Effects of Toxic Gases and Seasonal Variation in Plants Leaves and Stomata, a Case Study of Quetta City, Pakistan

EFFECTS OF TOXIC GASES AND SEASONAL VARIATION IN PLANTS LEAVES AND STOMATA, A CASE STUDY OF QUETTA CITY, PAKISTAN

A THESIS SUBMITTED TO THE FACULTY OF LIFE SCIENCES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN BOTANY UNIVERSITY OF BALOCHISTAN, QUETTA

SAADULLAH KHAN LAGHARI DEPARTMENT OF BOTANY SEPT, 2012

EFFECTS OF TOXIC GASES AND SEASONAL VARIATION IN PLANTS LEAVES AND STOMATA, A CASE STUDY OF QUETTA CITY, PAKISTAN

A THESIS SUBMITTED TO THE FACULTY OF LIFE SCIENCES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN BOTANY UNIVERSITY OF BALOCHISTAN, QUETTA

SAADULLAH KHAN LAGHARI

DEPARTMENT OF BOTANY UNIVERSITY OF BALOCHISTAN, QUETTA SEPT, 2012

CERTIFICATE

This is to certify that I have prepared Ph.D. dissertation (Reg No.1987/UB-2009/R-168.) entitled “Effects of Toxic Gases and Seasonal Variation in Plants Leaves and Stomata, a case study of Quetta city, Pakistan”. This is my original research completed under the guidance and supervision of Prof. Dr. Mudassir Asrar, in the Department of Botany, University of Balochistan, Quetta. I have not submitted this dissertation in any other University.

Saadullah Khan Laghari Ph. D Scholar, Department of Botany, University of Balochistan, Quetta.

CERTIFICATE

This is to certify that Mr. Saadullah Khan Laghari Ph.D. candidate in the Department of Botany, University of Balochistan, Quetta, has successfully completed his work on “Effects of Toxic Gases and Seasonal Variation in Plants Leaves and Stomata, a case study of Quetta city, Pakistan”. This is his original work and is a significant contribution in the field of Botany. He is submitting his thesis in the Department of Botany, University of Balochistan, Quetta for the partial fulfillment of Ph.D. Degree.

Prof. Dr. Mudassir Asrar Supervisor, Department of Botany, University of Balochistan, Quetta.

TABLE OF CONTENTS

CONTENTS Page No. Table of contents ……………………………………………………………... 5-9 List of Tables ………………………………………………..……………….. 10-14 List of Figures ……………………………………………….……………….. 15-16 List of Abbreviations …………………… …….…………………………….. 17-18 Acknowledgements...... 19 Abstract ………………………………………………………...…………….. 20-21

Chapter 1...... 22-40

GENERAL INTRODUCTION 1.1.Background …..…………………………………………………………... 22

1.2. DESCRIPTION OF STUDY AND ITS PARAMETERS……………. 24-30

1.2.1. Ambient status of air pollutants in Quetta City ………………….……. 24 1.2.1.1. Air Pollutants………………………………………………………… 24 A. Carbon monoxide………..…………….…………………………. 24 B. Sulfur dioxide (SO2)…..…………………………………………. 24 C. Nitrogen dioxide (NO2)…….………………………….………… 25 D. Suspended particulate matters (SPM)….………………………… 25 1.2.2. Heavy metals contamination of different common plant species of Quetta city………..………………………………………………….….. 25 1.2.2.1. Heavy Metals.…….…….……………………………………………. 25 A. Lead (Pb)….…………………………………………….………….. 26 B. Iron (Fe)….…………………………………………….…………… 26 C. Zinc (Zn)…..………………………………………….…………….. 27 D. Copper (Cu)…….………………………………..…………………. 27 E. Cadmium (Cd)……..………………………………………….…….. 27 F. Antimony (Sb)………….………………………………….……….. 27 1.2.3. Bio-indication of air pollution in relation to biochemical and physiological attributes of plants……………..………….…………….. 28 A. Ascorbic acid (AA)……..………………….……………………….. 28 B. Total chlorophyll content (TCC)……..……………………..………. 28 C. Leaf extracts pH………..…………………………………………… 29 D. Relative Water Content (RWC)……..……………………………… 29 E. Air Pollution Tolerance Index (APTI)……………….…..……….… 29 1.2.4. Effect of air pollution on the morphological attributes of plant leaf…… 29 1.2.4.1. Morphological attributes of plant leaf…………………………….….. 29 1.2.5. Effect of air pollution on the anatomical attributes of plant leaf………. 30 1.2.5.1. Anatomical attributes of plant leaf…………………………………… 30

1.3. INTRODUCTION AND DESCRIPTION OF STUDY AREA…..….. 31-35

1.3.1. General Introduction of Balochistan ……………….………………….. 31 1.3.2. Description of the Study Sites………………………………………….. 32 1.3.2.1. Quetta City………………………...…………………………………. 33 A. Geology…………………………………………………….………. 34 B. Climate of the study area…………………………………………… 34 C. Hydrology………………………………………………………….. 35 D. Soil…………………………………………………………………. 35 E. Biotic Factors………………………………………………………. 35

1.3.2.2. CONTROL SITES (NON- POLLUTED)………....……………… 36-38

A. Hazargangi Chiltan National………………………………...…….. 36 B. Wali Tangi Zarghoon area…………………………………………. 37 C. Botanical Garden of University of Balochistan, Quetta…………… 37

1.4. AIM AND OBJECTIVES OF THE STUDY….……………………… 39

1.4.1. The specific objectives of the study …………………...…………….. 39-40

Chapter 2…………………………………………………………………….. 41-47

REVIEW OF LITERATURE

2.1. Ambient Status of Air Pollutants and Their Seasonal Variation………… 41 2.2. Heavy Metal Contamination of Plant Leaves…………………………… 42 2.3. Bio-indication of air pollution in relation to biophysical and biochemical attributes of plant leaves………………………………………………….. 43 2.4. Effect of Air Pollution on Morphological and Anatomical Attributes of Plant Leaves………………………………………………………………. 45

Chapter 3………………………………………………………………………. 48-85

AMBIENT STATUS OF AIR POLLUTANTS AND THEIR SEASONAL VARIATION INQUETTA CITY.

3.1. INTRODUCTION………………………………………………………. 48

3.2. MATERIALS AND METHODS………………………………………. 49 3.2.1. Air Sampling……………………………………………………… 49 3.2.2. Analysis of Air Samples………………………………………….. 49

3.2.3. Air Quality Index (AQI)………………………………………….. 50 3.2.4. Gradation of Air Quality Index…………………………………… 50 3.2.5. Traffic counting…………………………………………………… 50 3.2.6. Statistical analysis………………………………………………… 51

3.3. RESULTS……………………………………………………………….. 52-81

3.4. DISCUSSION…………………………………………………………… 82 3.4.1. Carbon Monoxide (CO)…………………………………………… 82 3.4.2. Sulfur dioxide (SO2)………………………………………………. 82 3.4.3. Nitrogen dioxide (NO2)………………………………………...... 83 3.4.4. SPM10μg/m3…………………………………………………….... 83 3.4.5. SPM2.5μg/m3……………………………………………………... 84 3.5. CONCLUSIONS………………………………………………………... 85

Chapter 4…………………………………………………………………….. 86-124

HEAVY METALS CONTAMINATION AND THEIR SEASONAL VARIATION IN DIFFERENT PLANT SPECIES COLLECTED FROM URBAN AREA OF QUETTA CITY

4.1. INTRODUCTION………………………………………………………. 86 4.2. MATERIALS AND METHODS………………………………………. 87-88 4.2.1. Collection of soil and leaf samples………………………………... 87 4.2.2. Heavy metals analyses of plant samples…………………………... 87 4.2.3. Heavy metals analyses of soil samples……………………………. 87 4.2.4. Statistical analyses………………………………………………… 87

4.3. RESULTS……………………………………………………………….. 89-118

4.4. DISCISSION…………………………………………………………….. 119-123 4.4.1. Lead (Pb)………………………………………………………….. 119 4.4.2. Zinc (Zn)…………………………………………………………... 120 4.4.3. Iron (Fe)…………………………………………………………… 120 4.4.4. Copper (Cu)……………………………………………………….. 121 4.4.5. Cadmium (Cd)…………………………………………………….. 121 4.4.6. Antimony (Sb)…………………………………………………….. 122 4.4.7. Heavy metals in soil………………………………………………. 123 4.4.8. Correlation coefficient between heavy metal in soil and plants….. 123

4.5. CONCLUSIONS………………………………………………………... 124

Chapter 5…………………………………………………………………….. 125-138

BIOINDICATION OF AIR POLLUTION IN RELATION TO BIOCHEMICAL AND PHYSIOLOGICAL ATTRIBUTES OF PLANTS

5.1. INTRODUCTION………………………………………………………. 125

5.2. MATERIALS AND METHODS………………………………………. 126-127 5.2.1. Leaf Sample Collection……………………………………………. 126 5.2.2. Leaf Relative Water Content (RWC) Analysis……………………. 126 5.2.3. Total Chlorophyll Content (TCC) determination …………………. 126 5.2.4. Leaf Extract pH, Analysis…………………………………………. 126 5.2.5. Ascorbic Acid (AA) Content Analysis…………………………….. 127 5.2.6. APTI Determination………………………………………………... 127 5.2.7. Gradation of APTIs………………………………………………… 127 5.2.8. Statistical Analysis…………………………………………………. 127 5.3. RESULTS……………………………………………………………….. 128-135 5.4. DISCUSSION…………………………………………………………… 136 5.5. CONCLUSIONS………………………………………………………... 138

Chapter 6...... 139-168

EFFECT OF AIR POLLUTION ON THE LEAF MORPHOLOGY OF

DIFFERENT PLANT SPECIES OF QUETTA CITY

6.1. INTRODUCTION……………………………………………………… 139

6.2. MATERIALS AND METHODS………………………………………. 140 6.2.1. Samples collection………………………………………………... 140 6.2.2. Leaf morphological changes……………………………………… 140 6.2.3 Statistical analyses……………………………………………….... 140 6.2.4 Percentage increasing & decreasing………………………………. 140

6.3. RESULTS……………………………………………………………….. 141-165

6.4. DISCUSSION…………………………………………………………… 166

6.4.1. Grass leaf morphological changes……………………………….... 166 6.4.2. Foliage length……………………………………………………... 166 6.4.3. Foliage width……………………………………………………… 166 6.4.4. Foliage area……………………………………………………….. 167 6.4.5 Petiole length………………………………………………………. 167

6.5. CONCLUSIONS………………………………………………………. 168

Chapter 7…………………………………………………………………….. 169-190

EFFECT OF AIR POLLUTION ON THE ANATOMICAL CHARACTERISTICS OF PLANTS FOLIAGE GROWN ALONG THE ROAD SIDE OF QUETTA CITY

7.1. INTRODUCTION………………………………………………………. 169

7.2. MATERIALS AND METHODS………………………………………. 170 7.2.1. Samples Collection……………………………………………….. 170 7.2.2. Percentage increasing and decreasing…………………………….. 170 7.2.3. Anatomical Study of Leaf Epidermis……………………………... 170 7.2.4. Statistical Analysis………………………………………………... 170

7.3. RESULTS……………………………………………………………….. 171-186

7.4. DISCUSSION …………………………………………………………... 187-189

7.4.1. Epidermal cells……………………………………………………. 187 7.4.2. Number of stomata………………………………………………... 187 7.4.3. Number of closed stomata………………………………………… 188 7.4.4. Number of abnormal/injured stomata…………………………….. 188 7.4.5. Percentage of open stomata……………………………………….. 189

7.5. CONCLUSIONS………………………………………………………... 190

RECOMMENDATIONS………………………………………………. 191-196

1. Reducing of Transports pollution………………………………...... 191 i. Vehicle inspection and maintenance (VIM)……………………… 191 ii. Improving fuel quality……………………………………………. 192 iii. Introducing new vehicle technologies……………………………. 192 iv. Setting strict standards for newly imported vehicles……………... 192 v. Managing travel demand and improving transportation supply….. 192 2. Making Strategies to Reduce Air Pollution from Industrial Sources……. 193 3. Reducing Air Pollution, Caused by Open Burning of Wastes and Emanating from Natural Sources……………………………………...... 193 4. Natural resources used for managing air quality………………………… 194 5. Urban air quality improvement through air pollution tolerant plant species of the area……………………………………………………….. 194

REFERENCES………………………………………………………………. 197-215

LIST OF TABLES Page TABLES NO AND THEIR DISCRIPTION N o.

3.1. Ambient status of CO, SO2 and NO2 at different locations of Quetta city during spring season……………………………………………….. 53 3.2. Ambient status of CO, SO2 and NO2 at different locations of Quetta city during summer season……………………………………………. 54 3.3. Ambient status of CO, SO2 and NO2 at different locations of Quetta city during autumn season…………………………………………………... 55 3.4. Ambient status of CO, SO2 and NO2 at different locations of Quetta city during winter season……………………………………………….. 56 3.5. Ambient status of SPM at different locations of Quetta city during spring season……………………………………………………………. 57 3.6. Ambient status of SPM at different locations of Quetta city during summer season………………………………………………………….. 58 3.7. Ambient status of SPM at different locations of Quetta city during autumn season…………………………………………………………... 59 3.8. Ambient status of SPM at different locations of Quetta city during winter season…………………………………………………………… 60 3.9. Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during spring season…………………………………………………………… 61 3.10. Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during summer season…………………………………………………. 62 3.11. Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during autumn season………………………………………………….. 63 3.12. Over all percentage increase in air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during winter season…………………………………………………………... 64 3.13. Range of air pollutants during different seasons of the year (2010 & 2011) in the atmosphere of the Quetta city……………………………. 65 3.14. Range of air pollutants in Quetta city during different seasons of the year (2010 & 2011)……………………………………………………. 66 3.15. Air Quality Index of CO in the atmosphere of Quetta city during different seasons……………………………………………………….. 67 3.16. Air Quality Index of SO2 ppb in the atmosphere of Quetta city during different seasons……………………………………………………….. 68 3.17. Air Quality Index of NO2 ppb in the atmosphere of Quetta city during different seasons……………………………………………………….. 69 3.18. Air Quality Index SPM10 the atmosphere of Quetta city during

different seasons…………………………………………………….…. 70 3.19. Air Quality Index of SPM2.5 in the atmosphere of Quetta city during different seasons……………………………………………………….. 71 3.20. Standard of air pollutants in the atmosphere of urban area of the developing countries (WHO, 2006)…………………………………… 72 3.21. Average number of vehicles’ movement per five minutes at different locations of Quetta city during different seasons (2010 and 2011)…… 73 3.22. Correlation co-efficient between the number of Vehicles and air pollutant in the atmosphere of Quetta city…………………………….. 81 3.23. Correlation co-efficient among the air pollutants of Quetta city……… 81 4.1. Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season………………………………………………………….... 89 4.2. Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season…………………………………………………………. 90 4.3. Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season…………………………………………………………... 91 4.4. Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season…………………………………………………………..... 92 4.5. Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season………………………………………………………….. 93 4.6. Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season…………………………………………………………... 94 4.7. Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season…………………………………………………………..... 95 4.8. Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season………………………………………………………….. 96 4.9. Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season…………………………………………………………... 97 4.10. Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season……………………………………………………………. 98 4.11. Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season………………………………………………………….. 99

4.12. Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season…………………………………………………………... 100 4.13. Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season……………………………………………………. 101 4.14. Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season………………………………………………….. 102 4.15. Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season…………………………………………………... 103 4.16. Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season……………………………………………………. 104 4.17. Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season………………………………………………….. 105 4.18. Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season……………………………………………………. 106 4.19. Seasonal heavy metals contamination (μg/g-1) with increasing percentage increasing in all the plant species collected from polluted and non-polluted sites of Quetta city…………………………………… 107 4.20. Over all average concentration of heavy metals (μgg-1) in all the plant species of polluted and non-polluted sites during three seasons with increasing percentage…………………………………………………... 108 4.21. Seasonally over all average concentration (μg/g-1) of heavy metal in soil collect from polluted and non-polluted sites of Quetta city during different seasons of the year……………………………………………. 116 4.22. Overall average contents of heavy metal (μg g-1) in soil samples of polluted and non-polluted sites of Quetta city during throughout the season of the year………………………………………………………. 117 4.23. Correlation coefficient between heavy metal in soil and Plants of Polluted sites……………………………………………………………. 118 5.1. Ascorbic acid (mg g-1) concentration in the plant leaves of polluted and non polluted sites of Quetta city………………………………………... 128 5.2. Total chlorophyll content (μg g-1 f.wt.) in the plant leaves of polluted and non- polluted sites of Quetta city…………………………………... 129 5.3. pH level in the plant leaves of polluted and non-polluted sites of Quetta city……………………………………………………………………… 130 5.4. Relative Water Content (%) in plant leaves of polluted and non- polluted sites of Quetta city…………………………………………….. 131

5.5. Air Pollution Tolerance Index (APTI) of different Plant species of polluted and non-polluted sites of Quetta city………………………….. 132 5.6. Different Plants Tolerance gradation to the air pollution……………….. 133 6.1. Gross leaf morphological changes of the different plant species and growth stages growing at polluted and non-polluted of Quetta city……. 141 6.2. Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during spring season…………………………………………………………………… 145 6.3. Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during summer season………………………………………………………...... 146 6.4. Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during autumn………………………………………………………………….. 147 6.5. Effect of air pollution on the width of foliage in different plant species growing at polluted and non-polluted sites of Quetta city during spring. 148 6.6. Effect of air pollution on the width of foliage in different plant species growing at polluted and non-polluted sites of Quetta city during summer…………………………………………………………………. 149 6.7. Effect of air pollution on the width of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during autumn………………………………………………………………….. 150 6.8. Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during spring…………………………………………………………………… 151 6.9. Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during summer…………………………………………………………………. 152 6.10. Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during autumn………………………………………………………………….. 153 6.11. Effect of air pollution on the length of foliage petiole in different plant species growing from polluted and non-polluted sites of Quetta city during spring……………………………………………………………. 154 6.12. Effect of air pollution on the length of foliage petiole in different plant species growing form polluted and non-polluted sites of Quetta city during summer………………………………………………………….. 155 6.13. Effect of air pollution on the length of foliage petiole different plant species growing from polluted and non-polluted of Quetta city during autumn………………………………………………………………….. 156 6.14. Average length and width of foliage (cm) of different plant species growing from polluted and non-polluted site of Quetta city during all three growing seasons…………………………………………………... 157

6.15. Average area of foliage and length of petiole in different plant species growing from polluted and non-polluted site of Quetta city during all three growing seasons…………………………………………………... 158 6.16. Seasonally increasing percentage of foliage length and width in different plant species growing from Polluted and non-polluted site of Quetta city………………………………………………………………. 159 6.17. Seasonally increasing percentage of foliage area and petiole length in different plant species growing from polluted and non-polluted site of Quetta city……………………………………………………………..... 160 6.18. Seasonal decreasing percentage of morphological characteristics in all the plant species of polluted site with respect to non-polluted site…….. 161 7.1. Average number of epidermal cells/mm2 in the leaves, collected during spring season……………………………………………………………. 172 7.2. Average number of epidermal cells/mm2 in the leaves, collected during summer…………………………………………………………………. 173 7.3. Average number of epidermal cells /mm2 in the leaves, collected during autumn…………………………………………………………………. 174 7.4. Total Average number of stomata/mm2 in the leaves collected during spring…………………………………………………………………… 175 7.5. Total average number of stomata/mm2 in the leaves collected during summer…………………………………………………………………. 176 7.6. Total average number of stomata/mm2 in the leaves collected during autumn season………………………………………………………….. 177 7.7. Total average number of closed leaf stomata /mm2 in the leaves collected during spring…………………………………………………. 178 7.8. Total average number of closed stomata/mm2 in the leaves collected during summer…………………………………………………………. 179 7.9. Total average number of closed stomata/mm2 in the leaves collected during autumn………………………………………………………….. 180 7.10. Total average number of abnormal/injured stomata/mm2 in the leaves collected during spring season………………………………………... 181 7.11. Total average numbers of abnormal/injured stomata (/mm2) in the leaves collected during summer season………………………………. 182 7.12. Total average numbers of leaf abnormal/injured stomata (/mm2) in the leaves collected during autumn season……………………………….. 183 7.13. Total average numbers of open stomata (/mm2) with percentage in the leaves collected during spring season………………………………… 184 7.14. Total average number of open stomata/mm2 with percentage in the leaves collected during summer season………………………………. 185 7.15. Total average number of open stomata/mm2 with percentage in the leaves collected during autumn season……………………………….. 186

LIST OF FIGURES FIGURES NO AND DISCRIPTIONS Page No 1.1. A view of Balochistan province and its bordered ………………………... 32 1.2. Satellite view of Quetta valley……………………………………………. 33 1.3. Satellite view of Quetta city (Polluted site) ……………………………… 34 1.4. Control site for air sampling Hazargangi Chiltan National Park…………. 36 1.5. Wali Tangi Control site for air sampling…………………………………. 37 1.6. Botanical garden University of Balochistan (Control site)……………….. 38 3.1. Linear relationship between number of vehicles and CO during spring...... 74 3.2. Linear relationship between number of vehicles and CO during summer... 74 3.3. Linear relationship between number of vehicles and CO during autumn.... 74 3.4. Linear relationship between number of vehicles and CO during winter….. 75 3.5. Linear relationship between number of vehicles and SO2 during spring..... 75 3.6. Linear relationship between number of vehicles and SO2 during summer.. 75 3.7. Linear relationship between number of vehicles and SO2 during autumn... 76 3.8. Linear relationship between number of vehicles and SO2 during winter..... 76 3.9. Linear relationship between number of vehicles and NO2 during spring…. 76 3.10. Linear relationship between number of vehicles and NO2 during summer…………………………………………………………………… 77 3.11. Linear relationship between number of vehicles and NO2 during autumn……………………………………………………………………. 77 3.12. Linear relationship between number of vehicles and NO2ppb during winter…………………………………………………………………….. 77

3.13. Linear relationship between number of vehicles and SPM10 during spring……………………………………………………………………... 78 3.14. Linear relationship between number of vehicles and SPM10 during summer…………………………………………………………………… 78 3.15. Linear relationship between number of vehicles and SPM10 during autumn……………………………………………………………………. 78 3.16. Linear relationship between number of vehicles and SPM10 during winter…………………………………………………………………….. 79 3.17. Linear relationship between number of vehicles and SPM2.5 during spring…………………………………………………………………….. 79 3.18. Linear relationship between number of vehicles and SPM2.5 during summer…………………………………………………………………… 79 3.19. Linear relationship between number of vehicles and SPM2.5 during autumn…………………………………………………………………… 80 3.20. Linear relationship between number of vehicles and SPM2.5 during winter…………………………………………………………………….. 80 4.1. Overall concentration of Pb in different plant species of Quetta city…….. 108 4.2. Overall concentration of Zn in different plant species of Quetta city…….. 109 4.3. Overall concentration of Fe in different plant species of Quetta city…….. 109 4.4. Overall concentration of Cu in different plant species of Quetta city…….. 110

4.5. Overall concentration of Cd in different plant species of Quetta city…….. 110 4.6. Overall concentration of Sb in different plant species of Quetta city…….. 111 4.7. Annual increasing percentage of Lead (Pb) in polluted site plant species as compared to non-polluted site………………………………………….. 111 4.8. Annual increasing percentage of Zinc (Zn) in polluted site plant species as compared to non-polluted site………………………………………….. 112 4.9. Annual increasing percentage of Iron (Fe) in polluted site plant species as compared to non-polluted site…………………………………………….. 112 4.10. Annual increasing percentage of Copper (Cu) in polluted site plant species as compared to non-polluted site………………………………... 113 4.11. Annual increasing percentage of Cadmium (Cd) in polluted site plant species as compared to non-polluted site………………………………... 113 4.12. Annual increasing percentage of Antimony (Sb) in polluted site plant species as compared to non-polluted site………………………………... 114 4.13. Overall average concentration of Heavy metals during spring, summer and autumn in different plant species collected from non-polluted sites of Quetta city…………………………………………………………….. 115 4.14. Overall average concentration of Heavy metal during spring, summer and autumn in all plant species collected from polluted sites of Quetta city……………………………………………………………………….. 115 5.1. Comparison of Ascorbic acid between polluted and non-polluted sites plants…………………………………………………………………….. 134 5.2. Comparison of Total chlorophyll content (μg g-1 f.wt.) between polluted and non-polluted sites plants…………………………………………….. 134 5.3. Comparison of pH level between polluted and non-polluted sites plants…………………………………………………………………….. 135 5.4. Relative Water Content (%) in plant leaves of polluted and non-polluted sites……………………………………………………………………… 135 6.1-6.6. Different investigated plant species growing at polluted and non- polluted sites of Quetta city……………………………………………… 142-144 6.7. Decreasing % of foliage length………………………………………….. 162 6.8. Decreasing % of foliage width…………………………………………... 163 6.9. Decreasing % of foliage area…………………………………………….. 164 6.10. Decreasing % of petiole length…………………………………………. 165

LIST OF ABBREVIATIONS Abbreviations Discriptions A Absent AA Ascorbic acid APTI Air Pollution Tolerance Index AQI Air Quality Index ATSDR Agency for Toxic Substances and Disease Registry Ave Average Cd Cadmium CO Carbon monoxide Cu Copper DW Dry weight F F-test Fe Iron FW Fresh weight G Good Ha Harmful for all the peoples Hsg Harmful for sensitive group HT Highly tolerant Inc Increasing % IT Intermediate tolerant M Moderate Max Maximum Min Minimum MT Moderately tolerant NEPC National Environment Protection Council NO2 Nitrogen dioxide NP Non-Polluted site ns Non-significant P Polluted site Pb Lead ppb Part per billion ppm Part per million Rd% Reducing % RDS Respireable Dust Sampler RWC Relative Water Content S Sensitive S. group Sensitive group S.D Standard deviation Sb Antimony SLA Specific leaf area SO2 Sulfur dioxide SPM10μm Suspended particulate matters of 10 micrometer SPM2.5μm Suspended particulate matters of 2.5 micrometer t t-test TCC/TCh Total chlorophyll content TW Turgid weight V. Harmful Very Harmful Vh Very harmful for all population

Zn Zinc * Slightly significant p < 0.05 ** Highly significant p< 0.01 *** Very highly significant p < 0.001

ACKNOWLEDGMENTS

I want to express my sincere appreciation to my supervisor, Prof. Dr. Mudassir Asrar. I thank for her extremely helpful guidance, support and encouragement with her wisdom, knowledge and experience. She spent countless hours guiding both my research efforts and writing thesis invaluable for the successful completion of the dissertation, as well as for my future career ambitions. My appreciation must also extend to her families. I would like to send my special thanks to Prof. Dr. Abdul Kabir Khan Achakzai, chairperson of the Department of Botany at University of Balochistan, Quetta for his persistent encouragement and help during my Ph.D. studies. My further appreciation goes to Prof. Dr. Rasool Bakish Tareen, Dean Faculty of life sciences, and Prof. Dr. Abdullah Khan Dean Research at University of Balochistan, for their constructive suggestions and support. I would like to express my gratitude to my co-supervisor Dr. Atta Mohamad and Dr. Ghazala Shaheen for their insightful suggestions and assistance. I would also like to thank Mr. Abdul Manan Kakar senior lab technician for his help regarding the analysis of heavy metals. I gratefully acknowledge to my colleagues of Botany Department at the University of Balochistan, Quetta, encouragement and help during my research work. Many thanks are also due to my friend Mr. Muhamad Wasim Malik Assistant professor Department of Statistics University of Balochistan, Quetta for his assistance in various statistical aspects of my research and for his support as a friend. Finally, I would like to express my gratitude to my entire family for their continued support and encouragement. My parents and brothers have always been supportive of my ambitions and encouraged me to fulfill my dreams. I would like to thank my wife, for always encouraging perusal higher education. Her sacrifices, love, and steadfast support have brought about all of my success. I am also grateful to my beloved daughters, Sara and Ayesha for bringing me many joys during the course of my Ph.D. study.

Saadullah Khan Laghari Assistant professor Department of Botany University of Balochistan, Quetta September 2012

ABSTRACT

Ambient status of Quetta city was estimated by recorded the contents of air pollutants viz. CO, NO2, SO2, SPM10μm and SPM2.5μm from its atmosphere. Statistical analysis using t-test indicated that all the seasonally investigated air pollutants were significant high at Quetta city (polluted sites) than control sites at the significant level of P<0.01. The concentration of all the pollutants start increasing slightly from spring to summer and reached to its maximum during autumn and lowest was found in the winter. Correlation Coefficient and Linear relationship indicated that all the air pollutants were highly, positively and significantly correlated with the number of vehicles movement. Air Quality Index of Quetta city revealed that the atmosphere of city is harmful for people of sensitive group and particularly the contents of particulate matters (SPM10μm and SPM2.5μm) are more than permissible level. Statistical analysis of all estimated heavy metals (Pb, Zn, Fe, Cu, Cd and Sb) exhibited that these were found slightly (P<0.05) to highly (P<0.01) significant high from the polluted sites plant species of Quetta city as compare to the control sites.

Air pollution effects on biochemical and physiological attributes of plants leaves was determined by analysis of ascorbic acid content (AAC), total leaf chlorophyll content (TLC), leaf-extract pH and leaf relative water content (RWC). Statistical analysis indicated that all measured attributes in plant leaf showed slightly (P<0.05) to highly (P<0.01) significant variation between polluted and non-polluted sites. Air Pollution Tolerance Index (APTI) of different plant species exhibited that the overall APTI was significant in polluted site plants than those of non-polluted sites. On the basis of APTI, out of 14 plant species only two species, Eucalyptus tereticornis L. and Pinus halepensis Miller. were found to be highly Tolerant (T), other five plants i.e. Fraxinus excelsior L., Robinia pseudoacacia L., Punica granatum L., Prunus armeniaca L. and Elaeagnus angustifolia L. were moderately tolerant (MT) while other five species viz. Pistacia vera L., Rosa indica L., Melia azadirach L., Morus nigra L. and Ficus carica L. were Intermediately tolerant (IT), where as remaining two species Morus alba L. and Vitis vinifera L. were Sensitive (S). Effect of air pollution on morphological characteristics of leaves in different common plants species growing along the road side of Quetta city were calculated by measuring the foliage length, width, area and petiole length. All these investigated

20 parameters showed significant reduction in the polluted sites plant species. The results also exhibited that there was significant variation in the growth of morphological attributes from season to season, specie to specie and site to site (polluted and non-polluted). The effect of air pollution on anatomical characteristics of leaf epidermis revealed that total average number of epidermal cells/mm2 and stomata/mm2 at adaxial and abaxial side shown non-significant variation among polluted and non-polluted sites throughout the year. However there was variation from specie to species and on adaxial & abaxial sides. The number of closed, abnormal/injured and open stomata/mm2, in different investigated plant species were slightly to highly significant (P<0.05 & 0.01) different between polluted and non- polluted sites. Further that highest number of closed and abnormal/injured stomata/mm2 was recorded during autumn from polluted site and maximum number of open stomatas was found during spring from non-polluted site plant species.

Chapter 1

GENERAL INTRODUCTION

1.1. Background Pakistan and other developing countries have experienced a progressive degradation in their air quality. This is no more evident than in the cities. Quetta is one of the major cities of Balochistan province of Pakistan, which is facing the relentless pressure of air pollution. Among the various measures of air pollution, the most widely used is the detection of pollutants on plants and specifically their leaves (Flowers et al., 2007; Hoque et al., 2007).

Air pollution is one of the most severe problems of the world, mainly arising from over population, increasing traffic density and industrialization (Odilara, et al., 2006). The air pollutants are responsible for plant injuries and great loss of productivity (Joshi and Swami, 2007). Impact of regional air pollution on local plant species is one of the major environmental issues. The climate conditions, the physicochemical properties of air pollutants and their residence time in the atmosphere cause the impact on surrounding plants, animals and human (Wagh et al., 2006). Presence of plants in the urban areas can thus improve air quality through decreasing the upper limit of gases and particulates (McPherson et al., 1994, Smith, 1971). The plants being constantly exposed to the environment absorb, accumulate and integrate pollutants impinging on their foliar surfaces. They show visible or subtle changes depending on their sensitivity level (Sharma & Butler, 1973; Smith & Staskawicz, 1977). Therefore, any fluctuation in the environment can be treated as disturbance in overall growth of plants and human health. Uaboi-Egbenni et al., (2009) described that the plants growing in the urban area were greatly affected by air pollutants. The air pollutants have long term effects on plants by influencing CO2 contents, light intensity, temperature and precipitation. Ninova et al., (1983) reported that air pollution has adverse effect on the morphology and anatomy of different plants species growing in urban areas.

The present study was carried out to investigate the air pollution status of Quetta city by using the leaves of road side vegetation. The study considered five facets of air pollution in Quetta city. The first part of study deals with the measurement and analysis of ambient status of air pollutants and their seasonal

22 variation in the atmosphere of Quetta city. Any interference in the atmospheric environment is at once reflected by a change in the air quality. Hence, the measurement of air pollutants is an easy way to determine change in air quality.

The second part deals with the heavy metals contamination of different common plant species growing in the urban areas of the city. It has long been recognized that large concentrations of these metals sometimes bring obvious changes in the flora and fauna of the area (Gautam, 1990). The third part focuses on the bioindication of air pollution in relation to biochemical and physiological attributes of plants growing along the roads of Quetta. Any change in the atmospheric environment may also cause the change in the biochemical and physiological attributes of plants (Jaleel et al., 2009).

The fourth part evaluates the effect of air pollution on morphological characteristics of plant leaves. The fifth part was performed to find out the effect of air pollution on the anatomical characteristics of plant leaves (number of epidermal cells, number of open, close and abnormal stomata).

The aspects of air pollution revealed by this study have never been explored before in Balochistan, and even in Pakistan. Keeping in view the importance and gravity of the impact of air pollution on the vegetation, this study will benefit not only the researchers, scientists, health workers and farmers, but will also provide useful information for the general public.

1.2. DESCRIPTION OF STUDY AND ITS PARAMETERS

1.2.1. Ambient status of air pollutants in Quetta City:

This section discusses and compares the air pollutants (Carbon monoxide

(CO), Sulfur dioxide (SO2), Nitrogen dioxide (NO2), Suspended particulate matters (SPM10μm and SPM2.5μm) with their permissible limits and their seasonal variation in the atmosphere of the Quetta city. In this chapter, Air Quality Index (AQI), linear and correlation co-efficient between the number of Vehicles and air pollutants in Quetta city are also determined. Statistical analysis of the air pollutants and their seasonal variation are also presented in this chapter.

1.2.1.1. Air Pollutants: Air pollution can be defined as the human introduction into the atmosphere through chemicals, particulate matter or biological materials that cause harm or discomfort to humans, or other living creature or damage the environment (Anonymous, 2008). All combustion are responsible for the releases of gases and particles into the air, these can include SO2, NO2, CO and soot particles, as well as smaller quantities of toxic metals, organic molecules and radioactive isotopes. In this study following air pollutants are investigated from the Quetta city;

A. Carbon monoxide (CO)

B. Sulfur dioxide (SO2)

C. Nitrogen dioxide (NO2)

D. Suspended particulate matters (SPM) A. Carbon monoxide (CO): Carbon monoxide is a major atmospheric pollutant in urban areas chiefly coming from the exhaust of internal combustion engines (including vehicles, portable and back-up generators, lawn mowers, power washers, etc.). It also comes from incomplete combustion of various other fuels such as wood, coal, charcoal, oil, paraffin, propane, natural gas, and trash.

B. Sulfur dioxide (SO2): Sulfur dioxide is also a major air pollutant of the urban areas. It produced by the burning of common sulfur and sulfur rich materials like coal and fuel oil. Vehicle tires, wool, hair, rubbers, foam rubber, carpet pads and petroleum often contain sulfur compounds and burning of these substances release

SO2 in the atmosphere and cause many diseases in plants, animals and human beings (Agbaire and Esiefarienrhi, 2009; Joshi et al., 2009).

C. Nitrogen dioxide (NO2): Nitrogen dioxide is a prominent air pollutant that results from the oxidation of nitric oxide in air and primary sources of nitric oxide are motor vehicles, power generation stations, gas heaters and stoves, bomb blast and nuclear tests (Agbaire and Esiefarienrhe, 2009; Joshi et al., 2009).

D. Suspended particulate matters (SPM): Particulate air pollution is a mixture of solid, liquid or solid and liquid particles suspended in the air. These suspended particulate matters vary in size, composition and origin. There are two main types of the suspended particulate matters; SPM2.5μm and SPM10μm and there are also two main sources of these particulate matters. Some are emitted directly from sources e.g from vehicle exhausts and dust storm (Primary particulates) and some are formed by interactions with other compounds e.g nitrate formation from the photo-oxidation of NOx (Secondary particulates). These matters enter through respiration and may cause many diseases in humans. They also have adverse effects on plants. They are mostly vehicle-derived particulates (Prajapati et al., 2006).

1.2.2. Heavy metals contamination of different common plant species of Quetta city:

In this part of dissertation, detailed analysis of average contents of lead (Pb), zinc (Zn), iron (Fe), cupper (Cu), cadmium (Cd) and antimony (Sb) in different common plant species (Rosa indica L., Robinia pseudoacacia L., Melia azadirach L., Vitis vinifera L., Ficus carica L., Morus nigra L., Elaeagnus angustifolia L., Pistacia vera L., Fraxinus excelsior L., Eucalyptus tereticornis L., Morus alba L., Punica granatum L. and Pinus halepensis Miller.) of Quetta city and control area is presented. Data are illustrated seasonally (spring, summer and autumn seasons) and their comparison with standard limits for plant species is also shown. Relationship between investigated heavy metals in different plant species and soil samples was evaluated.

1.2.2.1. Heavy Metals: Heavy metals are chemical elements with a specific gravity that is at least 5 times the specific gravity of water (Lide, 1992). There are 35 metals of concern for humans and plants because of occupational or residential exposure; of

25 these 23 are the heavy elements or heavy metals (Glanze, 1996). Small amounts of these elements are commonly present in our environment and diet and are actually necessary for good health, but large amounts of any of them may cause acute or chronic toxicity (poisoning) to humans, animals and plants (Zevenhoven & Kilpinen, 2001; Hogan, 2010). In this chapter the following heavy metals are analyzed from the leavesof plant species of Quetta city;

A. Lead (Pb) B. Iron (Fe) C. Zinc (Zn) D. Copper (Cu) E. Cadmium (Cd) F. Antimony (Sb)

A. Lead (Pb): Lead accounts for most of the cases of pediatric heavy metal poisoning. It is a very soft metal and is used in pipes, drains, and soldering materials for many years. Millions of homes built before 1940 still contain lead (e.g., in painted surfaces), leading to chronic exposure from weathering, flaking, chalking, and dust. Every year, industry produces about 2.5 million tons of lead throughout the world (IOSHIC, 1999). Most of this lead is used for batteries. The remainder is used for cable coverings, plumbing, ammunition, and fuel additives. Lead, at certain exposure levels, is a poisonous substance to animals as well as for human beings and plants. Excessive lead damages the nervous system and causes brain, blood, kidneys, and thyroid gland diseases (Roberts, 1999).

B. Iron (Fe): Iron does not appear on the ATSDR's "Top 20 List," but it is a heavy metal of concern, particularly because ingesting dietary iron supplements may acutely poison young children (IOSHIC, 1999). Generally it is abundant in soil minerals because of the formation of insoluble iron oxides or hydroxides, so the excess of several other mineral may cause symptoms of iron deficiency by precipitating iron in unavailable forms. Much lower levels are known to produce cardiovascular difficulties (Roberts, 1999). Discussion of iron toxicity in this protocol is limited to ingested or environmental exposure. Iron overload disease (hemochromatosis), an inherited disorder, is discussed in a separate protocol and target organs are the liver and kidneys (Roberts, 1999).

C. Zinc (Zn): Generally zinc is widely distributed in soil and small amounts of it are also found in air. Heavy traffic exhaust emission is the primary sources of metallic nuisance such as zinc, which are present in fuel as anti-knock agents (Moller et al., 2005; Atayese et al., 2009 and Suzuki et al., 2008). Further that Zn in small amount plays an essential metabolic role in the plant, because it is the component of a variety of enzymes, such as dehydrogenase, proteinases, peptidases and phospohydrolases, while on the other hand its high concentration damage the metabolic processes in plants (Yap et al., 2010).

D. Copper (Cu): Copper is almost universally present in soil in small amounts. It is a necessary trace metal in plants, animals and human beings. It is also a component of proteins that have a role in the processing of oxygen. Copper plays exclusively catalytic roles in plants, being part of a number of important enzymes but concentrations above than 20μg g-1 are considered toxic to plants (Jones & Belling, 1967). It is mostly used in electrical wires, roofing and plumbing material and industrial machineries and the main sources of pollutant Cu in the atmosphere is considered Cu production & handling, fossil fuel combustion and iron steel production (Nriagu, 1979). E. Cadmium (Cd): Cadmium is a byproduct of the mining and smelting of lead and zinc and is number 7 on ATSDR's "Top 20 list (Roberts 1999; Tox FAQs™ for Cadmium, 1999: Fthenakis, 2004)". It is used in nickel-cadmium batteries, plastics, and paint pigments. It can be found in soils because it is used in insecticides, fungicides, sludge, and commercial fertilizers that are used in agriculture. Cadmium may be found in reservoirs containing shellfish. Cigarettes, dental alloys, electroplating, motor oil, and exhaust also contain cadmium (Roberts, 1999).

F. Antimony (Sb): Antimony is found in the earth's crust in silvery-white form and in soil it mixed with oxygen and formed antimony oxide. It is a byproduct of melting lead and other metals. Mostly it is used in batteries that contain lead, solder, pipe metals and sheets, bearings, castings, and pewter (Ozaki et al., 2004). The oxides of Antimony are used for the protection of textiles and plastics from catching fire and also used in paints, ceramics, and fireworks, and as enamels for plastics, metal and glass. It is assumed that an individual car emits small amounts of Sb in the short term, but great amounts in long term, causing chronic pollution in the neighboring

27 environment, that is highly toxic to human and plant in concentration (Huang et al., 1992; Mizohata et al., 2000 and Torre et al., 2002).

1.2.3. Bio-indication of air pollution in relation to biochemical and physiological attributes of plants: In this section the effect of air pollutants on biochemical and physiological attributes of plants are determined by analyzing the ascorbic acid contents, total chlorophyll contents, relative water contents and pH level from some common plant species of the Quetta city. Air Pollution Tolerance Index (APTI) of plant species including; Pinus halepensis Miller., Eucalyptus tereticornis L., Fraxinus excelsior L., Robinia pseudoacacia L., Punica granatum L., Prunus armeniaca L., Elaeagnus angustifolia L., Pistacia vera L., Rosa indica L., Melia azadirach L., Morus nigra L., Ficus carica L., Vitis vinifera L. and Morus alba L. Plant Tolerance gradation to the air pollution are also describe in this chapter. During this study the following parameters are investigated from the plant species:

A. Ascorbic acid (AA) B. Total chlorophyll content (TCC) C. Leaf extracts pH D. Relative Water Content (RWC) E. Air Pollution Tolerance Index (APTI) A. Ascorbic acid (AA): Ascorbic acid is a naturally occurring organic compound with antioxidant properties. It reacts with oxidants such as the hydroxyl radical, formed from hydrogen peroxide. Such radicals are damaging to plants and animals at the molecular level due to their possible interaction with nucleic acids, proteins, and lipids (Chen et al., 1990). Ascorbic acid plays a role in cell wall synthesis, defense, and cell division and it is a strong reducer and plays important roles in photosynthetic carbon fixation, with the reducing power directly proportional to its concentration (Conklin, 2001).

B. Total chlorophyll content (TCC): Total chlorophyll content has an important role in plant productivity and its content is also related to Ascorbic acid productivity (Aberg, 1958). Ascorbic acid is concentrated mainly in chloroplasts (Franke and Heber, 1964).

C. Leaf extracts pH: High pH may increase the efficiency of conversion from hexose sugar to ascorbic acid (Escobedo et al., 2008), while low leaf extract pH showed good correlation with sensitivity to air pollution. Mean while the TCC is also related to ascorbic acid productivity (Aberg, 1958) and ascorbic acid is concentrated mainly in chloroplasts (Franke and Heber, 1964). Photosynthetic efficiency was noted strongly dependent on leaf pH and it become decreased in plants when the leaf pH became low (Türk and Wirth, 1975).

D. Relative Water Content (RWC): Relative water content is the appropriate measure of plant water status in terms of the physiological consequence of cellular water deficit. High water content within a plant body will help to maintain its physiological balance under stress conditions such as exposure to air pollution, when the transpiration rates are usually high. High RWC favors drought resistance in plants (Dedio, 1975). If the leaf transpiration rate reduces due to the air pollution, plant cannot live well due to losing its engine that pulls water up from the roots to supply photosynthesis (1-2% of the total). Then, the plants neither bring minerals from the roots to leaf where biosynthesis occurs, nor cool the leaf.

E. Air Pollution Tolerance Index (APTI): Air pollution tolerance index has been used for the bio-indication of air pollution. Air pollutants have greater impact on ascorbic acid, total chlorophyll content, leaf-extract pH and relative water content of leaf (Rao, 1979; Klumpp et al., 2000; Flowers et al., 2007; Hoque et al., 2007). To evaluate the tolerance level of plants to air pollutants, four parameters (Ascorbic acid, Total Chlorophyll, Relative water content and pH of leaf-extract) are recognized and these four parameters are collectively formulated that is called air pollution tolerance index (APTI) of plants.

1.2.4. Effect of air pollution on the morphological attributes of plant leaf:

This part of the study deals with the evaluation of the effect of air pollution on morphological characteristics of 13 common plant species of Quetta city. Air pollution effects on leaf morphology are investigated by measuring the foliage length, width and area, length of petiole and gross leaf morphological changes such as color and shape at different growth stages. 1.2.4.1. Morphological attributes of plant leaf: External features of the plants leaf (foliage length, width and area, length of petiole and color and shape) are called leaf

29 morphological attributes and these are directly exposed to air pollution. Leaf is the most sensitive part to be affected by air pollutants instead of all other plant parts likes roots and stems (Shafiq et al., 2009). The major portions of the important physiological processes are concerned with leaf and therefore, the leaf at its various stages of development, serves as a good indicator to air pollutants (Bhatia, 2006; Eames & MacDaniels, 1947; Henry & Heinke, 2005; Horsfall, 1998; Rao, 2006; Silva et al., 2005 “b”; Sodhi, 2005 and Svetlana et al., 2010).

1.2.5. Effect of air pollution on the anatomical attributes of plant leaf:

The fifth part of this dissertation deals with the effect of air pollution on the anatomical characteristics (number of epidermal cells, number of stomata including closed, abnormal/injured and open stomata) of leaf in some common plant species of polluted and non-polluted sites of Quetta city. Study plants include Rosa indica L., Robinia pseudoacacia L., Melia azadirach L., Vitis vinifera L., Ficus carica L., Morus nigra L., Pistacia vera L., Fraxinus excelsior L., Eucalyptus tereticornis L., Morus alba L., Prunus armeniaca L. and Punica granatum L. Results of anatomical attributes of plant leaves including statistical analysis, seasonal variation, increasing and decreasing % of investigated parameters and their comparison with non-polluted site plant species are presented in this chapter.

1.2.5.1. Anatomical attributes of plant leaf: Anatomical attributes such as epidermal and stomata cells at both sides of leaf (abaxial and adaxial) are investigated. Stomata are usually termed for the opening in the epidermis through which gaseous exchange takes place between the intercellular spaces of the sub epidermal cells and the atmosphere (Eames and MacDaniels, 1947).

1.3. INTRODUCTION AND DESCRIPTION OF STUDY AREA

1.3.1. General Introduction of Balochistan: Balochistan is the largest Province of Pakistan, situated on the southwest and covers an area of 134,051 mi2 or (347,190 km2), thus constituting 44% of Pakistan's total land mass (Balochistan Encyclopedia, 2009). The Balochistan is bordered with Afghanistan to the north and northwest, Iran to the southwest, Punjab and Sindh to the east, and Khyber Pakhtunkhwa (KP) and the Federal Administrated Tribal Areas to the northeast. To the south lies the Arabian Sea. Balochistan is a land of varieties. It has mountains like Chiltan, Takatu, Sulaiman, Sultan etc. and plains stretching hundreds of miles. Its fertile land lise in Nasirabad district and the tracks which are thirsty for centuries in the Pat section of Sibi district and the Makran desert zone. It contain hottest area of the country like Sibi and the cool towns like Quetta, Ziarat, Kan Mehtarzai and Kallat where temperature goes below freezing point and these areas remain covered with a thick cover of snow in winter. Balochistan is situated on the south-eastern part of the Iranian plateau. It borders the geopolitical areas of the Middle East and Southwest Asia, Central Asia and South Asia. Seasonally the upper highlands areas of the province are very cold winters and hot summers. Winters of the lower highlands vary from extremely cold in Ziarat, Quetta, Kalat, Muslim Baagh and Khanozai the northern districts to mild conditions closer to the Makran coast. Summers are hot and dry, especially the arid zones of Chaghai and Kharan districts. The plain areas are also very hot in summer with temperatures rising as high as 50 °C (122°F). The highest record breaking temperature of 53°C (127 °F) has been recorded in Sibi (Pakmet.Com.Pk. 2010). Other hot areas include Turbat, and Dalbandin. Winters are mild on the plains with the temperature never falling below the freezing point. The desert climate is characterized by hot and very arid conditions. Occasionally strong windstorms make these areas very inhospitable. The population density is very low due to the mountainous terrain and scarcity of water in ruler areas. Balochistan had a population of more than 8 million inhabitants, representing approximately 5% of the Pakistani population (Federal Bureau of Statistics, Government of Pakistan, 2009). Official estimates of Balochistan's population grew from approximately 7.45 million in 2003 (Schrödinger, E., 2009) to 7.8 million in 2005 (Pakistan Balochistan Economic Report 2008). Balochistan is divided into five

31 different ecological zones based upon climate, soil and topography (Anees, 1980). In Balochistan shrub lands are still seen as a source of livestock feed and deciduous shrubs are most common in high latitudes and are usually associated with long, cold winters. There is not any proper classification of the shrub lands of Balochistan, but according to IUCN, (1999), report Balochistan is divided in to 4 major vegetation types; 1. Coniferous Forest 2. Scrub forests 3. Sub tropical desert 4. Riverain forest.

Fig 1.1. A view of Balochistan province and its bordered Source: Google maps

1.3.2. Description of the Study Sites: The study was conducted in four different areas of Quetta district. Following areas were selected for the study. 1. Quetta city urban area (polluted site) 2. Hazargangi Chiltan National Park (I Control area for air sampling) 3. Wallitangi Zarghoon area (II Control area for air sampling) 4. Botanical garden and campus University of Balochistan Quetta (Control area for plant studies)

1.3.2.1. Quetta City:

Quetta, the capital of Balochistan, lies between 29°-52' to 30°-15' latitude and 66°- 55' to 67°- 48' longitude, the city is about 1692 meters above sea level. The climate of this area is arid with cold winter, hot summer and has been classified as temperate desert bush type with Mediterranean trend (Qadir, 1968). It has three large mountains like Chiltan, Zarghun and Koh-e-Murdar that seem to brood upon this beautiful city. Quetta is a densely populated area of the mountainous region. It is situated in a river valley near the Bolan Pass, which has been used as the route of choice from the coast to Central Asia, entering through Afghanistan's region. The British and countless other historic empires have crossed the region to invade Afghanistan by this route (Encyclopedia of Balochistan 11 edi.). Quetta can rightly be called the fruit basket of Pakistan. Plums, peaches, pomegranates, apricots, apples, some unique varieties of melon like "Garma" and cherries, pistachios and almonds are all grown in abundance. Saffron grows very well on mountains around 5000 ft (1524 meters) high. It is being cultivated on a commercial scale here. The yellow and red varieties of tulip grow wild around Quetta.

Fig 1.2: Satellite view of Quetta valley. Source: Metrology dept Balochistan

Fig. 1.3: Satellite view of Quetta city (Polluted site) Source: Google maps

A. Geology: Quetta is surrounded by hill ranges having complicated geological structure. It makes a part of Irano-Anatolian folded zone of sedimentary strata. The disturbance that produced folded mountain has weakened the earth so that the region has come under great strain, as a result the beds of rock cause earth quake (Marwat & Haq, 1980). Quetta was completely destroyed in the earth quake of 1935 due to sharp bending of Fold Mountains (Marwat & Haq, 1980). The origin of the study area is traceable to tertiary period of earth formation. Mountains are sedimentary in nature, so it proves its origin as marine. These sedimentary rocks are rich in fossils. B. Climate of the study area: Climate of the area is dry temperate. Winters are dry and cold, while summers are dry and bracing. This variation in climate is the main ecological factor, due to which vegetation of southern zone differs from that of North. The annual climatic variations establish four seasons in the study area, spring, summer, winter and autumn. There is variation in temperature, wind, precipitation, atmospheric pressure and humidity. These are the main ecological climatic factors which determine the vegetation of the area. Due to variation in these factors, there is a variation in the penology of the vegetation from season to season. Maximum rainfall occurs in winter; however, monsoon shower occur occasionally in spring. Rainfall occurs more in winter than summer, spring and autumn. Snowfall occurs only from

December to February. Wind is important climate factor for vegetation. Persistent dry wind blows over the area for the greater part of the year, which becomes more strong and persistent in winter. It blows from North and North – West to South and South to East. Wind blow with higher speed in the evening and with low speed in the morning (Beg, 1966).

C. Hydrology: Quetta valley has shortage of water. Most of the area is Barani. The demand of water has increased due to increase in population, and the development of local industries and agricultures. Ground water is important water supply source of the area. Gravelly piedmont fans and aprons skirting the mountains constitute the main ground water reservoir. When precipitation on the water shed of the area occurs the ground water is recharged. Ground water is discharged by tube wills, Karazes, springs effluent discharged of streams. Mountain, rocky hills, gravelly piedmont, has safe and pure water, which are useful for irrigation, domestic and livestock consumption (Marwat & Haq, 1980).

D. Soil: The soil of the Quetta is formed from the parent rocks. Different types of parent rocks produce weathered particles of different sizes and chemical composition. The soil that accumulates on limestone contains practically, the same minerals that were in the original rock; only their proportions have been drastically changed (Anees, 1980). Weathering merely changes the texture and minerals proportions without producing a radically new set of minerals. The central part of the Quetta is covered by the soil that ranges from sandy loam to silt loam. At the margin of valley near foot hills the soils consist of sandy loam mixed pebbles and rock fragments.

E. Biotic Factors: Biotic factors play important role in the determination of vegetation of an area. Once vegetation is developed, it establishes itself in a particular habitat and it changes the climate of that habitat. Man is the main biotic factor that determines or establishes or destroys the plant communities. Wild animals and birds are also the consumers of the vegetation but their consumption of plants also depends on man.

1.3.2.2. CONTROL SITES (NON POLLUTED)

A. Hazargangi Chiltan National: Hazargangi Chiltan National Park is located near Quetta at a distance of 18 km on Quetta Mastung road towards N W at 30° 07’N longitude, 66° 58 ’E and 1700 m altitude. It is one of the oldest and most important protected enclosed areas of Balochistan. The region has Mediterranean climate, cold winter and dry summer. The park is characterized by a dry semi-arid type of vegetation. This vegetation is well preserved and occurs on the banks and terraces of water courses and along run-off channels on the hill slopes. The climate of Hazargangi is similar to Quetta. The precipitation is mostly confined to winter and spring seasons. Run-off water (rain as well as melting snow) flows down the hill slopes into the sloping plains as a result of which a number of water courses have developed this remains dry for the greater part of the year. The mean maximum temperature in summer is 36 °C and means minimum temperature in winter is10°C. According to Holdridge’s (1947) bio-climatic system, the region falls under the warm temperate bush type of bio-climate (Qadir, 1968; Qadir and Ahmed, 1989). The climate of this region indicates a Mediterranean trend due to restriction of precipitation to winter and spring months.

Fig. 1.4: Control site for air sampling Hazargangi Chiltan National Park

B. Wali Tangi Zarghoon Area: Wali Tangi is a small dam in the Urak Valley of Quetta. It is situated approximately 20 km east of Quetta at an elevation of approximately 8,350 ft (Raymond and Moore, 1969). Wali Tangi Dam was constructed by the Pakistan army (www.pakistanarmy.gov.pk) in the early 1960s (www.balochistan.gov.pk). The purpose of this Dam was to supplying clean water to the Urak Valley and Quetta for irrigation and human consumption. The dam stores and utilizes fresh water from melting snows in the surrounding Zarghoon Hills, which are part of the Sulaiman Range.

Fig. 1.5: Wali Tangi Control site for air sampling

C. Botanical Garden of University of Balochistan, Quetta: The Botanical garden of University of Balochistan, Quetta is a protected area includes a park, herbs, medicinal plants, cacti, succulents, shrubs, climbers, creepers, perennials, trees and conifers. It has many rare and unique plants. It has population of plants from Balochistan, Sindh and also from other countries. The garden is open for public and provides opportunity for visitors to see, learn and develop basic understanding of biodiversity. The main objective of Botanical Garden is education and to conserve rare, threatened and endangered species. A large number of economically important medicinal plants, rare, native and exotic species are introduced and successfully

37 grown for the first time in Baluchistan. This has provided an opportunity for the students of Botany, Agriculture and Forestry to carry out their research activities; see the unique plants practically on site and to recognize a large number of plants, they have only seen in books. Conserved area has large number of wild and cultivated plants.

Fig 1.6 Botanical garden University of Balochistan (Control site for plant study)

1.4. AIM AND OBJECTIVES OF THE STUDY

Air pollution in Quetta city has risen to an alarming state rapidly during the last few decades due to heavy automobile activities. Rapid increase in automobile activities and traffic congestion contributes to most of the air pollution problems, resulting in damage to the plant growth. This work was carried out to analyze the effects of air pollution, predominantly caused by vehicles, industrial pollution and microclimate, on morphology and anatomy of different plant species, growing near the roads of the city. The investigated plants species are very common and widespread in the investigated area and these can be cultivated as well as grow spontaneously. They have a wide distribution, which indicate a high ecologically plasticity and adaptability to different environmental conditions. The goal of this thesis is to prove the statement that plants respond to environmental stress, from different anthropogenic and non-anthropogenic sources, by changing the morphology of their leaves.

1.4.1. Spacific Objectives of the Study:

1. To determine the actual concentration of toxic matters (Gases and particulate matter PM) in the atmosphere of Quetta city, their comparison with non- polluted site and seasonal variation. 2. To find out Air Quality index of Quetta and to classified the air pollutants in different levels according to their effects. 3. To estimate the concentration of heavy metals in leaves of different common plant species collected from Quetta city, their comparison with the plants of non-polluted site and seasonal variation. 4. To evaluate the physiochemical attributes (RWC, AAC, pH and TCh) of leaf in different plant species and their comparison between polluted and non-polluted sites. 5. To establish the Air pollution tolerance index (APTI) of some common plant species of Quetta city and to classify them in order to their tolerance level in polluted atmosphere of the city. 6. To find out the effect of air pollutants on morphological (foliage length, width, area and petiole length) and anatomical (number of epidermal cells, number of

stomata cells, number of opened, closed and abnormal/injured stomata) attributes on plant leaves growing along the road side of Quetta city. 7. The finding of the study would be utilized for minimizing the air pollution in Quetta.

Chapter 2

REVIEW OF LITERATURE

2.1. Ambient Status of Air Pollutants and Their Seasonal Variation: Particulate matter (PM) was widely studied by many workers. Agarwal et al., (1999) indicated in his study that Indian cities are facing serious problems of airborne particulate matter. Manins et al., (2001) reported that agricultural activities and vehicular traffic may generate local dust concentrations close to the source that exceed environmental pollution. Hanesch and Rantitsch, (2007), Maher et al., (2008), Mitchell & Maher,

(2009) and Szo¨nyi et al., (2008) reported that traffic-derived PM10 values decrease not only with increased distance from roads, but also with increased height. Cacciola et al., (2002) in their studies reported that United Nations estimated that over 600 million people in urban areas worldwide were exposed to dangerous levels of traffic- generated air pollutants. Samal & Santra, (2002) established that leaves and exposed parts of a plant generally act as persistent absorbers in a polluted environment. Freer- Smith et al., (2005) proved that the presence of trees in the urban environment can improve air quality through enhancing the uptake of gases and particles near roadways. A number of studies have used the magnetic properties of deposited particles as a proxy for particulate pollution levels. According to Katiyar & Dubey, (2000) air pollutants cause chlorosis, necrosis, and epinasty in plants.

Trees act as a sink for air pollutants and thus reduce their concentration in the air Tewari, (1994). NO can be considered either toxic or protective both in animals and in plants, Beligni & Lamattina, (1999 & 2001) reported that depending on the concentration and the tissue where it is acting. Kalandadze, (2003) and Uaboi- Egbenni et al., (2009) observed that plants of urban areas were greatly affected by different air pollutants like Oxides of nitrogen and sulphur, hydrocarbon, ozone, particulate matters, hydrogen fluoride and peroxyacyl nitrates etc. They also found in their study, that the car pollutants have long term effects on plants by influencing CO2 contents, light intensity, temperature and precipitation. Dust interception capacity of plants depends on their surface geometry, phyllo-taxy, and leaf external characteristics such as hairs, cuticle etc., height, and canopy of trees.

Removal of pollutants by plants from air is by three means, namely absorption by the leaves, deposition of particulates and aerosols over leaf surfaces, and fallout of particulates on the leeward side of the vegetation because of the slowing of the air movement. Beckett et al., (2000) studied the Particulate pollution capture by urban trees and found that the presence of vegetation in the urban areas make the environmental air clean and improve the air quality by reducing toxic gases and particles. Fallon & Sieff, (2002) demonstrated that the particulate air pollution may block stomata, increase leaf temperature, reduce photosynthesis, reduce fruit set, leaf growth, pollen growth, leaf necrosis and chlorosis, reduced tree growth and bark peeling in plants and trees. They also reported that Sulfur dioxide has been historically known to produce destructive effects on vegetation and forests. It disrupted the cell metabolism, injured the leaf, reduced growth and reproduction and increase in susceptibility of plants to attacks by insect herbivores. Grantz et al., (2003) reported that the direct physical effects of mineral dusts on vegetation became apparent only at relatively high surface loads (>7g m–2) as compared with the chemical effects of reactive materials such as cement dust which may become evident at 2 g m–2.

Pal et al., (2000 “b”); Fang and Ling, (2005) and Martinez-Sala et al., (2006) reported that green belts not only reduce the air pollution, but also reduce noise pollution. Prajapati et al., (2006) reported that Vehicle-derived particulates were monitored using magnetic properties of leaf dust and it has been established that they are particularly dangerous to human health. Pryor et al., (2007) indicated that dry deposition of pollution particles is more important than wet deposition, particularly near to pollution sources and they found that different environmental conditions are always reflected to the plants. Intensive industrial production is usually connected with the emission of various pollutants to the environment.

2.2 Heavy Metal Contamination of Plant Leaves: Stankovic et al., (2009) analyzed the heavy metal content (Zn, Fe, Pb, Cu, Ni, Cr, Mn, Cd, As, Hg) in leaves of the trees growing in the urban part of the city of Belgrade, wider city area and rural area it may be noted that the content of Fe, Pb, Ni, Cr and Cd increases going from rural to urban area. Ceburnis et al., (2000 & 2002) investigated and found that bio-monitoring with mosses is based on the fact that terrestrial carpet - forming species obtain most

42 of their nutrients directly from wet and dry deposition, they clearly reflect the atmospheric deposition, especially well suited to heavy metals pollution on a larger time scale. Cie_ko et al., (2005), reported that some pollutants contain heavy metals that have bad effects on plants and plant organs. Zayed et al., (1991) pointed that coniferous trees are often regarded as better temporal bio-indicators of environmental contamination, as their wood type reduces the lateral transfer of contaminants between rings as with herbs and grasses, tree leaf surfaces may govern the extent of accumulation of particles.

Keane et al., (2001) examined the metal content in dandelion leaves in relation to environmental metal levels; the concentrations of eight metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) were analyzed in leaf and soil samples collected at 29 sites in the mid- western United States differentially impacted by pollution. They indicated that dandelions may not be a particularly effective tool for quantifying levels of environmental metal contamination, at least on the scale of pollution typifying industrialized urban areas of the mid-western United States.

2.3. Bio-indication of air pollution in relation to biophysical and biochemical attributes of plant leaves: Vegetation is a very important bio-indicator of the overall impact of air pollution, and the effect observed is more reliable than the one obtained from direct determination of the pollutant in air over a short period. It is a fact that different environmental conditions are always reflected to the plants. Flowers et al., (2007); Hoque et al., (2007) and Klumpp et al., (2000), studied the impact of air pollution on ascorbic acid content, chlorophyll content, leaf extract pH and relative water content and reported that separate parameters gave conflicting results for same species, hence a group of parameters may be used for bio-indication of air pollution. Several other researchers, Bhatia, (2006); Henry & Heinke, (2005); Rao, (2006) and Sodhi, (2005), agreed that air pollutants effect the plant growth adversely. Yan-Ju, (2008) indicated that the air pollution tolerance index is used by landscapers to select plant species tolerance to air pollution, which is best way for the indication of air pollution level.

According to the Delaware Health & Social Services, (2007), exposure of plants and trees to specific air pollutants such as Ozone, Sulfur dioxide, Nitrogen dioxide and Ammonia have physical effects such as speckle of brown spots, larger bleached-

43 looking areas, irregular brown or white collapsed lesions on inter costal tissue and near the leaf edge and unnatural green appearance with tissue drying out.

Syyednejad et al., (2009 “a” & “b”) demonstrated that leaf length, breadth of leaflets and area decreased in the stress of air pollution in the leaves of Albizia lebbeck. Honour et al., (2009) indicated that plants growing in polluted urban environments are likely to experience significant changes in the timing of key activities such as flowering and leaf senescence, as well as potentially detrimental changes in leaf surface characteristics and growth. Species differed in the magnitude of response to pollutant exposure.

Chauhan, (2010) studied 4 plant species Ficus religiosa, Mangifera indica, Polyalthia longifolia and Delonix regia for chlorophyll ‘a’, chlorophyll ‘b’, total chlorophyll content, ascorbic acid, carotenoid, pH, relative water content and APTI in the leaf samples of all trees collected from polluted site and compared with samples collected from control area, which reflects that there was significant changes in all these parameters and found the maximum reduction in the samples collected from polluted sites. Syyednejad and Koochak, (2011) studied the effect of Air Pollution on Eucalyptus camaldulensis found significant reduction in morphological attributes. According to Katiyar & Dubey, (2000) air pollutants cause chlorosis, necrosis, and epinasty in plants.

Lorenzini et al., (2006) and Kosiba, (2008) indicated that the leaf traits can be used as a tool for estimating the status of air pollution. Poikolainen, (2004) said that the term bio-indicator generally refers to all organisms that provide information about the environment or the quality of environmental changes. Some plant species reported sensitive to single pollutants and some are sensitive to mixtures of pollutants. Those species or cultivars are likely to be used in order to monitor the effects of air pollutants as bio-indicator plants. They have a great advantage to show clearly the effects of phytotoxic compounds present in the ambient air. As such, they are ideal for demonstration purposes. However, they can also be used to monitor temporal and spatial distributions of pollution effects (Temmerman et al., 2005).

Agarwal, (2000) studied twenty five leaf samples of Thevetia nerifolia Juss and twenty leaf samples of Cassia siamea L. both under polluted and non-polluted

44 environment. He established that the compound leaves show a greater damage than narrow simple leaves. He also found increase in densities of stomata, trichomes and epidermal cells, longer trichomes and reduction in size of epidermal cells at polluted sites as compared to that at reference site. Salgar and Chandarani (2000) indicated the effect of ambient air from chamber on the growth performance of wild plants collected from less polluted area Ghatala and R.C.F. colony in chamber and highly polluted area of collector’s colony which was also in chamber and found that the ambient air of chamber inhibited all the parameters such as length of shoot, from apex up to 4th inter-node, length of 4th inter-node, dry matter of shoot, basal area of the stem, area of 4th inter-node, and total number of branches; however dust fall/unit area of leaf was stimulated.

Moraes et al., (2002) studied three plants species viz Sodium guajava L., Psidium cattleyanum (Sabine.) and Mangifera indica L. under field conditions as possible tropical bio-indicators of industrial air pollution. They observed four different sites in the coastal mountains near the industrial complex, with high contamination of particulate matter, fluorides (F), sulphur (S) and nitrogen (N) compounds; Caminho do Mar (CM1, CM2), mainly affected by organic pollutants, S and N compounds, and secondary pollutants; and Parana piacaba (PP), affected by secondary pollutants, such as ozone.

Kardel et al., (2009) evaluated the urban habitat quality by studying specific leaf area (SLA) and stomatal characteristics of the common herb Plantago lanceolata L. SLA and stomatal density, pore surface and resistance were measured at 169 locations in the city of Gent (Belgium) and they found, stomatal density and stomatal pore surface are assumed to be potentially good bio-indicators for urban habitat quality.

2.4. Effect of Air Pollution on Morphological and Anatomical Attributes of Plant Leaves: Ahmad et al., (2009) studied a total of 36 dicot species distributed in 34 genera and 20 families for stomatal diversity and found seven types of stomata in which amphianisocytic was the dominant one. Curtis & Wang, (1998) and Medlyn et al., (2001) reported that stomatal responses to elevated CO2 are quite variable with literature reviews, they indicate that average reductions ranges was from 11 to 40%. Gardiner, (2006) and Santos, (1990) reported that the acid rain (a product of air pollution) severely affects trees and plants as well and it can kill trees, destroy the

45 leaves of plants. It is also associated with the reduction in forest and agricultural yields. Ghahreman et al., (1999) studied the leaf epidermis in genus Hyoscyamus L. in Iran and found that the most useful anatomical characters are stomatal occurrence, stomatal index, pattern of anticlinal walls and type of trichomes. Root, et al., (2003), indicated that certain plant traits, such as penology and leaf morphology, appeared to have changed in some cases, with leaf expansion and flowering occurring earlier in the spring and the increases in atmospheric CO2 concentration causes a reduction in stomatal density.

Sharma & Deepti, (2000) reported many types of stomatal variations in leaves of Mehndi (Lawsonia inermis L.) after treatment with different concentrations of detergent. The structure, shape and size of epidermal cells is seriously affected by different concentrations of detergent and caused abnormalities. Leaves of treated plants show increased number of epidermal cells though smaller in size as compared to those leaves from control site plants. Anderson and Michelle, (2003) studied the acquired changes in stomatal characteristics in response to ozone during plant growth and leaf development of bush beans (Phaseolus vulgaris L.). They also reported that stomata, as regulating mechanisms for gases entering or escaping from leaves, are the excellent apparatus to study the interaction between plants and their environment, i.e., the atmosphere and its associated air pollutants. Sahu & Warrir, (1985) indicated that the small amount of Lead could penetrate the cuticle probably through stomata and other openings.

Elagoz, et al., (2006) studied the changes in stomatal characteristics in response to ozone during plant growth and leaf development of bush beans (Phaseolus vulgaris

L.) and found that O3 has adverse affect on stomatal plasticity. Shenxi & Lue, (2003) studied the effects of leaf age on gas exchange, transpiration, stomatal resistance and structure of 07 year-old trees of Asian pear and found that net photosynthesis and stomatal conductance increased with leaf age, particularly in the early stage and reached a maximum value when the leaf was completely expanded. Balasooriya et al., (2009) focused their studies on the specific leaf area, stomatal density, stomatal pore surface, minimal stomatal resistance, chlorophyll a and b, C and N content, δ13C and δ15N in the leaf samples of a common herbaceous plant Taraxacum officinalis. They found that the stomatal pore surface and minimal stomatal resistance of T. officinalis varied significantly between lands uses classes i.e. in the harbor and

46 industry land use class and the urban land use class. Alireza et al., (2010) investigated whether leaves of plane trees (Platanus orientalis) are damaged by traffic pollution by conducting a study on trees from a mega-city (Mashhad, Iran). They found that soil and air from the urban center showed enrichment of several toxic elements, but only lead was enriched in leaves. Leaf size and stomata density were lower at the urban site. At the urban site leaf surfaces were heavily loaded by dust particles but the stomata were not occluded; the cuticle was thinner.

Chotani et al., (1975) and Yousfzai et al., (1970, 1984 & 1987) have indicated high amount of pollutants in Karachi city and found that the particulates type air pollutant such as ash, dust and dirt fall on the top of leaves. These particulates do not enter the leaf but may damage it by mechanical abrasion of the surface. Particulate matter can also block the stomata and reduce the food making ability of plant. Trag et al., (2001) made a comparative study of the leaves of Z. mauritiana L. collected from a non- polluted site and a heavily polluted site. They found out certain morphological, biochemical and physiological changes with respect to pollution. Mahmood and Iqbal, (1985) studied the impact of vehicular emission on germination and growth of certain roadside plants and revealed that maximum reduction in seed germination was recorded in Albizzia lebbek and Dalbergia sissoo which were collected from roadsides of Liaquataabad and Nazimabad area in Karachi. Shafiq et al., (2009) studied the effect of auto exhaust emission on the penology of Cassia siamea and Peltophorum pterocarpum growing in different areas of Karachi and found the significant variation on the morphological characters of plant leaves collected from polluted and non-polluted sites.

The present study will investigate the air pollution status of Quetta city by using the leaves of road side vegetation like trees, shrubs and climbers viz: Pinus halepensis Miller., Elaeagnus angustifolia L., Eucalyptus tereticornis L., Ficus carica L., Fraxinus excelsior L., Melia azadirach L., Morus alba L., Morus nigra L., Pistacia vera L., Prunus armeniaca L., Punica granatum L., Robinia pseudoacacia L., Rosa indica L. and Vitis vinifera L. This research will provide new insights into the problem as it has not been done before in Balochistan and even in Pakistan.

Chapter 3

AMBIENT STATUS OF AIR POLLUTANTS AND THEIR SEASONAL VARIATION IN QUETTA CITY

3.1. INTRODUCTION

Air is the invisible, tasteless, odorless mixture of gases that surrounds the earth. Some gases in this amalgam can be harmful in higher concentrations. Some components, such as oxides of nitrogen or sulfur are always present, but excessive quantities can harm human health and plants production and forests (Treshaw and Anderson, 1991). The atmosphere is used as a natural filter for air pollutants. The contamination of the atmosphere is so severe that are recognized as the serious issue of the world (Kumar, 1999). Air pollution may causes different diseases to man, animals and plants, contribute to the deterioration of both our cities and country. It also has a direct or indirect effect on our climate. The visible injury symptoms on plants and leaves have been noted by Chhatwal, (1997). The composition of the air pollutants can be inorganic, organic, or a complex mixture of both. Environmental sources for pollutants could include construction and demolition activities, mining and mineral processing, agricultural activities, wind-blown dust, automobiles and transportation related activities on the road. According to the World Health Organization (WHO, 2006), 4-8% of deaths occurring annually in the world are related to air pollution associated with anthropogenic activities (Kathuria, 2002; Lopez et al., 2005). Urban air pollution has become a serious threat to plants, animals and human health, due to which it is receiving a great attention of the world today. There are many factors which responsible for the urban air pollution like increased urbanization, lack of awareness, use of fuels with poor environmental performance, high dependability on fossil fuels, in effective rules and regulations for vehicular emission and increasing number of motor vehicles (Chauhan & Joshi, 2008; Joshi & Chauhan, 2008). Atmospheric pollution in urban area generally thought to be of different level and condition. This study investigates the status of particulates and gaseous pollution in and around Quetta city and their effects on various parameters in different seasons which have not been investigated in the area before.

3.2. MATERIALS AND METHODS

After preliminary surveys and field trips of Quetta city and surrounding city areas were selected as polluted areas and Hazargangi Chiltan National Park and Wali Tangi Zarghoon area were selected as control areas for the present study.

3.2.1. Air Sampling: Air sampling was done during 2010 and 2011 for the estimation of air-borne dust (SPM2.5μm and SPM10μm) concentration and gaseous concentration (CO, SO2, NO2). A walk through survey of different locations of Quetta city was carried out and on the basis of assessment of traffic density (vehicle count) and the amount of visible auto exhaust fumes/smoke and roadside dust, eleven different locations of the Quetta city were selected as polluted sites:-

1. Quetta Cantt 2. Hazara Town 3. Shabaz Town 4. Manan Chowk 5. Meezan Chowk 6. Jinnah Road 7. Sariab Road 8. Satellite Town (Mini Market Block 3) 9. Zarghoon Road (Railway Crossing) 10. Mitha Chowk (Abdul Sattar Road) 11. Golimar Chowk (Bolan Medical Complex) Control sites: 1. Hazargangi Chiltan National Park 2. Wali Tangi Zarghoon area 3.2.2. Analysis of Air Samples: Air sampling was carried out at each study site during 2010 and 2011 from January to December for particulates matter (SPM 2.5μm and SPM10μm) and gases (SO2, NO2 and CO). Air pollutants (SO2, NO2, CO, SPM 2.5μm and SPM10μm) were measured with the help of RDS APM 460 by sucking air into appropriate reagent for 1 hour at every 30 days interval. The SPM 2.5μm and SPM10μm were analyzed using Respireable Dust Sampler (RDS) PM 460 operated at an average flow rate of 1.0 _ 1.5m3 min-1. Pre-weighed glass fiber filters (GF/A) of

Whatman were used as per standard methods. SO2 and NO2 were collected by

49 bubbling the sample in a specific absorbing solution (sodium tetra-chloromercuate of

SO2 and sodium hydroxide for NO2 and Magnesium Per-chlorate for CO) at an average flow rate of 0.2-0.5 min-1, Carbon monoxide (CO) was determined by using automated non-dispersive infra red absorption gas analyzer (NDIR). The collected samples were put in ice boxes immediately and transferred to a refrigerator until analyzed. The apparatus was kept at a height of 2 m from the surface of the ground. The concentration of particulates matter and gases data was recorded in (μg/m3/hr), ppm and ppb. The concentration of NO2, SO2, CO and SPM10 and SPM2.5 was measured by standard modified method of Jacobs- Hochheiser, (1958), West and Gaeke, (1956) and Rao and Rao, (1998).

3.2.3. Air Quality Index (AQI): Air Quality Index of individual pollutants was calculated with the concentration values of NO2, SO2 CO and SPM10 and SPM2.5. The samples collected from all sites were analyzed using the computer based program called as AQI calculator and following the method given by Rao and Rao, (1998).

3.2.4. Gradation of Air Quality Index: The spectrum of AQI was divided in to five grades or categories for air pollutant referring to a previous study (Rao and Rao, 1998).

1. Good (G) 2. Moderate (M) 3. Harmful for sensitive group (Hsg) 4. Harmful for all the population (Ha) 5. Very harmful (Vh)

3.2.5. Traffic counting: The vehicles passing along the eleven selected roads of the city were counted three time a day/5minutes during rush hours (8-9am, 1:30-2:30pm and 6-7pm) for three consecutive working days of every month and then seasonal average for spring, summer, autumn and winter seasons was calculated. Buses, trucks, Wagons Cars, Motorbikes and Rickshaws were counted (Khan, 1996; Hamidullah et al., 1998). The amounts of pollutants from polluted sites were compared to non-polluted sites and the increasing percentage was calculated according to the formula given by Syed & Iqbal, (2008).

3.2.6. Statistical analysis: The standard deviation values of the means were calculated for comparison of site categories. To determine the significance of the samples, paired t-test was performed and significance of comparison of means was determined by using f-test. Relation between variables and linear relationship were assessed using correlation coefficient (Steel & Torrie, 1980).

3.3. RESULTS

Results regarding to the ambient status of CO, SO2, NO2 and SPM during different seasons of the year at different locations of the city are illustrated in Table 3.1-3.8. Overall increased percentage of all the investigated air pollutants in the atmosphere of the Quetta city with respect to control site during spring, summer, autumn and winter are shown in Table 3.9-3.12. The range of air pollutants in the city are illustrated in Table 3.13-3.14. Air Quality Index of the urban area and control site are described in Tables 3.15-3.19 and Standard for AQI are presented in Tables 3.20. Average numbers of vehicles’ moving per five minutes at different locations of the city during different seasons are given in Tables 3.21. Linear relationships between number of vehicles and air pollutants are presented in Fig 3.1 – 3.20, Correlation coefficient between vehicles and air pollutant aregiven in Table 3.23 and Correlation co-efficient among the air pollutants were presented in Table 3.22.

Table 3.1: Ambient status of CO, SO2 and NO2 at different locations of Quetta city during spring season

Locations CO (ppm) SO2 (ppb) NO2 (ppb) Ave S.D t Ave S.D t Ave S.D t Quetta Cantt 5.7 (1.0) 4.35** 18.0 (3.6) 4.11** 38.4 (14.8) 2.20* Hazara Town 6.3 (0.9) 5.87** 18.4 (3.5) 4.90** 52.3 (6.50) 9.33** Shabaz Town 6.3 (1.0) 5.34** 18.6 (2.7) 6.28** 53.4 (6.40) 9.74** Manan Chowk 6.7 (0.9) 6.68** 30.4 (2.5) 16.07** 88.2 (22.8) 5.79** Mezan Chowk 7.0 (0.9) 7.18** 30.8 (2.3) 17.62** 90.3 (22.5) 6.07** Satellite Town 7.2 (1.0) 6.95** 30.9 (2.4) 17.41** 86.0 (21.8) 5.87** Jinnah Road 7.5 (1.1) 7.14** 31.0 (2.5) 16.63** 87.7 (22.2) 5.90** Zarghoon Road 7.4 (1.5) 4.88** 31.3 (2.7) 15.62** 91.2 (21.7) 6.38** Metha Chowk 8.0 (1.2) 6.71** 31.8 (2.4) 18.07** 88.6 (22.6) 5.88** Golimar Chowk 8.0 (1.2) 7.29** 32.0 (2.9) 14.91** 89.1 (21.7) 6.24** Sariab Road 7.4 (0.9) 8.13** 29.0 (3.0) 12.83** 86.1 (20.9) 6.13** Mean 7.0 (1.1) 6.40** 27.4 (2.8) 12.54** 77.5 (17.8) 6.21** Mean value of Control Site 3.5 (0.3) 9.8 (0.8) 22.1 (2.93) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

During spring season over all mean contents of CO, SO2 and NO2 at urban area (Polluted sites) was found to be 7.0 ppm, 27.4 ppb and 77.5 ppb, while at control site it was 3.5 ppm, 9.8 ppb and 22.1 ppb, respectively. Statistical analysis (t-test) of the results (Table 3.1) exhibited that all the parameters at all locations were highly significant than control site at P<0.01 significant level. Only one location (Quetta

Cantt) showed slightly significant difference in the values of NO2 at P<0.05 significant level. Average contents of CO, SO2 and NO2 in the atmosphere of Quetta city during spring season was in the range of 5.7 - 8.0 ppm, 17.3 – 32.0 ppb and 38.4 – 91.2 ppb, respectively. Golimar Chowk keep count of highest contents of CO and

SO2 and highest contents of NO2 was recorded from Zarghoon Road, while Quetta Cantt showed minimum level of all the parameters during spring.

Table 3.2: Ambient status of CO, SO2 and NO2 at different locations of Quetta city during summer season

Locations CO (ppm) SO2 (ppb) NO2 (ppb) Ave S.D t Ave S.D t Ave S.D t Quetta Cantt 7.7 (0.3) 21.12** 26.5 (0.18) 53.97** 63.8 (1.5) 44.10** Hazara Town 7.9 (0.3) 24.09** 28.6 (0.09) 51.60** 65.6 (1.5) 46.48** Shabaz Town 8.3 (0.3) 25.30** 28.5 (0.14) 47.21** 67.6 (1.6) 44.90** Manan Chowk 10.5 (0.3) 44.25** 37.6 (0.16) 73.78** 112.6 (2.8) 57.29** Mezan Chowk 10.7 (0.3) 41.37** 38.3 (0.21) 71.23** 114.0 (2.4) 68.00** Satellite Town 9.8 (0.2) 57.84** 37.3 (0.28) 76.66** 109.7 (3.0) 52.10** Jinnah Road 10.0 (0.1) 85.23** 37.9 (0.18) 74.05** 111.0 (2.0) 78.14** Zarghoon Road 10.5 (0.2) 69.42** 38.5 (0.36) 75.59** 114.4 (2.5) 76.12** Metha Chowk 9.7 (0.1) 112.8** 38.4 (0.27) 89.11** 112.9 (3.5) 46.27** Golimar Chowk 10.5 (0.8) 14.42** 38.8 (0.19) 74.32** 114.4 (3.3) 50.35** Sariab Road 9.4 (0.6) 12.58** 36.9 (0.39) 57.28** 109.2 (1.9) 82.13** Mean 9.2 (0.7) 13.12** 35.2 (0.22) 68.19** 99.6 (2.3) 58.57** Mean Value of Control Site 4.6 (0.2) 13.9 (1.1) 30.7 (2.3)

Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

During summer season, values from all the locations at urban sites were CO;

9.2 ppm, SO2; 35.2 ppb, NO2; 99.6 ppb and at control site the values remained 4.6 ppm, 13.9 ppb and 30.7 ppb, respectively (Table 3.2). The t-test showed that all parameters were highly significant at urban site than control site at P<0.01 significant level. Average contents of CO, SO2 and NO2 in the atmosphere of Quetta city (polluted sites) during summer was found in the range of 7.7 – 10.7 ppm, 26.5 – 38.8 ppb and 63.8 – 114.4 ppb. Mezan Chowk, Golimar Chowk and Zarghoon road demonstrated highest contents of CO, SO2 and NO2 respectively, while Quetta Cantt showed lowest values of all the parameters.

Table 3.3: Ambient status of CO, SO2 and NO2 at different locations of Quetta city during autumn season

Locations CO (ppm) SO2 (ppb) NO2 (ppb) Ave S.D t Ave S.D t Ave S.D t Quetta Cantt 8.3 (0.19) 35.39** 27.7 (0.23) 54.92** 68.4 (0.96) 70.67** Hazara Town 8.6 (0.15) 46.53** 29.1 (0.23) 58.99** 69.9 (0.57) 141.26** Shabaz Town 9.1 (0.07) 26.10** 28.9 (0.15) 63.18** 73.8 (0.96) 81.83** Manan Chowk 10.4 (0.40) 27.05** 38.4 (0.41) 90.20** 119.3 (0.72) 193.83** Mezan Chowk 10.9 (0.26) 45.62** 38.8 (0.15) 70.28** 121.4 (0.96) 181.57** Satellite Town 11.1 (0.33) 36.91** 38.5 (0.57) 81.02** 118.3 (0.72) 191.52** Jinnah Road 11.2 (0.33) 38.40** 38.6 (0.27) 88.45** 118.1 (1.13) 147.28** Zarghoon Road 11.7 (0.27) 48.50** 39.2 (0.28) 73.61** 122.8 (1.10) 160.21** Metha Chowk 11.9 (0.29) 48.29** 39.1 (0.20) 75.87** 121.7 (1.91) 091.33** Golimar Chowk 12.2 (0.33) 44.26** 39.3 (0.18) 54.68** 122.5 (1.36) 128.31** Sariab Road 10.8 (0.31) 36.88** 38.1 (0.38) 55.02** 116.3 (1.44) 113.41** Mean 10.5 (0.20) 46.22** 35.9 (0.27) 111.2** 106.6 (1.02) 141.07** Mean value of Control Site 5.0 (0.13) 15.6 (0.53) 34.7 (0.62) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

During autumn season, over all mean contents at all the polluted sites were

CO; 10.5 ppm, SO2; 35.9 ppb and NO2; 106.6 ppb (Table 3.3), but at control site it remained 5.0 ppm, 15.6 ppb and 34.7 ppb, respectively. The t-test reported that the values of all the parameters at all the locations were highly significant (P<0.01) with respect to control. The average contents of CO, SO2 and NO2 in the atmosphere of Quetta city during autumn season were 8.3 – 12.2 ppm, 27.1 – 39.3 ppb and 68.4 –

122.8 ppb. Highest contents of CO, SO2 and NO2 were recorded from Golimar Chowk and Zarghoon Road respectively, while lowest at Quetta Cantt during autumn season.

Table 3.4: Ambient status of CO, SO2 and NO2 at different locations of Quetta city during winter season

Locations CO (ppm) SO2 (ppb) NO2 (ppb) Ave S.D t Ave S.D t Ave S.D t Quetta Cantt 5.4 (0.9) 4.37** 16.8 (3.8) 03.31** 35.3 (14.6) 2.05** Hazara Town 6.0 (0.9) 5.57** 18.0 (3.7) 04.08** 49.6 (6.7) 8.68** Shabaz Town 6.0 (1.0) 4.99** 18.0 (3.0) 04.98** 51.3 (6.3) 9.79** Manan Chowk 6.5 (0.9) 6.24** 29.6 (3.1) 12.33** 85.2 (22.3) 5.80** Mezan Chowk 6.7 (0.9) 6.81** 30.0 (2.9) 13.33** 87.4 (22.6) 5.93** Setalite Town 7.0 (1.0) 7.04** 30.3 (2.7) 14.45** 83.3 (22.0) 5.71** Jinnah Road 7.2 (1.0) 7.34** 30.3 (2.0) 19.39** 83.8 (21.0) 6.02** Zarghoon Road 7.1 (1.5) 4.83** 31.0 (2.8) 14.76** 88.6 (20.9) 6.51** Metha Chowk 7.4 (1.3) 6.14** 31.1 (2.8) 14.95** 86.7 (22.4) 5.90** Golimar Chowk 7.7 (1.2) 6.95** 31.6 (3.1) 13.63** 87.3 (21.7) 6.17** Sariab Road 7.2 (0.9) 7.82** 28.7 (2.9) 12.49** 83.0 (20.6) 6.08** Mean 6.8 (1.1) 6.19** 26.9 (3.0) 11.04** 74.7 (17.6) 6.18** Mean value of Control Site 3.5 (0.3) 10.5 (1.1) 20.27 (2.7) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

In winter season, the overall mean contents of CO, SO2 and NO2 (Table 3.4) from all the urban sites were recorded 6.8 ppm, 26.9 ppb and 74.7 ppb, while at control site it was 3.5 ppm, 10.5 ppb and 20.3 ppb, respectively. Statistical analysis of the results revealed that the values of all the parameters (CO, SO2, NO2) at all the locations were highly significant (P<0.01) different from the control site. Average contents of CO, SO2 and NO2 in city area were 5.4 – 7.7 ppm, 16.8 – 31.6 ppb and

35.3 – 88.6 ppb, respectively. Golimar Chowk achieved highest contents of CO, SO2 and Zarghoon road NO2, where as Quetta Cantt showed lowest values of all the parameters during autumn.

Table 3.5: Ambient status of SPM at different locations of Quetta city during spring season

Locations SPM10 SPM2.5 Ave S.D t Ave S.D t Quetta Cantt 234.2 (3.9) 89.6** 26.4 (2.9) 9.7** Hazara Town 240.2 (3.7) 96.9** 31.2 (4.6) 8.1** Shabaz Town 246.0 (2.8) 131.0** 34.6 (3.8) 11.6** Manan Chowk 326.5 (3.4) 157.2** 53.4 (8.3) 9.8** Mezan Chowk 331.4 (2.7) 200.1** 54.2 (8.2) 10.8** Satellite Town 341.6 (2.8) 198.3** 54.1 (7.7) 10.8** Jinnah Road 334.7 (3.2) 169.7** 53.0 (8.3) 9.7** Zarghoon Road 347.0 (2.3) 249.1** 54.2 (6.9) 12.0** Metha Chowk 340.0 (4.2) 133.8** 53.7 (8.7) 9.4** Golimar Chowk 362.2 (2.5) 235.7** 55.8 (7.5) 11.5** Sariab Road 348.5 (2.2) 262.8** 51.1 (5.8) 13.2** Mean 313.8 (3.0) 166.6** 47.4 (6.6) 10.6** Mean value of Control Site 057.3 (2.40 12.3 (0.3)

Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

Over all mean contents of SPM10μm and SPM2.5μm during spring season were found to be 313.8 μg/m3 and 47.4μg/m3 at city area, while at control site were 57.2μg/m3 and 12.3μg/m3, respectively (Table 3.5). Statistical test exhibited that the values of all parameters at all the locations were highly significant (P<0.01) then control site. Average values of SPM10 and SPM2.5 in the atmosphere of Quetta city was found in the range of 234.2 – 362.2 μg/m3 and 26.44 – 55.89μg/m3, respectively. Highest contents of both parameters were found from Golimar Chowk and lowest from Quetta Cantt.

Table 3.6: Ambient status of SPM at different locations of Quetta city during summer season

Locations SPM10 μm SPM2.5 μm Ave S.D t Ave S.D t Quetta Cantt 247.0 (2.5) 135.6** 38.5 (3.4) 13.6** Hazara Town 251.4 (2.1) 165.4** 43.0 (3.2) 16.8** Shabaz Town 255.7 (1.5) 246.6** 44.6 (2.4) 23.6** Manan Chowk 338.2 (2.5) 206.6** 158.7 (3.5) 91.0** Mezan Chowk 341.2 (2.4) 218.9** 160.6 (3.9) 88.1** Satellite Town 350.5 (2.3) 241.6** 155.2 (4.5) 65.8** Jinnah Road 345.1 (2.6) 209.7** 155.8 (2.8) 98.4** Zarghoon Road 356.1 (2.6) 218.1** 159.8 (3.3) 92.4** Metha Chowk 350.0 (2.2) 250.5** 157.8 (2.8) 98.9** Golimar Chowk 370.7 (2.5) 231.8** 160.2 (3.7) 78.9** Sariab Road 359.1 (2.3) 249.0** 155.8 (2.0) 137.7** Mean 324.1 (2.3) 215.3** 126.4 (3.1) 71.3** Mean value of Control Site 45.9 (5.9) 15.1 (1.9) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

Over all mean contents of SPM10 μm and SPM2.5 μm during summer season in urban areas were reported to be 324.1μg/m3 and 126.4μg/m3, but at the control site it remained 45.9μg/m3 and 15.1μg/m3, respectively (Table 3.6). Statistical analysis using t-test revealed that the values of all parameters at all the locations were highly significant (P<0.01) at city sites as compared to control sites. Average amount of

SPM10 and SPM2.5 in city area during summer was reported to be in the range of 247.0 –370.7μg/m3 and 38.55 – 160.6μg/m3 respectively. Golimar Chowk and Mezan

Chowk score the highest contents of SPM10 μm and SPM2.5 μm, respectively, while Quetta Cantt showed lowest in both the parameters.

Table 3.7: Ambient status of SPM at different locations of Quetta city during autumn season

Locations SPM10 μm SPM2.5 μm Ave S.D t Ave S.D t Quetta Cantt 254.0 (0.9) 325.8** 43.2 (2.0) 24.6** Hazara Town 260.0 (2.7) 121.9** 47.6 (2.0) 28.8** Shabaz Town 263.1 (2.4) 136.8** 48.4 (2.2) 27.6** Manan Chowk 348.4 (2.3) 219.7** 160.8 (2.3) 123.4** Mezan Chowk 349.5 (2.6) 195.3** 164.6 (0.7) 107.2** Satellite Town 360.7 (3.4) 156.7** 160.6 (2.3) 122.6** Jinnah Road 354.0 (2.9) 176.5** 161.2 (2.5) 110.7** Zarghoon Road 365.7 (3.1) 173.5** 162.7 (2.5) 111.9** Metha Chowk 357.2 (1.9) 275.2** 162.7 (2.4) 117.9** Golimar Chowk 379.2 (2.4) 232.3** 164.8 (2.3) 126.8** Sariab Road 368.6 (1.9) 279.7** 158.8 (2.9) 93.9** Mean 332.8 (2.4) 198.8** 130.5 (2.2) 101.5** Mean value of Control Site 94.1 (3.3) 18.0 (0.7) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

Over all mean values of SPM10 μm and SPM2.5 μm during autumn were recorded as 332.8μg/m3 and 130.6μg/m3, from polluted sites and 94.1μg/m3 and 18.0μg/m3 from control site, respectively (Table 3.7). The t-test exhibited that the values of all the parameters at all the locations from polluted sites were highly significant (P<0.01) different from control site. Average contents of SPM10 and 3 SPM2.5 during autumn season was in the range of 254.0 – 379.2μg/m and 43.22 – 3 164.8μg/m . Golimar Chowk showed highest contents of SPM10 and SPM2.5 while Quetta Cantt was found to be the lowest.

Table 3.8: Ambient status of SPM at different locations of Quetta city during winter season

Locations SPM10 μm SPM2.5 μm Ave S.D t Ave S.D t Quetta Cantt 231.1 (5.6) 59.9** 24.2 (2.6) 9.5** Hazara Town 236.3 (3.9) 89.3** 28.5 (4.5) 7.3** Shabaz Town 241.6 (2.8) 127.1** 31.5 (3.9) 9.9** Manan Chowk 323.3 (3.0) 173.0** 51.1 (8.50 9.2** Mezan Chowk 327.5 (2.8) 186.4** 52.0 (8.2) 9.8** Satellite Town 337.4 (2.5) 213.7** 51.6 (7.3) 10.9** Jinnah Road 330.5 (3.0) 179.0** 50.4 (8.2) 9.3** Zarghoon Road 342.5 (1.8) 303.9** 52.0 (6.8) 11.7** Metha Chowk 337.2 (4.4) 123.4** 51.2 (8.4) 9.2** Golimar Chowk 357.4 (2.0) 290.2** 52.8 (7.5) 10.9** Sariab Road 344.8 (2.2) 258.0** 48.2 (5.0) 14.4** Mean 310.0 (3.0) 164.1** 44.8 (6.4) 10.2** Mean value of Control Site 61.0 (0.6) 11.7 (0.3) Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001.

Over all mean contents of SPM10 μm and SPM2.5 μm (Table 3.8) during winter season were found to be 310.0μg/m3 and 44.8μg/m3, while from control site it ranged between 61.04μg/m3 and 11.7μg/m3 respectively. The t-test revealed that the values of all the parameters at all the locations from polluted sites were highly significant (P<0.01) than control sites. Average results of SPM10 and SPM2.5 in the atmosphere of Quetta city during winter season exhibited that they were in the range of 231.1 – 357.4μg/m3 and 24.2 – 52.8μg/m3 respectively. Maximum content were recorded from Golimar Chowk, while minimum was found from Quetta Cantt.

Table 3.9: Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during spring season Pollutants Non- Polluted WHO polluted site Diffe Standard site Ave S.D rence Inc% Moderate Harmful t Ave S.D CO ppm 3.3 (0.3) 7.0 (1.1) 3.7 52.8 1-9 10-15 6.4***

*** SO2 ppb 8.2 (0.8) 27.4 (2.8) 19.2 70.0 1-75 76-300 12.5 *** NO2 ppb 15.6 (2.9) 77.5 (17.8) 61.8 79.7 1-100 101-644 6.2 SPM2.5μg/m3 10.7 (0.2) 47.5 (6.6) 36.7 77.4 1-35 36-150 10.6*** SPM10μg/m3 45.2 (2.4) 313.9 (3.0) 268.6 85.5 1-154 155-354 166.6*** Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001and Inc%: Increasing percentage

Table 3.9 shows that during spring, the percentage increase of CO, SO2, NO2,

SPM2.5 and SPM10 from city areas were recorded to be 52.7, 70.0, 79.7, 85.5 and 77.4 % respectively. The t-test indicated that values of all the parameters were very highly significant (P<0.001) from polluted sites as compared to non-polluted sites.

Difference of CO, SO2, NO2, SPM2.5 and SPM10 between polluted and non-polluted site was found to be 3.7, 19.2, 61.8, 36.7 and 268.6 respectively. SPM10 showed maximum difference, while CO showed the least. The concentrations of all pollutants estimated from polluted sites were within the permissible limits given by WHO,

2006, except SPM10 exceeds the limits and can be considered as very harmful during spring season.

Table 3.10: Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during summer season

Pollutants Non- Polluted site WHO polluted Ave S.D Diffe Standard site rence Inc% Moderate Harmful t Ave S.D CO ppm 4.1 (0.2) 9.17 (0.6) 5.0 54.5 1-9 10-15 13.1***

*** SO2 ppb 9.0 (1.1) 35.21 (0.2) 26.1 74.3 1-75 76-300 68.1

*** NO2 ppb 21.4 (2.3) 99.57 (2.3) 78.1 78.4 1-100 101-644 58.5 SPM2.5μg/m3 12.8 (1.6) 126.4 (3.1) 113.5 89.8 1-35 36-150 71.3*** SPM10μg/m3 55.3 (5.9) 324.12 (2.3) 268.7 82.9 1-154 155-354 215.3*** Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001and Inc%: Increasing percentage

During summer, percentage increase of CO, SO2, NO2, SPM2.5 and SPM10 was recorded as 54.5, 74.3, 78.4, 89.8 and 82.9 % respectively (Table 3.10). The t-test revealed that the values of all the parameters were very highly significant (P<0.001) at polluted site then non-polluted sites. The difference between polluted and control sites recorded were CO; 5.0, SO2; 26.1, NO2; 78.1, SPM2.5; 113.5 and SPM10; 268.7, with CO showed the lowest difference, while SPM10 had the highest difference. The concentrations of CO, SO2, NO2 estimated from polluted sites were within the permissible limits, but the SPM2.5 and SPM10 were more than the limits given by WHO, 2006.

Table 3.11: Over all increasing percentage of air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during autumn season

Pollutants Non- WHO polluted Polluted Diffe Inc Standard Ave S.D Ave S.D rence % Moderate Harmful t CO ppm 4.2 (0.1) 10.54 (0.2) 06.3 59.8 1-9 10-15 46.2***

*** SO2 ppb 10.2 (0.5) 35.92 (0.2) 25.7 71.6 1-75 76-300 111.2 *** NO2 ppb 22.4 (0.6) 106.60 (1.0) 84.1 78.9 1-100 101-644 141.1 SPM2.5μg/m3 13.7 (0.7) 130.56 (2.2) 116.8 89.4 1-35 36-150 101.6*** SPM10μg/m3 53.6 (3.0) 332.80 (2.4) 279.1 83.8 1-154 155-354 198.8*** Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001and Inc%: Increasing percentage

During autumn, percentage increase in CO, SO2, NO2, SPM2.5 and SPM10 from polluted areas was recorded to be 59.8, 71.6, 78.9, 89.4 and 83.8 % respectively (Table 3.11). Significant test using t-test revealed that the values of all the parameters were very highly significant (P<0.001) at polluted sites than non-polluted sites. The difference between polluted and control sites were found CO; 6.3, SO2; 25.7, NO2;

84.1, SPM2.5; 116.8 and SPM10; 279.1 top to bottom, respectively. SPM10 was showed the highest difference while CO indicating the least. The concentrations of all gases and particulate matter estimated from polluted sites were more than the permissible limits except SO2 given by WHO, 2006.

Table 3.12: Over all percentage increase in air pollutants in the atmosphere of the Quetta city in comparison to control site and WHO standard during winter season

Pollutants Non- Polluted WHO polluted site site Differe Inc Standard Ave S.D Ave S.D nce % Moderate Harmful t CO ppm 3.2 (0.3) 6.7 (1.1) 3.5 52.3 1-9 10-15 6.1*** *** SO2 ppb 7.9 (1.0) 26.8 (2.9) 18.8 70.2 1-75 76-300 11.4 *** NO2 ppb 13.8 (2.7) 74.6 (17.6) 60.9 81.5 1-100 101-644 6.8 SPM2.5μg/m3 10.5 (0.9) 44.9 (6.4) 34.5 76.9 1-35 36-150 10.6*** SPM10μg/m3 40.4 (10.8) 310.0 (3.0) 269.7 86.9 1-154 155-354 164.1*** Ave: Average, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001and Inc%: Increasing percentage

During winter, the percentage increase in CO, SO2, NO2, SPM2.5 and SPM10 at city area was 52.3, 70.2, 81.5, 76.9 and 86.9 %, respectively (Table 3.12). The t-test revealed that the values of all the parameters were very highly significant (P<0.001) at polluted site as compared to non-polluted sites. The difference between polluted areas and control sites were CO; 3.5, SO2; 18.8, NO2; 60.9, SPM2.5; 34.5 and SPM10;

269.7, respectively. SPM10 was indicating the largest difference and CO showed least difference. The concentration of gases in air was within permissible limits, while the concentrations of particulate matter estimated from polluted sites were more than the permissible limits given by WHO, 2006.

Table 3.13: Range of air pollutants during different seasons of the year (2010 & 2011) in the atmosphere of the Quetta city

Air pollutants Spring Summer Max Min Range Max Min Range CO ppm 7.9 5.7 2.2 10.7 7.6 3.4

SO2 ppb 31.9 17.2 14.8 38.8 26.5 12.8

NO2 ppb 91.2 38.4 52.8 114.4 63.7 50.6 SPM2.5μg/m3 55.8 26.4 29.4 160.6 38.5 122.1 SPM10μg/m3 362.2 234.2 128.0 370.7 247.0 123.7

Max: Maximum and Min: Minimum

The range of air pollutants CO, SO2, NO2, SPM2.5 and SPM10 in the atmosphere of the Quetta city was found to be 2.23 ppm, 14.68ppb, 52.7 ppb, 29.4μg/m3 and 128.0μg/m3 respectively. Minimum and maximum values recorded

during spring season were, CO; 5.7 & 7.9 ppm, SO2; 17.2 & 31.9 ppb, NO2; 38.4 & 3 3 91.2 ppb, SPM2.5; 26.4 & 55.8 μg/m and SPM10; 234.2 & 362.2 μg/m . During

summer range of CO, SO2, NO2, SPM2.5 and SPM10 were found 3.4, 12.8, 50.6, 122.1

and 123.7 respectively. The highest and lowest values of CO; 10.7 & 7.6 ppm, SO2;

38.8 & 26.5, NO2; 114.4 & 63.7, SPM2.5; 160.6 & 38.5 and SPM10; 370.7 & 247.0 were recorded in summer (Table 3.13).

Table 3.14: Range of air pollutants in Quetta city during different seasons of the year (2010 & 2011)

Air pollutants Autumn Winter Max Min Range Max Min Range CO ppm 12.2 8.8 3.9 7.7 5.4 2.3

SO2 ppb 39.2 27.1 12.2 31.6 16.7 14.8

NO2 ppb 122.7 68.4 54.3 88.6 35.3 53.2 SPM2.5μg/m3 164.8 43.2 121.7 52.9 24.2 28.7 SPM10μg/m3 379.2 254 125.2 357.4 231.1 126.3 Max: Maximum and Min: Minimum

Table 3.14 shows that during autumn the range of air pollutants CO, SO2, 3 NO2, SPM2.5 and SPM10 were recorded 3.9 ppm, 12.2 ppb, 54.3 ppb, 121.7 μg/m and 125.2 μg/m3, respectively. Minimum and maximum values were CO; 8.8 & 12.2 ppm,

SO2; 27.1 & 39.2, NO2; 68.4 & 122.7, SPM2.5; 43.2 & 164.8 and SPM10; 254.0 &

379.2. During winter the range was CO; 2.3ppm, SO2; 14.8ppb, NO2; 53.2 ppb, 3 3 SPM2.5; 28.7 μg/m and SPM10; 126.3 μg/m respectively. The lowest and highest

values recorded during winter season were CO; 5.4 & 7.7 ppm, SO2; 16.7 & 31.6 ppb, 3 3 NO2; 35.3 & 88.6 ppb, SPM2.5; 24.2 & 52.9 μg/m and SPM10; 231’1 & 357.4 μg/m .

Table 3.15: Air Quality Index of CO in the atmosphere of Quetta city during different seasons

Sites Season Spring Summer Autumn Winter Average Quetta Cantt 63 M 83 M 89 M 60 M 74 M Hazara Town 69 M 85 M 92 M 66 M 78 M Shabaz Town 69 M 89 M 97 M 66 M 80 M Manan Chowk 73 M 118 Hsg 116 Hsg 71 M 95 M Sariab Road 81 M 100 M 123 Hsg 78 M 96 M Mezan Chowk 67 M 121 Hsg 125 Hsg 73 M 97 M Satellite Town 78 M 108 Hsg 128 Hsg 76 M 98 M Jinnah Road 81 M 111 Hsg 131 Hsg 78 M 101 Hsg Zarghoon Road 80 M 118 Hsg 138 Hsg 77 M 103 Hsg Metha Chowk 83 M 104 Hsg 142 Hsg 80 M 102 Hsg Golimar Chowk 85 M 118 Hsg 147 Hsg 83 M 108 Hsg Mean 76 M 098 M 118 Hsg 74 M 092 M Mean value of Control Site 40 G 052 M 56 M 40 G 047 G

G: Good, M: Moderate, Hsg: Harmful for sensitive group, Ha: Harmful for all, Vh: Very harmful

Over all average AQI of CO during the study period was found in the range of 74 – 108. Seven locations including Quetta Cantt, Hazara Town, Shabaz Town, Manan Chowk, Satellite Town and Sariab road had moderate index. Other remaining four locations Jinnah Road, Zarghoon road, Metha Chowk and Golimar Chowk showed harmful for sensitive group (Table 3.15). The mean values of all the sites during spring, summer and winter were found to be 76, 98 and 74, respectively showing moderate values, while autumn had harmful index for sensitive group (118). However control sites had good (40) AQI during spring and winter, while it was moderate during summer and autumn seasons (50 & 56). The polluted sites of the city indicated AQI in the range of 63 – 85 and 60 – 83 with moderate in spring and winter respectively. The summer and autumn showed with moderate to harmful for sensitive groups (83 – 121 & 89 – 147), respectively.

Table 3.16: Air Quality Index of SO2 ppb in the atmosphere of Quetta city during different seasons

Sites Seasons Spring Summer Autumn Winter Ave Quetta Cantt 24 G 39 G 39 G 24 G 32 G Hazara Town 26 G 41 G 41 G 26 G 34 G Shabaz Town 27 G 40 G 41 G 26 G 34 G Sariab Road 41 G 52 M 54 M 41 G 47 G Manan Chowk 43 G 54 M 54 M 43 G 49 G Mezan Chowk 44 G 54 M 55 M 43 G 49 G Setalite Town 44 G 52 M 55 M 43 G 49 G Jinnah Road 44 G 54 M 55 M 43 G 49 G Zarghoon Road 44 G 54 M 55 M 44 G 50 M Metha Chowk 46 G 54 M 55 M 44 G 50 M Golimar Chowk 46 G 55 M 55 M 46 G 51 M Mean 39 G 50 G 51 M 36 G 44 G Mean value of Control Site 14 G 20 G 23 G 14 G 18 G

G: Good, M: Moderate, Hsg: Harmful for sensitive group, Ha: Harmful for all, Vh: Very harmful

Overall average AQI of SO2 during all four seasons was in the range of 32 – 51. Eight sites Quetta Cantt, Hazara Town, Shabaz Town, Sariab road, Manan Chowk, Mezan Chowk, Satellite Town and Jinnah Road having good (G) index and other remaining three locations (Zarghoon Road, Metha Chowk and Golimar Chowk) showing harmful for sensitive group (Table 3.16). The mean values of all the sites were reported to be 39, 50 and 36, during spring, summer and winter indicating good index (G) respectively, while autumn was (51) harmful for sensitive group (Hsg). However control site showed good AQI in all seasons.

Table 3.17: Air Quality Index of NO2 ppb in the atmosphere of Quetta city during different seasons

Different Sites Seasons Spring Summer Autumn Winter Ave Quetta Cantt 36 G 62 M 66 M 33 G 50 G Hazara Town 49 G 64 M 68 M 47 G 57 M Shabaz Town 50 G 66 M 72 M 48 G 59 M Satellite Town 85 M 103 Hsg 104 Hsg 82 M 94 M Sariab Road 85 M 103 Hsg 104 Hsg 82 M 94 M Manan Chowk 87 M 103 Hsg 104 Hsg 84 M 95 M Jinnah Road 87 M 103 Hsg 104 Hsg 83 M 95 M Mezan Chowk 89 M 103 Hsg 105 Hsg 86 M 96 M Metha Chowk 88 M 103 Hsg 105 Hsg 88 M 96 M Golimar Chowk 88 M 103 Hsg 105 Hsg 86 M 96 M Zarghoon Road 90 M 103 Hsg 105 Hsg 88 M 97 M Mean 76 M 99 M 102 Hsg 73 M 88 M Mean value of Control Site 21 G 28 G 033 G 19 G 26 G

G: Good, M: Moderate, Hsg: Harmful for sensitive group, Ha: Harmful for all, Vh: Very harmful

Table 3.17 shows that overall average AQI of NO2 during all four seasons was found in the range of 50 – 97. Out of eleven locations, ten locations including Hazara Town, Shabaz Town, Sariab road, Manan Chowk, Mezan Chowk, Setalite Town, Jinnah Road Zarghoon road, Metha Chowk and Golimar Chowk was found to be moderate while remaining one Quetta Cantt showed good. The mean values of all the sites were reported as 76, 99 and 73 with moderate in spring, summer and winter respectively, while autumn showed (102) harmful for sensitive group (Hsg). However control site indicated good AQI during all seasons. The different sites of the polluted are as reported good (G) to moderate during spring and winter, while with moderate to harmful for sensitive group in summer and autumn.

Table 3.18: Air Quality Index SPM10 the atmosphere of Quetta city during different seasons

Different Sites Seasons Spring Summer Autumn Winter Ave Quetta Cantt 140 Hsg 147 Hsg 150 Hsg 139 Hsg 144 Hsg Hazara Town 143 Hsg 149 Hsg 153 Ha 141 Hsg 147 Hsg Shabaz Town 146 Hsg 151 Ha 155 Ha 144 Hsg 149 Hsg Manan Chowk 186 Ha 192 Ha 197 Ha 185 Ha 190 Ha Mezan Chowk 189 Ha 194 Ha 198 Ha 187 Ha 192 Ha Jinnah Road 191 Ha 196 Ha 200 Ha 188 Ha 194 Ha Metha Chowk 193 Ha 198 Ha 204 Vh 192 Ha 197 Ha Satellite Town 194 Ha 198 Ha 208 Vh 192 Ha 198 Ha Zarghoon Road 197 Ha 202 Vh 215 Vh 194 Ha 202 Vh Sariab Road 198 Ha 207 Vh 221 Vh 196 Ha 206 Vh Golimar Chowk 211 Vh 223 Vh 235 Vh 204 Vh 219 Vh Mean 180 Ha 185 Ha 190 Ha 178 Ha 183 Ha

Control Site 052 M 059 M 070 M 054 M 059 M

G: Good, M: Moderate, Hsg: Harmful for sensitive group, Ha: Harmful for all, Vh: Very harmful

The overall average AQI of SPM10 during the study period was ranged from 144 – 219. Three locations including Quetta Cantt, Hazara Town and Shabaz Town indicated harmful for sensitive group. Other five locations i.e. Manan Chowk, Mezan Chowk, Jinnah Road Metha Chowk and Satellite Town showed harmful for all the people (Ha) and remaining three sites; Zarghoon road, Sariab road and Golimar Chowk representing very harmful (Vh) to all the people (Table 3.18). The mean values of all the sites were recorded (108, 185, 190 and 178) harmful (Ha) for all the people during all the seasons. The control site indicated moderate AQI during all seasons. The polluted sites were found to be harmful (Hsg) for sensitive group and very harmful (Vh) during all the seasons.

Table 3.19: Air Quality Index of SPM2.5 in the atmosphere of Quetta city during different seasons

Different Sites Seasons Spring Summer Autumn Winter Ave Quetta Cantt 78 M 106 Hsg 113 Hsg 72 M 94 M Hazara Town 90 M 113 Hsg 121 Hsg 82 M 102 Hsg Shabaz Town 98 M 116 Hsg 122 Hsg 89 M 107 Hsg Jinnah Road 130 Hsg 206 Vh 112 Vh 125 Hsg 144 Hsg Sariab Road 127 Hsg 206 Vh 209 Vh 130 Hsg 168 Ha Manan Chowk 130 Hsg 209 Vh 211 Vh 126 Hsg 169 Ha Satellite Town 131 Hsg 206 Vh 211 Vh 126 Hsg 169 Ha Metha Chowk 131 Hsg 208 Vh 213 Vh 126 Hsg 170 Ha Zarghoon Road 132 Hsg 210 Vh 213 Vh 128 Hsg 171 Ha Mezan Chowk 132 Hsg 221 Vh 215 Vh 128 Hsg 174 Ha Golimar Chowk 134 Hsg 221 Vh 215 Vh 130 Hsg 175 Ha Mean 121 Hsg 186 Ha 189 Ha 116 Hsg 153 Ha Mean value of 040 G 049 G 057 M 038 G 046 G Control Site

G: Good, M: Moderate, Hsg: Harmful for sensitive group, Ha: Harmful for all, Vh: Very harmful

Overall average AQI of SPM2.5 during all four seasons was found in the range of 94 – 175 (Table 3.19). Quetta Cantt showed moderate and other three locations Hazara Town, Shabaz Town and Jinnah Road reported harmful for sensitive group. The remaining seven locations i.e. Sariab Road, Manan Chowk, Satellite Town, Metha Chowk, Zarghoon road, Mezan Chowk and Golimar Chowk representing harmful for all the people (Ha). Moreover the mean values of all the sites were found 121, 186, 189, 116, with harmful for sensitive group during spring and winter, while harmful for all the people during summer and autumn season. The control sites showed good AQI during spring, summer and winter and moderate during autumn. Different sites of the polluted areas were found to be moderate to harmful for sensitive group during spring and winter, while harmful for sensitive group and very harmful for all the people during summer and autumn.

Table 3.20: Standard of air pollutants in the atmosphere of urban area of the developing countries (WHO, 2006) Air pollutants Good Modera Harmful V. Harmful Hazar te S. group all population dous CO ppm 1 - 04 05 - 09 010 - 12.44 12.45 - 15 16 – 30 31< SO2 ppb 1 - 35 36 - 75 076 – 185 186 – 300 300< NO2 ppb 1 - 53 54 - 100 101 – 360 361 – 644 645 - 1244 1245< SPM2.5μg/m3 1 - 15 16 - 35 036 – 065 066 - 150 151 - 250 251< SPM10μg/m3 1 - 54 55 - 154 155 – 254 255 - 354 355 - 424 425<

Mod: moderate, S. group: Sensitive group, V. Harmfu: Very Harmful

These are the concentration of pollutants in the air, good quality air should

3 3 have CO: 1-4ppm, SO2: 1-35ppb, NO2: 1-53ppb, SPM2.5μg/m : 1-15 SPM10μg/m :54 as suggested by WHO, 2006. However moderate can also be considered as not harmful for human beings.

Table 3.21: Average number of vehicles’ movement per five minutes at different locations of Quetta city during different seasons (2010 and 2011)

Locations Numbers of Vehicles/5 minute spring summer autumn winter Ave S.D Quetta Cantt 95 100 110 90 98.7 (5.00) Hazara Town 142 150 160 112 141.0 (11.6) Shabaz Town 150 155 163 125 148.2 (9.30) Sariab Road 377 400 410 345 383.0 (17.6) Golimar Chowk 380 400 460 370 402.5 (23.0) Jinnah Road 392 405 462 350 402.2 (25.0) Setalite Town 390 400 460 380 407.5 (21.0) Manan Chowk 400 420 462 375 414.2 (21.4) Metha Chowk 400 420 465 375 415.0 (22.0) Zarghoon Road 442 450 466 410 442.0 (12.8) Mezan Chowk 440 460 485 400 446.2 (21.0) Mean 328 342 373 303 336.4 (16.8) Max 442 460 485 410 446.2 (19.1) Min 095 100 110 090 098.7 (5.0) Range 347 360 375 320 347.5 (14.1)

Ave: Average, S.D: Standard deviation, Max: Maximum, Min: Minimum

Overall average number of vehicles at different locations of the Quetta city during the study period was in the range of 98.75 – 446.25/5minute with Mezan Chowk having the largest number of vehicles and Quetta Cantt showed the least. While mean of the average was 336.4/5minute. During spring 95 – 440/5minute with mean value of 328/5minute, summer season had 100 – 460/5minute with mean value of 342 /5minute, autumn showed 110 – 485/5minute with mean value of 373 /5minute and during winter season only 90 – 400/5 minute vehicles were found with mean value of 303 /5 minute (Table 3.21).

Fig. 3.1: Linear relationship between number of vehicles and CO during spring

Fig. 3.2: Linear relationship between number of vehicles and CO during summer

Fig. 3.3: Linear relationship between number of vehicles and CO during autumn

Fig. 3.4: Linear relationship between number of vehicles and CO during winter

Fig. 3.5: Linear relationship between number of vehicles and SO2 during spring

Fig. 3.6: Linear relationship between number of vehicles and SO2 during summer

Fig. 3.7: Linear relationship between number of vehicles and SO2 during autumn

Fig. 3.8: Linear relationship between number of vehicles and SO2 during winter

Fig. 3.9: Linear relationship between number of vehicles and NO2 during spring

Fig. 3.10: Linear relationship between number of vehicles and NO2 during summer

Fig. 3.11: Linear relationship between number of vehicles and NO2 during autumn

Fig. 3.12: Linear relationship between number of vehicles and NO2ppb during winter

Fig. 3.13: Linear relationship between number of vehicles and SPM10 during spring

Fig. 3.14: Linear relationship between number of vehicles and SPM10 during summer

Fig. 3.15: Linear relationship between number of vehicles and SPM10 during autumn

Fig. 3.16: Linear relationship between number of vehicles and SPM10 during winter

Fig. 3.17: Linear relationship between number of vehicles and SPM2.5 during spring

Fig. 3.18: Linear relationship between number of vehicles and SPM2.5 during summer

Fig. 3.19: Linear relationship between number of vehicles and SPM2.5 during autumn

Fig. 3.20: Linear relationship between number of vehicles and SPM2.5 during winter

Results presented in Figures 3.1 – 3.20, shows leaner relationship of traffic with air pollutants. The air pollutants investigated (CO, SO2, NO2, SPM10 and SPM2.5 in the atmosphere of Quetta city had highly positive linear correlation with the number of vehicles moving on the roads during spring, summer, autumn and winter seasons. The contents of CO, SO2, NO2, SPM10 and SPM2.5 increased with the increased of the numbers of vehicles. The number of vehicles and all the air pollutants gradually increased from spring to summer and reached its maximum in autumn season and minimum was found during winter season.

Table 3.22: Correlation co-efficient between the number of Vehicles and air pollutant in the atmosphere of Quetta city

Air pollutants Number of vehicles’ movement Spring Summer Autumn Winter CO ppm 0.82*** 0.95*** 0.92*** 0.83*** *** *** *** *** SO2 ppb 0.98 0.99 0.99 0.98 *** *** *** *** NO2 ppb 0.99 0.94 0.99 0.98 SPM 2.5 μg/m3 0.98*** 0.98*** 0.99*** 0.99*** SPM 10 μg/m3 0.96*** 0.95*** 0.96*** 0.96***

Table 3.22 indicated that correlation co-efficient between the number of vehicles moving/5minute on different roads of Quetta city and air pollutants (CO,

SO2, NO2, SPM10, SPM2.5) in the atmosphere of Quetta city. The results exhibited that there was highly significant correlation between number of vehicles and air pollutants during all the seasons.

Table 3.23: Correlation co-efficient among the air pollutants of Quetta city

3 Air pollutants NO2 ppb SO2 ppb CO ppm SPM10μg/m SPM2.5μg/ m3

NO2 ppb 1 *** SO2 ppb 0.99 1 CO ppm 0.99*** 0.96*** 1 SPM10μg/m3 0.98*** 0.95*** 0.99*** 1 SPM2.5μg/m3 0.98*** 0.99*** 0.96*** 0.94*** 1

Data regarding relationship with in the investigated air pollutants like CO,

SO2, NO2, SPM10 and SPM2.5 (Table 3.23) revealed that there was very highly significant relation among all the air pollutants in the atmosphere of Quetta city.

3.4. DISCUSSION

The air quality parameters recorded from Quetta city, Balochistan provided a clear picture of the air quality. Quetta city is a cup like valley where these gases and dust particles remain suspended in the air which reduces visibility and a thick cloud like layer can be seen while flying over the city.

3.4.1. Carbon Monoxide (CO): The results reflected that the contents of CO started increasing from spring to summer and reached to its maximum during autumn and minimum during winter at both polluted and non-polluted sites. Similar observations were also noticed by Beg et al., (1987) and Saha and Padhy, (2011). Statistical analysis revealed that there was slightly to highly significant variation between the values of polluted and non-polluted sites during all the seasons at P<0.05 and 0.01 significant level. The high contents at polluted sites might be due to the exhaust from vehicles and other incomplete combustion of various fuels such as wood, coal, charcoal, oil, paraffin, propane, natural gas, and trash. The control site having good AQI of CO during spring and winter, but became moderate during summer and autumn. The present results are also supported by Yousufzai et al., (1970, 1984 & 1987) and Chotani et al., (1975) while working on the atmosphere of Karachi. The concentration of CO in the air of Quetta city including both from polluted and non polluted sites was within the permissible limits, while it was more during autumn when compared to WHO standards for developing countries.

3.4.2. Sulfur dioxide (SO2): Statistical analysis indicated that there was slightly to highly significant high contents of SO2 at polluted site then non-polluted sites during all the seasons at P<0.05 and 0.01 significant level. High contents in the urban area might be due to different reasons like burning of coal and fuel oil, vehicle tires and rubbers etc. Therefore, it is assumed that the toxic gases in the ambient air like CO,

NO, NO2 and SO2 are result of vehicular emissions. Agbaire and Esiefarienrhi, (2009) and Joshi et al., (2009) also found similar results. They indicated that all the combustion release gases and particles into the air. Seasonally SO2 contents started slight increase from spring to summer and reached to its maximum during autumn and minimum during winter at both polluted and non-polluted sites, which are highly significantly correlated with traffic density during all the seasons. Similar observations were also reported by Kozak et al., (1993) and Tiwari et al., (2006), they

82 studied the concentration of atmospheric SO2, NO2, and dust. They found high contents of SO2, NO2, and dust in the urban atmosphere and also found maximum during autumn and minimum during winter. Over all mean AQI of SO2 at all the investigated locations was found good during spring, summer and winter respectively. While during autumn it became moderate. At control sites it remained good during all the seasons. SO2 recorded was in permissible limits of WHO, 2006 and are not dangerous for health.

3.4.3. Nitrogen dioxide (NO2): Statistical analysis using t-test exhibited that there was slightly to highly significant high concentration of NO2 at polluted site then non- polluted site during all the seasons at P<0.05 and 0.01 significant level. The high contents of NO2 in the urban area Quetta city might be due to following reasons like motor vehicles, bomb blasts, gas heaters and stoves. This idea was also supported by Agbaire and Esiefarienrhi, (2009) and Joshi et al., (2009). Results also indicate that

NO2 contents started slightly increase from spring to summer and reached maximum during autumn and minimum during winter, that were highly correlated with traffic density on the road of the city. Similar observations were also noticed by Kozak et al., (1993) and Tiwari et al., (2006). AQI of NO2 at all the sites was reported moderate during spring, summer and winter respectively, while autumn showed harmful for sensitive group (Hsg). The concentrations of NO2 estimated from polluted sites were within the permissible limits except in autumn season when compared with WHO, 2006, standards.

3 3.4.4. SPM10μg/m : Percentage increases of SPM10 at the polluted sites as compare to non-polluted sites were significant high. Statistical analysis revealed that the values of SPM10μg/m3 were highly significant from polluted sites then non-polluted sites at P<0.01 significant level during all the seasons. Patil, (2001) concluded that the SPM in the ambient air at crusher sites ranged from 2340-24000 μg/m3, which is substantially higher than the desirable limits. High contents in the urban area might be due to motor vehicles, road and building construction and dust storms etc. this idea was also supported by Agbaire and Esiefarienrhi, (2009) and Joshi et al., (2009) they indicated that all the combustion release gases and particles in to the air. Seasonally observation indicated that there was variation from season to season, autumn scored highest amount and winter having least at both sites (polluted and non-polluted), this might be due to variation in traffic density which is low in

83 winter season. Further that many other factors including wind speed and precipitation also influence the particulate deposition on plant leaves and soil. Similar observations were made by Agarwal et al., (1999) and Saha and Padhy, (2011), they reported that Indian cities are facing serious problems of air borne particulate matter. Kozak et al., (1993) and Tiwari et al., (2006) also reported similar results. AQI of SPM10 was found harmful for all the people during all the seasons that were highly significant high then control sites. Very high index at polluted sites might be due to large number of vehicles, dust storms, lack of cleanliness, road building construction etc. Similar results were also reported by Cacciola et al., (2002) they reported that United Nations estimated that over 600 million people in urban areas worldwide were exposed to dangerous levels of traffic-generated air particulates. More over Borja-Aburto et al., (1998), NEPC, (1998) and Schwartz et al., (1996), indicated that the atmospheric particulate matter (PM) with aerodynamic diameter <10 µm (PM10) or <2.5µm (PM2.5) are of considerable concern for public health. The concentrations of particulate matter estimated from polluted sites were extremely high when compared to the permissible limits given by WHO, 2006. 3.4.5. SPM2.5μg/m3: Statistical analysis revealed that the values of SPM2.5μg/m3 were highly significant at polluted site then non-polluted site at P<0.01 significant level during all the seasons. High contents in the city area might be due to different reasons like motor vehicles emissions, road and building construction and dust storms etc. The above views were also supported by Agbaire and Esiefarienrhi, (2009) and

Joshi et al., (2009). SPM2.5 contents at polluted site started increased during spring to summer and reached to maximum in autumn while winterhad the minimum concentration. The observations reported by Agrawal, et al., (1999), Kozak et al., (1993) and Tiwari et al., (2006) also similar. AQI at all the locations was found harmful for sensitive group during spring and winter, while during summer and autumn it was harmful for all the people. Similar results were also reported by Cacciola et al., (2002). Borja-Aburto et al., (1998), Moreover NEPC, (1998) and Schwartz et al., (1996) reported that the atmospheric particulate matter (PM) with aerodynamic diameter <10 µm (PM10) or <2.5µm (PM2.5) are of considerable concern for public health. The concentrations of this particulate matter estimated from polluted sites were more than the WHO’s permissible limits in all seasons except during spring.

3.5. CONCLUSIONS On the basis of this study following conclusions were made;

The atmosphere of Quetta city is highly polluted due to CO, NO2, SPM10μm and SPM2.5μm throughout the year. CO concentration remained moderate to harmful for the people of sensitive group in city areas. SO2 concentration was found to be good to moderate but significantly more than control sites. NO2 concentration was reported to be moderate to harmful for the people of sensitive group. SPM10μm concentration falls in the categories of very harmful for all the population. SPM2.5μm concentration is also considered very harmful for all the population. Through the results of the study a very clear picture of levels of pollution in Quetta city has come up. These results could be utilized for minimizing the air pollution. Therefore it is concluded that the air quality of Quetta city is on the path of degradation and has bad affects on humans, animals and plants health.

Chapter 4

HEAVY METALS CONTAMINATION AND THEIR SEASONAL VARIATION IN DIFFERENT PLANT SPECIES COLLECTED FROM URBAN AREA OF QUETTA CITY

4.1. INTRODUCTION

Due to the increasing level of environmental pollution, heavy metals can be accumulated on plant leaves and on soil, which will increase potential risks to environment and population, both vegetation and human health (Raghunath et al., 1999 and Cohen et al., 2001). Generally, heavy metals absorption by plants is governed by soil characteristics such as pH and organic matter content (Csintalan and Tuba, 1992) but high levels of heavy metals in plants do not always correlate with the high concentrations found in soil, where they grows. The extent of accumulation of heavy metals and toxic level may also depend on the plant and heavy metals and their environmental conditions under which they are investigated. The uptake of elements from soil by plants as phytoremediation, an investigation of Zn, Cd, Cu, Ni and Pb uptake from air and soil by Achillea millefolium (Milfoil) and Hordeum vulgare (barley) in Denmark concluded that Cu and Pb concentrations in plant correlate with aerial deposition but not with soil concentration. In contrast, Ni and Cd content in the plants correlate with deposition and soil content (Pilegaard & Johnsen, 1984; Truby, 1995). High contents of heavy metals in plants may have adverse effect on many plant parameters likes stem, leaf and root growth, flowering/fruiting formation, biomass, photosynthesis, transpiration, mineral nutrition and their secondary metabolites etc. (Breckle & Kahle, 1992). The toxic levels of some heavy metals in air and soil are just above the concentrations found naturally. Therefore, it is necessary to take protective measures against excessive exposure toward them. Further, heavy metal determination in the environmental samples such as air, soils and plants is also very necessary for monitoring the environmental pollution (Zhou et al., 1997; Tuzen, 2003 and Al-Khashman, 2007). The purpose of this study is to assess the heavy metals concentration (Cu, Zn, Fe, Ni, Pb, Sb and Cd) and pollution levels in leaves of plants growing along the road side of Quetta city and to make a comparison with control site and to monitor their seasonal variation.

4.2. MATERIAL AND METHODS

4.2.1. Collection of soil and leaf samples: The study was carried out during 2010- 2011. Soil and leaf samples of 13 different plant species viz. Rosa indica L., Robinia pseudoacacia L. Melia azadirach L., Vitis vinifera L., Ficus carica L., Morus nigra L., Elaeagnus angustifolia L., Pistacia vera L., Fraxinus excelsior L., Eucalyptus tereticornis L., Morus alba L., Punica granatum L. and Pinus halepensis Miller. of trees, shrubs and climbers were collected under iso-ecological conditions (light, water and soil) by standardized methods (Krstić & Stanković, 2006) from Quetta city (Polluted site), Botanical garden and University of Balochistan Campus Quetta (non- polluted site). The samples were labeled and brought to the laboratory in polythene bags and then processed for different parameters.

4.2.2. Heavy metals analyses of plant samples: One gram samples of dried plant leaves were ashed in a furnace at 460oC for 24 hours. The weighed ash was then digested in concentrated HNO3 and evaporated to near dryness on a hot-plate.

Digested samples were then centrifuged, and make up to volume with 1% HNO3 following the procedure as described by previous researchers (AL-Shayed et al., 1995). The concentrations of each of the heavy metal i.e., Pb, Zn, Fe, Cu, Cd and Sb in leaf samples were then separately measured by using an atomic absorption spectrophotometer (Perkin Elmer model 1100).

4.2.3. Heavy metals analyses of soil samples: One gram samples of dried and sieved soil materials were ashed in a Furnace at 460oC for 24 hours. The weighed ash was then digested in 10 ml Aqua Regia (1 part concentrated HNO3 to 3 parts HCl) in a digestion tube on the heating block for a total of 9 hours, in the following sequence and duration of temperatures: two hours each at 25oC, 60oC and 105oC and finally three hours at 125oC. All digested samples were finally centrifuged, then made up to volume with 1% HNO3. After that the concentrations of the heavy metals viz. Pb, Zn, Fe, Cu, Cd and Sb were measured by using an atomic absorption Spectrophotometer (Perkin Elmer model 1100) as advised by other scientists (Berrow & Ure, 1981; Paveley & Davies, 1988).

4.2.4. Statistical analyses: The standard deviation values of the means were calculated for a comparison of site categories. To determine the significance of the samples a paired t-test was performed, comparing heavy metal contents of polluted

87 and non-polluted sites during different seasons. Significance of comparison of means was also determined by using F-test. Relationships between variables were assessed using correlation coefficient (Steel & Torrie, 1980). Percentage of heavy metals increasing in leaves collected from city area (polluted site) with respect to control site was calculated according to the formula used by Syed and Iqbal, (2008).

Percentage increasing (%) = (MHP- MHNP) 100 MHP

Where, M: Mean value, H: heavy metals in leaves, P: Polluted site and NP: non- polluted sites.

4.3. RESULTS

Table 4.1: Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Spring season Np S. D P S. D Inc % t Rosa indica L. 3.4 (0.21) 13.5 (0.18) 74.6 8.0** Eucalyptus tereticornis L. 4.6 (0.36) 14.7 (0.16) 68.7 6.7** Robinia pseudoacacia L. 5.5 (0.18) 15.5 (0.21) 64.6 9.2** Fraxinus excelsior L. 5.6 (0.21) 15.6 (0.14) 64.3 7.3** Punica granatum L. 5.7 (0.39) 15.8 (0.21) 63.8 7.4** Melia azadirach L. 5.8 (0.31) 15.8 (0.12) 63.0 4.2** Elaeagnus angustifolia L. 6.0 (0.32) 15.9 (0.18) 62.6 9.4** Pinus halepensis Miller. 6.5 (0.21) 16.6 (0.27) 60.7 4.8** Morus alba L. 6.6 (0.19) 16.6 (0.30) 60.3 9.0** Morus nigra L. 6.6 (0.19) 16.6 (0.39) 60.3 7.3** Pistacia vera L. 6.7 (0.06) 16.7 (0.38) 59.7 7.5** Vitis vinifera L. 7.6 (0.16) 17.6 (0.27) 56.9 7.9** Ficus carica L. 9.0 (0.31) 19.0 (0.21) 52.5 9.1** F 5.24*

Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant, F: Calculated values in F-test and Inc%: Increasing %

During spring the percentage increased of Pb in polluted site plant species was in the range of 52.5 – 74.6 %, (Table 4.1), with Rosa indica having the highest increase and Ficus carica showed the least. Test statistics using t-test indicated that all the plant species showed highly significant (p<0.01) variation between the values of polluted and non-polluted sites during spring. F-test revealed that there was slightly significant variation between the mean value of polluted and non-polluted sites at 5% significant level.

Table 4.2: Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plants Summer season Np S. D P S. D Inc % t Rosa indica L. 5.5 (0.29) 20.5 (0.31) 73.3 4.19** Eucalyptus tereticornis L. 6.7 (0.34) 24.6 (0.30) 72.9 2.81* Morus alba L. 8.1 (1.02) 27.8 (0.35) 71.1 5.87** Fraxinus excelsior L. 7.6 (0.21) 25.9 (0.43) 70.5 3.22* Robinia pseudoacacia L. 7.6 (0.20) 25.5 (0.20) 70.1 4.29** Pistacia vera L. 8.6 (0.13) 28.6 (0.29) 69.9 4.19** Punica granatum L. 7.8 (0.29) 25.9 (0.32) 69.8 4.39** Melia azadirach L. 7.7 (0.47) 25.6 (0.20) 69.8 4.63** Morus nigra L. 8.5 (0.26) 27.8 (0.57) 69.4 7.36** Elaeagnus angustifolia L. 7.9 (0.46) 25.8 (0.37) 69.2 8.04** Vitis vinifera L. 9.5 (0.33) 30.6 (0.22) 68.8 7.87** Pinus halepensis Miller. 8.5 (0.40) 26.3 (0.20) 67.5 9.88** Ficus carica L. 10.4 (0.39) 30.7 (0.50) 66.0 6.58** F 4.79*

During summer the percentage increase of Pb in polluted site plant species was recorded in the range of 66.0 – 73.3%, (Table 4.2). Rosa indica indicating largest increase and Ficus carica showed the smallest. Significant test using t-test indicated that 02 plant species i.e. Fraxinus excelsior and Eucalyptus tereticornis showed slightly significant variation (p<0.05) in their Pb concentration, and all the other remaining species indicated highly significant variation (p<0.01) in their values during summer. F-test exhibited that there was slightly significant difference between the mean value of polluted and non-polluted sites plant species at 5% significant level.

Table 4.3: Comparison of average concentration of Lead (Pb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season

Name of plants Autumn season Np S. D P S. D Inc % T Rosa indica L. 5.6 (0.32) 22.6 (0.36) 75.3 4.47** Eucalyptus tereticornis L. 6.9 (0.24) 26.6 (0.25) 74.2 6.15** Robinia pseudoacacia L. 7.6 (0.49) 27.4 (0.19) 72.4 3.20* Fraxinus excelsior L. 7.7 (0.45) 27.8 (0.43) 72.3 5.90** Melia azadirach L. 7.6 (0.60) 27.5 (0.20) 72.2 7.01** Elaeagnus angustifolia L. 7.7 (0.44) 27.8 (0.41) 72.2 5.27** Vitis vinifera L. 9.6 (0.58) 32.9 (0.41) 70.9 5.76** Pistacia vera L. 9.0 (0.19) 30.6 (0.15) 70.8 9.78** Morus nigra L. 8.7 (0.50) 29.8 (0.33) 70.7 4.41** Morus alba L. 8.8 (0.52) 29.8 (0.50) 70.4 9.02** Punica granatum L. 8.4 (0.42) 27.8 (0.31) 69.7 3.41* Pinus halepensis Miller. 9.0 (0.53) 28.2 (0.21) 68.1 5.14** Ficus carica L. 11.2 (0.35) 33.1 (0.54) 66.2 5.09** F 4.04*

During autumn, the increased percentage of Pb in polluted site plant species was found in the range of 66.2–75.3 % (Table 4.3) with Rosa indica had the largest increasing percentage and Ficus carica showed the least. Significant test using t-test indicated that out of 13 plant species 02 species viz. Robinia pseudoacacia and Punica granatum showed slightly significant variation (P<0.05) in their Pb contents. All the other remaining species indicated highly significant (P<0.01) variation in their values during autumn as compared to non-polluted site. F-test exhibited that there was slightly significant difference between the mean value of polluted and non- polluted sites at 5% significant level.

Table 4.4: Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Spring season Np S. D P S. D Inc % t Eucalyptus tereticornis L. 2.4 (0.1) 10.0 (0.2) 60.0 7.81** Rosa indica L. 3.3 (0.4) 7.4 (0.1) 55.3 5.23** Melia azadirach L. 4.4 (0.2) 11.5 (0.2) 41.1 4.73** Fraxinus excelsior L. 7.4 (0.2) 10.7 (0.2) 31.1 5.27** Morus alba L. 15.4 (0.2) 20.6 (0.2) 25.2 6.94** Vitis vinifera L. 25.1 (0.8) 33.5 (0.3) 25.1 5.82** Pinus halepensis Miller. 13.2 (0.1) 18.3 (0.2) 23.4 7.51** Pistacia vera L. 10.1 (0.2) 14.4 (0.2) 23.2 2.96* Robinia pseudoacacia L. 15.5 (0.1) 19.7 (0.2) 21.1 3.69* Elaeagnus angustifolia L. 15.5 (0.1) 19.6 (0.2) 21.0 3.32* Morus nigra L. 20.5 (0.3) 25.7 (0.3) 20.3 3.15* Punica granatum L. 15.3 (0.1) 18.5 (0.3) 17.2 4.13** Ficus carica L. 30.5 (0.2) 34.5 (0.3) 11.8 5.62** F 2.92ns

During spring, the percentage increase of Zn in plant species of polluted site was in the range of 11.8 – 60.0 % (Table 4.4) with Eucalyptus tereticornis had the largest increase and Ficus carica showed the least. Statistical test (t-test) revealed that out of 13 plant species 04 plants i.e. Pistacia vera, Morus nigra, Elaeagnus angustifolia and Robinia pseudoacacia showed slightly significant difference in their Zn contents at P<0.05 as compared to non-polluted sites. All the other species including, Eucalyptus tereticornis, Rosa indica, Melia azadirach, Fraxinus excelsior, Morus alba, Vitis vinifera, Pinus halepensis, Punica granatum and Ficus carica indicated highly significant variation (P< 0.01) in their values during spring. F-test, of the mean values exhibited that there was non-significant difference between polluted and non-polluted sites at 5% significant level.

Table 4.5: Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plants Summer season Np S. D P S. D Inc % T Rosa indica L. 4.4 (0.24) 8.5 (0.37) 48.2 8.32** Eucalyptus tereticornis L. 5.1 (0.10) 9.0 (0.20) 43.0 3.95** Fraxinus excelsior L. 9.3 (0.20) 13.6 (0.32) 31.5 4.06** Melia azadirach L. 7.5 (0.24) 10.6 (0.24) 29.1 9.38** Robinia pseudoacacia L. 19.4 (0.15) 23.6 (0.19) 18.0 6.93** Pistacia vera L. 12.6 (0.21) 15.4 (0.14) 17.9 4.49** Morus nigra L. 24.4 (0.26) 28.6 (0.34) 14.6 7.12** Punica granatum L. 18.6 (0.13) 21.5 (0.30) 13.5 5.79** Pinus halepensis Miller. 16.7 (0.15) 19.3 (0.23) 13.4 8.07** Morus alba L. 20.6 (0.23) 23.6 (0.20) 12.6 7.17** Elaeagnus angustifolia L. 18.5 (0.05) 20.7 (0.17) 10.6 3.02* Ficus carica L. 33.7 (0.21) 37.5 (0.31) 10.2 5.76** Vitis vinifera L. 33.2 (0.19) 36.5 (0.28) 09.1 7.13** F 3.08ns

During summer, the percentage increase of Zn in polluted site plant species was found in the range of 9.1– 48.2 % (shown in Table 4.5) with Rosa indica having the highest increase and Vitis vinifera showed the least. Statistical analysis (t-test indicated that Elaeagnus angustifolia showed slightly significant variation in their Zn contents at P<0.05. All the other species from polluted sites showed highly significant (P<0.01) differences in their values during summer. F-test exhibited that there was non-significant difference between the mean value of polluted and non-polluted sites plant species at 5% significant level.

Table 4.6: Comparison of average concentration of Zinc (Zn μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season

Name of plants Autumn season Np S. D P S. D Inc % t Eucalyptus tereticornis L. 7.4 (0.10) 12.9 (0.26) 42.7 4.18** Rosa indica L. 7.4 (0.21) 12.3 (0.15) 39.6 5.12** Melia azadirach L. 9.3 (0.21) 14.5 (0.24) 35.6 9.08** Fraxinus excelsior L. 11.4 (0.20) 17.5 (0.28) 34.9 6.90** Robinia pseudoacacia L. 20.3 (0.25) 27.5 (0.25) 26.1 3.78** Pistacia vera L. 14.6 (0.20) 19.4 (0.22) 24.9 9.25** Pinus halepensis Miller. 18.6 (0.18) 24.6 (0.30) 24.2 7.92** Punica granatum L. 20.4 (0.17) 25.5 (0.37) 19.7 2.93* Morus nigra L. 26.2 (0.10) 32.5 (0.32) 19.4 5.28** Morus alba L. 22.5 (0.29) 27.6 (0.32) 18.2 3.71* Ficus carica L. 34.1 (0.06) 41.4 (0.11) 17.5 5.32** Vitis vinifera L. 34.1 (0.05) 40.4 (0.10) 15.5 6.82** Elaeagnus angustifolia L. 20.7 (0.20) 24.5 (0.34) 15.4 7.46** F 3.10ns

During autumn, the percentage increase of Zn was in the range of 15.4 – 42.7 % (Table 4.6) with Eucalyptus tereticornis having the largest increased and Elaeagnus angustifolia showed the least. The t-test indicated that out of 13 plant species from polluted sites, Punica granatum and Morus alba showed slightly significant differences in their Zn concentration than non-polluted site at P<0.05. All the other were highly significant at P<0.01. Where as the F-test exhibited that there was non-significantly difference between the mean value of polluted and non-polluted sites at 5% significant level.

Table 4.7: Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plant Spring season A S. D B S. D Inc % t Eucalyptus tereticornis L. 7.9 (0.12) 15.3 (0.02) 48.5 9.88** Rosa indica L. 7.4 (0.12) 14.2 (0.10) 48.2 4.11** Melia azadirach L. 6.7 (0.07) 12.7 (0.12) 45.0 5.29** Fraxinus excelsior L. 12.6 (0.08) 23.2 (0.03) 45.8 7.83** Pistacia vera L. 16.4 (0.08) 26.3 (0.02) 37.7 7.76** Pinus halepensis Miller. 17.3 (0.08) 27.3 (0.08) 36.8 2.62* Robinia pseudoacacia L. 21.6 (0.06) 33.4 (0.16) 35.5 7.07** Punica granatum L. 20.7 (0.09) 31.1 (0.02) 33.5 9.19** Morus alba L. 22.3 (0.08) 33.5 (0.02) 33.2 5.01** Elaeagnus angustifolia L. 21.4 (0.04) 31.2 (0.06) 31.6 4.49** Morus nigra L. 27.5 (0.19) 35.3 (0.04) 22.1 6.06** Ficus carica L. 39.5 (0.12) 50.2 (0.10) 21.7 6.53** Vitis vinifera L. 36.4 (0.08) 45.5 (0.20) 19.9 5.25** F 3.24ns

During spring, the increased percentage of Fe in polluted site plant species was in the range of 19.9 – 48.5 % (Table 4.7). The Eucalyptus tereticornis had the maximum increasing percentage, while Vitis vinifera showed the least. Statistical test (t-test) revealed that Pinus halepensis of polluted site showed slightly significant difference in their Fe contents at P<0.05. All the other species revealed highly significant (P<0.01) variation in their values during spring. F-test exhibited that there was non-significant difference between the mean value of polluted and non-polluted sites plant species at 5% significant level.

Table 4.8: Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plant Summer season Np S. D P S. D Inc % t Eucalyptus tereticornis L. 8.4 (0.22) 18.3 (0.04) 54.0 5.33** Melia azadirach L. 7.6 (0.04) 15.9 (0.04) 52.4 4.22** Rosa indica L. 8.2 (0.12) 17.3 (0.07) 52.3 7.60** Fraxinus excelsior L. 13.4 (0.16) 26.5 (0.04) 49.3 7.48** Pistacia vera L. 17.8 (0.54) 30.3 (0.03) 41.3 4.39** Punica granatum L. 21.2 (0.16) 35.3 (0.11) 39.9 7.85** Pinus halepensis Miller. 18.3 (0.07) 30.2 (0.08) 39.4 4.63** Robinia pseudoacacia L. 22.3 (0.03) 36.3 (0.12) 38.6 7.28** Morus alba L. 23.3 (0.04) 37.4 (0.04) 37.6 6.19** Elaeagnus angustifolia L. 22.6 (0.46) 34.2 (0.08) 34.0 6.89** Morus nigra L. 27.9 (0.42) 39.4 (0.11) 29.2 7.39** Ficus carica L. 41.2 (0.08) 55.3 (0.08) 25.6 3.45* Vitis vinifera L. 38.3 (0.06) 50.1 (0.08) 24.0 3.20* F 3.14ns

During summer, the percentage increase of Fe in polluted site plant species recoded was 24.0–54.0 % (as illustrated in Table 4.8) with Eucalyptus tereticornis indicating the maximum increasing percentage and Vitis vinifera showed the minimum. Statistical test (t-test) exhibited that out of 13 plant species Ficus carica and Vitis vinifera showed slightly significant variation in their Fe contents at p<0.05 significant level between polluted and non-polluted sites. All the other species showed highly significant differences (p<0.01) in their values during summer. F-test revealed that there was non-significant difference between the mean value of polluted and non-polluted sites plant species at 5%.

Table 4.9: Comparison of average concentration of Iron (Fe μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season

Name of plants Autumn season Np S. D P S. D Inc % t Rosa indica L. 10.3 (0.17) 23.0 (0.61) 55.4 8.69** Eucalyptus tereticornis L. 10.5 (0.15) 22.5 (0.13) 53.5 7.00** Melia azadirach L. 09.7 (0.47) 20.7 (0.30) 53.0 5.78** Fraxinus excelsior L. 15.4 (0.17) 30.5 (0.16) 49.3 5.89** Punica granatum L. 22.4 (0.23) 40.4 (0.14) 44.6 3.91** Pistacia vera L. 19.7 (0.75) 35.4 (0.07) 44.3 3.61* Robinia pseudoacacia L. 24.5 (0.13) 42.5 (0.12) 42.4 9.28** Pinus halepensis Miller. 20.5 (0.13) 34.5 (0.06) 40.5 9.77** Morus alba L. 25.4 (0.13) 42.4 (0.06) 40.1 4.02** Elaeagnus angustifolia L. 25.4 (1.05) 38.8 (0.34) 34.6 3.35* Morus nigra L. 30.9 (0.53) 44.0 (0.42) 29.8 6.72** Vitis vinifera L. 40.0 (0.71) 56.7 (0.33) 29.4 3.84** Ficus carica L. 43.4 (0.13) 60.7 (0.38) 28.6 4.05** F 3.67* Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant, F: Calculated values in F-test and Inc%: Increasing %

During autumn, the increased percentage of Fe in polluted site plant species was in the range of 28.6–55.4 % (Table 4.9) with Rosa indica having the largest increase and Ficus carica L. indicating the smallest. Statistical analysis using t-test exhibited that out of 13 plant species Pistacia vera and Elaeagnus angustifolia showed slightly significant variation in their Fe concentration as compared to non- polluted site at p<0.05. All the other species indicated highly significant (p<0.01) difference in their values during autumn. F-test exhibited that there was also slightly significant variation between the mean value of polluted and non-polluted sites plant species at 5% significant level.

Table 4.10: Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Spring season Np S. D P S. D Inc % t Elaeagnus angustifolia L. 8.4 (0.03) 15.2 (0.05) 44.7 3.10* Eucalyptus tereticornis L. 6.5 (0.08) 11.4 (0.05) 43.2 7.48** Morus alba L. 8.2 (0.04) 14.4 (0.11) 42.9 8.19** Morus nigra L. 8.2 (0.03) 14.3 (0.10) 42.5 5.55** Fraxinus excelsior L. 6.1 (0.03) 10.5 (0.13) 41.8 5.66** Robinia pseudoacacia L. 6.4 (0.04) 10.5 (0.12) 39.5 4.78** Melia azadirach L. 6.3 (0.04) 10.3 (0.07) 39.2 8.61** Vitis vinifera L. 8.2 (0.11) 13.4 (0.09) 38.8 3.39* Ficus carica L. 11.5 (0.14) 17.5 (0.10) 38.5 4.24** Rosa indica L. 5.2 (0.06) 8.3 (0.05) 37.3 3.27* Pistacia vera L. 9.1 (0.06) 13.2 (0.05) 30.8 7.88** Pinus halepensis Miller. 10.3 (0.03) 13.2 (0.23) 22.0 2.42* Punica granatum L. 10.1 (0.03) 12.2 (0.12) 16.9 7.04** F 3.06ns

During spring, the percentage increase of Cu in polluted site plant species was in the range of 16.9 – 44.7% (Table 4.10) with Elaeagnus angustifolia showed the highest increase and Punica granatum indicated the least. Statistical analysis using t- test indicated that 4 plant species Elaeagnus angustifolia, Vitis vinifera, Rosa indica and Pinus halepensis showed slightly significant variation in their Fe contents at p<0.05 significant level between polluted and non-polluted sites. All the other species had highly significant (p<0.01) difference in the values during spring, while F-test exhibited that there was non-significant variation between the mean value of polluted and non-polluted sites plant species at 5%.

Table 4.11: Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plants Summer season Np S. D P S. D Inc % t Rosa indica L. 5.6 (0.15) 10.6 (0.05) 46.6 7.60** Fraxinus excelsior L. 6.4 (0.25) 11.7 (0.17) 44.8 7.48** Elaeagnus angustifolia L. 8.9 (0.42) 16.0 (0.58) 44.2 6.89** Eucalyptus tereticornis L. 7.0 (0.48) 12.5 (0.21) 43.9 5.33** Robinia pseudoacacia L. 6.6 (0.21) 11.7 (0.20) 43.2 7.28** Morus alba L. 8.5 (0.44) 14.9 (0.46) 42.9 6.19** Melia azadirach L. 6.8 (0.36) 11.9 (0.27) 42.6 4.22** Morus nigra L. 9.3 (0.14) 15.0 (0.57) 38.2 7.39** Ficus carica L. 12.0 (0.34) 20.6 (0.39) 37.7 3.45* Vitis vinifera L. 8.7 (0.34) 13.8 (0.25) 36.8 3.20* Pistacia vera L. 10.3 (0.13) 14.6 (0.16) 29.2 4.39** Pinus halepensis Miller. 10.3 (0.03) 13.5 (0.09) 23.2 4.63** Punica granatum L. 10.5 (0.28) 13.2 (0.07) 20.6 7.85** F 3.03ns

During summer, the percentage increase of Cu in polluted site plant species was in the range of 20.6 – 46.6 % (shown in Table 4.11) with Rosa indica had highest increase and Punica granatum showed the least. Statistical analysis using t-test indicated that out of 13 plant species 2 plants; Ficus carica and Vitis vinifera had slightly significant variation in their Cu concentration at p< 0.05 significant level. All the other species showed highly significant difference in their values during summer at p<0.01 while F-test exhibited that there was non-significant variation between the mean value of polluted and non-polluted sites plant species at 5% significant level.

Table 4.12: Comparison of average concentration of Copper (Cu μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season

Name of plants Autumn season NP S. D P S. D Inc % t Rosa indica L. 5.8 (0.32) 11.0 (0.15) 47.0 3.19** Elaeagnus angustifolia L. 9.0 (0.37) 16.3 (0.51) 44.8 8.24** Eucalyptus tereticornis L. 7.0 (0.38) 12.8 (0.12) 44.8 3.49* Fraxinus excelsior L. 6.7 (0.06) 12.0 (0.26) 44.2 9.86** Melia azadirach L. 6.8 (0.05) 12.1 (0.25) 43.9 7.84** Morus alba L. 8.6 (0.43) 15.2 (0.30) 43.4 5.77** Robinia pseudoacacia L. 6.9 (0.37) 12.0 (0.20) 42.4 7.23** Morus nigra L. 9.4 (0.24) 15.7 (0.16) 40.2 7.12** Vitis vinifera L. 8.8 (0.29) 14.1 (0.29) 37.5 5.49** Ficus carica L. 12.5 (0.15) 23.5 (0.47) 34.5 9.02** Pistacia vera L. 10.4 (0.08) 14.9 (0.20) 30.2 8.28** Punica granatum L. 10.5 (0.21) 14.1 (0.24) 25.4 8.44** Pinus halepensis Miller. 10.4 (0.07) 13.7 (0.05) 23.9 6.86** F 6.0*

Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant F: Calculated values in F-test and Inc%: Increasing %

During autumn, the increased percentage of Cu in plant species collected from polluted site was in the range of 23.9 – 47.0 % (Table 4.12). The Rosa indica had largest increasing percentage and Pinus halepensis indicated the smallest. Statistical analysis using t-test showed that out of 13 plant species only one plant i.e. Eucalyptus tereticornis had slightly significant difference in the Cu contents at p<0.05 significant level. All the other species exhibited highly significant (p<0.01) variations during autumn. F-test revealed that there was also slightly significant variation between the mean value of polluted and non-polluted sites plant species at 5% significant level.

100

Table 4.13: Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Spring season N P S. D P S. D Inc % t Rosa indica L. 0.07 (0.01) 0.26 (0.01) 72.7 2.95* Ficus carica L. 0.10 (1.69) 0.62 (0.02) 65.5 4.52** Melia azadirach L. 0.10 (1.70) 0.56 (0.02) 58.9 8.39** Eucalyptus tereticornis L. 0.11 (0.01) 0.47 (0.01) 58.4 9.12** Robinia pseudoacacia L. 0.11 (0.01) 0.56 (0.01) 57.7 5.17** Punica granatum L. 0.11 (0.01) 0.57 (0.01) 54.2 9.10** Pinus halepensis Miller. 0.15 (0.01) 0.59 (0.01) 48.2 8.43** Morus alba L. 0.13 (0.01) 0.54 (0.02) 47.3 6.26** Fraxinus excelsior L. 0.14 (0.01) 0.47 (0.01) 45.6 8.71** Morus nigra L. 0.14 (0.01) 0.58 (0.01) 45.5 6.26** Elaeagnus angustifolia L. 0.15 (0.01) 0.58 (0.01) 45.2 4.52** Pistacia vera L. 0.16 (0.01) 0.63 (0.01) 42.4 8.71** Vitis vinifera L. 0.18 (0.01) 0.65 (0.01) 35.4 3.34* F 10.6**

During spring, the percentage elevated of Cd from polluted site plant species was in the range of 35.4 – 72.7 % (Table 4.13) with Rosa indica had largest increase and Vitis vinifera showed the least. Statistical analysis using t-test indicated that Rosa indica and Vitis vinifera showed slightly significant difference between polluted and non-polluted sites at p<0.05 significant level. All the other remaining species exhibited highly significant (p<0.01) variations in their values during spring. F-test indicated that there was also highly significant difference between the mean value of polluted and non-polluted sites plant species at 5%.

101

Table 4.14: Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plants Summer season N P S. D P S. D Inc % t Ficus carica L. 0.11 (0.02) 0.77 (0.03) 67.0 7.47** Punica granatum L. 0.13 (0.01) 0.56 (0.02) 58.8 6.02** Melia azadirach L. 0.12 (0.01) 0.54 (0.02) 58.4 5.15** Rosa indica L. 0.13 (0.01) 0.47 (0.00) 57.8 8.19** Robinia pseudoacacia L. 0.14 (0.01) 0.50 (0.01) 52.3 6.42** Morus nigra L. 0.16 (0.02) 0.66 (0.00) 51.5 7.02** Fraxinus excelsior L. 0.14 (0.01) 0.57 (0.01) 51.1 9.12** Morus alba L. 0.14 (0.02) 0.63 (0.01) 51.1 9.12** Eucalyptus tereticornis L. 0.14 (0.01) 0.69 (0.01) 50.6 7.66** Pinus halepensis Miller. 0.14 (0.01) 0.52 (0.01) 50.6 5.81** Elaeagnus angustifolia L. 0.15 (0.03) 0.75 (0.01) 45.2 4.52** Pistacia vera L. 0.16 (0.01) 0.67 (0.01) 43.0 7.81** Vitis vinifera L. 0.18 (0.01) 0.65 (0.02) 40.2 7.81** F 15.0**

Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant F: Calculated values in F-test and Inc%: Increasing %

During summer, the percentage increase of Cd in plant species collected from polluted site was found between 40.2 – 67.0 % (shown in Table 4.14). Ficus carica L. had the largest increasing percentage while Vitis vinifera showed the lowest. Statistical analysis (t-test) indicated that all the plant species showed highly significant (p< 0.01) variations during summer. F-test revealed that there was also highly significant difference between the mean value of polluted and non-polluted sites at 5% significant level.

102

Table 4.15: Comparison of average concentration of Cadmium (Cd μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during autumn season

Name of plants Autumn season N P S. D P S. D Inc % t Ficus carica L. 1.34 (0.10) 0.14 (0.01) 89.3 7.08** Pistacia vera L. 1.36 (0.05) 0.20 (0.02) 85.0 7.46** Elaeagnus angustifolia L. 1.28 (0.08) 0.20 (0.02) 84.4 5.98** Pinus halepensis Miller. 1.28 (0.04) 0.22 (0.02) 82.5 6.46** Morus nigra L. 1.25 (0.04) 0.23 (0.02) 81.9 5.93** Melia azadirach L. 0.77 (0.06) 0.14 (0.01) 81.5 9.76** Fraxinus excelsior L. 1.42 (0.07) 0.27 (0.04) 80.9 3.62* Morus alba L. 1.40 (0.08) 0.29 (0.03) 79.1 5.89** Vitis vinifera L. 0.80 (0.04) 0.17 (0.01) 78.8 2.82* Eucalyptus tereticornis L. 1.25 (0.04) 0.27 (0.02) 78.1 7.14** Punica granatum L. 1.28 (0.08) 0.31 (0.01) 75.8 8.97** Rosa indica L. 0.71 (0.04) 0.23 (0.01) 67.5 5.76** Robinia pseudoacacia L. 0.72 (0.03) 0.25 (0.02) 64.6 3.95** F 15.3**

Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., F: Calculated values in F-test and Inc%: Increasing %

During autumn, the percentage increase of Cd in polluted site plant species with respect to non-polluted site was in the range of 64.6 – 89.3% (Table 4.15). The Ficus carica had the largest increased percentage while Robinia pseudoacacia showed the least. Statistical analysis using t-test indicated that Fraxinus excelsior and Vitis vinifera had slightly significant difference in their Cd concentration at p<0.05 significant level. All the other species showed highly significant (p< 0.01) variations in their values during autumn. F-test indicated that there was also highly significant difference between the mean value of polluted and non-polluted sites plant at 5% significant level.

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Table 4.16: Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Spring season NP S. D P S. D Inc % t Eucalyptus tereticornis L. 0.37 (0.007) 0.50 (0.006) 25.3 3.93** Ficus carica L. 0.20 (0.006) 0.26 (0.004) 24.1 1.70ns Vitis vinifera L. 0.34 (0.002) 0.44 (0.003) 22.1 3.84** Pinus halepensis Miller. 0.35 (0.005) 0.44 (0.005) 20.7 2.52** Morus alba L. 0.31 (0.004) 0.39 (0.004) 19.7 1.46 ns Rosa indica L. 0.34 (0.002) 0.42 (0.003) 19.5 3.46** Punica granatum L. 0.43 (0.006) 0.53 (0.007) 19.3 2.31** Robinia pseudoacacia L. 0.34 (0.005) 0.41 (0.007) 17.9 2.73** Morus nigra L. 0.30 (0.003) 0.36 (0.004) 17.7 4.13** Melia azadirach L. 0.35 (0.004) 0.42 (0.005) 16.9 2.17** Pistacia vera L. 0.39 (0.024) 0.47 (0.071) 16.4 2.71** Elaeagnus angustifolia L. 0.41 (0.004) 0.48 (0.001) 14.6 2.10 ns Fraxinus excelsior L. 0.42 (0.003) 0.48 (0.007) 13.5 3.17** F 3.25ns

During spring, the percentage increase of Sb in polluted site plant species with respect to non-polluted site was in the range of 13.5–25.3% (Table 4.16). Eucalyptus tereticornis had the maximum increased percentage while Fraxinus excelsior showed the minimum. Statistical analysis using t-test indicated that out of 13 plant species; Ficus carica, Morus alba and Elaeagnus angustifolia showed non- significant variation. All the other species had highly significant difference (p<0.01) during spring. F-test exhibited that there was non significant variation between the mean value of polluted and non-polluted sites plant species at 5%.

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Table 4.17: Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during summer season

Name of plants Summer season NP S. D P S. D Inc % t Pinus halepensis Miller. 0.44 (0.001) 0.52 (0.001) 15.5 1.44 ns Morus alba L. 0.38 (0.005) 0.43 (0.002) 11.7 2.69** Melia azadirach L. 0.42 (0.002) 0.47 (0.002) 10.7 3.89** Ficus carica L. 0.27 (0.006) 0.31 (0.007) 10.1 3.45** Punica granatum L. 0.54 (0.001) 0.60 (0.001) 10.1 4.03** Pistacia vera L. 0.47 (0.072) 0.53 (0.021) 9.71 3.85** Fraxinus excelsior L. 0.50 (0.002) 0.56 (0.005) 9.58 3.63** Eucalyptus tereticornis L. 0.52 (0.007) 0.58 (0.005) 9.37 2.56** Elaeagnus angustifolia L. 0.49 (0.001) 0.53 (0.004) 7.66 2.76** Robinia pseudoacacia L. 0.43 (0.007) 0.46 (0.007) 6.61 3.87** Rosa indica L. 0.44 (0.001) 0.47 (0.005) 6.44 1.54 ns Morus nigra L. 0.38 (0.001) 0.40 (0.003) 5.16 1.94 ns Vitis vinifera L. 0.48 (0.008) 0.49 (0.007) 2.34 1.78 ns F 4.0*

During summer, the percentage increase of Sb in polluted site plant species was in the range of 2.3 – 15.5 % (Table 4.17). Pinus halepensis had the maximum increased percentage and Vitis vinifera showed the minimum. The t-test revealed that out of 13 plant species 04 plants i.e. Pinus halepensis, Rosa indica, Morus nigra and Vitis vinifera showed non-significant variation in their Sb contents. All the other species exhibited highly significant (p< 0.01) difference during summer. F-test reported that there was slightly significant variation between the mean value of polluted and non-polluted site plant species at 5% significant level.

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Table 4.18: Comparison of average concentration of Antimony (Sb μgg-1 dry weight) in the leaves of polluted and non-polluted sites of Quetta city during spring season

Name of plants Autumn season NP S. D P S. D Inc % t Morus alba L. 0.52 (0.001) 0.40 (0.007) 21.49 4.39** Pinus halepensis Miller. 0.55 (0.001) 0.46 (0.006) 16.43 1.91 ns Pistacia vera L. 0.59 (0.005) 0.49 (0.023) 15.98 3.84** Fraxinus excelsior L. 0.63 (0.001) 0.53 (0.007) 15.82 2.97* Melia azadirach L. 0.53 (0.001) 0.45 (0.005) 15.25 4.16** Punica granatum L. 0.67 (0.001) 0.57 (0.006) 14.98 3.61* Eucalyptus tereticornis L. 0.65 (0.005) 0.55 (0.007) 14.46 3.29* Vitis vinifera L. 0.57 (0.001) 0.49 (0.006) 14.05 3.48* Ficus carica L. 0.34 (0.005) 0.29 (0.007) 13.92 4.99** Elaeagnus angustifolia L. 0.59 (0.001) 0.52 (0.008) 11.94 2.53* Robinia pseudoacacia L. 0.52 (0.001) 0.45 (0.008) 11.93 1.68 ns Morus nigra L. 0.46 (0.005) 0.40 (0.008) 11.80 2.95* Rosa indica L. 0.52 (0.006) 0.46 (0.006) 10.98 3.25* F 3.28ns

During autumn, the percentage increase of Sb in polluted site plant species was in the range of 11.0 – 21.5 % (shown in Table 4.18). Morus alba had the largest increased percentag while Rosa indica showed the least. Statistical analysis using t- test indicated that out of 13 plant 4 species i.e. Robinia pseudoacacia, Pistacia vera, Melia azadirach and Ficus carica exhibited highly significant difference (p< 0.01) during spring. Other seven species viz. Fraxinus excelsior, Punica granatum, Eucalyptus tereticornis, Vitis vinifera, Elaeagnus angustifolia, Morus nigra and Rosa indica were slightly significant at p< 0.05. The remaining 02 plants (Pinus halepensis and Robinia pseudoacacia) had non-significant variation during autumn. F-test showed that there was slightly significant variation between the mean value of polluted and non-polluted sites plant species at 5% significant level.

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Table 4.19: Seasonal heavy metals contamination (μg/g-1) with increasing percentage increasing in all the plant species collected from polluted and non-polluted sites of Quetta city

Elem Spring Summer Autumn ents NP S.D P S. D Inc% NP S. D P S. D Inc% NP S. D P S. D Inc% Pb 6.2 (1.4) 16.1 (1.3) 62.1 8.0 (1.2) 26.6 (2.7) 69.7 8.3 (1.4) 28.6 (2.8) 71.0 Cd 0.2 (0.1) 0.5 (0.02) 51.9 0.1 (0.0) 0.6 (0.1) 52.3 0.3 (0.1) 1.14 (0.1) 80.2 Cu 7.9 (1.7) 12.4 (2.2) 36.8 8.4 (1.7) 13.5 (1.8) 37.7 8.5 (1.7) 13.8 (1.7) 38.4 Fe 19.8 (10.3) 29.2 (11.3) 32.1 20.8 (10.6) 32.8 (11.9) 36.6 22.9 (10.6) 37.8 (12.2) 39.4 Zn 13.7 (8.4) 19.1 (9.3) 23.7 17.2 (9.5) 20.6 (9.5) 16.5 19.0 (9.0) 24.6 (9.5) 22.9 Sb 0.4 (0.1) 0.42 (0.1) 7.14 0.5 (0.1) 0.53 (0.1) 9.0 0.5 (0.1) 0.55 (0.1) 14.6 Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation and Inc%: Increasing %

Over all average increasing percentage of Pb during spring, summer and autumn, (Table 4.19) from all the polluted sites plants recorded was 62.6, 69.7 and 71.0 %, respectively, autumn had the maximum increasing percentage and spring showed the least. Increasing percentage during spring, summer and autumn of Cd: 51.9, 52.3 and 80.2%, Cu: 36.8, 37.7 and 38.4%, Fe: 32.1, 36.6 and 39.4% and Sb: 7.14, 9.0 and 14.6 %, respectively. Autumn showed highest increasing percentage and spring showed the lowest increasing percentage in all the metals. Percentage increase of Zn was recorded 23.7% during spring, 20.6% during summer and 22.9% during autumn. Spring showed maximum increasing percentage while summer the minimum contents of Zn from polluted site plant species with respect to non-polluted site.

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Table 4.20: Over all average concentration of heavy metals (μgg-1) in all the plant species of polluted and non-polluted sites during three seasons with increasing percentage. Elements Np S. D P S. D Inc % T Cd 0.2 (0.1) 0.6 (0.3) 78.5 3.17* Pb 7.5 (1.2) 23.8 (6.7) 68.5 4.20** Cu 8.3 (0.3) 13.3 (0.7) 37.7 12.51** Fe 21.2 (1.6) 33.3 (4.4) 36.4 4.78** Zn 16.7 (2.7) 21.1 (3.4) 22.4 2.89* Sb 0.5 (0.1) 0.55 (0.1) 14.0 3.01* Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant, F: Calculated values in F-test and Inc%: Increasing % Over all increasing percentage of Pb, Zn, Fe, Cu, Cd and Sb from polluted site plant species during all 3 seasons recorded were 68.5, 22.4, 36.3, 37.7, 78.5 and 14.0%, respectively (Table 4.20). Statistical analysis using t-test indicated that Pb, Fe and Cu showed highly significant variation at P<0.01 level between polluted and non- polluted sites. The contents of Zn, Cd and Sb showed slightly significant difference at P<0.05.

Fig. 4.1. Over all concentration of Pb in different plant species of 35 Quetta city Ficus carica L. Vitis vinifera L. 30 Pistacia vera L. 25 Pinus halepensis Miller.

Morus nigra L. 1)

20- Morus alba L.

15gg

μ Punica granatum L. ( 10 Elaeagnus angustifolia L. Melia azadirach L. 5 Fraxinus excelsior L.

Concentration of of Metal Concentration 0 Robinia pseudoacacia L. 1 2 Eucalyptus tereticornis L. Rosa indica L. 1= Control site 2= Polluted site

The variation in increasing concentration of Pb among all the investigated plant species from non-polluted to polluted site during the growing period was found, as shown in Fig 4.1. Vitis vinifera showed the highest increasing concentration while Rosa indica showed the least. Other remaining species indicated almost same increasing concentration from non-polluted to polluted sites.

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Fig 4.2. Overall concentration of Zn in different plant species of Quetta city Morus nigra L.

) 45 Ficus carica L. 1

- 40 Vitis vinifera L. gg

μ 35 Elaeagnus angustifolia L. 30 Morus alba L. Punica granatum L. 25 Pinus halepensis Miller. 20 Robinia pseudoacacia L. 15 Pistacia vera L. 10 Fraxinus excelsior L. 5 Melia azadirach L. 0 Eucalyptus tereticornis L.

1 2 Rosa indica L. Concentration of of ( metal Concentration 1= Control site 2= Polluted site

Variation increasing concentration of Zn in all plant species from non- polluted to polluted sites through out the year found illustrated in Fig 4.2. Ficus carica and Vitis vinifera had the highest increasing concentration, while Rosa indica showed minimum increased concentration from non-polluted to polluted sites.

Fig 4.3. Over all concentration of Fe in different plant species of Quetta city 60 Vitis vinifera L. Morus nigra L.

50 Ficus carica L. 1)

- Morus alba L. gg

μ 40 Elaeagnus angustifolia L. Punica granatum L. 30 Robinia pseudoacacia L. 20 Pinus halepensis Miller. Pistacia vera L. 10 Fraxinus excelsior L. Eucalyptus tereticornis L.

Metal Metal concentration ( 0 Rosa indica L. 1 2 Melia azadirach L. 1= Control site 2= Polluted site

Increasing concentration of Fe from non-polluted to polluted site in all 03 seasons varied from specie to species (Fig.4.3). The concentration showed its highest increased in Vitis vinifera and Ficus carica while Eucalyptus tereticornis and Melia azadirach had the lowest Fe concentration from non-polluted to polluted sites.

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Fig 4.4. Over all concentration of Cu in different plant species of Quetta city Ficus carica L. 25 Elaeagnus angustifolia L.

1) Pistacia vera L. - 20

Vitis vinifera L. gg μ Pinus halepensis Miller. 15 Melia azadirach L. 10 Morus alba L. Punica granatum L. 5 Morus nigra L. Robinia pseudoacacia L. Eucalyptus tereticornis L.

Metal Metal concentration ( 0 1 2 Rosa indica L. Fraxinus excelsior L. 1=Control site 2= Polluted site

Variation of increasing concentration of Cu in all investigated plant specie from non-polluted to polluted site in all 03 seasons is shown in Fig 4.4. The maximum increasing concentration from non-polluted to polluted sites showed by Pinus halepensis while Melia azadirach had minimum increasing contents of Cu.

Fig 4.5. Over all concentration of Cd in different Plant species of Quetta city Pistacia vera L. 1.2 Fraxinus excelsior L. 1 Morus alba L. Punica granatum L. 0.8 Ficus carica L. Elaeagnus angustifolia L. 0.6 Eucalyptus tereticornis L. 0.4 Pinus halepensis Miller. Morus nigra L. 0.2 Vitis vinifera L.

Metal Metal concencentration Robinia pseudoacacia L. 0 1 2 Rosa indica L. Melia azadirach L. 1 = Control site 2=Pollutred site

Increasing concentration of Cd from non-polluted to polluted site through out the year was recorded with variation from species to species (Fig 4.5). Out of 13 plant species 03 i.e. Robinia pseudoacacia, Rosa indica and Melia azadirach showed lowest increasing concentration while Ficus carica had the highest concentration. Almost same increasing concentration was recorded from all other species.

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Fig 4.6. Over all concentration of Sb in different plant specie of Quetta city 0.7 Pistacia vera L. Fraxinus excelsior L.

0.6 Morus alba L.

1) - Punica granatum L. gg 0.5 μ Ficus carica L. 0.4 Elaeagnus angustifolia L. 0.3 Eucalyptus tereticornis L. Pinus halepensis Miller. 0.2 Morus nigra L. 0.1 Vitis vinifera L. Robinia pseudoacacia L. 0 Rosa indica L. Concentration of metal ( metal of Concentration 1 2 Melia azadirach L. 1= Control site 2= Polluted site

Increasing concentration of Sb in the leaves of selected plants from non- polluted to polluted site were recorded and shown in Fig 4.6. Out of 13 plant species, only 01 Punica granatum showed highest increasing concentration from non-polluted to polluted site. Pistacia vera and Ficus carica showed minimum increasing concentration of Sb.

Over all average increasing percentage of lead (Pb) at polluted sites plant species throughout the year were in the range of 62.99 - 74.4 % with Ficus carica had the lowest increasing percentage and Rosa indica showed highest increasing percentage (Fig 4.7).

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Over all average increasing percentage of Zinc (Zn) in plants from polluted sites throughout year was in the range of 30.18 - 51.02 %. The Melia azadirach had the highest increasing percentage while Morus nigra showed the lowest (Fig 4.8).

Average increasing percentage of Iron (Fe) in plants from polluted site throughout the year recorded was 29.0 - 53.9 %. Lowest increasing percentage recoded from M. nigra while highest was found in F. carica (Fig 4.9).

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Results illustrated in Fig 4.10, indicated that over all average increasing percentage of Copper (Cu) contents at polluted site with respect to non-polluted site plant species throughout the year was found in the range of 37.0 - 60.6%. Lowest increasing percentage was recorded from M. azadirach while highest was from R. indica.

Average increasing percentage of Cadmium (Cd) from polluted site plant species during all the season was in the range of 68.1 - 83.7 %. Ficus carica had the highest increased percentage while Pistacia Vera showed the least (Fig 4.11).

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Data presented in Fig 4.12, indicated that over all average percentage increase of Antimony (Sb) at polluted site in comparison to non-polluted site during 3 seasons recorded between 17.0 - 37.9 %. Lowest increasing percentage was recorded from Morus nigra while Punica granatum had the highest.

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Fig 4.13: Overall average concentration of Heavy metals during spring, summer and autumn in different plant species collected from non-polluted sites of Quetta city.

Fig 4.14: Overall average concentration of Heavy metal during spring, summer and autumn in all plant species collected from polluted sites of Quetta city

Overall average concentration of heavy metals (Pb, Zn, Fe, Cu, Cd and Sb) in all the plant species collected from polluted and non-polluted sites of Quetta city during spring, summer and autumn (shown in Fig 4.13 & 4.14) exhibited that Pb from all investigated plant species was 6.12, 8.04 and 8.29 at non-polluted site, while at polluted site it was very high i.e. 16.14, 26.57 and 28.62, respectively. Zn contents were 13.73, 17.23 and 19.01from non-polluted site, while at polluted site it increased

115 by 19.10, 20.64 and 24.65 during spring, summer and autumn, respectively. Fe contents at non-polluted site were 19.79, 20.80 and 22.92, while at polluted site it increased as 29.15, 32.78 and 37.48 during spring, summer and autumn, respectively. Average contents of Cu from non-polluted site in all the plant species were recorded 7.89, 8.39 and 8.52, which rose by 12.41, 13.47 and 13.83 at polluted site during spring, summer and autumn, respectively. Cd contents in non-polluted site plant species were 0.13, 0.14 and 0.23, while at polluted site they became 0.54, 0.61 and 1.14 during springs, summer and autumn, respectively. Average contents of Sb recorded were 0.35, 0.45 and 0.47 from non-polluted site plant species, while it increased at polluted site that was 0.43, 0.49 and 0.55 during spring, summer and autumn, respectively. All the investigated heavy metals were found lowest in spring and highest in autumn from both sites.

Table 4.21: Seasonally over all average concentration (μg/g-1) of heavy metal in soil collect from polluted and non-polluted sites of Quetta city during different seasons of the year.

Elem Spring Summer Autumn ents Np S. D P S. D t Np S. D P S. D t Np S. D P S. D t Fe 64.7 (0.5) 64.7 (0.8) 0.6 ns 65.7 (0.5) 66.9 (0.1) 1.5 ns 65.7 (0.3) 66.8 (0.1) 1.3ns Zn 45.5 (0.1) 45.6 (0.3) 0.1 ns 45.5 (0.1) 45.8 (0.2) 0.3 ns 46.6 (0.1) 46.4 (0.3) 0.1ns Pb 37.5 (0.1) 37.5 (0.3) 0.3ns 37.6 (0.6) 36.7 (0.2) 0.4 ns 40.4 (0.3) 40.1 (0.2) 0.1ns Cu 17.5 (0.9) 17.6 (0.1) 0.9 ns 18.4 (0.9) 18.6 (0.1) 0.7 ns 17.4 (0.9) 18.5 (0.1) 0.8ns Cd 01.2 (0.1) 01.3 (0.0) 0.9 ns 01.2 (0.0) 01.3 (0.1) 1.0 ns 01.3 (0.1) 01.3 (0.0) 0.6 ns Sb 00.7 (0.1) 00.7 (0.0) 0.7 ns 00.7 (0.1) 00.8 (0.0) 0.9 ns 00.7 (0.0) 00.8 (0.0) 0.1ns Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001., ns: Non-significant

Seasonally average concentration of all the investigated heavy metals (Fe, Zn, Pb, Cu, Cd and Sb) in soil samples collected from polluted and non-polluted sites recorded was almost similar during all the seasons (spring, summer and autumn), but the variation with in metals contents were found (Table 4.21). Statistical analyses using t-test indicated that there was non-significant difference in soil samples between season to season and site to site.

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Table 4.22: Overall average contents of heavy metal (μg g-1) in soil samples of polluted and non-polluted sites of Quetta city during throughout the season of the year Elements Np S. D P S. D T Fe 65.4 (0.60) 68.0 (1.15) 0.49 ns Zn 45.9 (0.63) 48.7 (0.52) 0.50 ns Pb 38.5 (1.63) 40.1 (1.50) 0.50 ns Cu 18.5 (0.09) 18.5 (0.09) 0.49 ns Cd 1.2 (0.01) 1.3 (0.01) 0.49 ns Sb 0.7 (0.03) 0.7 (0.01) 0.50 ns

Np: Non-Polluted site, P: Polluted site, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001

Through out the year, over all average contents of Fe, Zn, Pb, Cu, Cd and Sb in soil samples collected from non-polluted sites were (described in Table 4.22) found 65.4, 45.9, 38.5, 18.5, 1.2 and 0.7 μgg-1, where as from polluted sites it was 68.0, 48.7, 40.1, 18.5, 1.3 and 0.7, respectively. Statistical analysis using t-test indicated that there was non-significant (P<0.05) variation between polluted and non-polluted sites soil samples.

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Table 4.23: Correlation coefficient between heavy metal in soil and Plants of Polluted sites Elements Pb in Zn in Fe in Cu in Cd in Sb in Pb in Zn in Fe in Cu in Cd in Sb in plant Plant plant Plant plant plant soil Soil Soil Soil Soil soil Pb in plant 1 Zn in plant 0.92** 1 Fe in plant 0.90** 0.99** 1 Cu in plant 0.84** 0.99** 0.99** 1 Cd in plant 0.80** 0.97** 0.98** 0.99** 1 Sb in plant 0.91** 0.99** 0.99** 0.98** 0.98** 1 Pb in soil 0.46ns 0.78** 0.80** 0.86** 0.89** 0.79** 1 Zn in soil 0.70** 0.93** 0.94** 0.98** 0.99** 0.93** 0.96** 1 Fe in soil 0.98** 0.82** 0.79** 0.71** 0.50* 0.81** 0.28ns 0.54* 1 Cu in soil 0.27ns 0.91** 0.66** 0.75** 0.89** 0.65** 0.98** 0.88** 0.07 ns 1 Cd in soil 0.67** 0.91** 0.92** 0.96** 0.99** 0.92** 0.97** 0.99** 0.50* 0.89** 1 Sb in soil 0.65** 0.89** 0.91** 0.96** 0.99** 0.91** 0.98** 0.99** 0.48ns 0.91** 0.99** 1 *Significant at 5%; **Significant at 1%

The correlation coefficient (r) between heavy metals concentration in soil and plant species collected from urban areas (polluted sites) of Quetta city (summarized in Table 4.23) revealed that Pb in plants and Pb (0.46) and Cu (0.27) in soil were not significantly correlated with each other. Further that Pb in soil and Fe (0.28) in soil were also not significantly correlated with each other. Fe in soil was not significantly correlated with Cu and Sb in soil (0.07 & 0.48), respectively, where as all the other heavy metals in soil samples and plant leaves were found slightly to highly significantly correlated with each other.

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4.4. DISCISSION

4.4.1. Lead (Pb): Lead is number 2 on the ATSDR's (The Agency for Toxic Substances and Disease Registry) “Top 20 List" and considered poisoning heavy metal for animals, plants and human being, even in very small amount (Roberts, 1999). Statistics test using t-test indicated that Pb contents in polluted site plant species were highly significant high from the non-polluted site plant species at P<0.01 significant levels. There was also a highly significant variation between the mean values of different 13 investigated plant species during different seasons (spring, summer and autumn). It has been noticed that seasonally Pb contents in plant leaves slightly increased from spring to summer and reached to its maximum during autumn season. The high concentrations of Pb in the plant leaves collected from polluted sites might be due to different factors like large number of vehicles moving on the road of Quetta city and also depend on the structure and age of leaves. Large leaf area provides enough space for the accumulation of air pollutants for long time over their surface, which may cause high contamination of Pb in plant leaf. Similar observations were also reported by many other researchers i.e. Ijeoma et al., (2011); Krstić et al., (2007); Krstić and Stanković, (2006) and Stanković, (2006). The higher levels of heavy metals contents in plant leaves growing near the industries, roadside and urban areas of Kayseri was also found during the study of Robinia pseudoacacia as a bio-monitor of Pb, Cd, Cu and Zn (Aksoy et al., 2000). Meaning full correlation between the numbers of cars and the heavy metal contents in plant leaves and soil samples during the study of Pb, Ni, Cd and Zn pollution of traffic in Kayseri was also reported in previous study (Kartal et al., 1992). Moreover Atayese et al., (2009) and Suzuki et al., (2008), reported that emission from heavy traffic on roads contain lead (Pb), cadmium (Cd), zinc (Zn) and nickel (Ni), which are the main source of heavy metal pollution in the urban area. The highest level of Pb contents recorded during autumn in the leaves of P. vera, V. vinifera and F. carica was considered at the toxic level of Pb in plants (Ross, 1994). Overall average contents in all the investigated plant species during through out year at polluted site were very high then non- polluted site, similar observation was also reported during previous study in Quetta city (Leghari et al., 2003).

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4.4.2. Zinc (Zn): Zinc in small amount plays an essential metabolic role in the plant, because it is the component of a variety of enzymes, such as dehydrogenase, proteinases, peptidases and phospohydrolases, while on the other hand its high concentration damage the metabolic processes in plants (Yap et al., 2010). Statistical analysis using t-test indicated that over all average contents of Zn in polluted site plant species are slightly significantly high from non-polluted site at P<0.05 significant level. Average contents of Zn in plant species collected from polluted sites showed significant variation from season to season. Seasonally Zn concentration in plant leaves started increasing from spring to summer and reached to its maximum during autumn season. The high concentration of Zn in the city area (polluted site) as compared to non-polluted site plant species might be due to high contents of air pollutants due to traffic emission in the city area. Similar observation was also reported by other workers i.e. Atayese et al., (2009); Moller et al., (2005) and Suzuki et al., (2008). They identified that exhaust emission have been the primary sources of metallic nuisance such as zinc. The concentration of Zn in all the investigated plants during all the seasons was found low from the toxic level in plants (Ross, 1994). Among the investigated plant species F. carica from polluted sites during autumn season showed highest level of Zn content (41.35μg g-1). Similar observation was also reported during previous study conducted by Ara et al., (1996) and Ijeoma et al., (2011), they found highest contents of Zn in the leaves of Azadirachta indica (34.58±2.07mg/kg) and in Eucalyptus sp and Ficus religiosa, collected from urban area.

4.4.3. Iron (Fe): Iron toxicity is limited to ingested or environmental exposure and it does not appear on the ATSDR's "Top 20 List," but it is a heavy metal of concern because its overload causes disease (hemochromatosis). Statistical analysis (t-test) exhibited that overall contents of Fe from polluted sites plant species were highly significant (P<0.01). There was also significant variation between the mean values of polluted and non-polluted sites plants during different seasons. Iron concentration in all the investigated plant species start increasing from spring to summer and reached to its maximum during autumn season. The highest concentration of Fe in polluted sites plant during autumn season might be due to high traffic density during autumn season, (which has been proved in previous chapter 3 of this dissertation). Similar results were also reported by Ara et al., (1996), they conducted their study at roadside

120 areas of Karachi city Pakistan; during which highest concentration of Cu, Fe, Ni, Pb, Zn, Cd and Cr in Eucalyptus sp and Ficus religiosa leaves are observed. Among the plant species highest level of Fe contents recorded (60.71μgg-1) in Ficus carica from polluted sites during autumn season was low than the toxic level in plants (Ross, 1994).

4.4.4. Copper (Cu): Cu is essential for growth, but concentrations above, 20 μg g-1 are considered toxic to plants according to previous study (Jones and Belling, 1967). Statistical analysis using t-test revealed that Cu contents at polluted site plant species were highly significant (P<0.01) high from the non-polluted site plant species and there is also significant variation between mean values of different seasons. Cu contents start its increasing from spring to summer and reached to its maximum during autumn season. High concentration of Cu in the leaves of city area might be due to aerial deposition and also transported from soil by root. This view is also supported by other researchers (Alfani et al., 1996). They found that the metal concentrations were significant higher in leaves collected from roadside than in leaves collected from control site. They also found positive correlations between Pb, Cu and Fe concentrations in leaf tissue and leaf surface demonstrated the significance of deposition to leaf tissue content. This supports the theory that aerial deposition to leaves is an important source of metals contamination in leaves, while Cu concentration in the shoots was significantly influenced by Cu concentration in soil and increased markedly with an increase in the soil Cu concentration (Xiong and Wang, 2005). The main sources of pollutant copper in the atmosphere are Cu production and handling, fossil fuel combustion and iron steel production (Nriagu, 1979). In this study the highest contents i.e., 20.6 & 23.5 μg g-1 noted in the leaves of F. carica during summer & autumn season are considered more then the toxic level (Ross, 1994). These findings are also in line with those described by other researchers (Aksoy and Demirezen, 2006). They found the highest concentration of Ni and Cu 27.04 μgg-1 & 16.21μgg-1, respectively in the leaves of F. excelsior collected from the urban roadside.

4.4.5. Cadmium (Cd): Cadmium is a byproduct of the mining and smelting of lead and zinc. It is used in nickel-cadmium batteries, plastics, and paint pigments. Statistical analysis using t-test exhibited that the contents of Cd in all the investigated

121 plants leaves collected from polluted sites had slightly significant variation at P<0.05 level from non-polluted sites plant species during all the seasons. There was also significant difference between seasons to season and species to species. The highest Cd concentration in plant leaves from polluted sites might be due to different reasons like contamination through soil and urban air, because Cd is found in reservoirs containing shellfish. Similar observation was also reported by Alfani et al., (1996), also reported a meaningful correlation between the numbers of cars and the heavy metal contents. Cigarettes, dental alloys, electroplating, motor oil, and traffic exhaust is the source of Cd, further that it is also the component of insecticides, fungicides, sludge and commercial fertilizers (Kartal et al., 1992; Suzuki et al., and Atayese et al., 2009). In this study the contents of Cd in all investigated plant species collected from both sites (polluted and non-polluted) during all the seasons were more than toxic level in plants (Ross, 1994). These findings are also in accordance with those described by other researcher i.e. Atayese et al., (2009). They reported the highest contents of Cd in the leaves of urban site at Afromedia (4.9 mg kg-1) and lowest at the control site (0.2 mg kg-1). High concentration of Cd was also noted in P. guajava (1.44 ±0.11 mg kg-1) (Ijeoma, et al., 2011) and (0.428 μgg-1) in the leaves of the F. excelsior collected from urban sites. Here too was evidence of a decrease in concentration with increase in distance at each site of the road.

4.4.6. Antimony (Sb): Statistical analysis (t-test) indicated that over all contents of Sb in polluted site plant species were slightly significant from non-polluted site. The high Sb concentration in the urban area might be due to high density of vehicles. This view is also supported by many previous studies. Kubota et al., (1998) Kubota, (1999) and Takamatsu et al., (2000), reported the high concentration of Sb in urban site plant species as compared to non-polluted site. Ozaki et al., (2004) and Torre et al., (2002), they indicated that Sb concentrations are to be higher in urban areas than rural ones on tree leaves and in road dust. They also indicated that As, Sb and Hg distributions are closely related to automobiles. It has been also already declared that Sb is used in many parts of a vehicle, such as the brake device, fire retardant (Torre et al., 2002) and battery. So it is clear that the use of a brake wears down the brake lining and releases Sb, especially around curves and intersections, where acceleration and deceleration are repeated often. Actually, gaseous Hg and particulate Sb absorbed into fine suspended particles were found in urban atmosphere. These atmospheric

122 pollutants deposit on the ground, led to soil pollution and plant leaf contamination. In this study all the plant species from polluted and non-polluted sites had less Sb contents then toxic level in plants, however there was variation in Sb contents form specie to specie. More concentration of As and Sb from the urban area has also been observed and, it is assumed that an individual car emits small amounts of Hg, Sb and As in the short term, but great amounts in long term, causing chronic pollution in the neighboring environment (Huang et al., 1992; Mizohata and Kusuya, 2000). These two elements are highly toxic and have serious effects on the environment, human and plants, thus the monitoring of them is very much important.

4.4.7. Heavy metals in soil: Statistical analysis using t-test indicated that contents of all the investigated heavy metals in soil samples collected from polluted and non- polluted sites showed non-significant (P<0.05) differences. These results support the views that heavy metals contamination in plant leaves of polluted site was not only contaminated from soil, automobile pollution in the urban area of Quetta city is also responsible for high level contamination in plant leaves. Similar observation was also noted in the previous studies (Pilegaard and Johnsen, 1984). They investigated that Zn, Cd, Cu, Ni and Pb in Achillea millefolium (milfoil) and Hordeum vulgare (barley) is uptake from air and soil, they also concluded that Cu and Pb in plant concentrations correlated with aerial deposition but not with soil concentrations.

4.4.8. Correlation coefficient between heavy metal in soil and plants: Lead (Pb) in plant significantly and positively correlated with Zn, Fe, Cu, Cd and Sb in plant and Zn, Fe, Cd and Sb in soil, but there was non-significant correlated between Pb in plant and Pb in soil and Cu in soil. Similar observation was also noted in the previous studies (Pilegaard and Johnsen, 1984). They investigated that Zn, Cd, Cu, Ni and Pb uptake from air and soil by Achillea millefolium (milfoil) and Hordeum vulgare (barley) in Denmark concluded that Cu and Pb in plant concentrations correlated with aerial deposition but not with soil concentrations. The non-significant correlation of Pb contents in plant and soil supported our results that high concentration of Pb in plant leaves from urban area was due to automobile emission. Similar observation was also noted by other workers (Hernandez et al., 1987). They found significant positive correlation between Pb levels in rose-bay leaves and traffic density in Madrid, Spain.

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Zn and Fe in plants were highly significantly correlated with all the investigated heavy metals in plant. The Pb in soil was non-significantly correlated with Fe in soil, but with other metal it was highly significantly correlation and Zn in soil slightly to highly significantly correlated with all investigated metals in soil. These results were also supported by previous studies (Ijeoma et al., 2011).

4.5. CONCLUSIONS In this study, heavy metals (Pb, Zn, Fe, Cu, Cd and Sb) concentration in different plant leaves and soil samples collected from Quetta city and Botanical garden was investigated. After discussion following conclusions are made:

All the investigated plant species of Quetta city are contaminated by all the investigated heavy metals. Lead concentration in P. vera, V. vinifera and F. carica of polluted sites and Cd in all the plants in both sites was more than maximum limit in plants. All the investigated heavy metals showed seasonally variation in plants, but not in soil samples. Pb in plants was non-significantly correlated with Pb in soil. So it is concluded that heavy metals contamination in plant leaves is not only from soil uptake, their deposition is also associated with a wide range of sources such as vehicular emissions; re-suspended road dust and diesel generator sets; small scale industries (including battery production, metal products, metal smelting & cable coating industries); brick kilns;. These can all be important contributors to the contamination found in different plant species of urban area.

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Chapter 5

BIOINDICATION OF AIR POLLUTION IN RELATION TO BIOCHEMICAL AND PHYSIOLOGICAL ATTRIBUTES OF PLANTS

5.1. INTRODUCTION

The green plants act as a filter of air pollutants and they reduce the concentrations of air pollutants from the environment (Prajapati and Tripathi, 2008).The plants being constantly exposed to the environment, absorb, accumulate and integrate pollutants impinging on their foliar surfaces. Consequently they show visible or subtle changes depending on their sensitivity level (Sharma and Butler, 1973; Smith and Staskawicz, 1977). It was further reported that depending on their sensitivity level, plants show visible changes which would include alteration in the biochemical processes or accumulation of certain secondary plant metabolites. Due to air pollutants our vegetation is directly affected via leaves or indirectly via soil acidification (Steubing et al., 1989). Air pollutants also adversely affect the plant growth (Bhatia, 2006; Horsefall, 1998; Rao, 2006; Sodhi, 2005). The vehicular emission significantly reduced the productivity, leaf area and leaf dry weight of Guaiacum officinale, F. bengalensis and Eucalyptus sp., collected from the polluted sites of the city as compared to non-polluted site (control) (Bhatti and Iqbal, 1988). Air pollution can be estimated by several instruments but plant response is one of the best ways of estimating it. Air pollution tolerance index has been used for the bioindication of air pollution. Research revealed that air pollutants have greater impact on ascorbic acid, total chlorophyll content, leaf-extract pH and relative water content of leaf (Rao, 1979; Klumpp et al., 2000; Flowers et al., 2007; Hoque et al., 2007). Therefore, the present study was mainly aimed to investigate the bioindication of some common plants species of urban areas of Quetta city subjected to polluted air and also compare them with those grown in non-polluted environment of Quetta.

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5.2. MATERIALS AND METHODS

5.2.1. Leaf Sample Collection: This study was carried out during 2010 and 2011. Leaf samples of 14 different plant species of trees, shrubs and climbers of Quetta city (polluted site) and Botanical garden and Campus, University of Balochistan, Quetta (Control site) were collected from iso-ecological conditions (light, water and soil) following the standardized methods of Ara et al., (1996). The leaf samples were brought to the laboratory in polythene bags; weighed immediately and then processed for various physiological and biochemical attributes:-

5.2.2. Leaf Relative Water Content (RWC): RWC was estimated by taking fresh weight (FW) of selected plants one by one. The leaves were then immersed in water overnight, blotted dry and then weighed to get the turgid weight (TW). The leaves were then oven-dried for 24 h at 70ºC and reweighed to obtain the dry weight (DW). RWC was calculated by the formula given by Singh, (1977).

RWC = [(FW – DW) / (TW – DW)] x 100

5.2.3. Total Chlorophyll Content (TCC): Three grams of fresh leaves were put in 100% acetone (50 ml for each gram), homogenized (homogenizer B. Braun Melsungen, Germany) at 1000 rpm for one minute. The homogenate was then filtered through double layered cheese cloths and centrifuged at 2500 rpm for ten minutes. The supernatant was separated and the absorbance read at 400-700 nm by using Schimadzu UV-1700 Spectrophotometer. Chlorophyll a showed the maximum absorbance at 663 nm, chlorophyll b at 645 nm and the amount of these pigments were calculated according to the formulas given by Lichtentaler and Wellburn, (1985).

Chlorophyll a = 12.7DX663 – 2.69DX645 x V/1000W (μg g-1 f.wt.)

Chlorophyll b = 22.9DX645 – 4.68DX663 x V/1000W (μg g-1 f.wt.)

TCh: Chlorophyll a + b (μgg-1f.wt.), DX: Absorbance of the extract at the wavelength x nm, V: Total volume of the chlorophyll solution (ml) and W: Weight of the tissue extracts (g).

5.2.4. Leaf Extract pH: Five grams of fresh leaves was homogenized in 40 ml deionized water and centrifuged at 2500 rpm. Leaf-extract pH was measured with a

126 photo-volt pH meter at 25°C, using the Ag/AgCl Sure-Flow TM electrode, Model No. 9165BN.

5.2.5. Ascorbic Acid (AA) Content Analysis: Ascorbic acid content (mg g-1) was measured using spectrophotometer method as described by Bajaj and Kaur, (1981). One gm of the sample was taken into a test-tube, 4ml oxalic acid – EDTA extracting solution was added. Then 1 ml of orthophosphoric acid and 1 ml of 5% tetraoxosulphate (vi) acid was also added in it. To this solution 2 ml ammonium molybdate and then 3 ml of water was added. The solution was then allowed to stand for 15 min, after which the absorbance at 760 nm was measured with a Schimadzu UV-1700 spectrophotometer. The concentration of ascorbic acid in samples was then extrapolated from a standard ascorbic acid curve.

5.2.6. APTI Determination: The air pollution tolerance indices (APTI) of 14 plants species were determined following the method of Singh and Rao, (1983). The formula used for APTI is given as below:-

APTI = {[A (T+P) + R] /10}

Where A: Ascorbic acid content, T: total chlorophyll, P: pH of leaf-extract and R: Relative water content of leaf.

5.2.7. Gradation of APTIs: The spectrum of APTI was divided as four grades of air pollution tolerance referring to a previous study Liu et al., (1983). Tolerant (T or grade I), moderately tolerant (MT or grade II), intermediate tolerant (IT or grade III), and sensitive (S). The tolerance grades were defined as follows:

(1) Tolerant: APTI > mean of APTI + SD

(2) Moderately tolerant: mean of APTI

(3) Intermediate: mean of APTI - SD

(4) Sensitive: APTI< mean APTI - SD

5.2.8. Statistical Analysis: The data obtained were statistically analyzed by using t- test at the significance level of P<0.05 and 0.01.

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5.3. RESULTS

The results about the effect of air pollution in relation to biochemical and physiological attributes of plants grown in Quetta and their tolerance index are illustrated in Tables 5.1 to 5.6 and Figs 5.1 to 5.4.

Table 5.1: Ascorbic acid (mg g-1) concentration in the plant leaves of polluted and non polluted sites of Quetta city.

Name of Plants Non Polluted Polluted Ave S.D Ave S.D Inc % t mean S.D Melia azadirach L. 0.10 0.02 0.15 0.02 31.1 8.05** Ficus carica L. 0.15 0.02 0.20 0.02 27.9 6.40** Vitis vinifera L. 0.11 0.03 0.15 0.02 26.1 4.52** Prunus armeniaca L. 0.13 0.03 0.17 0.02 20.0 3.76** Punica granatum L. 0.12 0.02 0.15 0.01 19.6 3.39* Rosa indica L 0.11 0.02 0.14 0.01 19.5 3.98** Pistacia vera L. 0.12 0.03 0.14 0.01 18.6 3.01* Elaeagnus angustifolia L. 0.17 0.03 0.21 0.01 16.1 4.98** Morus nigra L. 0.13 0.02 0.15 0.02 15.6 4.02** Pinus halepensis Miller. 0.17 0.01 0.19 0.01 14.9 4.46** Eucalyptus tereticornis L. 0.14 0.03 0.16 0.01 14.7 4.02** Fraxinus excelsior L. 0.16 0.02 0.18 0.02 14.6 5.27** Morus alba L. 0.16 0.02 0.18 0.02 14.6 3.01* Robinia pseudoacacia L. 0.14 0.02 0.15 0.01 4.4 3.98** Mean 0.14 0.02 0.17 0.02 18.4 3.03* *: Slightly significant at p < 0.05,**: highly significant at p < 0.01,Inc %: Increasing percentage, S.D: Standard deviation and t: Calculated values in t-test.

Percentage increase of ascorbic acid presented in Table 5.1 was recorded in the range of 4.4 to 31.1%, with M. azadirach had the largest and R. pseudoacacia showed the least percentage increase. However over all percentage increase was found to be 18.4% in polluted sites plants. Statistical analysis using t-test indicated that out of 14 plant species, 03 i.e. M. alba, P. vera and P. granatum showed slightly significant (P<0.05) differences in their ascorbic acid (AA) contents. All the other remaining species showed highly significantly (P<0.01) variation between polluted and non-polluted site. Over all average ascorbic acid (AA) contents in polluted site plant species remained slightly significantly (P<0.05) as compare to non-polluted sites. In general ascorbic acid contents were in the range of 0.14 - 0.21mg g-1 in the leaves of polluted site plant species and 0.10 - 0.17 mg g-1 in non-polluted site.

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Table 5.2: Total chlorophyll content (μg g-1 f.wt.) in the plant leaves of polluted and non- polluted sites of Quetta city.

Name of Plants Non polluted Polluted Ave S.D Ave S.D Dec % t Pistacia vera L. 42.0 2.7 26.8 1.3 57.0 9.6** Prunus armeniaca L. 33.7 1.2 22.2 1.7 51.8 16.3** Elaeagnus angustifolia L. 31.6 2.7 22.0 1.0 43.6 6.1** Eucalyptus tereticornisL. 34.0 1.6 23.8 1.8 43.3 10.8** Punica granatum L. 51.1 1.8 36.0 1.0 42.2 14.7** Rosa indica L 35.6 1.4 25.4 1.0 40.2 12.6** Morus nigra L. 42.1 1.6 30.0 1.4 40.1 13.2** Ficus carica L. 73.4 2.8 54.4 1.5 35.0 11.7** Morus alba L. 76.0 1.2 60.7 0.4 25.2 22.3** Vitis vinifera L. 55.3 2.0 47.1 0.8 17.4 14.2** Melia azadirach L. 76.9 1.0 65.7 0.6 17.1 18.5** Pinus halepensis Miller. 81.3 2.1 72.4 1.7 12.4 6.2** Fraxinus excelsior L. 82.2 2.1 73.4 2.0 12.0 16.5** Robinia pseudoacacia L. 70.6 1.5 63.4 0.5 11.4 19.5** Mean 56.1 20.0 44.5 19.8 26.1 10.7**

*: Slightly significant at p < 0.05, **: highly significant at p < 0.01, Dec %: Decreasing percentage, S.D: Standard deviation and t: Calculated values in t-test.

Percentage of total chlorophyll contents reduction (Table 5.2) was in the range of 11.4 - 57.0 % with Pistacia vera had the largest reduction and Robinia pseudoacacia showed the least. However, over all percentage decrease was found to be 26.1 %. Statistical analysis using a t-test indicated that all the plant species had highly significant (P<0.01) variation between polluted and non-polluted site. Over all average decreasing percentage of total chlorophyll contents in polluted sites plant species was highly significant (P<0.01) with respect to non-polluted sites. In general total chlorophyll content in different plant species of non-polluted sites was in the range of 31.6 - 82.2μg g-1 while in plants from polluted sites it was 22.0 - 73.4 μg g-1.

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Table 5.3: pH level in the plant leaves of polluted and non-polluted sites of Quetta city

Name of Plants Non polluted Polluted Ave S.D Ave S.D Inc % t Morus alba L. 5.9 1.7 4.2 0.8 29.3 3.85** Rosa indica L 6.8 1.9 4.8 1.0 28.7 3.36* Prunus armeniaca L. 5.8 1.7 4.1 1.0 28.6 2.95* Pistacia vera L. 5.8 1.6 4.1 0.6 28.6 4.65** Robinia pseudoacacia L. 6.5 1.7 4.8 0.8 25.9 3.63* Melia azadirach L. 6.9 1.8 5.2 0.9 25.5 3.24* Punica granatum L. 5.9 1.4 4.5 0.8 23.6 3.22* Pinus halepensis Miller. 6.2 1.4 4.8 1.1 22.9 3.32* Eucalyptus tereticornis L. 6.0 1.3 4.6 0.6 22.1 3.58* Elaeagnus angustifolia L. 5.9 1.2 4.7 0.3 20.5 5.57** Fraxinus excelsior L. 6.0 1.2 4.8 0.8 20.1 3.76** Morus nigra L. 6.1 1.1 5.0 0.4 18.2 5.31** Ficus carica L. 5.5 0.9 4.6 0.5 16.1 3.04* Vitis vinifera L. 5.2 0.7 4.5 1.0 13.3 3.36** Mean 6.0 0.5 4.6 0.3 23.3 9.39**

*: Slightly significant at p < 0.05, **: highly significant at p < 0.01, Inc %: Increasing percentage, S.D: Standard deviation and t: Calculated values in t-test.

The increasing percentage of pH level in the plant leaves of non-polluted sites was in the range of 13.3-29.3 % with M. alba had the highest increasing percentage and V. vinifera showed the lowest as presented in Table 5.3. Statistical analysis using t-test indicated that out of 14 plant species, 06 plants i.e. M. alba, P. vera, E. angustifolia, F. excelsior, M. nigra and V. vinifera showed highly significant (P<0.01) differences in their pH level between non-polluted and polluted sites. All the other species showed slightly significant (P<0.05) variation. Overall average increasing percentage of pH contents in plant leaves from non-polluted sites had highly significant (P<0.05) variation from polluted sites. The leaf-extract pH was found more acidic (5.2 to 4.1) in polluted site as compared to non-polluted site (6.9 to 5.2).

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Table 5.4: Relative Water Content (%) in plant leaves of polluted and non- polluted sites of Quetta city

Name of Plants Non –polluted Polluted Ave S.D Ave S.D Inc % t Ficus carica L. 61.6 2.0 72.6 3.0 15.2 6.3** Fraxinus excelsior L. 76.9 1.4 90.5 2.0 15.1 11.9** Morus alba L. 55.9 1.8 64.9 1.4 13.9 10.9** Pistaci avera L. 73.3 0.6 84.9 2.7 13.7 7.4** Melia azadirach L. 64.3 1.0 73.1 2.0 12.1 7.8** Punica granatum L. 77.6 1.0 86.2 2.5 10.0 6.1** Robinia pseudoacacia L. 82.3 1.2 90.8 2.7 9.4 5.6** Pinus halepensis Miller. 80.4 1.1 88.8 2.0 9.4 7.2** Rosa indica L 76.9 0.8 84.7 1.6 9.2 8.5** Morus nigra L. 77.8 0.6 85.1 1.6 8.5 7.9** Vitis vinifera L. 55.2 1.5 60.2 3.2 8.3 7.1** Elaeagnus angustifolia L. 80.5 1.1 87.3 2.1 7.8 5.7** Prunus armeniaca L. 79.9 1.0 86.6 1.7 7.7 6.9** Eucalyptus tereticornis L. 101.3 3.2 105.1 1.8 3.7 2.1*

Mean 75.2 12.2 82.31.9 8.6 1.7*

*: Slightly significant at p < 0.05,**: highly significant at p < 0.01,Inc %: Increasing percentage, S.D: Standard deviation and t: Calculated values in t-test.

The percentage increase of RWC in the plant leaves of polluted sites was in the range of 3.7 - 15.2 % with F. carica had the largest percentage increase and E. tereticornis showed the least (Table 5.4). Statistical analysis using a t-test indicated that out of 14 plant species, E. tereticornis showed slightly significant (P<0.05) differences in their RWC. All the other species had highly significant (P<0.01) variation between polluted and non-polluted site. Over all average RWC in polluted sites plant species was slightly significant (P<0.05). In general RWC in different plant species of non-polluted site was in the range of 55.2 - 101.3 % while in plants from polluted site it was 64.9 - 105.1 %.

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Table 5.5: Air Pollution Tolerance Index (APTI) of different Plant species of polluted and non-polluted sites of Quetta city

Name of Plants Non- polluted Polluted Ave S.D Ave S.D Inc % Fraxinus excelsior L. 9.1 1.2 10.5 1.1 13.5 Ficus carica L. 7.3 1.3 8.5 0.8 13.5 Melia azadirach L. 7.3 1.2 8.4 0.9 12.9 Pistacia vera L. 7.9 1.1 8.9 0.8 11.7 Morus alba L. 6.9 1.4 7.7 1.0 10.5 Pinushalepensis Miller. 9.5 0.6 10.4 0.9 8.5 Punica granatum L. 8.5 1.2 9.2 0.9 8.5 Rosa indicaL 8.2 0.1 8.9 0.8 8.2 Robinia pseudoacacia L. 9.4 1.2 10.1 1.0 7.7 Morus nigra L. 8.4 1.3 9.0 0.9 7.1 Prunus armeniaca L. 8.5 1.3 9.1 0.8 6.4 Elaeagnus angustifolia L. 8.7 0.9 9.3 0.7 6.3 Vitis vinifera L. 6.3 1.2 6.7 1.0 6.2 Eucalyptus tereticornis L. 10.6 1.3 11.1 0.9 4.4 Mean 8.4 1.2 9.1 1.1 8.3 Inc%: Increasing %

The percentage increase of APTI as shown in Table 5.5 was in the range of 4.4 - 13.5 % with F. excelsior and F. carica had the maximum percentage increase and E. tereticornis showed the least. The overall APTI of all the plant species was higher in polluted site plants (9.1) than those of non-polluted sites (8.4). However, differences among various plant species also exist. It also ranges from 6.7-11.1 in the polluted sites plant species and 6.3 - 10.6 in non-polluted site.

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Table 5.6: Different Plants Tolerance gradation to the air pollution

Name of Plants Average APTI Gradation

Eucalyptus tereticornis L. 10.8 T I Pinus halepensis Miller. 9.9 T I Fraxinus excelsior L. 9.8 MT II Robinia pseudoacacia L. 9.8 MT II Elaeagnus angustifolia L. 9.0 MT II Punica granatum L. 8.9 MT II Prunus armeniaca L. 8.8 MT II Morus nigra L. 8.7 IT III Rosa indica L 8.5 IT III Pistacia vera L. 8.4 IT III Ficus carica L. 7.9 IT III Melia azadirach L. 7.8 IT III Morus alba L. 7.3 S IV Vitis vinifera L. 6.5 S IV

T: tolerant (I), MT: moderately tolerant (II), IT: intermediate tolerant (III) and S: sensitive (IV)

The tolerance gradation of plant species growing in Quetta city was described in Table 5.6. It was found that out of 14 plant species 02 plants i.e. Eucalyptus tereticornis and Pinus halepensis were tolerant (T), other 05 i.e. Fraxinus excelsior, Robinia pseudoacacia, Punica granatum, Prunus armeniaca and Elaeagnus angustifolia were Moderately tolerant (MT). An other 05 species Pistacia vera, Rosa indica, Melia azadirach., Morusnigra and Ficus carica were Intermediate tolerant (IT) and other remaining 02 species i.e. Morus alba and Vitis vinifera were Sensitive (S) and their average APTI was in the range of 9.9 - 10.8% (Tolerant), 8.8 - 9.8% (Moderately tolerant), 7.8 - 8.7% (Intermediate tolerant) and 6.5 - 7.3 % (Sensitive), respectively.

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0.25

0.2 1) - 0.15

0.1

0.05

0 Ascorbic acid (mg (mg g Ascorbic acid

Polluted Fig 5.1. Comparison of Ascorbic acid between polluted and non- polluted sites plants Non-polluted

Results presented in Fig 5.1 indicated that over all Ascorbic acid contents in all the investigated plant species was found high from polluted site plant species then from non-polluted sites.

90 1 1

- 80 g g g

μ 70 60 50 40 30 20 10

0 Totalchlorophyll content (

Fig 5.2. Comparison of Total chlorophyll content (μg g-1 f.wt.) Polluted between polluted and non-polluted sites plants Non-polluted

Total chlorophyll content shown in Fig 5.2 exhibited that all the plant species from non-polluted sites showed high concentration of total chlorophyll as compared to polluted site plant species.

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8 7 6 5 4 3

PH PH level 2 1 0

Fig 5.3. Comparison of pH level between polluted and non- Polluted polluted sites plants Non-polluted

Data illustrated in Fig 5.3 revealed that in all the investigated plant species leaves extract high pH was found from non-polluted site plant species as compared to polluted site.

120 100 80 60 40 20

0 Relative Water Content (%) Content Water Relative

Fig 5.4. Relative Water Content (%) in plant leaves of polluted and Polluted non-polluted sites Non-polluted

Relative water contents shown in Fig 5.4 indicated that except one plant species all the other plant species showed high percentage of relative water contents from polluted sites as compare to non-polluted sites plants.

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5.4. DISCUSSION

Ascorbic acid is a strong reducer and plays important roles in photosynthetic carbon fixation (Pasqualini et al., 2001), with the reducing power directly proportional to its concentration (Lewin, 1976). So due to aforementioned properties it has been given top priority in estimation of air pollution tolerance indices and used as a multiplication factor in the formula. Statistical analysis exhibited that ascorbic acid (AA) contents from polluted sites plant species remain significant (P<0.05) as compared to non-polluted sites. However, variation among different plant species also exists. The AA in P. vera, P. granatum and M. alba was found slightly significant at P< 0.05, while it showed highly significant at P< 0.01 for rest of the plant species as compared to non-polluted sites plants. Similar observations were also noted by Liu & Ding, (2008). The percentage increase of AA from polluted sites plants was also high with respect of non-polluted sits plant species. The maximum and minimum percentage increase was found in M. azadirach and R. pseudoacacia, respectively. Similar observations were also recorded by Agbaire and Esiefarienrhe, (2009). Research revealed that AA is a naturally occurring organic compound with antioxidant properties. It reacts with oxidants such as the hydroxyl radical formed, from hydrogen peroxide. Such radicals are damaging to plants and animals at the molecular level due to their possible interaction with nucleic acids, proteins, and lipids Chen et al., (1990). AA plays an important role in cell wall synthesis, defense, and cell division (Conklin, 2001).

Research revealed that TCC is considered as an important factor for the calculation of air pollution tolerance index because it is related to AA productivity and AA is concentrated mainly in chloroplasts. The total chlorophyll content (TCC) from polluted sites plants showed significantly (P<0.01) less as compared with non- polluted plants. The highest percentage decrease of TCC was found in P. vera and the lowest in R. pseudoacacia from polluted sites. The overall percentage decrease of TCC in all plant species of polluted sites might be due to air pollutant in the city area. Similar observation was also recorded by Agrawal et al., (2003). They reported that the crop which was continuously exposed to alleviated concentration of NO2, SO2 and

O3 has low chlorophyll contents. Lerman, (1972) also indicated that due to dust fall on plant leaves, stomata close and exchange of gases becomes reduced which caused the reduction of total chlorophyll contents in plant leaves. Present findings are also in

136 line with the results recorded by Agbaire and Esiefarienrhe, (2009) and Chauhan, (2010). They explained that the low concentration of total chlorophyll contents in the polluted sites was due to acidic pollutants like SO2 that cause phaeophytin formation by acidification of chlorophyll.

Leaf-extract pH is very important parameter which is used in air pollution tolerance index (APTI), because it increases the efficiency of conversion of hexoses sugar in to the ascorbic acid at higher level. It has good correlation with the sensitivity of the plant to the air pollution at lower level. Further that photosynthetic activity strongly depends on the pH level. At low level photosynthetic activity also becomes reduced (Türk and Wirth, 1975). All the plant samples collected from polluted and non-polluted sites exhibited highly significant (P<0.01) reduction in their pH values. However, variation among different plant species also exists. The leaf-extract was found more acidicin polluted sites plant species as compared to non- polluted site. Statistical analysis of the data indicated that leaf-extract pH of F. excelsior, V. vinifera, P. vera, M. nigra, M. alba and E. angustifolia were highly significantly different (P< 0.01), while, it was only significantly different (P< 0.05) for rest of the plants between polluted and non-polluted sites. Highest percentage increase of pH of leaf-extract was found in M. alba and lowest in V. vinifera. This might be due to the presence of SO2 and NO, NO2, NOx in the ambient air, which causes the change of leaf-extract pH towards more acidic range. Similar observation was also noted by Swami et al., (2004) and Chauhan, (2010).

The relative water content (RWC) in all the investigated plant leaf samples were found to be significantly (P<0.05) high from polluted sites plants when compared with their non-polluted samples. However, variation among different plant species also exists. These finding are also supported by the observations explained by Agbaire and Esiefarienrhe, (2009). The maximum percentage increase of RWC was in F. carica and minimum in E. terticornis from polluted sites. Similar observation was also reported by Paulsamy et al., (2000) in A. indica of polluted site. High water content in plant leave may help to maintain its physiological balance under air pollution and stress condition (Dedio, 1975).

The APTI of all the plants species were significantly higher in polluted than those of non-polluted sites. However, differences among various plant species also

137 exist. These findings are also in agreement with the results depicted by Agbaire, (2009) and Agbaire and Esiefarienrhe, (2009). The highest percentage increase of APTI in polluted site was in F. carica and F. excelsior respectively and lowest found in E. terticornis. These conclusions were also supported by earlier researchers (Han et al., 1995). The tolerance gradation of plant species growing in Quetta city were found that out of 14 species 2 were tolerant (T), 5 were Moderately tolerant (MT), other 5 were Intermediate tolerant (IT) and remaining 2 were Sensitive (S). Plants which have higher index value are tolerant to air pollution and can be caused as sink to mitigate pollution, while plants with low index value show less tolerance and can be used to indicate levels of air pollution. These findings are also in accordance with Singh and Rao, (1983).

5.5. CONCLUSIONS

This study provides useful information to select those tolerant plant species which are fit for landscape on sites continuously exposed to air pollutants. Species ranked as ‘sensitive’ should be avoided. Base on APT index, the aforementioned experimental plants could be ranked as under:-

• Pinus halepensis (Miller.) and Eucalyptus tereticornis L. are proved to be highly tolerant species. • Fraxinus excelsior L.; Robinia pseudoacacia L.; Punica granatum L.; Prunus armeniaca L. and Elaeagnus angustifolia L. are classified as a moderately tolerant. • Pistacia vera L.; Rosa indica L.; Melia azadirach L.; Morus nigra L. and Ficus carica L. are considered as intermediate tolerant species. • Vitis vinifera L. and Morus alba L. are found to be sensitive species.

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Chapter 6

EFFECT OF AIR POLLUTION ON THE LEAF MORPHOLOGY OF DIFFERENT PLANT SPECIES OF QUETTA CITY

6.1. INTRODUCTION

Leaf is the most sensitive part to be affected by air pollutants instead of all other plant parts (stem and roots). The sensitivity rests on the fact that the major portions of the important physiological processes are concerned with leaf. Therefore, the leaf at its various stages of development, serves as a good indicator to air pollutants. Pollutants came from the auto emission can directly affect the plant foliage by entering in to the leaf, destroying individual cells, and reducing the plant ability to produce food. Urban air pollution is a major environmental problem, mainly in the developing countries (Mage et al., 1996). Air pollution due to vehicular emission mostly arises from cars, buses, minibuses, wagons, rickshaws, motorcycles and trucks these resources produce the varieties of pollutants (oxides of nitrogen and sulphur, hydrocarbon, ozone, particulate matters, hydrogen fluoride, peroxyacyl nitrates, etc.) into the environment which not only put adverse effect on the health of human beings and animals, the trees and crops are not free from it Kalandadze, (2003). Plants need special protection because they are not only a source of food but are also helpful in cleaning the environment. Some researcher Bhatti & Iqbal, (1988}; Darley et al., (1963); Godzik & Halbwacks, (1986); Gupta & Ghouse, (1988); Inamdar & Chaudahri, (1984); Iqbal, (1985); Krause & Dochinger, (1987); Karenlampi, (1986) and Ninova et al., (1983), reported the effects of air pollution on the morphology and anatomy of different plants species. The plants which are sensitive to air pollutants can showed changes in their morphology, anatomy, physiology and biochemistry as reported by many other authors (Azevedo, 1995; Chaves et al., 2002; Gabara et al., 2003; Hara, 2000; Moraes et al., 2000; Neufeld et al., 1985; Reig-Armiñana et al., 2004; Silva et al., 2005 “b”). The aim of present study was to investigate the effect of air pollutants on the leaf morphological characteristics of some common plant species growing along the roads of Quetta city.

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6.2. MATERIALS AND METHODS

6.2.1. Samples collection: This study carried out during 2010 and 2011. Leaf samples of different plant species (trees, shrubs and climbers) including Elaeagnus angustifolia L., Eucalyptus tereticornis L., Ficus carica L., Fraxinus excelsior L., Pistacia vera L., Prunus armeniaca L., Punica granatum L., Melia azadirach L., Morus alba L., Morus nigra L., Robinia pseudoacacia L., Rosa indica L., and Vitis vinifera L. from Quetta city as polluted site and Botanical garden and Campus University of Balochistan, Quetta as control site were collected. The samples were taken from iso-ecological conditions (light, water and soil) by following the standardized methods of Ara et al., (1996). 30 leaf samples were taken from each individual of a species from 3 different height positions on the plant (10 leaves from each position), representing 3 discrete leaf age classes, i.e. a young, expanding leaf on the upper portion of the plant; a mature, fully developed leaf near the middle portion of the plant; and an older, mature to senescing leaf on the lower portion of the plant throughout the plant canopy to give representative average sample. Quantitative characters of the leaves such as, leaflet length, width, area and length of petiole were recorded seasonally/periodically at regular interval of three months viz, (March-May, Jun-August, and September-November). All the measurements were based on three replicates.

6.2.2. Leaf morphological changes: Leaf morphological characteristics including leaf abnormalities of both young and mature leaves were observed on-both sites (polluted and non-polluted), with the following criteria: change in color (chlorosis, browning, yellowing, spotting or change in the leaf’s normal pigment) and shape (normal shape or deformed/modified). Leaf length, breadth, area and length of petiole were determined by using leaf area meter and graph paper method and petiole length was also recorded by scale in centimeter (Chippendale, 1973). 6.2.3. Statistical analyses: The standard deviation values of the means were calculated for a comparison of polluted and non-polluted sites. To determine the significance of the samples a paired t-test was performed (Steel & Torrie, 1980). 6.2.4. Percentage increasing & decreasing: Percentage increasing & decreasing of foliage length, width area and length of petioles during different seasons was calculated according to the formula used by Syed & Iqbal, (2008).

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6.3. RESULTS

The effect of air pollution on foliage morphology was evaluated by calculating foliage length, width and area, length of petiole and gross leaf morphological changes (Color and shape) at different growth stages. All the observations are described in Table 6.1 – 6.18 and Figs 6.1 – 6.6. Table 6.1: Gross leaf morphological changes of the different plant species and growth stages growing at polluted and non-polluted of Quetta city

Name of plant Growth Color Shape Stage NP P NP P Elaeagnus angustifolia L. Young Light Green Whitish Typical Deformed Mature Light Green Whitish Typical Deformed Eucalyptus tereticornis L. Young Dark Green Light Green Typical Deformed Mature Dark Green Browning Typical Deformed Ficus carica L. Young Dark Green Light Green Typical Deformed Mature Dark Green Light Green Typical Deformed Fraxinus excelsior L. Young Light Green Light Green Typical Typical Mature Dark Green Yellowish Typical Deformed Pistacia vera L. Young Light Green Light Green Typical Deformed Mature Dark Green Light Green Typical Deformed Prunus armeniaca L. Young Light Green Light Green Typical Deformed Mature Dark Green Yellowish Typical Deformed Punica granatum L. Young Dark Green Dark Green Typical Deformed Mature Dark Green Dark Green Typical Deformed Melia azadirach L. Young Dark Green Light Green Typical Typical Mature Dark Green Light Green Typical Deformed Morus alba L. Young Dark Green Light Green Typical Deformed Mature Dark Green Light Green Typical Deformed Morus nigra L. Young Light Green Light Green Typical Deformed Mature Light Green Browning Typical Deformed Robinia pseudoacacia L. Young Light Green Light Green Typical Typical Mature Dark Green Light Green Typical Deformed Rosa indica L. Young Light Green Light Green Typical Deformed Mature Dark Green Browning Typical Deformed Vitis vinifera L. Young Light Green Light Green Typical Deformed Mature Dark Green Yellowish Typical Deformed NP: Non-polluted, P: Polluted

Results about the gross leaf morphological changes of the different plant species and growth stages growing at two different sites (polluted and non-polluted) are given in Table 6.1. The results indicates that at non-polluted site color of leaves were light green to dark green, while at polluted site they became Light Green, Whitish, Browning and Yellowish. The shape of leaves changed from Typical to Deformed at the polluted site.

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Pistacia vera L. Pistacia vera L. Polluted ste Non-polluted site

Morus alba L. Morus alba L. Polluted site Non-polluted site

Fig. 6.1. Two plant species of polluted and non polluted site

Rosa indica L. Rosa indica L. Polluted site Non-polluted site

Vitis vinifera L. Vitis vinifera L. Polluted site Non-polluted site

Fig. 6.2. Two plant species of Polluted and Non polluted site

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Elaeagnus angustifolia L. Elaeagnus angustifolia L. polluted ste Non Polluted site

Fraxinus excelsior L. Fraxinus excelsior L. Non-polluted ste Polluted site

Fig. 6.3. Two plant species of polluted and non polluted site

Punica granatum L. Punica granatum L. Polluted ste Non-polluted ste

Eucalyptus tereticornis L. Eucalyptus tereticornis L. Polluted ste Polluted ste

Fig. 6.4. Two plant species of polluted and non polluted site

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Ficus carica L. Non-polluted ste Ficus carica L. polluted ste

Melia azadirach L. Melia azadirach L. polluted ste Non-polluted ste

Fig. 6.5. Two plant species of polluted and non polluted site

Robinia pseudoacacia L. Robinia pseudoacacia L. Polluted site Non-Polluted site

Fig. 6.6. Two plant species of polluted and non polluted site

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Effect of air pollution on foliage length: Results regarding to Effect of air pollution on foliage length was reported in Tables 6.2, 6.3 and 6.4.

Table 6.2: Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during spring season

Name of plants Length of Foliage (cm) NP S.D. P S.D. Rd% t Rosa indica L. 2.6 (0.6) 1.7 (0.3) 53.9 3.20*** Punica granatum L. 4.5 (1.0) 3.0 (1.0) 50.7 2.92*** Melia azadirach L. 3.7 (0.8) 2.5 (0.8) 48.0 3.23*** Morus nigra L. 7.1 (1.5) 5.0 (1.4) 41.2 2.24* Elaeagnus angustifolia L. 5.2 (1.6) 3.8 (1.6) 38.7 2.04* Pistacia vera L. 8.0 (2.0) 6.1 (1.5) 31.1 1.91* Morus alba L. 7.2 (2.1) 5.5 (2.1) 30.4 2.17* Robinia pseudoacacia L. 4.5 (1.1) 3.5 (1.2) 30.3 2.15* Prunus armeniaca L. 5.1 (1.3) 4.1 (1.0) 25.2 1.93 * Ficus carica L. 12.9 (2.2) 10.7 (1.9) 20.9 2.18* Fraxinus excelsior L. 6.3 (1.5) 5.2 (1.0) 20.2 2.16* Vitis vinifera L. 9.5 (1.0) 8.3 (1.8) 14.6 2.56** Eucalyptus tereticornis L. 11.0 (1.2) 9.9 (1.6) 11.1 1.95 *

Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001 and Rd%: Reducing % at polluted site During spring, the percentage of leaf length reduction (Table 6.2) was in the range of 11.1-53.9 % with E. tereticornis had the largest reduction and R. indica showing the least. Statistical analysis using a t-test indicated that out of thirteen plant species, 03 plants viz. R. indica, P. granatumand, M. azadirach showed very highly significant (P<0.001) differences in their foliage length. Other one species i.e. V. vinifera showed highly significant (P<0.01) variation. All other plant species had slightly significant (P<0.05) differences in their foliage length during spring between polluted and non-polluted sites.

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Table 6.3: Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during summer season

Name of plants Length of Foliage (cm) NP S.D. P S.D. Rd% t Punica granatum L. 8.0 (1.3) 4.4 (1.0) 79.5 2.53** Rosa indica L. 3.9 (1.0) 2.3 (0.5) 67.0 2.77*** Melia azadirach L. 5.3 (0.6) 3.4 (0.2) 55.6 2.62** Morus nigra L. 10.7 (2.9) 7.0 (1.7) 52.5 2.02* Robinia pseudoacacia L. 8.0 (1.2) 5.4 (1.4) 47.6 2.55** Elaeagnus angustifolia L. 7.9 (1.6) 5.4 (0.7) 45.9 2.20* Morus alba L. 10.1 (3.0) 7.3 (1.8) 38.7 2.05* Pistacia vera L. 13.4 (2.5) 9.8 (2.2) 37.5 2.79*** Eucalyptus tereticornis L. 15.8 (2.6) 12.0 (1.6) 32.4 3.27*** Prunus armeniaca L. 8.2 (1.4) 6.2 (1.1) 31.5 3.06*** Fraxinus excelsior L. 10.3 (2.0) 7.9 (1.8) 30.6 2.04* Ficus carica L. 17.4 (3.5) 13.4 (3.3) 29.7 2.46** Vitis vinifera L. 12.5 (2.8) 10.3 (2.5) 21.6 2.52**

During summer, the percentage of leaf length reduction (Table 6.3) was in the range of 21.6-79.5% with P. granatum had the highest reduction and V. vinifera showed the lowest. Statistical analysis using t-test indicated that out of 13 plant species, 4 plants i.e. R. indica, P. vera, E. tereticornis and P. armeniaca showed very highly significant (P<0.001) differences in their foliage length. Other five species viz. P. granatum, M. azadirach, R. pseudoacacia, F. carica and V. vinifera showed highly significant difference (P<0.01). All the other remaining plant had slightly significant (P<0.05) variation in their foliage length during summer.

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Table 6.4: Effect of air pollution on the length of foliage in different plant species growing at Polluted and non-polluted sites of Quetta city during autumn

Name of plants Length of Foliage (cm) NP S.D. P S.D. Rd% t Punica granatum L. 8.1 (1.3) 4.5 (1.0) 80.4 2.48** Rosa indica L. 4.2 (1.1) 2.4 (0.6) 74.8 2.46** Melia azadirach L. 5.6 (0.6) 3.6 (0.2) 56.9 2.55** Robinia pseudoacacia L. 8.7 (1.2) 5.6 (1.4) 56.2 2.53** Morus nigra L. 11.0 (3.4) 7.1 (1.7) 55.1 1.92 * Elaeagnus angustifolia L. 8.1 (1.6) 5.5 (0.7) 48.6 2.19* Morus alba L. 10.5 (2.5) 7.4 (1.8) 42.3 2.72*** Pistacia vera L. 14.0 (2.0) 9.9 (2.3) 41.1 2.23* Eucalyptus tereticornis L. 15.9 (2.6) 12.0 (1.7) 33.3 3.35*** Fraxinus excelsior L. 10.4 (2.0) 7.9 (1.8) 32.5 1.85 * Prunus armeniaca L. 8.3 (1.5) 6.2 (1.2) 32.2 2.96*** Ficus carica L. 17.6 (3.6) 13.5 (3.4) 31.1 2.44** Vitis vinifera L. 12.8 (2.8) 10.4 (2.5) 22.4 2.52**

During autumn, the percentage of leaf length decreasing (Table 6.4) was in the range of 22.4 - 80.4%, with P. granatum had the largest reduction and V. vinifera indicating the least. Statistical analysis using t-test revealed that out of 13 plant species, 03 plants like; M. alba, E. tereticornis and P. armeniaca showed very highly significant (P<0.001) differences in their foliage length. Other 06 plant species i.e. P. granatum, R. indica, M. azadirach, R. pseudoacacia, F. carica, and V. vinifera showed highly significant difference (P<0.01). All the other plant species had slightly significant (P<0.05) variation in their foliage length during autumn between polluted and non-polluted sites.

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Effect of air pollution on foliage width: Air pollution effect on the foliage width, their reducing percentage and significant levels in different plant species growing at polluted and non-polluted sites during spring, summer and autumn are reflected in Table 6.5-6.7, respectively.

Table 6.5: Effect of air pollution on the width of foliage in different plant species growing at polluted and non-polluted sites of Quetta city during spring

Name of plants Width of Foliage (cm) NP S.D P S.D Rd% t Elaeagnus angustifolia L. 2.5 (0.7) 1.8 (0.3) 40.9 2.87*** Rosa indica L. 2.1 (0.6) 1.6 (0.3) 37.2 2.31* Prunus armeniaca L. 5.9 (1.5) 4.3 (1.2) 35.5 2.27* Robinia pseudoacacia L. 2.7 (0.7) 2.0 (0.4) 32.4 2.22* Melia azadirach L. 1.8 (0.4) 1.4 (0.4) 26.1 0.41 ns Ficus carica L. 11.4 (2.4) 9.4 (2.4) 21.7 1.90* Morus alba L. 5.4 (1.0) 4.6 (0.6) 18.3 0.73 ns Vitis vinifera L. 11.1 (1.2) 9.6 (0.9) 15.5 2.13* Pistacia vera L. 5.1 (1.9) 4.5 (1.9) 15.3 0.11 ns Eucalyptus tereticornis L. 2.9 (0.7) 2.6 (0.5) 14.9 0.60 ns Punica granatum L. 5.7 (0.6) 5.0 (0.8) 13.9 3.29*** Morus nigra L. 5.7 (0.5) 5.0 (0.8) 13.9 3.29*** Fraxinus excelsior L. 2.6 (0.2) 2.4 (0.3) 11.0 2.97***

During spring, the percentage of leaf width reduction (Table 6.5) was in the range of 11.0 - 40.9 %, with E. angustifolia showed the maximum reduction and F. excelsior indicating the minimum. Statistical analysis (t-test) exhibited that 04 plant species, viz. E. angustifolia, P. granatum, M. nigraand F. excelsior, showed very highly significant (P<0.001) differences in their foliage length. Other four species (R. indica, P. armeniaca, R. pseudoacacia, F. carica and V. vinifera) showed slightly significant differences. All the other remaining four species (M. azadirach, M. alba, P. vera and E. tereticornis) had non-significant variation in their foliage width during spring between polluted and non-polluted sites.

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Table 6.6: Effect of air pollution on the width of foliage in different plant species growing at polluted and non-polluted sites of Quetta city during summer Name of plants Width of Foliage (cm) A S.D. B S.D. Rd% t Prunus armeniaca L. 8.4 (1.3) 5.6 (1.0) 51.2 1.94 * Elaeagnus angustifolia L. 3.8 (0.9) 2.6 (0.5) 47.8 2.47** Rosa indica L. 2.5 (0.9) 1.7 (0.6) 46.0 2.10 * Robinia pseudoacacia L. 3.4 (0.9) 2.5 (0.8) 35.9 2.17* Morus alba L. 7.9 (2.2) 5.9 (1.4) 33.9 1.98 * Ficus carica L. 13.5 (3.7) 10.3 (3.6) 31.6 1.91 * Melia azadirach L. 2.4 (0.5) 1.9 (0.2) 29.7 3.57*** Punica granatum L. 7.9 (2.0) 6.2 (1.6) 29.1 1.95 * Morus nigra L. 7.9 (2.0) 6.2 (1.6) 29.1 1.95 * Vitis vinifera L. 12.8 (2.6) 10.0 (2.9) 27.4 2.26* Eucalyptus tereticornis L. 4.2 (1.1) 3.3 (0.3) 26.7 1.75 * Fraxinus excelsior L. 3.9 (1.1) 3.1 (0.6) 25.9 2.16* Pistacia vera L. 6.7 (2.0) 5.7 (1.9) 17.9 1.89 *

During summer, the percentage of leaf width decreasing (Table 6.6) was found to be 17.9 - 51.2 %, with P. armeniaca showing the maximum decreasing percentage and P. vera showed the least. Statistical analysis using t-test exhibited that out of thirteen plant species, one (M. azadirach) showed very highly significant (P<0.001) difference in their foliage length. Other one plant i.e. E. angustifolia had highly significant variation and all the other remaining plants showed slightly significant (P<0.05) variation in their foliage width during summer between polluted and non-polluted sites.

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Table 6.7: Effect of air pollution on the width of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during autumn

Name of plants Width of Foliage (cm) NP S.D. P S.D. Rd% t Prunus armeniaca L. 9.7 (1.2) 6.3 (0.9) 53.4 2.06* Elaeagnus angustifolia L. 3.9 (0.7) 2.6 (0.5) 48.2 2.37* Rosa indica L. 2.6 (0.9) 1.8 (0.6) 48.0 2.09* Melia azadirach L. 3.0 (0.5) 2.1 (0.2) 42.9 3.73*** Robinia pseudoacacia L. 3.6 (0.9) 2.6 (0.7) 38.6 2.27* Morus alba L. 8.6 (2.2) 6.2 (1.5) 37.0 1.86 * Punica granatum L. 8.6 (2.0) 6.4 (1.6) 35.5 1.96 * Ficus carica L. 14.0 (3.7) 10.5 (3.6) 32.6 1.92 * Eucalyptus tereticornis L. 4.6 (1.1) 3.5 (0.4) 31.7 1.90 * Morus nigra L. 8.7 (2.0) 6.6 (1.6) 31.7 1.96 * Vitis vinifera L. 13.5 (2.6) 10.5 (2.9) 28.5 1.87 * Fraxinus excelsior L. 4.5 (1.1) 3.5 (0.6) 28.2 2.13* Pistacia vera L. 7.1 (2.0) 6.0 (1.9) 19.7 1.08 ns

During autumn, the percentage of leaf width reduction (Table 6.7) was in the range of 19.7 - 53.4 %, with P. armeniaca showed the highest reduction and P. vera had the least. Statistical analysis using t-test indicated that out of 13 plant species, one specie (M. azadirach) showed very highly significant (P<0.001) difference in their foliage length. Another one species (P. vera) were non-significant. All the other plant had slightly significant (P<0.05) variation in their foliage width between polluted and non-polluted sites during autumn.

150

Effect of air pollution on the area of foliage: Data regarding effect of air pollution on the area of foliage of different plant species collected from polluted and non- polluted sites of Quetta city during spring, summer and autumn are surmised in Table 6.8, 6.9 and 6.10, respectively.

Table 6.8: Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during spring

Name of plants Area of Foliage (cm2) NP S.D. P S.D. Rd% t Fraxinus excelsior L. 12.4 (2.0) 8.2 (2.3) 50.9 2.29* Rosa indica L. 3.2 (1.0) 2.1 (0.4) 50.5 3.41*** Melia azadirach L. 3.2 (1.1) 2.3 (1.0) 42.2 2.30* Punica granatum L. 3.5 (1.0) 2.5 (1.4) 40.0 3.24*** Prunus armeniaca L. 27.6 (6.1) 20.1 (4.6) 37.1 2.21* Morus nigra L. 35.4 (5.2) 26.6 (3.7) 33.0 2.99*** Morus alba L. 47.3 (7.8) 36.5 (6.5) 29.3 2.20* Vitis vinifera L. 57.9 (11.0) 45.2 (15.7) 28.0 2.92*** Robinia pseudoacacia L. 11.1 (1.6) 8.7 (1.4) 27.9 1.88 * Elaeagnus angustifolia L. 2.9 (0.6) 2.3 (0.8) 25.5 2.37* Ficus carica L. 60.3 (9.1) 51.1 (9.9) 18.0 2.36* Eucalyptus tereticornis L. 14.3 (3.2) 12.2 (3.2) 17.5 1.88 * Pistacia vera L. 41.2 (10.8) 35.3 (10.7) 16.8 1.40 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001 and Rd%: Reducing % at polluted site

During spring, the percentage of leaf area reduction (Table 6.8) was found in the range of 16.8 - 50.9 %, with P. vera having the maximum reduction and F. excelsior indicated the minimum. Statistical analysis (t-test) exhibited that out of 13 plant species, 4 plants like; R. indica, P. granatum, M. nigra and V. vinifera showed very highly significant (P<0.001) differences in their foliage area. Other 8 species i.e. F. excelsior, M. azadirach, P. armeniaca, M. alba, R. pseudoacacia, E. angustifolia, F. carica and E. tereticornis had slightly significant variation at P<0.05. The other remaining one plant (P. vera) reported with non-significant variation in their foliage area during spring between polluted and non-polluted sites.

151

Table 6.9: Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during summer

Name of plants Area of Foliage (cm2) NP S.D P S.D Rd% t Fraxinus excelsior L. 17.5 (4.3) 11.4 (2.6) 57.6 2.23* Rosa indica L. 5.2 (1.0) 3.3 (0.7) 57.6 3.78*** Melia azadirach L. 6.0 (0.8) 3.8 (1.2) 56.3 2.45** Prunus armeniaca L. 38.7 (6.8) 25.8 (7.9) 50.0 2.54** Punica granatum L. 5.2 (1.5) 3.5 (1.6) 49.7 2.07* Morus nigra L. 55.1 (8.5) 38.4 (10.6) 43.6 2.25* Robinia pseudoacacia L. 20.0 (1.8) 14.2 (1.7) 40.5 2.13* Elaeagnus angustifolia L. 4.9 (1.5) 3.5 (1.5) 38.9 1.96 * Vitis vinifera L. 80.1 (13.0) 58.9 (15.8) 36.0 2.22* Morus alba L. 63.2 (8.3) 47.1 (10.6) 34.4 1.92 * Eucalyptus tereticornis L. 18.9 (4.0) 15.3 (3.4) 23.7 2.04* Pistacia vera L. 67.4 (4.3) 54.8 (4.5) 23.0 6.77*** Ficus carica L. 79.9 (6.1) 65.3 (13.3) 22.4 2.73*** Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001 and Rd%: Reducing % at polluted site

During summer, the percentage decreased in the foliage area was recorded 22.4 - 57.6 % from polluted sites plants as compared to non-polluted sites. The maximum decreasing percentage of foliage area was found from F. excelsior and R. indica and lowest in the leaves of F. carica from polluted site with respect to non- polluted site (Table 6.9). Significant test (t-test) showed that the values of R. indica, P. vera and F. carica had very highly significant differences at P<0.001. The M. azadirach and P. armeniaca showed highly significant (P<0.01) difference, whereas all the other remaining plant species had slightly significant (P<0.05) variation in their foliage area during summer between polluted and non-polluted sites.

152

Table 6.10: Effect of air pollution on the area of foliage in different plant species growing from polluted and non-polluted sites of Quetta city during autumn

Name of plants Area of Foliage (cm2) NP S.D P S.D Rd% t Melia azadirach L. 6.5 (0.9) 4.0 (1.1) 64.6 2.55** Rosa indica L. 5.7 (1.0) 3.5 (0.7) 62.9 3.74*** Fraxinus excelsior L. 18.9 (4.3) 11.8 (2.8) 60.5 2.16* Prunus armeniaca L. 41.7 (6.8) 26.8 (7.9) 55.6 2.53** Punica granatum L. 5.8 (1.5) 3.8 (1.5) 54.7 2.01* Morus nigra L. 58.0 (8.3) 39.1 (10.6) 48.3 2.39** Robinia pseudoacacia L. 21.2 (1.9) 14.6 (1.7) 45.2 2.16* Vitis vinifera L. 85.1 (12.9) 60.1 (14.8) 41.6 2.22* Elaeagnus angustifolia L. 5.1 (1.5) 3.6 (1.4) 40.3 1.97 * Morus alba L. 65.1 (7.9) 47.8 (10.6) 36.4 2.20* Pistacia vera L. 70.5 (3.9) 55.5 (4.5) 27.1 3.96*** Ficus carica L. 84.0 (6.1) 66.4 (13.3) 26.5 2.73*** Eucalyptus tereticornis L. 19.5 (3.5) 15.5 (3.4) 26.2 2.50**

During autumn, the percentage of leaf area reduction (Table 6.10) was in the range of 26.2 - 64.6%, with M. azadirach having the largest reduction and E. tereticornis indicated the least. Statistical analysis (t-test) revealed that 03 plant species viz. R. indica, P. vera and F. carica showed very highly significant (P<0.001) differences in their foliage area. Other four species (M. azadirach, P. armeniaca, M. nigra, and E. tereticornis) were highly significant (P<0.01). All the other plant species had slightly significant (P<0.05) variation in their foliage area during autumn between polluted and non-polluted sites.

153

Effect of air pollution on the length of petiole: The results about the effect of air pollution on the length of foliage petiole of different plant species collected from polluted and non-polluted sites during spring, summer and autumn are illustrated in Tables 6.11, 6.12 and 6.13, respectively.

Table 6.11: Effect of air pollution on the length of foliage petiole in different plant species growing from polluted and non-polluted sites of Quetta city during spring

Name of plants Length of Foliage petiole (cm) Np S.D. P S.D. Rd% t Eucalyptus tereticornis L. 1.4 (0.6) 0.9 (0.2) 57.0 2.40** Fraxinus excelsior L. 0.6 (0.3) 0.4 (0.2) 48.7 1.21 * Rosa indica L. 0.3 (0.1) 0.2 (0.1) 42.9 3.40*** Elaeagnus angustifolia L. 0.6 (0.2) 0.4 (0.1) 39.5 2.00* Ficus carica L. 3.1 (0.7) 2.2 (0.9) 37.4 2.62** Prunus armeniaca L. 3.1 (0.9) 2.4 (0.8) 31.9 1.94 * Morus nigra L. 2.6 (0.6) 2.4 (0.5) 9.6 0.92 ns Punica granatum L. 0.5 (0.2) 0.4 (0.2) 9.5 0.22 ns Robinia pseudoacacia L. 0.3 (0.1) 0.3 (0.1) 8.0 0.38 ns Morus alba L. 2.5 (0.8) 2.3 (0.6) 7.9 0.21 ns Melia azadirach L. 0.3 (0.1) 0.3 (0.1) 7.7 0.58 ns Pistacia vera L. 1.0 (0.1) 0.9 (0.1) 6.5 0.15 ns Vitis vinifera L. 5.7 (1.5) 5.4 (1.2) 5.7 0.46 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001 and Rd%: Reducing % at polluted site

During spring, the percentage of petiole length decreasing (Table 6.11) was in the range of 5.7 - 57.0 %, with E. tereticornis having the largest reduction and V. vinifera showed the least. Statistical analysis using t-test indicated that out of 13 plant species, only 01 plant, (R. indica) showed very highly significant (P<0.001) differences in their foliage area. Another two species i.e. E. tereticornis and F. carica were highly significant (P<0.01). The other 03 plant species i.e. F. excelsior, E. angustifolia and P. armeniaca exhibited slightly differences (P<0.05) between polluted and non-polluted sites. All the other plant species have non-significant variation in their foliage area during autumn.

154

Table 6.12: Effect of air pollution on the length of foliage petiole in different plant species growing form polluted and non-polluted sites of Quetta city during summer

Name of plants Length of petiole(cm) NP S.D P S.D Rd% t Eucalyptus tereticornis L. 2.5 (0.4) 1.5 (0.2) 65.6 3.06*** Rosa indica L. 0.6 (0.2) 0.3 (0.1) 61.8 3.92*** Punica granatum L. 0.9 (0.4) 0.5 (0.4) 61.1 1.70 * Fraxinus excelsior L. 1.0 (0.4) 0.6 (0.3) 61.0 1.47 ns Elaeagnus angustifolia L. 1.0 (0.3) 0.7 (0.1) 47.8 1.75 * Melia azadirach L. 0.5 (0.2) 0.3 (0.0) 47.1 2.14* Ficus carica L. 4.0 (1.2) 2.8 (0.9) 44.6 1.97 * Prunus armeniaca L. 3.7 (0.6) 2.9 (0.6) 36.2 2.89*** Morus alba L. 3.7 (1.5) 3.0 (1.0) 26.4 2.47** Robinia pseudoacacia L. 0.5 (0.2) 0.4 (0.1) 25.0 2.31* Morus nigra L. 3.5 (0.9) 2.8 (0.7) 23.2 1.55 ns Pistacia vera L. 1.7 (0.2) 1.5 (0.1) 12.6 1.91 * Vitis vinifera L. 6.5 (0.9) 5.8 (0.9) 11.0 2.21*

During summer, the percentage of petiole length reduction (Table 6.12) was in the range of 11.0 - 65.6 % with E. tereticornis had the maximum reduction and V. vinifera indicated the minimum. Statistical analysis (t-test) exhibited that 03 plant species, E. tereticornis, R. indica and P. armeniaca showed very highly significant (P<0.001) differences in their foliage length. Another one plant (M. alba) had highly significant differences (P<0.01) and other seven species i.e. P. granatum, E. angustifolia, M. azadirach, F. carica, R. pseudoacacia, P. vera and V. vinifera showed slightly significant (P<0.05) variation. The remaining 02 plant species like F. excelsior and M. nigra had non-significant variation in their petiole length during spring between polluted and non-polluted sites.

155

Table 6.13: Effect of air pollution on the length of foliage petiole different plant species growing from polluted and non-polluted of Quetta city during autumn

Name of plants Length of petiole(cm) Np S.D P S.D Rd% t Punica granatum L. 1.0 (0.4) 0.6 (0.4) 75.4 2.89*** Eucalyptus tereticornis L. 2.7 (0.4) 1.6 (0.2) 70.1 3.06** Fraxinus excelsior L. 1.1 (0.4) 0.6 (0.3) 67.7 1.66 ns Rosa indica L. 0.6 (0.2) 0.4 (0.2) 62.9 3.87*** Elaeagnus angustifolia L. 1.1 (0.3) 0.7 (0.2) 50.7 1.67 * Melia azadirach L. 0.5 (0.2) 0.4 (0.0) 50.0 1.99 * Ficus carica L. 4.1 (1.2) 2.8 (0.9) 45.7 2.03* Prunus armeniaca L. 3.7 (0.6) 2.7 (0.5) 37.1 2.65** Robinia pseudoacacia L. 0.5 (0.2) 0.4 (0.1) 28.6 2.17* Morus alba L. 3.8 (1.5) 3.0 (1.5) 27.7 1.99 * Morus nigra L. 3.6 (0.9) 2.9 (0.6) 25.0 1.57 ns Pistacia vera L. 1.8 (0.1) 1.6 (0.1) 16.1 2.19* Vitis vinifera L. 6.7 (0.9) 5.9 (0.9) 13.1 2.22* Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01, *** very highly significant p < 0.001 and Rd%: Reducing % at polluted site

During autumn, the percentage of petiole length reduction (Table 6.13) was in the range of 13.1 - 75.4 % with P. granatum heaving the largest reduction and V. vinifera showed the minimum. Statistical analysis using t-test revealed that 2 plant species (P. granatum and R. indica) indicating very highly significant (P<0.001) differences in their foliage length. Other 02 plant species i.e. E. tereticornis and P. armeniaca showed highly significant differences (P<0.01). Other 07 plant species; E. angustifolia, M. azadirach, F. carica, R. pseudoacacia, M. alba, P. vera and V. vinifera showed slightly significant (P<0.05) variation. The remaining 02 species; F. excelsior and M. nigra had non-significant variation in their petiole length during autumn between polluted and non-polluted sites.

156

Table 6.14: Average length and width of foliage (cm) of different plant species growing from polluted and non-polluted site of Quetta city during all three growing seasons

Name of plants Average length of foliage Average width of foliage NP S.D. P S.D t NP S.D P S.D t Ficus carica L. 16.0 (2.7) 12.5 (1.6) 2.68* 13.0 (1.3) 10.1 (0.6) 3.01* Eucalyptus tereticornis L. 14.2 (2.8) 11.2 (1.2) 2.48* 4.0 (0.9) 3.1 (0.5) 2.47* Vitis vinifera L. 11.6 (1.8) 9.7 (1.2) 2.45* 12.5 (1.3) 10.0 (0.5) 2.96* Pistacia vera L. 11.8 (3.3) 8.6 (2.1) 2.41* 6.3 (1.0) 5.4 (0.8) 2.23* Morus alba L. 9.3 (1.8) 6.7 (1.0) 2.81* 7.3 (1.6) 5.6 (0.9) 2.56* Morus nigra L. 9.6 (2.2) 6.4 (1.2) 2.79* 7.4 (1.5) 5.9 (0.8) 2.51* Fraxinus excelsior L. 9.0 (2.4) 7.0 (1.5) 2.23* 3.7 (0.9) 3.0 (0.6) 2.09* Elaeagnus angustifolia L. 7.1 (1.6) 4.9 (1.0) 2.75* 3.4 (0.8) 2.2 (0.6) 2.72* Prunus armeniaca L. 7.2 (1.8) 5.5 (1.2) 2.29* 8.0 (1.9) 5.4 (1.0) 2.83* Punica granatum L. 6.9 (2.0) 4.0 (0.9) 2.70* 7.4 (1.5) 5.9 (0.7) 2.69* Robinia pseudoacacia L. 7.1 (2.2) 4.8 (1.2) 2.59* 3.3 (0.5) 2.4 (0.3) 2.99* Melia azadirach L. 4.9 (1.0) 3.2 (0.6) 2.89* 2.4 (0.6) 1.8 (0.3) 2.87* Rosa indica L. 3.1 (0.9) 2.2 (0.4) 2.98* 2.4 (0.3) 1.7 (0.1) 3.16* Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01 and *** very highly significant p < 0.001.

Overall average length of foliage during all the growing seasons was found in the range of 3.1 – 16.0 cm from non-polluted site plants, while from polluted site it was 2.2 – 12.5 cm. The lowest length of foliage showed by R. indica while highest had F. carica. Significant test (t-test) revealed that there was slightly significant (P<0.05) variation in length of foliage between two sites. The overall average width of foliage from non-polluted site plant species was recorded 2.4 - 13.0 cm, while from polluted site plants it was 1.7 - 10.1 cm. The R. indica showed minimum width and F. carica had maximum foliage width. Statistical test (t-test) indicated that there was slightly significant differences (P<0.05) in the foliage width of all the plant species between polluted and non-polluted sites (Table 6.14).

157

Table 6.15: Average area of foliage and length of petiole in different plant species growing from polluted and non-polluted site of Quetta city during all three growing seasons

Name of plants Average area of foliage Average length of petiole

NP S.D P S.D t NP S.D P S.D t Ficus carica L. 74.7 (9.6) 60.9 (8.5) 2.59* 3.7 (0.6) 2.6 (0.3) 2.96* Vitis vinifera L. 74.4 (9.5) 54.8 (8.3) 2.85* 6.3 (0.5) 5.7 (0.3) 2.70* Pistacia vera L. 59.7 (9.1) 48.5 (8.5) 1.98ns 1.5 (0.5) 1.3 (0.4) 1.15ns Morus alba L. 58.5 (9.8) 43.8 (6.3) 2.81* 3.3 (0.8) 2.7 (0.4) 2.18* Morus nigra L. 49.5 (8.3) 34.7 (7.0) 2.68* 3.2 (0.5) 2.7 (0.3) 2.49* Prunus armeniaca L. 36.0 (7.5) 24.2 (3.6) 2.95* 3.5 (0.3) 2.6 (0.2) 3.16* Eucalyptus tereticornis L. 17.6 (2.8) 14.3 (1.8) 2.61* 2.2 (0.7) 1.3 (0.4) 2.66* Robinia pseudoacacia L. 17.4 (5.5) 12.5 (3.3) 2.36* 0.4 (0.2) 0.4 (0.1) 1.74 ns Fraxinus excelsior L. 16.2 (3.4) 10.4 (1.9) 2.97* 0.9 (0.2) 0.5 (0.1) 2.82* Melia azadirach L. 5.2 (1.8) 3.4 (1.0) 2.62* 0.4 (0.1) 0.3 (0.1) 2.37* Punica granatum L. 4.9 (1.2) 3.3 (0.7) 2.82* 0.8 (0.3) 0.5 (0.1) 2.66* Elaeagnus angustifolia L. 4.8 (1.2) 3.1 (0.7) 2.37* 0.9 (0.3) 0.6 (0.2) 2.59* Rosa indica L. 4.7 (1.4) 3.0 (0.8) 2.76* 0.5 (0.2) 0.3 (0.1) 2.57* Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, NP: Non-polluted, P: Polluted, S.D: Standard deviation, t: t-test, *slightly significant p < 0.05, **highly significant p< 0.01 and *** very highly significant p < 0.001. Overall average area of foliage during all three seasons (Table 6.15) was found 4.7 – 74.7 cm2 from non-polluted site, while from polluted site plant species it was 3.0 – 60.9cm2 with R. indica had lowest while F. carica the highest growth. Statistical analysis using t-test revealed that out of 13 plant species, only one plant (P. vera) had non-significant variation in their area of foliage. All the other remaining plant species showed slightly significant (P<0.05) variation in the area of foliage between polluted and non-polluted sites. The Overall average length of petiole from non-polluted site plants was found 0.5 - 6.3cm, while from polluted site it was 0.3 - 5.7cm. The leaves of R indica had lowest length of petiole and V. vinifera showed the highest. The t-test indicated that except two species (P. vera and R. pseudoacacia) all the other plants had slightly significant differences at P<0.05 in the length of petiole between polluted and non-polluted sites.

158

Table 6.16: Seasonally increasing percentage of foliage length and width in different plant species growing from Polluted and non-polluted site of Quetta city

Name of plants Length of foliage (Inc %) Width of foliage (Inc %)

Spring to Summer to Spring to Summer to Summer Autumn Summer Autumn NP P NP P NP P NP P Robinia pseudoacacia L. 43.5 36.0 8.1 2.7 20.8 18.7 6.2 4.2 Punica granatum L. 43.3 32.4 1.6 1.1 28.0 18.4 8.0 3.5 Pistacia vera L. 40.2 37.2 4.1 1.6 23.1 21.4 6.3 4.9 Fraxinus excelsior L. 39.0 33.8 1.7 0.3 33.5 24.6 11.5 9.8 Prunus armeniaca L. 37.2 34.0 1.2 0.6 29.9 21.8 13.1 11.8 Morus nigra L. 34.0 28.7 3.2 1.5 28.0 18.4 8.2 6.4 Rosa indica L. 33.9 28.3 8.0 3.7 15.8 10.3 3.1 1.7 Elaeagnus angustifolia L. 33.4 29.9 3.1 1.3 34.2 31.0 2.2 1.9 Melia azadirach L. 30.5 26.9 4.5 3.7 25.4 23.2 20.0 11.9 Eucalyptus tereticornis L. 30.5 17.1 1.2 0.5 29.9 22.7 8.5 4.9 Morus alba L. 28.6 24.0 3.5 1.1 31.1 22.0 7.6 5.5 Ficus carica L. 25.7 20.2 1.5 0.5 15.3 8.5 3.2 2.5 Vitis vinifera L. 24.1 19.5 1.8 1.2 13.3 4.3 5.8 4.9 Mean: 30 readings, NP: Non-polluted, P: Polluted and In%: Increasing at non- polluted site

The percentage of foliage length increased from spring to summer was in the range of 24.1 - 43.5% from non-polluted sites with R. pseudoacacia had the maximum increasing percentage and V. vinifera showed the minimum. From polluted sites the percentage increasing was 17.1 - 37.2 %, the leaves of E. tereticornis had minimum percentage increase while P. vera showed the maximum from Spring to Summer. During summer to autumn increasing percentage of foliage length was found 1.2 - 8.1% from non-polluted site, while from polluted site plant species it was only 0.3 - 3.7 %. The percentage of foliage width increased from spring to summer was in the range of 13.3 - 34.2 % in the leaves of non-polluted site plant species. However from polluted sites plant species the increased percentage recorded was 4.3 - 31.0 % from spring to summer. During summer to autumn the percentage of foliage width increased was recorded 2.2 - 20.0% from non-polluted sites while from polluted sites plant species the recorded percentage was only 1.7 - 11.9 % (Table 6.16).

159

Table 6.17: Seasonally increasing percentage of foliage area and petiole length in different plant species growing from polluted and non-polluted site of Quetta city

Name of plants Inc % of foliage area Inc % of petiole length

Spring to Summer to Spring to Summer to Summer Autumn Summer Autumn NP P NP P NP P NP P Melia azadirach L. 46.7 41.4 7.7 2.8 44.0 23.5 7.4 5.6 Robinia pseudoacacia L. 44.6 39.1 5.7 2.5 46.0 37.5 7.4 4.8 Elaeagnus angustifolia L. 40.3 34.0 3.8 2.8 39.4 35.8 7.5 5.6 Rosa indica L. 39.2 36.4 8.8 5.7 45.5 38.2 3.5 2.9 Pistacia vera L. 38.9 35.6 4.4 1.1 42.4 39.1 5.6 2.6 Morus nigra L. 35.8 30.7 5.0 1.9 24.9 15.5 2.8 1.4 Punica granatum L. 33.2 28.6 9.7 6.7 47.1 22.2 13.0 5.3 Fraxinus excelsior L. 28.8 25.7 7.5 5.8 39.0 33.9 8.7 4.8 Prunus armeniaca L. 28.8 22.1 7.3 3.8 14.0 11.2 2.1 1.5 Vitis vinifera L. 27.7 23.2 5.9 2.0 11.6 07.2 3.2 1.4 Morus alba L. 25.3 22.3 2.9 1.5 34.5 23.3 2.4 1.3 Ficus carica L. 24.5 21.7 4.9 1.7 23.6 19.6 2.2 1.4 Eucalyptus tereticornis L. 24.0 20.0 3.2 1.3 46.0 43.1 6.4 3.8 Mean: 30 readings, NP: Non-polluted, P: Polluted and In%: Increasing at non- polluted site

The percentage of foliage area increased from spring to summer was in the range of 24.0 - 46.7% with M. azadirach had the maximum increasing percentage and E. tereticornis showed the minimum from non-polluted site plant species. From polluted site percentage increased was 20.0 - 41.4%, with E. tereticornis had the lowest while M. azadirach showed highest percentage increased. During summer to autumn increased percentage of foliage area recorded was 2.9 - 9.7 % from non- polluted site plant species, while from polluted site it was only 1.1 - 6.7 %. The percentage of petiole length increased from spring to summer was in the range of 11.6 - 46.0 % from non-polluted site plant species while from polluted site plant it was 07.2 - 43.1 %. During summer to autumn the percentage of petiole length increased was found 2.1 - 13.0 % from non-polluted site plants, while from polluted site it was recorded 1.3 - 5.6 % (Table 6.17).

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Table 6.18: Seasonal decreasing percentage of morphological characteristics in all the plant species of polluted site with respect to non-polluted site

Parameters Spring Summer Autumn Rd % S.D Rd % S.D Rd % S.D Area of foliage (cm2) 32.5 (21.6) 37.1 (14.0) 35.8 (13.8) Length of foliage (cm) 28.4 (12.3) 33.9 (8.6) 33.8 (8.4) Length of petiole (cm) 26.3 (23.6) 46.2 (23.6) 43.5 (21.7) Width of foliage (cm) 23.5 (19.7) 36.6 (13.2) 35.9 (13.6) Rd%: Reducing percentage and S.D: Standard deviation

Over all decreasing percentage of foliage area during spring, summer and autumn season was 32.5, 37.1 and 35.8 %, respectively. Percentage of foliage length reduction from polluted site plant species during spring, summer and autumn was recorded 28.4, 33.9 and 33.8 %, respectively. The length of petiole showed 26.3, 46.2 and 43.5 % reduction percentage from polluted sites plants during, spring, summer and autumn seasons, while foliage width was 23.5, 36.6 and 35.9 %, respectively.

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Overall average decreasing percentage of different parameters: Overall average decreasing percentage of foliage length, width, area and petiole length of leaves samples collected from polluted site with respect to non-polluted site are evaluated. All the results are shown in Figs 6.7- 6.10, respectively.

Fig 6.7 indicated that over all decreasing percentage in foliage length during all three growing seasons from polluted site with respect to non-polluted site was ranged between 19.86 – 72.59 %. The lowest decreasing percentage showed by V. vinifera and P. granatum had the highest.

V. vinifera E. angustifolia 19.9 45.1

R. indica 66.5 E. tereticornis 26.5 F. carica 27.7 R. pseudoacacia 46.8 F. excelsior 28.7 P. vera M. nigra 37.4 50.5

M. alba P. armeniaca 37.7 30.2

P. granatum M. azadirach 72.6 54.1

Fig 6.7: Decreasing % of foliage length

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Results described in Fig 6.8 exhibited that over all decreasing percentage of foliage width from polluted site as compared to non-polluted sites during all growing seasons was in the range of 17.81 – 50.58 %. The P. avera had the lowest decreasing percentage while E. angustifolia showed the highest.

V. vinifera 24.0 E.ngustifolia 50.6

R. indica 44.0 E.tereticornis 25.3 F. carica R. pseudoacacia 28.8 35.8 M. nigra 25.8 F. excelsior 22.9 P. vera M. alba 17.8 30.8 P. armeniaca 47.8 M. azadirach 33.9 P. granatum 27.1

Fig. 6.8. Decreasing % of foliage width

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Over all average percentage of foliage area decreasing from polluted site plants as compare to non-polluted sites during through out seasons was found 22.66 - 57.98 %. The Maximum reducing percentage showed by R. indica and minimum had in F. carica (Fig 6.9).

V. vinifera E. angustifolia 35.8 36.1

R. indica E. tereticornis 58.0 22.9 F. carica R. peudoacacia 22.7 39.4

F. excelsior 56.9

M. nigra . 42.7 P. vera 23.1 P. armeniaca M. alba 48.5 33.7

P. granatum M.. azadirach 49.1 56.4

Fig. 6.9. Decreasing % of foliage area

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Data regarding to the overall average percentage of foliage petiole decreased in polluted site plant with respect to non-polluted site during all growing seasons was found 10.1–65.5 %. The V. vinifera showed the lowest decreasing percentage while E. tereticornis had highest (Fig 6.10).

E. angustifolia V. vinifera 10.1 47.0

R. indica 57.8

R. pseudoacacia E. tereticornis 22.4 65.5

M. nigra 19.8

M. alba 21.8 F. carica 43.0 M. azadirach 37.5

F. excelsior P.granatum 60.6 52.3 P. armeniaca P. vera 35.2 12.6

Fig 6.10. Decreasing % of petiole length

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6.4. DISCUSSION

6.4.1. Grass leaf morphological changes: The plants growing in urban area Quetta city are continuously exposed to different air pollutants (carbon monoxide, oxides of nitrogen and sulphur, particulate matter, lead and other heavy metals etc.). Therefore all the plant species investigated showed some morphological changes (Colour and shapes) and hidden injury or physiological disturbance. The observations of Gielwanowska et al., (2005); Makbul et al., (2006), supported the above mention facts. They found that the plants growing close to the busy road of the city are highly affected by auto-emission. The inhibitory effects on the growth of plants are due to the presence of toxic material in the auto-emission. Rao, (2006) and Svetlana et al., (2010), also agreed that air pollutants effect the plant growth and morphological characters adversely.

6.4.2. Foliage length: Statistical analysis (t-test) indicated that there was slightly significant (P<0.05) variation in the values of foliage length between polluted and non-polluted sites. Seasonally maximum reduction percentage of foliage length in all the investigated plant species from polluted site was found during summer that followed by autumn and lowest was during spring. Slow increasing percentage and maximum reduction of foliage length from polluted site as compared to non-polluted site might be due to high level of particulates deposition and heavy metals accumulation on plant leaves. Similar observation was also made by Bhatti & Iqbal, (1988) they found significant decline in leaf length of Ficus bengalensis at the polluted sites. Preeti, (2000 “a”) also observed that leaves of Thevetia nerifolia and Cassia siamea growing in the polluted environment showed reduction in growth.

6.4.3. Foliage width: Significant test (t-test) indicated that there was slightly significant (P<0.05) differences in the foliage width of all the plant species between polluted and non-polluted sites. Similar observations were also reported by Shafiq et al., (2009), they found that the leaves taken from the polluted sites showed decline in length, width and area. Seasonally maximum reduction percentage of foliage width from polluted site plant species was found during summer that followed by autumn and lowest was in spring. This might be due to high contents of air pollutants generated by high traffic density and their movement. The results noticed by Gielwanowska et al., (2005); Makbul et al., (2006) also supported these views.

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Similar observation was also reported by Preeti (2000 “a”), he observed that leaves of Thevetia nerifolia and Cassia siamea growing in the polluted environment showed reduction in growth, he also found that compound leaves showed greater damage than narrow simple leaves and the portion of injured area was 15.57% in T. nerifolia and 22.33% in C. siamea.

6.4.4. Foliage area: Statistical analysis using t-test revealed that out of 13 plant species, one plant i.e. Pistacia vera showed non-significant variation in their area of foliage between polluted and non-polluted sites. However other remaining plant species exhibited that there was slightly significant (P<0.05) variation in their foliage area between polluted and non-polluted sites. Similar observation was also reported by Tiwari et al., (2006). A significant (p<0.05) decline in leaf area of a roadside plant, Bougainvillea spectibilis has been also observed by Hussain et al., (1997). The results noticed by Qadir & Iqbal, (1991), also supported the present results. They found that the constituents of petrol and lubricating oils deposit on the aerial parts of plants and these pollutants in combinations cause greater or synergistic effects to plants. Seasonally maximum reducing percentage of leaf area in all the investigated plant species from polluted site with respect to non-polluted site was found during summer that followed by autumn and lowest was during spring. This reduction in leaf area at polluted site might be due to high concentration of toxic gases emitted from vehicles and deposition of particulates matter on plant leaves. Similar observation was also noticed by many other researcher; Bhatia, (2006); Henry & Heinke, (2005); Rao, (2006) and Svetlana et al., (2010). The reduction in leaf area growing in the vicinity of heavy pollutants was also observed in many other plants by Bhatti & Iqbal, (1988); Gupta & Ghouse, (1988) and Sodnik et al., (1987). Moreover other workers Iqbal & Shafiq, (1999); Shafiq & Iqbal, (2003 & 2005), also reported that the plants growing adjacent to roadsides of Karachi city exhibited considerable damage in response to automobile exhaust emission. They also reported that atmospheric pollutants after making their entry through stomata of leave cause reduction in leaf size of plants due to damage of photosynthetic tissues.

6.4.5. Petiole length: The test (t-test) indicated that except 02 species viz, (P. vera and R. pseudoacacia) all the other plants had slightly significant (P<0.05) differences in the length of petiole between polluted and non-polluted sites. Observation reported by Dineva, (2004) and Tiwari et al., (2006) supported the present findings. Seasonally

167 maximum percentage reduction in all the investigated plant species at polluted site was found during summer, which followed by autumn and lowest was in spring. Similar observation was also reported by Iqbal, (2006) in the leaves of G. officinale which showed significant reduction in length of petiole, length of leaf and area of leaflet. Other workers also reported significant reduction in different leaf variables at the polluted environment with respect to clean atmosphere, Jahan & Iqbal, (1992) and Sodnik et al., (1987). In their study on Platanus acerifolia showed changes in leaf blade and petiole size at polluted site. Shafiq et al., (2009) noticed that leaf growth (leaf length, width and length of petiole) of C. siamea and P. pterocarpum was significantly affected by the polluted environment as compared to clean area. Leaf size of both tree species reduced progressively depending on the level of pollutant in the city.

6.5. CONCLUSIONS This study concluded that all the plant species growing at polluted environment of the city are badly affected by auto-emission. On the morphological point of view, the plants from polluted sites had important changes especially regarding the colors, shapes, foliage length, width area and petiole length. However, despite these changes, plants were survived well at the polluted environment of Quetta city. After this study, we can consider that there is still a serious lack of knowledge of the impact of air quality on vegetation in the urban areas. There is a need to set limits on how much of a pollutant is allowed in the air. The exchange of experience and information from the developed countries on this aspect of pollution impact on plants might be useful. Our goal must be to have clean air for flora and fauna. We should take necessary steps to get rid of the over increasing pollution.

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Chapter 7

EFFECT OF AIR POLLUTION ON THE ANATOMICAL CHARACTERISTICS OF PLANTS FOLIAGE GROWN ALONG THE ROAD SIDE OF QUETTA CITY

7.1. INTRODUCTION

The plants being constantly exposed to the environment absorbs, accumulation integrate pollutants impinging on their foliar surfaces and consequently they show visible or subtle changes depending on their sensitivity level (Sharma & Butler, 1973; Smith & Staskawicz, 1977). Air pollution not only effect on stomatal conductance, it also have adverse effect on seed germination and growth of certain roadside plant species. Air pollutants caused the leaf injury, stomatal damage, premature senescence, and decrease photosynthesis activity, disturb membrane permeability, decreased growth and productivity (Tiwari et al., 2006). Moreover other workers Iqbal & Shafiq, (1999); Shafiq & Iqbal, (2003 & 2005), also reported that the plants growing adjacent to roadsides of Karachi city exhibited considerable damage in response to automobile exhaust emission. They also reported that atmospheric pollutants after making their entry through stomata of leave cause reduction in leaf size of plants due to damage of photosynthetic tissues. Most of the automobiles emit black smoke due to incomplete combustion of fuel. These toxic materials such as carbon particles, unburned and partially burned hydrocarbons, fuels, tar materials, lead compounds and other elements are the constituents of petrol and lubricating oils. These all are deposit on the aerial parts of plants and cause greater effects to plants (Qadir and Iqbal, 1991). Stomata worked as a regulating mechanism for gases entering or escaping from leaves and offer an excellent opportunity to study the interaction between plants and their environment i.e., the atmosphere and its associated air pollution. The main object of this study is to explore the anatomical features of different plants leaves as adaptability indicator. The goal was to prove the statement that the plants answer to environmental pollution by changing morphology and anatomy of leaves.

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7.2. MATERIALS AND METHODS

7.2.1 Samples Collection: The leaves samples were collected following the methods given by Ara et al., (1996), details are given in chapter 6. Quantitative characters of the leaves such as, number of epidermal cells, total number of stomata and total number of closed, abnormal or injured and open stomata were recorded seasonally/periodically at regular interval of three months viz, (March-May, Jun- August, and September-November). All the measurements were based on three replicates.

7.2.2. Percentage increasing and decreasing: Percentage increasing and decreasing of different parameters during different seasons was calculated according to the formula used by Syed & Iqbal, (2008).

7.2.3. Anatomical Study of Leaf Epidermis: Anatomical Study of leaf epidermis was done by using method given by Salisbury, (1927) revised by Radoglou & Jarvis, (1990 “b”). Impression of adaxial (upper) and abaxial (lower) epidermis were taken from the point of maximum leaf width near the central vein of the leaf, using colorless nail polish and adhesive transparent tape. Replica impression were taken from leaf epidermis and examined under a light microscope (Ernst Leitz Gmbh Wetzlar, Type 20-446.023, Germany) at a different magnification of microscope (*50, *125 or *1250) for stomatal and epidermal cell studies. At least five microscopic fields were randomly selected per replica. Total number of epidermal cells, total number of stomata and number of open, closed and abnormal/injured stomata/mm2 were counted under the microscope.

7.2.4. Statistical Analysis: The standard deviation values of the means were calculated for a comparison of site categories. To determine the significance of the samples a paired t-test was performed, comparing different air pollutants contents of polluted and non-polluted sites during different seasons (Steel & Torrie, 1980).

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7.3. RESULTS

The leaves samples of polluted and non-polluted sites Plant species collected from Quetta city, their seasonal variation and effects of air pollution on leaf anatomy was evaluated. The total number of epidermal cells/mm2, total number of stomata/mm2, total number of opened; closed and abnormal/injured stomata’s/mm2 on adaxial and abaxial surface were counted. All the results are described in Table 7.1– 7.15.

Number of epidermal cells: The air pollution effects on the epidermal cells, during spring, summer and autumn seasons are presented in Tables 7.1-7.3, respectively.

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Table 7.1: Average number of epidermal cells/mm2 in the leaves, collected during spring season

Name of Number of epidermal cell Number of epidermal cell plants (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Melia 5378.4 (6.7) 5360.0 (10.0) 0.57 ns 6072.0 (6.6) 6080.0 (8.7) 0.28 ns azadirach L. Eucalyptus 5282.4 (8.7) 5293.6 (11.6) 0.28 ns 5365.6 (9.0) 5360.0 (8.7) 0.19 ns tereticornis L. Pistaci avera L. 4904.0 (4.4) 4920.0 (5.0) 0.98 ns 5042.4 (4.0) 5034.4 (4.0) 0.61 ns Vitis vinifera L. 2128.0 (5.2) 2141.6 (5.5) 0.74 ns 2160.0 (2.0) 2173.6 (2.9) 1.41 ns Morus nigra L. 1946.4 (4.2) 1960.0 (5.0) 0.82 ns 2064.0 (6.2) 2066.4 (5.8) 0.14 ns Fraxinus 1938.4 (9.5) 1960.0 (10.0) 0.65 ns 1920.0 (6.2) 1920.0 (5.0) 0.00 ns excelsior L. Robinia 1741.6 (8.7) 1749.6 (8.1) 0.30 ns 1813.6 (7.6) 1826.4 (10.4) 0.39 ns pseudoacacia L. Morus alba L. 1485.6 (4.0) 1501.6 (4.6) 1.06 ns 1840.0 (4.4) 1834.4 (4.0) 0.40 ns Ficus carica L. 1336.0 (7.6) 1346.4 (8.5) 0.38 ns 1357.6 (3.5) 1360.0 (5.0) 0.16 ns Punica 866.4 (8.5) 893.6 (7.6) 1.07 ns 1261.6 (5.7) 1266.4 (5.8) 0.28 ns granatum L. Prunus 853.6 (6.1) 880.0 (5.0) 1.63 ns 1677.6 (9.1) 1693.6 (7.6) 0.64 ns armeniaca L. Rosa indica L. 560.0 (5.0) 573.6 (4.7) 0.86 ns 1288.0 (4.6) 1298.4 (4.0) 0.81 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted and P: Polluted During spring season, the average number of epidermal cells on adaxial surface was in the range of 560.0 - 5378.4/mm2 from non-polluted site plant species, whereas from polluted sites it was 573.6 - 5360.0/mm2. The M. azadirach had largest number of epidermal cells while R. indica showed the lowest. Statistical analysis (t-test) indicated that all the investigated plant species showed non-significant variation in their number of epidermal cells on adaxial surface during spring. On abaxial side the average number of epidermal cells calculated was 1261.6 -6072.0/mm2 from non- polluted site plant species and 1266.4 - 6080.0 from polluted site. The M. azadirach had the highest number of epidermal cells and P. granatum indicating the least. The t- test exhibited that all the plant species had non-significant variation in their number of epidermal cells on abaxial side during spring season (Table 7.1).

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Table 7.2: Average number of epidermal cells/mm2 in the leaves, collected during summer Name of plants Number of epidermal cell Number of epidermal cell (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Melia azadirach L. 5301.6 (12.5) 5320.0 (10.0) 0.57 ns 6032.0 (6.9) 6045.6 (8.1) 0.50 ns Eucalyptus 5248.0 (12.2) 5258.4 (11.1) 0.30 ns 5298.4 (8.7) 5328.0 (7.9) 1.13 ns tereticornis L. Pistaci avera L. 4845.6 (6.0) 4866.4 (7.6) 0.86 ns 4965.6 (4.0) 4994.4 (4.0) 2.22* Vitis vinifera L. 2080.0 (5.0) 2101.6 (6.4) 1.02 ns 2128.0 (3.6) 2141.6 (4.6) 0.88 ns Morus nigra L. 1906.4 (4.7) 1925.6 (5.1) 1.11 ns 2040.0 (5.0) 2034.4 (5.1) 0.32 ns Fraxinus excelsior L. 1906.4 (12.6) 1922.4 (11.2) 0.44 ns 1861.6 (6.4) 1880.0 (5.0) 1.14 ns

Robinia 1680.0 (10.0) 1698.4 (7.5) 0.76 ns 1786.4 (10.4) 1797.6 (9.3) 0.35 ns pseudoacacia L. Morus alba L. 1450.4 (5.1) 1466.4 (5.8) 0.85 ns 1773.6 (5.8) 1794.4 (4.0) 1.62 ns Ficus carica L. 1314.4 (9.3) 1328.0 (7.9) 0.51 ns 1274.4 (9.3) 1317.6 (5.0) 2.60* Punica granatum L. 816.0 (7.2) 850.4 (7.8) 1.37ns 1221.6 (6.4) 1240.0 (6.2) 0.92 ns Prunus armeniaca L. 808.0 (8.5) 845.6 (6.0) 1.90* 1680.0 (8.7) 1650.4 (7.8) 1.16 ns Rosa indica L. 504.0 (4.5) 520.0 (5.0) 0.98 ns 1226.4 (6.1) 1245.6 (6.0) 0.95 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted and P: Polluted

On adaxial surface during summer, the average number of epidermal cells was in the range of 504.0 - 5301.6/mm2 from non-polluted site plant species, while from polluted site it was 520.0 - 5320.0/mm2 (Table 7.2). M. azadirach had the largest number of epidermal cells and R. indica showed the least. The t-test indicated that P. armeniaca showed slightly significant (P<0.05) variation, while all the other species had non-significant variation in their number of epidermal cells during summer. On the abaxial side the average number of epidermal cells recorded was 1221.6 - 6032.0/mm2 from non-polluted site plant species and 1240.0 - 6045.6/mm2from polluted site. The M. azadirach showed the highest number of epidermal cells and P. granatum had the least. Statistical analysis exhibited that 2 plant species i.e. P. avera and F. carica showed slightly significant differences at P<0.05 in their number of epidermal cells. All the other species had non-significant variation during summer season.

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Table 7.3: Average number of epidermal cells /mm2 in the leaves, collected during autumn Name of Number of epidermal cell Number of epidermal cell plants (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Melia azadirach 5280.0 (10.0) 5296.0 (10.2) 0.48 ns 5400.0 (10.0) 6018.4 (8.7) 0.65 ns L. Eucalyptus 5226.4 (10.4) 5232.0 (9.6) 0.17 ns 5280.0 (8.7) 5301.6 (6.4) 1.02 ns tereticornis L. Pistaci avera L. 4786.4 (7.6) 4805.6 (9.0) 0.63 ns 4946.4 (4.7) 4960.0 (5.0) 0.82 ns Vitis vinifera L. 2061.6 (6.4) 2077.6 (5.7) 0.86 ns 2101.6 (4.6) 2117.6 (5.0) 0.97 ns Fraxinus excelsior 1930.4 (2.3) 1922.4 (5.5) 0.44 ns 1826.4 (6.5) 1848.0 (6.6) 1.00 ns L. Morus nigra L. 1882.4 (6.4) 1901.6 (6.8) 0.84 ns 1986.4 (7.6) 2002.4 (5.5) 0.89 ns Robinia 1666.4 (6.5) 1674.4 (9.0) 0.27 ns 1760.0 (8.9) 177.6 (8.2) 0.60 ns pseudoacacia L. Morus alba L. 1432.0 (3.6) 1445.6 (4.0) 1.01 ns 1754.4 (4.0) 1765.6 (4.0) 0.81 ns Ficus carica L. 1288.0 (6.6) 1293.6 (7.6) 0.21 ns 1272.0 (3.6) 1285.6 (4.0) 1.01 ns Punica granatum 840.0 (4.4) 816 .0 (7.2) 1.02 ns 1205.6 (5.1) 1213.6 (7.6) 0.32 ns L. Prunus armeniaca 800.0 (8.7) 816.0 (7.2) 0.68 ns 1576.0 (7.6) 1600.0 (10.0) 0.73 ns L. Rosa indica L. 488.0 (6.6) 501.4 (5.5) 0.74ns 1213.6 (7.6) 1226.4 (6.5) 0.63 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site and P: Polluted

During autumn, the average number of epidermal cells on adaxial side was in the range of 488.0 - 5280.0/mm2 from non-polluted site plant species, while from polluted site the range was 501.4 - 5296.0/mm2. The M. azadirach had the largest number of epidermal cells and R. indica showed the lowest. Statistical analysis (t-test) exhibited that all the investigated plant species had non-significant variation in their number of epidermal cells during autumn between polluted and non-polluted sites (Table 7.3). The epidermal cells on abaxial surface during autumn were found 1205.6 - 5400.0/mm2 from non-polluted site plant species and 1213.6 - 6018.4/mm2 from polluted site. The maximum number of epidermal cells was in the leaves of M. azadirach and minimum was in P. granatum. Statistical analysis using t-test exhibited that all the plant species had non-significant variation in their number of epidermal cells during autumn season between polluted and non-polluted sites.

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Effect of air pollution on the number of stomata: The results regarding to number of stomata revealed that out of 12 investigated plant species 6 species i.e. R. indica, R. pseudoacacia, V. vinifera, F. carica, P. armeniaca and P. granatum showed no stomata on their adaxial surface, while on abaxial side all the plants showed the presence of stomata. All The observations during spring, summer and autumn are presented in Tables 7.4 - 7.6, respectively.

Table 7.4: Total Average number of stomata/mm2 in the leaves collected during spring Name of plants Number of total stomata Number of total stomata (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Eucalyptus tereticornis 221.4 (4.9) 216.0 (3.6) 0.45 ns 250.6 (2.3) 248.0 (3.6) 0.23 ns L. Pistaci avera L. 218.6 (3.2) 218.7 (2.5) 0.00 ns 578.6 (4.0) 576.0 (3.6) 0.23 ns Fraxinus excelsior L. 192.0 (3.0) 186.7 (3.5) 0.46 ns 280.0 (2.0) 277.4 (0.6) 0.41 ns Morus nigra L. 72.0 (3.6) 64.0 (3.6) 0.68 ns 653.4 (4.2) 648.0 (4.6) 0.39 ns Morus alba L. 50.7 (1.5) 56.0 (2.0) 0.82 ns 168.0 (5.6) 165.4 (4.1) 0.20 ns Melia azadirach L. 45.4 (2.5) 42.7 (2.5) 0.32 ns 434.6 (5.1) 432.0 (3.6) 0.23 ns Rosa indica L. A A A 146.6 (3.8) 146.6 (3.5) 0.00 ns Robinia pseudoacacia A A A 184.0 (2.0) 181.4 (2.5) 0.32 ns L. Vitis vinifera L. A A A 181.4 (2.5) 178.6 (2.5) 0.32 ns Ficus carica L. A A A 242.6 (6.0) 240.0 (5.0) 0.16 ns Prunus armeniaca L. A A A 280.0 (2.0) 274.7 (4.1) 0.40 ns Punica granatum L. A A A 306.6 (2.9) 304.0 (3.6) 0.23 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site and A: Absent

During spring, total number of stomata/mm2 at adaxial surface was in the range of 45.4 - 221.4 /mm2 from non-polluted site plant species (Table 7.4). E. tereticornis had the largest number of stomata and M. azadirach showing the least. From polluted site number of stomata was 42.7 - 218.7/mm2, with P. vera showing the maximum number of stomata and M. azadirach had the minimum. While in R. indica, R. pseudoacacia, V. vinifera. F. carica, P. armeniaca and P. granatum on adaxial surface no stomata were found. Statistical analysis (t-test) indicated that all the investigated plant species showed non-significant variation in their number of stomata during spring between polluted and non-polluted sites. On the abaxial side the total number of stomata was found in the range of 146.6 - 653.4/mm2 from non- polluted site plant species and 146.6 - 648.0/mm2 from polluted site. M. nigra had the highest number of stomata and R. indica showed the lowest. The t-test exhibited that

175 all the plant species had non-significant variation in their number of stomata on the abaxial side during spring between polluted and non-polluted sites.

Table 7.5: Total average number of stomata/mm2 in the leaves collected during summer

Name of plants Number of total stomata Number of total stomata (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Pistaciavera L. 210.6 (3.2) 194.6 (3.1) 1.60 ns 557.4 (2.3) 546.6 (2.9) 1.13 ns Eucalyptus 210.6 (4.0) 192.0 (3.6) 1.59 ns 229.4 (5.5) 218.6 (4.0) 0.81 ns tereticornis L. Fraxinus excelsior 181.4 (3.1) 168.0 (3.6) 1.13 ns 272.0 (3.6) 261.4 (2.5) 1.29 ns L. Morus nigra L. 64.0 (3.6) 50.6 (3.2) 1.27 ns 658.6 (5.5) 645.4 (5.1) 0.79 ns Morus alba L. 50.6 (1.5) 37.4 (1.5) 2.67** 152.0 (3.6) 141.4 (3.1) 1.07 ns Melia azadirach L. 34.6 (1.5) 32.0 (2.0) 0.41 ns 418.6 (2.5) 397.4 (2.5) 2.59* Rosa indica L. A A A 141.4 (4.0) 125.4 (3.5) 1.39 ns Robinia A A A 162.6 (3.8) 149.4 (3.2) 1.27 ns pseudoacacia L. Vitis vinifera L. A A A 176.0 (2.7) 157.4 (3.5) 1.63 ns Ficus carica L. A A A 234.6 (4.0) 218.6 (3.2) 1.52 ns Prunus armeniaca A A A 258.6 (4.6) 253.4 (4.9) 0.33 ns L. Punica granatum A A A 293.4 (5.5) 280.0 (5.0) 0.82 ns L. Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non- polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent During summer season the total number of stomata/mm2 at adaxial side (Table 7.5) was in the range of 34.6 - 210.6 /mm2 from non-polluted site plant species. P. vera and E. tereticornis had the largest number of stomata and M. azadirach showed the least. From polluted sites the range of stomata was 32.0 - 194.6/mm2 with P. vera showing the maximum number of stomata and M. azadirach had the minimum. The t- test indicated that except one specie (M. alba) all the investigated plant species showed non-significant variation in their number of stomata during summer between polluted and non-polluted sites. On abaxial surface the total average number of stomata recorded from non-polluted site plant species was 141.4 - 658.6/mm2 and from polluted sites it was 125.4 - 645.4/mm2. M. nigra had the highest number of stomata and R. indica showed the lowest. Statistical analysis exhibited that except one plant (M. azadirach) all the plant species had non-significant variation in their number of stomata during summer on abaxial surface between polluted and non- polluted sites.

176

Table 7.6: Total average number of stomata/mm2 in the leaves collected during autumn season

Name of plants Number of Stomata Number of Stomata (adaxial side) (abaxail side) NP S.D P S.D t NP S.D P S.D t Pistaciavera L. 205.4 (4.0) 186.6 (3.5) 1.63 ns 552.0 (3.6) 533.4 (3.5) 1.63 ns Eucalyptus 192.0 (1.7) 178.6 (2.5) 1.62 ns 224.0 (4.4) 208.0 (3.6) 1.36 ns tereticornis L. Fraxinus excelsior L. 168.0 (3.6) 149.4 (3.1) 1.87* 269.4 (3.2) 250.6 (3.5) 1.63 ns Morus alba L. 53.4 (1.5) 40.0 (1.0) 4.08*** 152.0 (3.6) 133.4 (3.1) 1.87* Morus nigra L. 53.4 (2.5) 42.6 (2.5) 1.30 ns 658.6 (6.4) 632.0 (6.6) 1.25 ns Melia azadirach L. 32.0 (1.0) 24.0 (1.0) 2.45** 397.4 (2.5) 381.4 (2.5) 1.95* Rosa indica L. A A A 133.4 (3.5) 117.4 (3.5) 1.39 ns Robinia A A A 157.4 (2.5) 138.6 (2.5) 2.27* pseudoacacia L. Vitis vinifera L. A A A 165.4 (4.0) 146.6 (3.5) 1.63 ns Ficus carica L. A A A 221.4 (4.5) 210.6 (3.5) 0.93 ns Prunus armeniaca L. A A A 264.0 (5.3) 242.6 (5.0) 1.30 ns Punica granatum L. A A A 285.0 (4.0) 264.0 (3.6) 1.81* Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

Table 7.6 showed that during autumn 6 plant species out of 12 showed the presence of stomata on their adaxial side that was in the range of 32.00 – 205.36/mm2 from non-polluted site. From polluted sites the range was 24.0–186.64/mm2. The lowest number of total stomata was in the leaves of M. azadirach and highest in P. vera. The t-test indicated that on adaxial side one plant (M. alba) was very highly significant (P<0.001), while M. azadirach was highly significant (P<0.01) and another one F. excelsior showed slightly significant (P<0.05) variation in their number of stomata during autumn. All the other remaining species were non-significant. On abaxial side total average number of stomata was found in the range of 133.4– 58.6/mm2 from non-polluted site and 117.4–632.0/mm2 from polluted site. The lowest number was in the leaves of R. indica and highest was recorded from M. nigra. On abaxial side out of 12 only 4 plant species i.e. M. alba, M. azadirach, R. pseudoacacia and P. granatum showed slightly significant differences at P<0.05 in their number of stomata between polluted and non-polluted site. All the other plant species showed non-significant difference in the number of stomata during autumn.

177

Number of closed stomata due to air pollution: The results regarding to number of closed stomata due to air pollution during spring, summer and autumn are presented in Tables 7.7 - 7.9, respectively.

Table 7.7: Total average number of closed leaf stomata /mm2 in the leaves collected during spring

Name of plants Number of closed Number of closed stomata stomata Adaxial side Abaxial side NP P S.D t NP S.D P S.D t Melia azadirach L. 0 0 0 8.0 (0.0) 16.0 (1.0) 2.45** Morus nigra L. 0 0 0 10.6 (0.6) 21.4 (0.6) 5.66*** Pistaci avera L. 0 16.0 (1.0) 4.89*** 13.4 (0.6) 26.6 (0.6) 7.07*** Fraxinus excelsior L. 0 0 0 5.4 (0.6) 8.0 (1.0) 0.82 ns Eucalyptus tereticornis 0 8.0 (0.2) 2.60** 16.0 (1.0) 16.0 (1.0) 0.00 L. Morus alba L. 0 0 0 0 (0.0) 0.0 (0.0) 0 Rosa indica L. A A A 2.7 (0.6) 8.0 (1.0) 1.63 ns Robinia pseudoacacia A A A 0 (0.0) 0 (0.0) 0 L. Vitis vinifera L. A A A 0 (0.0) 0.0 (0.0) 0 Ficus carica L. A A A 8.0 (0.0) 16.0 (1.0) 2.45** Prunus armeniaca L. A A A 10.6 (1.2) 13.4 (0.6) 1.41 ns Punica granatum L. A A A 10.6 (1.2) 16.0 (1.0) 1.63 ns Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted, P: Polluted, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

Table 7.7 shows that out of 12 plants only 6 plant species had stomata on their adaxial surface. During spring plants from non-polluted sites showed no one closed stomata. From polluted site out of 6 plant species only two species P. vera and E. tereticornis showed 16 and 8/mm2 number of closed stomata respectively. Statistical analysis using t-test indicated that on adaxial side both the plants showed very highly to highly significant variation at P<0.001 & P<0.01 in their number of closed stomata during spring, respectively.

On the abaxial side 03 plant species from non-polluted site i.e. R. pseudoacacia, V. vinifera and M. alba had no closed stomata while other plant species showed closed stomata in the range of 2.7 - 16.0/mm2. The largest number of closed stomata from non-polluted site was in E. tereticornis while R. indica had the least. Polluted sites plant species showed closed stomata in the range of 8.0–26.0/mm2. Highest number of closed stomata from polluted sites during spring was found in the

178 leaves of P. vera while R. indica showed the lowest. On abaxial side 02 plant species i.e. M. nigra and P. vera were reported to be very highly significant (P<0.001) in their number of closed stomata as compare to non-polluted sites. Another two M. azadirach and F. carica were highly significant (P<0.01), whereas all the other species showed non-significant variation in their number of closed stomata as compared to non- polluted sites plants during spring.

Table 7.8: Total average number of closed stomata/mm2 in the leaves collected during summer

Name of plants Number of closed stomata Number of closed stomata (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Pistaci avera L. 26.6 (1.5) 58.6 (2.5) 3.89*** 53.4 (1.5) 141.4 (2.5) 10.7*** Eucalyptus 18.6 (0.6) 45.4 (1.5) 5.35*** 26.6 (1.5) 72.0 (2.0) 6.94*** tereticornis L. Fraxinus excelsior L. 13.4 (0.6) 37.4 (1.5) 4.81*** 24.0 (1.0) 77.4 (2.5) 6.59*** Morus nigra L. 8.0 (0.0) 18.6 (0.6) 5.66*** 42.6 (2.5) 170.6 (1.5) 25.7*** Melia azadirach L. 5.4 (0.6) 18.6 (0.6) 7.07*** 37.4 (0.6) 93.4 (1.5) 11.2*** Morus alba L. 2.6 (0.6) 13.4 (0.6) 5.66*** 13.4 (0.6) 37.4 (1.5) 4.81*** Rosa indica L. A A A 13.4 (0.6) 40.0 (1.0) 8.16*** Robinia A A A 5.4 (0.6) 32.0 (1.0) 8.16*** pseudoacacia L. Vitis vinifera L. A A A 13.4 (0.6) 32.0 (1.0) 5.72*** Ficus carica L. A A A 24.0 (1.0) 61.4 (2.5) 4.54*** Prunus armeniaca L. A A A 24.0 (1.0) 69.4 (1.5) 9.09*** Punica granatum L. A A A 24.0 (1.0) 82.6 (2.5) 7.14*** Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non- polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

During summer on adaxial surface the total average number of closed stomata was found 2.6 - 26.6/mm2 from non-polluted site plants (Table 7.8) while from polluted sites it was in the range of 13.4 - 58.6/mm2. The largest number of closed stomata was in P. vera while M. alba showed the least. On abaxial surface from non- polluted sites average number of closed stomata was recorded 5.4 – 53.4/mm2. The lowest number recorded from the leaves of R. pseudoacacia and highest from P. vera. Polluted sites plant species showed in the range was 32.0 – 170.6/mm2 with M. nigra having the highest number of closed stomata and R. pseudoacacia and V. vinifera showed the lowest on abaxial surface. The t-test indicated that from polluted sites plant species the number of closed stomata on both side (adaxial and abaxial) was found to be very highly significant as compared to non-polluted sites plants at P<0.001.

179

Table 7.9: Total average number of closed stomata/mm2 in the leaves collected during autumn Name of plants Number of closed stomata Number of closed stomata (adaxial side) (abaxial side) NP S.D P S.D t NP S.D P S.D t Eucalyptus 37.3 (0.8) 77.3 (1.5) 8.02*** 42.7 (1.5) 98.7 (2.5) 6.81*** tereticornis L. Pistaciavera L. 32.0 (2.0) 82.7 (2.5) 6.16*** 80.0 (2.0) 216.0 (2.6) 15.7*** Fraxinus excelsior 26.7 (1.5) 58.7 (2.5) 3.89*** 48.0 (1.0) 101.3 (2.5) 6.49*** L. Morus nigra L. 13.3 (0.8) 26.7 (1.5) 2.67*** 112.0 (3.1) 280.0 (1.0) 51.4*** Morus alba L. 10.7 (0.8) 26.7 (1.5) 3.21*** 29.3 (1.5) 64.0 (3.0) 3.54*** Melia azadirach L. 8.00 (0.0) 24.0 (1.0) 4.90*** 50.7 (1.5) 128.0 (2.0) 11.8*** Rosa indica L. A A A 24.0 (1.0) 58.7 (1.5) 6.95*** Robinia A A A 21.3 (0.5) 50.7 (1.5) 5.88*** pseudoacacia L. Vitis vinifera L. A A A 26.7 (0.5) 48.0 (2.0) 3.27*** Ficus carica L. A A A 34.7 (1.5) 77.3 (2.5) 5.19*** Prunus armeniaca A A A 45.3 (1.5) 106.7 (1.5) 12.29** L. Punica granatum L. A A A 53.3 (1.5) 120.0 (3.0) 6.80*** Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

During autumn, on adaxial surface total average number of closed stomata was found in the range of 8.00 - 37.3/mm2 in the plants leaves from non-polluted site with E. tereticornis indicating the maximum number of closed stomata while M. azadirach showed the minimum (Table 7.9). Plants from polluted site showed the closed number of stomata in the range of 24.0 - 82.7/mm2, with P. vera had the largest number of closed stomata and M. azadirach showed the least during autumn season. On the abaxial surface the average number of closed stomata was in the range of 21.3 –112.0/mm2 from non-polluted site. Lowest were recorded from the leaves of R. pseudoacacia and highest from M. nigra. From polluted sites the closed stomata recorded were in the range of 48.0 – 280.0/mm2, with M. nigra had the highest number of closed stomata while Vitis vinifera showed the lowest number. Statistical analysis using t-test indicated that from polluted sites plants the number of closed stomata was found to be very highly significant than non-polluted site at P<0.001 on both adaxial and abaxial surfaces.

Number of Abnormal/injured stomata due to air pollution: The results regarding to number of abnormal/injured stomata due to air pollution during spring, summer and autumn are illustrated in Tables 7.10 -7.12, respectively.

180

Table7.10: Total average number of abnormal/injured stomata/mm2 in the leaves collected during spring season

Name of plants Abnormal/injured Abnormal/injured stomata stomata Adaxial side Abaxial side NP P S.D t NP P S.D t Eucalyptus tereticornis L. 0 13.3 (0.6) 7.07*** 0 8.00 (1.0) 2.45** Pistaci avera L. 0 8.00 (1.0) 2.45** 0 5.33 (0.5) 2.83*** Fraxinus excelsior L. 0 5.33 (0.6) 2.83*** 0 5.33 (0.6) 2.83*** Morus alba L. 0 2.67 (0.6) 1.41ns 0 5.33 (0.6) 2.83** Melia azadirach L. 0 0 0 0 10.7 (0.7) 5.66*** Morus nigra L. 0 0 0 0 13.3 (0.6) 7.07*** Rosa indica L. A A A 0 5.33 (0.6) 2.83*** Robinia pseudoacacia L. A A A 0 10.7 (0.6) 5.66*** Vitis vinifera L. A A A 0 5.33 (0.5) 2.83*** Ficus carica L. A A A 0 2.67 (0.6) 1.41 ns Prunus armeniaca L. A A A 0 2.67 (0.6) 1.41 ns Punica granatum L. A A A 0 8.00 (0.7) 2.00* Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non- polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

During spring season from non-polluted site plants no one abnormal or injured stomata were recorded on adaxial surface. From polluted sites only four plant species i.e. M. alba, F. excelsior, P. vera and E. tereticornis had 13.3, 8.0, 5.5, and 2.7/mm2 abnormal/injured stomata, respectively (Table 7.10). The results of t-test indicated that on adaxial side out of 4 plant species 2 species i.e. E. tereticornis and F. excelsior showed very highly significant variation at P<0.001. The P. vera was highly significant (P<0.01) while remaining one species i.e. M. alba showed non-significant difference in their number of abnormal/injured stomata. On abaxial side average number of abnormal/injured stomata/mm2 from the polluted sites plants species recorded were 2.7 – 13.3/mm2 with F. carica and P. armeniaca had the highest number of abnormal/injured stomata while M. nigra showed the least number. The abnormal/injured stomata/mm2 were completely absent during spring season from non- polluted site plants. Statistical test exhibited that on abaxial side out of 12 plant species 7 plants viz., P. vera, F. excelsior, M. azadirach, M. nigra, R. indica, R. pseudoacacia and V. vinifera) exhibited very highly significant variation (P<0.001). Other 2 species i.e. E. tereticornis and M. alba were highly significant, while P. granatum was slightly significant. The F. carica and P. armeniaca showed non- significant variation in their number of abnormal/injured stomata during spring.

181

Table 7.11: Total average numbers of abnormal/injured stomata (/mm2) in the leaves collected during summer season.

Name of plants Abnormal/injured stomata Abnormal/injured stomata adaxial side adaxial side NP S.D P S.D t NP S.D P S.D t Eucalyptus tereticornis L. 13.3 (0.6) 42.7 (2.1) 4.3*** 1.67 (0.8) 34.7 (1.2) 5.66*** Pistaci avera L. 8.00 (1.0) 29.3 (1.5) 4.3*** 2.00 (1.0) 45.3 (1.5) 5.88*** Fraxinus excelsior L. 8.00 (1.0) 24.0 (1.0) 4.9*** 1.67 (0.8) 32.0 (1.0) 5.72*** Morus alba L. 2.67 (0.6) 8.0 (0.0) 1.67* 1.00 (1.0) 18.7 (1.5) 2.14* Melia azadirach L. 0 0 0 2.00 (1.0) 56.0 (2.0) 6.12*** Morus nigra L. 0 0 0 2.00 (1.0) 50.7 (2.5) 4.22*** Rosa indica L. A A A 0.67 (0.8) 18.7 (0.6) 7.08*** Robinia pseudoacacia L. A A A 0.67 (0.8) 18.7 (0.6) 7.08*** Vitis vinifera L. A A A 1.33 (1.2) 26.7 (1.5) 3.21*** Ficus carica L. A A A 2.00 (1.0) 37.3 (2.5) 2.59** Prunus armeniaca L. A A A 1.00 (1.0) 24.0 (1.0) 4.89*** Punica granatum L. A A A 2.00 (1.0) 37.3 (1.2) 5.66*** Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non- polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

During summer, on adaxial surface the average number of abnormal/injured stomata/mm2 was found 29.3, 24.0, 42.7 and 8.0/mm2 from polluted site plant species (Table 7.11) while from non-polluted site it was 8.0, 13.3 and 2.67/mm2 in the leaves of P. vera and F. excelsior, E. tereticornis and M. alba, respectively. The abnormal/injured stomata on abaxial surface were found in the range of 18.67 – 50.67 from polluted site and 0.67 – 2.00/mm2 from non-polluted site plant species, respectively. Statistical test (t-test) indicated that at adaxial side one plant specie (M. alba) showed slightly significant (P<0.05) difference in their number of abnormal stomata. All the other remaining species showed highly significant variation (P<0.01). On abaxial side one plant species (M. alba) showed slightly significant and other one (F. carica) was highly significant. All the other remaining plant species indicated very highly significantly variation (P<0.001) in their number of abnormal stomatal during summer.

182

Table 7.12: Total average numbers of leaf abnormal/injured stomata (/mm2) in the leaves collected during autumn season

Name of plants Abnormal/injured stomata Abnormal/injured stomata at Adaxial side at Abaxil side NP S.D P S.D t NP S.D P S.D t Pistaci avera L. 24.0 (1.0) 66.7 (2.5) 5.19*** 32.0 (1.0) 82.7 (2.5) 6.16*** Eucalyptus tereticornis 24.0 (1.0) 80.0 (4.0) 4.29*** 24.0 (1.0) 61.3 (2.5) 4.54*** L. Fraxinus excelsior L. 16.0 (1.0) 40.0 (2.0) 3.67*** 24.0 (1.0) 58.7 (2.5) 4.22*** Morus alba L. 2.67 (0.6) 10.7 (0.6) 4.25*** 13.3 (0.6) 32.0 (2.0) 2.86*** Melia azadirach L. 0 0 0 32.0 (1.0) 96.0 (3.0) 6.53*** Morus nigra L. 0 0 0 24.0 (1.0) 85.3 (3.1) 6.15*** Rosa indica L. A A A 16.0 (1.0) 34.7 (1.5) 3.74*** Robinia pseudoacacia A A A 16.0 (1.0) 34.7 (1.5) 3.74*** L. Vitis vinifera L. A A A 16.0 (1.0) 50.7 (2.5) 4.22*** Ficus carica L. A A A 24.0 (1.0) 66.7 (3.5) 3.72*** Prunus armeniaca L. A A A 16.0 (1.0) 42.7 (1.5) 5.35*** Punica granatum L. A A A 24.0 (1.0) 64.0 (2.0) 6.12*** Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non- polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

Data presented in Table 7.12 revealed that during autumn on adaxial side the average number of abnormal/injured stomata/mm2 were 24.0, 16.0 and 2.67/mm2 from non-polluted site and 66.7, 80.0, 40.0, and 10.7/mm2 from polluted sites in P. vera, E.tereticornis, F. excelsior, and M. alba, respectively. On abaxial side number of leaf abnormal/injured stomata/mm2 was in the range of 13.3 – 32.0/mm2 from non-polluted site, with P. vera and M. azadirach had largest number of abnormal/injured stomata and M. alba L. showing the least. From polluted site number of abnormal/injured stomata was 34.7 – 96.0/mm2. The highest number of abnormal/injured stomata was in M. azadirach and lowest in M. albaduring autumn season. The t-test indicated that number of abnormal stomata found was very highly significant (P<0.001) from polluted site as compared to non-polluted site on both surfaces (adaxial and abaxial).

183

Total numbers and percentage of open stomata: Results about the total numbers with percentage of open stomata at polluted and non-polluted sites plants species during spring, summer and autumn are illustrated in Tables 7.13 – 15.

Table 7.13: Total average numbers of open stomata (/mm2) with percentage in the leaves collected during spring season

Name of Number of open stomata Number of open stomata plants adaxial side abaxial side NP S.D % P S.D % NP S.D % P S.D % Eucalyptus 222.0 (5.9) 100 195 (6.9) 90 234.6 (4.6) 93.6 224.0 (6.9) 90.3 tereticornis L. Pistaci avera L. 219.0 (7.4) 100 195 (7.4) 89 565.4 (7.6) 97.7 544.0 (4.5) 94.4 Fraxinus excelsior 192.0 (7.6) 100 187 (8.6) 100 272.0 (3.1) 98.1 266.6 (4.2) 95.2 L. Morus nigra L. 72.0 (3.1) 100 64.0 (4.0) 100 637.4 (8.8) 98.4 618.6 (6.3) 94.7 Morus alba L. 51.0 (2.0) 100 56.0 (2.0) 100 168.0 (5.4) 100 160.0 (4.4) 96.8 Melia azadirach 45.4 (2.5) 100 42.6 (2.0) 100 426.6 (8.1) 98.2 405.3 (7.6) 93.8 L. Rosa indica L. A A A A 144.0 (5.8) 98.2 133.4 (5.6) 90.9 Robinia A A A A 184.0 (4.8) 100 170.6 (6.6) 94.1 pseudoacacia L. Vitis vinifera L. A A A A 178.6 (5.6) 100 176.0 (4.0) 97.1 Ficus carica L. A A A A 234.6 (5.4) 96.7 221.4 (3.5) 92.2 Prunus armeniaca A A A A 269.4 (8.8) 96.2 258.6 (7.1) 94.2 L. Punica granatum A A A A 296.0 (7.8) 96.5 284.0 (5.7) 93.4 L. Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

During spring, in polluted site plant species the percentage of open stomata on adaxial surface (Table 6.13) was in the range of 89-100 % with F. excelsior, M. nigra, M. alba and M. azadirach had the largest number of open stomata on the adaxial side and P. vera showing the least. The plant species from non-polluted sites showed 100 % open stomata. On abaxial surface in the non-polluted site plant species the percentage of open stomata was in the range of 93.6 – 100 %, with M. alba, R. pseudoacacia and V. vinifera having the maximum percentage of open stomata while E. tereticornis showed the minimum percentage. The percentage of open stomata was 90.3 - 97.1% with V. vinifera indicating the largest percentage and E. tereticornis showing the least from polluted sites.

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Table 7.14: Total average number of open stomata/mm2 with percentage in the leaves collected during summer season.

Name of Number of open stomata Number of open stomata plants (adaxial side) (abaxial side) NP S.D % P S.D % NP S.D % P S.D % Morus alba L. 45.4 (2.5) 89.5 16.0 (2.1) 42.9 85.4 (3.1) 85.9 130.6 (9.1) 60.4 Fraxinus 160 (2.5) 88.2 106.6 (7.6) 63.5 152 (8.5) 86.3 234.6 (8.8) 58.2 excelsior L. Morus nigra L. 56.0 (3.5) 87.5 32.0 (2.5) 63.2 424 (9.1) 91.1 600.0 (9.2) 65.7 Eucalyptus 179 (2.5) 84.8 104.0 (8.1) 54.2 112 (7.5) 82.6 189.4 (7.6) 51.2 tereticornis L. Melia azadirach 29.4 (5.2) 84.7 13.4 (3.2) 41.7 248 (13.0) 87.3 365.4 (8.0) 62.4 L. Pistaci avera L. 176 (3.1) 83.5 106.6 (8.4) 54.8 360 (13.0) 87.6 488.0 (9.5) 65.9 Rosa indica L. A A A A 66.6 (2.5) 86.8 122.6 (5.5) 53.2 Robinia A A A A 98.6 (1.4) 93.4 152.0 (8.4) 66.1 pseudoacacia L. Vitis vinifera L. A A A A 98.6 (2.2) 86.4 152.0 (7.3) 62.7 Ficus carica L. A A A A 120 (4.5) 82.9 194.6 (4.5) 54.9 Prunus A A A A 160 (6.5) 87.6 226.6 (6.6) 63.2 armeniaca L. Punica A A A A 160 (7.5) 86.4 253.4 (7.4) 57.2 granatum L. Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

Percentage of open stomata on adaxial side during summer season was found in the range of 83.5-89.5% from non-polluted site with M. alba having the largest number of open stomata and P. avera showing the least. From polluted site the number of open stomata was 41.7 - 63.5% with F. excelsior and M. nigra having the largest percentage and M. azadirach showing the least on the adaxial side. On abaxial side during summer season, the percentage of open stomata from polluted site was 51.2 – 66.1%, with R. pseudoacacia showing the highest percentage and E. tereticornis indicating the lowest. From non-polluted sites it was 82.6 – 93.4 %, maximum was found in the leaves of E. tereticornis and minimum from R. pseudoacacia, respectively (Table 7.14).

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Table 7.15: Total average number of open stomata/mm2 with percentage in the leaves collected during autumn season.

Name of Number of open stomata Number of open stomata plants (adaxial side) (abaxial side) NP S.D % P S.D % NP S.D % P S.D % Morus alba 40.0 (2.6) 75.0 2.60 (2.1) 6.7 109.4 (4.1) 71.9 37.4 (2.1) 28.0 Morus nigra 40.0 (3.5) 75.0 16.0 (2.1) 37.5 522.6 (9.5) 79.4 266.6 (9.2) 42.2 Melia azadirach 24.0 (2.5) 75.0 0 0 314.6 (9.0) 79.2 157.4 (8.0) 41.3 Fraxinus 125.4 (6.7) 74.6 50.6 (4.1) 33.9 197.4 (7.5) 73.3 90.6 (8.5) 36.2 excelsior Pistaci avera 149.4 (4.0) 72.7 37.4 (2.5) 20.0 440 (8.5) 79.7 234.6 (8.5) 44.0 Eucalyptus 130.6 (4.1) 68.1 21.4 (1.1) 11.9 157.4 (7.6) 70.2 48.0 (7.5) 23.1 tereticornis. Rosa indica. A A A A 93.4 (6.3) 70.0 24.0 (3.5) 20.5 Robinia A A A A 120 (8.5) 76.3 53.4 (4.4) 38.5 pseudoacacia Vitis vinifera A A A A 122.6 (6.2) 74.2 48.0 (2.2) 32.7 Ficus carica. A A A A 162.6 (4.6) 73.5 66.6 (4.5) 31.7 Prunus A A A A 202.6 (6.5) 76.8 93.4 (4.5) 38.5 armeniaca. Punica A A A A 208.0 (7.5) 72.9 80.0 (5.4) 30.3 granatum Mean: 30 readings, S.D: Standard deviation, ns: Non-significant, t: Calculated values in t-test, NP: Non-polluted site, P: Polluted site, *: Slightly, **: Highly, ***: Very highly significant and A: Absent

The percentage of opened stomata from non-polluted site plant species on adaxial side during autumn season was in the range of 68.1 – 75.0% (Table 7.14) with M. alba, M. nigra and M. azadirach had the largest percentage of open stomata and E. tereticornis showed the least. From polluted site it was 6.7 - 37.5 %, with M. nigra had the highest percentage and M. alba showed the lowest, on the adaxial side. One plant species (M. azadirach) from polluted site on adaxial side showed no open stomata during autumn. On abaxial surface during autumn the percentage of opened stomata at polluted site was 20.5 – 44.0 %, with P. vera showing the maximum percentage of open stomata and R. indica indicating the minimum percentage. The non-polluted showed 70.0–79.7% open stomata. Maximum were in the leaves of R, indica and minimum were recorded from P. vera.

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7.4. DISCUSSION

7.4.1. Epidermal cells: Statistical test indicated that all the plant species during all the seasons showed non-significant variation in their number of epidermal cells between polluted and non-polluted site on both surface (adaxial & abaxial). Seasonally the maximum average number of epidermal cells/mm2 was recorded during spring and minimum during autumn, this might be due to small size of the epidermal cells during spring that became large in size during autumn season. The number of epidermal cells was high in polluted site plant species with respect to non- polluted site, which might be due to different reasons like at urban area the level of air pollutants remained high due to vehicular emission, burning of hospital and household waste, burring of gases, fire and bomb blast and poor road conditions etc. make the urban environment wormer, that cause the cell division before maturation. Similar observation was also obtained by Sharma & Deepti, (2000) they found that leaves of treated plants by air pollutants show increased number of epidermal cells though smaller in size as compared to those leaves from control plant. Total numbers of epidermal cells on adaxial surfaces during all three seasons were significantly low as compared to abaxial surface that is the natural phenomena.

7.4.2. Number of stomata: Statistical analysis exhibited that total number stomatal cells during spring and summer seasons showed non-significant variation between polluted and non-polluted sites. During autumn season the total number of stomata were slightly to very highly significant between two sites (polluted and non-polluted sites) on both surfaces at P<0.01 & P<0.001. The study exhibited that large number of stomata in urban plant species, might be due to high concentration of air pollutants i.e. Pb, Cu, CO, SO2, NO and particulate matters in urban city areas, similar observation was also supported by other researcher like Alireza et al., (2010), they investigated whether leaves of plane trees (Platanus orientalis) are damaged by traffic pollution, trees from a mega-city (Mashhad, Iran) and found that leaf size and stomata density were lower at the urban site and leaf surfaces were highly loaded by dust particles. They also reported that soil and air from the urban center showed enrichment of several toxic elements, but only lead was enriched in leaves. Ticha, (1982) and Masarovicova, (1991) demonstrated that stomatel density was strongly affected by the polluted environment. The observation reported by Sharma & Deepti, (2000) also supported these views. Moreover the study revealed that the total number

187 of stomata varied from season to season, specie to specie and surface to surface (adaxial and abaxial). The variation in stomatal number between two surfaces and season to season was also reported by Evans and Ting, (1974).

7.4.3. Number of closed stomata: Statistical analysis using t-test indicated that number of closed stomata during all the seasons on both surface (adaxial & abaxial) was highly to very highly significant in polluted site plant species as compared to non-polluted sites plant species at P<0.01 and 0.001 significant level. The variation in number of closed stomata between polluted and non-polluted site and between adaxial and abaxial side in this study was also supported by Lerman & Darley, (1975), Ricks & Williams, (1974) and Williams et al., (1971), they investigated and revealed that the foliage from trees near air pollution sources can even be ‘coated’ with particulates and these particulates may cause stomatal occlusion, thus, leading to reduced photosynthesis. Seasonally the highest number of closed stomata during autumn from polluted sites plants might be due to different reasons like leaf age and maximum air pollution i.e, particulate matters, SO2, NO2, Pb and other heavy metals during autumn season in the city area. Similar observation was also reported by Shenxi & Lue, (2003). David et al., (1981) revealed that air pollutants induced stomatal closure and injury. Carlos and Lorenzo, (2001) indicated that NO and others derived compounds was responsible for the induction of stomatal closure.

7.4.4. Number of abnormal/injured stomata: The t-test exhibited that except few species all the plants showed slightly to very highly significant variation in their number of abnormal/injured stomata from polluted to non-polluted sites on both sides (adaxial & abaxial). The observations of Sharma and Deepti, (2000) supported our results; they reported structural abnormalities in pollutants treated plants on both surfaces of the leaf. Alireza et al., (2010) investigated and found that the leaves of plane trees (Platanus orientalis) of urban area are damaged by traffic pollution. David et al., (1981) revealed that the air pollutant induced stomatal closure and injury at urban area. Statistical analysis of the data (t-test) also indicated that M. alba on adaxial surface in spring and summer, while F. carica and P. armeniaca only in spring had non-significant variation in their number of abnormal/injured stomata between polluted and non-polluted sites, which might be due to minimum air pollution during spring season in the urban areas. The research also exhibited that there was seasonal variation in the number of abnormal or injured stomata’s.

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Seasonally high abnormalities in stomata’s found during autumn from polluted sites species, might be due to high concentration of dust fall and other toxic gases at city area during autumn. Similar observation was also reported by Yousufzai et al., (1970, 1984 & 1987) and Chotani et al., (1975) they indicated high amount of pollutants in Karachi city during autumn season and found that the particulates type air pollutant such as ash, dust and dirt fall on the top of leaves. These particulates do not enter the leaf but may damage it by mechanical abrasion of the surface, block and reduce the food making ability of plants.

7.4.5. Percentage of open stomata: Data of the study indicated that there was significant variation in the number of open stomata’s from season to season, specie to specie, surface to surface and site to site (polluted and non-polluted). Low percentage of open stomata from polluted site plant species with respect to non-polluted site might be due to high amount of air pollutants in Quetta city like particulates type air pollutant such as ash, dust and dirt fall on the leaves (as already reported in chapter 3 of this dissertation). These particulates may damage it by mechanical abrasion of the surface and can also block the stomata, similar observation was also reported by Yousufzai et al., (1970, 1984 & 1987) and Chotani et al., (1975). Particulate matter can also block and injured the stomata and reduce the food making ability of plant. Curtis & Wang, (1998) and Medlyn et al., (2001) reported that stomatal responses to elevated CO2 are quite variable with literature reviews, they indicate that average reductions ranges was from 11 to 40%. The above mentioned results of this study also indicated that highest percentage of open stomata during spring and lowest during autumn supported the views that as the age of leaf increased they exposed more time to the air pollutants, may cause blocking of stomata during autumn. Similar observations were also reported by other researchers Sharma and Butler, (1973 & 1975), Garg and Varshney, (1980), they found that the air pollutants created negative effects on stomata densities and their opening. Other worker Jeffrey et al., (2003) also supported the present observations.

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7.5. CONCLUSIONS

After discussion of the investigated parameters in the study following findings are made as under:

All the investigated parameters (except numbers of epidermal cells) were badly affected due to air pollutants. A large number of leaf stomata’s were closed and abnormal/injured from polluted sites plants species that cause adverse effects on their productivity. It was also concluded that adverse effect of air pollutants increased with increase of leaf age, particularly in the early stage and reached a maximum when the leaf was completely expanded (in autumn).

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RECOMMENDATIONS

The ultimate goal of my research is to develop strategies to reduce the risk of ambient air pollutions adverse effect on plants, human health and the environment. The complete control of air pollution is an impossible task. It is a global issue and a single nation cannot overcome the menace of atmospheric pollution. Since the industrialized countries are responsible for 80% of this trouble, therefore, they should contribute accordingly towards the mitigation measures.

Air quality in Quetta city is degrading day by day as discussed in this dissertation. The deterioration of air quality is caused by the activity of different factors like i.e., vehicles, industries, waste disposal or deforestation activities and burning of wastes materials, that directly or indirectly affecting the plant growth, human health and ecosystems. A sufficient amount of relevant and reliable information about the problem (air pollution) of an area is necessary at each stage for successful improving and controlling the air quality. From the discussions in chapter 3-7 of this thesis, it is possible to identify the sources and impact of air pollutants within the city. After the identification of air pollution sources following recommendations are made to reduce the air pollutants and to improve the air quality.

1. Reducing Transports pollution: A number of options are now available and are being used in cities to counter the air pollution resulting from transportation. Although technical measures alone are not sufficient to ensure the desired reduction of urban air pollution, they are an indispensable component for any cost effective strategy for limiting vehicle emissions. Fuel and the vehicle types have a great impact on air quality situations. This is true in Pakistan that the growth rate of private vehicles ownership is increasing day by day. In developing countries like other thick populated and polluted cities, Quetta also has a large numbers of older vehicles that were cheaply imported. So overall strategies to reduce vehicular pollution may include:

i. Vehicle inspection and maintenance (VIM): Emissions from old vehicles can be successfully reduced by inspection and maintenance of the vehicles and by ensuring that new vehicles remain in good condition. Pollutants such as carbon monoxide (CO) and hydrocarbons (CnHn) of individual vehicles

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can be reduced by up to 25% through vehicles inspection and maintenance process.

ii. Improving fuel quality: The air pollutants generated by engine combustions (like sulfur and lead) can be reduced by the used of good quality fuels in vehicles. Using more volatile diesel addresses the problem of black smoke from heavy diesel-powered vehicles, such as buses and trucks. Improving fuel quality should also involve the introduction of alternatives fuels as, for example, are bio fuels from crops, used cooking oils or bio gas from sewerage and waste. An other alternatives fuels is the hydrogen kits and natural gas (CNG) which not contain lead or sulfur, and TSP (total suspended particulate)

and is lower in NOx, SO and CO than conventional fuel. iii. Introducing new vehicle technologies: New vehicle technologies help to reduce pollution. These include promoting the use of three-way catalysts that can reduce emissions up to 90% per vehicle or particulate filters for diesel vehicles. Other types of vehicles run on electricity and the first prototypes of fuel cell powered cars are under testing. But those only fill a small niche market. Hybrid technology will take an intermediary role before switching to new technologies, such as the hydrogen economy. Installing pollution control equipment like particle traps in vehicles or switching from two-stroke to four- stroke engines that allow the use of catalytic converters.

iv. Setting strict standards for newly imported vehicles: In developing countries like Pakistan, by setting strict standards for newly imported vehicles can help to reduce the already existing problem of vehicle pollution in the city.

v. Managing travel demand and improving transportation supply: Cities cannot continue to expand their urban transportation systems forever. Although some expansion is necessary, the economic, social, and environmental costs of doing so are prohibitive. Instead, cities must re- examine urban transportation demand and devise, new strategies that provide maximum access at minimum total cost. Parking spaces, driveways and any widening there of shall be provided and maintained with stable surfaces such

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as, concrete or other hard surfaced material, crushed stone or gravel, and shall be maintained in a dust free condition.

2. Making Strategies to Reduce Air Pollution from Industrial Sources: The industrial air pollution can be reduced by;

a) It is strongly recommended to focus urban air quality policy on the implementation of best available/affordable techniques for specific industrial processes. The advantage is that local governments can make an action plan for the implementation of best available and/or affordable techniques in cooperation with the industries themselves.

b) Emission standards for specific types of industries should be set. However, experience shows that enforcement is often weak; it is thus recommended that this enforcement strategy be combined with the best available/affordable techniques. Promoting cleaner production (prevention solutions rather then end-of-pipe remedies)

c) Restricting the location of new industries; vicinity to residential zones or other sensitive areas should be prohibited.

d) Relocation of existing industries away from residential zones if economically viable. Controlling of emissions in sensitive areas, for example by implementing special control areas or smoke-free zones.

e) Area planning - based on emission assessments and air quality objectives, cities can determine what kind of industrial activities and pollution control equipment is required per area (including sensitive areas as well as industrial and commercial areas).

f) Setting priorities by focusing on pollution control devices for the most serious polluting factories.

3. Reducing Air Pollution, Caused by Open Burning of Wastes and Emanating from Natural Sources: For the rescue of local air quality enhancement different organizations (i.e. Government sectors, Universities, research institutions NGO’s and private sectors) should make their coordination with each other. Strategies should be

193 made for reducing air pollution caused by open burning of wastes and emanating from natural sources. In many developing cities Like Quetta, lacking a comprehensive system of waste collection, open burning of waste a major contribution to the city’s air quality. At the same time, pollution due to natural sources, such as dust (particulate matter) emanating from open lands contribute to the city’s air quality situation. Open burning of waste can produce mixed fumes that are very toxic. In order to address this issue, it is strongly recommended to identify areas where burning occurs; to assess the extent of the problem in terms of how many residents practice uncontrolled domestic waste burning; then to assess the adequacy of the city’s disposal provisions in these areas; and to improve these facilities and the capacities for waste management, if necessary.

4. Natural resources used for managing air quality: Flying dust carried by the wind can cause high levels of TSP (total suspended particulate) in the air (sometimes up to 50%). Comprehensive means to control such dust pollution should be adapted that include: 1. Adoption of measures to control the stocks of powdery items; 2. Mobilization of resources to gradually adopt the practice of spraying water to clean roads as opposed to the traditional dry cleaning (only where water resources are abundant). 3. Improvement of environmental management at construction sites for reducing dust emissions. 4. Strengthening the enforcement of regulations to control waste burning and Improvement of municipal waste collection and disposal practices.

5. Urban air quality improvement through air pollution tolerant plant species of the area:

i. It has been deduced from present study Chapter 3 that, in certain residential areas and along the road sides the SPM levels in Quetta city was in critical level. There fore it is necessary to develop the Green Belt with dense plantation of Effective Dust capturing plant species, highly and moderately air pollution tolerant species.

ii. Based on the studies (chapter 5), the following plant species; Pinus halepensis (Miller.), Eucalyptus tereticornis L., Fraxinus excelsior L., Robinia pseudoacacia L., Punica granatum L., Prunus armeniaca L. and Elaeagnus angustifolia L have been observed as the highly and moderately tolerant

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species in the climate of Quetta city. These plants are recommended for the Green Belt / Urban Forest Development in vicinity of Residential areas; Road Sides and Industrial Sites. The green belt with efficient dust capturing plants can act as efficient biological filters, removing significant amounts of particulates from urban atmosphere and may prove not only as cost effective technology, but also enhance aesthetic value at urban agglomerations.

iii. The Geographical, Environmental, Morphological, Anatomical & Physiological aspects of plants species have been found influencing the dust capture by plant species, therefore following criteria should be adopted for selection of plant species for urban forest green belt development.The species should be adapt to site and should be able to produce optimum harvest on a sustained basis for example tree like Ficus religiosa (Peepal), Ficus bengalensis (Banyan), Ficus elastica (Indian Rubber) and Artocarpus integrifolia (Jack Fruit). iv. The leaf litter should decompose quickly thus adding organic matter to the soil tree like Acacia farmesiana (Vilayati kicker), Delonix regiosa (Gulmohar), Accacia nelotica ((Babul), Azardirachta indica (Neem) Melia azedarch (Melia) are suitable for the purpose.The morphological characters of the species must suit the objectives of plantation and the cultivation practice; e.g. a wide crown may be preferred for dust capturing and fuel wood plantation but small-narrow crown with minimum effect on agriculture crop and providing valuable wood. v. Multi-purpose tree plant species have a special significance in fulfilling the objectives of environment as well as needs of the people. The combination of species to address the local needs is more beneficial. The trees like Quaking Aspen (Populus tremuloides); Blue Gum (Eucalyptus globules; Acacia farmesiana (Vilayati kicker), Delonix regiosa (Gulmohar), Accacia nelotica (Babul), Azadirecta indica (Neem) Melia azedarch (Melia) are more valuable. vi. The interactive factors involving urban trees and air quality needs to be further investigated in order to understand the impact of urban trees on air quality. Future research should be needed to investigate the interactive relationships of

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pollution removal; trace gas emissions; and air temperature and building energy use effects of urban trees on overall air quality. vii. The particulate level at various urban areas are moderate to critical level therefore critical level, cost effective particulate control technology will be necessarily required for controlling fugitive emissions. viii. The plant species constituting Green Belt of Effective Dust capturing plant species should be developed around residential areas/ industrial area, as the Trees can act as efficient biological filters, removing significant amounts of particulate pollution from urban atmospheres. This is a cost effective technology for controlling particulate and gaseous emission generated due to vehicular movement, domestic emission and even industrial emissions. Future research should be needed to investigate the impact of climate change on human health, plant growth and local environment.

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