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This study was entered in the1st “Vigila tu Aire” (Watch your Air) competition organised by BIOVÍA Environmental Consultants in July 2014. Thejudges awarded second prizeto theAsturian branch of

“Ecologistas en Acción” for their years of work on air pollution and morespecifically about theeffects ofmercury on human health and theenvironment. This projects forms part of thegroup’s on-goingactivitiesinvolvingmonitoringand determiningtheeffects of mercury emissions fromthermal power plants, oneof the

principal sources of this pollutant. Thegroup’s previous experienceincluded participation in projects onmercury pollution in springs in thearea surroundingtheAboño Thermal Power Station.


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INDEX

I.- INTRODUCTION

II.- AIMS AND OBJECTIVES

III.- MATERIALS AND METHODS

3.1 Study area and experimental design

3.1.1 Study area

3.1.2 Emission of pollutants in the study area

3.1.3 Dispersal of pollutants

3.2 Experimental design

3.2.1 Sample network design

3.2.2 Transplant Preparation

3.3 Chemical analysis

3.4 Data analysis

IV.- RESULTS AND DISCUSSION

4.1. Scale and spread of mercury pollution

4.2. Spatial Structure

V.- CONCLUSION

BIBLIOGRAPHY


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Biomonitoring Aboño – Gijón Page 4

VIGILA TU AIRE WATCH YOUR AIR

I. INTRODUCTION

The chaotic model of urban growth experienced in our cities in the last few decades has led

to some industrial areas being swallowed up by the cities and therefore becoming focal

points of pollution. This may be having a negative impact on people who are exposed to

the pollutants, and extensive pollution monitoring is therefore essential.

Traditional techniques for determining concentrations of air pollutants need complicated

automatic or semiautomatic physical and chemical equipment. Continual measurements in

fixed locations (for example in monitoring networks) and in mobile monitoring stations

allow the extent of pollution to be established and the efficiency of measures in place to

reduce air pollution to be evaluated.

Biological monitoring (biomonitoring) has many advantages over traditional monitoring

methods used to determine levels of pollution that affect organisms. Biomonitoring

informs researchers about the possible entry of these pollutants in the food chain and also

about their synergistic and antagonistic effects. Another advantage is that there is no need

to install expensive equipment; biomonitoring methods are inexpensive, have good spatial

resolution and can be adapted to real needs. In addition, many pollutants can be monitored

at the same time and different combinations can be selected for different study

environments. Finally, the biomonitoring “equipment” is biodegradable and

environmentally friendly.

Terrestrial bryophytes (mosses and liverworts) have been widely used to measure the levels

of pollutants in the atmosphere since the 1960s (Tyler 1990). Mosses are ideal organisms

because of their morphological, physiological and ecological characteristics. If no native

moss species are found in the study area, transplanted specimens of moss, known as moss

bags (Tyler, 1990), can be used. In recent years, moss bags have been successfully used in


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air pollution monitoring, particularly in urban and industrial areas (Fernández and

Carballeira 2000; Areset al., 2009; Giordanoet al., 2013).

1.1. Air pollution by mercury

Mercury is a heavy metal included in the list of the 10 most dangerous chemicals for

human health compiled by the World Health Organisation (WHO). It has negative effects

on the nervous, digestive and immune systems as well as on lungs and kidneys. Excessive

exposure to mercury can cause death. Mercury can accumulate in organisms, particularly

those at the end of food chains. It can also be transported via the air across long distances

from its point of origin. It is therefore important to measure and assess the concentrations

of mercury that people are exposed to, as stated in the European Parliament and European

Council Directive 2004/ 107/EEC concerning the levels of arsenic, cadmium, mercury,

nickel and polycyclic aromatic hydrocarbons (PAHs) in the air. Both this directive and

Spanish Royal Decree 102/2011 envisage that, independently of the concentrations, one

sampling point should be established every 100 000km2to measure total concentrations of

gaseous mercury in the ambient air. These Directives also describe a reference method for

measuring the total concentrations of gaseous mercury in the ambient air. This is an

automatic method that involves atomic absorption spectroscopy and atomic fluorescence

spectroscopy. However, if use of the suggested sampling method is not possible, EU

member states can use their national standardized sampling methods, ISO standardized

methods, or another method that can be used to produce equivalent results, as in the case

of biomonitoring.

Many successful studies have used terrestrial bryophytes to monitor mercury levels. For

example, Real et al. (2008) used native moss species to study the temporary nature of


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regional levels of mercury pollution. Fernández and Carballeira (2000) used moss bags to

characterize the spatial distribution of Hg in the area surrounding a chlorine-alkali factory,

and Ares et al. (2014) used moss transplants to monitor different pollutants in urban-

industrial settings.


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II. AIMS AND OBJECTIVES

The objectives of this project were as follows:

1. To obtain a spatial representation of mercury pollution by using a biomonitoring

network to obtain information about the spread and scale of mercury pollution in

the study area.

2. To characterize the spatial structure of the bioconcentration of mercury in the

study area in order to identify possible sources of this pollutant.


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III. MATERIALS AND METHODS

3.1. Study area and experimental design

3.1.1. Study area

The study area, which is located west of the city of Gijón (population 275 735 in 2014),

covers an area of 9km2 and includes the Carreño and Gijón city councils (region of

Asturias). The study area includes the Aboño Thermal Power Station as well as the

ArcelorMittal Steelworks and the Tudela Veguin Cement Factory (Map 1).

Aboño Thermal Power Station

This is a conventional thermal power

station, of capacity 921.7MW, located in

the Aboño valley, between Carreño and

Gijón. It is sited 7m above sea level

according to the Cartographic and

Geological Institute of Catalonia (IGC).

The Power station is located at a distance

of 8km from Gijón and 2km from the

port of El Musel. It has two generators: Aboño I and Aboño II. Aboño I has a capacity of365.5MW and came into service on 15 March 1974. Aboño II has a capacity of 556.2MW

and came into service on 23 September 1985. Both units use Spanish coal, mainly produced

in Asturias, as their source of power, as well as some imported coal and fuel oil. The close

location to the ArcelorMittal Steelworks enables use of some of the gases from the steel

production.

Source: www.edpenergia.es


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Arcelor-Mittal Steelworks

Crude steel is melted (primary or secondary melting) in the ArcelorMittal Steelworks at a

continuous rate of up to 2.5t/h. This is the only steel plant in Spain where the entire

manufacturing process is completed in the same steelworks; steel is produced using mineral

iron as the raw material. The maximum annual production of the plant is over five million

tonnes of liquid steel. This equates to a quarter of the steel production in the whole of

Spain.

Tudela Veguin Cement Factory

The Tudela Veguin Cement Factory produces different types of clinker, cement and raw

materials.

Source: www.lne.es

Source: ww.cementostudelaveguin.com


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The factory has three wet process ovens that can produce cement at a maximum rate of

1450 t/ day and one dry process oven of capacity 2600 t/ day. Due to the current recession,

the three wet process ovens were turned off during 2008 and are still out of use.

3.1.2. Pollutant emissions in the study area

Table 1 (below) shows pollution emissions in the study area. The table was produced using

data from The State Register of Emissions and Pollution Sources (E-PRTR Spain:

http:/ /www.prtr-es.es).

The emission inventory includes the three companies in the study area that release mercury;

emissions from ArcelorMittal Spain are particularly high (73.4 kg/ year), followed by Aboño

Thermal Power Plant (54 kg/ year) and The Tudela Veguin Cement Factory (10.2 kg/ year).

Table 1.- Concentration of pollutant gases produced in kg/ year (year of emission) by the threecompanies in the study area. Data are from The State Register of Emissions and Pollution Sources(E-PRTR Spain).

Concentration of pollutant emitted to the atmosphere (kg/ year) As Cd Cr Cu Hg Ni Pb Zn

Aboño Thermal Power Station62

(2013)126

(2005)159

(2013)111

(2011)54

(2013)201

(2013)280

(2008)-

ArcelorMittal Spain 91(2011)

164(2013)

736(2013)

590(2013)

73.4(2013)

439(2013)

14.000(2013)

3.170(2013)

Tudela Veguin Cement Factory- - - - 10.2

(2011)- -

3.1.3. Dispersal of pollutants

Hourly wind speed and direction data from the HCA Tranqueru (Perlora) and ARC

Monteana (Fresno) weather stations was used to plot “spray roses” (the inverse of wind

roses) with the WRPLOT program. These graphs show the direction of predominant


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weather conditions including wind direction, and as a consequence, the dispersal of

pollutants.

Figure 1 shows that the predominant direction of pollution dispersal is towards the east

and northeast, especially in the Monteana weather station.

Figure 1. “Spray Roses” plotted using data from the HCA Tranqueru (left) and ARC Monteana(right) weather stations.

3.2. Experimental design

3.2.1. Sample network design

For the purposes of the study, a theoretical network of mesh size 500m was devised with

the main focus on the area around the Aboño Thermal Power Station (Map 1). The

optimal number of exposure sites (ES) for hanging the moss bags was 49 due to the size

and shape of the sample area. This theoretical network was transferred to the study area. At

each of the coordinates, the presence of a street light or other structure allowed the moss

bags to be hung at 3-4 m above the ground and away from obstacles. The list of possible

exposure sites for the transplants was modified according to the resources available and the

actual sample network was produced (Map 1). At exposure sites 7, 17 and 22 in the


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theoretical network, transplants were not able to be hung due to their location inside

industrial premises. In addition, access to exposure sites 37 and 44 was not possible, and

therefore one new site was established between the other two. Transplants ES 9 and 18

were lost during the study period.

Map 1.- Location of the exposure sites in the theoretical and actual biomonitoring air pollutionnetworks where dead transplants of P. purum were used.


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3.2.2. Transplant preparation

The method for use of moss bags was invented by Tyler in 1969 (Tyler, 1990) and

comercialized by Biovía for use in air pollution monitoring. The technique simply involves

exposing moss to air in the study area for a certain length of time. The moss is held inside a

polyethylene net bag.

The moss species used was Pseudoscleropodiumpurum(Hewd.) collected from an area free of

pollution, in southeastern Galicia (Oseira, Ourense; Aboal et al., 2004). In order to

standardize the moss used in the transplants, apical segments (5cm) were separated in the

laboratory and the remaining parts of the moss plants were discarded. The selected

segments were sieved in a plastic net (0.7cm mesh size). The standardized procedure

outlined by Ares et al. (2012; 2014) was followed. The moss was washed in a 10mM

solution of EDTA and stirred for 20 minutes to remove any elements bound to the cation

exchange surfaces and thus increase its capacity for pollutant retention.

The moss samples were then washed with distilled water and stirred constantly for 20

minutes to change the balance of cations bound to the extracellular matrix (Brown and

Wells, 1990). This leads to “activation” of the moss and increases its capacity for

bioconcentration of cations. Excess moisture was then removed by blotting the segments

on filter paper and the moss was dried in an oven, with a temperature ramp (50ºC for 8

hours, 80ºC for 8 hours and 100ºC for the final 8 hours) to remove 100% of the moisture.

The moss bags (15x25cm) were made of polyethylene (mesh size 2mm), previously washed

with HNO3 to remove all traces of pollutants. The moss segments were weighed and

spread evenly inside the bags. The open sides of the bags were then sewn shut with nylon

thread and a zigzag stitch, to prevent the material moving inside the bags. Finally, each bag


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In the laboratory, the samples were dried (< 40ºC), pulverized and homogenized in a

ultracentrifuge mill (Restch ZM 200, heavy metal free) to yield particles of size less than

100 μm.

Figure 2.- Photographs showing the moss bags and how they were installed

3.3. Chemical analysis

The concentrations of mercury were determined in an elemental mercury analyzer

(Milestone DMA 80). To ensure analytical quality, 1 in 10 samples were subjected to

analytical repeats and the standard deviation was calculated according to Ceburnis and

Steinnes (2000):n

C C

S

i

n

i

2

)( 221∑ −

, where C1 and C2 are the repeated concentrations. In

order to monitor the analytical process, 1 in 10 alternate samples were analyzed according

to the certified reference materials M2 (Steinnes et al., 1997) corresponding to the moss


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Pleuroziumschreberi. The possibility of contamination of the material during the process was

also controlled by use of analytical blanks (1 each 10 samples analyzed). Recovery of the

reference materials was satisfactory: >75% for Hg. The technical quantity limit (LOQT) in

P. purumfor Hg was 37 ng.g-1(Coutoet al. 2004).

3.4. Data analysis

A robust semivariogram (Boqueteet al., 2009) was used to check the spatial structure in the

mercury concentrations. This method is less sensitive than other methods to the existence

of anomalous values. A random sampling method was used to confirm the existence of a

spatial structure (Aboal et al., 2006): this yielded a semivariance distribution of the

semivariogram -under the hypothesis of no spatial structure- compared with the

semivariogram obtained for mercury.

When the robust semivariogram confirmed the existence of spatial structure, the next step

was to apply median polish (Boqueteet al., 2009) to separate the deterministic and random

contamination processes. The value obtained by this method at each sampling station

would yield a large-scale deterministic component, whereas the remainder would

correspond to the random component. The technique described in the previous paragraph

can then be used to check for any spatial structure in the remainders.

Linear interpolation was used with the estimated values and median polish for each sample

station to produce a surface diagram showing the pattern of mercury pollution in the study

area.


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IV. RESULTS AND DISCUSSION

4.1. Scale and spread of mercury pollution

Three quality controls were used (C1, C2, C3) to verify that the samples were not

contaminated during collection, transport or analysis. The mercury content of these

samples, which were not exposed to the air, was the same as the content at the start of the

experiment (T0), indicating no contamination of the other samples during the above-

mentioned procedures.

Table 3 shows the concentrations of mercury in the moss bags installed in exposure sites

(ES) and in used as controls and T0. The same concentrations, grouped by level of

bioconcentration, are shown on Map 2.

Table 3.- Concentrations of mercury (ng·g-1) in dead (dried) transplants of Pseudoscleropodiumpurumafter exposure for 8 weeks.

ES Hg ES Hg ES Hg ES Hg

1 48 15 42 30 40 42 542 178 16 75 31 48 43 403 63 19 52 32 48 45 914 68 20 57 33 51 46 1475 117 21 76 34 45 47 1086 63 23 43 35 49 48 1268 59 24 45 36 43 49 12010 50 25 40 37/ 44 78 C1 3211 62 26 47 38 47 C2 32

12 78 27 64 39 75 C3 3213 54 28 45 40 69 T0 3114 95 29 49 41 86

The mercury concentrations varied between 30 ngg-1 and 178 ngg-1 (mean value, 68

ngg-1). These results can be interpreted by comparing them with others from similar

areas. Areset al. (2014) used transplants of two moss species (Sphagnumdenticulatumand P.


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purum) to biomonitor different environments (such as steelworks, thermal power stations

and aluminium factories) in Galicia, an area with a similar climate to the study area. The

average concentrations of mercury for different exposure periods for P. purumand the

different environments were very variable. The initial values of 36-43 ngg-1 were similar

to those found in the present study (31 ngg-1), although values of 1400 ngg-1 were

recorded in the steelworks.

By contrast, the concentrations of mercury reported by Areset al. (2011) in transplants of

P. purumin Santa Cruz, Tenerife, an area affected by an oil refinery, were very low (between

3 and 24ngg-1), although the concentrations of other pollutants (i.e. V, Ni, flouranthene,

pyrene) were very high.

In the area surrounding a chlorine-alkali factory in Pontevedra (Fernándezet al. 2000), the

concentrations of mercury reached 2750 ngg-1 (i.e. classified as High Pollution). These

values were obtained using moss transplants located at the perimeter of the factory, and the

levels decreased rapidly with distance from the factory. Thus, at a distance of 300m, the

levels had returned to background values. This rapid decrease suggests that the pollution

was mostly due to particulate mercury that was being deposited in areas near the factory.

For correct interpretation of the results obtained in this study, it is important to calculate

the enrichment factor (EF) for each sample. The enrichment factor is defined as the ratio

between the concentrations observed at the end of the sample period and the initial or

background levels. The enrichment factors calculated in this study are shown on Map 2.

Calculation of enrichment factors enables classification of pollution levels. Thus, if the

value of the enrichment factor is 1 or lower, the pollution is classified as Null, if the value is

between 1 and 2 the situation is Unconvincing, if the value is between 2 and 3 the pollution


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is Weak, between 3 and 8 it is Moderate, a value between 8 and 27 represents High

pollution and values above 27 indicate Severe or Extreme Pollution.

Map 2.- Concentrations of Hg and Enrichment Factors (EF) in dead transplants of P. purumafter 8 weeks of exposure to ambient air.

In this study, the values were between 1 and 6. In most of the exposure sites, the value was

≤ 2, indicating Null or Unconvincing levels. In the northeast of the study area near the port

(Exposure Site ES 14), pollution was moderate (EF =3). The northern zone includes some

isolated areas ES 2 and ES5 with Moderate levels of pollution (EF = 6 and EF = 4

respectively). The lack of intermediate values hampers our ability to reach valid conclusions

about the source of pollution that affects these two areas.


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The south-southeastern area has the highest pollution levels, with EF=5 at ES 46,

indicating moderate pollution levels. This area is in the direction affected by emissions

from the ArcelorMittal Steelworks (B). In comparison, Ares et al. (2014) reported Severe

pollution levels (EF =14) and observed many Moderate enrichment factor values (5-8),

which are higher than those found in this study in the area surrounding the steelworks.

4.2. Spatial structure

The robust semivariogram for mercury seems to show a linear model with a significant

initial lag (Figure 3). This indicates the existence of a weak spatial structure in the mercury

transplants. However, the structure seems to disappear after application of median polish

and calculation of the remainders. We can therefore assume that the median polish

indicates the structure of the existing mercury levels (Map 3). The percentage variation

between the original data and the data calculated using the median polish (calculated as the

coefficient of determination between the original data and those obtained using the median

polish) was 42% (r2 = 0.42). A low percentage of variation was therefore explained by the

median polish. The rest of the variation was caused by corresponding processes on a

smaller scale than that studied, and by analytical noise. The highest concentrations on Map

3 are in the southeast of the study area. Higher concentrations were also observed in the

northeast of the area.


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Figure 3.- A: Robust semivariogram of the concentrations of mercury measured. The lines representthe median and the 2.5 and 97.5% quartiles calculated using a randomization method. B: Robustsemivariogram of the remainders from the median polish of the mercury concentrations. The linesrepresent the 2.5 and 97.5% quartiles obtained by a randomization method.


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V. CONCLUSION

Most of the study area was characterized by Null or Unconvincing levels of mercury

pollution.

In the north of the study area, some isolated areas with worrying pollution levels were

identified.

The south of the biomonitoring network includes an area in which a group of exposure

sites clearly indicate mercury pollution.

The weak spatial structure impedes definite identification of the pollution sources in

the area.

An increase in the size of the study area towards the north and south could greatly

increase the information available about the mercury pollution and thus enable

identification of spatial patterns.

Other pollutants associated with the possible existing pollution sources in the area

could be analyzed. Thus, analysis of other heavier pollutants with less capacity for

dispersal than mercury could help in the identification of the pollution sources.


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BIBLIOGRAPHY

Aboal J.R., Real C., Fernández J.A. and Carballeira A. 2006. Mapping the results of

extensive surveys: the case of atmospheric biomonitoring and terrestrial mosses.

Science of the Total Environment 356:256-274

Ares A., Aboal J.R., Fernández J.A., Real C. and Carballeira A. 2009. Use of the terrestrial

moss Pseudoscleropodium purum to detect sources of small scale contamination by

PAHs. Atmospheric Environment 43 (34):5501-5509.

Ares A., Fernández J.A., Aboal J.R. y Carballeira A. 2011. Study of the air quality in

industrial areas of Santa Cruz de Tenerife (Spain) by active biomonitoring with

Pseudoscleropodium purum. Ecotoxicology and Environmental Safety 74(3): 533-541

Ares A., Fernandez JA., Carballeira A., Aboal JR. 2014. Towards the methodological

optimization of the moss bag technique in terms of contaminants concentrations and

replicability values. Atmospheric Environment 94:496-507

Boquete T., Fernández J.A., Aboal J.R., Real C. and Carballeira, A. 2009. Spatial structure

of trace elements in biomonitoring surveys with terrestrial mosses. Science of the Total

Environment 408(1): 153-162

Brown DH. And Wells JM. 1990. Physiological effects of heavy metals on the moss

Rhytidiadelphus squarrosus. Annals of Botany 66:641-647.

Ceburnis D. and Steinnes E. 2000. Conifer meeddles as biomonitors of atmospheric heavy

metal deposition: comparaison with mosses and precipitation, role of the canopy.

Atmospheric Environment 34:4265-4271.


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Couto JA., Aboal JR., Fernández JA., Carballeira A. 2005. A new method for testing the

sensitivity of active biomonitoring: an example of its application to a terrestrial moss.

Chemosphere 57:303-308.

Fernández A. and Carballeira, A. 2000. Differences in the responses of native and

trasplanted mosses to atmospheric pollution. The importance of Selenium.

Environmental Pollution 110: 73-78.

Fernández A. Aboal, J. and Carballeira A. 2000. Use the native and trasplanted mosses as

complementary techniques for biomonitoring mercury around an industrial facility.

The Science of the Total environment 256:151-161.

Fernández A., Rey A. and Carballeira, A. 2000. An extended study of heavy metal

deposition in Galicia (NW Spain) based on moss analysis. The Science of the Total

Environment 254:31-44.

Giordano S., Adamo P., Spagnuolo V., Tretiach M., Bargagli R. 2013. Accumulation of

airborne trace elements in mosses, lichens and synthetic materials exposed at urban

monitoring stations: towards a harmonization of the moss-bag technique.

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Real C., Fernández J.A., Aboal J.R. and Carballeira A. 2008. Detection of pulses of

atmospheric mercury deposition with extensive surveys and frequently sampled

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