non-exhaust emissions (tire and break

2

wear and road dust re-suspension), which generally appear more often at the coarse

3

fractions (Eleftheriadis and Colbeck, 2001; Pio et al., 2013; Pant and Harrison,

4

2013). The contribution of the non-exhaust emissions is also supported by the

5

PM2.0/TSP ratios for these elements, which were very low (ranging from 0.03 and

6

0.20) in the warm period, suggesting the presence of mechanical abrasion particles.

7

Significant enrichment with respect to crustal composition (EFs > 10) was observed

8

for all traffic-related elements (i.e., Zn, Cu, Cr, and Ba) for all PM fractions in both

9

measurement sites and seasons (Fig. 4a and 4b), clearly pointing to a significant

10

anthropogenic contribution to the PM pollution. The strong impact of road dust re-

11

suspension was also indicated by the fact that most of these traffic-related elements

12

(i.e., Cr, Cu and Mn) appear in the fine fractions, as well as from the good

13

correlations (R2 ranging from 0.40 to 0.87; Table 6) between Ca and Mg.

14

3.3.4 Heating & other combustion sources

15

In the case of other elements associated with anthropogenic emissions such as As,

16

average concentrations in all three PM fractions were at least two times higher at both

17

sites during the cold period, indicating contributions from combustion sources such as

18

residential heating and coal combustion (Bem et al., 2003; Sun et al., 2014;

19

Manousakas et al., 2015). In addition to that, high K concentrations, which are

20

indicative of wood combustion emissions if it is in the finer fraction and soluble

21

(Molnár et al., 2005; Saffari et al., 2013), were also observed at SSM in the cold

22

period, suggesting that residential heating in Mytilene partly relies on wood burning.

23

This is also reflected by the corresponding EF values (5 < EF < 10) as discussed

24

above (cf. Fig. 4), further supporting the association of K with combustion sources,

16

1

and specifically wood combustion that has increased since the beginning of the

2

economic crisis, at least for the larger cities in the country (Saffari et al., 2013; Florou

3

et al., 2017). In addition, the fact that K correlated strongly with S in the cold period

4

(R2 ranging from 0.72 to 0.75; Table 6), also suggests that sources such as biomass

5

burning are important contributors to PM pollution in the city (Liu et al., 2000;

6

Minguillón et al., 2012a). Attributing K to anthropogenic combustion in the cold

7

period is further supported by the fact that higher elemental concentrations are

8

observed at smaller particle sizes (i.e., from 0.32 to 0.56µm) as shown in Fig. 5.

9

3.3.5 Thermal power plant

10

High concentrations of As, Cu, Cr, Mn and Zn in all three PM fractions (TSP, PM2.0

11

and PM1.0) in both periods (cf. Tables 3 and 4) and their EF values that are higher than

12

10, provide evidence that particulate pollution in the region is influenced by

13

combustion sources like the local power plant (Reddy, et al., 2005) or traffic and

14

heating (see subsections 3.3.3 and 3.3.4). Concentrations of As are higher during the

15

cold period, suggesting that it can be partly attributed to thermal power plant

16

emissions but also to activities taking place during that period (i.e. domestic heating).

17

In the fine fraction (cf. Table 6), the presence of Zn, Cr, Cu, and Mn correlate well

18

with each other indicating that the power plant and vehicles are their common source.

19

3.3.6 Shipping emissions

20

The high concentration levels and the high EFs (values >10) for S at both sites and

21

seasons indicate that its sources, which are commonly related to anthropogenic

22

activities, are important contributors to PM pollution in the city. The anthropogenic

23

origin of S is also supported by its size distributions (Fig.5) which exhibited peaks in

24

the fine mode (at 0.32 – 0.56 µm) during both seasons. S-containing aerosol particles 17

1

may very well be attributed to local shipping emissions and the subsequent formation

2

of sulfates as a results of the increased photochemical activity, or to long range

3

transport of S-containing particles in the region (Zhang et al., 2010; Lü et al., 2012;

4

Becagli et al., 2012). Higher PM2.0/TSP ratio for S is determined in the cold period,

5

but the opposite is observed in the warm period, indicating that it is related to

6

anthropogenic and more specifically to S-containing fuel combustion in the cold

7

period. According to the correlation analysis, average S concentrations at PAM can

8

partly be attributed to fuel combustion from shipping emissions (Daher et al., 2013;

9

Johnson et al., 2014), as the concentrations of the element associated with those of V

10

and Mn during the warm period (Table 5), but not at the SSM site as mentioned above

11

(cf. section 3.1). This can be explained by the proximity of PAM to the port as

12

compared to SSM.

13

3.3.7 Long-range transported pollution

14

Contribution of long-range transported polluted air masses to the air quality of

15

Mytilene was observed during both seasons (cf. section 3.1 and Figs. S3a and S3b).

16

This is indicated by the higher concentrations of some crustal (e.g., K, Ca, Ti, Mg and

17

Fe) and anthropogenic elements during the transport events, in comparison to the days

18

influenced mainly by local emissions. More specifically, elemental concentrations in

19

the TSP samples increased by ca. 50% for K, Ca, Ti, Mg and 90% for Zn and As

20

during the regional transport events in the warm period, while the associated increase

21

in the cold period was estimated to be ca. 45% for K, Ca, Ti, Fe and 40% for Zn and

22

S. The observed higher contributions in the warm period associated with long-range

23

transported polluted air masses are also indicated by the correlations between S and

24

crustal components (i.e., Ca, Mg) or Na during the warm period (Table 5 and 6),

18

1

which may be related to the long-range transport of dust along with sea-salt and

2

secondary sulfates as were observed by Diapouli et al. (2017b).

3

4. Conclusions

4

This paper studies the influences that local and remote air pollution sources can have

5

to the atmospheric aerosol over a small insular city. We report measurements of the

6

atmospheric aerosol at a representative small insular coastal city in the NAS, namely

7

the city of Mytilene, during a warm and cold period. Particle mass concentration

8

levels in the city are up to a factor of 2 lower compared to those observed in larger

9

cities in the region. Mass concentrations of TSP, PM2.0 and PM1.0 were higher (by ca.

10

32, 26, and 36%, respectively) in the cold period compared to warm period, which can

11

be attributed to the additional emissions from domestic heating, and to the weaker

12

atmospheric dilution associated to the lower average values of wind speed (ca. mean

13

difference of 56%) and boundary layer height.

14

Higher particulate concentrations were recorded at the site located at the port of the

15

city (i.e., PAM) only in the warm period due to enhanced port activities, and not at the

16

site located at the city centre (i.e., SSM) as the prevailing wind directions did not

17

favour the transport of air masses to the direction of city centre. A similar observation

18

can be made for the higher contribution of sea-salt particles at PAM because of its

19

higher proximity to the open sea, in comparison to SSM site.

20

Re-suspension of polluted soil particles and non-exhaust traffic emission sources are

21

important contributors mainly in the TSP samples at both sites and seasons. Re-

22

suspension of polluted soil particles is more significant in the warm period, as shown

23

by the higher concentrations of Ca, Mg, Fe, and Ti, due to the drier conditions. Strong

24

correlations among anthropogenic elements like Fe, Zn, Cr, Cu, and Mn, suggest that

19

1

traffic and power plant are major contributors to PM pollution. The smaller PM

2

fractions during both periods were also affected largely by other anthropogenic

3

activities such as wood and fuel combustion (i.e., residential heating and shipping

4

emissions), as indicated by high concentrations of K and S.

5

In addition to the local sources, high contribution of long-range transported polluted

6

air masses was observed during the warm compared to the cold period. This

7

contribution was further supported by the higher concentrations and the strong

8

relationship among some crustal and anthropogenic elements that were recorded

9

during the long-range transport events, as well as by the diurnal variability of the size

10

distribution measurements that are more pronounced in the cold period.

11

Our findings improve our understanding of the contribution that different pollution

12

sources can have to the properties of the atmospheric aerosol in coastal insular urban

13

environments, which in turn can help us assess their potential impacts to human health

14

and subsequently design effective mitigation strategies.

20

1

Acknowledgements

2

We would like to thank the Research Funding Program: THALIS –“Green Transport

3

in Island Areas (GreTIA)”. This project was co-financed by the European Regional

4

Development Fund (ERDF) and the Greek State. Also, special thanks to Pr. Kallos

5

George and Dr. Spyrou Christos at the University of Athens for providing the

6

modelled data from SKIRON dust forecast model. E. Triantafyllou thanks the

7

Hellenic State of Scholarship Foundation (IKY) for funding her PhD studies (grant

8

number 5928).

9

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Table 1. Statistics of average hourly wind speed and boundary layer height reanalysis data from ECMWF during the cold and warm sampling periods. Wind speed (m s-1)

Boundary layer height (m)

Cold period

Warm period

Cold period

Warm period

Average

2.3

4.1

662

980

St. dev.

1.2

1.9

371

328

Min

1.0

1.0

56

378

Max

5.8

9.3

1514

1741

Table 2. Concentration ratios of the different PM fractions measured at Mytilene during cold and warm period. Cold period Whole period PM2.0/ PM1.0/ TSP PM2.0

Warm period Whole period PM2.0/ PM1.0/ TSP PM2.0

Average

0.34

0.80

0.34

0.75

Min

0.23

0.45

0.24

0.50

Max

0.54

0.89

0.46

0.88

Table 3. Average and the standard deviation of elemental concentrations (in ng m−3) inTSP mass at the monitoring sites SSM and PAM in cold and warm period.

Na S Ca K Fe Cl Mg Ba Zn Mn Ti Cu V Cr As

Cold period n (8) n (7) TSP SSM TSP PAM (ng m-3) (ng m-3) Av±Std Av±Std 1118±1351 1823±2284 960±409 1550±495 631±298 1250 ±551 374±256 510±285 239±198 619±526 169±193 352±649 68±52 209±76 56±49 117 ±129 56 ±77 88±130 6±11 33±31 13±10 27±13 6±4 10±6 1±2 4±3 1±1 11±14 18±9 23±10 n: number of samples

Warm period n (10) n (10) TSP SSM TSP PAM (ng m-3) (ng m-3) Av±Std Av±Std 672±396 1338±470 1004±393 1620±635 1285±645 5010±2260 211±119 623±397 656±1309 1611±1069 99±67 1610±971 226±136 634±276 125±76 166±67 11±21 25±28 20±35 46±26 36±27 151±114 7±17 15±33 4±5 9±6 32±67 23±11 6±7 10±5

Table 4. Average and standard deviation of elemental concentrations (in ng m−3) of the PM2.0 and PM1.0 samples collected at the monitoring site SSM in cold and warm period.

Na S Ca K Fe Cl Mg Ba Zn Mn Ti Cu V Cr As

Cold period n (9) n (9) PM2.0SSM PM1.0SSM (ng m-3) (ng m-3) Av±Std Av±Std 182±58 79±37 402±141 354±128 73±43 33±40 178±107 157±97 27±7 8±4 29 ±40 1±4 17±14 5±10 11±4 7±3 9±3 4±1 2 ±1 1±1 1±1 0.5±0.5 3±4 3±3 0.6±0.3 0.6±0.3 1±1 1±1 3±1 2±1 n: number of samples

Warm period n (10) n (10) PM2.0SSM PM1.0SSM (ng m-3) (ng m-3) Av±Std Av±Std 124±44 80±31 255±95 227±85 157±67 95±37 30±21 19±12 45±38 18±11 15±11 1±1 35±15 19±6 3±3 2±3 3±2 2±1 4±1 3±1 6±4 3±1 1±0.5 0.4±0.5 1±1 1±1 3±1 2±1 2±1 1±1

Table 5. Correlation coefficients (R2) among the TSP elemental concentrations at SSM and PAM during the cold (a and b, respectively) and the warm period (c and d, respectively). Only R2 equal or higher than 0.40(p-value of 0.05) are shown. a) Cold periodfor elemental correlations in TSP mass at SSM Fe Zn Cr Cu Mn As V S Na Ti Ca K Mg

Fe 1.00 0.84 0.88 0.53 0.97

Zn 1.00 0.99 0.62 0.86

Cr

Cu

Mn

As

V

S

Na

Ti

Ca

K

c) Warm period for elemental correlations in TSP mass at SSM Mg

Fe 1.00

Cr

Cu

Mn

As

V

0.99

1.00 0.45

0.40 1.00

0.97

0.97

0.64

1.00 0.63 0.73 0.74

1.00 0.44 0.46

1.00 0.67

1.00

1.00 1.00

0.82

0.43

0.89

1.00 0.40

1.00 0.51 0.51

1.00

Zn

Cr

1.00 0.79 0.67 0.50

1.00 0.40 0.53

Cu

Mn

As

V

S

Na

Ti

Ca

K

d) Warm period for elemental correlations in TSP mass at PAM Mg

Fe 1.00

Zn

Cr

Cu

Mn

As

V

S

Na

Ti

Ca

K

Mg

1.00 0.43

1.00

1.00 1.00 1.00

0.40 1.00

1.00 1.00

0.80 1.00

1.00 1.00

0.99

Mg

1.00

1.00

0.63

K

1.00

1.00 0.51

0.59

Ca

1.00

1.00

Fe 1.00 0.65 0.98

Ti

1.00 0.91

1.00 0.99

Na

1.00

0.95

1.00

0.81

S

1.00 1.00

b) Cold period for elemental correlations in TSP mass at PAM Fe Zn Cr Cu Mn As V S Na Ti Ca K Mg

Zn

0.72

0.59

0.50

1.00 0.45

0.51 1.00

0.44 1.00

0.75 0.55 0.80

1.00 1.00 1.00

0.46 0.68

1.00 0.55

1.00 0.43 0.88 0.58 0.78 0.47

1.00 0.40 0.54 0.42

1.00 0.64 0.79 0.40

1.00

Table 6. Correlation coefficients (R2) between the elemental concentrations of the PM2.0 and PM1.0 mass at SSM, that were equal or higher than 0.40 (p-value of 0.05) in the cold period (a and b, respectively) and the warm period (c and d, respectively). a) Cold periodfor elemental correlations in PM2.0 mass at SSM Fe Zn Cr Cu Mn As V S Na Ti Ca K Mg

Fe 1.00 0.43 0.43 0.40 0.65

Zn

Cr

Cu

Mn

As

V

S

Na

Ti

Ca

K

c) Warm period for elemental correlations in PM2.0 mass at SSM Mg

1.00 1.00 0.99 0.59

1.00 0.57

1.00

Fe 1.00 0.75 0.40

Zn

Cr

1.00 0.46

1.00

0.62

0.71

0.45

Mn

1.00 0.47

1.00

1.00

As

V

0.57

0.49

0.55

0.50

0.60

1.00 1.00

0.56

0.95

0.93

0.65

0.47

1.00 1.00

0.75 0.41

0.80

0.76

Fe 1.00 0.70

0.78

Zn

Cr

Cu

0.47

Mn

0.53

As

0.69

1.00

0.69 0.64 0.89 0.93 0.73

V

S

Na

Ti

Ca

K

0.74

0.70

0.58

0.53

0.40 0.40 0.40

0.82 0.61 0.87 0.71 0.70

Fe 1.00

Zn

Cr

Cu

Mn

1.00 0.51

1.00

As

V

1.00 0.46

1.00 0.41 1.00

0.67 1.00

K

Mg

1.00 0.72 0.46 0.55 0.61 0.46

1.00 0.64 0.89 0.63 0.73

1.00 0.80 0.77 0.90

1.00 0.58 0.89

1.00 0.63

1.00

S

Na

Ti

Ca

K

Mg

1.00 1.00 1.00

0.88

0.89

0.59 0.77

0.78

0.50 0.72 0.58

1.00 1.00

0.46

0.63 1.00

0.56

0.53

0.42

1.00 0.40 0.40

1.00

0.63

0.40 0.57

0.40 0.97

1.00

0.72 0.40

Ca

1.00 1.00 0.99 0.47 0.40

1.00 0.41 0.84 0.40

Ti

d) Warm period for elemental correlations in PM1.0 mass at SSM Mg

1.00

0.62

Na

1.00

1.00 0.69

S

1.00 1.00

b) Cold periodfor elemental correlations in PM1.0 mass at SSM Fe Zn Cr Cu Mn As V S Na Ti Ca K Mg

Cu

0.54

0.70

1.00 1.00 0.44

1.00

0.40

0.65

1.00 0.70

1.00

Fig. 1. Map of Greece showing the islands of Lesvos (39° 10΄ N, 26° 20΄ E) and the cities of high population density (up to 1 million inhabitants) in the Eastern Mediterranean area (black solid circles). The detailed map on the right, show the city of Mytilene, the airport, the power plant and the monitoring stations, at the centre (Sapfous Square, SSM) and at the port (Port Authorities, PAM) of the city.

Fig. 2. Mass concentrations of TSP, PM2.5 and PM1.0 measured at SSM and PAM during the cold and warm period (a) and during the days with or without desert dust sources during the cold period (b).

Fig. 3. Mass size distributions of particles having diameters in the size range 0.1-3.2 µm measured at SSM during (a) the cold and (b) the warm period.

Fig. 4. Enrichment factors for the major elements in TSP mass at SSM and PAM and in PM2.0 and PM1.0 at SSM in the cold (a) and the warm (b) period. The horizontal dashed lines represent the detection limits for the origin of the major elements through enrichment factors (EFs).

Fig. 5. Elemental size distributions of S, Ti and K measured at the monitoring site SSM during the cold (a, c and e, respectively) and the warm (b, d and f, respectively) period.

• • • •

We characterise the atmospheric aerosol in a small insular coastal city Particulate Matter concentrations are smaller than those of larger nearby cities Particulate Matter concentrations are close to those set by the EU limits Traffic and heating or long-rage transport are the main sources of particles

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2 3. Intellectual Property We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.

4. Research Ethics We further confirm that any aspect of the work covered in this manuscript that has involved human patients has been conducted with the ethical approval of all relevant bodies and that such approvals are acknowledged within the manuscript. IRB approval was obtained (required for studies and series of 3 or more cases) Written consent to publish potentially identifying information, such as details or the case and photographs, was obtained from the patient(s) or their legal guardian(s).

5. Authorship The International Committee of Medical Journal Editors (ICMJE) recommends that authorship be based on the following four criteria: 1. Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND 2. Drafting the work or revising it critically for important intellectual content; AND 3. Final approval of the version to be published; AND 4. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All those designated as authors should meet all four criteria for authorship, and all who meet the four criteria should be identified as authors. For more information on authorship, please see http://www.icmje.org/recommendations/browse/roles-andresponsibilities/defining-the-role-of-authors-and-contributors.html#two. All listed authors meet the ICMJE criteria. 
We attest that all authors contributed significantly to the creation of this manuscript, each having fulfilled criteria as established by the ICMJE.

3 One or more listed authors do(es) not meet the ICMJE criteria. We believe these individuals should be listed as authors because: [Please elaborate below] 


We confirm that the manuscript has been read and approved by all named authors. We confirm that the order of authors listed in the manuscript has been approved by all named authors.

6. Contact with the Editorial Office The Corresponding Author declared on the title page of the manuscript is: George Biskos

This author submitted this manuscript using his/her account in EVISE. We understand that this Corresponding Author is the sole contact for the Editorial process (including EVISE and direct communications with the office). He/she is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that the email address shown below is accessible by the Corresponding Author, is the address to which Corresponding Author’s EVISE account is linked, and has been configured to accept email from the editorial office of American Journal of Ophthalmology Case Reports: [[email protected]]

Someone other than the Corresponding Author declared above submitted this manuscript from his/her account in EVISE: [Insert name below]

4 We understand that this author is the sole contact for the Editorial process (including EVISE and direct communications with the office). He/she is responsible for communicating with the other authors, including the Corresponding Author, about progress, submissions of revisions and final approval of proofs.

On behalf of all the co-authors I declare that all the co-authors agree with all of the above.

Author’s name (Fist, Last)

1. George Biskos

Signature

Date

13 December 2019