Chemosphere 131 (2015) 130–138
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Integrated environmental quality monitoring around an underground methane storage station Linda Pieri a,⇑, Marco Vignudelli a, Fabrizio Bartolucci b, Fiorenzo Salvatorelli a, Cesare Di Michele c, Nicola Tavano d, Paola Rossi a, Giovanni Dinelli a a
Department of Agricultural Science, University of Bologna, Italy University of Camerino – Aquila, Italy PROGER S.p.A., Italy d Agronomist, Pescara, Italy b c
h i g h l i g h t s The environmental quality of an area with a methane station was evaluated. Two monitorings were applied: measures of air components and lichens biomonitoring. The two monitorings results were in agreement. The environment quality of the area surrounding the station did not show signs of declining. Results suggest the validity of biomonitoring to integrate the environmental network for pollution assessing.
a r t i c l e
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Article history: Received 21 March 2014 Received in revised form 9 March 2015 Accepted 10 March 2015 Available online 29 March 2015 Handling Editor: J. de Boer Keywords: Biomonitoring Lichens Air quality Natural gas Italy
a b s t r a c t The study reports an integrated environmental quality monitoring of a 100 km2 area in central Italy mostly occupied by an underground station of methane storage, working since 1982. The nitrogen oxides, ozone and isoprene concentration detached with a network monitoring of passive filters were compared with the results of lichens biomonitoring. Data from the two monitorings were in accordance: there was an inversely correlation between lichen biodiversity index (IBL) and NOx ( 0.96) and ozone ( 0.80), and a positive correlation between IBL and isoprene (0.67). IBL indicated that the area ranged between medium naturalness and medium alteration status, values fully compatible with the medium–high level of eutrophication, caused by intensive agriculture. Only two areas were in high alteration status, due to their proximity to glass factories and to a quarries area. Despite almost thirty years of activity, the environment quality of the area around the station did not show signs of declining. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Natural gas is an essential resource as it represents a source of clean energy for homes, public buildings and businesses. Italy is in close dependence on other countries: more than 40% of Italian natural gas consumption is imported, with growth forecast to 70% in 2020.
⇑ Corresponding author at: Department of Agricultural Science, University of Bologna, viale Fanin n.44, 40127 Bologna, Italy. Tel.: +39 051 2096693; fax: +39 051 2096241. E-mail address: [email protected] (L. Pieri). http://dx.doi.org/10.1016/j.chemosphere.2015.03.009 0045-6535/Ó 2015 Elsevier Ltd. All rights reserved.
The storage of natural gas can be considered a strategic process. In fact, while the gas supply is basically constant throughout the year, the demand has a marked seasonal variation and this is more evident in case of adverse weather that result in the absence of cover the natural gas needs. Since during the compression activity there are emissions of chemical species, these stations may be sources of pollution and therefore require a monitoring to assess their environmental impact. This environmental monitoring can be due through direct and continuous monitoring of the main pollutants, generally operated with stationary or mobile automatic stations. Among these, passive filter has been increasingly used, because of low operating cost, simplicity of sampling, independence from the
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electricity and good correlation results with compared direct monitoring methods (Lozano et al., 2009). The measurements of potential harmful chemical species are necessary to evaluate the effect of polluting sources, but they do not provide information on the impact of these pollutants on the environmental matrices. For this kind of evaluations the biomonitoring is very suitable, because assesses the effects of the atmospheric constituents through the observations of biological materials. The most appropriate biological species used for biomonitoring are lichens, for their demonstrated high sensitivity to air pollution (Loppi et al., 2002; Gombert et al., 2004; Munzi et al., 2007; Frati et al., 2007; Pinho et al., 2008). This feature is due to their slow growth and efficiency in absorbing nutrients from air and water (Nash, 1996). Among the biomonitoring methods, the official procedure ANPA (2001) consists in the determination of the lichen biodiversity index (ILB). This method is most widely applied in Italy and the ILB is computed by the sum of the presence of lichen species occurred in a defined grid. Its evaluation allows to define the areas with an alteration state, based on the scale of naturalness/alteration proposed by Frati et al. (2003). The thallus physiological properties and structure make lichens mainly dependant on atmospheric deposition for their nutrition, especially for the nitrogen supply (Gombert et al., 2003). Several researches demonstrate an influence of nitrogen deposition on the lichen communities (Loppi and de Dominicis, 1996; Van Dobben and De Bakker, 1996), as a high concentration of nitrogen in environmental matrices leads to regional acidification and eutrophication (Erisman et al., 2003) and therefore the selection of lichen species suitable to these environmental conditions. Indeed, the level of substrate acidity can be also influenced by dust deposition. Calcareous dust, typically present in Mediterranean areas (Pieri et al., 2009) or deriving from human activity (e.g. rushing machinery in quarries), raises the bark pH, favoring the selection of lichen species adapted to basic substrates (Gilbert, 1976; Loppi and De Dominicis, 1996; Loppi et al., 1997). While the relationship nitrogen-lichens and dust-lichens is quite known, previous studies do not identify a clear and univocal correlation between ozone and lichens communities: Nali et al. (2007) reports no correlation between ozone patterns and lichen distribution (Parmelia and Lecanora genus), while Scheidegger and Schroeter (1995) highlights that high ozone concentration determines biophysical and physiological modifications on several species. The tropospheric ozone (O3) reflects the climatic conditions and the presence of precursor substances sources (VOCs, NOx, CH4, CO, isoprene). The stations for methane storage are VOCs sources, emitting nitrate oxides, sulphur oxides, carbon dioxide, and methane, during the combustion processes, but their contribution in the ozone production is low (Derwent et al., 2007). The two monitorings (direct and biomonitoring) provide information substantially different: the direct monitoring of pollutants provides an assessment of the current state of air quality, while the biomonitoring photographs an ecological condition, stabilized in a wider timeframe. The correlation between IBL and the main pollutants distribution could suggest the validity of biomonitoring to integrate the environmental network for assessing the atmospheric pollution. The aim of this paper is three folds: (i) evaluating the environmental impact of a station of methane storage, (ii) comparing and finding correlation between two approaches of environmental quality monitoring, the pollutants direct monitoring and the lichens biomonitoring; (iii) providing a general picture of pollution pattern of the investigated area and determining the main causes of changes in lichens communities.
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2. Materials and methods 2.1. Location The monitored area is located in an hilly sub-mediterranean area of about 100 km2 in Central Italy. During the monitoring period, weather stations within the area recorded mean temperature ranging between 16.1 °C and 36.4 °C, with mean of 26 °C. Compared with the climate historical data, this period can be considered typical for the area. The wind direction was predominantly W–NW, with some episodes from E–ESE. Within the area there are four Site of Community Importance (SCI), in which natural habitats and animal and vegetables species have to be safeguarded: SCI1 ‘‘Gessi di Lentella’’ (IT7140126), SCI2 ‘‘Macchia Nera – Colle Serracina’’(IT228226), SCI3 ‘‘Fiume Trigno’’(IT7140127), and SCI4 ‘‘Colle Gessaro’’ (IT 222212) (Fig. 1). The main potential sources of NOx and VOCs within the area are the following: (i) an underground station of storage and distribution of methane, (ii) a landfill, (iii) a mining zone, and (iv) an industrial area. The rest of the surface is occupied by heavy cultivated arable lands (Fig. 1). In particular the methane station, located at Cupello (80 km South-East from Chieti), covers about the 80% of the total monitored area. In the past the station was used for primary production of methane, while since 1982 the activity has been limited to the compression and the storage of methane coming from the national network, and the delivery when requested by customers. The mean annual volume of the stored gas is about 8.3 109 S m3, and the delivery is about 7.6 109 S m3. The storage occurs within a gas compression station, which during spring and summer stocks methane in underground reservoirs through wells distributed throughout the station, while in fall and winter the gas is distributed to customers. The landfill and the mining zones are located within the area of the methane storage station, the first one in North-West and the second in South-East direction (Fig. 1). The landfill has a volume of 300 000 m3 and contains a plant of biogas and cogeneration. In the quarries area, sand, clay, gravel, and rock are excavated from the ground. Moreover, next to the excavation area, there is a station for the treatment of quarried material (brick industry with kilns for the production of expanded clay). Finally, outside the storage station, there is an industrial area, with two glass factories. Technical reports on environmental impact provided by the glass factories show NOx emissions of 320 t ha 1, while in an official document, the methane station declares NOx emissions of 80 t ha 1. There are no official emission data of the other potential sources of pollution. However, as visually observed, the area occupied by quarries is characterized by dust arising from the excavations. Moreover, a survey of the area revealed that, the riverbed Trigno, which passes through this zone, is in a severe degradation state, while the riparian vegetation (shrubs, hornbeam and poplars) leaves are very damaged.
2.2. Monitoring of air components The direct air quality monitoring network was based on a total of 12 sampling points. The monitoring was done through passive filters, which provided the daily average concentration for each week of the period June 18–September 10, 2012. The monitored potentially harmful substances were ozone and its common precursors, nitrogen oxides (NO and NO2) of anthropogenic origin, and isoprene of prevalent biogenic origin. The detected concentrations were compared with the EU Limit Values (Directive 2008/50/ EC on air quality).
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Fig. 1. Monitoring area: the black dots are the twelve passive sampler air monitoring stations, the star indicates the compression station and the red line marks the total area of storage. The figure shows also the location of the landfill, the industrial area, the quarries and the four Site of Community Importance (SCI). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
2.3. Lichens Survey and methodology The monitoring of lichens was conducted using the official procedure ANPA (2001), which is currently the national benchmark for biomonitoring. Eleven primary sampling units (PSU) were selected on the territory corresponding to cells cartographic 1 1 km2. For each PSU, 4 Secondary Sampling Unit (SSU) have been identified. They were placed in each of the 4 quadrants that divide the PSU (area of each quadrant = 0.25 km2), according to the directions NE (SSU 01), SE (SSU 02), SW (SSU 03), NW (SSU 04). The SSU centre was 177 m from the PSU centre and from the centre of the respective quadrant. The circular area of each SSU was equal to approximately 0.05 km2 for a radius of 125 m. Within this area, trees suitable for the detection were selected. When there were no fitted tree within the SSU, a replacement was identified, moving along the relative directress (to the NE for the quadrant 1, SE for the quadrant 2, SW for the quadrant 3, and NW for the quadrant 4). The suitable trees should respect the requirements of the ANPA guidelines (free-standing tree with inclination not exceeding 10°, trunks no damaged or irregular, circumference >60 cm) and be close to the centre of the SSU. Each sampled tree was georeferenced. According to the ANPA procedure and for a good comparability of results, biomonitoring was conducted only on oaks, belonging to the genus Quercus, in particular the species Quercus pubescens Willd. subsp. pubescens (38/40, equal to 95% of the trees analyzed) and Quercus cerris L. (2/40, accounting for 5% of sampled trees). The acid bark of these trees is more favourable for the growth of lichens. Trees in closed forest vegetation were excluded and, where possible, trees sited in clearings, forest, and road margins were preferred, trying to maintain a distance of 10 m between adjacent trunks.
For the determination of the frequency of lichens, in each oak a sampling grid, consisting of four sub-units, was used. The grid subunits were placed on the trunk of oak at least one meter above the ground, each of them directing at the four cardinal points. To exclude from sampling any unsuited part of the trunk, a shift from verticality up to 20° clockwise was allowed when positioning grid sub-units (Castello and Skert, 2005). Damaged trunks or with presence of evident knots, corresponding to seepage tracks of rainwater, or with more than 25% cover of bryophytes were excluded from the samplings. 2.4. Procedures for the calculation and interpretation of lichen biodiversity For each oak, the index of lichen biodiversity (ILB) was computed, with the sum of the frequencies detected in each cardinal point (minimum 3 oaks). The ILB value of each monitoring site was the average of the values detached in oaks. To interpreter the ILB values in term of environmental quality, the scale of environmental status naturalness–alteration, proposed by Frati et al. (2003) and adapted for a dry sub-mediterranean climate was used. The status of the environment can be described in term of alteration from a natural condition, where with natural we mean the areas free from heavy anthropization and far from important pollution sources (Nali et al., 2007). 2.5. Statistical analysis of data The ILB and the concentration of the chemical species NOx, ozone, and isoprene were converted in digital raster maps and interpolated with the IDW spatial analyst extension for ArcGis 10 (ESRI). The ILB values were then correlated with each single chemical species, using the correlation matrix tool, provided by the
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ArcGis 10. The correlation matrix provides a measure of the dependency between the two datasets, showing the values of correlation coefficients that depict their relationship (Snedecor and Cochran, 1968). 3. Results and discussion 3.1. Biomonitoring with lichens and ecological indices Overall, in the eleven survey stations (A–K, Fig. 2), eight lichen species were classified (Table 1). The main species were Xanthoria parietina (L.) Th.Fr. (34/40 surveys) and Physcia biziana (A.Massal.) Zahlbr. (30/40 surveys), which together make up the 58.8% of the lichen flora present in the whole area. Hyperphyscia adglutinata (Flörke) H.Mayrhofer & Poelt (17/40 surveys) and Candelariella xanthostigma (Ach.) Lettau (11/40 surveys) accounted for 26.1% of total lichens, while the remaining 15.1% included species occurring at low frequency, namely Lecanora subfusca (L.) Ach. aggr. (7/40 surveys), Lecidella elaeochroma (Ach.) M. Choisy (4/40 surveys),
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Caloplaca cerina (Hedw.) Th.Fr. (4/40 surveys), and Physconia distorta (With.) J.R.Laundon (1/40 surveys). The eight identified species are attributable to only two of the six prevalent vegetation units in Italy, Xanthorion and Lecanorion (ANPA, 2001). Xanthorion (P. biziana, X. parietina, H. adglutinata, C. cerina, P. distorta, C. xanthostigma) is a community of relatively light-loving species, xerophile, neutral-basophile and nitrophilous present particularly in anthropic environments and to the south side of isolated trees. In areas where the atmospheric humidity is a limiting factor, some of these species also penetrate in anthropic environments, proving resistance to atmospheric pollution. The four dominant species of the present biomonitoring (P. biziana, X. parietina, H. adglutinata) are adapted to environments with high or medium levels of antrophization, so they are considered indicator species of the Xanthorion group. Lecanorion (L. subfusca aggr. and L. elaeochroma) is a community of crustose lichens pioneers of rind smooth, generally present in isolated trees, and they often precede or are mixed with species
Fig. 2. Cartography of lichen biomonitoring. The figure shows the 11 PSU (A–K), each one subdivided in 4 SSU. The dots indicate the position of individual oaks. The central storage is indicated in the figure by the factory symbol.
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Table 1 List of the eight lichen species surveyed during the biomonitoring study and their mean frequency in the 11 survey stations (PSU). Lichens species
Primary Sampling Units (PSU)
Physcia biziana Xanthoria parietina Hyperphyscia adglutinata Lecidella elaeochroma Caloplaca cerina Lecanora subfusca aggr. Physconia distorta Candelariella xanthostigma
A
B
C
D
E
F
G
H
I
J
K
6.5 2.8 5.4 – – – 1.3 –
6.5 5.2 6.6 – – – – 1.1
5.6 2.7 0.8 1.3 6.9 – – –
1.9 7.8 – 0.1 – – – –
8.1 3.2 7.3 – 0.9 – – –
8.6 3.2 – 6.9 1.1 – – –
4.8 4.0 0.1 3.1 2.3 – – –
9.2 3.3 5.3 6.1 1.4 3.8 – –
6.8 1.5 2.7 2.0 1.9 – – –
2.7 0.7 4.4 – – 1.3 – –
2.8 6.0 – – – – – –
of Xanthorion. They are relatively frequent in anthropic environments. X. parietina and P. biziana were detected in all the stations: the dominance of a limited number of species, spread throughout the biomonitoring territory, suggests rather uniform environmental and ecological conditions. According to the ANPA procedure, the species frequency data (Table 1) were processed together with the indices of ecological tolerance (pH, light level, humidity condition, and eutrophication) of each lichen species, to characterize ecologically the different survey stations (data from ITALIC, http://dbiodbs.univ.trieste.it/). Table 2 puts in evidence that PSUs ecological characteristics were very homogeneous: the substrate (bark) has pH classified as sub-neutral (3.0–3.7), direct exposure to light (4.1–4.4), low humidity conditions (3.5), and medium–high level of eutrophication (3.3–3.8). 3.2. Lichen adaptation ability Since the biomonitoring was conducted selecting acidic peel oaks, the presence of species not suitable to sub-acid substrates (i.e. P. biziana, H. adglutinata, C. cerina, L. subfusca aggr., P. distorta) indicates an abnormality. Probably the colonization of those species is due to external factors, such as calcareous dust, which raise
Table 2 Ecological indices of the 11 monitoring stations (PSU), based on the average frequency of detected lichen species. PSU
Ecological parameters pHa
Lightb
Aridityc
Eutrophicationd
A B C D E F G H I J K
3.5 3.4 3.3 3.0 3.6 3.0 3.1 3.3 3.3 3.7 3.0
4.4 4.3 4.1 4.1 4.4 4.2 4.1 4.3 4.3 4.4 4.1
3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5
3.7 3.7 3.5 3.5 3.7 3.3 3.4 3.5 3.5 3.8 3.5
Mean
3.3
4.2
3.5
3.5
Formalism on the interpretation of the different levels or states for growth form and ecological index (ANPA, 2001): a Index of pH of the substrate (5 states): 1 – very acid, 2 – sub-acid, 3 – subneutrum, 4 – slightly basic, 5 – basic. b Index of light (5 states): 1 – heavily shaded situations, 2 – shaded situations, 3 – situations with diffused light but lack of direct sunlight, 4 – sites exposed to direct sunlight, but not exposed at noon except at low inclinations of the surface, 5 – in sites with high direct irradiation. c Index of aridity (5 states): 1 – igrophytic (areas with frequent fog), 2 – fairly igrophytic, 3 – mesophytic, 4 – xerophyitic (dry situations, but absent from places extremely arid), 5– very xerophyitic. d Eutrophication (5 states): 1 – none, 2 – very weak, 3 – medium, 4 – relatively high, 5 – very high.
pH bark. Specifically in the quarries zones, the calcareous dust derives plausibly from the mining extraction. The medium–high level of eutrophication in all the investigated area is comparable with the intensive agricultural activity, considering also the minimal presence of industrial activities and the limited vehicular traffic. This is corroborated by the thallus and leaf features to explain the ecological indices results. The thallus structure (foliose or crustose) and the leaves shape (with broad or narrow lobes) are important in determining the exchange surface with the atmosphere and thus the ability of lichens to grow in a specific area. In the same air quality condition, lichens with foliose thallus are generally more susceptible than those with crustose thallus, because they expose a greater leaf surface area for the absorption and deposition of polluting agents. As shown in Fig. 3, in the studied area the most common species had foliose thallus (X. parietina, P. biziana, H. adglutinata, and P. distorta), with a discrete predominance of narrow-leaved lichens (P. biziana, H. adglutinata, P. distorta). This would suggest an ecological pressure, as the presence of pollutants in the atmosphere, with low environmental impact. This is compatible with pollutants deriving from an heavy agricultural activity. 3.3. Lichen biodiversity index (ILB) The collected data allowed the computation of the index of lichen biodiversity (IBL). The ILB values in the survey stations (A–K) ranged between 32.2, which corresponds to high level of alteration (site K) to 108.0, which is equivalent to medium naturalness (site H). The mean ILB (calculated on the basis of the values observed in the 11 PSUs) amounted to 65 ± 28, corresponding to low alteration. Fig. 4 shows the Lichen Biodiversity Index (ILB) naturalness/alteration map for the monitored area. It was created using the ILB values of the 40 analyzed oaks and applying methods of spatial interpolation.
Fig. 3. Percentage of the diverse growth forms (foliose and crustose thallus or foliose broad-lobed and foliose narrow-lobed) in the investigated area.
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Fig. 4. Naturalness–Alteration map of the bio-monitored area, derived by interpolation of the ILB values observed for the 40 investigated oaks.
Using the scale of IBL of Frati et al. (2003) to interpreter the values, it is evident that most of the area, 70%, was characterized by a lichen biodiversity corresponding to a state of low or medium alteration (classes 3a and 3b), the 19% was in a state of naturalness (classes 2a and 2b), and the 11% was in a state of high alteration or very high alteration (classes 4a and 4b). Specifically, the methane storage station area had the following ILB: 20% had medium alteration (class 3b), 70% had low alteration (class 3a), and the remaining 10% was in the state of medium–low naturalness (class 2). Thus, all the sites had acceptable levels of lichen biodiversity, with the exception of two critical areas, sites J and K, located in zones with high level of anthropic pressure: site K, in the south of the methane station area, is near the quarries, while site J is located in the industrial area. The best IBL values, which identify a medium–low naturalness status, were observed in the Site of Community Importance SCI1 (IT7140126 ‘‘Gessi di Lentella’’). The SCI1 is mostly located within the storage station area, at a distance of about 2.8 km from the compression station. Despite almost thirty years of compression and storage of methane, this SCI did not reveal an evident symptom of decline in terms of environmental quality; conversely it resulted to be the area with the most natural condition of the entire area subjected to biomonitoring.
3.4. Monitoring of the chemical species ozone, nitrogen and isoprene The pollutant chemicals concentration detected with passive samplers were compared with the EU Limit Values indicted in the EU Directive 2008/50/EC on air quality. During the sampling period, ozone concentrations ranged between 51 ppb and 103 ppb, respectively recorded in site 10
and 6 (Fig. 5a). Since the ozone threshold limit for vegetation protection is 65 ppb (mean on 24 h), only the concentration of the site 6, located in proximity of the landfill, were high and dangerous. Nitrates (NO + NO2) were always and everywhere below the EU reference limit (EU Limit Value for sensitive vegetation and ecosystems is 30 ppb), with mean values between 6.1 ppb and 15.9 ppb, recorded respectively in site 6 and 8. The only exceptions were the sites 10 and 11, both close to the industrial area, where the average values were 41.6 ppb and 29.8 ppb respectively, with peaks of 55 ppb for the10, recorded on 28, August (Fig. 5b). Finally, the concentration of isoprene fluctuated between 0.3 and 4.8 ppb. For this chemical species no reference values are fixed, but the lowest values, indicating a low presence of vegetation areas, were recorded at sites 10 and 11 in the industrial area with glass factories. Conversely the highest were detected at site 2, located in the south-west, in proximity to the SCI1 (Fig. 5c).
3.5. Integrated assessment of the air quality The biomonitoring results were consistent with those obtained from the monitoring of chemical species, confirming that the anthropic pressure influences the lichen communities. In general, most of the area was characterized by good level of naturalness or low level of alteration, associated to a small anthropic pressure, as also confirmed by the predominance of lichens with foliose narrow-lobed growth form. This general low anthropic pressure was probably caused by agricultural activity, which constitutes a source of diffuse pollution of low environmental impact, but it may be the main cause of the medium–high eutrophication of the substrates. During the fertilization, high amount of nutrients reach the trees barks, creating the environmental condition for a
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Fig. 5. Map of daily mean concentration distribution of the chemical species: ozone (a), nitrogen oxides (b), and isoprene (c).
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selection among lichens community. This is corroborated by the lichen species frequency data: all the recorded lichen species belong to the Xantorium and Lecanorion group, which are typical in anthropized environment, with high level of nutrients. As affirmed by Frati et al. (2008) and Ruisi et al. (2005) the presence of lichen clearly nitrophilus, such as X. parietina, H. adglutinata, L. elaeochroma, indicates a medium–high eutrophication due to the heavy agricultural activity. The worst IBL values were in proximity of specific punctual source of pollution. The site J, located next to the glass factories and defined by the ILB in the status of high alteration, presented the highest mean NOx concentration (Fig. 5b). It is plausible that the repeated exposure over the years to high NOx concentrations caused a reduction of lichen biodiversity. The second critical area, site K, was close to quarries areas and a station for the treatment of quarried material (Fig. 5a). In this area the NOx and ozone average concentrations were low, because there were not pollution sources, but the limited biodiversity is probably due to the dust generated by mining activities. In fact, as affirmed by Del Guasta and Sbrilli (1990), lichens are sensitive also to the dust, especially of calcareous origin. Actually, a survey of the area revealed that, the riverbed Trigno, which passes through this zone, was in a severe degradation state, while the riparian vegetation (shrubs, hornbeam and poplars) leaves were very damaged. Finally the prevailing wind direction in the area (W–WNW) corroborates the hypothesis that the state of alteration of the lichen flora observed in the monitoring site K is to be ascribed to the effects of the transport of dust surrounding the active quarries. The suffering state of the lichens in these two critical areas was confirmed also by the concentrations of isoprene, which were the lowest in the entire monitored area (Fig. 5c). As evinced by the map in Fig. 5a, the highest concentrations of ozone were recorded in the area surrounding the landfill (site 6). Considering the high potential of the wind in transporting ozone and the prevalent wind direction, it seems plausible that the ozone detected in site 6 and the observed relative reduction in lichen biodiversity were due to the NOx and VOC emission from the landfill (Derwent et al., 2007).
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4. Conclusion The lichens biodiversity is confirmed to be an excellent indicator of environmental pollution, as demonstrated by the significative inverse correlation between IBL distribution with NOx and ozone. Furthermore the lichen biodiversity resulted to be influenced also by the level of eutrophication of their substrates and by the presence of element of disturbance, such as the calcareous dust, which inhibit or restrict lichen communities, depending on the specific tolerance. They are complicating elements especially in Mediterranean areas, subjected to Saharan dust intrusion. Results of the present survey and elaboration showed that the station of methane storage did not seem influencing negatively the air pollution. There were not critical areas within the station considering both biomonitoring and chemicals concentration, a part from zones with specific punctual pollution sources, the landfill (considering the ozone concentration) and the quarries and the glass industries (considering the IBL). The highest values of IBL, corresponding to a state of environmental quality medium–low naturalness, were observed within the station area at a distance of about 2.8 km from the compression station, in SCI1 (IT7140126 ‘‘Gessi di Lentella’’). In conclusion the results of the two monitorings, direct and biomonitoring, are in agreement, but the information that they provide are substantially different: the ILB distribution provides information mainly covering a wide period of time and the past, as the selection of species occurred over time. On the other hand the current direct monitoring allows to get a clear picture of the actual spatial distribution of pollutants, obtained from punctual measure of some specific chemical species and interpolation techniques. The biomonitoring can difficulty be considered an alternative methods to the instrumental monitoring, but taking account of its low cost respect to the monitoring station (especially lab analysis), the biomonitoring should be correctly used for several application such as the rapid individuation of risky area, the evaluation of measure adopted to reduce pollution emission for long period, or to individuate the potential harmful area, to suggest where automatic station should be installed. Acknowledgments
3.6. Correlation between IBL and the chemical species distribution The correlation between IBL and the chemical species obtained with the correlation matrix tool are all significative. Specifically the correlation between NOx and IBL is inverse ( 0.96), confirming that the presence of elevate concentration of NOx in the atmosphere determines a reduction in the lichens biodiversity. Similar relationship was found between IBL and ozone ( 0.80). Evidently also the ozone influences the lichen biodiversity development and high level of ozone concentration causes a reduction of lichens biodiversity. The relation between IBL and isoprene was positive (0.67). Indeed since the isoprene is prevalently generated by plants, its presence indicates an area with few pollution sources, and consequently an high level of lichen biodiversity. The correlation coefficients between the chemical species showed that ozone was inversely correlated with the NOx ( 0.57). This is reasonable since NOx are the main precursors of ozone. The presence of one excludes the presence of the other. The relationship between ozone and isoprene is inverse, though not significant ( 0.42). The isoprene is instead significantly and inversely correlated with NOx ( 0.88), emphasizing the diverse sources: vegetated and natural areas for isoprene, industrial and urban areas (combustion process) for nitrogen oxides.
The authors thank Stogit S.p.A. and Proger S.p.A. for the research funding and the collaboration to the project. References ANPA, 2001. IBL Indice di Biodiversità Lichenica. Manuale ANPA, Manuali e Linee Guida, 2/2001, Dipartimento stato dell’Ambiente, Controlli e Sistemi Informatici. Roma, 85pp. Castello, M., Skert, N., 2005. Evaluation of lichen diversity as an indicator of environmental quality in the North Adriatic submediterranean region. Sci. Total Environ. 336, 201–214. Del Guasta, M., Sbrilli, G., 1990. Distribuzione di licheni epifiti in un’area industriale dotata di rete di monitoraggio chimico dell’inquinamento atmosferico. Acqua aria 9, 787–797. Derwent, R.G., Jenkin, M.E., Passant, N.R., Pillino, M.J., 2007. Photochemical ozone creation potentials (POCPs) for different emission sources of organic compounds under European conditions estimated with Master Chemical mechanism. Atmos. Environ. 41, 2570–2579. Erisman, J.W., Grennfelt, P., Sutton, M., 2003. The European perspective on nitrogen emission and deposition. Environ. Int. 29, 311–325. Frati, L., Brunialti, G., Caastello, M., 2003. Interpretazione dei dati di Biodiversità lichenica nella fascia bioclimatica adriatica. In: Proceeding of the Workshop ‘‘Strumenti tecnici e biologici per il monitoraggio ambientale-Licheni come biosensori’’. Torino, 3-4 aprile 2003. Frati, L., Santoni, S., Nicolardi, V., Gaggi, C., Brunialti, G., Guttova, A., Gaudino, S., Pati, A., Pirintsos, S.A., Loppi, S., 2007. Lichen biomonitoring of ammonia emission and nitrogen deposition around a pig stockfarm. Environ. Pollut. 146, 311–316.
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Frati, L., Brunialti, G., Loppi, S., 2008. Effects of reduced nitrogen compounds on epiphytic lichen communities in Mediterranean Italy. Sci. Total Environ. 407 (1), 630–637. Gilbert, O.L., 1976. An alkaline dust effect on epiphytic lichens. Lichenologist 8, 173–178. Gombert, S., Asta, J., Seaward, M.R.D., 2003. Correlation between the nitrogen concentration of two epiphytic lichens and the traffic density in an urban area. Environ. Pollut. 123, 281–290. Gombert, S., Asta, J., Seaward, M.R.D., 2004. Assessment of lichen diversity by index of atmospheric purity (IAP), index of human impact (IHI) and other environmental factors in an urban area (Grenoble, southeast France). Sci. Total Environ. 324, 183–199. Loppi, S., De Dominicis, V., 1996. Effects of agriculture on epiphytic lichen vegetation in Central Italy. Israel J. Plant Sci. 44, 297–307. Loppi, S., Pirintsos, S.A., De Dominicis, V., 1997. Analysis of the distribution of epiphytic lichens on Quercus pubescens along an altitudinal gradient in a Mediterranean area (Tuscany, central Italy). Israel J. Plant Sci. 45, 53–58. Loppi, S., Ivanov, D., Boccardi, R., 2002. Biodiversity of epiphytic lichens and air pollution in the town of Siena (Central Italy). Environ. Pollut. 116, 123–128. Lozano, A., Usero, J., Vanderlinden, E., Raez, J., Contreras, J., Navarrete, B., 2009. Air qualità monitorino network design to control nitrogen dioxide and ozone, applied in malaga, Spain. Microchem. J. 93, 164–172. Munzi, S., Ravera, S., Caneva, G., 2007. Epiphytic lichens as indicators of environmental quality in Rome. Environ. Pollut. 146, 350–358.
Nali, C., Balducci, E., Frati, L., Paoli, L., Loppi, S., Lorenzini, G., 2007. Integrated biomonitoring of air quality with plants and lichens: a case study on ambient ozone from central Italy. Chemosphere 67, 2169–2176. Nash III, T.H., 1996. Lichen Biology. Cambridge University Press, Cambridge. Pieri, L., Matzneller, P., Gaspari, N., Marotti, I., Dinelli, G., Rossi, P., 2009. Bulk atmospheric deposition in the Southern Po Valley (Northern Italy). Water Air Soil Pollut. 210, 155–169. Pinho, P., Augusto, S., Martins-Loução, M.A., Pereira, M.J., Soares, A., Máguas, C., Branquinho, C., 2008. Causes of change in nitrophytic and oligotrophic lichen species in a Mediterranean climate: impact of land cover and atmospheric pollutants. Environ. Pollut. 154, 380–389. Ruisi, S., Zucconi, L., Fornasier, F., Paoli, L., Frati, L., Loppi, S., 2005. Mapping environmental effects of agriculture with epiphytic lichens. Israel J. Plant Sci. 53 (2), 115–124. Scheidegger, C., Schroeter, B., 1995. Effects of ozone fumigation on epiphytic macrolichens: ultrastructure, CO2 gas exchange and chlorophyll fluorescence. Environ. Pollut. 88, 345–354. Snedecor, G.W., Cochran, W.G., 1968. Statistical Methods, 6th ed. The Iowa State University Press, Ames, Iowa. Van Dobben, H.F., De Bakker, A.J., 1996. Re-mapping epiphytic lichen biodiversity in The Netherlands: effects of decreasing SO2 and increasing NH3. Acta Botanica Neerlandica 45 (1), 55–71.
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Chemosphere journal homepage: www.elsevier.com/locate/chemosphere
Integrated environmental quality monitoring around an underground methane storage station Linda Pieri a,⇑, Marco Vignudelli a, Fabrizio Bartolucci b, Fiorenzo Salvatorelli a, Cesare Di Michele c, Nicola Tavano d, Paola Rossi a, Giovanni Dinelli a a
Department of Agricultural Science, University of Bologna, Italy University of Camerino – Aquila, Italy PROGER S.p.A., Italy d Agronomist, Pescara, Italy b c
h i g h l i g h t s The environmental quality of an area with a methane station was evaluated. Two monitorings were applied: measures of air components and lichens biomonitoring. The two monitorings results were in agreement. The environment quality of the area surrounding the station did not show signs of declining. Results suggest the validity of biomonitoring to integrate the environmental network for pollution assessing.
a r t i c l e
i n f o
Article history: Received 21 March 2014 Received in revised form 9 March 2015 Accepted 10 March 2015 Available online 29 March 2015 Handling Editor: J. de Boer Keywords: Biomonitoring Lichens Air quality Natural gas Italy
a b s t r a c t The study reports an integrated environmental quality monitoring of a 100 km2 area in central Italy mostly occupied by an underground station of methane storage, working since 1982. The nitrogen oxides, ozone and isoprene concentration detached with a network monitoring of passive filters were compared with the results of lichens biomonitoring. Data from the two monitorings were in accordance: there was an inversely correlation between lichen biodiversity index (IBL) and NOx ( 0.96) and ozone ( 0.80), and a positive correlation between IBL and isoprene (0.67). IBL indicated that the area ranged between medium naturalness and medium alteration status, values fully compatible with the medium–high level of eutrophication, caused by intensive agriculture. Only two areas were in high alteration status, due to their proximity to glass factories and to a quarries area. Despite almost thirty years of activity, the environment quality of the area around the station did not show signs of declining. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Natural gas is an essential resource as it represents a source of clean energy for homes, public buildings and businesses. Italy is in close dependence on other countries: more than 40% of Italian natural gas consumption is imported, with growth forecast to 70% in 2020.
⇑ Corresponding author at: Department of Agricultural Science, University of Bologna, viale Fanin n.44, 40127 Bologna, Italy. Tel.: +39 051 2096693; fax: +39 051 2096241. E-mail address: [email protected] (L. Pieri). http://dx.doi.org/10.1016/j.chemosphere.2015.03.009 0045-6535/Ó 2015 Elsevier Ltd. All rights reserved.
The storage of natural gas can be considered a strategic process. In fact, while the gas supply is basically constant throughout the year, the demand has a marked seasonal variation and this is more evident in case of adverse weather that result in the absence of cover the natural gas needs. Since during the compression activity there are emissions of chemical species, these stations may be sources of pollution and therefore require a monitoring to assess their environmental impact. This environmental monitoring can be due through direct and continuous monitoring of the main pollutants, generally operated with stationary or mobile automatic stations. Among these, passive filter has been increasingly used, because of low operating cost, simplicity of sampling, independence from the
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electricity and good correlation results with compared direct monitoring methods (Lozano et al., 2009). The measurements of potential harmful chemical species are necessary to evaluate the effect of polluting sources, but they do not provide information on the impact of these pollutants on the environmental matrices. For this kind of evaluations the biomonitoring is very suitable, because assesses the effects of the atmospheric constituents through the observations of biological materials. The most appropriate biological species used for biomonitoring are lichens, for their demonstrated high sensitivity to air pollution (Loppi et al., 2002; Gombert et al., 2004; Munzi et al., 2007; Frati et al., 2007; Pinho et al., 2008). This feature is due to their slow growth and efficiency in absorbing nutrients from air and water (Nash, 1996). Among the biomonitoring methods, the official procedure ANPA (2001) consists in the determination of the lichen biodiversity index (ILB). This method is most widely applied in Italy and the ILB is computed by the sum of the presence of lichen species occurred in a defined grid. Its evaluation allows to define the areas with an alteration state, based on the scale of naturalness/alteration proposed by Frati et al. (2003). The thallus physiological properties and structure make lichens mainly dependant on atmospheric deposition for their nutrition, especially for the nitrogen supply (Gombert et al., 2003). Several researches demonstrate an influence of nitrogen deposition on the lichen communities (Loppi and de Dominicis, 1996; Van Dobben and De Bakker, 1996), as a high concentration of nitrogen in environmental matrices leads to regional acidification and eutrophication (Erisman et al., 2003) and therefore the selection of lichen species suitable to these environmental conditions. Indeed, the level of substrate acidity can be also influenced by dust deposition. Calcareous dust, typically present in Mediterranean areas (Pieri et al., 2009) or deriving from human activity (e.g. rushing machinery in quarries), raises the bark pH, favoring the selection of lichen species adapted to basic substrates (Gilbert, 1976; Loppi and De Dominicis, 1996; Loppi et al., 1997). While the relationship nitrogen-lichens and dust-lichens is quite known, previous studies do not identify a clear and univocal correlation between ozone and lichens communities: Nali et al. (2007) reports no correlation between ozone patterns and lichen distribution (Parmelia and Lecanora genus), while Scheidegger and Schroeter (1995) highlights that high ozone concentration determines biophysical and physiological modifications on several species. The tropospheric ozone (O3) reflects the climatic conditions and the presence of precursor substances sources (VOCs, NOx, CH4, CO, isoprene). The stations for methane storage are VOCs sources, emitting nitrate oxides, sulphur oxides, carbon dioxide, and methane, during the combustion processes, but their contribution in the ozone production is low (Derwent et al., 2007). The two monitorings (direct and biomonitoring) provide information substantially different: the direct monitoring of pollutants provides an assessment of the current state of air quality, while the biomonitoring photographs an ecological condition, stabilized in a wider timeframe. The correlation between IBL and the main pollutants distribution could suggest the validity of biomonitoring to integrate the environmental network for assessing the atmospheric pollution. The aim of this paper is three folds: (i) evaluating the environmental impact of a station of methane storage, (ii) comparing and finding correlation between two approaches of environmental quality monitoring, the pollutants direct monitoring and the lichens biomonitoring; (iii) providing a general picture of pollution pattern of the investigated area and determining the main causes of changes in lichens communities.
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2. Materials and methods 2.1. Location The monitored area is located in an hilly sub-mediterranean area of about 100 km2 in Central Italy. During the monitoring period, weather stations within the area recorded mean temperature ranging between 16.1 °C and 36.4 °C, with mean of 26 °C. Compared with the climate historical data, this period can be considered typical for the area. The wind direction was predominantly W–NW, with some episodes from E–ESE. Within the area there are four Site of Community Importance (SCI), in which natural habitats and animal and vegetables species have to be safeguarded: SCI1 ‘‘Gessi di Lentella’’ (IT7140126), SCI2 ‘‘Macchia Nera – Colle Serracina’’(IT228226), SCI3 ‘‘Fiume Trigno’’(IT7140127), and SCI4 ‘‘Colle Gessaro’’ (IT 222212) (Fig. 1). The main potential sources of NOx and VOCs within the area are the following: (i) an underground station of storage and distribution of methane, (ii) a landfill, (iii) a mining zone, and (iv) an industrial area. The rest of the surface is occupied by heavy cultivated arable lands (Fig. 1). In particular the methane station, located at Cupello (80 km South-East from Chieti), covers about the 80% of the total monitored area. In the past the station was used for primary production of methane, while since 1982 the activity has been limited to the compression and the storage of methane coming from the national network, and the delivery when requested by customers. The mean annual volume of the stored gas is about 8.3 109 S m3, and the delivery is about 7.6 109 S m3. The storage occurs within a gas compression station, which during spring and summer stocks methane in underground reservoirs through wells distributed throughout the station, while in fall and winter the gas is distributed to customers. The landfill and the mining zones are located within the area of the methane storage station, the first one in North-West and the second in South-East direction (Fig. 1). The landfill has a volume of 300 000 m3 and contains a plant of biogas and cogeneration. In the quarries area, sand, clay, gravel, and rock are excavated from the ground. Moreover, next to the excavation area, there is a station for the treatment of quarried material (brick industry with kilns for the production of expanded clay). Finally, outside the storage station, there is an industrial area, with two glass factories. Technical reports on environmental impact provided by the glass factories show NOx emissions of 320 t ha 1, while in an official document, the methane station declares NOx emissions of 80 t ha 1. There are no official emission data of the other potential sources of pollution. However, as visually observed, the area occupied by quarries is characterized by dust arising from the excavations. Moreover, a survey of the area revealed that, the riverbed Trigno, which passes through this zone, is in a severe degradation state, while the riparian vegetation (shrubs, hornbeam and poplars) leaves are very damaged.
2.2. Monitoring of air components The direct air quality monitoring network was based on a total of 12 sampling points. The monitoring was done through passive filters, which provided the daily average concentration for each week of the period June 18–September 10, 2012. The monitored potentially harmful substances were ozone and its common precursors, nitrogen oxides (NO and NO2) of anthropogenic origin, and isoprene of prevalent biogenic origin. The detected concentrations were compared with the EU Limit Values (Directive 2008/50/ EC on air quality).
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Fig. 1. Monitoring area: the black dots are the twelve passive sampler air monitoring stations, the star indicates the compression station and the red line marks the total area of storage. The figure shows also the location of the landfill, the industrial area, the quarries and the four Site of Community Importance (SCI). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
2.3. Lichens Survey and methodology The monitoring of lichens was conducted using the official procedure ANPA (2001), which is currently the national benchmark for biomonitoring. Eleven primary sampling units (PSU) were selected on the territory corresponding to cells cartographic 1 1 km2. For each PSU, 4 Secondary Sampling Unit (SSU) have been identified. They were placed in each of the 4 quadrants that divide the PSU (area of each quadrant = 0.25 km2), according to the directions NE (SSU 01), SE (SSU 02), SW (SSU 03), NW (SSU 04). The SSU centre was 177 m from the PSU centre and from the centre of the respective quadrant. The circular area of each SSU was equal to approximately 0.05 km2 for a radius of 125 m. Within this area, trees suitable for the detection were selected. When there were no fitted tree within the SSU, a replacement was identified, moving along the relative directress (to the NE for the quadrant 1, SE for the quadrant 2, SW for the quadrant 3, and NW for the quadrant 4). The suitable trees should respect the requirements of the ANPA guidelines (free-standing tree with inclination not exceeding 10°, trunks no damaged or irregular, circumference >60 cm) and be close to the centre of the SSU. Each sampled tree was georeferenced. According to the ANPA procedure and for a good comparability of results, biomonitoring was conducted only on oaks, belonging to the genus Quercus, in particular the species Quercus pubescens Willd. subsp. pubescens (38/40, equal to 95% of the trees analyzed) and Quercus cerris L. (2/40, accounting for 5% of sampled trees). The acid bark of these trees is more favourable for the growth of lichens. Trees in closed forest vegetation were excluded and, where possible, trees sited in clearings, forest, and road margins were preferred, trying to maintain a distance of 10 m between adjacent trunks.
For the determination of the frequency of lichens, in each oak a sampling grid, consisting of four sub-units, was used. The grid subunits were placed on the trunk of oak at least one meter above the ground, each of them directing at the four cardinal points. To exclude from sampling any unsuited part of the trunk, a shift from verticality up to 20° clockwise was allowed when positioning grid sub-units (Castello and Skert, 2005). Damaged trunks or with presence of evident knots, corresponding to seepage tracks of rainwater, or with more than 25% cover of bryophytes were excluded from the samplings. 2.4. Procedures for the calculation and interpretation of lichen biodiversity For each oak, the index of lichen biodiversity (ILB) was computed, with the sum of the frequencies detected in each cardinal point (minimum 3 oaks). The ILB value of each monitoring site was the average of the values detached in oaks. To interpreter the ILB values in term of environmental quality, the scale of environmental status naturalness–alteration, proposed by Frati et al. (2003) and adapted for a dry sub-mediterranean climate was used. The status of the environment can be described in term of alteration from a natural condition, where with natural we mean the areas free from heavy anthropization and far from important pollution sources (Nali et al., 2007). 2.5. Statistical analysis of data The ILB and the concentration of the chemical species NOx, ozone, and isoprene were converted in digital raster maps and interpolated with the IDW spatial analyst extension for ArcGis 10 (ESRI). The ILB values were then correlated with each single chemical species, using the correlation matrix tool, provided by the
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ArcGis 10. The correlation matrix provides a measure of the dependency between the two datasets, showing the values of correlation coefficients that depict their relationship (Snedecor and Cochran, 1968). 3. Results and discussion 3.1. Biomonitoring with lichens and ecological indices Overall, in the eleven survey stations (A–K, Fig. 2), eight lichen species were classified (Table 1). The main species were Xanthoria parietina (L.) Th.Fr. (34/40 surveys) and Physcia biziana (A.Massal.) Zahlbr. (30/40 surveys), which together make up the 58.8% of the lichen flora present in the whole area. Hyperphyscia adglutinata (Flörke) H.Mayrhofer & Poelt (17/40 surveys) and Candelariella xanthostigma (Ach.) Lettau (11/40 surveys) accounted for 26.1% of total lichens, while the remaining 15.1% included species occurring at low frequency, namely Lecanora subfusca (L.) Ach. aggr. (7/40 surveys), Lecidella elaeochroma (Ach.) M. Choisy (4/40 surveys),
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Caloplaca cerina (Hedw.) Th.Fr. (4/40 surveys), and Physconia distorta (With.) J.R.Laundon (1/40 surveys). The eight identified species are attributable to only two of the six prevalent vegetation units in Italy, Xanthorion and Lecanorion (ANPA, 2001). Xanthorion (P. biziana, X. parietina, H. adglutinata, C. cerina, P. distorta, C. xanthostigma) is a community of relatively light-loving species, xerophile, neutral-basophile and nitrophilous present particularly in anthropic environments and to the south side of isolated trees. In areas where the atmospheric humidity is a limiting factor, some of these species also penetrate in anthropic environments, proving resistance to atmospheric pollution. The four dominant species of the present biomonitoring (P. biziana, X. parietina, H. adglutinata) are adapted to environments with high or medium levels of antrophization, so they are considered indicator species of the Xanthorion group. Lecanorion (L. subfusca aggr. and L. elaeochroma) is a community of crustose lichens pioneers of rind smooth, generally present in isolated trees, and they often precede or are mixed with species
Fig. 2. Cartography of lichen biomonitoring. The figure shows the 11 PSU (A–K), each one subdivided in 4 SSU. The dots indicate the position of individual oaks. The central storage is indicated in the figure by the factory symbol.
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Table 1 List of the eight lichen species surveyed during the biomonitoring study and their mean frequency in the 11 survey stations (PSU). Lichens species
Primary Sampling Units (PSU)
Physcia biziana Xanthoria parietina Hyperphyscia adglutinata Lecidella elaeochroma Caloplaca cerina Lecanora subfusca aggr. Physconia distorta Candelariella xanthostigma
A
B
C
D
E
F
G
H
I
J
K
6.5 2.8 5.4 – – – 1.3 –
6.5 5.2 6.6 – – – – 1.1
5.6 2.7 0.8 1.3 6.9 – – –
1.9 7.8 – 0.1 – – – –
8.1 3.2 7.3 – 0.9 – – –
8.6 3.2 – 6.9 1.1 – – –
4.8 4.0 0.1 3.1 2.3 – – –
9.2 3.3 5.3 6.1 1.4 3.8 – –
6.8 1.5 2.7 2.0 1.9 – – –
2.7 0.7 4.4 – – 1.3 – –
2.8 6.0 – – – – – –
of Xanthorion. They are relatively frequent in anthropic environments. X. parietina and P. biziana were detected in all the stations: the dominance of a limited number of species, spread throughout the biomonitoring territory, suggests rather uniform environmental and ecological conditions. According to the ANPA procedure, the species frequency data (Table 1) were processed together with the indices of ecological tolerance (pH, light level, humidity condition, and eutrophication) of each lichen species, to characterize ecologically the different survey stations (data from ITALIC, http://dbiodbs.univ.trieste.it/). Table 2 puts in evidence that PSUs ecological characteristics were very homogeneous: the substrate (bark) has pH classified as sub-neutral (3.0–3.7), direct exposure to light (4.1–4.4), low humidity conditions (3.5), and medium–high level of eutrophication (3.3–3.8). 3.2. Lichen adaptation ability Since the biomonitoring was conducted selecting acidic peel oaks, the presence of species not suitable to sub-acid substrates (i.e. P. biziana, H. adglutinata, C. cerina, L. subfusca aggr., P. distorta) indicates an abnormality. Probably the colonization of those species is due to external factors, such as calcareous dust, which raise
Table 2 Ecological indices of the 11 monitoring stations (PSU), based on the average frequency of detected lichen species. PSU
Ecological parameters pHa
Lightb
Aridityc
Eutrophicationd
A B C D E F G H I J K
3.5 3.4 3.3 3.0 3.6 3.0 3.1 3.3 3.3 3.7 3.0
4.4 4.3 4.1 4.1 4.4 4.2 4.1 4.3 4.3 4.4 4.1
3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5
3.7 3.7 3.5 3.5 3.7 3.3 3.4 3.5 3.5 3.8 3.5
Mean
3.3
4.2
3.5
3.5
Formalism on the interpretation of the different levels or states for growth form and ecological index (ANPA, 2001): a Index of pH of the substrate (5 states): 1 – very acid, 2 – sub-acid, 3 – subneutrum, 4 – slightly basic, 5 – basic. b Index of light (5 states): 1 – heavily shaded situations, 2 – shaded situations, 3 – situations with diffused light but lack of direct sunlight, 4 – sites exposed to direct sunlight, but not exposed at noon except at low inclinations of the surface, 5 – in sites with high direct irradiation. c Index of aridity (5 states): 1 – igrophytic (areas with frequent fog), 2 – fairly igrophytic, 3 – mesophytic, 4 – xerophyitic (dry situations, but absent from places extremely arid), 5– very xerophyitic. d Eutrophication (5 states): 1 – none, 2 – very weak, 3 – medium, 4 – relatively high, 5 – very high.
pH bark. Specifically in the quarries zones, the calcareous dust derives plausibly from the mining extraction. The medium–high level of eutrophication in all the investigated area is comparable with the intensive agricultural activity, considering also the minimal presence of industrial activities and the limited vehicular traffic. This is corroborated by the thallus and leaf features to explain the ecological indices results. The thallus structure (foliose or crustose) and the leaves shape (with broad or narrow lobes) are important in determining the exchange surface with the atmosphere and thus the ability of lichens to grow in a specific area. In the same air quality condition, lichens with foliose thallus are generally more susceptible than those with crustose thallus, because they expose a greater leaf surface area for the absorption and deposition of polluting agents. As shown in Fig. 3, in the studied area the most common species had foliose thallus (X. parietina, P. biziana, H. adglutinata, and P. distorta), with a discrete predominance of narrow-leaved lichens (P. biziana, H. adglutinata, P. distorta). This would suggest an ecological pressure, as the presence of pollutants in the atmosphere, with low environmental impact. This is compatible with pollutants deriving from an heavy agricultural activity. 3.3. Lichen biodiversity index (ILB) The collected data allowed the computation of the index of lichen biodiversity (IBL). The ILB values in the survey stations (A–K) ranged between 32.2, which corresponds to high level of alteration (site K) to 108.0, which is equivalent to medium naturalness (site H). The mean ILB (calculated on the basis of the values observed in the 11 PSUs) amounted to 65 ± 28, corresponding to low alteration. Fig. 4 shows the Lichen Biodiversity Index (ILB) naturalness/alteration map for the monitored area. It was created using the ILB values of the 40 analyzed oaks and applying methods of spatial interpolation.
Fig. 3. Percentage of the diverse growth forms (foliose and crustose thallus or foliose broad-lobed and foliose narrow-lobed) in the investigated area.
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Fig. 4. Naturalness–Alteration map of the bio-monitored area, derived by interpolation of the ILB values observed for the 40 investigated oaks.
Using the scale of IBL of Frati et al. (2003) to interpreter the values, it is evident that most of the area, 70%, was characterized by a lichen biodiversity corresponding to a state of low or medium alteration (classes 3a and 3b), the 19% was in a state of naturalness (classes 2a and 2b), and the 11% was in a state of high alteration or very high alteration (classes 4a and 4b). Specifically, the methane storage station area had the following ILB: 20% had medium alteration (class 3b), 70% had low alteration (class 3a), and the remaining 10% was in the state of medium–low naturalness (class 2). Thus, all the sites had acceptable levels of lichen biodiversity, with the exception of two critical areas, sites J and K, located in zones with high level of anthropic pressure: site K, in the south of the methane station area, is near the quarries, while site J is located in the industrial area. The best IBL values, which identify a medium–low naturalness status, were observed in the Site of Community Importance SCI1 (IT7140126 ‘‘Gessi di Lentella’’). The SCI1 is mostly located within the storage station area, at a distance of about 2.8 km from the compression station. Despite almost thirty years of compression and storage of methane, this SCI did not reveal an evident symptom of decline in terms of environmental quality; conversely it resulted to be the area with the most natural condition of the entire area subjected to biomonitoring.
3.4. Monitoring of the chemical species ozone, nitrogen and isoprene The pollutant chemicals concentration detected with passive samplers were compared with the EU Limit Values indicted in the EU Directive 2008/50/EC on air quality. During the sampling period, ozone concentrations ranged between 51 ppb and 103 ppb, respectively recorded in site 10
and 6 (Fig. 5a). Since the ozone threshold limit for vegetation protection is 65 ppb (mean on 24 h), only the concentration of the site 6, located in proximity of the landfill, were high and dangerous. Nitrates (NO + NO2) were always and everywhere below the EU reference limit (EU Limit Value for sensitive vegetation and ecosystems is 30 ppb), with mean values between 6.1 ppb and 15.9 ppb, recorded respectively in site 6 and 8. The only exceptions were the sites 10 and 11, both close to the industrial area, where the average values were 41.6 ppb and 29.8 ppb respectively, with peaks of 55 ppb for the10, recorded on 28, August (Fig. 5b). Finally, the concentration of isoprene fluctuated between 0.3 and 4.8 ppb. For this chemical species no reference values are fixed, but the lowest values, indicating a low presence of vegetation areas, were recorded at sites 10 and 11 in the industrial area with glass factories. Conversely the highest were detected at site 2, located in the south-west, in proximity to the SCI1 (Fig. 5c).
3.5. Integrated assessment of the air quality The biomonitoring results were consistent with those obtained from the monitoring of chemical species, confirming that the anthropic pressure influences the lichen communities. In general, most of the area was characterized by good level of naturalness or low level of alteration, associated to a small anthropic pressure, as also confirmed by the predominance of lichens with foliose narrow-lobed growth form. This general low anthropic pressure was probably caused by agricultural activity, which constitutes a source of diffuse pollution of low environmental impact, but it may be the main cause of the medium–high eutrophication of the substrates. During the fertilization, high amount of nutrients reach the trees barks, creating the environmental condition for a
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Fig. 5. Map of daily mean concentration distribution of the chemical species: ozone (a), nitrogen oxides (b), and isoprene (c).
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selection among lichens community. This is corroborated by the lichen species frequency data: all the recorded lichen species belong to the Xantorium and Lecanorion group, which are typical in anthropized environment, with high level of nutrients. As affirmed by Frati et al. (2008) and Ruisi et al. (2005) the presence of lichen clearly nitrophilus, such as X. parietina, H. adglutinata, L. elaeochroma, indicates a medium–high eutrophication due to the heavy agricultural activity. The worst IBL values were in proximity of specific punctual source of pollution. The site J, located next to the glass factories and defined by the ILB in the status of high alteration, presented the highest mean NOx concentration (Fig. 5b). It is plausible that the repeated exposure over the years to high NOx concentrations caused a reduction of lichen biodiversity. The second critical area, site K, was close to quarries areas and a station for the treatment of quarried material (Fig. 5a). In this area the NOx and ozone average concentrations were low, because there were not pollution sources, but the limited biodiversity is probably due to the dust generated by mining activities. In fact, as affirmed by Del Guasta and Sbrilli (1990), lichens are sensitive also to the dust, especially of calcareous origin. Actually, a survey of the area revealed that, the riverbed Trigno, which passes through this zone, was in a severe degradation state, while the riparian vegetation (shrubs, hornbeam and poplars) leaves were very damaged. Finally the prevailing wind direction in the area (W–WNW) corroborates the hypothesis that the state of alteration of the lichen flora observed in the monitoring site K is to be ascribed to the effects of the transport of dust surrounding the active quarries. The suffering state of the lichens in these two critical areas was confirmed also by the concentrations of isoprene, which were the lowest in the entire monitored area (Fig. 5c). As evinced by the map in Fig. 5a, the highest concentrations of ozone were recorded in the area surrounding the landfill (site 6). Considering the high potential of the wind in transporting ozone and the prevalent wind direction, it seems plausible that the ozone detected in site 6 and the observed relative reduction in lichen biodiversity were due to the NOx and VOC emission from the landfill (Derwent et al., 2007).
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4. Conclusion The lichens biodiversity is confirmed to be an excellent indicator of environmental pollution, as demonstrated by the significative inverse correlation between IBL distribution with NOx and ozone. Furthermore the lichen biodiversity resulted to be influenced also by the level of eutrophication of their substrates and by the presence of element of disturbance, such as the calcareous dust, which inhibit or restrict lichen communities, depending on the specific tolerance. They are complicating elements especially in Mediterranean areas, subjected to Saharan dust intrusion. Results of the present survey and elaboration showed that the station of methane storage did not seem influencing negatively the air pollution. There were not critical areas within the station considering both biomonitoring and chemicals concentration, a part from zones with specific punctual pollution sources, the landfill (considering the ozone concentration) and the quarries and the glass industries (considering the IBL). The highest values of IBL, corresponding to a state of environmental quality medium–low naturalness, were observed within the station area at a distance of about 2.8 km from the compression station, in SCI1 (IT7140126 ‘‘Gessi di Lentella’’). In conclusion the results of the two monitorings, direct and biomonitoring, are in agreement, but the information that they provide are substantially different: the ILB distribution provides information mainly covering a wide period of time and the past, as the selection of species occurred over time. On the other hand the current direct monitoring allows to get a clear picture of the actual spatial distribution of pollutants, obtained from punctual measure of some specific chemical species and interpolation techniques. The biomonitoring can difficulty be considered an alternative methods to the instrumental monitoring, but taking account of its low cost respect to the monitoring station (especially lab analysis), the biomonitoring should be correctly used for several application such as the rapid individuation of risky area, the evaluation of measure adopted to reduce pollution emission for long period, or to individuate the potential harmful area, to suggest where automatic station should be installed. Acknowledgments
3.6. Correlation between IBL and the chemical species distribution The correlation between IBL and the chemical species obtained with the correlation matrix tool are all significative. Specifically the correlation between NOx and IBL is inverse ( 0.96), confirming that the presence of elevate concentration of NOx in the atmosphere determines a reduction in the lichens biodiversity. Similar relationship was found between IBL and ozone ( 0.80). Evidently also the ozone influences the lichen biodiversity development and high level of ozone concentration causes a reduction of lichens biodiversity. The relation between IBL and isoprene was positive (0.67). Indeed since the isoprene is prevalently generated by plants, its presence indicates an area with few pollution sources, and consequently an high level of lichen biodiversity. The correlation coefficients between the chemical species showed that ozone was inversely correlated with the NOx ( 0.57). This is reasonable since NOx are the main precursors of ozone. The presence of one excludes the presence of the other. The relationship between ozone and isoprene is inverse, though not significant ( 0.42). The isoprene is instead significantly and inversely correlated with NOx ( 0.88), emphasizing the diverse sources: vegetated and natural areas for isoprene, industrial and urban areas (combustion process) for nitrogen oxides.
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