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THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY NGO DUC GIANG Potential use of Lichens as an indicator of air polution in urban airshed BACHELOR THESIS Study Mode: Full-time Major : Environmental science and management Facully : International Training and Developing centre Batch : 43 Advance Education Program Thai Nguyen, 21/09/2015 Thai Nguyen University of Agriculture and Forestry Degree Program Bachelor of Environment science and Management Student name Ngo Duc Giang Student ID DTN1153110179 Thesis title Potential use of Lichens as an indicator of air polution in urban airshed Duong Van Thao Supervisors David Blake Andrea Hinwood Will Stock Abstract: The aim of this study was to assess the effectiveness lichens as an indicator of air pollution in the Perth Metropolitan Region (PMR) urban airshed Sample sites were selected by identifying regions of high, medium and low NOx concentrations based on interpolation models using data from a previous study In each of these regions 40 rooves were sampled for the presence and abundance of lichen species Additionally sites within Kings Park and within 1km and 5km of the park were selected It was hypothesized that large regions of urban vegetation would improve air quality and therefore the presence and abundance of lichen species Environmental variables such as road density and vegetation density within a specified distance of the sample location were collected for each of the sample sites using GIS Two way analysis of variance (ANOVA) was used to evaluate the i relationship between lichen abundance at each site of sample and each environmental variable Correlations between lichen abundance and each environmental variable at each site were also undertaken Vegetation cover was significantly associated with lichen abundance Generalized linear model to examine those environment variables which best predicted a response in lichen abundance Results show that urban bushland has significantly associated with lichen abundance Other final conclusions were contrary to what have expected that areas containing greater NOx concentration had higher lichen abundance, more lichen abundance with an increasing of road density The results of this investigation suggest that lichens have the potential to evaluate the air quality in urban bushland but some others factors were influencing the result Keywords: Lichens, air quality, Perth Metropolitan Region, NOx concentration, environment variables, vegetation cover Number of pages: 46 Date of submission: September 30, 2015 Supervisor’s signature ii ACKNOWLEDGEMENT I would like to express my sincere thanks and appreciations to my supervisor David Blake for his continuous support throughout the project, from initial advice and every step of the way Furthermore, I am also my immensely grateful to Prof Andrea Hinwood, Dr Duong Van Thao and Prof Will Stock for comments that greatly improved the manuscript and for guiding me from very first steps of this project Many thanks and appreciations go to Emily Allen, Jonathon Boeyen for their contributions and supports throughout the process of this project iii TABLE OF CONTENT LIST OF FIGURES LIST OF TABLES LIST OF ABBREVIATIONS PART I INTRODUCTION 1.1 Research rationale 1.2 Research’s objectives 1.3 Research questions and hypotheses 1.4 Limitations 1.5 Definitions PART II: LITERATURE REVIEW 11 PART III: METHODS 13 3.1 Material 13 3.2 Methods 14 3.2.1 Study area 14 3.2.2 Sites selection 16 3.2.3 Sampling 18 PART IV: RESULT 24 4.1 Air quality categories 24 4.2 Environmental variables 27 4.3 Generalized linear model (GLZ) 33 PART V: DISCUSSION AND CONCLUSION 35 5.1 Discussion 35 iv 5.1.1 Air quality categories 35 5.1.2 Environmental variables 36 5.1.3 Generalized linear model 38 5.2 Conclusion 38 REFERENCES 41 v LIST OF FIGURES Figure 2.1: Lichens (light grey) living on rooves top of house…………………….…11 Figure 3.1: Perth metropolitan region………………… ………………………………16 Figure 3.2: NOx interpolations model at PMR using DER AQMS and HIMAQs study sites Interpolations were modeled using data collected in autumn…………………18 Figure 3.3: 300m Buffer vegetation regions…………………………………………….20 Figure 3.4: 300m buffer road density regions………………………………………… 22 Figure 3.5: Distances from each house to Industrial facility…………………………23 Figure 4.1: Mean and standard error bars of lichen abundance at High, Medium and Low concentration zones…………………………………………………………… 27 Figure 4.2: Distribution of lichens in correlation with 300m road density in each house at Kings Park sites……………………………………………………………… …30 Figure 4.3: Distribution of lichens in correlation with 300m road density at 1km buffer to Kings Park……………………………………………………………… ……31 Figure 4.4: Distribution of lichens in correlation with proximity to industry at 1km buffer to Kings Park……………………………………………………………………….31 Figure 4.5: Distribution of lichens in correlation with vegetation cover at Low concentration of NOx sites…………………………………………………………………32 Figure 4.6: Distribution of lichens in correlation with 500m road density at Medium concentration NOx sites……………………………………………………………………33 Figure 4.7: Distribution of lichens in correlation with proximity to industry at high concentration of NOx sites……………………………………………………………… 34 LIST OF TABLES Table 4.1: Anova test between groups and within groups of lichen abundance in each sites of NOx concentration 25 Table 4.2: Multiple Comparisons lichen abundance between Low, medium and high concentration of NOx 25 Table 4.3: Correlation of environment variable with each category sites 28 Table 4.4: Generalized linear model of lichen abundance with environment variables 34 LIST OF ABBREVIATIONS Abbreviations Meaning DER AQMS Department of Environment Regulation Air Quality Monitoring Sites NDVI Normalized Difference Vegetation Index GIS Geographic information system RL Road length PM Particle material VOCs Volatile organic compound 0.350 0.300 pixel 0.250 0.200 NDVI_Mean_500 0.150 Linear (NDVI_Mean_500) 0.100 0.050 0.000 10 20 30 40 50 lichen abundance Figure 4.5: Distribution of lichens in correlation with vegetation cover at Low concentration of NOx sites The figure 4.5 showed the correlation between vegetation cover and lichen abundance at Low concentration of NOx sites The higher vegetation covered the higher lichen abundance 31 12000 10000 m 8000 6000 RL_in_500 4000 Linear (RL_in_500) 2000 0 10 20 30 lichen abundance Figure 4.6: Distribution of lichens in correlation with 500m road density at Medium concentration NOx sites The figure 4.6 showed the correlation between lichen abundance and 500m road density at medium concentration of NOx sites 32 4500 4000 3500 m 3000 2500 2000 near_industry 1500 Linear (near_industry) 1000 500 0 20 40 60 lichen abundance Figure 4.7: Distribution of lichens in correlation with proximity to industry at high concentration of NOx sites The figure 4.7 showed the correlation between lichen abundance and proximity to industry at high concentration of NOx sites 4.3 Generalized linear model (GLZ) The table 4.4 below shows six groups that could explain the response to lichen abundance If they have a delta AIC of less than it means they are similar The greatest responses to the effects on lichen abundance are 300m road density, 300m vegetation cover and proximity to industrial area Other predictors show correlation but not as strong as comparing between delta AIC of each group 33 Table 4.4: Generalized linear model of lichen abundance with environment variables Degr of Var Var Var Var Var AIC ∆AIC Freedom RL_in_300 NDVI_Mean_300 RL_in_300 NDVI_Mean_300 RL_in_300 near_industry 3113.664751 3114.631185 -0.9664 3115.409219 3115.644588 Near RL_in_500 -1.74 NDVI_Mean_300 industry Near -1.97 RL_in_300 NDVI_Mean_300 NDVI_Mean_500 industry RL_in_300 NDVI_Mean_300 3116.255600 -2.59 RL_in_300 NDVI_Mean_300 NDVI_Mean_500 3116.630863 -2.96 RL_in_300 3117.405609 -3.74 3118.239433 -4.57 3129.956153 -16.29 3131.509297 -17.84 RL_in_500 RL_in_500 NDVI_Mean Near _500 industry NDVI_Mean_300 NDVI_Mean RL_in_300 RL_in_500 NDVI_Mean_300 _500 RL_in_300 NDVI_Mean_500 10 RL_in_300 NDVI_Mean_500 near_industry 34 PART V: DISCUSSION AND CONCLUSION 5.1 Discussion 5.1.1 Air quality categories This study has shown that there is a significant association between concentration of NOx and lichen abundance on roof tops of houses in the PMR The fact that this study found the lichen abundance associated with high modeled concentrations of NOx (representative of poor air quality) is in contrast to the findings of other studies Gadsdon et al, (2010) found that NO2 concentrations were negatively correlated with the total cover of lichens The contrasting results of this study could be as a result of generally low NO x concentrations in Perth as compared with other studies A studied of Marmor & Randlane, 2007 at Tallinn, Estonia has shown that lichens had been affected when NOx exceeds70 µg m-3 while this investigation at PMR had a high NO x concentration at only 23.9 µg m-3 Also the results could be affected by other factors: the type of roof substrate, the age of the building/roof and whether the roof had been cleaned recently Alternatively, it may indicate that using NOx concentrations as an indicator of air quality may not have been the best indicator of poor air quality in Perth Although not statistically significant, the results suggest that even at these low concentrations there is some relationship between lichen abundance in the medium and low NOx concentration zones Lichen abundance was greater found at low NOx concentration zones and this was expected The non-significant 35 relationship between lichen abundance in the medium and low NOx concentration zones could be due to the lichen presence/abundance data are calculated based on week sampling period for autumn They may not be a true reflection of the annual air quality in that region Otherwise due to time limited in months and lack of some information needed for the aims of this investigation, the results could be also affecting 5.1.2 Environmental variables The results of this study show that lichen abundance is affected by the air quality but there are a number of factors which may influence air quality within an urban airshed Road density showed the most significant correlation with lichen abundance but was not what was expected Instead of more lichens present with less road density, we found more lichen abundance with an increase in road density This was unexpected and comparable with other studies Previous studies have shown that road traffic is considered as important pollutant influencing epiphytic lichen vegetation in urban environments and close to motorways (Marmor & Randlane, 2007) Another investigation showed that lichens are sensitive to pollution caused by traffic and abundance declines significantly close to roads (Llop, et al, 2012) The limitation of this study might be because of road density is a proxy measure for vehicle density and may not be an accurate reflection of traffic and emission 36 Urban bushland was significantly associated with lichen abundance Lichens were abundant in the location closer to large expanses of urban vegetation and they decreased further away There was a significant difference between lichen abundance in Kings Park, within 1km of Kings Park and within 5km of Kings Park Based on the initial results lichens were more abundant at sites within the 1km buffer zone than the 5km buffer zone However, it was observed that a number of sites within Kings Park potentially had new rooves and returned zero abundance lichen counts When the data was reanalyzed without these sites the results showed that there were more lichen abundance in Kings Park than the 1km buffer zone and 5km buffer zone This confirms what was expected that lichens will be more abundant in the locations closer to large expanses of urban vegetation and they will be decline with further away Findings similar to the current study Elsinger, et al, (2007) found that higher concentrations of air pollutants lower lichen abundance An investigation of lichens in the USA noted that lichen communities strongly associated with vegetation cover (Root & McCune, 2012) Elsinger et al, (2007) found that lichens were abundant in locations further from industrial areas than lichens observed closer to the pollution sources, similar to the findings from the current study Other study in the USA (Bennett & Wetmore, 2010) found that lichen diversity around the sites of industrial and urban disturbances was affected by air pollution There is also a significant relationship 37 between lichen abundance and increasing distance to nearest industrial zones Lichens cover increased with greater distance to pollution source 5.1.3 Generalized linear model The results from table show the highest responses for lichen abundance were 300m road density, 300m vegetation cover and proximity to industrial Those three categories have the most significant relationship with lichen abundance Correlation tested with a 300m road density showed a significant correlation with lichen abundance, corresponding to findings similar with GLZ Urban trees remove large amounts of air pollution are well documented (David J Nowak, et al, 2006) Elsinger, et al, (2007) found that lichens were abundant in locations further from industrial areas than lichens observed closer to industrial area Other predictors show weak correlation but it doesn’t mean they don’t have a relationship They might be affected by others factors: Differences of microsite and lichens species richness, types of rooves on each house of sample sites may have affected the findings at some sites The rooves had been cleaned recently also affected the findings at some sites Ages of each house due to ages of rooves itself, it also has affecting to result 5.2 Conclusion The findings from this study demonstrated that urban bushland has significantly associated with lichen abundance Areas containing large areas of 38 vegetation had higher lichen abundance compared with areas containing less vegetation Other variables that effected lichen abundance were 300m road density, 300m vegetation cover and increase proximity to industrial area Vegetation cover was positively correlated with total cover of lichens The distances to industrial zones were negatively correlated with total cover of lichens The results were contrary to what have expected that areas containing greater NOx concentration had higher lichen abundance Lichens seem less abundance in low NOx concentration areas than in high NOx concentration Used low NOx value measured might not give enough evidence for evaluate the correlation of NOx concentration sites with lichen abundance or used only NO x to taking sample sites of interpolation model to investigate for bioindicator of lichens might be incorrect The results of this investigation suggest that lichens have the potential to evaluate the air quality in urban bushland but some others factors were influencing the result The problem of model NOx concentration make a contrasting result of this study could be as a result of generally low NOx concentrations in Perth Further studies should have vehicle counting methods to responses accuracy on correlation results with lichen abundance They will have to face several issues 39 that have not been explored yet which need further investigations to support their modeling work 40 REFERENCES Ahmadjian, V (1993) The lichen symbiosis John Wiley & Sons Ahmadijian, V (Ed.) 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Environmental pollution, 183, 113-122 38 Yilmaz, H., Toy, S., Irmak, M A., Yilmaz, S., & Bulut, Y (2008) Determination of temperature differences between asphalt concrete, soil and grass surfaces of the City of Erzurum, Turkey Atmósfera, 21(2), 135-146 39 Wade, T., & Sommer, S (2006) A to Z GIS, An illustrated dictionary of geographic information systems ESRI press 40 Western Australian Planning Commission (2004, July) Bushland Policy for the PMR Statement of Planning Policy 2.8 41 WHO (2015) Air Pollution Children’s Environmental Health 45 ... indicator of air polution in urban airshed Duong Van Thao Supervisors David Blake Andrea Hinwood Will Stock Abstract: The aim of this study was to assess the effectiveness lichens as an indicator of air. .. Limitations In an urban airshed, the presence and abundance of lichens may be affected by a number of factors besides air quality These include the type of roof substrate, the age of the building/roof and... for business or other demands This can release high amounts of air pollutants to urban airshed (Newman & Kenworthy, 2006) This study made use of visual inspection of roof tops using binoculars