Correlation of atmospheric purity index to the diversity of lichens in the Horton Plains National Park, Sri Lanka

: Horton Plains National Park (HPNP) has been declared as a world heritage site, because of its unique biodiversity. Die-back of certain areas of this park is widely believed to be due to acidic precursor depositions carried over from other parts of the country and also from neighboring countries. Air pollution data for the two pollutants, NO 2 and SO 2 were obtained from the passive air sampling method. The data revealed that the concentrations of ambient NO 2 and SO 2 were very low in the HPNP. The variations of ambient NO 2 and SO 2 concentrations during the study period showed insignificant positive correlation (p≥ 0.05) with the rainfall data. Considering the variations of these two pollutants with Relative Humidity and the number of vehicles visiting HPNP, both pollutants had insignificant positive correlation. The Index of Atmospheric Purity (IAP) value obtained for the whole area of the HPNP was 54.22. This value belongs to the quality level 5 which represents the ‘very low’ pollution level. The results including lichen distribution and air quality data could confirm that the ambient air quality at HPNP is very high. The high diversity of lichens and the minimum levels of air pollutants suggested that the forest health of HPNP is at a favorable level. Therefore, it is essential to maintain at least the current air pollution level of HPNP in order to conserve the


INTRODUCTION
Horton Plains National Park of Sri Lanka, a cloud forest, recently designated as a World Heritage Site by UNESCO. Because of the unique climatic and physiographic features, it ranks high among the biodiversity super hotspots within the Western Ghats and Sri Lanka harboring a large number of endemic flora and fauna within its range (World Heritage Report, 2010). HPNP is located about 24 km south of Nuwara Eliya between latitude 6° 47'-6° 50' N and longitudes 80° 46'-80° 51' E at an elevation ranging from 1500 m to 2524 m Above Sea Level (ASL) with a plateau starting from about 2,100 m ASL. This is the only montane plain in Sri Lanka with a natural history dating back to pre-historical times (Green, 1990). The unique characteristics of this ecosystem highlight the importance of its conservation. However, the forest die back at HPNP in recent times has initiated a debate regarding air pollution issues at the park.
In one of the rare studies related to the atmospheric pollution at the HPNP,  reported the possibility of acid deposition in the fog which arrives predominantly from the Indian continent and from the western parts of the country where more than 50 % of the vehicle population and the major industries are located. Further, they reported that atmospheric pollution levels in the HPNP may increase due to the trans-boundary pollution from the Indian Sub-continent during the North-East monsoon. environment. Biological monitoring of air pollutants can be passive or active. Passive methods involve observing plants growing naturally within the area of interest. Active methods detect the presence of air pollutants by introducing test plants of known genotypes and its response within the study area (Mulgrew and Williams, 2000).
The diversity of HPNP lichen flora can use as a tool for biomointoring air pollutant levels at the HPNP (Jayalal et al., 2006). The most recent check list of flowering plants within the HPNP prepared by Wijesundara (2007) indicated 653 species belong to 102 families and 461 genera. However, no extensive collection of lichens have been recorded in the past in HPNP other than Santesson and Moberg who visited Sri Lanka in 1975 and collected about 10 specimens of Thelotremataceae, mostly from the Horton Plains area (Hale, 1981). More recently,many lichen species have been recorded from HPNP (Jayalal et al., 2012;Wijesundara & Karunaratne, 2015).
According to the past literature and some recent investigations on lichens carried out in Sri Lanka, the numbers of lichen species already recorded from Sri Lanka may exceed 1,000 species (Jayalal et al., 2008). Importantly several new species have been added to the Sri Lankan lichen flora (Orange et al., 2001;Jayalal et al., 2012;Weerakoon et al., 2012). The rich chemical substances and their biological/pharmaceutical activities have made lichens important organisms (Karunaratne et al., 2005;Kathirgamanathar et al., 2006;Thadhani et al., 2012). Finally, in terms of the soil ecology, phenolic lichen metabolites are known to play siderophore type iron chelating ability (Karunaratne et al., 1992;Jayasinghe et al., 2015), thus affecting soil microbial dynamics.
The objective of this study was firstly to determine the quality of ambient air chemically, by measuring the concentrations of SO 2 and NO 2 , over a period of 12 months, and secondly to correlate the data to biomonitoring of lichens through determining their diversity at HPNP using the Index of Atmospheric Purity (IAP) modeling.

Climatic parameters
Climatic parameters such as rainfall, maximum and minimum daily temperature, wind direction and relative humidity during the research period were obtained on a daily basis from the Seetha Eliya Meteorological Station which is located about 10 km from the sampling sites.

Preparation of air samplers and sampler stands
Reagents were prepared, using high purity chemicals from Sigma-Aldrich, in small vials immediately prior to the use. Samplers were in house assembled using 25 mm diameter Teflon rods and were prepared using the method followed by Ileperuma and Abeyratne (2001). The sampler stands were also manufactured inhouse using PVC tubes and plastic plates. Prior to use, all sampler components and glass vials were soaked in a detergent solution to remove contaminants, rinsed thoroughly, dried in an oven and stored in a clean environment.
The coating solution for NO 2 was prepared by dissolving 0.44 g of NaOH and 3.95 g of NaI in 10 ml of water and diluting to 50 ml with methanol. For SO 2 determination, the coating solution was prepared by dissolving 0.5 g of NaOH in the minimum of water followed by dilution to 50 ml with methanol.

Sampling sites
Air sampling sites (5) and lichen sampling sites (12) were selected using a map of HPNP ( Figure  1). Lichen sampling sites were situated in both continuous forest (6) and forest islands (6). All the air sampling sites were situated facing the north-west or south-east wind directions. The longitude, latitude and altitude of all the sampling sites are given in the Table 1.

Air sample storage
After exposure, the samplers (in duplicate) were removed and sealed and taken to the laboratory for further analysis. In the laboratory, the sorbent filter was removed and sealed in a small polythene bag. These were then marked with an identifying code indicating the pollutant, site and sample number and stored at 4 0 C for three days until analyses. At the same time, a set of samplers was prepared in an identical manner and kept unexposed at each sampling site to be used as controls for each pollutant type.

Analysis of NO 2
Before the analysis, filters with trapped pollutants were transferred into clean glass vials (20 ml) using Teflon covered tweezers. Pollutants were then extracted into deionized water (5 ml) by sonicating for 10 minutes in a shaker. The same procedure was carried out to the blank. The solution was then analyzed for nitrite using a colourimetric technique (Saltzman, 1954). For the preparation of the colour reagent, phosphoric acid (25 ml of 85 %) and 2.5 g of sulfanilamide were added to 200 ml of deionized water in a 250 ml volumetric flask. After dissolving sulfanilamide completely, 0.25 g of N-(1-napthyl)-ethylenediamine dihydrochloride was added and mixed to provide a clear solution. It was then diluted to 250 ml with water. Then the colour reagent (0.2 ml) was added to 5 ml of the sample while mixing the solution. After 10 minutes, the absorbance was measured using a colourimeter (Janway-6050) at a wavelength of 540 nm against a blank, which was treated with the same quantities of the reagents employed for colour development. Finally, a calibration curve was obtained for solutions in the concentration ranged from 1-10 ppm.

Analysis of SO 2
A buffer solution [3 g of MgCl 2 . 6 H 2 O, 0.5 g of CH 3 COONa. 3H 2 O, 0.1 g of KNO 3 and 2 ml of acetic acid (99%)] was made in 50 ml of distilled water and it was made up to 100 ml. To prepare the standard sulphate solution, 0.0148 g anhydrous Na 2 SO 4 was dissolved in deionized water and was diluted to 100 ml in a volumetric flask. For the measurement of turbidity, the sample (20 ml) was filtered and placed in a 25 ml conical flask. The buffer solution (4 ml) was added and mixed using a magnetic stirrer. To this solution, 1 g of BaCl 2 crystals was added at once and stirred for 1 min. The solution was poured into the cell of the turbidity meter (DRT-15CE) and the absorbance reading was taken after 5 minutes. Finally, a calibration curve was obtained for solutions in the concentration ranged from 0.5-5.0 ppm.

Concentrations of absorbed pollutants
The concentration of each pollutant was calculated in nM M -3 as follows: The resulting value from the above equation was converted to parts per billion by volume (ppbv) using the following formula.

Lichen collection and Identification
Lichen distribution on one third of the trees (GBH ≥ 10 cm) present in each plot (50 × 20 m 2 ) was studied. Lichen diversity and their distribution pattern were studied by recording the presence or absence of lichens on each tree up to 2 m height from the ground level, using a 20 × 20 cm 2 grid. The lichen specimens collected were observed under the dissecting microscope for morphological characters. A cross-section of the thallus and ascomata were taken using a sharp blade prior to observe under the compound stereomicroscope. At each stage, illustrations were made as much as possible. Characters were noted according to the lichen data sheet. Finally, all the lichens were identified up to genus level according to lichen determination keys and previous literature.

Index of Atmospheric Purity (IAP)
The IAP was calculated using the occurrence and frequency of lichens at the study sites and an ecological index for each species using the formulae; where, n is the number of lichen species found at a given station, Q is the ecological index of a species or the average species richness and f is the number of sampled trees on which this lichen species was found at the site; The value for Q × f is divided by 10 to give a more manageable number (Johnsen and Søchting, 1973).

Variation of meteorological data in HPNP
The highest maximum temperature has been observed during March to April and the lowest was recorded in July. The average highest rainfall occurred during October to December and the lowest rainfall in February (Data not given). According to the correlation analysis, the mean temperature and the relative humidity were significantly correlated ( Table 2).

Variation of ambient NO 2 concentrations
Data used in this study for passive sampling was the average values of 15-30 days. The obtained values were further averaged in to 24 hours. As there are no standards available for the period of 15-30 days, 24 h values were compared with 24 h standards (WHO, 2000;.

Variation of ambient SO 2 concentrations
The average concentrations of SO 2 during the study period (August, 2005to September, 2006 at each sampling point showed considerable variations ( Figure 2). The variation pattern of SO 2 concentrations among five sampling points was also showed almost a similar trend throughout the study period. World's End showed comparatively low concentration of SO 2 throughout the study period. Comparatively higher concentrations were observed during the whole period at Pattipola road and at the middle point.     Figure 3). The highest concentration of SO 2 (0.0063 ppm) was observed at the Pattipola sampling point and the second highest value (0.0061 ppm) was observed at the Middle sampling point which was situated close to the vehicle park in HPNP. The lowest concentration of SO 2 (0.0042 ppm) was observed at the World's end.
The variations of the average NO 2 and SO 2 concentrations in each month were almost similar throughout the study period with a significant positive correlation at p≤0.05 ( Figure  2). Similarly, the average concentrations of the two pollutants in each sampling site showed similar variations (Figure 3), but with an insignificant positive correlation at p≤0.05.
Relative Humidity (RH) at HPNP showed values >70 % throughout the year. Lower RH was recorded during February to March (˂70 %). The highest wind velocity was observed during June to July and the lowest was observed in April (Data not given). RH and wind velocity correlated positively but was insignificant ( Table  2).

Variation of ambient NO 2 concentration with environmental and vehicular factors
temperature, relative humidity, bright sunshine and the total number of vehicles visiting the HPNP are given in Figure 4. The variation of ambient NO 2 concentration during the study period showed insignificant positive correlation (p≥ 0.05) with the rainfall pattern (Table 3). Similar insignificant relationship was observed between wind velocity and RH, hours of bright sunshine and the number of vehicles visiting to HPNP. However, a positive significant correlation (p≤ 0.05) was observed between the ambient NO 2 concentration and temperature ( Table 3).

Variation of ambient SO 2 concentration with environmental and vehicular factors
Variation of the ambient SO 2 concentration with respect to rainfall, wind velocity, average temperature, relative humidity, bright sunshine and the number of vehicles visiting HPNP were comparable to those of the ambient NO 2 concentration. However, the correlations of variations of the ambient SO 2 concentration with meteorological parameters were different to those for NO 2 concentrations. The ambient SO 2 concentration showed a positive correlation with rainfall, wind velocity, ambient temperature, RH and the number of vehicles visiting HPNP during the study period. The positive correlation was higher with wind velocity and the number of vehicles visiting, while the correlation was less with rainfall, ambient temperature and RH. However, all these correlations were insignificant at p≤0.05 (Table 3). Further, ambient SO 2 concentration was inversely varied with the precipitation in many months of the study period ( Figure 5A). A negative but insignificant correlation was observed between the ambient SO 2 concentration and bright sunshine (Table 3).

Lichen taxa in the HPNP
A total of 379 lichen taxa belonging to 67 genera and 23 families were identified during the survey ( Table 4).

Number of lichen species in each plot
The distribution of lichens from the 12 plots is shown in the Figure 6. The highest number of taxa (107) was recorded from B1 closely followed by B9 (106 taxa) and B7 (101 taxa). All these sampling sites are located in forest islands in HPNP. Considering the continuous forest of the HPNP, the highest number of lichens (89 taxa) were recorded from the plot A4, while the least (50 taxa) was recorded in A8. Some lichen species were recorded exclusively from a single sampling location. A total of 219 lichen species were confined to 10 sampling plots. The maximum number of exclusive species was recorded from B9 (34 species) followed by A4 (31 species). The lowest number was recorded from A8 (7 species).

Index of Atmospheric Purity (IAP) in HPNP
The IAP value obtained for the whole area of the HPNP was 54.22. This value was calculated using 379 lichen species spread in 12 quadrats in forest islands and continuous forest of HPNP. The IAP value for each site is given in

DISCUSSION
Owing to the adverse effects caused by air pollution, studies on air quality parameters are becoming important in atmospheric and environmental research today (Ghazali et al., 2009). These adverse effects have direct and indirect consequences on ecosystems and the environment. Such effects can include visible injury on vegetation and adverse impact on growth, changes in productivity, nutritive quality and community structure and biological diversity, with or without symptoms of injury to the plant foliage (Legge, 2009).
At HPNP, the average concentration of both NO 2 and SO 2 were comparatively low in months during September, 2005to March, 2006 and then began to increase until September, 2006. These variations are highly correlated with the wind velocities at HPNP. Different wind velocities are due to seasonal wind patterns in Sri Lanka. Since Sri Lanka is situated close to the equator within an altitude of 6 o to 10 o N, it experiences a tropical climate which is somewhat modified by the seasonal wind reversal of the Asiatic monsoons. According to Domroes (1974) and Suppiah (1984) Sri Lanka and the other South Asian countries experience four climatic monsoons, namely, Southwest monsoon (May-September), the first inter-monsoon (October-November), Northeast monsoon (November-February), and the second inter-monsoon (March-May).
The lower concentrations of NO 2 and SO 2 were observed during the intermediate and northeast monsoonal period compared to the period during the southwest monsoonal. This could be due to relatively low wind speed experienced during inter-monsoons and north-east monsoons. During a given year, south-west winds towards the island are regular and as a result the central part of the country could also be affected due to the air pollutants coming from the more industrialized Western province. Air pollution in main cities such as Colombo and Kandy is mainly caused by increasing traffic congestions (Ileperuma, 2000). Romero et al., (1999) reported that the wind decreases pollution in some areas at Santiago in Chile. In contrast to present findings, Abeyratne (2005)  Similarly, Abeyratne (2005) observed sudden increases in NO 2 and SO 2 in Kandy during festival seasons such as Christmas, Sinhalese and Tamil New Year and Kandy Esala Perahera while reporting relatively low levels during school vacations, when the vehicular traffic was the least. Shankar (2002) in India stated that the possible reasons for increase in the levels of NO 2 are due to tremendous increase in the number vehicles in the Mumbai city.
The recommended 24 h Sri Lankan air quality standards for SO 2 and NO 2 are 0.03 and 0.05, respectively. Both SO 2 and NO 2 concentrations in HPNP were much lower than the standard air quality levels in Sri Lanka. A similar study carried out by Aberathne (2005), revealed that NO 2 and SO 2 analyzed in Kandy exceeded the recommended Sri Lankan standard by about 14 % and 41 % of the sampling occasions respectively. Another study carried out at Galaha junction in Peradeniya revealed that both pollutants exceeded the Sri Lankan standard on 60 % of the twenty sampling occasions (Ileperuma and Dissanayake, 2004). In comparison, the average concentrations of NO 2 and SO 2 observed for the period of 14 months indicates that the air quality in HPNP is very high. However, there were no records available for the same study carried out in any national park in Sri Lanka.
Since HPNP is a remote, undisturbed forest reserve, the pollution levels could be low. However, the very low concentrations of ambient NO 2 and SO 2 reported in HPNP may perhaps due to the conversion of ambient NO 2 and SO 2 into nitric and sulfuric acid in presence of moisture, respectively (U.S. EPA report, 1998 andMartin, 1989). These acids may be deposited on the earth's surface in dry form as gases or aerosols or in wet form as acid rain. Wet deposition is determined by the amount, duration, and location of precipitation and changes in the total acid levels, which are in turn determined by atmospheric chemistry and precipitation patterns.  reported that that the pH of rain water varied from 5.37 to 7.47 with sulphate and nitrate concentrations ranging from 0-3.39 mg/l and 0-3.54 mg/l, respectively. In the same study , the fog had shown much higher acidities with pH values as low as 3.88 recorded during the dry season of April to May. All the air samples in the current study were collected inside the forest of HPNP. Hence, considerable amount of ambient NO 2 and SO 2 might have been taken up by the foliage of plants. Lendzian (1984) found foliar uptake of SO 2 via stomata although the cuticle is impermeable to the gas. According to Rondon and Granat (1994), NO 2 also enters via the cuticle of leaves without internal resistance. The lower NO 2 concentrations at the HPNP might also be due to the conversion process, in which ambient NO 2 converts into O 3 in the presence of sunlight (Ghazali et al., 2009). In addition to individual effects, a combination of above factors may also have contributed to the low levels of NO 2 and SO 2 at HPNP.
The average concentrations of NO 2 and SO 2 between sampling points showed considerable variations in the present study. The highest ambient concentrations of both NO 2 and SO 2 at Pattipola, which is situated in a hilly terrain close to a main road. The main entrance of the HPNP is situated along the Pattipola road with more than 90 % of vehicles arriving in HPNP. Moreover, this area directly faces Nuwara Eliya and Pattipola, where large-scale livestock farms are situated. Livestock farms generate large amount of organic waste and through anaerobic decomposition it generates ammonia and hydrogen sulphide (H 2 S) (Ileperuma, 2000). H 2 S oxidizes to form SO 2 rapidly under atmospheric conditions (Finlayson-Pitts and Pitts, 1986;Jacobson, 1999). This could have contributed to high levels of SO 2 at Pattipola. The middle sampling point which was situated very close to the vehicle park at HPNP showed the highest concentrations of pollutants. Abeyratne (2005) also mentioned that the sampling sites closer to city centers recorded higher pollutant levels.
The lowest ambient NO 2 and SO 2 were recorded at the World's End sampling point, which faces directly towards the windward direction. High speed winds are able to carry pollutants away and perhaps account for the low pollutant concentrations in the present study. Çelik and Kadi (2007) showed that pollutants can accumulate due to slow wind speeds at high hills and mountains in a study carried out in Turkey. Furthermore, Ileperuma (2000) reported that calm weather conditions in valleys make the air quality very poor. At Kirigalpotta, where the sampling point was situated at the base of the mountain, showed higher concentrations of ambient NO 2 and SO 2 than in the World's End but lower than Pattipola and Middle point concentrations.
The medium pollutant concentrations at Kirigalpotta site may be due to wind break effect of the Kirigalpotta Mountain. Penner et al. (1989) and Robinson (1989) have shown that the atmospheric chemical reactions were influenced by local weather patterns such as temperature, precipitation, clouds, atmospheric water vapor, wind speed, and wind direction. The variations of ambient NO 2 and SO 2 concentrations during the study period showed insignificant positive correlation with the rainfall pattern. Abeyratne (2005) observed a lower concentration of NO 2 and SO 2 during high rainfall periods, perhaps due to dissolving the gases in rainwater. A positive significant correlation was observed between the ambient NO 2 concentration and temperature, but not with SO 2 concentration. In contrast, Salem et al. (2009) have found an insignificant positive correlation between temperature and NO 2 concentrations and a significant positive effect with SO 2 concentration. Çelik and Kadi (2007) also reported that SO 2 concentration increased with temperature at Karabük City in Turkey. Abeyratne (2005) found a negative relationship between NO 2 concentration and ambient temperature only.
Considering the variations of the pollutants with relative humidity and number of vehicles visiting HPNP, both pollutants had insignificant positive correlation. According to Sánchez-Ccoyllo and Andrade (2002), high values of pollution concentrations prevail due to weak ventilation, low relative humidity and an absence of precipitation. However, bright sunshine hours were positively and significantly correlated with t ambient NO 2 concentrations and negatively with SO 2 concentrations. Although the ambient NO 2 and hours of bright sunshine were positively correlated with each other in the current study, Logan et al., (1981); Thompson (1992) and Ghazali et al., (2009) have shown that a considerable amount of NO 2 is converted to O 3 through photochemical reactions in the presence of sunlight. Similarly, the same correlation was observed by Trebs et al. in 2009. The diversity and abundance of lichens are considered as indicators of environmental quality, where high values correspond to good air quality (Asta et al., 2002a(Asta et al., , 2002b. In addition to the air quality, a combination of bark pH, light, humidity, tree diameter, tree height and distribution is important in determining the richness of lichens (Kotelko et al, 2008). The results of the present study showed that forest islands are highly diverse compared to the continuous forest. However, evenness values were lower in forest islands than that of continuous forests.
The IAP value obtained for the whole area of the HPNP was 54.22. This value belonged to the quality level 5 indicating a 'very low' level of SO 2 . This value was calculated using 379 lichen species spread in 12 quadrats situated in forest islands and continuous forests at HPNP. However, IAP values calculated were different in each quadrat in HPNP. Relatively low IAP values were obtained from quadrats placed in continuous forests than that in forest islands, indicating relatively higher levels of SO 2 in continuous forests (Pattipola and Middle points) than that of forest islands (Ohiya road and Kirigalpotta points). IAP values have provides a quantitative measure of the differences in richness and diversity of lichen communities influenced by activities such as habitat disturbances and urbanization (DeSloover and Leblanc, 1968;Kricke and Loppi, 2002). According to Ruoss and Vonarburg (1995) and van Dobben and ter Braak (1998) many lichen species respond negatively to high SO 2 concentrations while the direct effects of O 3 and NO 2 on lichen communities are not well understood. However, Fuentes and Rowe (1998) observed no consistent relationship between IAP and SO 2 concentration, but a reliable relationship with SO 2 . However, van Dobben et al., (2001) stated that, atmospheric SO 2 and NO 2 concentrations are the most important factors in determining the lichen biodiversity

CONCLUSION
Though several studies have been carried to evaluate air quality using passive gas sampling technique in Sri Lanka, this was the first study to correlate the air quality and the lichen diversity in a National Park. In the present study, a total of 379 lichen taxa were recorded and they were used to calculate IAP. The resulting higher IAP value significantly correlated with the very low level of SO 2 concentration of the ambient air quality of the HPNP. These results were further confirmed by the data of passive gas sampling, in which very low levels of the ambient SO 2 and NO 2 concentrations were recorded. .