Cardiff Metropolitan University Prifysgol Fetropolitan Caerdydd
Determination of heavy metal contamination in the surface sediments at
Sohar Industrial Port (SIP) and the nearby coastal regions
By
Abdulaziz Al Sawai
PhD
April 2015
Determination of heavy metal contamination in the surface sediments at
Sohar Industrial Port (SIP) and the nearby coastal regions
Abdulaziz Al Sawai, BSc. Education (Chemistry), MSc in Analytical Chemistry.
Thesis submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Environmental Health at Cardiff Metropolitan University School of Health Sciences
Supervisors
Prof. George. Karani- Director of study
Dr. Peter Sykes
Dr. Salim Al-Rawahi
April 2015
DECLARATION
I hereby declare that this research is the result of my own investigation under the supervision of my supervisors.
I declare that the work has not previously been accepted in substance for any degree and is not being concurently submitted for any degree at another university.
I hereby give consent for my thesis, if accepted, to be available for photocopying and for inter- library loan, and for the title and summary to be made available to outside organizations.
Abdulaziz Al sawai
Signature......
Date ...... April 2015......
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DEDICATION
I would like to dedicate this thesis to my mother, brothers and sisters who cared for me since my childhood, and since my father's death. I would like to thank them for their efforts and their encouragement to me at all times in my life, which have helped me to achieve my aims.
Furthermore, I would like to dedicate this research to my wife, daughters and sons for their efforts and patience in giving me time to finish the work.
I would like to thank all of them for their support throughout the process. They have all been an inspiration for me in my bid to complete this thesis.
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ACKNOWLEDGEMENTS
Glory and praise be to Almighty ALLAH (God) who enabled me to complete this research.
I am very thankful to Prof. George Karani, the director of study, for giving me a chance to study at Cardiff Metropolitan University under his supervision. I would like to thank him for his highly skilled supervision, helpful suggestions and excellent guidance in order to achieve the aims of the research.
I would like to thank Dr. Peter Sykes, second supervisor, for his support, constant guidance and feedback during the period of the study.
I would like to thank Dr. Salim Al Rawahi, Co-supervisor, for his great effort, guidance, and compassion, for harnessing his time for me and his sincere efforts to raise my aspirations in order to achieve this research.
I would like to extend my gratitude to all government authorities, private sector bodies and individuals, who provided information, helped me during the study and provided kind assistance and excellent contributions to the process of the research. In particular, I would like to take this opportunity and thank the Environmental Research Centre, Sohar University, for their great support and excellent guidance. Thanks also go to the Ministry of Higher
Education and to the Food and Water Laboratories Centre, Ministry of Regional
Municipalities and Water Resources, for their co-operation during my study. Moreover, thanks and appreciation are expressed to the Sohar Environmental Unit, Ministry of
Environment and Climate Affairs, and to the Sohar Industrial Port Company for their support and for providing various types of assistance during the study. I would like to extend my gratitude to College of Science, Sultan Qaboos University, for their assistance to achieve this research. Additionally, I would like to thank all companies at Sohar Industrial Company for their assistance in the period of this research.
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It gives me pleasure to thank and appreciate the contribution of Under-Secretary of the
Ministry of Environment and Climate Affairs, his Excellency, Najeeb Al Rawas, for his excellent effort and encouragement of the work in order to promote scientific research and study in Oman.
I would like to thank Dr. Abood Al Sawafi, Ex Vice Chancellor of Sohar University, for his support and provide me this opportunity to complete my studies.
I would like to extend my gratitude and appreciation to Dr. Nasser Al Jahwari, Head of the
Department of Archaeology in Sultan Qbaoos University for his continuous interest in this research. My thanks are also extended to Prof. Tony Chiffings and Prof. Steve Hall, Director of the Environmental Research Centre – Sohar University, and Dr. Lance Bode for their time, helpful suggestions and continuous assistance during the period of the research. In addition, I would like to send my gratitude and appreciation to Dr Ali Al Manai in Higher Technology
College and Dr. Ashraf Al Hinai, Dr.Abdulaziz Al Hashmi and Charles Saki Bakheit, in
Sultan Qbaoos University for their efforts. I would like to thank my friends Eng. Nasser
Rashid Al Jahwari and Dr Mustafa Megrahi for their efforts and assistance to achieve my aims.
Finally, I would like to extend my gratitude and appreciation to all of my family members and friends as they were the source of my inspiration in this study.
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ABSTRACT
An increase of heavy metals in the natural environment, as a result of human development activities, may lead to further impacts on environment and human health. The project aim was to investigate the potential impact of heavy metal sources on the marine sediment at
Sohar Industrial Port (SIP) and nearby coastal regions. SIP was established in 1999 and this is the first comprehensive evaluation of heavy metal pollution at the port.
The research focused on the levels of Al, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, V, Zn , Hg,
As and Sn over a period of two years. The concentration of anions F, Br, Cl and SO4 in the sediment was also evaluated.
The research has, based on published literature, evaluated the public and environmental issues at SIP and nearby regions area. A theoretical fingerprinting technique was used to establish sources of pollution in the SIP region using a combination of field data, laboratory analyses of samples and statistical modeling techniques.
Results from the study indicate that concentration of heavy metals was significantly higher at the SIP than in the nearby coastal regions. The data indicated that Cd, Cr, Cu, Ni, Pb, Zn, Hg and As sediment concentrations exceeded levels for International Sediment Quality
Guidelines (ISQG) values from USA, Canade, Holland, Australia and New Zealand . Heavy metals that exceed ISQG provide higher potential risks of contamination and may cause human health problems at the SIP and surrounding areas.
Potential sources of pollution at SIP include petrochemical industries, various metal processing industries, cooling water outfalls, dust emissions from industries and open hazardous storage sites. Consideration needs to be given to the use of addition new technologies for cleaning of pollution in the environment around SIP. The project proposes development of policies and strategies to mitigate and prevent further sediment contamination at SIP and nearby regions. v
TABLE OF CONTENTS
DECLARATION ...... i
DEDICATION ...... ii
ACKNOWLEDGEMENTS ...... iii
ABSTRACT ...... v
TABLE OF CONTENTS ...... vi
List of Figures ...... xii
List of Tables ...... xix
Chapter 1: Introduction ...... 2
1.1 Introduction ...... 2
1.2 Research problem ...... 3
1.3 Rationale and Contribution of the Research ...... 4
1.4 Definition of the research topic ...... 6
1.4.1 Aim ...... 6
1.4.2 The objective of the study: ...... 7
1.5 Limitations ...... 7
1.6 Thesis Layout ...... 8
2 Chapter 2: Literature Review ...... 10
2.1 Introduction ...... 10
2.2 Pollution and Sources ...... 11
2.3 Marine Sediments:...... 18
2.4 Chemical Compositions of Marine Environment: ...... 22
vi
2.5 Impacts of Heavy Metals...... 27
2.6 Risk Assessment Methods and Policies Assessing Environmental Pollution ...... 31
2.6.1 Risk Assessment Terminology: ...... 31
2.6.2 Risk Assessment methodology ...... 33
2.6.2.1 Problem formulation: ...... 34
2.6.2.2 Assess Risk ...... 35
2.6.2.3 Appraisal option ...... 36
2.6.2.4 Address Risk ...... 36
2.6.3 Risk Assessment Policy and Oman methodology ...... 37
2.7 Finger Printing Technique ...... 39
2.7.1 Fingerprinting methods ...... 42
2.7.2 The importance of Fingerprinting ...... 45
2.7.3 Finger printing in pollution assessment ...... 47
2.8 Conclusions ...... 50
Chapter Three ...... 51
3 Chapter 3: Methodology ...... 52
3.1 Introduction ...... 52
3.2 Site Description ...... 53
3.2.1 Study Area: North Al Batinah, Sohar, Oman Coastal Environment...... 53
3.2.2 Sohar Industrial Port ...... 56
3.3 Pilot study ...... 59
3.3.1 Pilot Study Result ...... 61
3.4 Monitoring Area ...... 64
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3.5 Field Sampling ...... 66
3.6 Chemical preparation for Heavy Metals ...... 70
3.6.1 Microwave digestion and samples preparation for Inductively Coupled Plasma
Optical Emission Spectrometer (ICP-OES) ...... 70
3.6.2 Using ICP-OES ...... 71
3.6.3 ICP-OES Running and Analyzing ...... 71
3.7 Sample Analysis for Anions – Ion Chromatography (IC) ...... 72
3.7.1 Sample Extraction ...... 73
3.7.2 Eluent and regeneration solutions &Demonized water ...... 73
3.7.3 Preparation of Eluent ...... 73
3.7.4 Preparation of standard solutions ...... 74
3.8 Statistical analysis ...... 74
Chapter Four ...... 75
4 Chapter 4: Result ...... 76
4.1 Introduction ...... 76
4.2 Contamination levels of sediments at Sohar Industrial Port (SIP) and the
surrounding area ...... 77
4.2.1 Pollutant data in 2011 and 2012...... 77
4.2.2 Pollutant data at SIP ...... 86
4.2.3 Pollutant data at west and east of the port...... 89
4.2.4 Pollutant data at all sites in 2011 & 2012 ...... 95
4.2.5 Concentrations of anions at all sites in 2012 ...... 101
4.3 Statistical Analysis of data ...... 103
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4.3.1 Correlation of data between sites and years for heavy metals ...... 104
4.3.2 The correlation between Heavy metals and anions 2012...... 121
4.3.3 ANOVA Analysis ...... 131
4.3.3.1 One Way ANOVA ...... 131
4.3.3.2 Two Way ANOVA 2011 and 2012 ...... 139
4.3.3.3 Analysis of differences between means ...... 145
4.4 Comparison between the current study data and the International Sediment Quality
Guidelines (ISQG)...... 147
4.5 Conclusion:...... 162
5 Chapter 5: Discussion ...... 164
5.1 Introductions...... 164
5.2 Risk assessment of SIP and its surroundings ...... 165
5.2.1 Heavy metals exceeded international sediment quality guidelines in this study
166
5.2.1.1 Cadmium ...... 167
5.2.1.2 Chromium...... 168
5.2.1.3 Copper ...... 169
5.2.1.4 Nickel ...... 170
5.2.1.5 Lead ...... 171
5.2.1.6 Zinc...... 173
5.2.1.7 Mercury ...... 174
5.2.1.8 Arsenic ...... 175
5.2.1.9 Molybdenum ...... 176
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5.2.2 Environmental and health risk perspective: ...... 183
5.3 Sources of pollution in the SIP region using a combination of field data and inventory data ...... 188
5.3.1 Sources of Pollution at SIP and surrounding areas ...... 190
5.3.1.1 Anthropogenic Sources: ...... 190
5.3.1.1.1 Industrial Sources: ...... 191
5.3.1.1.1.1 Sources of Aluminum: ...... 191
5.3.1.1.1.2 Sources of Cadmium ...... 193
5.3.1.1.1.3 Sources of Cobalt ...... 194
5.3.1.1.1.4 Sources of Chromium ...... 195
5.3.1.1.1.5 Sources of Copper ...... 196
5.3.1.1.1.6 Sources of Iron ...... 197
5.3.1.1.1.7 Sources of Manganese ...... 202
5.3.1.1.1.8 Sources of Molybdenum ...... 202
5.3.1.1.1.9 Sources of Nickel ...... 203
5.3.1.1.1.10 Sources of Lead ...... 204
5.3.1.1.1.11 Sources of Vanadium ...... 205
5.3.1.1.1.12 Sources of Zinc ...... 206
5.3.1.1.1.13 Sources of Mercury ...... 207
5.3.1.1.1.14 Sources of Arsenic ...... 208
5.3.1.1.1.15 Sources of Tin ...... 209
5.3.1.1.2 Domestic sources: ...... 220
5.3.1.2 Geochemical Sources ...... 222
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5.4 Conclusion:...... 226
Chapter Six...... 227
6 Chapter 6: Conclusions and Recommendations ...... 228
6.1 Introduction ...... 228
6.2 Conclusions of data from the current project ...... 229
6.3 Recommendations ...... 231
6.3.1 Recommendations based upon the results ...... 231
6.3.2 Secondary recommendations ...... 232
6.3.2.1 Risk Mitigation Technology...... 232
6.3.2.2 Hazardous Waste Management ...... 232
6.3.2.3 Marine and Coastal Management Plan...... 233
6.3.2.4 Re-Conduct Baseline Study of SIP and Surrounding Areas ...... 233
6.3.2.5 Establish World-Class Environmental Policies and Permits for SIP ...... 234
6.3.2.6 Development of Environmental Management Programs and Strategies for
SIPC at Sohar Port ...... 234
6.3.2.7 Establishment of Food and Environment Control Centre ...... 235
6.3.2.8 Planning for Environmental Events & Awards ...... 235
7 References ...... 236-254
8 Appendix A: Approval letter from MECA to collect samples from SIP ...... 255
Appendix B: Approval letter from MECA to Company at SIP to provide detail about chemical in the plant...... 256-263
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List of Figures
Figure 2-1: Possible environmental impact of industrial emissions (ICC et al., 1997) ...... 13
Figure 2-2: A framework for environmental risk assessment and management (Gormley et al.,
2011) ...... 34
Figure3-1:Map of the Sultanate of Oman showing the extent of the Al Batinah plain and the location of the cities of Shinas, Liwa and Sohar (Source: Ministry of Transport and
Communications) ...... 54
Figure3-2: Number of Vessels at SIP from 2007 to 2013 (Source: SIPC) ...... 57
Figure 3-3: The layout of the SIP showing the co-location of different industrial production facilities. (Source: SIPC) ...... 58
Figure3-4: Locations of the pilot areas (not to scale) ...... 60
Figure3-5: The mean concentrations and standard error samplings of a pilot study of Cd and
Mo...... 62
Figure3-6: The mean concentrations and standard error samplings of a pilot study of Co, Pb,
V and Zn...... 62
Figure3-7: The mean concentrations and standard error samplings of a pilot study of Cr and
Cu...... 63
Figure 3-8: Location of the sampling sites used in the study. Sites labeled as A were either side of the ocean outfall at the eastern end of the Port. Results from the three sample sites to the west of the Port (B, C and D) were designated as such for an initial assessment of the results and likewise for sites to the east of the Port (E, F and G)...... 65
Figure3-9: Sieve Process continued ...... 69
4-1: Mean and standard error (S.E.) of Al concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 78
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Figure 4-2: Mean and standard error (S.E.) of Cd concentrations at each sample site showing the variation between sites in 2011& 2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 79
Figure 4-3: Mean and standard error (S.E.) of Co concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 79
Figure4-4: Mean and standard error (S.E.) of Cr concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 80
Figure4-5: Mean and standard error (S.E.) of Cu concentrations at each sample site showing the variation between sites in 2011& 2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 80
Figure4-6: Mean and standard error (S.E.) of Fe concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 81
Figure4-7: Mean and standard error (S.E.) of Mn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 81
Figure4-8: Mean and standard error (S.E.) of Mo concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 82
Figure4-9: Mean and standard error (S.E.) of Ni concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 82
Figure4-10: Mean and standard error (S.E.) of Pb concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 83
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Figure4-11: Mean and standard error (S.E.) of V concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 83
Figure4-12: Mean and standard error (S.E.) of Zn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 84
Figure4-13: Mean and standard error (S.E.) of Hg concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 84
Figure4-14:Mean and standard error (S.E.) of As concentrations at each sample site showing the variation between sites in 2011 &2012.The number of samples in site A is 15, and the number of samples on other sites is 5...... 85
Figure4-15: Mean and standard error (S.E.) of Sn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5...... 85
Figure4-16: The mean concentration and standard error (SE) of Al, Fe, Ni, Mn, Cr and Cu at the SIP in 2011 compared to 2012 ...... 88
Figure 4-17: The mean concentration and standard error (SE) of Zn, V, As, Pb and Co at the
SIP in 2011 compared to 2012 ...... 88
Figure 4-18: The mean concentration and standard error (SE) of As, Sn, Hg, Mo, and Cd at the SIP in 2011 compared to 2012 ...... 89
Figure4-19:Mean sediment concentrations in 2011of Al, Fe, Ni, Mn, Cr, Cu, and Zn in descending order of concentration at the port compared to the means at the sites to the east and west of the Port. Error bars are for the Standard Error to the mean with n=15 ...... 96
Figure 4-20: Mean surface sediment concentrations in 2011 of V, Co, Pb and As in descending order of concentration at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15...... 96
xiv
Figure 4-21: Mean surface sediment concentrations in 2011 of Hg, Sn, Mo and Cd in descending order of concentrations at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15...... 97
Figure4-22: Mean sediment concentrations in 2012of Al, Fe, Ni, Mn, Cr, Cu and Zn in descending order of concentration at the port compared to the means at the sites to the east and west of the Port. Error bars are for the Standard Error to the mean with n=15 ...... 99
Figure 4-23:Mean surface sediment concentrations in 2012 of V, Co, Pb and As in descending order of concentration at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15...... 100
Figure 4-24: Mean surface sediment concentrations in 2012 of Hg, Sn, Mo and Cd in descending order of concentrations at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15...... 100
Figure4-25: Mean concentration and standard error (S.E.) of F- concentrations at each sample site showing the variation between sites. The number of samples atsite A is 15, and the number of samples on other sites is 5 ...... 101
Figure4-26: Mean concentration and standard error (S.E.) of Cl- concentrations at each sample site showing the variation between sites. The number of samples at site A is 15, and the number of samples on other sites is 5 ...... 102
Figure4-27: Mean concentration and standard error (S.E.) of Br - concentrations at each sample site showing the variation between sites. The number of samples at site A is 15, and the number of samples on other sites is 5 ...... 102
2- Figure4-28: Mean concentration and standard error (S.E.) of SO4 concentrations at each sample site showing the variation between sites. The number of samples in A site is 15, and the number of samples on other sites is 5 ...... 103
Figure 4-29: The layout of the SIP showing the co-location of one industrial company in
2005. (Source: SIPC) ...... 160
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Figure 4-30: The layout of the SIP showing the co-location of different industrial production facilities till 2013. (Source: SIPC) ...... 161
Figure5-1: The mean concentrations of Cd that exceeded ISQG in sites...... 168
Figure5-2: The mean concentrations of Cr that exceeded ISQG in sites...... 169
Figure5-3: The mean concentrations of Cu that exceeded ISQG in sites...... 170
Figure5-4: The mean concentrations of Ni that exceeded ISQG in sites...... 171
Figure5-5: The mean concentrations of Pb that exceeded ISQG in sites...... 172
Figure5-6: The mean concentrations of Znthat exceeded ISQG in sites ...... 173
Figure5-7: The mean concentrations of Hg that exceeded ISQG in sites ...... 174
Figure5-8: The mean concentrations of Asthat exceeded ISQG in sites ...... 175
Figure5-9: The comparison of mean concentrations of Mo with ISQG in sites ...... 176
Figure5-10: Iron ore store at SIP (source Company 1) ...... 177
Figure5-11: Work accident and chemicals escape at SIP (source Company 2)...... 178
Figure 5-12: Waste material stores from SIP Companies outside to the West (source: liwa
Resident group)...... 178
Figure5-13: Stock of petrochemicals waste outside SIP to the West (source: LiwaResident group)...... 179
Figure5-14: Stock of petrochemicals waste outside SIP to the West (source: Liwa Resident group)...... 179
Figure5-15: Stock of different chemicals waste outside SIP to the West (source: Liwa
Resident group)...... 180
Figure5-16: Waste disposed of in an open area outside SIP to the West (source: Liwa
Resident group)...... 180
Figure5-17: Chemical waste disposed of outside SIP to the West (source: Liwa Resident group)...... 181
Figure5-18: Chemical Waste which has been absorbed (source: Liwa Resident group)...... 181
Figure5-19: Polluted areas due to chemicals waste (source: Liwa Resident group)...... 182
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Figure5-20: Waste from a water treatment plant outside SIP to the West (source: Liwa
Resident group)...... 182
Figure5-21: Outfall discharge from companies at SIP to the sea (source: company C3) ...... 192
Figure5-22: Productionat SIP (source: company C3)...... 192
Figure5-23: Wastewater Lake from the Mining process (Copper Mining) ...... 197
Figure5-24: The transfer of iron ore direct by conveyor belts to the yard area (Sources:
Company 3)...... 199
Figure5-25: Theyard storage area for iron ore at SIP (Sources: Company 3)...... 200
Figure5-26: Iron ore distributed from SIP to surrounding areas (Source: liwa Society group)
...... 201
Figure5-27: Shipping of Iron at SIP (Source:Company 1) ...... 201
Figure5-28: Air emissions from SIP from different companies to the surrounding area
(Source: Liwa Resident group)...... 210
Figure5-29: Catalysts transferred to the human environment around SIP (Source: liwa Society group)...... 211
Figure5-30: Catalysts transferred to the car around SIP (Source: liwa Society group)...... 211
Figure5-31: Catalysts transferred to homes around SIP (Source: Liwa Resident group)...... 212
Figure5-32: Accident in Petrochemical company at SIP (Source: Company 2)...... 212
Figure5-33: Leak of Chemicals at SIP (Source: Company 2)...... 213
Figure5-34: Chemicals escape at SIP (Source: Company 2)...... 213
Figure5-35: Petrochemical waste at SIP (Source: liwa Resident group)...... 214
Figure5-36: Effected land due to petrochemical waste at SIP (Source: liwa Resident group).
...... 214
Figure5-37: Stock of different chemicals outside SIP, to the West (Source: liwa Resident group)...... 215
Figure5-38: Rain and wadi discharge to the sea (Source: liwa Society group)...... 217
Figure5-39: Vessel calls development from 2007 to 2013 at SIP (Source: SIPC)...... 220
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Figure 5-40: Construction material dumped on the beach at Carowan village, Sohar (Source:
Chiffings, (2012) ...... 221
Figure 5-41: Two beach dumping sites use in Sohar (Source: Chiffings, (2012)...... 222
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List of Tables
Table 2-1: Grain Size classifications of Sediments ...... 19
Table 3-1: The mean concentrations of selected heavy metals (ppm) Cd, Co, Cr, Cu, Mo, Pb,
V and Zn in SIP, Harmul and Majis ...... 61
Table 3-2: Sites location, populations and sample numbers ...... 65
Table 4-1:Minimum and Maximum value, mean value of heavy metals (ppm), and standard errors within the SIP 2011& 2012 with total sample size of 15...... 87
Table 4-2:Minimum and Maximum value, mean value of heavy metals (ppm) , and standard errors at the West of the port 2011& 2012 with sample size of 15...... 91
Table 4-3: Minimum and Maximum value, mean value of heavy metals (ppm), and standard errors at the East of the port, 2011& 2012 with sample size of 15...... 94
Table 4-4: Spearman's rhocorrelations coefficient between mean concentrations of heavy metals at site A...... 107
Table 4-5: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site B...... 108
Table 4-6: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site C...... 109
Table 4-7: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site D...... 110
Table 4-8: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site E...... 111
Table 4-9: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site F...... 112
Table 4-10: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site G...... 113
Table 4-11: Spearman's rhocorrelationscoefficient of Cr, Mo, Ni, Pb, Hg and Sn in site A in both 2011 & 2012 ...... 114
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Table 4-12: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site B in both 2011 & 2012 ...... 115
Table 4-13: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site C in both 2011 & 2012 ...... 116
Table 4-14: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site D in both 2011 & 2012 ...... 117
Table 4-15: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site E in both 2011 & 2012 ...... 118
Table 4-16: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site F in both 2011 & 2012 ...... 119
Table 4-17: Spearman's rhocorrelations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site G in both 2011 & 2012 ...... 120
Table 4-18: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site A...... 124
Table 4-19: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site B...... 125
Table 4-20: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site C...... 126
Table 4-21: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site D...... 127
Table 4-22: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site E...... 128
Table 4-23: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site F...... 129
Table 4-24: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site G...... 130
Table 4-25: The P values for the One Way ANOVA analysis for Al in sitesA-G ...... 131
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Table 4-26: The P values for the One Way ANOVA analysis for Cd in sites (A-G) ...... 132
Table 4-27: The P values for the One Way ANOVA analysis for Co in sites (A-G) ...... 132
Table 4-28: The P values for the One Way ANOVA analysis for Cr in sites (A-G) ...... 133
Table 4-29: The P values determined by ANOVA for Cu in sites A-G ...... 133
Table 4-30: The P values for the One Way ANOVA analysis for Fe in sites (A-G) ...... 134
Table 4-31: The P values for the One Way ANOVA analysis for Mn in sites (A-G) ...... 134
Table 4-32: The P values for the One Way ANOVA analysis for Mo in sites (A-G) ...... 135
Table 4-33: The P values for the One Way ANOVA analysis for Ni in sites (A-G) ...... 135
Table 4-34: The P values for the One Way ANOVA analysis for Pb in sites (A-G) ...... 136
Table 4-35: The P values for the One Way ANOVA analysis for V in sites (A-G) ...... 136
Table 4-36: The P values for the One Way ANOVA analysis for Zn in sites (A-G) ...... 137
Table 4-37: The P values for the One Way ANOVA analysis for Hg in sites (A-G) ...... 137
Table 4-38: The P values for the One Way ANOVA analysis for As in sites (A-G) ...... 138
Table 4-39: The P values for the One Way ANOVA analysis for Sn in sites (A-G) ...... 138
Table 4-40: The P values for the Two Way ANOVA analysis for Cr by year ...... 139
Table 4-41: The P values for the Two Way ANOVA analysis for Mo by year ...... 140
Table 4-42: The P values for the Two Way ANOVA analysis for Ni by year ...... 141
Table 4-43: The P values for the Two Way ANOVA analysis for Pb by year ...... 142
Table 4-44:The P values for the Two Way ANOVA analysis for Hg by year ...... 143
Table 4-45: The P values for the Two Way ANOVA analysis for Sn by year ...... 144
Table 4-46: Sites which have highest mean concentrations of Cr, Mo, Ni, Pb, Hg and Sn by year ...... 145
Table 4-47: Duncun‘scomparative test of sites which have highest mean concentrations of Al,
Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, V, Zn, Hg, As and Sn...... 146
Table 4-48: Comparison of the mean concentrations of the selected heavy metals (Cd, Cr, Cu,
Ni, Pb, Zn, Hg, Mo and As) in 2011 in the surface sediments at the site study with the
Sediment Quality Guidelines in international organizations such as Environment Canada,
xxi
Australian and New Zealand Environment Conservation Council ANZECC, US
Environmental Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland...... 150
Table 4-49: Percentage excess of Sediment Quality Guidelines in Environment Canada (EC) and Australian and New Zealand Environment Conservation Council (ANZECC) in 2011 for
Cr, Cu, Ni, Hg, and As...... 151
Table 4-50: Percentage excess of Sediment Quality Guidelines US Environmental Protection
Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM)
Netherland in 2011 for Cd, Cr, Cu, Ni, Pb, Zn, Hg, and As...... 152
Table 4-51: Comparison of the mean concentrations of the selected heavy metals (Cd, Cr, Cu,
Ni, Pb, Zn, Hg, Mo and As) in 2012 in the surface sediments at the sites studied with the
Sediment Quality Guidelines in international organizations such as Environment Canada,
Australian and New Zealand Environment Conservation Council ANZECC, Environmental
Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment
(VROM) Netherland...... 155
Table 4-52: Percentage excess of Sediment Quality Guidelines in Environment Canada (EC) and Australian and New Zealand Environment Conservation Council (ANZECC) in 2012 for
Cr, Cu, Ni, Hg, and As...... 156
Table 4-53: Percentage excess of Sediment Quality Guidelines US Environmental Protection
Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM)
Netherland in 2012 for Cd, Cr, Cu, Ni, Pb, Zn, Hg, and As...... 157
Table 4-54: Comparison of the concentrations of the heavy metals (Cd, Cr, Cu, Mn, Ni, Pb,
V, Zn, Hg and As) between the current study and the study conducted by Al-Shuely et al.,
(2009) in Harmul and Majis...... 158
Table 5-1: List of chemicals used at SIP by different companies...... 189
xxii
List of Abbreviations
(FIDIC) International Federation of (Al) - Aluminum Consulting Engineers (UNEP) - United Nations Environment (ANOVA) Analysis of variance Program (ANZECC) - Australian and New Zealand (ICP-OES) - Inductively Coupled Plasma Environment and Conservation Council Optical Emission Spectrometer
(ARMCANZ) - Agriculture and Resource (IMO) - International Maritime Management Council of Australia and Organization New Zealand (ISQG-High) - Interim Sediment Quality (As) - Arsenic Guidelines - High: Probable effects concentrations below which biological (ASTM) - American Society for Testing effects would possibly occur. and Materials Concentrations above these values (Br-) - Bromide represent a probable-effects range within which effects would be expected to (Cd) - Cadmium frequently occur.
- (Cl ) - Chloride (ISQG-Low) - Interim Sediment Quality Guidelines - Low: Probable effects (Co) - Cobalt concentrations below which biological (Cr) - Chromium effects would rarely occur. (ISQGs) - International Sediment Quality (Cu) - Copper Guidelines standards (DNA) - Deoxyribonucleic acid (JICA) - Japan International Cooperation Agency (EC) - Environment Canada (K) – Potassium (EF) - Enrichment Factor (Kms)- Kilometers (EIA) - Environmental Impact Assessment (Li) - Lithium (ERA) - Environmental Risk Assessment (MECA) - Ministry Of Environment and (F-) - Fluoride Climate Affairs (Fe) - Iron (MISC) -Majis Industrial Services Company (GTZ)- Deutsche Gesellschaft für Technische Zusammenarbeit (Mn) - Manganese (Hg) - Mercury (Mo) - Molybdenum (IC) - Ion Chromatography (Ni) -Nickel (ICC)- International Chamber of (Pb) -Lead Commerce
xxiii
(PEL) - Probable effects level (TEL) - Threshold effect level
(UNEP) - United Nations Environment (SEU) – Sohar Environmental Unit, Program Ministry Of Environment and Climate Affairs Unit at Sohar Industrial Port (USEPA) – United States Environmental Protection Agency (SIP) - Sohar Industrial Port (V) – Vanadium (Sn) - Ten
2- (VROM) Ministry of Housing, Spatial (SO4 ) - Sulphate Planning and the Environment, (SPSS) - Statistical Package for the Social Netherland. Sciences (WHO) - World Health Organization (SQP) - Sultan Qaboos Port (Zn) – Zink (Sr) - Strontium
xxiv
Chapter One Introduction
1
Chapter 1: Introduction 1.1 Introduction
Nowadays, heavy metal pollution is becoming a global concern with worries expressed in many different countries due to the toxicity, extensive sources, non- biodegradable properties and accumulative behaviors of heavy metals (Hui-na et al.,
2012; Dou et al., 2013). Heavy metals in marine and coastal sediments represent a potential source of contaminants to the overlying water and hence can influence water quality. This is the result of waste disposal and waste water discharge into the sea, which causes serious impacts on the marine environment (Dou et al., 2013). Heavy metals in the environment have two main sources: lithogenic and anthropogenic.
Lithogenic include natural processes, for example the weathering of rocks and volcanic activities. Anthropogenic sources are caused by human activities from mining, industry, agriculture, and construction of urban developments, all of which transfer contaminants to the marine environment (Sany et al., 2011).
Harbors and port terminals are the business gates to the international economy, in which transport and storage of traded goods are controlled. However, their activities are potentially dangerous to marine and coastal environments, however, due to their harmful impacts spreading within these environments. Other anthropogenic heavy metals and contaminants in sea water and sediments lead to additional complex risky compounds, which could be toxic for several sea creatures and create pollution in the sea environment (Buruaem et al., 2012)
Metals occur naturally in the environment, including in seawater (Riley and Chester,
1971, Esslemont G, 2000; Pérez-López et al., 2003) and in marine sediments
(De Lucaa et al; 2004; Gang Xu et al., 2014; Sany et al., 2014) with concentrations that vary from place to place as a result of geochemical and anthropogenic sources
(McConchie et al., 1988; Sany et al., 2011). This is a relatively common situation
2 with consequent natural bio-accumulation in a range of species. This can lead to making key human food species unsuitable for consumption within specific regions as a result of a natural set of processes. In particular, the natural occurrence of heavy metals raises the issue of using generically available regulatory standards for environmental occurrence, particularly if these are expressed as an absolute value rather than as an alert level in the context of a risk assessment framework (Simpson et al., 2005). Heavy metals are naturally found in rocks and soils and enter the environment as a result of erosion and weathering through runoff (Kilemade et al.,
2004; Gang et al., 2014). However, as early as 1976, De Groot and co-workers made the observation that no direct evidence existed as to the heavy metal contents of sediments in the pre-industrial period. Anthropogenic release to the marine environments is through wastewater discharge, and run-off (Kilemade et al., 2004).
In developing countries there is a risk that environmental regulations are applied that are formulated in developed countries, in many cases with little consideration given to the environmental context to which they are about to be applied. An example of this is
European regulations developed for air pollution index being applied in arid, tropical environments, such as Oman, where different weather and climatic conditions apply regionally (Preston et al., 2013).
1.2 Research problem
In the Sultanate of Oman industrialization outside the capital city of Muscat has occurred only over the last two decades or less, and only at a small number of sites.
The development of several industrial areas and associated ports along the Omani coastline as a major diversification of the economy provides the opportunity to reconsider the relationship between natural and anthropomorphic sources of heavy
3 metals in the marine environment and the levels of environmental and human health risk presented. At Sohar Industrial Port (SIP), major industrial operations and processing occur, which are supposed to have efficient environmental management systems and risk reduction mechanisms. However, from general observation it was realized that this was not the case; no background data and no proper studies on pollution and risk assessments were conducted at SIP relating to heavy metals.
Therefore, this study is essential to evaluate the SIP and its surrounding areas in terms of heavy metal concentrations. It is expected that it will serve as a starting point for offering background information on pollution for future comparisons and assessments. Attempts will be made to focus on risk assessment to the public and the environment, and fingerprinting will be used for the study of heavy metals to determine potential sources.
1.3 Rationale and Contribution of the Research
Within the past few years, the identification of contaminants has become a significant ecological subject in the entire Arabian Gulf Area (Al-Rawahi, 2012). A number of studies carried out in the Arabian Sea showed the ubiquity of heavy metal contaminants in diverse sea environments. Increasing concentrations of contaminants in seawater, sediments and marine organisms cause to deteriorating ecological indicators of likely toxicological impacts for sea organisms and increasing risk for human's health (Naser, 2013). For the Sohar region, marine products (fish and shellfish) are essential diet items for local communities and in some communities they are significant, commercially exported items. Consequently, observing contaminants must be established to protect the health of humans and to save the environment.
Regarding sea pollution, studies carried out thus far in the Sea of Oman and the
Arabian Sea are characterized by notable shortcomings and lack of recommendations. 4
This project intends to evaluate the heavy metal concentrations in marine sediment and compare them with some international guidelines. The study will open the door for future studies, including monitoring and examination of the accumulation of pollutants, using heavy metals as a measuring stick in assessing the health status of the marine environment relative to the level of pollution. The accumulation of information from this study will similarly be valuable for future toxicological investigations and ensure suitable examination of the impacts of environmental contamination on sea species over the passage of time, to assist in biodiversity protection and sustainable progress.
In addition there has been a major increase in shipping to transport solid and liquid cargoes at SIP, for which numerous new quays and oil terminals have been built and for which many more are under consideration. Scientists are required to provide solutions for decision makers by assessing the ecological impacts of coastal developments and suggesting appropriate environmental management plans to minimize probable ecological impacts. One such program is gathering data on local impacts and combining these studies for a broader understanding of regional impacts.
Risk assessments and pollution fingerprints are essential in understanding environmental quality. This study therefore aims to provide initial pollution data that can be used in a broader understanding of regional environments and thus contribute to the environmental sustainability of the regional marine ecosystem.
5
1.4 Definition of the research topic
1.4.1 Aim
The aim of the research is to investigate the heavy metal composition of sediments within and near Sohar Industrial Port (SIP) and the nearby coastal regions and recommend the necessary measures to improve the environmental condition within the study area.
This includes, in particular, Sohar Industrial Port (SIP) (site A), three sites extended along the coast to the northwest (B,C and D) and three extended along the coast to the southeast (E,F and G).
The research is intended to investigate the mean concentrations of the metal (Al), heavy metals (Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, V, Zn and Hg), and metalloids (As and Sn) for two years in order to evaluate pollution potential in the study area and to attempt a fingerprinting method to evaluate a theoretical risk assessment based upon the data that have been collected. The mean concentration of the anions (F, Br, Cl
2- and SO4 ) in the surface sediment will be analyzed for one year in order to see the relationship between heavy metals and anions. For simplicity the term heavy metal will be used in this research to cover all of the metals and metalloids studied in the research.
6
1.4.2 The objective of the study:
The objectives of the research are:
i. To design a monitoring programme for pollution evaluation at SIP and the
nearby coastal regions.
ii. To analyze cations (two years) and anions (one year) in SIP and the nearby
coastal regions in order to determine the differences between mean
concentrations of cations and anions in different areas. iii. To evaluate the public and environmental requirement of Sohar Industrial Port
and the surrounding area. iv. To review a theoretical fingerprinting technique to establish sources of
pollution in the SIP region using a combination of field data collection,
laboratory analyses of samples and statistical modeling techniques.
1.5 Limitations
This research is investigating the sources of heavy metals at SIP and the surrounding area. The study has encountered the following limitations:
i. Sample collection at SIP proved to be difficult because the port has very strict
entrance permits, as well as several inner gates to certain establishments which
also require special permits.
ii. Lack of a database and background information on the study area. iii. Insufficient research funding that in some instances caused drawbacks in
sample analysis. iv. Study at SIP required permits from more than one authority –a long process
involving inefficient systems which caused delays and greatly reduced the
quality of the study.
7
v. Communication with different establishments at SIP for obtaining data was
cumbersome and in some instances it was not possible to obtain data because
of the privacy of the information and sensitivity of data.
1.6 Thesis Layout
This thesis consists of six chapters. Chapter One includes an introduction and discusses the research problem, the original and regional contexts, definition of the research topic (aim, objectives), limitations and thesis layout. Chapter Two is on literature review which includes an introduction and further sections entitled pollution and sources, marine sediment, chemical composition of marine environment, impact of heavy metals, risk assessment methods and policies assessing environmental pollution, fingerprinting technique and conclusions. Chapter Three sets out the methodology of the research and covers an introduction, site description, pilot study, monitoring area, field sampling, chemical preparation for heavy metals, sample analysis for anions – Ion Chromatography (IC),and statistical analysis. Chapter Four is about result and discussions divided into four sections: contamination levels of sediments at Sohar Industrial Port (SIP) and surrounding areas in one section; a statistical analysis of monitored data using SPSS analysis, Spearman‘s rho correlations and ANOVA in the middle section; and discussion of the results from this study in relation to International Sediment Quality Guidelines standards (ISQGs) in a third section and conclusions in final section. Chapter Five is divided into four sections:section one is about evaluating the risk assessment from pollutants at SIP and its surrounding areas; and section two is about environmental and health risk perspective, section three is about the sources of pollution in the SIP region, using a combination of field data and inventory data and sections four is conclusions. Finally,
Chapter Six contains a conclusion of the research and provides a set of recommendations.
8
Chapter Two Literature Review
9
2 Chapter 2: Literature Review 2.1 Introduction
This chapter aims to discuss concerns about heavy metals in the marine environment.
It is divided into the following sections:
(i) Introduction (Section 2.1)
(ii) Pollution and Sources (Section 2.2)
(iii) Marine Sediment (Section 2.3)
(iv) Chemical Composition of Marine Environment (Section 2.4)
(v) Impact of Heavy Metals (Section 2.5)
(vi) Risk Assessment Methods and Policies Assessing Environmental Pollution
(Section 2.6)
(vii) Fingerprinting Technique (Section 2.7) and
(viii) Conclusion (2.8)
10
2.2 Pollution and Sources
Environmental pollution is a widespread concern globally. Pollution is a serious problem that affects most and perhaps all environments in the world. It is a condition in which a harmful material comes in contact with life-sustaining resources such as water, soil or air. Pollution has been defined as ‗the introduction by man, directly or indirectly, of substances or energy into the environment resulting in deleterious effects of such a nature as to endanger human health, harm living resources or interfere with amenities or other legitimate use of the environment.‘(Reeve,
2002).There is different types of pollution such as air pollution, soil pollution, water pollution, radioactive pollution and industrial pollution (Reeve, 2002).
Pollution in the ocean is considered a major problem worldwide (de Mora et al.,
2004). It directly or indirectly affects ocean organisms and human health. Oil spills, toxic wastes, and dumping of harmful materials are all major sources of pollution in the ocean. Scheer, 2005 and Kojadinovic et al., 2007 in their report concluded that the oceans hold contamination and litter from the poles to the tropics, from beaches to the deep sea. Some reports have estimated that runoff from land is the largest source of ocean pollution followed by atmospheric pollution, marine transportation, dumping of waste and offshore oil production.
The coastal waters where most pollution occurs contain some of our most productive ecosystems. Because of the availability of rich nutrients, coral reefs, mangrove ecosystems, estuaries and coastal lagoons are the nurseries of vast numbers of young organisms. These young organisms are the most sensitive to pollution (Jerez et al.,
2010). The economic consequences are also significant. About 99% of the global catch of marine fish comes from within less than 300 kms of shore, and much of the decline in the worldwide fishing industry is attributed to loss of coastal habitat (Al-
Awadhi, 1999). The coastal strip, where land meets the sea, is home to some of the 11 richest communities and although this coastal strip is narrow; its influence is enhanced by the wealth of organisms present. In the littoral zone (area covered by the periodical rise and fall of the tides), the sea, the land and the air all play important roles in establishing the complex environmental conditions to which communities must adapt. The complex interplay of these environmental conditions and variety of shore life itself create an abundance of niches for coastal organisms, all interrelated: crabs, snails, barnacles, mussels, chitins, limpets, brown/red/green algae, seaweeds, various coastal plant species that support small mammals and various bird species.
Most coastal communities, however, are under threats from various anthropogenic activities, including development, industries, tourism and pollution (Al-Rawahy et al.,
2007).
Human activities along the coastlines and far inland affect the health of our ocean.
Velusamy et al. (2014) reported that pollution introduced to the environment could be from different sources such as industrial effluent discharge, agricultural drainage, accidental chemical waste spills, gasoline from fishing boats and sewage discharge.
Non-point source pollution is one of the major sources of ocean pollution, which occurs as a result of runoff (Kojadinovic et al., 2007). It includes different sources such as farms, livestock ranches, and timber harvest areas (larger sources) and trucks, boats, septic tanks, and cars as small sources, (Botkin& Keller, 2005). However, point source pollution comes from a single source like oil discharges from factories: chemical spills are also common. Sources of pollution in harbors from the discharge of petroleum derived hydrocarbons include, for example, discharges from engines, absorbent tanks operational, releases from tankers and accidental spills. Moreover, antifouling paints from ship hulls and other immersed structures can cause pollution in harbors (Martínez-Llado et al., 2007). These contaminants tend to be maintained by the environment and will be highly toxic to biota (Kilemade et al., 2004).
12
Industrial discharges have become serious concerns in different countries. There are various industrial discharges such as sewage treatment, water supply, water quality, air and solid waste disposal. Certain environmental issues such as acid precipitation, ozone depletion, global climate change and deposition of persistent chemicals are common side-effects of large industrial estates. Therefore, in industrialized zones, contaminating soil, air and water will adversely affect the environment and health
(ICC et al., 1997). Figure 2.1 shows the different environmental impacts of industrial emission.
Contaminated Soil and lost future land use
Disposal of Spills Soil Wastes
Landscape Local Nuisances such Disturbance as Noise, Lighting and Transport INDUSTRI
Ozone Depleting and Exposure to Greenhouse Gases ToxicChemicals
ESTATES Habitat Risks from Degradation Waste
Air Pollution Marine Pollution Freshwater Pollution
Figure 2-1: Possible environmental impact of industrial emissions (ICC et al., 1997)
13
Oil pollution of the ocean affects the creatures of the oceans, which in turn affects the environment. For example oil pollution slows down the growth and hampers the life cycle of coral reefs (de Mora et al.; 2004).Oil could clog the gills of fish and block the sunlight from being absorbed by marine plants as well (Islam & Tanaka, 2004). Most oil pollution, however, does not come from maritime spills. According to an estimation by the International Maritime Organization (IMO, 2007), globally nearly half comes from land-based sources such as atmospheric pollution, cities, and industrial waste and runoff. Marine transportation provides another 48%, but less than one third of this is from oil spills as a result of accidents (Al-Awadh, 1999). Most of these oil spills come from routine ship operations (de Moral et al; 2004). Tankers often discharge oily bilge and ballast water at sea. Still a major oil spill can be significant, and one such incident has the potential to affect the above annual average greatly.
Another persistent pollution problem in our ocean is marine debris such as litter.
Marine debris injures and kills marine life, interferes with navigation safety, and poses a threat to human health. Pollution in our oceans and waterways comes from an extensive diversity of sea remains ranging from plastic bags and soda cans to abandoned fishing equipment and vessels (Clark, 2001). Most of the waste and remains that covers seashores originates from sewers and drains, and from coastline and leisure activities. Another main problem is discarded or abandoned fishing equipment as this waste can tangle, harm, and kill sea wildlife and destroy belongings.
These marine remains and litter can harm and kills sea-life, and may affect sea transport security.
14
The quantity of plastic in the seas might be as high as one hundred million metric tons. Marine life can be endangered via asphyxia and absorption. Several animals living on or in the sea eat debris by mistake, as it frequently appears like their natural prey. Plastics accrue due to the fact that they do not biodegrade like numerous other materials do. They will photo damage under exposure to the sun, however they do so appropriately only within dry environments, and water prevents this procedure. In sea environments, photo damaged plastic fragments into ever smaller parts whereas the polymers remain, even down to the particle level (Ivar do Sul & Costa, 2014). Once floating plastic atoms photo damage down to zooplankton sizes, jellyfish try to eat them, and then the plastic arrives in the sea nutrition chain. Several of these long- lasting parts end up in the stomachs of sea wildlife.
Toxic extracts applied in the production of plastic tools can leak out into their environments once exposed to water. Floating hydrophobic contaminants accumulate and enlarge on the surface of plastic remains, therefore leading to the plastic being far more lethal in the sea than it would be on land. Moreover, hydrophobic pollutants are recognized to bio-accumulate in oily tissues, bio-expanding up the nutrition chain and creating pressure on top predators. Certain plastic extracts are recognized as disturbing the endocrine system once consumed; others can overpower the immune system or decline generative powers (Ivar do Sul & Costa, 2014). Furthermore, floating remains can engrosses certain organic contaminants from sea-water, containing polychlorinated biphenyl (PCBs), dichlorodiphenyltrichloroethane (DDT) and polycyclic aromatic hydrocarbons (PAHs) (Freije, 2014).
Contamination of the coastal ecosystems in the Indian Ocean receives continued attention (Siddeek et al., 1999; Al-Awadhi, 1999; de Mora et al., 2004; Al-Rawahy et al., 2007; Kojadinovic et al., 2007). The Northwest Indian Ocean, including the Sea of
Oman and the Arabian Sea, is considered one of the most polluted seas in the world,
15 though pollution levels in this area are poorly measured at this time (Al-Rawahy et al.,
2017). Considering about half of the world oil production comes from the Middle East and passes through the Arabian Sea, its vulnerability to pollution is more than that of any other ocean (Al-Awadhi, 1999). There are also key industrial developments in the
Gulf and Western Arabian Sea that act as localized sources of pollution (de Mora et al., 2004). Wastewater discharge from various anthropogenic activities, such as mining, industrial processes, military waste discharge, shipment, treated and untreated sewage discharge and distillation plants are sources of heavy metal contamination
(Adamo et al., 2005; Al-Bahry et al., 2012; Hou et al., 2013). In this respect, Adamo et al (2005) studied the extent of heavy metal pollution in the marine sediments within the port of Nepal. This was done by studying twenty surface sediments. The results demonstrated that heavy metal pollution is concentrated in the area of the port and that this was the result of shipbuilding activities as well as the impact of petroleum refineries. The study showed that the sources of Cd, Zn, Cr and Cu in the port of
Naples are the result of anthropogenic sources.
The Northwest Indian Ocean, including the Sea of Oman and the Arabian Sea, is an area of very busy maritime traffic connecting the Indian Ocean to the Arabian Gulf, the Gulf of Aden and the Red Sea, making it one of the highest polluted seas in the world, and in terms of volume it is listed 4th top of the 10 oil spills in the world.
Considering approximately 49% of world oil production comes from the Middle East and passes through the Arabian Sea, its vulnerability to pollution is many times more than any other ocean (Al-Awadhi, 1999). There are also key industrial developments in the Gulf and Western Arabian Sea that act as localized sources of pollution (Al-
Rawahy et al., 2007). These kinds of development in the Arabian Gulf have been comprehensive and include economic, social and rapid construction activities which have caused intensive dredging and reclamation on the coastal and marine environments in the Arabian Gulf (Naser, 2013). Furthermore, the expansion of 16 tourism in the region has resulted in the construction of manmade beaches. It is feasible that these activities could result in further pollution arising from the movement of contaminated sediments.
These anthropogenic heavy metal pollutions of aquatic environments have been recognized as serious environmental concerns. Recent reports indicate that contamination of coastal waters may have played a role in the decline of many marine organisms such as green turtles (Aguirre et al., 1994; Godley et al., 1999; Miao et al.,
2001; Al-Rawahy et al., 2007; Hou et al., 2013; Naser, 2013).
Heavy metal contamination of marine environment resulting from industrial areas and harbors has been given great attention in many countries. There are several studies from all over the world dealing with this issue. Among these are, for example, Chen et al. (2007) who investigated the distribution, enrichment and accumulation of heavy metals (e.g. Hg, Pb, Cd, Cr, Cu, Zn and Al) in the sediments of Kaohsiung Harbor,
Taiwan. They reported that all investigated heavy metals, except Cr, had high enhancement elements and geo-accumulation indexes in the estuaries. They also concluded that metal concentrations are closely associated to the sediments of physical-chemical properties. This strongly suggests that the influence of anthropogenic sources is responsible for the high concentration of the above mentioned heavy metals. In addition, Huerta-Diaz et al (2014) reported that the sediments of Santa Rosalia harbor in Mexico are contaminated with Mn, Co, Pb, and
Zn, and harshly contaminated with Cu and Cd. They showed that the high concentration of contaminated sediment results from slugs, mineral ore and mine wastes. They also concluded that, due to the magnitude of trace metals, dredging sediments from the harbor will cause large quantities of trace metals in the open ocean, which will create a threat to marine organisms.
17
2.3 Marine Sediments:
Marine sediment is mainly solid particles that settle down at the bottom of sea water forming a layer on the surface that have can be silt, sand, gravel, chemical precipitates, and fossil fragments (Briggs et al., 1998).
Physical properties of sediments, such as density and grain size, are important in the formation of sediment and transport processes (ANZECC and ARMCANZ, 2000).
Sediments are mainly a heterogeneous mixture of particles ranging from a millimeter to a submicron in size. Table 1 shows a classification of particles on the basis of grain size (ANZECC and ARMCANZ, 2000). Marine sediments are in close interaction with sea water that fills spaces between particles and within the holes of sediment particles. The size of this water falling between gaps depends on the sediment's porosity and is greater within the grainier sand segment than with the finer clay/silt segment (ANZECC and ARMCANZ, 2000).
Moreover, the size of the sediment's particles is important to the depths that can be burrowed by organisms (ANZECC and ARMCANZ, 2000). This determines the organism accepting the chemical environment and the pores of the sediments (Traven,
2013). Silty sand is considered to be a more suitable standard for numerous benthic organisms in comparison to compressible clay and thus higher contamination levels in areas of salty sand will have a bigger influence (ANZECC and ARMCANZ, 2000).
18
Table 2-1: Grain Size classifications of Sediments
Grain Scale Classification
<0.06 µm Fine Clay
0.06 – 0.2; 0.2-0.63 µm Medium Clay
0.63-2 µm Coarse Clay
2-6.3 µm Fine Silt
6.3-20 µm Medium Silt
20-63 µm Coarse Silt
>63 µm Sand
>2 mm Coarse Material, Rocks, Detritus
(ANZECC and ARMCANZ, 2000)
The chemistry of sediments and their associated contaminants is mainly influenced by physical processes in sediments. Chemical sedimentary rocks are formed from precipitation of aqueous solutions through chemical or biochemical processes. They are grouped into carbonates, evaporate and chart (ANZECC and ARMCANZ, 2000).
The chemical procedures of sedimentation are measured by redox conditions (melted oxygen, sulfides), pH, and the geo-chemistry of sediment particles (ANZECC and
ARMCANZ, 2000).
Metals are not party to the same degradation processes that occur to many organic molecules: they may exist in both complex and labile forms of sediments. In many cases, the chemical form and physical and microbial degradation processes are important especially in considering the environmental threat to organics by metals
(Peterson & Batley 1993). 19
Chemical contaminants that are associated with sediment phases are more likely to be in thermodynamic equilibrium with the associated pore waters (Oakley et al. 1980).
This equilibrium will involve contaminants that are bound to adsorption sites on the sediment and adsorption occurs during sedimentation and re-suspension of particulates (ANZECC and ARMCANZ, 2000).
Sediments might represent a fundamental source of contaminants to the sea water and therefore can affect water quality. Sediment contaminants are released physically by their dissolution into the sediment pore waters. The release of these contaminants to the surrounding water will occur if the concentration of pore water exceeds that of the surrounding water (ANZECC and ARMCANZ, 2000).
Marine sediments are deposit materials that have mineral particulates, inorganic components and organic matter in different phases of decomposition (De Lucaaet al;
2004). Contaminated sediments have been defined by the U.S. USEPA as "soils, sand and organic matter or minerals that accumulate on the bottom of a water body and contain toxic and hazardous material which may adversely affect human health or the environment" (USEPA, 1998). Moreover, they are sensitive indicators between natural and anthropogenic variables (De Lucaa et al; 2004). Marine sediment is considered as the main deposit and source of the heavy metals in coastal and marine environments and is therefore a suitable indicator of pollution because it can work as a hunter agent for heavy metals and hydrocarbons and an adsorptive sink in aquatic environments for many anthropogenic contaminants. Sediment chemistry controls the transportation and storage of these hazardous metals (Kilemade et al., 2004; Idris et al., 2007; Liu et al., 2010; Qiao et al., 2013).
In coastal environments, sediments are important carriers of pollutants (Morelli et al.,
2012). With different industrial plants in the SIP area, heavy metal use in industrial processes and their subsequent discharge into the wastewater becomes unavoidable. 20
Additional anthropogenic heavy metals and other pollutants in the sea water and sediments makes more complex compounds dangerous, which may be toxic for various marine life and cause threats to the coastal ecosystem.
Considering the main deposition site for heavy metals in coastal and marine environments, numerous studies have been undertaken to assess the heavy metal contamination of harbor sediments as a result of human activities (Denton et al., 2005;
Guerra-Garcia and Garcia-Gomez, 2005; Sprovieri et al., 2007; Zonta et al., 2007;
Huerta-Diaz et al., 2008; Cukrov et al., 2011; Sany et al., 2013; Velusamy et al.,
2014). Metal concentrations in sediments are not only a suitable indicator of pollution
(De Lucaa et al., 2004; Denton et al., 2005; Guerra-Garcia and Garcia-Gomez, 2005;
Sprovieri et al., 2007; Zonta et al., 2007; Huerta-Diaz et al., 2008; Cukrov et al. 2011;
Sany et al., 2014) but the physical movement and chemical interactions within the sediments can also control the transportation and storage of these hazardous metals and therefore the degree of risk they represent to the environment and people consuming seafood (Kilemade et al., 2004; Idris et al., 2007; Liu et al., 2010; Hou et al., 2013; Naser, 2013). In this respect, Naser (2013) reviewed some studies concerning the levels of heavy metals in fish and mollusks and concluded that the levels are similar or lower in a number of mollusks species to other regions. But hotspots of heavy metals contamination were encountered in defined areas that resulted from oil pollution coming from refiners and other reclamation activities.
Additionally, he showed that some studies about heavy metals in fish tissues demonstrated that they exceeded the WHO levels. He therefore suggested that there must be controlling and monitoring of heavy metals in fish species in order to prevent health risks.
21
2.4 Chemical Compositions of Marine Environment:
In sediments, the key nutrient components of ecological concern are nitrogen and phosphorus that exist in organic and inorganic forms. Nitrate, nitrite and ammonium are considered to be inorganic forms of nitrogen. Organic nitrogen experiences microbial degradation and de-nitrification through ammonia, nitrite, and nitrate, the process bringing back elemental nitrogen as N2. In oxygen-restricted systems, these responses can stop at ammonia. Phosphorus occurs as phosphates, both monomeric and polymeric. Moreover, in sediments it is regularly bound with iron. Because phosphorus and nitrogen can be bound by bacteria, microscopic living creatures form an important part of the sediment structure (ANZECC and ARMCANZ, 2000).
Heavy metal pollution of the marine environment from waste discharges has been a significant concern in many countries for the last 50 years or so. The main sources of the heavy metals introduced to the environment from anthropogenic inputs are from industry wastewater discharges, sewage, atmospheric deposition, the combustion of fossil fuels, and agricultural activities (Birch et al., 1996; Linnik and Zubenko, 2000;
Lwanga et al., 2003; Chaparro et al., 2004; Jordanova et al., 2004; Spiteri et al., 2005;
Rijal et al., 2010; Sekabira et al., 2010; Zhang et al., 2011; Velusamy et al., 2014).
The USA Environmental Protection Agency (USEPA) in a report on Erosion,
Sediment and Runoff control for Roads and Highways in Urban Runoff (1995) concluded that the main sources of heavy metals in urban runoff are roadways and automobiles. They listed eight heavy metals that are found in high concentrations, namely lead, zinc, cadmium, copper, iron, nickel, manganese and chromium. In addition, mining waste is also a potential source of heavy metal contamination
(Förstner, 1995; Salomons, 1995; Hou et al., 2013).
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Activities leading to heavy metal pollution of marine and coastal environments have been occurring since the start of the process of urbanization and industrialization some 400 years ago in the Western part of the world, but it was only with the advent of modern analytical methods and the recognition of the impacts of bioaccumulation in sea foods that the problem was identified. A dramatic example of this was the discovery and consequent documentation of Hg poisoning in Minamata, Japan in the late 1950s (Fujiki 1980a, b; Tomiyasu et al., 2014). Many studies have now shown that anthropogenic sources are the mostly likely cause of increased heavy metal concentrations in and around urban and industrial regions of the world (Sakan et al.,
2011; Naser, 2013; Popadic et al., 2013). Despite this and the associated monitoring and management interventions that have prevailed the occurrence of high metal concentrations continues to be an issue because metals are toxic, non-biodegradable, and as a result persistent. They accumulate in biota with strong evidence of species damage. The bio-accumulation properties of these chemicals also mean that they remain a threat not only to the environment but also to the safe consumption of seafood (Singh et al., 2005; Idris et al., 2007). They are readily absorbed onto particulate material (Griffin, 2009) and as a consequence transported considerable distances from the original source. In effect, the ecological and human health risks of exposure to heavy metals can be expected to persist in the marine environment well beyond the duration of any discharge to the environment.
Heavy metal pollutions are becoming a significant concern because of their toxicity, and may be non-biodegradable, and persistent in organs. The extent of heavy metal pollution is likely to produce widespread effects on marine life and habitats. They can be dangerous to living organisms if present in the form of cations which have the capacity to bind with short carbon chains, but are not particularly toxic if present as the free elements. Some can be retained in tissues for years and show an age-related accumulation and strong bio-magnification in the food web because of their slow 23 elimination from the body (Kilemade et al., 2004; Popadic et al., 2013; Zahra et al.,
2014).
Heavy metals are known to cause deleterious effects on marine organisms (Talavera-
Saenzi et al., 2007). Excessive exposure to heavy metals has shown to cause various diseases (Ayres and Hellier, 1998; Al-Awadhi, 1999). The determination of heavy metals in marine environments is a critical part of bio-monitoring studies. Such studies include the recent published data on relative metal bioaccumulation comparisons in the Sea of Oman and western Arabian Sea (de More et al., 2004;
Abdul-Wahab and Yaghi., 2004; Fowler et al., 2007; Al- Shuely et al., 2009; Al-
Hatrushi. 2011; Baawain et al., 2011; Naser, 2013). In this respect, as was mentioned earlier, Naser (2013) in his review of some studies highlighted the impact of heavy metals on fish and mollusk species resulting from different human activities and which exceeded the WHO levels.
These anthropogenic heavy metal pollutions of aquatic environments have been recognized as serious environmental concerns (Tüzen, 2003; Zahra et al., 2014).
Heavy metals may accumulate to toxic levels and cause ecological and biological damage (Linde et al., 1998) and can have a negative effect at several levels of organization from a biochemical response to a change in population size (Dauwe et al., 2004). As a consequence, heavy metals are considered to be one of the most important forms of pollution of the aquatic environment because of their toxicity and accumulation in tissues of marine organisms (Emmam-Khansari et al., 2005). Recent reports indicated that heavy metal contamination of coastal waters may have played a role in the decline of various marine organisms in the world (Jerez et al., 2010).
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Marine sediments are formed from weathering processes with major transportation from terrestrial sources under high runoff from rivers, storms and floods. Various anthropogenic sources of marine heavy metal pollution are discharges from urban, industrial and mining activities (Al-Rawahy et al., 2007).
Lee et al (2008) studied metal contamination at the Youngil bay and the Hyungsan river estuary on the south-east Coast of Korea. In their study the modified geo- accumulation index was used to determine the pollution status, while for the major controlling factors for the distribution of metals in sediments they employed correlation matrix and R-mode factor analyses at 27 stations during winter and summer. Grain size and organic carbon content were major controlling factors for the distribution pattern of heavy metals in the marine sediments. The results of their study revealed strong correlations of Al, Fe, Cr, Li and Pb with the mean grain size, and correlations of Cd, Cu, Zn and Sn with the organic carbon content. Moreover, they determined the mobility of sediment by studying fractions of sedimentary metals into lattice and labile fractions. Labile fractions were Pb>Zn>Cd>Cu>Ca>Sn and lattice fractions were of the order of Al=K>Cr>Li>Sr>Fe. They concluded countermeasures must be taken to stop the influx of contaminated wastewater discharge into the seawater and to improve the quality of sediments polluted with heavy metals.
López et al. (2010) reported increased metal solubility and reduced metal absorption in sediments with lower pH. This resulted in increased uptake of metals by clams due to increased free metal ions. Mobility of metals within the sediments and their bioaccumulation within the biota are altered with the change of pH, hence pH is an important factor in determining the mobility and bioaccumulation of metals in the sediments and biota respectively. Cd movement from sediment to water and vice versa increased with acidification. The affinity of cadmium to bind with other substances like chlorines carbonates and other results in formation of complex
25 compounds. (Aleksander-Kwaterczak & Helios-Rybicka, 2009). If ligands are present they can bind Cd and this excess of free Cd ions is counterbalanced, and as a result reduces bioavailability of Cd to organisms (Aleksander-Kwaterczak& Helios-
Rybicka, 2009). López et al. (2010) concluded that any accidental or intentional acid spill into the sea water can cause sediment acidification because capture of CO2 or excess organic matter can alter bioavailability of metals to the organisms. This effect is dependent on the type and amount of sediment contamination.
Ahumada and Vargas (2005) studied metal distribution in sediments within an embayment system. Quantitative analysis of water polluted with industrial waste showed that lead (Pb) is greater or equal to Zinc (Zn), which was greater than copper
(Cu) and chromium (Cr) > or = Ni > Cd. And metals from trap showed Zn greater than Cr, which was equal to Cu > or = Pb> Ni > Cd. The most abundant metals were
Zn > Cr > Cu >Pb> Ni > Cd in the sediments of the studied areas. Karbassi et al.
(2008) determined bulk concentrations of metals (Pb, Cd, Zn, Cu, Fe, Ca and Al) and their proportions in bed sediments of the Shur River and water around the
Sarcheshmeh copper mine. Assessment of contamination was done using three different indices - an Enrichment Factor (EF), geo-accumulation index and by pollution index. The authors concluded that the concentration of metals was correlated with the proximity of the water area to mining activities. Areas of water near mining activity had highest concentrations of metal pollutions, while concentration levels fell in areas away from the mining activities. River mouths had higher concentrations of metal than other areas. Geo-accumulation indices and enrichment factors were high for all heavy metals under this study except Cr. Chen et al. (2007) reported that metal concentrations strongly correlated with the physical-chemical properties of the sediments. Discharged industrial and municipal wastewaters strongly affect the chemical properties of the sediments.
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High concentrations of heavy metals in the marine environment are due to mineralized rocks, mining and smelting activities from past and current processes.
Prior studies have confirmed highly polluted sediments and sea water in the vicinity of industrial activity. Vertical distribution of the metals in the sediment cores and metal (Zn, Pb and Cd) concentrations in the upper layer of bottom sediments was determined by Aleksander-Kwaterczak& Helios-Rybicka (2009). The metals mobility and their bioavailability were determined based on metal partitioning in the sediments and metal concentrations in pore waters.
2.5 Impacts of Heavy Metals
Pollution of the biosphere by toxic metals has increased dramatically since the beginning of the industrial revolution. The main sources of this pollution include the burning of fossil fuels, mining and smelting of metal ores, municipal wastes, fertilizers, pesticides and sewage.
Emissions of heavy metals to the environment occur via a wide range of processes and pathways, including to the air, to surface waters, to the soil and into groundwater.
In terms of human health, atmospheric emissions tend to be of most concern due to the amounts involved and the extensive dispersal and potential for exposure that frequently ensues (Jacobson, 2002).
Heavy metals are among the most harmful pollutants in the environment and can cause various diseases including cancer, acute poisoning, and damage to the nervous system, muscles and bones (Baawain et al., 2011). Heavy metals can contribute to degradation of marine ecosystems by reducing species diversity and abundance and through accumulation of metals in living organisms and food chain (Naser, 2013).
Exposure to potentially harmful chemicals by humans can be through physical and
27 biological agents in air and food and water consumption. Nevertheless, it is not necessary that exposure results from the occurrence of a dangerous agent in the environment. There is a completed pathway of exposure when there is contact at a boundary between a human and the environment which has a particular concentration of contaminant at a specified time (Griffin, 2009).
Particular heavy metals cause acute toxic effects and cancer in animals, and this is due to DNA damage (Taylor and Little, 2014). Because heavy metals incline to bio- accumulate within tissues of organisms they are dangerous. Bioaccumulation means an increase in the concentration of a chemical in a biological organism over time, compared to the chemical's concentration in the environment. It is argued that compounds are accumulated in living things whenever they are taken up and stored quicker than they are broken down (metabolized) or excreted (Griffin, 2009).
Breathing heavy metal particles, even at levels well below those considered toxic, can have serious health effects (Griffin, 2009).The immune system function related to all aspects of animal and human is compromised by the inhalation of heavy metal particulates. Moreover, it has been found that toxic metals are able to increase allergic reactions, cause genetic mutation, compete with "good" trace metals for biochemical bond sites, and act as antibiotics, killing both harmful and beneficial bacteria within human systems (Jacobson, 2002).A large amount of the damage caused by toxic metals stems from the increase of oxidative free radicals they cause (Jacobson, 2002).
A free radical is an actively unstable particle, consisted of an unpaired electron which
"steals" an electron from another particle to return it to its equilibrium. Naturally, free radicals result once cell particles respond with oxygen (oxidation).However, with a heavy toxic load or occurring antioxidant deficiencies, uncontrolled free-radical production happens. Unimpeded, free radicals can lead to damaging tissue all over the body; free-radical damage causes all degenerative diseases. Some heavy metals such
28 as Cu, Zn and Fe are necessary in low concentrations for all living organisms, but most of them present toxicity hazard at high concentrations (Abdul Rida and Bouché,
1997).
Additionally, toxic metals set up circumstances which cause irritation in arteries and tissues, which lead to drawing more calcium to the area as a buffer. The calcium covers the irritated areas in the blood vessels such as a bandage, patching up a problem but generating another, that is the solidifying of the artery walls and progressive impasse of the arteries. Moreover, without replacement of calcium, the stable removal of this significant mineral from the bones will create osteoporosis (loss of bone thickness causing brittle bones) (Davydova, 2005).
All heavy metals are considered dangerous at higher levels (Freije, 2014), but the most pollutant heavy metals worldwide are probably Lead, Cadmium, Copper,
Chromium, Selenium and Mercury (de Mora, 2004). Long term exposure to lead can cause acute or chronic damage to the nervous system in humans (Haddad, 2012).
Cadmium exposure is associated with renal dysfunction. The primary indication of the renal lesion is frequently a tubular dysfunction, attested by an increased emission of low molecular weight proteins [such as β2-microglobulin and α1-microglobulin
(protein HC)] or enzymes [such as N-Acetyl-β-D-glucosaminidase (NAG)]. It has been proposed that the tubular damage is reversible, but there is good evidence indicating that the cadmium damage to tubes is irreversible (Edwards et al; 2001).
Fumes or particles of the inhalation of cadmium can be life intimidating, and while severe pulmonary impacts and deaths are unusual, irregular instances still occur (de
Mora, 2004).
Animal experiments have suggested that cadmium may be a risk factor for cardiovascular disease, but studies of humans have not been able to confirm this
(Edwards et al; 2001). However, a Japanese study showed an excess risk of 29 cardiovascular mortality in cadmium-exposed persons with signs of tubular kidney damage compared to individuals without kidney damage (Ueshima et al., 2003).
Increased exposure can cause disruptive lung disease and has been associated with lung cancer, and damage to the respiratory systems of human (Abdul Rida and
Bouché, 1997). Children are mainly at risk of exposure as a result of increased gastrointestinal uptake and the porous blood–brain wall (Brito et al.; 2005). Both
Copper and Mercury are known to cause damage to the human brain and central nervous system (Edwards et al.; 2001). Mercury leads to damage to the brain and the central nervous system, causing psychological alterations as well as making development alterations in young children (Brito et al.; 2005). Mercury is a toxic material and in human biochemistry has no known function. The route of exposure to mercury is food, fish being a major source of methyl mercury exposure. The public does not encounter an important health risk from methyl mercury, though specific groups with increased fish consumption could achieve blood levels linked to a low risk of neurological damage to adults. Because there is a risk to the foetus particularly, it is therefore important that pregnant women must stay away from a high intake of specific fish taken from contaminated fresh waters (Edwards et al.; 2001).
Copper is considered as a fundamental material to human life, however in increased doses it can cause anaemia, damage to the liver and kidney, and irritation to the stomach and intestines. Chromium is employed in metal alloys and colors for paints, paper, cement, rubber and other materials. Low-level exposure can cause irritation to the skin and ulceration. Long-term exposure can cause damage to the kidney and liver, as well as damaging circulatory and nerve tissue. Chromium frequently builds up in marine life, counting to the danger of consuming fish which might have been exposed to increased levels of chromium (Edwards et al.; 2001).
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It has been estimated that the lowest observable Cr effect limit in sea fish is 0.03 mg kg -1 dry weight, while the limit in water concentrations for sea fish is 170- 400 mg l-1
(Ayres and Hellier, 1998).
2.6 Risk Assessment Methods and Policies Assessing Environmental Pollution
2.6.1 Risk Assessment Terminology:
Nowadays, a range of health hazards and man-made threats are increasing in their occurrence, complication and interconnectedness due to increasing use of hazardous chemicals and globalization. For about four decades the field of risk assessment has received widespread attention within both the scientific and regulatory communities
(Griffin, 2009). There are numerous definitions of hazard and risk; both are terms that are central to the risk assessment process, and so it is useful to begin by defining what is meant by these two terms. A hazard is any physical situation or object that has the potential to cause harm to people, and risk is the likelihood of a specific undesired event occurring within a specified period (Griffin, 2009). Gormley et al (2011) define hazard as ―a situation or biological, chemical or physical agent that may lead to harm or cause adverse effects‖ and risk is ―the consequence(s) of a hazard(s) being realized, and their likelihoods/probabilities Risk is therefore a function of both the likelihood and consequence of a specific hazard being realized.
Risk assessment is an important framework that provides the way for a structured review of information relevant to estimating health or environmental outcomes. Risk is defined as the expected value of undesirable consequences on hazard (Griffin,
2009). Gormley et al (2011) defined risk assessment as ―the formal process of evaluating the consequences of a hazards being realized and their likelihoods/probabilities‖. In other words, risk assessment is looking at studying
31 effects of an agent on ecosystems (Ecological Risk Assessment) and humans (Health
Risk Assessment) (Fairman et al., 1998).
The term Environmental Impact Assessment normally defines a process by which information about the potential environmental and human health risks arising from a proposed development project is determined by the planning authority in forming their judgment on whether the development can proceed or not
According to the USEPA (2001), a health risk assessment is the process that scientists and authorities use to estimate the increased risk of health problems in people who are exposed to different amount of toxic substances. It combines results of studies on health effects on various animals and human exposures to the pollutant with results of studies that estimate the level of people‘s exposures at different distances from the source of the pollutant.
Environmental Risk Assessment (ERA) can be defined as the examination of risks resulting from human activities that threaten ecosystems, animals and people. In specific it is about human health risk assessment, ecological or eco-toxicological risk assessment, and specific industrial applications of risk assessment that examine end- points in people, biota or ecosystems (Fairman et al., 1998).
An ecological risk assessment is the process for evaluating how likely it is that the environment may be impacted as a result of exposure to one or more environmental stressors such as industrial run-off, chemicals, land change, disease, invasive species and climate change. Nowadays, humanity faces questions about various environmental concerns, many of them related to plants, animals, ecosystems as a whole, and how we interact with them. These questions may be about potential risks such as impacts on health effects of pollution or the consequences of long-term release of contaminants to an ecosystem. Form the point of view of public health,
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―risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from certain human activities‖ (Griffin, 2009).Such approach must be taken into caution when using epidemiological data, which is subject to bias, in extrapolating experimental data to human health. A number of limitations in the estimation of risk from scientific data have been identified, including questionable statistical significance and limitations in accurately measuring or modeling exposure (Sykes et al, 2007). Risk to human health can only be truly assessed if a hazard exists, a pathway of concerned pollutants occurs through which the effects of that hazard can be transmitted, and the population is then exposed to doses of contaminated hazard (Halls, 1996). According to international law, the use of particular chemical agents is not allowed unless it can be revealed that they do not increase the risk of death or disease over an exact threshold. The majority of world- wide chemicals that have these properties have been earlier measured quantitatively by national and international health organizations (WHO, 2012).
2.6.2 Risk Assessment methodology
Gormley et al (2011) reported that countries and organizations developed risk management ‗frameworks‘ and used them as road maps for management. They mentioned that frameworks identify four main components: (1) formulating the problem; (2) carrying out an assessment of the risk; (3) identifying and appraising the management options available; and (4) addressing the risk with the chosen risk management strategy. Figure 2.2 shows a framework for environmental risk assessment and management. This is a globally accepted methodology to determine human health from environmental exposures.
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Figure 2-2: A framework for environmental risk assessment and management (Gormley et al., 2011)
2.6.2.1 Problem formulation:
Initially the problem in question must be formulated in clear and unambiguous terms this will help to select the level and types of assessment methodology used.
Development of the conceptual model is an important stage that presents the hypothesized relationships between the source (S) of a hazard, the pathways (P) by which exposure might occur and the receptors (R). The S-P-R relationship identifies potential completed pollution linkages and determines the potential receptors at risk
34 of exposure to the hazard. After the risk screening phase sufficient knowledge will have been gained to identify which scenarios will need to be examined in more detail.
Once the problem is formulated and scoped, this may need to be revisited as the assessment proceeds.
2.6.2.2 Assess Risk
Risk assessment is the second phase which has four stages: Identifying the hazard(s); assessing the potential consequences; assessing their probabilities; and Characterizing the risk and uncertainty. Figure 2.2 illustrates these risk assessment stages. The output of this process provides a decision as to the presence of the risk and its consequence, and gives details on how the risk was assessed and where assumptions and uncertainties exist.
The identification of the hazard will have an important bearing on the scope of the overall assessment. One common pit fall is to overlook secondary hazards that may also arise. For example, during a river flood, sediments may be deposited on agricultural land in the flood plain. If these sediments were to be contaminated, they may pose an additional hazard. Secondary hazards need consideration during problem formulation when the scope of the risk assessment is being agreed.
The potential consequences that may arise from any given hazard are inherent to that hazard. The full range of potential consequences must be considered at this stage. For example, while the potential consequences of a discharge of high levels of nitrates and phosphates from a point source to surface waters may be self-evident, a flood may have additional, non-obvious consequences, such as pollution arising from an over- stretched sewerage system, or loss of habitats due to river scouring (Gormley et al.,
2011)
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With the range of potential impacts (which could be qualitatively or quantitatively described), the likelihood that they will occur may be expressed as a probability or frequency. It is important to assess probability with some degree of confidence as the credibility of the risk assessment is undermined if the probability presented appears to be wholly subjective or, conversely, indefensibly precise. Indeed, using data to define probabilities for discrete and rare events is more difficult than for those that can be readily observed. It is therefore best to consider how relevant the data is to the problem (Gormley et al., 2011).
2.6.2.3 Appraisal option
Appraisal option is a process of identifying and selecting the most appropriate strategy for managing risk. Various criteria are used for identifying best managing risk options which may involve scoring, weighting and/or reporting that seek to maximize human and social well-being, environmental benefits, and value for money.
One of the main inputs for the appraisal phase is the controlling factor for the risk identified during the problem formulation stage (Gormley et al., 2011).
2.6.2.4 Address Risk
Phase 4 as detailed in figure 2-2 is about addressing the risk and undertaking appropriate action to fulfill the objectives of the environmental risk management strategy identified at the options appraisal stage. This phase is about addressing the risk and undertaking appropriate action to fulfill the objectives of the environmental risk management strategy identified at the options appraisal stage (Gormley et al.,
2011).
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2.6.3 Risk Assessment Policy and Oman methodology
Public policy choice is needed if a recognizable sub-population is more susceptible due to inherent genetic or other aspects. Internationally, the issue of not growing lifetime risk by more than one in a million has been used widely in public health dialogue and policy. It is an empirical measure; and it offers a statistical source for creating a very low increase in risk. Some discretion for considering individual risks potentially "acceptable" is allowed if they represent less than a one in ten thousand chance of increased lifetime risk (Griffin, 2009).
These low risk standards offer some protection for a situation where individuals could be exposed to various hazardous agents. In practice, a true zero-risk is difficult to achieve and is likely only with the control of all risk-causing activities and the complete clean-up of the polluting chemicals if they occur as residuals in the environment. Criteria of one in a million lifetime risk that discussed by Griffin (2009) might not be technologically possible or could be so excessively costly as to make the risk-causing activity un maintainable, which causes the best degree of reducing benefits of using chemical agents in human development (Gormley et al.; 2011).The best option is to find alternatives that balance risk verses benefit. For sure, there are public health risks, as well as economic costs, associated with all options.
Major projects, including special economic zones, complex industrial areas, seaports, airports, dams, power plants, wastewater projects, and the projects of coastal flood protection, oil and natural gas extraction have been revealed to be highly risky in terms of funding, security, and social and environmental influences
Risk assessment can be thought of as a tool to aid decision-making. The process of carrying out a risk assessment will result in an understanding of the level and significance of workplace risks that should inform decisions relating to the
37 implementation of appropriate risk control and reduction measures (USEPA, 2001).
Even though, the risks themselves are often assessed qualitatively, not quantitatively because of the lack of data. Risk assessment is an integral part of successful health and safety management. In the Sultanate of Oman law, employers are required to have arrangements in place to cover their management of health and safety (MECA, 2005).
Thus, risk assessment is an essential component of the planning and implementation element of effective health and safety management. Although authority guidance
(MECA, 2009) has been developed for conducting environmental assessment, the guidelines focus primarily on human exposure assessment, and detailed environmental risk assessment methodologies have not been applied.
According to MECA, risk assessment methods can be used to decide on priorities and to set objectives for eliminating hazards and controlling and reducing risks (MECA,
2009). The goal of Risk Analysis is to estimate the nature and level of impact of each risk. It offers the source for Risk Evaluation and decisions for Risk Treatment.
Risk analysis conducted by project developers and assessed by government authorities on the risks has been defined and reserved for additional analysis in terms of their occurrence and general importance. The aim of the government authority procedure is to measure the risk in a standardized way by using a common process and steps.
The assessment of risks at establishments in Oman is carried out on a biannual basis.
In the context of the MECA, an all hazards method does not necessarily indicate that all hazards will be measured biannually, but rather that all threats will be measured at the start of each new cycle.
The biannual evaluation will concentrate on the most likely and important risks. It is neither likely nor essential to evaluate all risks within a given year; rather, a detailed risk picture will be constructed over some cycles under the direction of MECA
38 experts. The assessment of risk at MECA is based on a methodology that includes the following steps (MECA, 2009):
i. Setting the Context – The procedure of articulating an organization‘s
objectives and describing its external and internal limits to be considered
when managing risks.
ii. Risk Identification – The procedure of finding, recognizing, and recording
risks.
iii. Risk Analysis – The procedure of getting to understand the nature and level
of risk, by understanding its effects and possibility.
iv. Risk Evaluation – The procedure of comparing the outcomes of Risk
Analysis with risk standards to define whether a risk and/or its greatness are
satisfactory or tolerable.
v. Risk Treatment – The procedure of finding and recommending risk control or
Risk Treatment choices.
The MECA procedure uses a scenario-based risk valuation method. From a high-level viewpoint, the MECA concentrates on the five steps mentioned earlier and is associated with the general emergency management method. For better future of our environment; MECA requires a solid implementation plan for conducting risk assessment in the field as well as increased capabilities including equipment and a trained work force for field monitoring and assessment.
2.7 Finger Printing Technique
The fingerprinting technique involves identifying and characterizing potential sources of sediments on the basis of their chemical and physical properties. These properties are then compared with those of samples of suspended sediment. This method
39 determines the relative importance of different potential sources (Legout et al., 2013).
Due to numerous limitations and problems associated with the traditional methods of identifying original sources of suspended sediments, the fingerprinting technique has recently become a more popular and reliable method because it provides a rapid method of determining the source of environmental pollution. Traditional methods involve long-term monitoring at a wide range of areas: however, fingerprinting requires only a limited amount of field data (source material and suspended sediment samples) and requires only small area coverage (Voli et al., 2013).
In order to maintain good water quality and reduce pollution in the marine environment, scientists are searching for reliable information about sediment dynamics in catchments. Sediment represents the main factor in the transport and destination of key pollutants. Sediment dynamics can only be understood with reliable information on the principal sources involved (Dutton et al., 2013). Techniques used previously for identifying sources have limitations and constraints, including the use of spot sediment samples and its cost (Collins et al.; 2001).Thus, sediment fingerprinting is now developed in order to provide reliable alternative methods of gathering information on properties of sediments and their sources. Fingerprinting methods include several diagnostic sediment properties to create a composite fingerprint, in which more representative and consistent methods of verifying sediment origin are provided and greater numbers of sources can be determined
(Collins and Walling, 2002; Franz et al., 2013).
Quantitative descriptions of fingerprinting technique involve two stages: first to use a statistical verification procedure and then to compare the composite fingerprints of source samples (Collins et al., 2001). One aspect of fingerprinting is sediment fingerprinting. This type is based on two main assumptions; the basis of geochemical and geophysical properties of catchment sediment sources is different from one
40 another, and the determination of potential sediment sources is applicable by comparison of deposited sediment and source samples (Collins et al.; 2001). Several properties of sediment, also called fingerprint properties, can be used to discriminate potential sediment sources within a catchment (Franz et al., 2013), including Franz geochemical composition (Passmore and Macklin, 1994; Collins et al., 2010), mineralogy (Klages and Hsieh, 1975), mineral magnetism (Walden et al., 1997), environmental radionuclides (Devereux et al., 2010), stable isotopes (Douglas et al.,
1995), biogenic properties (Brown, 1985), and particle size (Stone and Saunderson,
1992).
Some studies established groups of fingerprinting properties, including Organic constituents, base cations, acid extractable metals, clay minerals and magnetic properties consisting of Low Frequency Magnetic Susceptibility (XLF) and Frequency
Dependent Magnetic Susceptibility (XFD) (Kouhpeima et al., 2013). These groups were selected on the basis of available analytical equipment and their successful use in previous studies to discriminate sediment sources (Collins and Walling, 2002;
Collins et al., 2008). In procedure where a particular property was used, results showed that the most powerful individual fingerprint property is the organic constituent (Brown, 1985). However, an individual fingerprinting property measured for a given sediment sample could match that of a specific sediment source, or might represent a mixture of sediments originating from a number of potential sources.
Using several properties reduces the potential for spurious source sediment linkages, and affords more powerful source discrimination than individual fingerprint properties (Kouhpeima et al., 2013).
Important information on the source of the suspended sediment can be obtained by sediment source fingerprinting techniques. The techniques attempt to match the properties of the sediment to those of potential sources and to base the relative
41 contribution of those sources in a given sediment sample. Source types could include surface erosion from cultivated areas and areas of permanent pasture or range, gully erosion, and channel erosion. Composite fingerprinting, in most cases, is required to discriminate between potential sediment sources (Walling et al., 2011).
Recently, properties of fingerprinting have been based on compound specific stable isotopes (CSSIs) associated with the fatty acids produced by plants (Devereux et al.,
2010). This type offers the potential to discriminate between source areas supporting different vegetation covers (Walling et al., 2011). The fingerprinting approach has also been applied to overbank sediment deposits on floodplains (Bottrill et al., 2000) and fine sediment recovered from salmon spawning gravels (Walling et al., 2003).
2.7.1 Fingerprinting methods
Innumerable problems have arisen in the past in determining the primary sediment sources of diffuse pollutants within a river catchment. The fingerprinting approach was developed to replace more conventional methods that have proved to be more reliable and provides a direct means of determining information about likely sources
(Kouhpeima et al., 2010). The fingerprinting technique is based on the fact that the physical and geochemical properties of sediment and its sources are related. The proposition is that the potential sources can be discriminated on the basis of physical and geochemical fingerprinting of the materials; therefore, the origin of the sediments can be determined by comparing sediment fingerprints with those of possible sources
(Sherriff et al., 2013). Matching properties of sediments and sources in fingerprints are compared and used for establishing correct sources (Walling et al., 2008).
Use of the fingerprinting method is increasing in determining resources as it produces more accurate results in a shorter time-span as compared to other more conventional
42 methods. The primary benefits of using fingerprinting techniques are that it is relatively cost effective, simple to use and time saving (Walling et al., 2008).
Efforts to recognize the primary sediment sources and their relative importance in contributing load within a catchment or river basin face a number of important problems (Peart and Walling, 1988; Collins and Walling, 2004). Conventional techniques are frequently hampered by problems of spatial and temporal sampling, operational difficulties and the costs involved (Collins and Walling, 2004). These conventional techniques involve field profile meters (Toy, 1983), soil erosion plots
(Loughran, 1989), observations and mapping (Cao and Coote, 1993), the use of erosion pins (Lawler et al., 1997), terrestrial photo geometry (Barker et al., 1997), and remote sensing (Vrieling, 2006) that are, however, not pertinent.
Knowledge of suspended sediments‘ origin is imperative for studying in detail the properties of sediments and to take necessary actions to control pollution. It is also vital for the assessment of sediment delivery and routing in the building of reservoir sediment resources (Kouhpeima et al., 2010). Kouhpeimaet al. (2011) suggested that with regards to management of water quality, it is a necessity to recognize the sediment sources and then apply correct strategies to manage mobilization of sediment and control effects related to it, such us catchments sedimentation and siltation of river channels. Moreover, since sediment sources also determine to some extent the mobilization of nutrients and contaminants in water runoff as well as the physical and chemical properties and contaminant contents, a specific management strategy will require finding the origin of such real sediment (Kouhpeima et al., 2010;
Kouhpeima et al., 2011).
Most traditional fingerprinting monitoring techniques are insufficient to determine the relative importance of sources because of several operational problems; as they prove useless for larger areas due to sampling constraints. Latest fingerprinting techniques 43 prove to be more reliable for studying large basin areas and remove several such constraints faced by other conventional methods (Peart and Walling, 1988; Collins and Walling, 2004).
The clear-cut information required on sediment sources will enable resolution of sediment-related problems. On the other hand, knowledge about the source type and spatial location are both often required (Walling et al., 2008; Sherriff et al., 2013). It is of utmost importance to have reliable information regarding sources of suspended sediments gathered in river from diverse sources. It is imperative to design rigorous and effective strategies to control pollution and contamination of suspended sediments within the water catchments (Kouhpeima et al., 2011; Sherriff et al., 2013). The suspended sediment carried by means of a river represents a combination of sediment mixture originating from diverse locations and different kinds of sediment sources that are found in the contributing drainage basin. The suspended sediment concentrations within the water runoff also determine the quality of water and generally characterize the types of sediment sources originating from the supplying drainage basin (Kouhpeima et al., 2010; Kouhpeima et al., 2011; Sherriff et al., 2013).
The important steps in the fingerprinting process involve the selection of appropriate diagnostic property which is best suitable for discriminating potential sediment sources, and then comparing these properties of sediment fingerprints with those of catchment source samples to determine the original source of sediments (Walling et al., 2008).
In this study, the sources of heavy metals were speculated on according to the data available from different companies using the type of chemical in their operations. At
SIP, lack of geological and other background data led to limitations in the study. For this reason information on chemicals used at SIP was based on assumptions about potential sources and chemical use at different companies. 44
2.7.2 The importance of Fingerprinting
Fingerprinting has several advantages over other methods. The first is that a limited amount of field data collection is required. It replaces the conventional, costly and long-standing methods that produce results after long endurance periods (Kouhpeima et al., 2010; Kouhpeima et al., 2011). Chemical and physical properties used in fingerprinting techniques are sediment chemistry, mineralogy, mineral magnetism, and environmental nucleotides. These properties have been successfully used to differentiate possible sediment sources in drainage basins. The most commonly employed fingerprinting properties are color (Grimshaw and Lewin, 1980), mineral magnetism (Caitcheon, 1993), mineralogy, geochemical composition (Foster and
Walling, 1994), environmental radionuclides (Wallbrink and Murray, 1998), acid extractable metals (Collins and Walling, 2002; Kouhpeima et al., 2010), clay minerals
(Feiznia and Kouhpeima, 2010; Kouhpeima et al., 2010), organic constituents (Collins and Walling, 2002; Walling et al., 2008; Feiznia and Kouhpeima, 2010; Kouhpeima et al., 2010), particle size (Stone and Saunderson, 1992; Walling et al., 2008) and base cations (Feiznia and Kouhpeima, 2010; Kouhpeima et al., 2010).
Such properties have proved to be effective in determining the individual source types and their relevant importance in contributions in catchments. Sources like surface soils and subsoil channel banks under different land uses can be discriminated from each other (Walden et al., 1997). These properties are also effective in determining the spatial location of sediment origin,e.g. whether it is from sub-catchments or discrete geologies (Collins et al., 1996, 1998) or a mix of both (Walling and
Woodward, 1995; Collins et al., 1997a), and also in determining regular changes in sediment sources using sediment cores (Collins et al., 1997b; Owens et al., 2000).
45
Use of a single diagnostic property should be avoided in differentiating various potential sediment sources, since spatial variability of drainage basins and complex delivery processes and routing of sediment diverse sources makes it difficult to detect several potential sources with only one or two diagnostic properties (Kouhpeima et al., 2010; Kouhpeima et al., 2011).
To take full advantage of the fingerprinting procedure in order to produce effective results, the different diagnostic properties should be used and must be managed by different environmental controls and therefore acquire an independence at huge scale, so that in combination it produces significantly verified source segregation (Feiznia and Kouhpeima, 2010; Kouhpeima et al., 2010). One tracer will differentiate only one potential source and discrimination among other sources will remain unresolved
(Walling et al., 2008; Feiznia and Kouhpeima, 2010; Kouhpeima et al., 2010).
Walling et al. (1993) employed cluster analysis methods to differentiate between source groupings which are statistically significant and a mixing model was used to calculate the relative contribution from all possible sources to the overall suspended sediment concentration in basins. This is done in order to obtain a better understanding of pollution types, their sources, and the erosion and suspended sediment transport that is necessary to set up sediments budgets, dispersed sediment yield models, and estimate sediment yields to know the landscape evolution. This information will help find out whether the land is for cultivation or not. The fingerprinting technique also has extensive potential to detect diverse sources based on the use of chemical and physical properties of sediments (Feiznia and Kouhpeima,
2010; Kouhpeima et al., 2010).
Selection of the best and appropriate fingerprinting properties is based on respective environmental controls and capabilities of differentiating potential sediment sources.
Statistical analysis of obtained sediment sources is necessary against the fingerprint
46 properties to confirm their validity. Finding out the relative importance of each source and the load produced by comparing composite fingerprints of suspended sediment and potential sources using objective algorithms is also needed. Selection of fingerprint properties must be based on the fact that they must reflect different controls, should reveal conservative behaviour during erosion and fluvial transport, and must be able to differentiate potential sources and enhance the degree of discrimination by various composite fingerprints (Kouhpeima et al., 2010).
A variety of fingerprinting techniques use different fingerprint properties to detect original source. Technique Gamma spectrometry measures Pb and Cs, while Carla
Erba Elemental Analyzer measures concentrations of organic carbon and nitrogen
(Kouhpeima et al., 2010). Even fingerprinting technique has problems associated with it and results remain inconclusive and discrimination is possible (Kouhpeima et al.,
2010): this is especially when fingerprints depict high and low values of a particular property for a mixture of two possible sources, or an intermediate value with no significance of a property of a single source. This problem can be overcome by the use of a composite fingerprint. This includes comparing and contrasting a variety of fingerprinting properties with contrasting behaviour (Collins et al., 1997).
2.7.3 Finger printing in pollution assessment
Quantitative descriptions of fingerprinting techniques involve two stages: first using a statistical verification procedure and then comparing the composite fingerprints of source samples. A quantitative composite fingerprinting technique was used to study sediment sources in the Kaleya catchment (Collins et al.; 2001). It was found in this study that the load-weighted mean relative contributions to the sediment load sampled
47 at the catchment were: commercial cultivation (2.0%), bush grazing (17.1%), channel banks/gullies (17.2%) and communal cultivation (63.7%).
Isotopic fingerprinting was used in soak away sediments to investigate the isotopic variation of Pb. That variation was compared with soils and road dusts to trace their contamination characteristics, mobility and source (Kumar et al.; 2013).In the study, isotopic signatures of metal content display higher metallic content of anthropogenic origin with high mobility in soak away sediment and residential road dust. Some anthropogenic markers are paint, petrol and aerosols (Kumar et al., 2013).
Fingerprinting techniques use natural tracer technology, field data collection, laboratory analyses and statistical analysis to fingerprint the properties of pollutant sources. This technique is a valuable tool for assessing pollutants‘ load in water on a daily basis in order to design strategies to get rid of pollution and obtain a clean environment and water in coastal areas. Steps involved in sediment fingerprinting techniques are classification of sediment sources, identification of unique tracers, fingerprinting and determination of tracer pollutants origination from their respective sediment sources and their transportation to the marine water sink (David and Fox,
2009).
The limitation in the use of fingerprinting techniques is that there is uncertainty in linking sediments back to their original sources because of the non-conservative properties of sediment properties (Loiter et al., 2013).Several chemical processes may cause change in the sediment properties during the passage of sediments from sediment source locations and the sink (where sediments are collected), thus illuminating sediment fingerprinting approach (Legout et al., 2013). Koiter et al.,
(2013) pointed out that current literature on fingerprinting approaches tends to assume that there is no alteration of sediments during their passage from sources to the collecting sink and there is a direct connection between sources of origin and sinks. 48
However, much of the literature in environmental sedimentology sheds light on the fact that several biological, chemical, and physical processes occur that alter the chemical and physical properties of sediments as they move through the landscape.
Various biological and chemical processes transform sediments‘ particle size, geochemical, physical, chemical and biological properties. The study of such processes and understanding the transformations will help to guide sample collection, the fingerprint approach, the type of fingerprinting method selection and data analysis
(Koiter et al., 2013).
49
2.8 Conclusions
From this review it is concluded that it has long been recognized that an increase in heavy metals in the natural environment as a result of human development activities will lead to an increase in the risk of impacts on environmental and human health.
The quantification of these effects and the associated assessment of the level of risk is still very much an evolving science. Where point sources of polluting discharges can be identified and sampled, correlations between cause and effect are more likely, whereas in situations where diffuse sources are also implicated or involved it is much more difficult to identify sources and hence remediation and management strategies.
The development and application of qualitative and preferably quantitative risk management assessments in Environmental Impact Assessments has provided a consistent and hopefully more reliable way of assessing both environmental and human health risks. However the problem of source identification with respect to heavy metals remains. The development of fingerprinting approaches to look at sediment sources and the associated metals they carry is the most recent advance made in dealing with this problem.
50
Chapter Three Methodology
51
3 Chapter 3: Methodology 3.1 Introduction
This chapter focuses on evaluating the heavy metals and anions in surface sediment, to investigate the influence of Sohar Industrial Port (SIP) and anthropogenic sources on the study area. Surface samples were collected from seven stations in this area – within the port, in the vicinity of the port, and in the surrounding area. Samples were collected during February to April 2011 and during February to April 2012. The seven stations started within the port (site A), with three extending along the coast to the north-west and three extending along the coast to the south-east. The total number of samples collected was 45. The analysis of heavy metals was as per the USEPA protocol (3050B), using an Inductively Coupled Plasma Optical Emission
Spectrometer (ICP-OES). Anions were extracted from sediments, using ion chromatography as the most appropriate method.
The Chapter is divided into the following sections:
(i) Introduction (Section 3.1)
(ii) Site Description (Section 3.2)
(iii) Pilot study (Section 3.3)
(iv) Monitoring Area (Section 3.4)
(v) Field Sampling (Section 3.5)
(vi) Chemical preparation for Heavy Metals (Section 3.6)
(vii) Sample Analysis for Anions – Ion Chromatography (IC) (Section 3.7)
(viii) Statistical analysis (Section 3.8)
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3.2 Site Description
3.2.1 Study Area: North Al Batinah, Sohar, Oman Coastal Environment
The Sultanate of Oman is situated in the eastern corner of the Arabian Peninsula between latitudes 16°40' and 26°20' north at the head of Musandam and longitudes
51°50' and 59°40' south-east at Ra's al-Hadd (Ministry of Information, 2009).
Being located north and south of the Tropic of Cancer, it is a hot and dry area. The peninsula is surrounded by three seas: the Arabian Gulf in the north; the Sea of Oman in the north-east and the Arabian Sea in the south-east (Al-Jahwari, 2013). This location has given the Sultanate a long coastal strip that extends for 3,165 kms
(Ministry of Information, 2009). This coastal strip includes several natural seaports that have been exploited over time either for fishing or for local and regional trade
(Al-Jahwari, 2013).
The North Al Batinah Governorate where Sohar City is located varies between 30-50 kms wide and extends from the east of Muscat (the capital city area of Oman) to the convergence of the Al Hajar mountain chain with the coastline at Dabba al Bayah in the west (Figure 3.1) (Ministry of Information, 2009 and 2013). It is located along the southern shore of the Sea of Oman (Ministry of Information, 2009). The area plays a vital role in the economics of the country and of the region, as it is geographically easy to reach the Gulf Cooperation Council (GCC) states and the Indian sub-continent from it (Muscat daily, 2013). Its economic activities have developed as a result of this. According to the National Centre for Statistics and Information report (2013),
North Al Batinah Governorate‘s population in 2013 is 638,574 which is one of the highest populated areas in Oman, after Muscat itself.
53
The coastal environment of North Al Batinah is characterized by a long coastal strip between the sea and the mountains which is approximately 25 kms in length, formed by the wadis which flow down from the Hajar Mountains (Al-Jahwari, 2013). It varies between 15 and 80 kms in width (Figure 3.1). It has over time become a major maritime and trading link with different countries in the Gulf and the Indian Ocean, and has several economic resources, including agriculture and mineral deposits that formed the basis for heavy industrial projects such as the Sohar Industrial Port and
Sohar Industrial Estate (Ministry of Information, 2009 and 2013).
Figure3-1:Map of the Sultanate of Oman showing the extent of the Al Batinah plain and the location of the cities of Shinas, Liwa and Sohar (Source: Ministry of Transport and Communications)
54
The study area along the Al Batinah coastline is densely populated (National Center for Statistics and Information, 2013) and people are mostly dependent on the marine coastal environment for their culture and economy. They prefer to live close to the coast, and practice fishing along the coast.
The Arabian Gulf has been extensively studied and the environmental degradation associated with regional development well-documented (see recent reviews by Hamza and Munawar, 2009; and Sheppard et al., 2010). In contrast the adjacent Sea of Oman has had little attention, though some environmental impacts have been described from both the passage of ships through it and the international maritime route through the
Strait of Hormuz. The Annual Report of the Ministry of Transport and
Communications (2013) indicated that during 2013, 34,395 vessels passed through the
Strait of Hormuz, either towards the east or the west.
Overall, the Al Batinah coast is considered to be eroding as a result of reduced sediment supply to the coast due to climate change. Recent construction of a series of flood mitigation measures and the building of dams along almost all major wadis and groundwater wadis has played their part too (Salm and Dobbin, 1989; Dibajnia et al.,
2010).
Gently sloping at an incline of 1:400 (Dobbin, 1992) the beaches are shaped by a low energy environment that has a meso-height tidal range of between 1.0 meters and 2.3 meters, neaps to springs tides. It is a low energy wave environment characterized by a typically significant wave height of less than 0.5 m (designated as ―Calm‖) for 85% of the time. Wave heights in the Sea of Oman show seasonality, which is a product of the tropical weather systems of the North West Indian Ocean. Significant wave heights can reach 3m in September or October at the peak of the south-easterly monsoons (McCue, 2005). Superimposed on this seasonal pattern is a diurnal sea
55 breeze for much of the time. Therefore, the selection of sampling times was influenced by the tide.
3.2.2 Sohar Industrial Port
Since the discovery and subsequent export of oil starting in 1967, Oman has developed rapidly. During the last third of the twentieth century and the beginning of the twenty-first century, Oman has consequently started building commercial and industrial ports in different areas along the coastline in order to make the economy stronger and ensure that development covers important regions in the country
(Ministry of Information, 2009).
As part of this development the Sultanate is also investing in a range of industrial sectors, including a dedicated heavy industry port and associated industrial infrastructure at Sohar, a rapidly growing urban and industrial city in the most heavily populated and developed region of the Al Batinah coastline facing the Sea of Oman.
Sohar Industrial Port (SIP) covers approximately 2 kms of coastline. SIP was established as the third major industrial area in the country in three phases, starting in
1999 with breakwaters, jetties and the dredging of the entrance channel and harbor basin. The last phase was completed in 2008.
SIP started with 16 jetties, and now has 21 that are between 16 and 25metres deep.
There are four main terminals for containers, general goods and loose dry cargo.
Furthermore, there is a terminal for handling liquid cargoes. The number of ships in the SIP in 2009 was 1,013, including 236 container vessels and 432 liquid cargo vessels, and it handled over 76,000 standard containers. In 2013 the number of ships had increased to1, 964, showing an increment of around 97% in a period of 4 years
56
(Ministry of Information: 2009& 2013). Figure 3.2 shows the growth in vessels calling between 2007 and 2013.Concentrations of heavy metals and of hydrocarbon pollution would be expected to increase in this area as a result of such expansion.
2500
2000
1500
Vessels 1000
500
0 2007 2008 2009 2010 2011 2012 2013 Years
Figure3-2: Number of Vessels at SIP from 2007 to 2013 (Source: SIPC)
The SIP now has a number of different petrochemical industries based there, including an oil refinery producing gasoline, fuel oil, kerosene, Liquefied petroleum gas (LPG), propylene, naphtha, low-sulphur gas oil, and granulated sulphur; a polypropylene plant; an aromatics plant producing benzene, paraxylene and other related products; a methanol plant; and a urea fertilizer plant. The Port also hosts several metal-based industries including an aluminum smelter, an iron pelletizing plant and a fully-integrated steel plant. Moreover, the construction of a sugar refinery is underway. Power generation, feed-water and cooling water supplies and
57 wastewater disposal are all undertaken as integrated processes within the Port, with the cooling and wastewater being discharged from a common outfall channel located within the SIP (Oman Establishment for Press Publication and Advertising, 2011&
2014). The layout of the SIP in figure 3.3 shows the co-location of different industrial production facilities.
Figure 3-3: The layout of the SIP showing the co-location of different industrial production facilities. (Source: SIPC)
At the moment all treated wastewater influence within the SIP is disposed of by discharging it through the cooling water return channel. This channel discharges an estimated 334,000 m3/hour of seawater and this is about to be doubled in capacity
(SIPC personal communication, 2012).The present outfall is located at the tidal boundary at the east end of the Port. Planning is now underway to implement a ―no discharge‖ policy for wastewater through improved wastewater treatment and re-use.
This wastewater is a potential contributor of heavy metals to the waters of the Port and surrounding areas, as are stack discharges, the fugitive dust from stockpiles from
58 past and ongoing construction activities, and vehicle movements (Oman
Establishment for Press Publication and Advertising, 2011).
3.3 Pilot study
A pilot study was undertaken as a first step to get information about the research before starting the more extensive sampling for the project. There are important reasons for undertaking a pilot study: it gives us a clear picture about the extent to which the project could be unsuccessful; whether the protocol for the research may not be practicable; and finally whether the research is overly-complicated or too expensive (Thabane et al., 2010). Moreover, Teijlingen and Hundley (2001) have suggested several other reasons for pilot studies such as designing the protocol of a study and assessing whether it is realistic and workable, assessing the feasibility of a study, testing the adequacy of research instruments, establishing whether sampling and analysis techniques are effective, identifying logistical problems which might occur using proposed methods, obtaining preliminary data, developing a research question and research plan, and convincing funding bodies that the main study is feasible and worth funding. A pilot study is the conduct of the main study in miniature
(Morin, 2013).
A pilot study was carried out for this current research in order to collect samples from three areas– see Figure 3.4:
a) Sohar Industrial Port (SIP): Area A
b) Harmul: Area B
c) Majis: Area C
59
These areas were considered to represent the core SIP area and the surrounding two areas to the north-west and to the south-east of the SIP. To our knowledge, no previous studies had been conducted on the SIP area, though surrounding sites were included in a study conducted by Al-Shuely et al (2009).
Due to cost and time constraints, the total number of samples collected was nine, three at each location. The samples were rinsed with sea water from the same site at which the sample was collected, then washed each time with Nitric acid (10%), and finally washed with distilled water. Samples were stored in plastic bags, placed on ice and transported to the laboratory within 3 hours of collection (ASTM, 2000a; USEPA,
2001; Simpson et al., 2005). Sampling procedures were according to the USEPA
(3050B) (USEPA, 1996).
CB
C B A
A Figure3-4: Locations of the pilot areas (not to scale)
60
3.3.1 Pilot Study Result
The mean concentrations of selected heavy metals Cd, Co, Cr, Cu, Mo, Pb, V and Zn
in SIP, Harmul and Majis are presented in Table 3.1. The mean concentration of Cd in
SIP was 0.9(ppm) but in Harmul it was 0.98 (ppm) and in Majis 1.6 (ppm), while the
mean concentrations of Co were 30.52 (ppm), 30.87 (ppm) and 16.60 (ppm)
respectively. Harmul had higher mean concentrations of Cr than SIP and Majis at
310.50 (ppm), 410.77 (ppm) and 110.29 (ppm) respectively. Moreover, Cu was higher
in Harmul than the other sites with mean concentrations of 300.25 (ppm),
200.31 (ppm) and 90.30 (ppm) respectively.
Table 3-1: The mean concentrations of selected heavy metals (ppm) Cd, Co, Cr, Cu, Mo, Pb, V and Zn in SIP, Harmul and Majis
Parameters Cd Co Cr Cu Mo Pb V Zn SIP 0.9 30.52 310.5 200.3 1.39 50.60 26.50 61.80 Harmul 0.98 30.87 410.8 300.25 18.50 70.60 28.00 66.60 Majis 1.60 16.60 110.3 90.30 4.80 20.20 16.40 19.40
The comparison of the mean sediment concentrations of the heavy metals are
presented in Figures 3.5- 3.7. The results show that the mean concentrations of Co,
Cr, Cu, Mo, Pb, V and Zn are higher at Harmul than SIP and Majis whereas the
concentration of Cd is highest at Majis.
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20 18 16 14 Cd-Port 12 Cd-Harmul 10 ppm Cd-Majis 8 Mo-Port 6 4 Mo-Harmul 2 Mo-Majis 0
Figure3-5: The mean concentrations and standard error samplings of a pilot study of Cd and Mo.
80 Co-Port 70 Co-Harmul 60 Co-Majis
50 Pb-Port
40 Pb-Harmul ppm Pb-Majis 30 V-Port 20 V-Harmul 10 V-Majis 0 Zn-Port Zn-Harmul Zn-Majis
Figure3-6: The mean concentrations and standard error samplings of a pilot study of Co, Pb, V and Zn.
62
450 400 350
300 Cr-Port
250 Cr-Harmul
ppm 200 Cr-Majis 150 Cu-Port 100 Cu-Harmul 50 Cu-Majis 0
Figure3-7: The mean concentrations and standard error samplings of a pilot study of Cr and Cu.
It can be concluded that Harmul has the highest concentrations of Cr, Cu, Mo and Pb.
Moreover, SIP and Harmul have the higher concentrations overall. The mean concentration of Cd is highest in Majis while Co, V, Zn are comparably higher in concentration at SIP and Harmul.
Therefore, the pilot study gave us a clear picture that we could expect certain heavy metals to be present at the investigated sites. As the SIP has different petrochemical and metal companies, additional trace elements (Al, Fe, Mn, Ni, Hg, As and Sn) were added to the study to monitor their emissions by companies and anthropogenic sources.
63
3.4 Monitoring Area
Figure 3.8 shows the sampling areas, consisting of the core and control areas. One of the challenges of this project was to decide what the investigation area was going to be, including the need for control samples. As the research focus was on the potential impact on the SIP and on surrounding areas, it was decided that the area to be investigated should extend from the SIP outwards along the coastline in both directions.
The sampling area within the Port (site A) was adjacent to the cooling water/ wastewater outfall. Sampling site B was selected immediately north-west of the SIP boundary at Harmul (Liwa), with a second sampling site at A‘rumyla (Liwa) 5 kms north-west from the SIP area (site C), and a third sampling site at
AsrarBaniSa‘d(Shinas) 10 kms north-west from the SIP area (site D).This was considered as the control site. Sampling to the south-east of the SIP along the coast included sites at Majis (Sohar) immediately south-east of the SIP area (site E),
Al‘sanqar (Sohar) 5 kms further from the SIP area (site F) and Salan (Sohar) 10 kms from the SIP area (site G), which was considered as the control site (Al-Shuaily et al.,
2009). Within the SIP, samples were taken at three places away from the Port along the beaches to the West and the East at distances of 1, 5 and 10 kms (Figure 3.8), with sites 10 kms to the east and west from the port being considered as control areas (Al-
Shuaily et al., 2009). Hence, the total number of sample sites for the investigation area is seven.
Sample sites and populations are shown in Table 3.2. The co-ordinates of the sampling sites were obtained by using a hand-held GPS (Simpson et al., 2005).
64
Figure 3-8: Location of the sampling sites used in the study. Sites labeled as A were either side of the ocean outfall at the eastern end of the Port. Results from the three sample sites to the west of the Port (B, C and D) were designated as such for an initial assessment of the results and likewise for sites to the east of the Port (E, F and G).
Table 3-2: Sites location, populations and sample numbers
Sample Location Site Location description Population Latitude Longitude No.
A Sohar Industrial Port (SIP) 24o 28.639‘ 56o 38.176’ 15 E Majis south-east of the SIP 24o 27.163‘ 56o 39.658‘ 5 Sohar 196340a F Al‘Sanqar 5kms. south-east of the SIP 24o 25.826‘ 56o 41.177‘ 5 G Salan 10 kms. south-east of the SIP 24o 25.758‘ 56o 41.202‘ 5 B Harmul north-west of the SIP 24o 31.398‘ 56o 36.176‘ 5 Liwa 39232a C A‘rumyla 5 kms. north-west of the SIP 24o 33.941‘ 56o 34.265‘ 5 Asrar Bani Sa‘d 10 kms. north-west of Shinas D 62995a 24o 35.893‘ 56o 32.876‘ 5 the SIP Notes: a: National Centre for Statistics and Information
65
Sites B and E were closer to the port area and expected to have some pollution discharge from the port, as the out charge was close to site E and the main gate for shipping was close to site B. The areas would give a good indication of the levels of transportation of materials from core port areas to adjacent areas. Moreover, both sites
B and E were investigated for levels of pollution by Al-Shuely et al. (2009). Sites C and F at A‘rumylah (Liwa) north-west and Al‘sanqar (Sohar) south-east, respectively, are located 5 kms from the SIP core area.
These sites were expected to provide good indications of material diffusion and transportation from the core port areas to extended surrounding areas. Sites D and G at Asrar bani Sa‘d (Shinas) and Salan (Sohar) are located 10 kms north-west and south-east from the SIP core area respectively. Site G in the south-east was studied by
Al-Shueily et al. (2009) and the site was considered by the authors as a control site.
Similarly, site D was considered in this study as a control in the north-west area because it was a similar distance from the SIP as site G on the opposite side. In addition, both sites were expected to be less directly influenced by port activity.
3.5 Field Sampling
Field sampling was conducted in 2011 and 2012. The sampling plan was as follows:
a) First Phase of fieldwork in 2011
February – April 2011:
In this period, field sampling was conducted for the analysis of heavy metals.
b) Second Phase of fieldwork in 2012
February – April 2012:
In this period, field sampling was conducted for the analysis of both heavy
metals and anions.
66
This research focused on evaluating heavy metals and anions in surface sediment, to investigate the influence of the SIP and the anthropogenic sources in the investigated area. The information on the most recently deposited sediment materials was obtained from the surface layer and should be used to determine the horizontal variation in sediment properties and the distribution of contaminants (Simpson et al; 2005). Surface samples were collected from seven sites during low tide at tidal zone to avoid the mixing of sediment layers and sea water during sampling
(Taillefert et al., 2007). Sampling sites were located in the core port area and the surrounding areas, as explained in section 3.4. The total number of samples collected was 45, with five at each site except for site A where 15 samples were collected. This number of samples was chosen to provide a comparable number of samples to the east and west locations: therefore the number of samples was proportional to each site area. The sampling locations east and west of the port were selected to provide a good representation of potential contamination arising from the port.
Sampling periods were from February to April, towards the end of a non-intensification of a cyclonic eddy period to avoid the predominant south-easterly seawater flow along the north-east coast of Oman, in case nutrients and sediments may reach the site and change the sedimentation process, and which may therefore not represent the real local levels of pollutants. The regions south and east of Sohar the process of sedimentation due to cyclone is happening during monsoon period (Johns et al., 1999). Fifteen samples within the port area, fifteen samples to the west (five samples at each site – B, C and D) and fifteen samples to the east (five samples at each site – E, F and G) was deemed a sufficient number to determine contamination levels. Figure 3.8 shows the location of the sampling sites used in the study.
67
Sediment samples were collected within the intertidal zone during low tides, using a plastic sampling scoop. The samples were rinsed with sea water from the same site at which the sample was collected, then washed each time by Nitric acid (10%), and finally washed with distilled water to avoid any contamination and the mixing of samples with other samples from different sites.
Samples were stored in plastic bags, placed on ice and transported to the laboratory within 3 hours of collection. Samples were stored in the dark at 4˚C (ASTM, 2000a; USEPA, 2001;
Simpson et al; 2005). Sampling procedures were according to USEPA (3050B) (USEPA, 1996).
All samples were placed in an oven at 60-100 °C for 24-48 hours. The dried samples were removed from the oven and put in analytical sieve shakers ―Vibratory Sieve Shaker – analysette
3 from FRITSCH‖ to obtain different fractions. The reason for using the sieve process is to remove large materials such as rocks, shells, debris, and wood ˃ 2mm which could affect analysis, looking for sediment size fractions and to remove organisms (Simpson et al., 2005:).
Figure3.9 shows the sieve process. All sieve plates were cleaned thoroughly with double distilled water and dried. In this study the fraction of sediments to be analyzed was 63= d ˂
125µmportion.
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Figure3-9: Sieve Process continued
69
3.6 Chemical preparation for Heavy Metals
3.6.1 Microwave digestion and samples preparation for Inductively Coupled Plasma
Optical Emission Spectrometer (ICP-OES)
1gm. of sediment samples was weighed using an analytical balance (Cubis, Sartorius, UK).
Samples were digested with 5 mls. of concentrated nitric acid (70% HNO3) and 1 ml. of 30%
H2O2 in a Teflon bomb. All digestion bombs were securely closed and placed on the rotor of a microwave oven (Milestone 1200 MDR, USA) and heated to 200oC for about 20 minutes.
Samples were left to cool, filtered through glass micro-filters into 25 mls volumetric flasks, with double distilled water then added to make the sample volume up to 50 mls. The concentrations of fifteen heavy metals (Al, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, V, Zn, Hg, As and Sn) were determined using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES, type Perkin Elmer 3300 DV ICP (USA)).
All chemicals and solutions used in this study were of analytical reagent grade purchased from
Sigma-Aldrich Chemicals, USA, and Merck, UK.
Results have been reported as parts per million (ppm) and the detection limit of the ICP method used is in the order of 0.1-0.5 parts per million (ppm).
70
3.6.2 Using ICP-OES
The accuracy of the analysis was checked using Blanks (ICP multi-element celebration standard solutions IV (Merck-111355) and XIII (Merck-109480)) and certified reference materials
(CRMs) obtained from the Marine Environment Laboratory (MEL-IAEA) in Monaco and the
Laboratory of the Government Chemists (LGC) in the UK.
As a standard procedure, the standards were run just prior to the samples, and the percentage recovery values in the average of 8 determinations were calculated as a minimum 91% and maximum 107% for all elements, and the results were accepted when the coefficient of variation was within 5%. The continuity calibration test was used to ensure the validity of the calibration throughout the analysis run and carried out at a frequency of every 10 analytical samples. For quality assurance, the accuracy was also checked by performing Inter-Element Correction (IEC).
3.6.3 ICP-OES Running and Analyzing
Operation of the ICP was according to standard procedure as per the manufacturer, or USEPA procedures. A series dilution experiment consisted of a five-fold dilution of each sample. The diluted results were then compared with the original undiluted results, and the results had to agree within ± 5% .Samples was run 3 times and the mean value was taken for the analysis of results.
71
3.7 Sample Analysis for Anions – Ion Chromatography (IC)
Ion chromatography is an appropriate method for the analysis of water soluble anions from sediment samples (Jackson, 2000).In this research, the sample were passed through an ion exchange column where anions interact with the ion exchange sites on the stationary phase in the column. Mobile phase ions (or eluent ions) compete with sample ions for ion exchange sites on the column that separates the ions. Once ions are separated the concentration of each ionic species present in the sample is measured using an electrical conductivity detector. This produces a chromatogram that can be used to identify the concentration of the ions, using peak height or peak area (Khwaja et al., 1999).
These samples were ionized using a Metrohm Professional Compact Ion Chromatography system 881 and Metrohm 858 Professional Sample Processor with conductivity detector and packed bed suppressor. Inorganic anions of fluoride, chloride, bromide and sulphate were analysed with Metrohm Column -Metrosep A Supp 5 250/4.0 with Guard Column, Suppressor
Regenerating Agent: 50 mM / Litre Sulphuric Acid and 18 MOhm ultrapure Deionised Water.
The eluent solution used was 3.2mM Na2CO3 + 1.0mM NaHCO3 at a flow rate of 0.7ml/min. A series of mixed standard solutions was prepared in the laboratory from stock standard solutions
(Fluka) to establish calibration curves.
72
3.7.1 Sample Extraction
Ultra sonication is commonly used to extract water soluble anions and cations using distilled water. The sediment samples of given weight were extracted with a given volume of ultrapure water (Khwaja et al., 1999; Karim et al., 2008).
The pH of the samples was first measured and then the samples were extracted. To extract, these sediment samples were first weighed into 2.0 - 2.2gms.in 25 mls. conical skirted base screw capped polypropylene tubes.20mls. of ultrapure water (18 MOhm) was added and ultrasonicated for 1 hour to extract the anions from the sediments. Then the samples were filtered through 45um
Nylon Syringe filters (VWR chemicals supplier).
3.7.2 Eluent and regeneration solutions &Demonized water
Eluent Solution: 3.2 mM Sodium Carbonate (Na2CO3) + 1.0mM Sodium Bicarbonate
(NaHCO3): Sodium Carbonate (VWR Chemicals Annular: 98.0% (purity)); Sodium Carbonate
(VWR Chemicals Annular: 99.0% (purity)).
3.7.3 Preparation of Eluent
i. 678.4 mgs. Na2CO3 &168 mgs. of NaHCO3 were dissolved in 2 Litres of deionised
ultrapure water.
ii. Regenerating Agent: 50 mM / Litre Sulphuric Acid (Honeywell Specialty Chemicals,
analytical grade). iii. Deionised Water: 18 MOhm water (SG Ultrapure Water System, Germany).
73
3.7.4 Preparation of standard solutions
Four standard solutions of different anion concentrations were prepared from certified standards
(Fluka). Results have been reported as part per million (ppm) and the detection limit of the IC method used is in the order of 0.01-0.03 parts per million (ppm).
3.8 Statistical analysis
Data were analyzed using a factorial design analysis of variance (ANOVA) using the SPSS package and presented as means ± standard errors. Comparisons were made between sites and between years using least significant differences (LSD) at level P<0.05. Correlations between metals at sites were made using SPSS Bivariate Correlation. Compilation of data was into suitable graphs or tables. For graphics, Microsoft Excel 2010 was used.
74
Chapter Four Results
75
4 Chapter 4: Results 4.1 Introduction
This chapter is designed to present the results from the study sample sites (A, B, C, D, E, F& G) at the SIP and surrounding sites during 2011 and 2012. It has been divided into the following three sections:
i. Contamination levels of sediments at Sohar Industrial Port (SIP) and the surrounding
area (section 4.2)
ii. Statistical analysis of monitored data using SPSS analysis; Spearman's
rhocorrelations, ANOVA (section 4.3) iii. Discussion of the results from this study in relation to International Sediment Quality
Guidelines standards (ISQGs) (section 4.4) iv. Conclusion (4.5)
76
4.2 Contamination levels of sediments at Sohar Industrial Port (SIP) and the
surrounding area
4.2.1 Pollutant data in 2011 and 2012
The results of assessment of the regional distribution of heavy metals in 2011 and 2012 are shown in figures 4.1-4.15. The results indicated that the concentrations of Al, Cd, Cu, Fe, Mo Ni,
Zn, As and Sn are identified as significantly higher (P<0.05) at the Port (site A). Iron and Zn are only high at the port, while all other sites have a low mean of concentrations. Cadmium and As indicate what appears to be a gradient of reducing values in both directions away from the Port, whereas Al only shows this gradient to the east from the port, with all western sites having the same low values, which is comparable to the eastern side as seen for the Zn results. These patterns suggest that the Port represents a probable source for these metals, as the higher results are at the Port.
There are notably low values at Site B for Al, Co, Cr, Fe and Mo, and at Site D for Zn and Cd as well, compared to all other sites. The beach at Site B, Harmul, is relatively young being formed at the front of an extensive dredge spoil disposal site built up from the dredging of the small utilities port to the immediate west of the main port during 2006. This beach is also close to a major drainage outlet at the port‘s boundary which captures water and sediment from two wadis that extend immediately inland to the south of the Port. For certain metals (Co and V) the site which has the highest mean concentrations compared to other sites is the site E. For Cr sites E and F have comparably the highest mean concentrations. It is surprising that Pb has higher concentrations to the East (Site G as control site during 2011and Site F during 2012) of the SIP,
77 which is just west of a major wadi outlet and closest to the rapidly growing city of Sohar. It is possible that the runoff from the city of Sohar has some effect on the concentration of Pb. The results of Ni, Hg, Mn and Cr have no distinct patterns that may reflect a point source such as the
Port, geological causes or a wadi, but do show variability between sites.
Aluminum, Cd, Cu, Fe, Mo, Ni, Zn, As and Sn have higher mean concentrations in the port than in the coastal region which might be related to the issue of industrial discharge and geo-sourcing in the site during the construction of the port.
900.0
800.0
700.0
600.0
500.0 2011 ppm 400.0 2012 300.0
200.0
100.0
0.0 D C B A E F G
4-1: Mean and standard error (S.E.) of Al concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
78
4.00
3.50
3.00
2.50
2.00 2011 ppm 2012 1.50
1.00
0.50
0.00 D C B A E F G
Figure 4-2: Mean and standard error (S.E.) of Cd concentrations at each sample site showing the variation between sites in 2011& 2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
160.0
140.0
120.0
100.0
80.0 2011 ppm 2012 60.0
40.0
20.0
0.0 D C B A E F G
Figure 4-3: Mean and standard error (S.E.) of Co concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
79
800.0
700.0
600.0
500.0
400.0 2011 ppm 2012 300.0
200.0
100.0
0.0 D C B A E F G
Figure4-4: Mean and standard error (S.E.) of Cr concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
400.0
350.0
300.0
250.0
200.0 2011 ppm 2012 150.0
100.0
50.0
0.0 D C B A E F G
Figure4-5: Mean and standard error (S.E.) of Cu concentrations at each sample site showing the variation between sites in 2011& 2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
80
800.0
700.0
600.0
500.0
400.0 2011 ppm 2012 300.0
200.0
100.0
0.0 D C B A E F G
Figure4-6: Mean and standard error (S.E.) of Fe concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
700.0
600.0
500.0
400.0
2011 ppm 300.0 2012
200.0
100.0
0.0 D C B A E F G
Figure4-7: Mean and standard error (S.E.) of Mn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
81
6.0
5.0
4.0
3.0 2011 ppm 2012 2.0
1.0
0.0 D C B A E F G
Figure4-8: Mean and standard error (S.E.) of Mo concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
800.0
700.0
600.0
500.0
400.0 2011 ppm 2012 300.0
200.0
100.0
0.0 D C B A E F G
Figure4-9: Mean and standard error (S.E.) of Ni concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
82
120.0
100.0
80.0
60.0 2011 ppm 2012 40.0
20.0
0.0 D C B A E F G
Figure4-10: Mean and standard error (S.E.) of Pb concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
160.0
140.0
120.0
100.0
80.0 2011 ppm 2012 60.0
40.0
20.0
0.0 D C B A E F G
Figure4-11: Mean and standard error (S.E.) of V concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
83
250.0
200.0
150.0
2011 ppm 100.0 2012
50.0
0.0 D C B A E F G
Figure4-12: Mean and standard error (S.E.) of Zn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
12.0
10.0
8.0
6.0 2011 ppm 2012 4.0
2.0
0.0 D C B A E F G
Figure4-13: Mean and standard error (S.E.) of Hg concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
84
60.0
50.0
40.0
30.0 2011 ppm 2012 20.0
10.0
0.0 D C B A E F G
Figure4-14:Mean and standard error (S.E.) of As concentrations at each sample site showing the variation between sites in 2011 &2012.The number of samples in site A is 15, and the number of samples on other sites is 5.
30.0
25.0
20.0
15.0 2011 ppm 2012 10.0
5.0
0.0 D C B A E F G
Figure4-15: Mean and standard error (S.E.) of Sn concentrations at each sample site showing the variation between sites in 2011&2012. The number of samples in site A is 15, and the number of samples on other sites is 5.
85
4.2.2 Pollutant data at SIP
The pH for sediment samples at site A (port) range from 7.44 to 9.07. The results of mean, minimum, and maximum values of concentration of heavy metals and standard errors for site A
(SIP) during 2011 and 2012 are presented in Table 4.1.
The table shows that the minimum value of Al in 2011 is 102.2ppm and the maximum is
1351.3pmm with a mean of 746.7 ppm. However, in 2012 the mean decreased to 619.1ppm a decrease of 17% with an increase in minimum value to 241 ppm but at the same time the maximum value decreased to 857ppm. Cadmium ranged from 1.5ppm to 6.5ppm in 2011, while it slightly decreased in 2012 ranging from 1.2ppm to 5.1ppm, a decrease of 21.7 %. Moreover, there was a general decrease in the concentrations of Al, Fe, Ni, Mn, Cr, Cu and Cd in 2012 compared to 2011 with percentages of 17%, 13.3%, 10.5%, 20.3%, 20.1%, 9.6% and 21.7% respectively (see Figures 4.16, 4.17& 4.18). On the other hand, there was an increase in the concentrations of Zn, V, Pb, Co, As, Sn, Hg, and Mo in 2012 with percentages of 4.153%,
13.19%, 59.58%, 6.743%, 13.76%, 188.0%, 21.13%, and 21.62%respectively (see Figures
4.17&4.18). Figure 4.16 show the mean concentrations and standard error figures of Al, Fe, Ni,
Mn, Cr and Cu at the SIP in 2011 compared to 2012. The general trend of the result of figure
4.16 shows a decrease in 2012 compared with 2011. In figures 4.17 &4.18result shows a mixed trend; an increase in 2012 compared with 2011 for all heavy metals except for Cd in figure 4.18.
86
Table 4-1:Minimum and Maximum value, mean value of heavy metals (ppm), and standard errors within the SIP 2011& 2012 with total sample size of 15.
Heavy Metals Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn
Parameter Sohar Industrial port (SIP) 2011 Min 102.1 1.50 19.40 215.8 215.8 463.6 410.5 2.80 356.2 16.50 38.90 123.9 3.70 19.50 2.40 Max 1351 6.50 73.90 517.3 517.4 1036 771.3 5.80 1016.4 87.60 142.4 255.0 13.50 74.20 25.40 Mean 746.7 3.40 44.50 355.4 348.6 715.1 504.7 3.70 683.8 38.90 75.80 187.80 7.10 40.70 8.90 SE 82.30 0.30 4.20 22.90 24.10 41.80 33.90 0.30 49.0 4.80 6.90 13.20 0.70 3.90 2.10 Sohar Industrial port (SIP) 2012 Min 241.0 1.200 16.70 146.7 213.5 312.5 274.9 1.80 295.9 29.70 37.10 85.20 3.40 22.50 13.50 Max 857.0 5.100 68.40 435.7 411.5 856.4 527.3 7.40 1022.3 121.5 163.8 275.3 15.70 78.30 41.60 Mean 619.1 2.900 47.50 284.1 315.2 619.7 402.0 4.50 611.9 61.60 85.80 195.6 8.60 46.30 25.60 SE 48.00 0.30 3.60 24.70 15.40 43.40 23.90 0.40 53.80 6.60 10.00 18.70 0.80 3.70 2.20
87
900.00
800.00
700.00
600.00
500.00 Mean 2011
ppm 400.00 Mean 2012 300.00
200.00
100.00
0.00 Al Fe Ni Mn Cr Cu
Figure4-16: The mean concentration and standard error (SE) of Al, Fe, Ni, Mn, Cr and Cu at the SIP in 2011 compared to 2012
250.00
200.00
150.00
Mean 2011 ppm 100.00 Mean 2012
50.00
0.00 Zn V As Pb Co
Figure 4-17: The mean concentration and standard error (SE) of Zn, V, As, Pb and Co at the SIP in 2011 compared to 2012
88
30.00
25.00
20.00
15.00 Mean 2011 ppm Mean 2012 10.00
5.00
0.00 Sn Hg Mo Cd
Figure 4-18: The mean concentration and standard error (SE) of As, Sn, Hg, Mo, and Cd at the SIP in 2011 compared to 2012
4.2.3 Pollutant data at west and east of the port
The pH for sediment samples to the west of the port (sites B, C& D) ranges from 8.10- 8.95. The results of mean, minimum and maximum values of concentration of heavy metals and standard errors for west of the port (B, C and D) during 2011 and 2012 are presented in Table 4.2. The table shows that the minimum value of Al in 2011 in site B is 87.6 ppm and the maximum is
245.5 ppm with mean 138.4 ppm while, the minimum value of Al in 2011 in site C is 41.8 ppm and the maximum is 364.2 ppm with mean 178.2 ppm. However, the minimum value of Al in
2011 in site D is 158.9 ppm and the maximum is 521.5 ppm with mean 338 ppm. However, in
2012 the mean concentration of Al increased to 204.4 ppm (47.69 %) and to 220.4 ppm (23.68
%) in sites B and C respectively. On the other hand, the mean concentration of Al decreased to
280 ppm with 17.2.31% in site D. The mean concentration of cadmium in all sites increased in
89
2012 with increases of 20.00%, 5.882%, and 14.29% for sites B, C and D respectively.
Moreover, there was a general decrease in the concentrations of Al (site D 17.20%), Co (site B
11.44% and C 13.61%),Cr (site C 16.48% and D 10.53%), Ni (site B 17.57% and D 8.745%), V
(site C 32.94%), Zn (site C 5.357% and D 12.63%), Hg (site D 2.17%), As (site B 8.52%) and Sn
(site B20% and C 3.75%) in 2012 compared to 2011. On the other hand, there was an increase in the concentration of Al (site B 47.69 %and C 23.68 %), Cd (site B 20.00%, site C 5.882% and site D 14.29% ), Co (site D 14.30%), Cr (site B 47.87%), Cu (site B 18.29%, site C 23.95% and site D 15.91%), Fe (site B 146.4.5%, site C 31.50% and site D 14.41%), Mn (site B 20.59%, site
C 47.26% and site D 0.2268%), Mo (site B 53.85%, site C 38.46% and site D 17.24%),
Pb (site B 20.38%, site C 84.64% and site D 33.94%), V (site B 34.70% and D 17.33%),
Zn (site B 25.81%), Hg (sit B 24.44% and C 23.61%), As (site C 22.70% and D 33.67%) and Sn
(site D 39.32%) in 2012.
These changes over time in the west of the SIP are due to this area being the main gateway for shipping which was close to the west monitoring location (site B). In addition, the distribution of heavy metals to the surrounding area is related to waves and wind (see chapter 5 in more details).
90
Table 4-2:Minimum and Maximum value, mean value of heavy metals (ppm) , and standard errors at the West of the port 2011& 2012 with sample size of 15.
Heavy Metals Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn
Site Parameter s West of the port 2011 Min 87.60 0.50 10.40 56.80 94.20 51.60 263.2 0.40 482.3 19.10 47.60 19.30 2.60 14.70 6.90 Max 245.5 3.60 34.60 165.3 281.4 142.4 612.5 1.90 822.3 42.10 100.3 40.60 6.90 35.70 14.20 B Mean 138.4 2.00 20.10 98.80 200.7 91.30 442.7 1.30 657.5 31.40 68.30 31.50 4.50 26.30 10.10 SE 28.70 0.60 4.60 18.80 32.80 16.10 63.30 0.30 63.30 4.20 8.90 4.10 0.70 4.10 1.30 Min 41.80 1.20 3.00 278.4 57.40 254.6 183.5 0.60 228.5 15.80 22.80 36.80 4.70 9.40 4.20 Max 364.2 2.30 98.30 548.4 171.3 371.4 311.4 2.20 520.4 44.20 81.40 83.20 12.80 25.70 12.30 C Mean 178.2 1.70 52.90 425.4 112.3 292.2 237.3 1.30 380.8 30.60 51.00 56.40 7.20 16.30 8.00 SE 60.10 0.20 15.50 52.00 19.40 23.40 23.10 0.30 52.70 5.70 10.90 8.40 1.50 2.90 1.40 Min 158.9 0.50 47.90 178.3 165.3 175.2 327.8 2.00 259.3 12.40 51.40 11.40 2.70 6.20 9.90 Max 521.5 1.20 104.0 451.3 459.1 291.3 562.9 4.30 517.9 50.40 99.10 34.50 7.30 15.20 14.40 D Mean 338.0 0.70 74.80 304.8 282.8 222.0 441.3 2.90 411.7 27.40 73.90 19.80 4.60 9.80 11.70 SE 76.10 0.10 9.50 48.80 51.30 21.90 37.60 0.40 44.00 6.80 8.70 4.00 0.80 1.70 0.80 West of the port 2012 Min 96.00 1.10 11.80 79.50 162.4 121.5 293.5 1.30 372.6 23.70 81.80 17.70 3.20 12.60 5.40 Max 292.0 3.40 24.60 213.2 316.8 388.4 710.4 2.70 725.2 61.40 129.4 76.30 8.20 34.90 12.50 B Mean 204.4 2.40 17.82 146.1 237.4 225.5 533.9 2.02 5420 37.8 92.00 39.70 5.66 24.06 8.08 SE 34.59 0.60 2.60 40.30 32.00 45.50 73.40 0.30 67.50 6.50 11.20 10.40 0.80 4.10 1.30 Min 154.0 1.30 27.60 246.5 105.7 322.6 274.6 0.90 341.5 31.6 18.50 41.30 7.40 11.30 11.4 Max 325.0 2.70 76.80 477.6 199.1 469.8 466.2 2.80 520.1 82.6 49.20 62.60 11.90 32.40 11.6 C Mean 220.4 1.88 45.72 355.3 139.2 384.4 349.4 1.82 427.1 56.5 34.26 53.40 8.90 20.08 7.70 SE 31.29 0.22 8.40 40.30 19.00 26.10 33.80 0.40 33.40 9.00 6.00 3.80 0.90 4.20 1.30 Min 177.0 0.40 63.70 187.4 236.9 168.4 382.1 2.30 235.8 17.40 62.70 9.50 2.80 7.20 9.40 Max 380.0 1.40 108.5 328.9 392.4 352.4 573.2 4.60 571.4 62.80 108.5 27.50 6.10 19.40 26.20 D Mean 280.0 0.82 85.52 239.6 327.8 254.2 442.4 3.42 377.9 36.76 87.02 17.30 4.50 13.14 16.38 SE 39.98 0.12 7.80 24.50 30.40 34.30 34.50 0.50 59.00 8.20 7.70 3.20 0.60 2.00 2.80
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The pH for sediment samples in the east of the port (sites E, F &G) ranges from 7.98- 8.85. The results of mean, minimum, and maximum values of concentration of heavy metals and standard errors for west of the port (E, F and G) during 2011 and 2012 are presented in Table 4.3. The table shows that the minimum value of Al in 2011 in site E is 427.8 ppm and the maximum is
694.2 ppm with mean 558.4 ppm while the minimum value of Al in 2011 in site F is 394.3 ppm and the maximum is 612.4 ppm with a mean of 495 ppm. However, the minimum value of Al in
2011 in site G is 124.5 ppm and the maximum is 284.3 ppm with a mean of 211.5 ppm.
However, in 2012 the mean concentration of Al decreased to 297.2 ppm (46.78%) and to 354.8 ppm (28.32%) and 171.2 ppm (19.05%) in sites E, F and G respectively. The mean concentration of Cu in all sites increased in 2012 with increases of 36.57%, 17.31% and 18.89% for sites E, F and G respectively. Moreover, there was a general decrease in the concentration of Al (site E
46.78%, site F 28.32% and site G 19.05%), Cd (site E 22.4% ),Co (site E 18.87%), Cr (site E
27.48%, site F 22.55% and site G 17.95%), Fe (site E 12.25%), Mn (site F 9.2%), Mo (site F
7.69%), Ni (site E 12.23%, site F 28.17% and site G 24.11%), Pb (site G 22.66%), V (site F
23.64% and site G 30.11%), Zn (site F 7.005% and G 8.852%), Hg (site F 1.333%), and Sn (site
F 13.72%) in 2012 compared to 2011. On the other hand, there was an increase in the concentration of Cd (site F 5.882%, site G 1.818%), Co (site F 22.54% and G 4.787%), Cu (site
E 36.57%, site F 17.31% and site G 18.84%), Fe (site F 77.54%, site G 29.01%), Mn (site E
50.84% and site G 28.16%), Mo (site E 60.00%, site G 20.00%), Pb (site E 26.10% and site F
88.46%), V (site E 21.92% ), Zn (site E 34.69%), Hg (sit E 12.57% and G 81.74%), As (site E
57.56% and F 4.314% and site G 6.42%) and Sn (site E 60.88% and site G 57.94%) in 2012.
East of the SIP is affected by different sources such as discharge of wastewater from the SIP itself, Wadi Al Jizi, local industrial area and urban activity. Therefore, these differences in
92 results in the east of the SIP are due to the influence of anthropogenic sources and geochemical sources which transported by wadi, wind and waves. This is give good indication that the level of transportation of materials from core areas to adjacent areas is higher (see chapter 5 in more details).
93
Table 4-3: Minimum and Maximum value, mean value of heavy metals (ppm), and standard errors at the East of the port, 2011& 2012 with sample size of 15.
Heavy Metals Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn
Site Parameter East of the port 2011 Min 427.8 1.70 79.40 477.9 42.70 258.5 64.80 0.90 277.2 15.40 84.20 37.20 1.40 14.70 8.20 Max 694.2 3.80 163.5 683.1 153.7 533.8 165.8 2.40 523.5 54.70 135.9 79.50 5.30 26.30 19.40 E Mean 558.4 2.50 118.9 565.2 96.80 372.9 112.5 1.50 384.9 33.10 109.5 59.50 3.50 18.90 14.00 SE 50.90 0.40 14.80 45.20 19.00 48.30 21.70 0.30 46.20 7.50 10.90 8.30 0.70 2.20 1.80 Min 394.3 1.30 21.50 348.9 72.40 105.6 247.3 1.80 411.8 23.80 25.80 30.90 4.20 7.30 5.70 Max 612.4 2.30 73.90 826.4 247.2 262.6 462.9 3.50 782.9 68.40 61.30 52.30 8.70 14.60 11.70 F Mean 495.0 1.70 46.50 579.6 150.2 177.2 346.4 2.60 632.3 46.80 40.60 41.40 6.00 10.20 8.60 SE 42.50 0.20 9.80 98.20 30.40 27.50 38.90 0.30 65.00 8.20 6.10 3.60 0.80 1.30 1.00 Min 124.5 0.60 17.80 260.4 53.70 137.5 73.50 0.70 651.6 42.70 25.50 20.50 2.80 4.20 8.40 Max 284.3 1.60 49.60 403.5 231.6 314.6 158.3 2.10 691.5 103.2 56.30 67.90 6.80 11.70 16.30 G Mean 211.5 1.10 30.50 328.2 140.8 205.1 114.0 1.40 627.5 70.60 42.10 41.80 4.60 8.10 13.60 SE 26.20 0.20 5.60 24.90 30.50 31.80 16.10 0.20 30.40 10.30 5.10 7.90 0.70 1.20 2.80 East of the port 2012 Min 188.0 0.70 64.80 242.6 76.80 250.2 82.40 1.50 268.3 18.50 92.80 53.70 1.80 22.60 13.70 Max 402.0 3.10 124.8 518.4 216.7 426.8 311.5 3.80 502.6 66.20 167.4 114.7 6.30 45.10 31.70 E Mean 297.2 1.94 96.46 409.9 132.2 327.2 169.7 2.40 337.8 41.74 133.5 80.14 3.94 29.78 22.52 SE 40.08 0.35 10.20 48.50 23.50 29.50 44.20 0.40 42.60 9.10 13.20 10.30 0.80 4.00 3.20 Min 217.0 1.10 33.80 259.3 134.8 226.4 199.3 1.60 328.3 56.20 14.80 21.60 3.70 5.80 3.20 Max 485.0 2.40 73.50 642.8 210.4 406.5 384.8 3.30 621.3 138.4 43.8 64.70 8.60 14.20 10.80 F Mean 354.8 1.80 56.98 448.9 176.2 313.9 314.4 2.40 454.2 88.20 31.00 38.50 5.92 10.64 7.42 SE 45.03 0.17 8.10 66.00 15.90 33.20 34.50 0.30 52.80 13.60 4.90 7.60 0.90 1.50 1.20 Min 74.00 0.60 19.50 273.1 114.2 205.6 101.5 0.70 317.2 36.20 20.60 15.30 3.90 3.60 14.60 Max 247.0 1.70 53.40 307.4 263.7 311.2 214.7 2.40 702.5 78.50 37.50 61.40 12.5 16.10 32.10 G Mean 171.2 1.12 31.96 269.3 167.4 264.6 146.1 1.68 476.2 54.60 29.42 38.10 8.36 8.62 21.48 SE 33.20 0.18 5.90 19.80 26.80 18.80 19.00 0.30 64.70 7.40 3.20 8.00 1.50 2.10 3.00
94
4.2.4 Pollutant data at all sites in 2011 & 2012
The comparison of the mean sediment concentrations of the heavy metals in 2011 are presented in Figures 4.19, 4.20 & 4.21. Itshows the first seven elements in descending order of concentrations at the Port compared to the overall mean concentrations to the East and West of the Port. It shows that the mean concentrations of Al, Fe, Ni, Mn, Cu and Zn are highest in the port compared to overall concentrations to the east and west of the port, with Cr being an exception as it is highest to the east of the port. This indicates that SIP might be one of the sources of these trace elements due to the fact that the site is in the vicinity of industrial activities including petrochemicals and metals factories. Moreover, copper mining occurs close to the SIP and its surrounding site. Additionally, figure 4.20 presents the mean concentrations of V, Co, Pb and As. The levels of Co and Pb are higher to the east of the port than they are to the west and at the port itself. While V and As are highest in the port, compared to east and west of the port. The mean concentrations of Hg, Sn, Mo and Cd are demonstrated in figure 4.21. It is clear that the port has high mean concentrations of Hg, Mo and Cd, while east of the port has the high Sn concentration. East of the port is closer to the port‘s outfall discharge, and there is also wadi passing through - Wadi Al Jizi- where mining sites are located. In addition, this wadi system also passes through the local industrial site, which might increase the deposition and concentration of these elements in the water system and eventually into coastal waters and sediments. It is therefore not surprising to find that the levels of Cr, Co, Pb and Sn are highest to the east of the port compared with the port site itself (see chapter 5 for more details).
95
900.0 800.0 700.0 600.0 500.0
400.0
ppm 300.0 200.0 100.0
0.0
East East East East East East East
Port Port Port Port Port Port Port
West West West West West West West Al Fe Ni Mn Cr Cu Zn
Figure4-19:Mean sediment concentrations in 2011of Al, Fe, Ni, Mn, Cr, Cu, and Zn in descending order of concentration at the port compared to the means at the sites to the east and west of the Port. Error bars are for the Standard Error to the mean with n=15
90.0 80.0 70.0 60.0 50.0
40.0
ppm 30.0 20.0 10.0
0.0
East East East East
Port Port Port Port
West West West West V Co Pb As
Figure 4-20: Mean surface sediment concentrations in 2011 of V, Co, Pb and As in descending order of concentration at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15
96
16.0
14.0
12.0
10.0
8.0
6.0 ppm 4.0
2.0
0.0
East East East East
Port Port Port Port
West West West West Hg Sn Mo Cd
Figure 4-21: Mean surface sediment concentrations in 2011 of Hg, Sn, Mo and Cd in descending order of concentrations at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15
Figures 4.22, 4.23 & 4.24 shows the comparison between mean sediment concentrations in 2012 of the heavy metals at the Port compared to the means at the sites to the east and west of the port.
It shows that the concentrations of Al, Fe, Ni, Cu, Zn, V, Pb, As, Hg, Sn, Mo and Cd are highest in the port compared to east and west of the port. The comparative data clearly shows that there was an increase in Pb concentration at the Port from 38.9 ppm in 2011 to 61.6 ppm in 2012, an increase of 61.68%. In 2011, Pb was higher in the east but in 2012 it observed highest at the port.
This clearly demonstrates that the port is one of the sources of Pb contamination in the site. It contains a number of different petrochemical and metal factories and companies which could be a source of Pb. It is also possible that high numbers of automobiles and trucks moving within the port are causing additional pollution of the Pb from leaded gasoline or diesel from their exhausts
(see chapter 5 in more details).
97
The same applies for Sn concentrations: it was higher in 2011 to the east of the port, while in
2012 it becomes higher within the port. The comparative data in figure 4.24 clearly demonstrate that there was an increase in Sn concentrations in the port from 8.9 ppm in 2011(figure 4.21) to
25.63 ppm in 2012, an increase of 188.0%. On the other hand, the comparison (figure.4.22) shows that the mean concentration of Mn in the port decreased in 2012 to 402 ppm compared to
504.7 ppm in 2011. In fact, it could have been expected that Mn would increase in the port due to the previously mentioned sources of contamination. Further investigation is needed to study the input of the industries at the SIP and mining process. By contrast, Mn increased to the west of the port in which it was 373.8 ppm in 2011 and increased to 441.8 ppm in 2012, making it even higher than in the port itself. Additionally, the mean concentration of Ni decreased in almost all sites with the exception of the west where there was a slight increase probably due to the effects wadi runoff which passing through mining area as well from natural sources from the Al Hajar
Mountain. However, it is still highest within the port. Moreover, Figures 4.22 & 4.23 demonstrates that the mean concentrations of Cr and Co remained at the same level in both years, in which they were higher to the east of the port. Generally, from figures 4.19, 4.24, the mean concentrations of Al, Fe, Ni, Cu, Zn, V, As, Hg, Mo and Cd are highest at the port rather than west or east of the port in both 2011 and 2012. However, the mean concentrations of Cr, Co and Pb are highest to the east of the port in both 2011 and 2012; the mean concentration of Mn in
2011is highest at the port, while in 2012 it is highest to the west of the port; and Sn is highest to the east of the port in 2011, but is higher in the port in 2012.
As described earlier, the port is one of the main sources of heavy metals contamination where various petrochemical industries and metal factories are found. It is also possible that road transportation within the port area is causing additional pollution of some heavy metals as
98 reported elsewhere (USEPA, 2002) that the urban runoff are roadways and automobiles are the sources of heavy metals pollution including of Pb, Zn, Cd, Cu, Fe, Ni, Mn and Cr from leaded gasoline or diesel from their exhausts (see chapter 5 in more details).
The location of the sites in the west and east of the port is closer to the port‘s outfall discharge and affected also by wadi system which passing through - Wadi Al Jizi- where mining sites are located and as well as local industrial site where wadi is passing to the east of the SIP. (See chapter 5 for more details).
800.0
700.0
600.0
500.0
400.0
300.0 ppm
200.0
100.0
0.0
East East East East East East East
Port Port Port Port Port Port Port
West West West West West West West Al Fe Ni Mn Cr Cu Zn Figure4-22: Mean sediment concentrations in 2012of Al, Fe, Ni, Mn, Cr, Cu and Zn in descending order of concentration at the port compared to the means at the sites to the east and west of the Port. Error bars are for the Standard Error to the mean with n=15
99
100.0 90.0 80.0 70.0 60.0
50.0
40.0 ppm 30.0 20.0 10.0
0.0
East East East East
Port Port Port Port
West West West West V Co Pb As
Figure 4-23:Mean surface sediment concentrations in 2012 of V, Co, Pb and As in descending order of concentration at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15
30.0
25.0
20.0
15.0
ppm 10.0
5.0
0.0
East East East East
Port Port Port Port
West West West West Hg Sn Mo Cd
Figure 4-24: Mean surface sediment concentrations in 2012 of Hg, Sn, Mo and Cd in descending order of concentrations at the port compared to the means at the sites to the east and west of the port. Error bars are for the Standard Error to the mean with n=15
100
4.2.5 Concentrations of anions at all sites in 2012
- - - 2- The inorganic anions Fluoride (F ), Chloride (Cl ), Bromide (Br ) and Sulphate (SO4 ) were analyzed in sediment samples in 2012 in the port and at three sites both east and west of the port.
- - - 2- Figures 25-28 show the concentration of anions F , Cl , Br and SO4 . The mean concentrations of F- to the east and west of the port are higher than at the port. It was observed that when moving towards the port from the west and from the east the concentration of F- increases, and
- 2- while site G has the highest value. Site D has the highest mean concentration of Cl and SO4 the port has it for Br-. It is surprising that both control sites (D & G) have the highest mean
- - 2- concentrations of F (site G), Cl and SO4 (site D).
0.4
0.35
0.3
0.25
0.2 ppm 0.15
0.1
0.05
0 D C B A E F G
Figure4-25: Mean concentration and standard error (S.E.) of F- concentrations at each sample site showing the variation between sites. The number of samples at site A is 15, and the number of samples on other sites is 5
101
700
600
500
400
ppm 300
200
100
0 D C B A E F G
Figure4-26: Mean concentration and standard error (S.E.) of Cl- concentrations at each sample site showing the variation between sites. The number of samples at site A is 15, and the number of samples on other sites is 5
2.5
2.0
1.5
1.0 ppm
0.5
0.0 D C B A E F G
Figure4-27: Mean concentration and standard error (S.E.) of Br - concentrations at each sample site showing the variation between sites. The number of samples at site A is 15, and the number of samples on other sites is 5
102
90.0
80.0
70.0
60.0
50.0
40.0 ppm 30.0
20.0
10.0
0.0 D C B A E F G
2- Figure4-28: Mean concentration and standard error (S.E.) of SO4 concentrations at each sample site showing the variation between sites. The number of samples in site A is 15, and the number of samples on other sites is 5
4.3 Statistical Analysis of data
Spearman's rho Correlation and ANOVA was performed between the concentrations of anions
(2012) and concentrations of heavy metals in 2011 & 2012 in the study area. There are no significant (P< 0.05) differences within each site between years. Therefore, the data for two years were combined to evaluate whether there was any difference in concentration levels at the sites in Table 4.4 – 4.10 for each site. The analysis shows that there is a significant (P < 0.05) difference for Cr, Mo, Ni, Pb, Hg and Sn between the two years at each site. So, analyses were performed on the mean concentrations of Cr, Mo, Ni, Pb, Hg and Sn in the area studied for each year. Moreover, Duncun‘s Analysis was performed for areas with high concentrations of Cr,
Mo, Ni, Pb, Hg and Sn in order to identify the most affected sites or sites that have the highest mean concentrations of heavy metals.
103
4.3.1 Correlation of data between sites and years for heavy metals
Spearman's rho Correlation analyses were performed to determine relationships between the concentrations of heavy metals and concentration of anions in 2011 & 2012 in the study area
(Table 4.4 – 4.10). Moreover, analyses were performed between the mean concentrations of Cr,
Mo, Ni, Pb, Hg and Sn to show that there is significant (P< 0.05) difference for Cr, Mo, Ni, Pb,
Hg and Sn between the two years with each site in the study area for 2011 and 2012 - tables
4.11-4.17 for each area respectively.
Data in table 4.4 indicate that at site A, there was a high positive correlation between the following paired heavy metals: Al and Ni, Cd and Cr, Co and Cr, Co and Cu, Co and Mo, Cu and
V, Pb and As, Pb and Sn, and V and As. Furthermore, the correlation analysis showed significant positive correlations between the following paired heavy metals: Al and Cr, Al and Zn, Co and
Hg, Cu and Fe, Cu and Hg, Fe and Mn, and Hg and Sn. This may indicate that the origin of these paired heavy metals was the same particular source (see Chapter Five).
Table 4.5 shows the correlation analysis for site B. There is significant high positive correlation between the following paired heavy metals: As and F, and Cl and Br only. Additionally, the correlation analysis showed significant positive correlations between the following paired heavy metals: Al and Sn, Cd and Mo, Co and Ni, Cu and Zn, Mn and Hg, Mo and As, and Ni and V.
Similarly, these correlations show that the origin of these paired heavy metals is likely to be from the same source.
The correlation analysis in site C in table 4.6 shows significant high positive correlations between the following paired heavy metals: Co and Cl, Co and Br, Mo and Cl, Fe and SO4, and
Cl and Br. Additionally, the correlation analysis showed significant positive correlations between
104 the following paired heavy metals: Al and Cr, Al and Mo, Al and Hg, Co and V, Cr and Mn, Cu and Mn, and Mo and Hg. The correlation in the above paired heavy metals showed that the origins were probably the same particular source.
The results in table 4.7 show the correlation analysis at site D, with significant high positive correlations between the following paired heavy metals: Co and Cr, Cu and Hg, Mo and V, Mo and Hg, and V and F. Additionally, the correlation analysis showed significant positive correlations between the following paired heavy metals: Al and Zn, Co and V, Cr and Cu, Fe and
Pb, and Ni and Sn. The source of these paired heavy metals is likely to be the same.
Table 4.8 shows the correlation analysis for site E, with significant high positive correlations only between Cd and Zn. Additionally, the correlation analysis showed significant positive correlations between the following paired heavy metals: Al and Mo, Cd and Mn, Co and V, Cr and Mo, Cu and Mn, Cu and Ni, and V and As. Likewise, the correlation showed that the origin of these paired heavy metals was the same particular source.
Table 4.9 demonstrates that the correlation analysis in site F provides significant positive correlations between the following paired heavy metals: Cd and As, Fe and Pb, and Mo and Zn.
The correlation in the above paired heavy metals shows that their origin is the same specific source.
The correlation analysis in table 4.10 illustrates that site G has significant high positive correlations for the following paired heavy metals: Al and Co, Co and Zn, and Fe and V. The correlation analysis showed significant positive correlations between the following paired heavy metals: Al and Mo, Mo and Hg, Ni and Pb. These paired heavy metals are likely to be from the same source.
105
Generally, the correlation coefficients detailed in table‘s 4.4 - 4.10 indicated that there are positive correlations between heavy metals in all sites. For example, table 4.4 shows that there is a positive correlation between Al and Cr (0.406) in the site A which means that the concentrations of Al and Cr are both increasing or decreasing in site A. This is clear from the figures 4.1 for Al and 4.4 for Cr which demonstrated that the concentration of Al and Cd in 2011 and 2012 is decreasing. Moreover, correlations coefficient in table 4.4 shows that there is a positive correlation between Cu and Hg (-.0401) which means if the concentration of one of them is increased the other is decreased. Figures 4.5 and 4.13 indicated that the concentration of
Cu in site A is decreased while the concentration of Hg is increased. This is true for all heavy metals in tables 4.4 to 4.10 that demonstrated correlations coefficient between heavy metals.
These findings indicate that the heavy metal contamination is arising from a common source and this is discussed further in Chapter 5.
106
Table 4-4: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site A.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co .392* 1.000
Cr .406* .602** .484** 1.000
Cu -.497** 1.000
Fe .451* 1.000
Mn -.456* 1.000
Mo .471** 1.000
Ni .695** 1.000
Pb 1.000
V -.497** 1.000
Zn .425* 1.000
Hg .373* -.401* 1.000
As .550** .594** 1.000
Sn .552** .416* .571** 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01level (2-tailed)
a. Site= A.
107
Table 4-5: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site B.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co 1.000
Cr 1.000
Cu 1.000
Fe 1.000
Mn 1.000
Mo .747* 1.000
Ni -.697* 1.000
Pb 1.000
V -.758* 1.000
Zn .758* 1.000
Hg .657* 1.000
As -.692* 1.000
Sn -.648* 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed) a. Site= B.
108
Table 4-6: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site C.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co 1.000
Cr -.636* 1.000
Cu 1.000
Fe 1.000
Mn -.648* .650* 1.000
Mo .669* 1.000
Ni 1.000
Pb 1.000
V .721* 1.000
Zn 1.000
Hg .693* .643* 1.000
As 1.000
Sn 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01level (2-tailed) a. Site= C.
109
Table 4-7: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site D.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co 1.000
Cr -.891** 1.000
Cu -.636* 1.000
Fe 1.000
Mn 1.000
Mo 1.000
Ni 1.000
Pb .661* 1.000
V -.709* .848** 1.000
Zn -.661* 1.000
Hg .772** -.789** 1.000
As 1.000
Sn -.685* 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed) a. Site= D.
110
Table 4-8: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site E.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co 1.000
Cr 1.000
Cu 1.000
Fe 1.000
Mn -.681* .636* 1.000
Mo -.711* -.663* 1.000
Ni -.669* 1.000
Pb 1.000
V -.648* 1.000
Zn -.912** 1.000
Hg 1.000
As .697* 1.000
Sn 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= E.
111
Table 4-9: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site F.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co 1.000
Cr 1.000
Cu 1.000
Fe 1.000
Mn 1.000
Mo 1.000
Ni 1.000
Pb .709* 1.000
V 1.000
Zn .736* 1.000
Hg 1.000
As .723* 1.000
Sn 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed) a. Site= F.
112
Table 4-10: Spearman's rho correlations coefficient between mean concentrations of heavy metals at site G.
Correlations
Variable Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn Al 1.000
Cd 1.000
Co -.855** 1.000
Cr 1.000
Cu 1.000
Fe 1.000
Mn 1.000
Mo .701* 1.000
Ni 1.000
Pb .729* 1.000
V -.842** 1.000
Zn -.770** 1.000
Hg .731* 1.000
As 1.000
Sn 1.000 *. Correlation is significant at the 0.05 level (2 -tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed) a. Site= G.
113
The correlation analysis in Table 4.11 shows high significant positive correlations in site between all elements in both 2011 and 2012, except there is no significant correlation between
Ni and Moin 2012.
Table 4-11: Spearman's rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn in site A in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn 2011 1.000 Cr 2012 1.000 ** 2011 .530 1.000 Mo 2012 ** .549 1.000 ** ** 2011 .307 .495 1.000 Ni ** 2012 .211 1.000 ** ** ** 2011 .479 .491 .479 1.000 Pb ** ** ** 2012 -.193 -.127 .393 1.000 ** ** ** ** 2011 .307 .466 .071 .232 1.000 Hg ** ** ** ** 2012 -.125 .050 .182 .171 1.000 ** ** ** ** ** 2011 .461 .326 .079 475 .304 1.000 Sn 2012 -.461** -.111** .204** .646** .396** 1.000
**. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= A, Years = 2011 & 2012
114
Table 4.12 presents the correlation analysis in site B is high significant positive correlations between all elements in both 2011 and 2012, except in 2011 there is no significant positive correlation between Sn and Ni.
Table 4-12: Spearman‘s rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site B in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn
2011 1.000 Cr 2012 1.000 ** 2011 .600 1.000 Mo 2012 ** -.300 1.000 ** ** 2011 .200 .400 1.000 Ni ** ** 2012 -.300 -.200 1.000 ** ** ** 2011 .300 .500 .700 1.000 Pb ** ** ** 2012 -.300 .700 -.200 1.000
2011 -.300** .100** -.300** -.700** 1.000 Hg ** ** ** ** 2012 -.300 -.300 .700 -.700 1.000
** ** ** ** 2011 .200 -.600 -.300 -.300 1.000 Sn ** ** ** ** ** 2012 -.100 .600 .500 .100 .400 1.000
**. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= B, Year = 2011 & 2012
115
The correlation analysis in Table 4.13 demonstrates that site C has high significant positive correlations between all elements in both 2011 and 2012, except between Sn and Pb in 2011 while in 2012 between Mo and Cr & Sn and Cr.
Table 4-13: Spearman‘s rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site C in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn 2011 1.000 Cr 2012 1.000 ** 2011 -.900 1.000 Mo 2012 1.000 ** ** 2011 -.100 -.200 1.000 Ni ** ** 2012 .300 .100 1.000 ** ** ** 2011 .200 -.100 -.500 1.000 Pb ** ** ** 2012 .400 .300 .900 1.000
2011 -.300** .600** -.600** -.300** 1.000 Hg 2012 ** ** ** ** .564 .616 .154 .154 1.000 ** ** ** ** 2011 -.200 .100 -.500 .300 1.000 Sn ** ** ** ** 2012 -.500 -.800 -.900 -.051 1.000
**. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= C, Year = 2011 & 2012
116
It is clear from Table 4.14 that the correlation analysis in site D is high significant positive correlations in between all elements in both 2011 and 2012.
Table 4-14: Spearman‘s rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site D in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn 2011 1.000 Cr 2012 1.000 ** 2011 .600 1.000 Mo 2012 ** .500 1.000 ** ** 2011 -.300 -.100 1.000 Ni ** ** 2012 .300 .600 1.000 ** ** ** 2011 -.400 -.300 .100 1.000 Pb ** ** ** 2012 -.300 -.100 .300 1.000
2011 -.500** -.800** .400** -.700** 1.000 Hg ** ** ** ** 2012 -.200 -.900 -.700 -.300 1.000
** ** ** ** ** 2011 .300 .600 -.700 -.500 -.900 1.000 Sn 2012 .400** .300** -.400** -.900** .100** 1.000 **. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= D, Year = 2011 & 2012
117
Table 4.15explains the correlation analysis in site E is high significant positive correlations between all elements in both 2011 and 2012 except between Pb and Cr in 2011 while in 2012 between Pb and Ni.
Table 4-15: Spearman's rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site E in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn 2011 1.000 Cr 2012 1.000 ** 2011 -.400 1.000 Mo ** 2012 -.500 1.000 ** ** 2011 -.900 .200 1.000 Ni ** ** 2012 .200 .700 1.000 ** ** 2011 -.600 .400 1.000 Pb 2012 ** ** -.200 .300 1.000
2011 .400** .300** -.300** .100** 1.000 Hg ** ** ** ** 2012 -.500 1.000 .700 .300 1.000 ** ** ** ** ** 2011 -.900 .300 .800 -.100 -.700 1.000 Sn 2012 .400** -.600** -.100** -.400** -.600** 1.000 **. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= E, Year = 2011 & 2012
118
Table 4.16 describes the correlation analysis in site F, which has high significant positive correlations between all elements in both 2011 and 2012, except between Ni and Cr in 2011 and between Hg and Ni in 2012.
Table 4-16: Spearman‘s rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site F in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn
2011 1.000 Cr 2012 1.000 ** 2011 -.300 1.000 Mo 2012 ** .700 1.000 ** 2011 .100 1.000 Ni ** ** 2012 .200 -.500 1.000 ** ** ** 2011 -.100 .600 -.300 1.000 Pb ** ** ** 2012 .900 .500 .500 1.000
2011 -.500** .400** .800** 1.000 Hg 2012 ** ** ** ** .100 .400 -.100 .300 1.000 ** ** ** ** ** 2011 -.100 .600 -.300 1.000 .800 1.000 Sn 2012 -.200** -.700** .800** .100** .100** 1.000
**. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= F, Year = 2011 & 2012
119
The results in table 4.17 show that the correlation analysis in site G has high significant positive correlations between all elements in both 2011 and 2012, except between Ni and Cr in 2011.
Table 4-17: Spearman's rho correlations coefficient of Cr, Mo, Ni, Pb, Hg and Sn at site G in both 2011 & 2012
Correlationsa
Year Cr Mo Ni Pb Hg Sn 2011 1.000 Cr 2012 1.000 ** 2011 .200 1.000 Mo 2012 ** -.100 1.000 ** ** 2011 -.300 .300 1.000 Ni ** 2012 .100 1.000 ** ** ** 2011 -.100 .900 .600 1.000 Pb ** ** ** 2012 .300 .600 .700 1.000
2011 -.100** .900** .600** 1.000** 1.000 Hg ** ** ** ** 2012 -.600 .300 .600 .500 1.000 ** ** ** ** ** 2011 .500 .800 -.200 .600 .600 1.000 Sn 2012 .300** .400** .200** .200** -.400** 1.000 **. Correlation is highly significant at the 0.01 level (2-tailed). a. Site= G, Year = 2011 & 2012
120
4.3.2 The correlation between Heavy metals and anions 2012
The correlation analysis at site A in table 4.18 shows significant high positive correlations between the following paired heavy metals, heavy metals and anions and paired anions: Al and
Ni, Cd and Cr, Co and Cr, Co and Cu, Co and Mo, Cr and F-, Cu and V, Pb and As, Pb and Sn, V
- - 2- - - - 2- - and Hg, Zn and F , Hg and Br, As and Sn, F and SO4 , Cl and Br , Cl and SO4 , and Br and
2- SO4 . Furthermore, the correlation analysis showed significant positive correlations between the following paired heavy metals, heavy metals and anions and paired anions: Al and Cr, Al and
- 2- Zn, Al and F , Cd and Co, Co and Hg, Cu and Fe, Cu and Hg, Fe and V, Fe and SO4 , V and Br,
2- 2- - - - V and SO4 , Zn and SO4 , Hg and Sn, Hg and Cl , and F and Br .The correlation in the above paired heavy metals shows that their origin is from the same particular source.
The result in table 4.19 shows the correlation analysis at site B, with significant high positive correlations between the following heavy metals and anions: As and F-. Additionally, the correlation analysis showed significant positive correlations between the following paired heavy
2- metals and heavy metals and anions and paired anions: Al and Sn, Cd and Mo, Cd and SO4 , Co
2- and Ni, Cr and Zn, Fe and Hg, Fe and SO4 , Mn and As, Mo and As, Ni and Cl, Ni and Br, Ni
- 2- and V, and F and SO4 . These paired heavy metals are likely to be from the same sources.
Data in table 4.20 indicate that at site C, there were high positive correlations between the following heavy metals and anions and paired anions: Co and Cl-, Co and Br-, Mo and Cl-, F- and
2- - - SO4 , and Cl and Br .The correlation analysis showed significant positive correlations between the following paired heavy metals, heavy metals and anions: Al and Cr, Al and Mo, Al and Hg,
Co and V, Cr and Mn, Cu and Mn, Mo and Hg, Mo and Br-, V and Cl-, and V and Br-. This may indicate that the origins of these paired heavy metals were from the same source.
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Table 4.21 shows the correlation analysis in site D, showing significant high positive correlations between the following paired heavy metals, heavy metals and anions and paired anions: Co and
- - - 2- - Cr, Co and F , Cr and F , Cu and Hg, Mo and V, Mo and Hg, V and F , Hg and SO4 , and Cl and
2- SO4 . Additionally, the correlation analysis shows significant positive correlations between the following paired heavy metals, heavy metals and anions and paired anions: Al and Zn, Co and V,
- 2- 2- 2- Co and Cl , Co and SO4 , Cr and Cu, Fe and Pb, Mo and SO4 , Ni and Sn, V and SO4 , Sn and
Cl, F- and Cl-, and Cl- and Br-. Similarly, the correlation shows that the origins of these paired heavy metals are the same particular source.
Table 4.22 demonstrates that the correlation analysis in site E is significant positive correlations between the following paired heavy metals and paired anions: Cd and Zn, and Cl- and Br-.
Additionally, the correlation analysis shows significant positive correlations between the following paired heavy metals and heavy metals and anions: Al and Mo, Cd and Mn, Co and V,
Cr and Mo, Cu and Mn, Cu and Ni, Mn and Cl-, Mn and Br-, V and As, V and Cl-, and V and Br-.
The correlation in the above paired heavy metals shows that the origins were the same particular source.
The correlation analysis in table 4.23 illustrates that site F has significant high positive
2- correlations between the following heavy metal and anion: Cr and SO4 . Additionally, the correlation analysis showed significant positive correlations between the following paired heavy metals and heavy metals and anions and paired anions: Cd and As, Cu and Cl-, Fe- and Pb, Mn
2- - - - - and F, Mo and Zn, V and SO4 , F and Br , and Cl and Br . These paired heavy metals are likely to be from the same sources.
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Table 4.24 shows the correlation analysis in site G significantly high positive correlations between the following paired heavy metals and paired anions: Al and Co, Co and Zn, Fe and V,
2- - - F and SO4 , and Cl and Br . Additionally, the correlation analysis showed significant positive correlations between the following paired heavy metals and heavy metals and anions: Al and
- - 2- - 2 Mo, Cd and Cl, Cd and Br , Co and F , Co and SO4 , Mo and Hg, Zn and F , and Zn and SO4 .
The correlation in the above paired heavy metals shows that their origin is from the same source.
Generally, correlation coefficients in Table‘s 4.18- 4.24 indicated that there are positive correlations between heavy metals and anions in all sites in 2012. This means that under certain conditions some of heavy metals in presence of anions will release from sediment to sea water
(Zhong, A.P et al., 2006). For example, Table 4.24 shows that there is a positive correlation between Cd and Cl (0.658). Therefore, abundance of Cl- will accelerate to release Cd from sediment in site G. Furthermore, figure 4.2 demonstrated that the concentration of Cd is decreased when going away from the port and site G has low concentration of Cd and the concentration of Cl- is over 400 ppm which can lead to release Cd from sediment. The formation of these compounds has potential detrimental environmental and human health effects and is discussed in Chapter 5.
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Table 4-18: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site A.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4 Al 1.000 Cd 1.000 Co .392* 1.000 Cr .406* .602** .484** 1.000 Cu .497** 1.000 Fe .451* 1.000 Mn 1.000 Mo .471** 1.000 Ni .695** 1.000 Pb 1.000 V .497** .456* 1.000 Zn .425* 1.000 Hg .373* .401* .594** 1.000 As .550** 1.000 Sn .552** .416* .571** 1.000 F- .428* .501** .517** 1.000 Cl- .423* 1.000 Br - .364* .505** .420* .911** 1.000 2- .742** .668** .768** SO4 .439* .463* .399* 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= A.
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Table 4-19: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site B.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co 1.000 Cr 1.000 Cu 1.000 Fe 1.000 Mn 1.000 Mo .747* 1.000 Ni .697* 1.000 Pb 1.000 V .758* 1.000 Zn .758* 1.000 Hg .657* 1.000 As .692* .692* 1.000 Sn .648* 1.000 F- .798** 1.000 Cl- .714* 1.000 Br - .714* 1.000** 1.000 2- SO4 .728* .763* .667* 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site=B.
125
Table 4-20: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site C.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co 1.000 Cr .636* 1.000 Cu 1.000 Fe 1.000 Mn .648* .650* 1.000 Mo .669* 1.000 Ni 1.000 Pb 1.000 V .721* 1.000 Zn 1.000 Hg .693* .643* 1.000 As 1.000 Sn 1.000 F- 1.000 Cl- .837** .803** .640* 1.000 Br - .862** .753* .665* .900** 1.000 2- .791** SO4 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= C.
126
Table 4-21: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site D.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co 1.000 Cr .891** 1.000 Cu .636* 1.000 Fe 1.000 Mn 1.000 Mo 1.000 Ni 1.000 Pb .661* 1.000 V .709* .848** 1.000 Zn .661* 1.000 Hg .772** .789** 1.000 As 1.000 Sn .685* 1.000 F- .884** .821** .783** 1.000 Cl- .665* .640* .667* 1.000 Br - .700* 1.000 2- .900** SO4 .640* .718* .714* .778** 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= D.
127
Table 4-22: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site E.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co 1.000 Cr 1.000 Cu 1.000 Fe 1.000 Mn .681* .636* 1.000 Mo .711* .663* 1.000 Ni .669* 1.000 Pb 1.000 V .648* 1.000 Zn .912** 1.000 Hg 1.000 As .697* 1.000 Sn 1.000 F- 1.000 Cl- .640* .714* 1.000 Br - .640* .714* 1.000** 1.000 2- SO4 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= E.
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Table 4-23: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site F.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co 1.000 Cr 1.000 Cu 1.000 Fe 1.000 Mn 1.000 Mo 1.000 Ni 1.000 Pb .709* 1.000 V 1.000 Zn .736* 1.000 Hg 1.000 As .723* 1.000 Sn 1.000 F- .695* 1.000 Cl- .689* 1.000 Br - .763* .667* 1.000 2- SO4 .837** .640* 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= F.
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Table 4-24: Spearman's rho correlations coefficient between mean concentrations of heavy metals and anions in 2012 at site G.
- - - 2- Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn F Cl Br SO4
Al 1.000 Cd 1.000 Co .855** 1.000 Cr 1.000 Cu 1.000 Fe 1.000 Mn 1.000 Mo .701* 1.000 Ni 1.000 Pb 1.000 V .842** 1.000 Zn .770** 1.000 Hg .731* 1.000 As 1.000 Sn 1.000 F- .665* .665* 1.000 Cl- .658* 1.000 Br- .683* .900** 1.000 2- 1.000** SO4 .665* .665* 1.000 *. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is highly significant at the 0.01 level (2-tailed)
a. Site= G
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4.3.3 ANOVA Analysis
4.3.3.1 One Way ANOVA
One Way ANOVA analyses were performed between the concentrations of anions and concentrations of heavy metals in order to determine the difference between sites and years for each parameter (Tables 25-39). Moreover, Two Way ANOVA analyses were performed between the mean concentrations of Cr, Mo, Ni, Pb, Hg and Sn in the area studied for each year in Tables
32-37 respectively.
There were significant (P< 0.05) differences for Al in table 4.25 between site B and site C with sites E and F. Moreover, Sites E and F have significant (P< 0.05) differences with site G. There are no significant difference between site A and D and others.
Table 4-25: The P values for the One Way ANOVA analysis for Al at sites A-G
A B C D E F G A 1.000 B 1.000 C 1.000 D 1.000 E 0.002 0.004 1.000 F 0.002 0.005 1.000 G 0.003 0.004 1.000
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Table 4.26 demonstrates that there were significant (P< 0.05) differences for Cd between site A and sites B and E. Site B shows significant (P< 0.05) differences with sites D and G. Moreover, Site C has significant (P< 0.05) differences compared with site D. For site D the results show significant (P<
0.05) differences with E and site F. Site E shows significant (P< 0.05) differences with site G.
Table 4-26: The P values for the One Way ANOVA analysis for Cd in sites (A-G)
A B C D E F G A 1.000 B 0.007 1.000 C 1.000 D 0.001 0.020 1.000 E 0.008 0.001 1.000 F 0.025 1.000 G 0.010 0.010 1.000
There were significant (P< 0.05) differences for Co in Table 4.27 between site A and site G. Site B shows significant (P< 0.05) differences with sites C. Moreover, Site C has significant (P< 0.05) differences with site D and site G (0.042). For site D the results show significant (P< 0.05) differences with E and F. Site F shows significant (P< 0.05) differences with site G.
Table 4-27: The P values for the One Way ANOVA analysis for Co in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 0.001 1.000 D 0.001 1.000 E 0.002 1.000 F 0.002 1.000 G 0.025 0.042 0.022 1.000
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Based on the study results (Table 4.28) there were significant (P< 0.05) differences for Cr between site
B and site D. Site C shows significant (P< 0.05) differences with E and D and E. However, there are no significant difference between sites A and G and others sites.
Table 4-28: The P values for the One Way ANOVA analysis for Cr in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.002 0.014 1.000 E 0.043 1.000 F 0.010 1.000 G 1.000
The studied sites‘ analysis results demonstrate in Table 4. 29 that there were highly significant
(P< 0.05) differences for Cu between site B and sites C, D, E and G. However, there are no significant differences between sites A and F with others sites.
Table 4-29: The P values determined by ANOVA for Cu in sites A-G
A B C D E F G A 1.000 B 1.000 C 0.003 1.000 D 0.006 1.000 E 0.001 1.000 F 1.000 G 0.035 1.000
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Table 4.30 shows that there were significant (P< 0.05) differences for Fe between site B and site C.
Moreover, Site C is significant (P< 0.05) differences with site G while site D is significant (P< 0.05) differences with site E. Moreover, site E the results show significant (P< 0.05) differences with sites F and G. There is no significant difference between site A and others.
Table 4-30: The P values for the One Way ANOVA analysis for Fe in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 0.010 1.000 D 1.000 E 0.032 1.000 F 0.046 1.000 G 0.048 0.028 1.000
It has been shown by this study‘s results in table 4.31 that there were significant (P< 0.05) differences for Mn between site A and site F. Site B shows significant (P< 0.05) differences with sites F.
Moreover, Site C has significant (P< 0.05) differences with sites D, E and G. For site D the results show significant (P<0.05) differences with site F.
Table 4-31: The P values for the One Way ANOVA analysis for Mn in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.001 1.000 E 0.001 1.000 F 0.001 0.001 0.016 1.000 G 0.001 1.000
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Data analyses in Table 4.32 indicate that there were significant (P< 0.05) differences for Mo between site A and site D. Site B shows significant (P< 0.05) differences with site D. Moreover, for site C the results show significant (P< 0.05) differences with site F. For site D there is significant (P< 0.05) differences with sites E. Site F shows significant (P< 0.05) differences with site G.
Table 4-32: The P values for the One Way ANOVA analysis for Mo in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.008 0.001 1.000 E 0.008 1.000 F 0.039 1.000 G 0.032 1.000
Table 4.33 demonstrates that there were significant (P< 0.05) differences for Ni between site B with sites C, D and E. Moreover, sites C and D have significant (P< 0.05) differences with sites F and G.
For site E the results show significant (P< 0.05) differences with F and G. There were no significant differences between sites A and others sites.
Table 4-33: The P values for the One Way ANOVA analysis for Ni in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 0.005 1.000 D 0.004 1.000 E 0.001 1.000 F 0.045 0.033 0.009 1.000 G 0.033 0.024 0.007 1.000
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The results in Table 4.34 explain that there were significant (P< 0.05) differences for Pb between site
A and B, D and F. Site B shows significant (P< 0.05) differences with sites F and G, while site C has significant (P< 0.05) differences between sites F and G. Moreover, site D has significant (P< 0.05) differences with sites G. For site E the results show significant (P< 0.05) differences with F and G.
There is no significant difference between sites F and G.
Table 4-34: The P values for the One Way ANOVA analysis for Pb in sites (A-G)
A B C D E F G A 1.000 B 0.032 1.000 C 1.000 D 0.014 1.000 E 1.000 F 0.029 0.001 0.011 0.002 1.000 G 0.003 0.041 0.001 0.007 1.000
Based on the study results in table 4.35, there were significant (P< 0.05) differences for V between site
B and sites C. Moreover, Site C has significant (P< 0.05) differences with sites D. For site D the results show significant (P< 0.05) differences with sites E. There are no significant differences between sites A, F and G with others sites.
Table 4-35: The P values for the One Way ANOVA analysis for V in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 0.001 1.000 D 0.001 1.000 E 0.001 1.000 F 1.000 G 1.000
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It has been shown by this study‘s results in Table 4.36that there were significant (P< 0.05) differences for Zn between site C and sites D. Moreover, Site D has significant (P< 0.05) differences with site E. There is no significant difference between sites A, B, F and G and others.
Table 4-36: The P values for the One Way ANOVA analysis for Zn in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.045 1.000 E 0.005 1.000 F 1.000 G 1.000
Our data analyses in table 4.37 indicate that there were significant (P< 0.05) differences for Hg between site A and sites B and F. Site B shows significant (P< 0.05) differences with site C.
Moreover, site C has significant (P< 0.05) differences with sites D. Site E shows significant (P<
0.05) differences with sites F and G. Site G does not have significant differences with all sites, except with E.
Table 4-37: The P values for the One Way ANOVA analysis for Hg in sites (A-G)
A B C D E F G A 1.000 B 0.001 1.000 C 0.007 1.000 D 0.002 1.000 E 1.000 F 0.025 0.041 1.000 G 0.013 1.000
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It has been shown by this study‘s results in Table 4.38 that there were significant (P< 0.05) differences for As between site B and sites D and F. Moreover, Site C has significant (P< 0.05) differences with site G. For site D the results show significant (P< 0.05) differences with E. For site E the results show significant (P< 0.05) differences with F and G. There is no significant difference between sites A and others.
Table 4-38: The P values for the One Way ANOVA analysis for As in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.003 1.000 E 0.005 1.000 F 0.002 0.003 1.000 G 0.033 0.001 1.000
Based on the study results in Table 4.39there were significant (P< 0.05) differences for Sn between site A and G. Site B shows significant (P< 0.05) differences with sites E and G. Moreover, site C has significant (P< 0.05) differences with site D. Site D shows significant (P< 0.05) differences with site
F. Site F shows significant (P< 0.05) differences with site G.
Table 4-39: The P values for the One Way ANOVA analysis for Sn in sites (A-G)
A B C D E F G A 1.000 B 1.000 C 1.000 D 0.021 1.000 E 0.001 1.000 F 0.025 1.000 G 0.031 0.002 0.001 1.000
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4.3.3.2 Two Way ANOVA 2011 and 2012
The studied sites‘ analysis results demonstrate in Table 4.40 that there were significant (P< 0.05) differences for Cr between site A and sites E and F in 2011 while with site B is only in 2012. Site
B shows significant (P< 0.05) differences with sites C in 2012 and with site D in 2011 but with site G both in 2011 and 2012. Moreover, Site C has significant (P< 0.05) differences only with site F in 2011. Site D shows significant (P< 0.05) differences with site E and F in both 2011 and
2012 and site G only in 2012. For site E the data shows significant (P< 0.05) differences with only with site G in 2011. Site F shows significant (P< 0.05) differences with site G in both 2011 and 2012.
Table 4-40: The P values for the Two Way ANOVA analysis for Cr by year
A B C D E F G 2011 1.000 A 2012 1.000 2011 1.000 B 2012 0.006 1.000 2011 1.000 C 2012 0.010 1.000 2011 0.008 1.000 D 2012 1.000 2011 0.003 0.001 1.000 E 2012 0.012 0.006 1.000 2011 0.002 0.04 4 0.001 1.000 F 2012 0.001 0.001 1.000 2011 0.004 0.003 0.002 1.000 G 2012 0.042 0.001 0.004 1.000
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Table 4.41 explains that there were significant (P< 0.05) differences for Mo between site A and site F in both 2011 and 2012 and with site D in 2011 and with site E in 2012. Site B shows significant
(P< 0.05) differences with sites D and F in 2011. Additionally, Site C has significant (P< 0.05) differences with site D both in 2011 and 2012and with site F in 2012. Site D has significant (P< 0.05) differences in 2011 with site E and with site G both in 2011 and 2012. For site F the results show significant (P< 0.05) differences with G only in 2011.
Table 4-41: The P values for the Two Way ANOVA analysis for Mo by year
A B C D E F G A 2011 1.000
2012 1.000 B 2011 1.000 2012 1.000 C 2011 1.000 2012 1.000 D 2011 0.043 0.003 0.004 1.000 2012 0.029 1.000
E 2011 0.001 0.012 1.000 2012 0.012 1.000 F 2011 0.001 0.018 0.02 1.000 2012 0.001 1.000 G 2011 0.005 0.026 1.000 2012 0.019 1.000
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Table 4.42 demonstrates that there were significant (P< 0.05) differences for Ni between site A and site C in 2011 and site D in both 2011 and 2012 and with site E only in 2012. Sites B show significant
(P< 0.05) differences with sites C, D and E only in 2011. Moreover, the results show site C has significant (P< 0.05) differences with sites F and G only in 2011.The results show site F has highly significant (P< 0.01) differences with site G in 2011.
Table 4-42: The P values for the Two Way ANOVA analysis for Ni by year
A B C D E F G 2011 1.000 A 2012 1.000
2011 1.000 B 2012 1.000
2011 0.005 1.000 C 2012 0.031 1.000
2011 0.001 0.011 1.000 D 2012 0.007 1.000
2011 0.005 1.000 E 2012 0.002 1.000
2011 0.009 0.021 0.01 1.000 F 2012 1.000
2011 0.011 0.024 0.012 0.026 1.000 G 2012 1.000
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From Table 4.43it is clear that that there were significant (P< 0.05) differences for Pb between site A and sites B, D and E in 2012 and with site G in 2011. The results show that sites B, C, D and E have significant (P< 0.05) differences with site F in 2012 and with site G in 2011. Moreover, site F has significant (P< 0.05) differences with site G in both 2011 and 2012.
Table 4-43: The P values for the Two Way ANOVA analysis for Pb by year
A B C D E F G 2011 1.000 A 2012 1.000
2011 1.000 B 2012 0.048 1.000
2011 1.000 C 2012 1.000
2011 1.000 D 2012 0.04 1.000
2011 1.000 E 2012 1.000
2011 1.000 F 2012 0.028 0.001 0.032 0.001 0.002 1.000
2011 0.002 0.001 0.001 0.001 0.002 0.044 1.000 G 2012 0.024 1.000
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The result in Table 4.44 indicates that there were significant (P< 0.05) differences between site A and sites B, D, E in both 2011 and 2012, and with site G in 2011 only. Site C shows significant (P< 0.05) differences with site D in 2012 and with site E in both 2011 and 2012. The results show that sites D and E have significant (P< 0.05) differences with site F in 2012.
Table 4-44: The P values for the Two Way ANOVA analysis for Hg by year
A B C D E F G 2011 1.000 A 2012 1.000
2011 0.016 1.000 B 2012 0.034 1.000
2011 1.000 C 2012 1.000
2011 0.021 1.000 D 2012 0.004 0.01 1.000
2011 0.002 0.012 1.000 E 2012 0.001 0.004 1.000
2011 1.000 F 2012 0.024 0.01 1.000
2011 0.019 1.000 G 2012 1.000
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Table 4.45 shows that there were significant (P< 0.05) differences between site A and sites B in 2011 and with site D in both 2011 and 2012. Sites B and C have significant (P< 0.05) differences with sites
E and G in 2012. Moreover, site C has significant (P< 0.05) differences with site D in 2012. The results show sites D and E have significant (P< 0.05) differences with site F in 2012. Site F has significant (P< 0.05) differences with site G only in 2012.
Table 4-45: The P values for the Two Way ANOVA analysis for Sn by year
A B C D E F G 2011 1.000 A 2012 1.000 2011 0.002 1.000 B 2012 1.000 2011 1.000 C 2012 1.000 2011 0.01 1.000 D 2012 0.009 0.041 1.000 2011 1.000 E 2012 0.001 0.001 1.000 2011 1.000 F 2012 0.035 0.001 1.000 2011 1.000 G 2012 0.002 0.002 0.001 1.000
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4.3.3.3 Analysis of differences between means
The above ANOVA analyses show that there is a significant (P < 0.05) difference for Cr, Mo,
Ni, Pb, Hg and Sn between the two years with each site. Therefore, Duncun‘s multiple
comparison tests was performed in order to determine which area has the highest concentrations.
Table 4.46 demonstrates that site A has the highest mean concentrations of Mo, Ni, and Sn in
both years, except for Hg and Pb in 2011alone, compared to all other sites. However, site F has
high mean concentrations of Cr in both 2011 and 2012 and of Pb in 2012.
Table 4-46: Sites which have highest mean concentrations of Cr, Mo, Ni, Pb, Hg and Sn by year
Cr Mo Ni Pb Hg Sn
2011 2012 2011 2012 2011 2012 2011 2012 2011 2012 2011 2012
A 3.807 4.480 692.49 611.9 40.16 61.59 7.407 8.593 18.97 25.63
B 657.5 542.0 4.520
C 355.3 427.1 7.240 8.900
D 2.920 3.420 4.640
E 565.2 409.9 5.920 13.98 22.52
F 579.6 448.9 632.3 454.2 46.78 88.20 6.040 8.360
G 627.5 476.2 70.58 4.580 13.64 21.48
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Based on data in Table 4.47, it is clear that site A still has the highest mean concentrations of most of the heavy metals except for Co,
Cr, Mn, Pb, V and Hg, although these heavy metals are still high in site A compared to all other sites. Site E has high mean concentrations of Co and V, while site F has the highest mean concentrations Cr and Pb. Duncun‘s comparative test shows that site A
(SIP) has the highest mean concentrations of most of the heavy metals compared to all other sites.
Table 4-47: Duncun‘s comparative test of sites which have highest mean concentrations of Al, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, V, Zn, Hg, As and Sn
Al Cd Co Cr Cu Fe Mn Mo Ni Pb V Zn Hg As Sn A 697.5 3.190 319.9 677.1 455.8 4.143 652.2 50.88 194.3 8.000 43.37 22.29 B 488.3 599.8 C 8.07 D 305.3 441.8 E 107.7 487.5 121.5 18.25 F 514.2 543.2 67.49 5.98 G 551.8 62.59 6.47 17.56
146
4.4 Comparison between the current study data and the International Sediment Quality
Guidelines (ISQG)
Since no national standard relating to heavy metal pollution is available, international reference values have been used to assess the risk. Tables 4.48- 4.50 show comparisons and percentage of the mean concentrations of the selected heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg, As and Mo) in the surface sediments at the area studied with the International Sediment Quality Guidelines
(ISQG) for international organizations such as Environment Canada (EC), Australian and New
Zealand Environment Conservation Council (ANZECC), the US Environmental Protection
Agency (USEPA) and Ministry of Housing, Spatial Planning and the Environment (VROM)
Netherland.
The 2011 results in Tables 4.48-4.50 show that the mean concentrations and percentage of Cr,
Cu and Ni in the SIP exceeded all available sediment quality guidelines. However, Cd and As in the SIP are over the value of the USEPA with percentage of 404.4% and 461.7% respectively and close to the EC probable effects level (PEL). However, the values are between Interim
Sediment Quality Guidelines - Low (ISQG-Low) and Interim Sediment Quality Guidelines -
High (ISQG-High) in ANZECC standard and between target value and intervention value in
VROM criteria. Lead and Zn in the port exceeded the USEPA value by 28.94% and 51.53% respectively but below (ISQG-Low) in ANZECC guideline. Pb is between TEL and PEL value of the EC while Zn is below between TEL and PEL value and between target value and intervention value in VROM.
Mercury at the SIP exceeded all quality guidelines, with the exception of the VROM value, in percentage of 915.7% of EC, 901.4% of ANZCC and 5369% of EPA guideline. Generally speaking, all selected heavy metals in the SIP exceeded the USEPA values. By contrast, apart
147 from three metals (which are Cr, Cu and Ni), all selected heavy metals in the SIP were over the target value of the VROM. In the case of Mo, no value exceeded international guidelines .
Both the west (B, C & D) and east (E, F & G) sites have high mean concentrations of Ni and exceeded all guideline standards. The mean concentrations of Cr to the east of SIP exceed the value of all organizations guidelines in site E, at 253.3% above EC, 52.76% above ANZECC,
980.7% above EPA and 48.74% above VROM standards. Site F values were 262.3% above EC standard, 56.65% above ANZECC, and 52.52% above VROM value. While the mean concentrations of Cr to the east of SIP in site G is close to the (ISQG-High) of ANZECC and intervention value of VROM; whereas in the western sites C values exceeded all quality guidelines with percentage of 165.9% for EC value, 14.97% for ANZECC, 713.4% for EPA and
11.95% for Dutch guidelines. Site D values only exceeds the PEL of EC in USEPA standard.
However, site B concentrations do not exceed those of any organizations.
Copper to the west of SIP has exceeded the value of all organizations in site D, of 161.9% in EC value, 4.741% in ANZECC, 1412% in EPA and 48.84% in VROM values, while in site B it has not exceeded the ISQG-High of ANZECC value, and in site C it has exceeded only the PEL of
EC (3.981%) and 500.5% in USEPA values. However, in the East the mean concentration of Cu has only exceeded EC values in site F and G with percentage of 39.07% and 30.37% receptively and the USEPA value in sites E, F and G with percentage of 417.6%, 703.2% and 652.9 receptively. Lead has exceeded EPA value to the west ( 4.04% in site B and 1.46% in site C) and east ( 9.74% in site E, 54.90% in site F and 133.7% in site G) of the port, except site D, while As exceeded only the USEPA value, with percentage of 263.0% in site B, 124.6% in site C, 34.81% in site D, 161.6% in site E, 41.16% in site F and 12.15% in site G, and was between TEL and
PEL in EC standards, between ISQG-Low and ISQG-High in ANZECC standards and between target value and intervention value in VROM standards. 148
Cadmium only exceeded the USEPA both west (200.0% in site B, 152.9% in site C and 8.823% in site D) and east (270.6% in site E, 152.9% in site F and 58.82% in site G) of the SIP. Mercury both east and west of the SIP exceeded the values laid down by the EC (545.7% in site B,
934.3% in site C, 562.9% in site D, 405.7% in site E, 762.9% in site F and 554.3% in site G),
ANZECC (536.6% in site B, 919.7% in site C, 553.5% in site D, 398.6% in site E, 750.7% in site
F and 545.1% in site G) and USEPA (3376% in site B, 5485% in site C, 3469% in site D, 2623% in site E, 4546% in site F and 3432% in site G). Molybdenum to the west and east is below the target value according to the VROM value. The only metal that did not exceed any of the international standards is Zn. Both to the east and the west the level of Zn is below the value for all organizations. In general, apart from Zn, all selected heavy metals exceeded USEPA levels both east and west of the port.
There is a strong imperative to look carefully at the need to constrain any further increases as a result of discharges due to human activities. These guidelines are intended to be conservative, and results indicate the need for greater investigation as part of a strategic risk-based approach to impact assessment.
149
Table 4-48: Comparison of the mean concentrations of the selected heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg, Mo and As) in 2011 in the surface sediments at the site study with the Sediment Quality Guidelines in international organizations such as Environment Canada, Australian and New Zealand Environment Conservation Council ANZECC, US Environmental Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland.
Site Study value1 2011
ECvaluea ANZECC valueb VROMd SIP West of SIP East of SIP USEPA c
Values No. Metals ISQG- Target interventio
Low ISQG- A B C D E F G TEL2 PEL3 Value6 n value7 (Trigger High5 value)4
1 Cd 3.43 2.04 1.72 0.74 2.52 1.72 1.08 0.68 4.21 1.50 9.60 0.68 0.80 12.00 2 Cr 382.7 98.82 425.4 304.8 565.2 579.6 328.2 52.30 160.0 80.00 370.0 52.30 100.00 380.0 3 Cu 363.0 200.7 112.3 282.8 96.80 150.2 140.8 18.7 108.0 65.00 270.0 18.70 36.00 190.0 4 Ni 683.8 657.5 380.8 411.7 384.9 632.3 627.5 15.9 42.80 21.00 51.60 15.90 35.00 210.0 5 Pb 38.94 31.42 30.64 27.40 33.14 46.78 70.58 30.20 112.0 50.00 218.0 30.20 85.00 530.0 6 Zn 187.85 31.54 56.64 19.80 59.54 41.36 41.84 124 274.0 200.0 410 124.0 140.0 720.0 7 Hg 7.11 4.52 7.24 4.64 3.54 6.04 4.58 0.13 0.70 0.15 0.71 0.13 0.30 10.00 8 As 40.67 26.28 16.26 9.76 18.94 10.22 8.12 7.24 41.6 20.00 70.00 7.24 29.00 55.00 9 Mo 3.75 1.30 1.32 2.92 1.54 2.58 1.38 10.00 200.0 Notes 1 Mean concentrations of metals at SIP, west and east of SIP (2011) 2 TEL, threshold effect level 3 PEL, probable effects level 4 ISQG-Low, Interim Sediment Quality Guidelines - Low: Probable effects concentrations below which biological effects would rarely occur 5 ISQG-High, Interim Sediment Quality Guidelines - High: Probable effects concentrations below which biological effects would possibly occur. Concentrations above these values represent a probable-effects range within which effects would be expected to frequently occur 6 Indicates the level that has to be achieved to fully recover the functional properties of the soil for humans and plant and animal life 7 Functional properties of the soil for humans, plant and animal life, is seriously impaired or threatened a- EC, Environment Canada. (Burton, 2002) b- (ANZECC) ANZECC, Australian and New Zealand Environment and Conservation Council. (Burton, 2002) c- Environmental Protection Agency. US Values. (USEPA; 2006) d- Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland(Dutch Target and Intervention Values, 2000 (the New Dutch List)(Esdat, 2000)
150
Table 4-49: Percentage excess of Sediment Quality Guidelines in Environment Canada (EC) and Australian and New Zealand Environment Conservation Council (ANZECC) in 2011 for Cr, Cu, Ni, Hg, and As.
Site Study value 2011 % samples which exceeded % samples which exceeded PEL ECa ISQG-High ANZECCb
No. Metals A B C D E F G A B C D E F G
1 Cr 139.2 ------165.9 90.5 253.3 262.3 105.1 3.432 ------14.97 ----- 52.76 56.65 ------
2 Cu 236.1 85.83 3.981 161.9 ------34.07 30.37 34.44 ------4.741 ------
3 Ni 1498 1436 789.7 861.9 799.3 1377 1366 1225 1173 638 697.9 645.9 1125 1116
4 Hg 915.7 545.7 934.3 562.9 405.7 762.9 554.3 901.4 536.6 919.7 553.5 398.6 750.7 545.1
5 As ------
Notes: a- EC, Environment Canada. (Burton, 2002) b- (ANZECC) ANZECC, Australian and New Zealand Environment and Conservation Council. (Burton, 2002)
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Table 4-50: Percentage excess of Sediment Quality Guidelines US Environmental Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland in 2011 for Cd, Cr, Cu, Ni, Pb, Zn, Hg, and As.
Site Study value 2011 % samples which exceeded
% samples which exceeded EPA Intervention VRON
No. Metals A B C D E F G A B C D E F G 1 Cd 404.4 200.0 152.9 8.823 270.6 152.9 58.85 ------2 Cr 631.7 88.95 713.4 482.8 980.7 1008 527.5 0.7105 ------11.95 ----- 48.74 52.52 ------3 Cu 1841 973.3 500.5 1412 417.6 703.2 652.9 91.05 5.632 ------48.84 ------4 Ni 4200 4035 2295 2489 2320 3877 3847 225.6 213.1 81.33 96.05 83.29 201.1 198.8 5 Pb 28.94 4.04 1.46 ------9.74 54.90 133.7 103.9 25.17 87.09 21.72 38.21 192.1 80.79 6 Zn 51.53 ------57.73 ------7 Hg 5367 3376 5485 3469 2623 4546 3423 6508 4254 6746 3361 2931 4454 6331
8 As 461.7 263.0 124.6 34.81 161.6 41.16 12.15 ------
Notes: a- Environmental Protection Agency. US Values. (USEPA; 2006) b- Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland (Dutch Target and Intervention Values, 2000 (the New Dutch List) (Esdat, 2000)
152
The 2012 results presented in Table 4.51 demonstrate that the mean concentrations of Cu and Ni in SIP exceeded the quality guidelines for all organizations, which is exactly the same as presented in the results of 2011. This is almost the same for Hg, which exceeds the PEL value of
EC (1127% in site A, 708.6% in site B, 1171% in site C, 542.9% in site D, 462.9% in site E,
745.7% in site F and 1094% in site G), ISQG-High of ANZECC (1111% in site A, 697.2% in site B, 1153% in site C, 533.8% in site D, 454.9% in site E, 733.8% in site F and 1077 % in site
G). and USEPA (6508% in site A, 4254% in site B, 6746% in site C, 3361% in site D, 2931% in site E, 4454% in site F and 6331% in site G) but is close to the intervention value of the VROM.
This is the same pattern presented by the 2011 results.
On the other hand, Cd, Pb and Zn at the SIP only exceeded the value of USEPA with the percentage of 332.4%, 103.9% and 57.73% respectively and were between (ISQG-Low) and
(ISQG-High) in ANZECC standard and between target value and intervention value of VROM criteria; except Pb is below VROM criteria and Zn is below ANZECC standard. In 2011, Pb and
Zn showed the same values; however, Cd was only over the value of USEPA in percentage of and close to the EC PEL value. Chromium (631.7%) and As (538.8%) exceeded the values of the
EC and USEPA only, and the same can be seen in the results of 2011. Again as was the case with the 2011 results, all selected heavy metals exceeded the USEPA value. By contrast, apart from two (Cu & Ni), all mean concentrations of selected heavy metals remained at the normal value of the VROM, which was the same as the results for 2011. Additionally, the Mo value is normal in the VROM value in both 2011 and 2012.
In contrast, the coastal regions (west and east of SIP) have high average concentrations of Ni which exceeded all organizations‘ standards. Table 4.51 and 4.53 shows the percentage of Ni in all organizations‘ standards. These are the same results as those found in 2011. The mean concentration of Cr to the east of SIP exceeds the PEL value of the EC (156.2% in site E, 153
180.6% in site F and 68.31% in site G), ISQG-High of the ANZECC (1087% in site E and
21.32% in site G only), and USEPA ( 683.7% in site E, 758.3% in site F and 414.9% in site G) while in site G it is below the ISQG-High value of the ANZECC and intervention value of
VROM standard, whereas in the west both sites C and D exceeded the PEL value of EC (122.1% and 49.75% respectively) and USEPA (579.3% and 358.1) but site B only exceeded the USEPA value with percentage of 179.3%. This is similar to a certain extent to the 2011 results to the east of the port but different to the west. Moreover, as was the case in 2011, the coastal regions (west and east of SIP) have high average concentrations of Hg in 2012 and exceed the PEL value of
EC, ISQG-High value of ANZECC and USEPA standards. Cadmium (253.0% in site B, 176.5% in site C and 20.59% in site D), Pb (25.17% in site B, 87.09% in site C and 21.72% in site D) and
As (232.3% in site B, 177.3% in site C and 81.49% in site D) in all sites (east &west) exceed only the USEPA value and are over the TEL in EC, ISQG- LOW in ANZECC and Target value in VRON. Comparison with the 2011 results shows that Pb and As in all sites are also within the standards of these organizations, while Cd only exceeds the USEPA for 2012. In site D west of
SIP, Cu exceeded the value of all organizations ( 203.5% in EC, 21.41% in ANZECC, 1653%
USEPA and 72.53% in VROM), in site B it exceeded the PEL value of EC (119.8%), USEPA
(1170%) and intervention value of VRON standards (24.95%), and in site C exceeded only PEL of EC (28.89%) and USEPA ( 644.4%) values, while to the east of SIP it only exceeded the PEL of EC (22.41% in site E, 63.15% in site F and 55.00% in site G) and USEPA (607.0% in site E,
842.2% in site F and 795.2% in site G) values. This also applies for the data of Cu in the 2011. In the case of Zn, it lay always within the standards of all organizations both to the east and west of
SIP. Apart from Zn, all selected heavy metals to both east and west exceeded the values of
USEPA, which is also true for the results in 2011.
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Table 4-51: Comparison of the mean concentrations of the selected heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg, Mo and As) in 2012 in the surface sediments at the sites studied with the Sediment Quality Guidelines in international organizations such as Environment Canada, Australian and New Zealand Environment Conservation Council ANZECC, Environmental Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland.
Site Study value1 2012
ECvaluea ANZECC valueb VRONd SIP West of SIP East of SIP USEPAc No. Values Metals ISQG- Low ISQG- Target A B C D E F G TEL2 PEL3 Intervention7 (Trigger High5 Value6 value)4
1 Cd 2.94 2.40 1.88 0.82 1.94 1.80 1.12 0.68 4.21 1.50 9.60 0.68 0.80 12.00 2 Cr 284.1 146.1 355.3 239.6 409.9 448.9 269.3 52.30 160.0 80.00 370.0 52.30 100.0 380.0 3 Cu 315.2 237.4 139.2 327.8 132.2 176.2 167.4 18.70 108.0 65.00 270.0 18.70 36.00 190.0 4 Ni 611.9 542.0 427.1 377.9 337.8 454.2 476.2 15.90 42.80 21.0 51.60 15.90 35.00 210.0 5 Pb 61.59 37.80 56.50 36.76 41.74 88.20 54.60 30.20 112.0 50.0 218.0 30.20 85.00 530.0 6 Zn 195.6 39.70 53.40 17.30 80.14 38.50 38.10 124.0 274.0 200.0 410.0 124.0 140.0 720.0 7 Hg 8.59 5.66 8.90 4.50 3.94 5.92 8.36 0.13 0.70 0.15 0.71 0.13 0.30 10.00 8 As 46.25 24.06 20.08 13.14 29.78 10.64 8.62 7.24 41.60 20.00 70.00 7.24 29,00 55.00 9 Mo 4.48 2.02 1.82 3.42 2.40 2.40 1.68 10.00 200.0 Notes 1 Mean concentrations of metals at SIP, West and East SIP (2012) 2 TEL, threshold effect level 3 PEL, probable effects level 4 ISQG-Low, Interim Sediment Quality Guidelines - Low: Probable effects concentrations below which biological effects would rarely occur 5 ISQG-High, Interim Sediment Quality Guidelines - High: Probable effects concentrations below which biological effects would possibly occur. Concentrations above these values represent a probable-effects range within which effects would be expected to frequently occur 6 Indicate the level that has to be achieved to fully recover the functional properties of the soil for humans and plant and animal life 7 Functional properties of the soil for humans, plant and animal life, is seriously impaired or threatened c- EC, Environment Canada. (Burton, 2002) d- (ANZECC) ANZECC, Australian and New Zealand Environment and Conservation Council. (Burton, 2002) e- Environmental Protection Agency. US Values. (USEPA; 2006) f- Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland (Dutch Target and Intervention Values, 2000 (the New Dutch List)(Esdat, 2000)
155
Table 4-52: Percentage excess of Sediment Quality Guidelines in Environment Canada (EC) and Australian and New Zealand Environment Conservation Council (ANZECC) in 2012 for Cr, Cu, Ni, Hg, and As.
Site Study value 2012 % samples which exceeded % samples which exceeded PEL EC ISQG-High ANZECCb
No. Metals A B C D E F G A B C D E F G
1 Cr 77.56 ------122.1 49.75 156.2 180.6 68.31 ------10.78 21.32 ------
2 Cu 191.9 119.8 28.89 203.5 22.41 63.15 55.00 16.74 ------21.42 ------
3 Ni 1330 1166 897.9 782.9 689.3 961.2 1013 1086 950.4 727.7 632.4 5547 780.2 822.9
4 Hg 1127 708.6 1171 542.9 462.9 745.7 1094 1111 697.2 1153 533.8 4549 733.8 1077
5 As 11.18 ------Notes: a- EC, Environment Canada. (Burton, 2002) b- (ANZECC) ANZECC, Australian and New Zealand Environment and Conservation Council. (Burton, 2002)
156
Table 4-53: Percentage excess of Sediment Quality Guidelines US Environmental Protection Agency USEPA, and Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland in 2012 for Cd, Cr, Cu, Ni, Pb, Zn, Hg, and As.
Site Study value 2012 % samples which exceeded % samples which exceeded EPAa Intervention VRON
No. Metals A B C D E F G A B C D E F G 1 Cd 332.4 2253.0 176.5 20.59 185.3 164.7 64.71 ------2 Cr 443.2 179.3 579.3 358.1 683.7 758.3 414.9 ------7.868 18.13 ------3 Cu 1585 1170 644.4 1653 607.0 842.2 795.2 65.89 24.95 ------72.53 ------4 Ni 3748 3309 2586 2277 2024 2757 2894 191.4 158.1 103.4 79.95 60.86 116.3 126.8 5 Pb 103.9 25.17 87.09 21.72 38.21 192.1 80.79 ------6 Zn 57.73 ------7 Hg 6508 4254 6746 3361 2931 4454 6331 ------
8 As 538.8 232.3 177.3 81.49 311.3 46.96 19.10 ------
Notes: a- Environmental Protection Agency. US Values. (USEPA; 2006) b- Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland (Dutch Target and Intervention Values, 2000 (the New Dutch List) (Esdat, 2000)
157
Table 4.54 shows comparison of the concentrations of the heavy metals (Cd, Cr, Cu, Mn, Ni, Pb,
V, Zn, Hg and As) between the current study and the study conducted by Al-Shuely et al., (2009) in Harmul and Majis. The minimum concentrations of Cd, Pb, Zn and Hg in this study were
1.94 ppm in site E, 31.40 ppm in site B, 31.00 ppm in site B, and 3.50 ppm in site E, respectively. There was no data presented by Shuely et al., (2009) for Cd, Pb, Zn and Hg.
The current study has recorded significantly higher concentrations of Cr, Cu, Mn, Ni, V and As, being minimum levels recorded were 98.80 ppm in site B, 96.80 ppm in site E, and 442.0 ppm in site B respectively, while the maximum levels obtained by Shuely et al. (2009) were
0.06377 ppm in Harmul, 0.002685 ppm in Majis and 0.1271 ppm in Harmul.
Table 4-54: Comparison of the concentrations of the heavy metals (Cd, Cr, Cu, Mn, Ni, Pb, V, Zn, Hg and As) between the current study and the study conducted by Al-Shuely et al., (2009) in Harmul and Majis.
Cd Cr Cu Mn Ni Pb V Zn Hg As Site Ba 2011 2.00 98.80 200.7 442.0 657.5 31.40 68.30 31.00 4.50 26.30 Site Ba 2012 2.40 146.1 237.4 533.9 542.0 37.80 92.00 39.70 5.66 24.06 Site Ea 2011 2.50 565.2 96.80 112.5 384.9 33.10 109.5 59.50 3.50 18.90 Site Ea 2012 1.94 409.9 132.2 169.7 337.8 41.74 133.46 80.14 3.94 29.78 Harmulb No No 2009 data 0.06377 0.002685 0.1271 0.08367 No data 0.003107 No data data 0.008911 Majisb No No 2009 data 0.02115 0.001214 0.05633 0.03722 No data 0.001845 No data data 0.009563 Notes
a. Current study. b. Alshuealy et al., 2009 study.
158
From the comparison between current study and the study conducted by Al-Shuely et al. (2009), it was found highly significant difference (P<0.01) in the concentration of metals between two studies, being higher in the current study. The sampling process of the current study was during
2011 and 2012, while the sampling process of the study of Al-Shuely et al. (2009) was during
2005 where the SIP was in the infant stages with few numbers of industries mainly petrochemical such as refinery. The first production of the refinery was in 23 of June 2006
(Al watan.com, 2006). The companies operating at SIP during the sampling process of the current study were significantly higher compared with the period where the sampling was conducted for the study of Al-Shuely et al. (2009), including metal processing industries, different petrochemicals industries and polypropylene plant, aromatics plant, methanol plant, urea fertilizer plant, aluminum smelter, iron pelletizing plant, fully-integrated steel plant, power generation plant and many other processing and distribution industries (Oman Establishment for
Press Publication and Advertising, 2011& 2014). The number of shipment and transportation processes within the SIP and surrounding areas were significantly higher during the period of this study compared with year 2005. The number of ships has increased 556 to 1,964 during
2007 and 2013, respectively, as demonstrated in figure 3-2 in chapter three. Furthermore, hazardous wastes storage and open disposal areas are within the SIP of nearby surrounding areas, and feed-water and cooling water supplies are drained onto the ocean through the outfall channel within the SIP area. This channel discharges an estimated 334,000 m3/hour of seawater (SIPC personal communication, 2012). The layout of the SIP in Figure4-29 shows the co-location of industrial production facility 2005 and Figure4-30 shows the co-location of different industrial production facilities after 2010. Moreover, as discussed before in chapter three all wastewater within the SIP is disposed of by discharging it through the cooling water return channel.
159
In relation with all these above factors, it is expected that the concentrations of the heavy metals in the SIP and surrounding areas especially site B (Harmul) and site E (Majis) to be higher in the current study compared with 2005 demonstrated in the study published by Al-Shuely et al.
(2009).
Figure4-29: The layout of the SIP showing the co-location of one industrial company
in 2005. (Source: SIPC)
160
Figure4-30: The layout of the SIP showing the co-location of different industrial
production facilities till 2013. (Source: SIPC)
As can been seen from the Table 4.54 there are significant increases in contamination levels between 2009 and 2011/12. Whilst the methods adopted in Al-Shuely et al. 2009 and the current study was broadly comparable, care should be taken in comparing these data sets. Having said this, the size of the increase is of concern. Activity in the port is due to increase over the coming years and further evaluation of contamination levels over time is recommended (see Chapter 6).
161
4.5 Conclusion:
The statistical analysis shows that the port (site A) has the highest mean concentrations of heavy metals Al, Cd, Cu, Fe, Mo, Ni, Zn, As, Sn compared to all other sites in both 2011 and 2012.
Highest mean concentrations of Mn were observed in site B. Site E has higher mean concentrations of V and Co, while site F has higher mean concentrations of Cr. Some heavy metals were higher in 2011 in some sites and then increased in different sites during the subsequent year. For example, in 2011 site A had the highest mean concentrations of Hg but in
2012 it became site C. Lead was highest in site G in 2011, but in 2012 this was site F.
The data obtained in this study indicate that eight heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg, As) exceeded the International Sediment Quality Guidelines (ISQG) for international organizations such as Environment Canada (EC), Australian and New Zealand Environment Conservation
Council (ANZECC), the US Environmental Protection Agency (USEPA) and Ministry of
Housing, Spatial Planning and the Environment (VROM) Netherland. It seems that all the above heavy metals in all sites exceed the USEPA standard except for Pb in site D, and Zn in sites B,
C, D, E, F and G in both 2011 and 2012. Nickel exceeds all ISQG in both 2011 and 2012. The mean concentration of Cu at the port exceeded all ISQG in 2011and 2012 too. In 2011 the mean concentration of Cr exceeded all ISQG, but in 2012 it exceeded only the EC and USEPA standards. Mercury exceeded all ISQG except the VROM standards during both 2011 and 2012.
162
Chapter Five Discussion
163
5 Chapter 5: Discussion 5.1 Introductions
The aim of this chapter is to discuss the results of heavy metals obtained from sediment samples at SIP site and surrounding sites during 2011 and 2012.
The chapter has been divided into the following two sections:
i. Evaluate the risk assessment from pollutants at SIP and its surroundings (Section
5.2)
ii. Sources of pollution in the SIP region using a combination of field data and
inventory data (Section 5.3)
iii. Conclusions (Section 5.4)
164
5.2 Risk assessment of SIP and its surroundings
This section will highlight the risk assessment of the area that already exceeds the ISQG by using the results of the current research.
Risk assessment is an important framework that provides a means for a structured review of information relevant to estimating health or environmental outcomes. It is the expected value of undesirable consequences on hazard (Griffin, 2009).
The beach system of SIP comprises of an industrial outlet and major wadi outlets. The industrial outlet passes through different petrochemical and metal factories before discharging into the SIP beach. wadi outlet systems pass close to the rapidly growing city of Sohar, as well as some which pass through the local industrial area.
Considered the main deposition site for heavy metals in coastal and marine environments, numerous studies have been undertaken to assess the heavy metal contamination of harbor sediment as a result of human activities (Denton et al., 2005; Guerra-Garcia and Garcia-Gomez,
2005; Ashley and Napier, 2005; Sprovieri et al., 2007; Zonta et al., 2007; Huerta-Diaz et al.,
2008; Cukrov et al., 2011; Popadic et al,. 2013). Metal concentrations in sediment are not only a suitable indicator of pollution (De Lucaa et al. 2004, Denton et al., 2005; Guerra-Garcia and
Garcia-Gomez, 2005; Sprovieri et al., 2006; Zonta et al., 2007; Huerta-Diaz et al., 2008; Cukrov et al. 2011) but the physical movement and chemical interactions within the sediments can also control the transportation and storage of these hazardous metals and therefore the degree of risk they represent to the environment and people consuming sea food (Kilemade et al., 2004; idris et al. 2007; Liu et al. 2010).
165
5.2.1 Heavy metals exceeded international sediment quality guidelines in this study
Presently, one of the most concerning pollutants around the world is heavy metals. Unlike the natural wadi and river systems, a large proportion of heavy metal pollution present in coastal sediments is not associated with the original geological strata. In the current study, a total of 45 sediment samples were taken from the SIP and surrounding areas. As mentioned early in Chapter
Four, no national standard related to heavy metal pollution is available, so international reference values have been used to assess the risk. Chemical compositions of these sediment samples show higher concentrations of several heavy metals, which exceeded some international standards.
This study compared the results obtained with the International Sediment Quality Guidelines
(ISQG) for several international organizations including the guidelines of Environment Canada,
Australian and New Zealand Environment Conservation Council (ANZECC), United States
Environmental Protection Agency (USEPA), and the Ministry of Housing, Spatial Planning and the Environment (VROM) Netherland.
There are a number of reasons for the occurrence of heavy metals at the SIP and surrounding areas. The industrial activities at the port provide the vital source of pollution from fugitive dust from stockpiles, dumping of waste and wastewater discharges, as well as possible contamination from wadi systems passing through mining, factory and local industrial areas and the growing city of Sohar and surrounding cites. Tables 4.48 and 4.49 in Chapter Four show the comparison of the mean concentrations of the selected heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg, As and Mo) in the surface sediments during 2011 & 2012 at the study area with the above ISQG. The 2011&
2012 results presented in Maps (Figures 5.1- 5.8) demonstrate the mean concentrations of the selected heavy metals that exceeded ISQG as discussed in Chapter Four. Moreover, the comparison of mean concentrations of Mo with ISQG in sites presented in figure 5.9.
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5.2.1.1 Cadmium
In this study, Cadmium was higher than USEPA standard at all sites, both 2011 and 2012 (Figure
5.1). However, it was lower than the exceeding value for most heavy metals compared with all other guidelines. Cadmium and its compounds are highly toxic and usually carcinogenic and have been designated as one of the most hazardous substances in industrial processes (Jinadas et al. 2014). According to the Agency for Toxic Substances and Disease Registry (ATSD) in
United State, Cd is number seven in the list of the hazardous substances (ATSD, 2013).
In humans, Cd and its compounds are extremely toxic by ingestion and inhalation. Cadmium and its compounds are used in the manufacture of electronics, lightings, pigments/paints, polymer stabilizers, alloys, and ceramics (Ayres and Hellier, 1998). In many countries a number of directives have been issued to reduce or eliminate the use of cadmium. Acute ingestion of cadmium concentrations above 0.1 mg/kg/day produces symptoms of nausea, vomiting, abdominal cramps, muscle pain and headache. Inhalation of Cd dust may cause chronic lung diseases. Long-term exposure to Cd may affect body organs and systems, especially the kidneys, chronic rhinitis and pharyngitis, nasal bleeding, increased risk of lung and prostate cancer, and reduces the activity of the digestive enzymes trypsin and pepsin in the stomach (Burton, 2009).
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Figure5-1: The mean concentrations of Cd that exceeded ISQG in sites.
5.2.1.2 Chromium
Chromium was high in terms of almost all international guidelines in both 2011 and 2012 except in sites D, B and G, which were low as per ANZECC and VROM (Figure 5.2). Chromium is a common element, and the main anthropogenic sources of chromium in the environment are the oil industry, chromium steel manufacture, the textile industry, industrial effluents enriched in sewage sludge, and the building industry. Chromium is very important to the health of living organisms.
Although Chromium is probably the least toxic of the trace elements, severe nephron toxicity is due to acute exposure to the metal, and this will cause renal failure and probably death (Ayres and Hellier, 1998).
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Figure5-2: The mean concentrations of Cr that exceeded ISQG in sites.
5.2.1.3 Copper
Copper was found higher, as per all guidelines, in site A and D (Figure 5.3). Site A is the SIP core area where Cu input can be from industries. Site D may be affected by wadi runoff from Cu mining. Copper is one of the elements known to be essential to humans. It occurs in different proteins, such as galactose oxidase, ceruloplasmin, super oxide dismutase and haemocyanin.
However, intake above 100 mg/kg is toxic to humans. Copper has the ability to block sulfhydryl group in proteins and enzymes, which is an important factor in the toxicity. Chronic exposure to copper or its salts is known to cause disturbances of the liver, kidney and nervous systems, as well as ulceration and perforation of the nasal septum. Various diseases like cardiovascular ones have been related to contaminated drinking water. The rare genetic disorder Wilson‘s disease is also associated with Cu. Copper enters the environment through many ways including copper 169 mining and industries, and through manufacturing of wire, alloys, electrical and plumbing materials(Ayres and Hellier, 1998).
Figure5-3: The mean concentrations of Cu that exceeded ISQG in sites.
5.2.1.4 Nickel
Nickel was found higher as per all guidelines available at all sites (Figure 5.4). Nickel enters the environment through electrical components, alloy production, steel industries, batteries and heating elements containing batteries. Metallic Ni and Ni compounds are carcinogenic in experimental animals. The carcinogenicity of Ni in humans has been shown from workers employed in factories related to nickel matte, nickel copper matte and in the extraction of nickel salts (Ayres and Hellier, 1998). At SIP, Ni is used or emitted from various processes including fertilizer production and the refinery, and is present in high concentrations in catalysts (also see table 5.1). The current research results indicated high risk as it exceeded international standards at all areas. A management plan to prevent further Ni contamination is urgently needed. 170
Figure5-4: The mean concentrations of Ni that exceeded ISQG in sites.
5.2.1.5 Lead
Lead was only higher as per USEPA guidelines in all sites (Figure 5.5). Lead is a non-essential element, and is a cumulative poison that is built up in tissues and organs and eventually reaches a point at which symptoms and disabilities occur (Ayres and Hellier, 1998). On the ATSDR‘s list,
Pb is number two of the top 20 list (ATSD, 2013). Reports from various studies have documented that marine pollution by Pb metal may have played a role in poisoning and in the decline of various populations of coastal and marine life in various parts of the world (Zauke et al., 2003; Jeffree et al., 2006; Kannan et al., 2006; Harper et al., 2007; Kojadinovic et al., 2007;
Storelli et al., 2008). Once Pb is inside the body, through either inhalation or ingestion, there are two major effects which happen immediately, namely effects on the formation of blood due to the interference in the activity of enzymes responsible for blood formation, and effects on the
171 central nervous system (Jinadas and Ahmad, 2014). A major source of emission of lead from SIP in the environment is the emission from fuels and refineries.
Exposure to Pb in humans can result in a wide range of biological effects, depending on the level and duration of exposure, including injury to the brain, kidney and nervous system. Lead performs no known essential function in human physiology. Various effects occur over a broad range of doses, with infants and young people being more sensitive than adults. Lead is a particularly dangerous chemical in ecology, as it can accumulate in individual organisms and in entire food chains (Wuana and Okieimen; 2011).
Figure5-5: The mean concentrations of Pb that exceeded ISQG in sites.
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5.2.1.6 Zinc
Zinc exceeded USEPA guidelines at site A only (Figure 5.6). Zinc is essential for human health and lack of Znin the body causes birth defects (Wuana and Okieimen; 2011). The toxicity of Zn and its compounds to humans and animals can cause clinical symptoms and acute/chronic poisoning (Ayres and Hellier, 1998). It seems from the figures that area A is polluted by Zn due to industrial activities. However, future plans for expansion of SIP activities bring with them a high risk of Zn contamination. Environmental management plans must be in place to prevent all sources of Zn pollution.
Figure5-6: The mean concentrations of Znthat exceeded ISQG in sites
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5.2.1.7 Mercury
Mercury exceeded all international guidelines in all sites, except the VROM standard (Figure
5.7). Mercury is in the number three of the ATSD list of the hazardous substances (ATSD,
2013). Mercury is a non-essential element in biological systems, but has been found to accumulate in some fish by 10,000 bio-concentration factors (Ayres and Hellier, 1998). Mercury is bio- accumulated in tissues and shows bio-magnification in the food chain because of its slow excretion from the body (Nigro and Leonzio, 1996). Mercury has wide applications in modern industries and agriculture, which are believed to be the main sources of it in the environment.
Figure5-7: The mean concentrations of Hg that exceeded ISQG in sites
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5.2.1.8 Arsenic
Arsenic was only higher than the norm as per USEPA guidelines in all sites (Figure 5.8).The main sources of arsenic are lead and copper supplied ores. Arsenic is generally found as a mixed supply •arsenide, or with other metals such as gold, silver, iron, cobalt and nickel (Ayres and
Hellier, 1998). The situation at SIP is ideal for the production of As as it enters the environment through steel, iron productionand manufacturing of chemicals and glass (Baby et al., 2010).
Arsenic is in the top of the ATSD list for hazardous substances (ATSD, 2013). Air borne emissions of As can be from copper mining and industries, smelting, coal burning, and land fill wastes of copper flue dusts and coal fly ash. The situation at SIP is ideal for the contamination of As, as it enters the environment through iron and copper production and processes. Arsenic is found in plants and animals in minute quantities. In humans, small concentrations are very toxic when present in tissues at <0.3ppm and in blood at <0.004mg/l
(Ayres and Hellier, 1998).
Figure5-8: The mean concentrations of As that exceeded ISQG in sites
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5.2.1.9 Molybdenum
Molybdenum did not exceed any international value as per Figure 5.9. The potential source of
Mo in the environment is coal burning (Jacobson, 2002), which is not consider among the main sources of pollution at SIP or surrounding areas. Caution should be taken to accelerate its presence in the environment, as higher than normal levels of Molybdenum compounds are toxic to humans, animals and plants (Ayres and Hellier, 1998).
Figure5-9: The comparison of mean concentrations of Mo with ISQG in sites
Using the current research results and international guidelines, the sediment samples of SIP and its surrounding areas are found to be polluted with most of the heavy metals studied. This distribution of heavy metals in the area in the coastal sediments strongly indicates anthropogenic input in the form of wastewater outlets, wadi systems‘ discharge and fugitive dust and atmospheric disposition directly from industrial stacks or uncovered materials from waste storage areas surrounding the SIP area, as is clear from the photos (Figure 5.10- 5.20). Although
176 limited published results are available from SIP and the surrounding areas, the current results show significant increases compared with a previous study conducted by Al-shuely et al (2009).
Thus, initially it could be concluded that the anthropogenic inputs may have caused the elevated readings of Cd, Cr, Cu, Ni, Pb, Zn, Hg and As in the coastal sediment of SIP and the surrounding areas. The toxicological threshold levels of these elements are above international guidelines
(figures 5.1-5.8). The situation raises concerns about the latent adverse effect on public health and environmental quality of Sohar City and the surrounding areas. The quality of life has already been affected; communities at Sohar and nearby areas are suffering from fumes, dusts, chemical odours and poor visibility because of emissions from SIP (see figures 5.28 to 5.31 in section 5.3). In these exposed inhabitants at Sohar and surrounding areas, excess accumulation of heavy metals in outdoor dust can directly threaten the well-being of people via ingestion, inhalation and skin contact routes. Future studies related to human contamination risks are therefore needed.
Figure5-10: Iron ore store at SIP (source Company 1)
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Figure5-11: Work accident and chemicals escape at SIP (source Company 2).
Figure 5-12: Waste material stores from SIP Companies outside to the West (source: liwa
Resident group).
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Figure5-13: Stock of petrochemicals waste outside SIP to the West (source: LiwaResident group).
Figure5-14: Stock of petrochemicals waste outside SIP to the West (source: Liwa Resident group).
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Figure5-15: Stock of different chemicals waste outside SIP to the West (source: Liwa Resident group).
Figure5-16: Waste disposed of in an open area outside SIP to the West (source: Liwa Resident group).
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Figure5-17: Chemical waste disposed of outside SIP to the West (source: Liwa Resident group).
Figure5-18: Chemical Waste which has been absorbed (source: Liwa Resident group).
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Figure5-19: Polluted areas due to chemicals waste (source: Liwa Resident group).
Figure5-20: Waste from a water treatment plant outside SIP to the West (source: Liwa Resident group).
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As per these photos, an important aspect of public health protection is the prevention or reduction of exposure to environmental agents that contribute, either directly or indirectly, to increased rates of discomfort, disease or death (Kelepertzis, 2014). There are many chemicals used by industries in different processes and applications. Despite the important economic and social benefits of chemicals, when misused they may cause adverse effects on human health and environmental integrity (Bouwman, 2012). It is therefore recognized that the assessment of risks from exposure to chemicals is among the highest priorities in pursuing the principles of sustainable development (WHO, 2009).
5.2.2 Environmental and health risk perspective:
A considerable number of publications exist in the scientific literature documenting the effect of industrial emissions on human population (Kilemade et al., 2004; Idris et al. 2007; Liu et al.
2010; Salim and Driss, 2014; Ayeni, 2014; Hawrami and Hassan, 2014; Martin et al., 2015).
From a human health risk perspective, some evidence exists that the prevalence of leukemia in children, lung, kidney, nervous system, urolithiasis, and cancer diseases is relatively higher in inhabitants closer to industrial emissions (Linos et al., 2011; Kelepertziz, 2014; Martin et al.,
2015). Studies must be established to assess the potential health risks of human exposure to multiple environmental contaminants from SIP via air, soil, and water. Metals that enter human body are carried by blood to proteins, where they move first to the liver (Edwards et al., 2001).
They can bio-accumulate over time to reach sub-lethal, or even lethal levels, and then are gradually accumulated into other tissues including kidneys and reproductive organs unless they are excreted or detoxified (Fent, 1996).Toxicity of ingested heavy metals has been an important human health issue for decades. The prevalence of contamination from both natural and
183 anthropogenic sources has increased concern about the health effects of chronic low-level exposure. Anthropogenic sources of heavy metal contaminants are likely to be the cause of the human health and ecological problems.
Metals that exceed ISQG have higher potential risk of contamination and may cause human health problems at the SIP and surrounding areas. Many people in these areas could be at risk of adverse health effects from inhalation or consuming common local vegetables grown in contaminated soil, or consuming sea food products. To our knowledge the condition of soil in
Sohar and surrounding areas is unknown or undocumented because of lack of studies and research; therefore, exposure to toxic levels from elevated heavy metal concentrations can occur without being noticed. In the population, the most affected by heavy metal toxicity are pregnant women or very young children (Devanath et al, 2009). Diseases like neurological disorders, central nervous system (CNS) destruction, and cancers of various body organs are reported to have increased in these areas during the past 10 years which may indicate that these are some of the effects of heavy metal poisoning which occur. Low birth weight and severe mental retardation of new born children have been reported elsewhere where the pregnant mother ingested or inhaled high concentrations of toxic materials (Devanath et al, 2009).
Humans are dependent upon ecosystem services such as air, water, soil for food and provision of materials for development and construction. The importance of these services cannot be under estimated. However, a wide range of natural systems and environmental services have been altered, eroding their capacity to deliver services for human well-being. Lack of effective management of our industrial zones to ensure sustainability of the environment and human health remains the biggest challenge of our time. This is threatening the stability and prosperity of the communities surrounding these industrial and economic zones. Governors of these industrial areas and economic zones still struggle in their endeavors to ensure sustainable 184 development and environmental protection. Poor environmental quality has many economic costs associated with it, including health-related costs. Industrial activities are important sources of pollution and a growing cause of environmental degradation and water pollution. In most of the industrial areas in Oman, water is used in the industrial processes in one way or another, and this water is typically returned in a degraded condition and SIP is no exception in this regards, where treated wastewater outlets discharge into the sea facing a leak of some catalysts in some case. This discharged outlet water alters the characteristics of coastal water quality, such as its acidity, turbidity and as shown here heavy metal contamination. Impacts can be heightened by the synergistic combination of contaminants which may increase sediment metal contents and affect various species communities and may reach human food through food chains. The condition can cause an impact on human health through consumption of fish resources. Indeed, the communities inhabiting these areas are mostly dependent on fisheries and fish protein is one of the important sources of protein.
In SIP, industrial pollution is expected to increase in an emerging market economy with industrial development and a shift of cargo shipments from Sultan Qaboos Port (SQP) to SIP
(Oman Establishment for Press Publication and Advertising, 2014). Rapid economic and industrial growth should not however cause a negative impact on environmental quality and human well-being in SIP‘s surrounding areas. Industries based on metals and mining processes represent the major risk for heavy metal releases. Indeed, heavy metals from SIP discharges and dust emissions represent a vital hazard source that cause vast environmental degradation and can accumulate in the tissues of humans, plants and other organisms. This is despite there being increased use of EIA processes in the Sultanate of Oman to address the environmental issues during project developments.
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While both hazard and risk assessments involve the integration of exposure and effects assessments, risk assessment also contains estimates of the probabilities of adverse effects. This distinction between hazard and risk is not well recognized in EIA requirements and as a result the term ecological risk assessment often is used very broadly to refer to any process that determines potential adverse ecological effects resulting from human activities. Hazard identification involves the use of exposure and requires data from scientific research and observations to determine the agent of concern and whether it can cause a particular adverse health effect (USEPA, 2002). However, the breadth and complexity of most ecological systems may require considerable efforts to define the scope of the problem. In human health assessment, risk assessors conduct an exposure assessment to measure or estimate the magnitude, frequency and duration of exposure, and to characterize the human populations that are subject to exposure.
The process must be conducted in depth specifically in the Sohar area as well all surrounding SIP areas that have higher potential of receiving materials from SIP industries and processes.
The SIP in future is projected to host many more thousands ships, staff, workers, residents, and vehicles, which will consume large amounts of electricity, potable water and other resources.
Additionally, ever-increasing amounts of minerals, hazardous chemicals, paper, and other material resources will be used to support industrial and commercial activities. The city of Sohar and surrounding towns are developing ever-faster. Correspondingly, this community produces several thousand tons of waste every month, an amount which is increasing in line with population, commercial and industrial growth. Other expected or known environmental changes will include rising pollution of the air, soils, ground and surface waters, and the sea. Therefore, as per the research data and comparison with international guidelines and the accompanying photographs, it is apparent that SIP requires further studies to investigate the health risk assessment on populations surrounding the SIP. The issue of pollution and social well-being in
186 the investigated area should be included in the future study .Specific objectives of the proposed study should include the possible influence of human activities at SIP on the quality of the environment (air, soil and water) by applying statistical techniques and benchmarking environmental (air, soil, and water) chemical composition against data obtained from background environments. The study should also investigate the potential health risk to inhabitants surrounding SIP and evaluate the most significant pollutants and exposure pathways with regards to human health. Any future research should investigate all pathways of exposure to determine the potential environmental and human health impacts that may arise from heavy metal contamination.
After reviewing the results of this study, some recommendations requesting strong action to be implemented are listed in Chapter Six. Amongst the recommendations, the highest priority areas where the MECA & SIPC need to take immediate action are noted.
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5.3 Sources of pollution in the SIP region using a combination of field data and inventory
data
A theoretical finger printing method was used to determine the sources of heavy metals in all sites by using the results of the current research and the list of chemicals that are used in the processes of different companies at SIP.
Table 5.1 shows a list of chemicals that are used in the process and laboratories‘ analysis of different companies at the SIP. It demonstrates that Company 2 (C.2) uses all chemicals under study in its processes and production, followed by Company 1 (C.1) which uses almost 58% while company 4 (C.4) utilizes 42% of the 19 chemicals under study. This last company does not
- use chemicals Cd, Co, Cu, Zn, As, Sn and Br .
In terms of chemicals, Cl- is the most common used among companies (C.1, C.2, C.4, C.5 &
C.6), accounting for 62.5% of the total companies. Moreover, Al and Mn are used by four companies as presented in the table, totaling 50% of the total companies. By contrast, Cr, Fe,
- -2 Mo, V, F & SO4 are only used by three companies.
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Table 5-1: List of chemicals used at SIP by different companies.
Parameters C.1a C.2b C.3c C.4d C.5e C.6f C.7g C.8h
Al (Aluminium) ✓ ✓ ✓ ✓ Cd (Cadmium) ✓ ✓ Co (Cobalt) ✓ Cu (Copper) ✓ ✓ ✓ Cr (Chromium) ✓ ✓ ✓ ✓ Ni (Nickel) ✓ Fe (Iron) ✓ ✓ ✓ Mn (Manganese) ✓ ✓ ✓ ✓ Mo (Molybdenum) ✓ ✓ ✓ Pb (Lead) ✓ ✓ ✓ V (Vanadium) ✓ ✓ ✓ Zn (Zinc) ✓ ✓ Hg (Mercury) ✓ ✓ ✓ As (Arsenic) ✓ Sn (Tin) ✓ - F (Fluoride) ✓ ✓ ✓ - Cl (Chloride) ✓ ✓ ✓ ✓ ✓ - Br (Bromide) ✓ 2- SO4 (Sulphate) ✓ ✓ ✓ Notes:
a. C.1: Company 1 b. C.2: Company 2 c. C.3: Company 3 d. C.4: Company 4 e. C.5: Company 5 f. C.6: Company 6 g. C.7: Company 7 h. C.8: Company 8
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5.3.1 Sources of Pollution at SIP and surrounding areas
This section discusses the possible sources of heavy metals at the study sites. Each element used by companies at SIP is individually considered (Table 5.1) to determine their possible sources.
The studied area at SIP and surrounding has various potential sources of pollution. Petrochemical industries are leading polluter sources around the world (Griffin, 2009). In addition to petrochemical industries at SIP, there are various metal processing industries, which are expected to be the main sources of heavy metal pollution within the port and surrounding areas. Other possible potential sources are cooling water outfalls as well dust emissions from industries within SIP and hazardous storage sites outside SIP. Various reports have shown that roadways and automobiles are one of the possible sources of contamination of pollution and heavy metals in urban runoff (USEPA, 1995&2002). The discussion in this section will cover anthropogenic sources and geochemical sources at SIP and surrounding area.
5.3.1.1 Anthropogenic Sources:
Anthropogenic sources are caused by human activities such as mining, industry, agriculture, and construction of urban development‘s (Sany et al., 2011). This section will focus in industrial activities at SIP and surrounding area and domestic sources.
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5.3.1.1.1 Industrial Sources:
5.3.1.1.1.1 Sources of Aluminum:
Based on the study results (Figure 4.1, Chapter Four) that show the mean concentrations of Al in
2011 & 2102, the highest concentration of Al is in the port compared to the all sites. The source of Al in these sites might be related to the fact that four companies are using this element (C1,
C2, C3 & C4) in their processes and site A is close to the SIP wastewater outfall to the sea.
Moreover, SIPC has a channel to provide companies‘ industrial water from Majis Industrial
Services Company (MISC). MISC is responsible for industrial water, and most companies at SIP use this channel to discharge their wastewater to the sea. Figure 5.21 shows the Outfall discharge from the one company at SIP to the main channel and to the sea. Moreover, company C4 produces aluminum in its processes. It uses different raw materials such as alumina, pitch, coke and diesel to produce various forms of aluminum, such as ingots, sows, and hot metals for export
(Figure 5.22). It used about 87 trucks every day for the transportation of aluminum products from the steel plant outside SIP into SIP. In examples of air emissions from the plant particulates of NOx, SO2, CO, tars and HF have been found. The comparative graph clearly shows that the mean concentrations of Al decrease in the East, which gives a good indicator that the port could be one of the sources of Al as East of the port is affected by the discharge of SIP waste (Figure
5.21). Moreover, Al could be delivered from the mining activities, containers and utensils, solid and liquid emissions from aluminum and other industries (Ayres and Hellier, 1998; JICA, 2001;
Al-Sulaimani, 2005).
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Figure5-21: Outfall discharge from companies at SIP to the sea (source: company C3)
Figure5-22: Production at SIP (source: company C3).
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5.3.1.1.1.2 Sources of Cadmium
The study site analysis results demonstrate (Figure 4.2, Chapter Four) that Cd has a mean concentration of 2.9 ppm in 2012 and 3.4 ppm in 2011, which is highest in the port with a declining gradient both to the West and East. The source of Cd in these sites might be related to the fact that Company 2 (C2) and Company 3 (C3) are using this element.
Muniz et al. (2004) reported that Cd contains a high risk to both aquatic and terrestrial organisms even at low concentrations. Abdul-Wahaba and Jupp (2009) stated that oil activity will introduce
Cd to the environment with concentrations around 10 ppm. The current results show the maximum value in SIP with mean concentrations of 3.4 ppm in 2011 and 2.9 ppm in 2012, therefore oil activity may be not contributing directly to Cd pollution at SIP but should not ignore it as the number of ships is going to increased due the ship cargo is moved from SIP to
SIP. Cadmium (Cd) is a component introduced to the environment by ore mining, sewage and industrial wastes (Ayres and Hellier, 1998).
Cadmium is used for domestic purposes in rechargeable batteries (Ni-Cd batteries), paints, and photography. Moreover Cd is found in diffuse sources of food - for example through storm water, detergents, body care products and food products in urban wastewater as main sources
(European Communities, 2001).
Figure 4.2, in Chapter Four, demonstrates clearly that SIP is one of the sources as the mean concentration of Cd decreases towards the downstream sites. Mohiuddin et al., (2011) reported that the possible sources of the Cd in urban areas could be sewage, deposition of organic and fine grain sediments, atmospheric emissions and industrial activity, leaches from defused Ni-Cd batteries and Cd plated items. Moreover, the yearly report submitted to MECA by Company 4 shows the content of Cd at the outfall discharge at SIP (Company 4 personal communication, 193
2014). This discharge of Cd to sea water could cause contamination to the East and West site of the SIP and thus SIP could be the source of Cd in the surrounding environment. This is consistent with the distribution of Cd as evidenced in the highest concentrations in sediments occurring at the SIP and progressively diminishing to the east and the west. Refined petroleum, phosphate fertilizers, and detergents have Cadmium as an impurity in their products. Moreover, the geochemical mobility of Cd has been increased by acid rain and the resulting acidification of soils and surface waters. Hence, the concentration of Cd be likely to increase as lake water pH decreases (Wuana and Okieimen; 2011).
5.3.1.1.1.3 Sources of Cobalt
Figure 4.3 in Chapter Four shows the mean concentrations of Co in 2011 & 2102. The results of this study indicate that the highest concentration of Co is in the East (site E). The source of this element in the East might be related to the fact that Company 2 (C2) is using this element and the discharge channel which is close to site E. It is also possible that the source of Co in this site is the wadi system from copper mining, as Co is obtained as a by-product from copper ore. The sources of the Co include plastic, detergent industry, the manufacture of alloys (welding material, steel, magnets), in the manufacture of pigments, inks and glass production and used as a catalyst in petrochemicals. It is introduced to the environment by different sources, such as sewage sludge burning of fossil fuels, by industries processing and pollution from mining and smelting (Tjandraatmadja et al; 2010).
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5.3.1.1.1.4 Sources of Chromium
It has been shown by this study‘s results (Figure 4.4, Chapter Four) that the highest concentration of Cr is in the East (sites E& F). The source of this element in this site could be related to the fact that it is used by four companies (C1, C2, C4& C6) and therefore site E is affected due to companies‘ discharge from the SIP. Furthermore, JICA (2001) and Al-Sulaimani
(2005) demonstrated that Cr could be delivered from mining activities. Hence, Cr sources in the investigated effected sites are anthropogenic and geochemical. Chromium naturally occurs in its compound form and is one of the less common elements. In the form of the mineral chromite
(FeCr2O4) Cr is mined as a primary ore product. Chromium is released from electro plating processes and the disposal of Cr containing wastes and this is the major source of Cr-
2− 2− contamination. Chromium in the form chromate (CrO4 ) and dichromate (Cr2O7 ) readily precipitate in the presence of different metal cations such as Pb2+. These forms of Cr can be absorbed by soil, especially iron and aluminum oxides.
− Under pH (<4) Cr can form complex solutions with soluble organic ligand and with NH3, OH ,
− − − 2− Cl , F , CN , SO4 and above pH 5 the solubility of Cr is low due to the form Cr(OH)3(s) where the mobility of Cr is increased. The pH of samples is over 5 which mean the mobility of Cr is increased and causes formations of Cr (OH)3(s) in the investigated area. Moreover, as the pH is over 5, the mean leak ability of Cr(VI) will increase as soil pH increases and this will lead to Cr deposited in sediments (Wuana and Okieimen; 2011).
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5.3.1.1.1.5 Sources of Copper
It has been shown by this study‘s results (Figure 4.5, Chapter Four) that the highest concentration of Cu is in the Port and the West (D, control site). The source of this element in the
SIP could be related to the fact that Company 2 (C2), Company 4 (C4) and Company 8 (C8) are using it. Copper is very important, used for growth of both plants and animals as an essential micronutrient (Wuana and Okieimen; 2011). Oxides of Copper catalysts are used as incinerator catalysts in solid form and stored in the original suppliers‘ drum packing at SIP by company 4.
The high concentration in the West (D, control site) might be due to the fact that this site is close to a wadi coming from south to west where a mining site and copper smelter are located. Figures
5.23 show a wastewater lake from the copper mining. Particularly after rain, Cu may be transported from the mining site to other stations. Figure 4 in Chapter Four shows that Cu in the investigated area increased in 2012 compared with 2011, except in SIP. This increase most probably comes from anthropogenic input carried with water runoff from Sohar mining areas and urban areas. Copper (Cu) is introduced to the environment from anthropogenic sources especially from roadways, automobiles, and from mining wastes (Förstner, 1995; Salomons,
1995; MEND, 1997; JICA 2001;USEPA, 2002; Al-Sulaimani 2005; Sakan et al 2009).
Mohiuddin et al. (2011) reported that the urban and industrial wastes could be the sources of Cu.
Moreover,(European Communities, 2001) reported that urban wastewater could be one of the Cu sources as it can be found in paints, antifouling, wood preservatives, larvicides, (copper acetoarsenite), pigments, leaching of plumbing, fungicides (cuprous chloride) and corrosion.
Therefore, the mean concentration of Cu in some sites such as A and control site G are relatively high, suggesting possible anthropogenic input such as industrial activities, mining processes and antifouling paints on the hull of boats and ships.
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Figure5-23: Wastewater Lake from the Mining process (Copper Mining)
5.3.1.1.1.6 Sources of Iron
It is shown that the Port has the highest concentration of Fe (Figure 4.6, Chapter Four), which might be caused by companies (C1, C2 & C3) who are using it in the SIP. The mean concentration of Fe decreases towards the downstream sites. In addition, mining activities, domestic sewage, roadways and automobiles could be possible sources that introduce Fe to the environment (JICA, 2001; USEPA, 2002; Al-Sulaimani, 2005; Velusamy et al., 2014).
Velusamy et al (2014) demonstrated that the increased input of organic matter and anthropogenic metals from industrial pollution will cause increased concentrations of Fe.
Company 3 at SIP has a process that imports iron ore and exports pelletized iron and iron ore.
They used different raw materials such as pellet feed, anthracite, limestone bulk, bentonite and bauxite. The raw materials required for production of pellets are iron ore fines, bentonite and anthracite as additives and natural gas as fuel energy. However, there are some preventive 197 measures taken by Company 3, including that it receives industrial water from MISC and uses a closed circle of process water without any discharge to the sea or SIPC channel, as happens with other companies (Company C3 personal communications, 2014). The transfer of materials from ships (Figure 5.23) to the yard area of Company 3 is by conveyor belts (Figure 5.24). The yard storage area is provided with a Wind Fence, spray systems and dust suppressants to control and stabilize the raw material and keep it inside. Nevertheless, it is clear from Figure 5.25 that Fe is high at the port due to the fact that large quantities of iron ore are shipped into the SIP and stored in the yard storage area at SIP. The yard storage area is an open area which can be a potential source of pollution by wind to the surrounding sites (Figure 5.26). Wind direction is affecting the distribution of the heavy metals around the pollution sources (Al- Shayeb and Seaward, 2001).
Hence, it is not surprising that the concentration of Fe is high and it is expected to increase in coming years as C3 is expected to increase the quantity of iron ore to 9 million tons per year
(Company C3, personal communications). These results demonstrate that there are some significant concentrations of pollution in the port and its source could result from the port itself.
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Figure5-24: The transfer of iron ore direct by conveyor belts to the yard area (Sources:
Company 3).
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Figure5-25: The yard storage area for iron ore at SIP (Sources: Company 3).
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Figure5-26: Iron ore distributed from SIP to surrounding areas (Source: liwa Society group)
Figure5-27: Shipping of Iron at SIP (Source: Company 1)
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5.3.1.1.1.7 Sources of Manganese
Data analyses indicate that the highest concentration of Mn (Figure 4.7, Chapter Four) is presented in the Port and to the West. This could be related to the fact that it is used by four companies (C1, C2, C6 & C8) which increase the possibility of its spread. Oxides of Manganese are used as incinerator catalysts in their solid form and stored in the original supplier drum packing at SIP by company 3. The main anthropogenic sources of the Mn comprise industrial emissions, sewage sludge, mining and mineral processing (particularly nickel), municipal wastewater discharges, emissions from the combustion of fuel additives, emission from steel, and iron production and combustion of fossil fuels (Howe et al; 2004).
In the West, the site is affected by a wadi coming from south to west where there is a mining zone process as mentioned previously. Therefore Mn is one of the listed heavy metals introduced to the environment in mining waste (Förstner, 1995; Salomons, 1995; MEND, 1997; Ayres and
Hellier, 1998: JICA 2001, Al-Sulaimani, 2005).
5.3.1.1.1.8 Sources of Molybdenum
Molybdenum is highly represented in the Port (Figure 4.8, Chapter Four) due to the fact that it is used by three companies (C1, C2 & C3). Moreover, the source of Mo might be from the use of
Mo as a metal (Iron Molybdenum) oxide catalyst in its solid phase and stored in original supplier drum packing at SIP by company 8 and used to produce formaldehyde. The level of Mo indicates that there is a trend of increasing from year 2011 to year 2012 in most studied areas (Figure 4.8,
Chapter Four). Ayres and Hellier (1998) looked at the sources of Mo from the production of mining operations and the burning of fossil fuels. Moreover, Tjandraatmadja et al (2010)
202 reported that the sources of Mo include electrical contacts, screens, chemicals and ceramics, in catalysts, pigments, the manufacture of steel and non-ferrous alloys, radio valves and lamp filaments, fertilizers and lubricants.
5.3.1.1.1.9 Sources of Nickel
The results demonstrate that Ni has significant concentrations at all study sites (Figure 4.9,
Chapter Four). This element is used by company (C2), which might cause this concentration. It may also be attributed to roadways and automobile contamination sources (diesel fuel and gasoline, lubricating oil, metal plating, bushing wear, brake lining wear and asphalt paving)
(USEPA, 2002). Nickel mining, combustion of fossil fuels, electro plating and metal plating industries are the main sources of Ni (Wuana and Okieimen, 2011) together with, probably, industrial wastewater outfall. The industrial outfall at SIP could be one of the sources that increased Ni levels. Hence, high concentrations are expected at sites close to the SIP outfall. It is also noted though that mining activities have introduced Ni to the local underground water which will flow to the coast in time and will be one of the likely Ni sources (JICA 2001, Al-Sulaimani,
2005). Nickel is used in alloy production, stainless steels and as a catalyst in industrial processes
(Ayres and Hellier, 1998). Therefore power plants and trash incinerators release Nickel to the air which then goes into the ground after undergoing precipitation reactions and which needs a long time to remove it from the air (Wuana and Okieimen, 2011).
Nickel metal exists in the form of the nickels Ni(II) ion in low pH regions. It is precipitated in the form of a stable compound as nickelous hydroxide, Ni(OH)2, in neutral to slightly alkaline solutions (Wuana and Okieimen, 2011). The other sources of Ni could also be urban wastewater, as Ni is found in protective coatings and rechargeable batteries (Ni-Cd), in the form of alloys that
203 are used in sanitary installations and food processing (European Communities, 2001).
Combustion of fossil fuels for energy production as well as vehicle transportation within SIP could add to potential sources of Ni pollution.
5.3.1.1.1.10 Sources of Lead
Lead is highly represented in SIP and East of SIP (Figure 4.10, Chapter Four) which could result from its usage by two companies (C1 & C2). Moreover, the Figure demonstrates that the concentration of Pb significantly increased in 2012 compared with the 2011 result except in site
G. These results indicate the presence of potential sources of Pb in or surrounding the SIP.
USEPA reported that roadways and automobiles are possible sources of contamination of heavy metals in urban runoff and that leaded gasoline is one source of pollution of the Pb in which it comes from auto exhausts and tyre wear. Additionally, fuel combustion, urban sewage, marine traffic, petroleum refinery, industrial effluents, municipal runoff, and atmospheric deposition could be the sources of the Pb (Muniz et al, 2004; Nasr et al, 2006; Wuana and Okieimen, 2011).
Lead (Pb) is used in different industrial production processes such as paint pigments and in PVC plastics, X-ray shielding, crystal glass production, and pesticide pipes. Hence, industrial outputs could be another source of Pb contamination. Mohiuddin et al. (2011) stated that Pb is good to use as an indicator of anthropogenic pollution such as traffic related sources or battery recycling plants. Förstner (1995), Salomons (1995) and MEND (1997) reported that mining waste is one of the sources of Pb introduced to the environment.
Interestingly, the control site has the highest mean concentration of Pb in 2012 and site F in
2011. These sites are 10 kms away from SIP, and hence are affected by Pb. The speculation is that these concentrations at sites far from SIP originated from activities related to fishery boats, 204 urban runoff from vehicle emissions, local industries and by wadi runoff from Cu mining, as before reaching the area it passes a local industrial area.
Lead is found naturally as a mineral combined with oxygen such as in PbCO3, or sulphur (PbS,
−1 PbSO4), and its range in the earth‘s crust is from 10 to 30 mg kg .
The general forms of Pb that are released into surface waters, groundwater and soils or sediments are Ionic lead, Pb(II), lead-metal oxyanion, and lead oxide and hydroxide complexes. The lead- hydroxy and Pb(II) complexes are the most stable forms.
Lead has many compounds that are insoluble such as lead carbonates, lead (hydr) oxides and lead phosphates. For example lead carbonates will form when the pH is more than 6. It is clear that pH is above 6 and lead carbonates are likely to form in the investigated sites.
Urban wastewater is the other source of Pb as it contains Pb from different products, for example certain cosmetics, old lead piping in the water distribution system on ceramic dishes and porcelain (it is banned now for use in glazes), crystal glass, solder, pool cue chalk (as carbonate) and old paint pigments (as oxides, carbonates) ( European Communities, 2001).
5.3.1.1.1.11 Sources of Vanadium
The data show that the East (site E) has a high concentration of V (Figure 4.11, Chapter Four), due perhaps to the fact it is used in SIP by three companies (C1, C2 & C5). Vanadium is introduced to the environment from oil or petroleum activities as well from ships while waiting at the terminals (Al-Rawahi, 2012). JICA (2001) and Al-Sulaimani (2005) reported that mining waste and wastewater could form the source of V pollution in the environment. Vanadium is an
205 oil related metal present mainly in the organo metallic form in crude oil (Fowler et al.,1993;
Literathy, 1993cited at Jupp and Jameison, 2004). The existence of V in sediment samples may be attributed to the illegal discharges of oily wastes from ballast tanks by tankers passing off shore en route to the Gulf (JuppandJameison, 2004). According to Fowler et al (1993)most sediment around the coasts of Oman contains over 20 ppm of Vanadium (Jupp and Jameison,
2004). Vanadium in site E has higher mean concentrations than other sites due to the fact that this site is close to the out fall from SIP and could be discharged from SIP or leakage from oil ships while they are waiting at the terminals. Moreover, west (sites B and D) of the Port has approximately the same concentration of V as in the port and this could be from distribution of V by wave action to west of SIP.
5.3.1.1.1.12 Sources of Zinc
According to the results, Zn is highly concentrated in the Port (Figure 4.12, Chapter Four). This could be the result of being used by two companies (C2 & C6). Moreover, at SIP Zn was a component of the construction material and thus it is not surprising that it is elevated in the surrounding area. Also Zn containing material was used in the construction of jetty to prevent iron from redox reaction with sea water to avoid iron corrosion. Therefore, it is expected that the concentration of Zn would be higher in the Port than surrounding area (SEU personal communication, 2014). Additionally, sources of this element could result from roadways and automobiles (tyre wear, motor oil and grease) (USEPA, 2002) and mining waste (Förstner, 1995;
Salomons, 1995; MEND, 1997; JICA 2001, Al-Sulaimani 2005) and associated with sewage
(Muniz et al; 2004). Lagerkvist, (2002) identified domestic construction and car related sources and untreated wastewater as the main sources of Zn (Lagerkvist, 2002, quoted in Mohiuddin et
206 al., 2011). Site A has the highest mean concentration of Zn, which may be due to vehicle traffic in that area and construction at SIP.
The concentration of Zn in the natural soil (crystal rocks) is about 70 mg kg−1. However, due to anthropogenic additions, Zn concentrations become unnaturally high. Wuana and Okieimen
(2011) explained that industrial activities such as waste combustion, coal, steel processing and mining, as well as food stuffs and drinking water if stored in metal tanks could cause pollution in the environment. Zinc could find its way to the wastewater from different sources such as printing inks and artists paints, coloring agents, water-proofing products, anti-pest products, insecticides, fungicide, rat poison, corrosion and leaching of plumbing, wood preservatives, deodorants and cosmetics, medicines and ointments, and antiseptic (European Communities,
2001). Regionally, de Mora et al.(2004) found the highest concentration of Zn close to the industrial area of BAPCO oil refinery in Bahrain (52.5 mg/kg) (reported by Al-Rawahi, 2012).
Al-Rawahi (2012) described the important sources of Zn in the Al Batinah costal near shore environment as being runoff, Zn-base antifouling paints, municipal wastewater and industrial effluents.
5.3.1.1.1.13 Sources of Mercury
Figure 4.65 shows that Hg is high in almost all sites of the study (Figure 4.13, Chapter Four).
This could be related to the fact that it is used in the SIP by two companies (C.1&C.2).
Moreover, the results indicate a significant contamination in the study site most probably because of mining processes that introduce Hg and accumulated in the mining waste with high concentrations. Muniz et al. (2004) reported that the sources of Hg could be fuel combustion and coal combustion. Moreover, dredging activity can also affect the bioavailability of heavy metals
207 in the disposal site, through changes in the oxidation–reduction conditions caused by removal and later deposition of material. Moreover, manometers at pressure-measuring stations could be one of the sources of Hg as releases along gas/oil pipelines. Current results shown in Figure
13,Chapter Four, indicate a slight increase in the concentration of Hg at sites C, B and A and significant increases at site G from year 2011 to year 2012. When Hg exists in the environment it occurs in different forms such as its alkylated form (methyl/ethyl mercury), mercuric (Hg2+) and
2+ mercurous (Hg2 ). Under acidic conditions HgS(s) will precipitate when pH < 4, and in this current research the pH > 4 which means HgS(s) will not precipitate.
The other source of Hg is found in urban wastewater when it enters the water. They still use Hg in dental amalgams, thermometers, old paints for water proofing and marine antifouling
(mercuric arsenate), in embalming fluids (mercuric chloride), in germicidal soaps and antibacterial products (mercuric chloride and mercuric cyanide), as mercury-silver-tin alloys and for "silver mirrors", pesticides (mercuric chloride in fungicides, insecticides) and in wood preservatives (mercuric chloride) (European Communities, 2001).
5.3.1.1.1.14 Sources of Arsenic
The mean concentration of As is highest in the SIP (Figure 4.14, Chapter Four) but decreases towards the downstream sites. This is due perhaps to being used by one company (C2). Arsenic is introduced to the environment during mining processes, glass production and from the smelting processes of zinc, copper and lead (Baby et al., 2010; ATSDR; 2011). Sources of arsenic are present in ashes from coal combustion and recovered from processing of ores containing mostly Zn, Ag, Au, Cu and Pb, and found in a wide variety of minerals, mainly as
As2O3. The speciation As (V) is dominant in aerobic environments, usually in the form of 208
3− − 2− 3− arsenate (AsO4 ) in different protonation states: H3AsO4, H2AsO4 , HAsO4 , and AsO4 . In the presence of metal cation, arsenate and other anionic forms of arsenic can precipitate.
The other sources of As in urban environments are household products such as old paints and pigments, wood preservatives, garden products, medicines and washing products, and in natural background quantities. Arsenic in urban effluents and sewage sludge exists as As (III) (arsenite) and DMAA (dimethylarsinic acid) (European Communities, 2001).
5.3.1.1.1.15 Sources of Tin
The data analysis indicates that the Port and the East have the highest concentration of Sn
(Figure 4.15, Chapter Four). Again this might be related to the fact that it is used by one company (C2). The source of Sn needs to be identified at SIP. The use of Sn compounds as anti- fouling paints for boats is now for bidden since it is highly toxic to most aquatic species, but it is still used illegally in many small boat industries and by individuals (Al-Rawahyet al., 2007).
The present results indicate that the levels of most heavy metals studied are high in different sites. There are a number of possible sources of heavy metals at the SIP and surrounding areas.
The port has different petrochemical and metal processing industries, which are expected to be the main sources of various pollutants within the port and surrounding sites. The main point sources are the cooling water outfall which contains high concentrations of pollutants (see figure
5.21). The dust emissions from the port can be expected to have a broader distribution as a result of a number of sources dispersing by prevailing winds (Figure 5.28). Figures 5.29 to 5.31 show the catalyst used in C2 is distributed to homes, cars and schools close to SIP and the identification from the supplier shows that this catalyst contains different chemicals such as
209
Iron Oxide, Aluminum, Silicate, Nickel, Vanadium and petrochemicals. In 2014, Sohar
Environmental Unit (SEU) MECA carried out an investigation when a foaming water discharge was reported. SEU discovered there was a significant leak of catalyst coming from one company at SIP. This company normally discharged 5% of catalyst on a daily basis (SEU personal communication, 2014). Therefore, this give confidence to the research data that expectation of the Fe, Al, Ni and V should be higher in the investigated area as these metals are known to be a part of the chemical composition of the catalyst.
These sources include fugitive dust from piles, transportation and stack emissions. Moreover, the occurrence of accidents at SIP may cause chemical disposal at SIP and waste from different companies within the SIP to reach outside the SIP (Figures5.32 to 5.37). These give an obvious message that the discharges from SIP, dust emissions and the dumping of waste outside SIP could be sources of heavy metals in the study area.
Figure5-28: Air emissions from SIP from different companies to the surrounding area (Source: Liwa Resident group).
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Figure5-29: Catalysts transferred to the human environment around SIP (Source: liwa Society group).
Figure5-30: Catalysts transferred to the car around SIP (Source: liwa Society group).
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Figure5-31: Catalysts transferred to homes around SIP (Source: Liwa Resident group).
Figure5-32: Accident in Petrochemical company at SIP (Source: Company 2).
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Figure5-33: Leak of Chemicals at SIP (Source: Company 2).
Figure5-34: Chemicals escape at SIP (Source: Company 2).
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Figure5-35: Petrochemical waste at SIP (Source: liwa Resident group).
Figure5-36: Effected land due to petrochemical waste at SIP (Source: liwa Resident group).
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Figure5-37: Stock of different chemicals outside SIP, to the West (Source: liwa Resident group).
There are a number of reasons explaining the occurrence of heavy metals at the port and surrounding sites. Industrial activities at the port provide a vital source of pollution from fugitive dust from stock piles, wastewater discharge and dumping, measured along the coast in the vicinity of the SIP and surrounding sites. It is obvious from the data that the Port itself is a potential source - from the wastewater discharged with the cooling water stream at the east end of the Port, as is fugitive dust from stock piles and vehicles, as well as particles from stack emissions. The distinction between these is that the cooling water outfall is a point source, whereas the dust emissions from the Port can be expected to have a broader distribution as a result of a number of sources and dispersion being in response to prevailing winds.
Determination of the source of selected heavy metals in the port was difficult because there is no related research focused on heavy metals that can be used in providing data.
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There are two distinct distribution patterns of metals across the sites. The reason for these two distinct distribution patterns in relation to the Port is not clear. The net advection of coastal sediments for the Batinah coast in the vicinity of Sohar is from east to west as a result of the balance between prevailing wave regimes (Dibajnia et al 2010; Chiffings, 2012). As a result it may be expected that there would be a bias towards higher concentrations of particulate material to the west from a source near the Port and this is clear in the mean concentrations of Al, Cr, Cu,
Mn, Mo, Ni, Pb, V, Hg and Fe. However for material sourced from the eastern side of the Port the Port infrastructure now presents a barrier to the transport of all bar the lightest of particles as they need to be carried by the relatively weak currents that occur to move from the east to the west. On the other hand, while net advection is to the west, there is some movement of material to the East of the Port as a result of the south easterly winds that occur for part of the year
(Dibajnia et al., 2010; Chiffings, 2012) and this could include both cohesive and non-cohesive sediment as the mean concentration of Fe, Ni, Pb, V, Zn, Hg and Sn is high. Moreover, wind direction is potentially affecting the distribution of the heavy metals around the pollution sources
(Al- Shayeb and Seaward, 2001).
Li. J, (2014) demonstrated that iron metals including Cd, Pb and Zn could be discharged into river from smelting and steel plants. Rainfall is also one of the sources could transport metals from the main sources to the river (see figure 5.38). The author suggested that higher concentration of the Cd and Ni might be ascribed to the effluents of different of industrial plants, such as leather factory, flour mill, oil refining plants, scattered along the river. In the current study, SIP area has different metal smelting, steel plants and petrochemicals companies, therefore the influence of these industries could be increasing discharge of metals including Pb
Zn, Ni and Cd in the SIP area and surrounding coastal regions.
216
Figure5-38: Rain and wadi discharge to the sea (Source: liwa Society group).
Buruaem et al; (2012) have demonstrated that the port causes different environmental impacts on the coastal region for example (1) waste generation; the discharge of contaminants, for example wastewater and sewage, petroleum and its derivatives; and compounds that are released by antifouling paints; (2) the construction of jetties, which can change sediment transport; and (3) the introduction of exotic species to the community through ballast water. They discussed the case of Pecem harbor during jetty installation, with heavy sedimentation in the southeast and erosion on the northwest end of the structure with shoreline reduction caused by interruption of sediment transport. After a while, the sediment was restored and conditions returned to baseline with coastline stability. At SIP, the arrangement of jetties and current directions could make the disposition process similar to what happened in Pecem harbor. However, additional studies must be carried out, covering current modeling and sediment transport, in order to clarify this question.
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The government of the Sultanate of Oman decided to transform all activities from Sultan Qaboos
Port (SQP) to SIP in July 2011. Then the Ministry of Transportation and Communications started to communicate with SIPC in order to start preparations for this plan and make all requirements ready before 1stSeptember 2014. The first phase was start on1stSeptember 2014 when they stop receiving cargo shipments in SQP and all activities in this port should be finished by August
2015 (Oman Establishment for Press Publication and Advertising, 2014).Therefore, this will lead to an increase in the number of companies, employees, shipping, and vehicles due to this big transformation of commercial cargoes. Hence, SIPC has started to make a new plan for making its gates ready before 1stSeptember 2014. At this point, ―Main Gate Study and Design‖ in Sohar
Industrial Port ‗‗Interim Traffic Study Report‖ was prepared by Parson International and
Company and submitted to SIPC. This report shows that the number of vehicles in 2005 was
800vph when operations of some companies started within two years. Seven years after operations started, in 2012 the total number of vehicles had increased to 1174vph that entered the SIP in the morning peak hour while this increased in 2013 to 1362vph with a total difference of 16% from
2012. This report includes a design for the SIP new gates, as it is expected that by 2014 the number of vehicles will be 2600vph (Ministry of Transport and Communications, 2014).
Moreover, as mentioned previously the main sources of heavy metals such as lead, zinc, cadmium, copper, iron, nickel, manganese and chromium in urban runoff are roadways and automobiles (USEPA, 1995). Hence, increase of the listed heavy metals is expected in the future due to increase of the number of companies, employees, shipping, and vehicles at SIP.
Moving ship cargoes from SQP to SIP means increasing seaborne trade and it may affect the environment and health of coastal population. GTZ (2010) demonstrated that increased numbers of ships will cause risk of collisions, air pollution (particularly the particulate matter (PM), nitrogen oxides and large emissions of diesel exhaust), accidental and operational oil spills, and
218 other threats to the environment. The report explained that the environment and the health of coastal populations had been effected by shipping.
According to this report, the increasing of shipping trade causes harmful emissions due to the daily operational release of various materials. They include different adverse impacts from these operations such as sewage, cleaning agents, anti-fouling paints, exhaust and other air emissions, intentional and unintentional discharges of oil, non-indigenous species from ballast water, and chemical cargo residues and waste (often highly toxic). Moreover, Figure 5.39 shows the number of vessel calls at SIP increased from 2007 to 2013from 556 to 1,964. Consequently, as seaborne trade is going to increase at SIP due to moving all trading operations from SQP to SIP, we expect that the area will be affected as a result of the above adverse impacts. The SIP management expect that Ship movements will increase to 9000 visits (in the high scenario), trucks will increase from roughly 1000/day presently to 6000/day in 2030 (high scenario) (SIPC personal communication, 2013).
219
2500
2000
1500
Vessels 1000
500
0 2007 2008 2009 2010 2011 2012 2013 Years
Figure5-39: Vessel calls development from 2007 to 2013 at SIP (Source: SIPC).
5.3.1.1.2 Domestic sources:
Industrial discharge is not the only source for heavy metals in the investigated area. Local people also have an effect on the environment as all beaches are open and easy to be used for dumping.
European Communities (2001) reported that domestic sources in wastewater have toxic elements which are difficult to separate from industrial sources. The toxic elements discharged from the corrosion of materials used in distribution, household and plumbing networks, tap water and detergents may enter urban wastewater in different products that contain Cd, Cu, Hg, Ni and Pb.
For example, food products, detergents and body care products are the main sources in urban wastewater. Moreover, Cd could be found in paints, Ni-Cd batteries and photography.
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Dumping of waste could be a major source of heavy metals (Chiffings, 2012). In his report to
Sohar University, Chiffings, (2012) reported that Sohar beaches are affected by dumping of construction waste such as old bricks, cement rubble and pieces, steel bars, tiles, fibro-cement sheet/asbestos and other materials (Figure 5.40). This occurred at two principal sites (Figure
5.41) Carowan – to the east of the old fish souk and to the west of the open area at the end of the cornice which is site G (control area) in the current research. This dumping of construction waste caused deposition of material physically dangerous to people using the beaches and the possible introduction of toxic chemicals – Sohar University has found high concentrations of the highly toxic chemical lead in the beach sands to the east of the Carowan site. Moreover, the current research found site G has the highest mean concentrations of Pb, which gives a good indicator that the influence of local people on the marine environment could be one of the sources of increasing heavy metals.
Figure 5-40: Construction material dumped on the beach at Carowan village, Sohar (Source:
Chiffings, (2012)
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Figure 5-41: Two beach dumping sites use in Sohar (Source: Chiffings, (2012)
5.3.1.2 Geochemical Sources
The Al Hajar Mountains that sit at the back of the Al Batinah plain, and their erosion which has led to its formation, are a product of plate tectonics that lead to the abducting of an expansive sheet of the Tethyan Cretaceous oceanic lithosphere over the marine sedimentary and volcanic rocks of the Tethyan continental margin some 4-6 million years ago (Glennie, 2005). Composed predominantly of the crystalline rocks of the Seminal ophiolitenappe (Lippard et al., 1986) the progressive erosion and consequent outwash of sediments in association with folding, faulting, tectonic uplift, climate and sea level changes has resulted in the extensive movement of sediments northwards into what we know as the Sea of Oman. The consequent indented shoreline was subsequently eroded leading to the loss of the deltas, formed headlands and the infilling of the adjacent bays to create what is today a relatively smooth and gently curving coastline. As a consequence, the beach sediments that characterize the Sohar coastline reflect a
222 composition of dark mineral fragments of ophiolite mixed with lighter biogenic carbonates to form a range of medium to dark beach sands (McLachlan et al. 1998) composed of fine to very fine sands (Al-Shuely et al. 2010). This process of beach formation represents a major geochemical source of some minerals within the beach sediments. Geochemical sources would be expected to contribute to all of the sites sampled but there is also strong evidence that discharges from the Port are significant, as will be discussed below.
While sediments at the SIP represent a potential geochemical metal source, the contribution in our present results cannot be ignored. The formation of the Al Batinah plain from the erosion of the Al Hajar Mountains to the south has led to the transport of significant metal bearing materials to the coast. The Al Batinah coastal plain is mainly composed of gravels and coastal deposits which are thought to be formed from a series of alluvial outwashes from the extensive wadi systems that transect the mountains (Abrams and Chadwick 1994). The indented shoreline was subsequently eroded leading to the loss of the delta formed headlands and the infilling of the adjacent bays to form what is today a relatively smooth and gently curving coastline comprised of fine to very fine beach sediments (Al-Shuely et al. 2010) made up of a composition of dark mineral fragments of ophiolite mixed with lighter biogenic carbonates (McLachlan et al. 1998).
This process of beach formation represents a major geochemical source of some minerals within the beach sediments.
Coastal sediments at the Al Batinah coast have high concentrations of Ni due to mineralization of the ophiolite rocks of the Hajar Mountains (Al-Rawahi, 2012). The wadis and hills behind
Sohar have been mined for Cu since Mesopotamian times reflecting the very high Cu content found in lava rocks within the region. These rocks, along with some of the Mantle sequences of the Seminal ophiolites and subsequent volcanic intrusions are largely composed of Si (46-57%),
Al (10-16%) and Fe (10-20%) oxides and exhibit high Mn, Cr, Ni, and V concentrations in the 223 order of 10s to 1000s ppm (Lippard et al. 1986). An analysis of recent gravel material from two wadis behind the SIP (Wadi Suq and Wadi Bani Umar) shows that these also contain high levels of Zn as well as Cr, Cu and Ni (Al-Sulaimani, 2005). Lead was below detection limits and Hg was not analyzed for. In historical times and most recently in the last 30-40 years both Cu and Cr have been mined and extracted at an industrial scale in two of the wadis behind the SIP (JICA,
2001).
Environmental studies of the Cu mine in Wadi Suq which discharges at the coast between Majis
(site E) and Harat ash Shakan (site F) show that mining activities have contaminated the ground water although this water has not yet reached the coast (JICA 2001; Al-Sulaimani 2005). It is not unusual therefore for those samples collected from the beaches to have high levels of metals, specifically Al, Fe, Mn, Cr, Cu, Ni, V and Zn. This is seen to be the case as reflected by the relatively high values at most Sohar sites when compared with the beaches further to the East. It has been suggested by Abdul-Wahab and Jupp (2009) that the high concentrations of Fe, Ni and
Cr they found are a result of geochemical sources from the ophiolite wadi fans running into the coastline and this seems to be consistent, while Al Suwadi and Al Khaboura have low concentrations because of great amounts of marine biogenetic carbonates.
In a preliminary study conducted by Al-Shuely et al (2009) on eleven heavy metal contents on beach sediments in the North and South regions of SIP, they concluded that there are higher concentrations of Cr, Mn and V in Harmul than at Majees and Zafaran: in the current study these are sites B, E and D respectively. The authors could not provide an explanation of these higher concentrations due to lack of data, but they speculated that these concentrations represent anthropogenic additions. Another study also suggested anthropogenic pollution (Izquierdo etal,
1997) or a natural background from the ophiolite rocks in the region leading to sediments which are transferred to the site from these rocks (McLachlan et al., 1998). 224
The present study found that the investigated areas have high levels of mean concentrations of heavy metals in different locations. Therefore, the author has concluded that these higher levels of heavy metals in sediment samples are from two main sources: anthropogenic activities or a natural background from the ophiolite rocks in the region. It is speculated that the following heavy metals originated from both natural background and the anthropogenic industrial activities
Al,Cr, Cu, Fe, Mn, Ni, V and Zn. Industrial activities should be added to the natural input because most of these heavy metals are used extensively at SIP and mining activities in the immediate area. However, it is strongly believed that the main sources of Cd, Co, Mo,Pb, Hg,
As and Sn are industrial activities due to reasons mentioned above from the evidence of levels of these heavy metals presented in the results (Chapter Four).
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5.4 Conclusion:
This chapter discusses the current research data in order to evaluate the risk assessment from pollutants at SIP and its surroundings. Moreover, it determines the sources of pollution in the SIP and surrounding areas using data research and list data from companies.
Heavy metals that exceed ISQG provide higher potential risks of contamination and may cause human health problems at the SIP and surrounding areas. Many people in these areas could be at risk of adverse health effects from inhalation or consumption of food and fish products. To our knowledge the condition of soil in Sohar and the surrounding areas is unknown or undocumented; therefore, exposure to toxic levels from elevated heavy metal concentrations can occur without being noticed.
This study has also tracked the record of 19 chemicals used by 8 companies (Table 4.51) at SIP.
A simple fingerprinting process has initially indicated the possible source of pollution of this chemical list. These studied companies as well as other companies within and surrounding SIP, for example companies at the Sohar Industrial Estate, are potential sources of pollution. In addition to petrochemical industries and various metals processing industries at SIP, cooling water outfalls as well as dust emissions from industries and open hazardous storage sites are also potential sources of pollution. This study has suggested various prevention measures to prevent environmental consequences in the future, and strongly recommended the implementation of these measures. The present study also suggests that the higher levels of heavy metals discussed in this chapter are from anthropogenic activities, or a natural background emanating from the ophiolite rocks in the region.
226
Chapter Six Conclusions and Recommendations
227
6 Chapter 6: Conclusions and Recommendations 6.1 Introduction
This Chapter will focus on summarizing and providing some recommendations emanating from the current research. The Chapter is divided into the following sections:
i. Conclusions of the data from the current project (Section 6.2)
ii. Recommendations (Section 6.3)
228
6.2 Conclusions of data from the current project
The present project was carried out to provide an essential step towards accumulating background environmental data at SIP and its surrounding areas. The study used sediment samples obtained from SIP and surrounding sites as the basis for the research carried out.
This project discusses investigation of the heavy metal composition of sediments within and near
Sohar Industrial Port (SIP) and the nearby coastal regions. The investigated areas were Sohar
Industrial Port (SIP) (site A), three extended sites 10km along the coast to the north-west (B,C and D) and three extended sites 10km along the coast to the south-east (E,F and G).
The research analyzed the concentrations of the heavy metals over two years and anions in one year in the surface sediments, in order to evaluate pollution levels in the study area and to undertake fingerprinting and risk assessment from the data that were collected. The total number of samples collected was 45. The method that was used to analyze the heavy metals was as per the USEPA protocol (3050 B). The equipment used to analyze heavy metals was an Inductively
Coupled Plasma Optical Emission Spectrometer (ICP-OES). Ion chromatography was used to analyze anions.
The statistical analysis shows that the mean concentrations of Al, Cd, Cu, Fe, Mo, Ni, Zn, As, Sn are higher at the port (site A) compared to the all sites in both 2011 and 2012. There was a decrease in the concentrations of Al (SIP Site A, 17%), Cd (SIP Site A, 21.7%), V (site C,
32.94%), As (site B, 8.52%), Al (site E, 46.78%) and Pb (site G, 22.66%), and increase in the concentration of Pb (SIP Site A, 58.35%), As (SIP Site A, 13.76%), Sn (SIP Site A, 187,6%), Hg
(SIP Site A, 21.13%), Fe (site B, 146.4.5%), Pb (site C, 84.64% ), Fe (site F, 77.54%), Pb (site F,
88.46%), Hg (site G, 81.74%), As (site E, 57.56%) and Sn (site E, 60.88%) in 2012 compared to
2011. 229
In this study, eight heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Hg and As) exceeded the International
Sediment Quality Guidelines (ISQG) for international organizations such as Environment
Canada (EC), Australian and New Zealand Environment Conservation Council (ANZECC), the
US Environmental Protection Agency (USEPA), and VROM. It seems that nickel is the only heavy metal that exceeds all ISQGs in both 2011 and 2012. However; all the above heavy metals exceed USEPA standards in all sites, except Pb at site D and Zn at sites B, C, D, E, F and G in both 2011 and 2012. In 2011and 2012, the mean concentration of Cu at the port exceeded all
ISQGs with percentage of 236.1% in EC, 34.44% in ANZECC, 1841% USEPA and 91.09%
VROM in 2011 and 191.9% in EC, 16.74% in ANZECC, 158%5 USEPA and 65.89% VROM.
Mercury exceeded all ISQGs except the VROM standards during both 2011 and 2012 with percentage of 915.7% in EC, 901.4% in ANZECC and 5369% USEPA in 2011 and 1127% in
EC, 1111% in ANZECC and 6508% USEPA in 2012. Both the west (B, C & D) and east (E, F &
G) sites of the SIP have high mean concentrations of Ni and exceeded all guideline standards.
Cadmium (253.0% in site B, 176.5% in site C and 20.59% in site D), Pb (25.17% in site B,
87.09% in site C and 21.72% in site D) and As (232.3% in site B, 177.3% in site C and 81.49% in site D) in all sites (east &west) exceed only the USEPA value in 2012.
Chapter Five evaluates the risk assessment of the heavy metals that exceeded ISQGs. The eight heavy metals which exceeded ISQG have a higher potential risk of contamination and may cause human health problems at the SIP and surrounding areas. Many people in these areas could be at risk of adverse health effects from inhalation or consumption of food and fish products. The condition of soils in Sohar and the surrounding areas is unknown or undocumented; therefore, exposure to toxic levels from elevated heavy metal concentrations can occur without being noticed.
230
Additionally, this Chapter also discussed the sources of the heavy metals at SIP and surrounding areas. A simple fingerprinting method initially indicated the possible sources of pollution of chemicals used by 8 companies (Table 5.1) at SIP. These companies, as well as others not included under this study but located at SIP or surrounding areas are potential sources of pollution. In addition to petrochemical industries and various metal processing industries at SIP, cooling water outfalls as well as dust emissions from industries and open hazardous storage sites are also potential sources of pollution. The present study suggests that the sources of the higher levels of heavy metals are from anthropogenic activities or emanate from the natural background of the ophiolite rocks in the region.
6.3 Recommendations
6.3.1 Recommendations based upon the results
Based upon the results of the current research, the following recommendations are proposed:
Further studies related to pollutant concentrations, pollution sources and pathways, transport mechanisms and potential risks facing humans and the environment are needed. Regarding sediment analysis, more samples along the SIP coastal area and surrounding areas are needed that provide qualitative and quantitative data that can give better models for risk assessment and fingerprinting. Different depths of sediment sampling are essential to understand the history of these pollutants and provide clearer results on the comparison between natural and anthropogenic inputs of pollutants.
If all of the above mentioned proposed research is undertaken it would be possible to develop a model system of heavy metal contamination in the SIP region. This model could assist in the
231 development of policies and strategies to mitigate and prevent further sediment contamination.
Some of these policies and strategies are discussed in the next section.
6.3.2 Secondary recommendations
6.3.2.1 Risk Mitigation Technology
Consideration needs to be given to the use of new technologies such as phyto remediation and the use of geoplymers for cleaning of pollution in the environment. Phyto remediation uses fast growing plants to restore the contaminated lands. Few studies conducted at Sultan Qaboos
University in collaboration with Petroleum Development Oman (PDO) showed very promising results in reducing the contamination of heavy metals and hydrocarbons on soil and wastewater from petroleum exploration sites at Fahud sites. Various plant species are growing well and adapted in dry and semi-dry hot climates that can be utilized for areas suffering ongoing pollution. The technology has become increasingly accepted in Oman but awaiting for the application in the field.
The use of geopolymers for cleaning of pollution in the environment is also being developed globally but has yet to be considered in Oman. Intensive research is needed to explore further application of this technology.
6.3.2.2 Hazardous Waste Management
At SIP, air, liquid and solid wastes contain a wide variety of materials. Some can decompose naturally but many others do not. SIP authorities must now think of an approach to industrial ecology, meaning that wastes from one part would be a resource for another part. This was
232 considered impossible, but the concept is catching on by using modern integrated waste management concepts including the reuse, reduction, recycling, composting, sanitary landfill, and waste-to-energy mechanisms.
Transportation of hazardous waste requires special arrangements and the system known as
―cradle-to-grave‖ to monitor the journey of the waste from its point of origin to the point of final disposal. Proper storage of hazardous waste is necessary because of the potential for serious harm to public health and environmental damage in the event of an accidental discharge.
6.3.2.3 Marine and Coastal Management Plan
As shown by the results of this study, there is a potential risk of bioaccumulation of heavy metals into the human food chain. The following should therefore be considered. Given the marine sensitivities in the region, it is important to have a proper marine environmental management plan and coastal zone management plan in SIP and surrounding areas to maintain seawater quality and ensure periodic monitoring of sensitive marine parameters, including bio-monitoring programs to measure the levels of chemical substances in marine organisms which occur due to exposure in contaminated marine water.
6.3.2.4 Re-Conduct Baseline Study of SIP and Surrounding Areas
A comprehensive heavy metal contamination baseline study including waters, sediments and biota is required to complete the survey of the remaining SIP and surrounding areas for these environmental pollutants. Failure to conduct the study could lead to a lack of essential data required for the completion of planning for future strategies for infrastructure development which are economically and environmentally sound, socially acceptable and culturally appropriate. 233
6.3.2.5 Establish World-Class Environmental Policies and Permits for SIP
Environmental policies and permits will provide measures to control the most common risks of pollution and provide regulations on how to comply with the best environmental standards.
Various industrial/mining/commercial activities require environmental permits, and SIP should start to prepare the process of issuing permits according to published policies.
6.3.2.6 Development of Environmental Management Programs and Strategies for SIPC at
Sohar Port
Planning for environmental management is becoming increasingly important. The complexity of such management means expanding the tools and procedures for addressing the issues requires great sophistication. It is very important to ensure that planning initiatives, processes and decisions are aligned and well informed by environmental and sustainability considerations.
SIP should develop and implement the following working environmental strategies:
i. SIP Environmental Strategy.
ii. Environmental Management System (EMS). iii. Nature Conservation and Protected Area Action Plan for Sohar and surrounding area. iv. Coastal Zone Management Action Plan and the Protection of Marine Environment.
v. SIP Action Plan for Hazardous Waste Management. vi. SIP Action Plan for the Management of Chemicals. vii. Environmental Information and Awareness Strategy.
234
6.3.2.7 Establishment of Food and Environment Control Centre
This is to ensure the periodical monitoring of environmental quality of all products on the market, so that they are maintained up to the standards required for protection of public health and the environment.
6.3.2.8 Planning for Environmental Events & Awards
SIP‘s participation in celebrating local, regional and international environmental occasions should be part of SIP‘s environmental vision. This would assist in interaction and be a move towards unification of efforts, and promotion of the implementation of programs of environmental conservation and protection.
SIP should also consider initiating an environmental prize, to be awarded for outstanding contributions by organizations in the management and protection of the environment.
235
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8 Appendix A: Approval letter from MECA to collect samples from SIP
Sohar industrial Port Company SAOC P.O.box 9 P.C 327 Sohar
Subject: Approval of sample from Sohar University
After Compliments,
Based on the information provided by Sohar University in the letter dated on 21 November 2010, I suggest you approve the sample testing of Sohar University to support general research of the environmental situation of the port of Sohar.
The generated information should be approved by SEU first prior to any publication or (verbal) communication from SU towards the general public and/or media.
We are looking forward to the results.
255
Appendix B: Approval letter from MECA to Company at SIP to provide detail about chemical in the plant.
Company: 1
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full suppor to Mr. Abdulaziz Alsawaei, aresearcher from Sohar University, whois working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as veryconfidential information.
Thecontactdetails:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
256
Company: 2
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
257
Company: 3
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr. Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
258
Company: 4
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
259
Company: 5
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
260
Company: 6
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
261
Company: 7
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
262
Company: 8
Subject: Providing the details about Chemical substances in the plant
After Compliments
Following to the instructions of H.E Undersecretary, I would like to ask you to give full support to Mr.Abdulaziz Alsawaei, a researcher from Sohar University, who is working to collect information about the chemical substances that are handled and processed in the various installations in the port. Mr.Alsawaei signed anon-disclosure agreement with SEU that all the data would be collected from the companies under this topic will be treated as very confidential information.
The contact details:
Sohar Environmental Unit P O Box No 398 Postal Code No 322 FalajAl Qabail Sultanate of Oman
263