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J Environ Health Sustain Dev 2020, 5(1): 962-970 |
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Shahryari A, Safari H, pahlavanzade B. Assessment of the Microbiological Quality of Caspian Seawater and the Role of Physicochemical Factors on Microbial Load. J Environ Health Sustain Dev 2020; 5 (1) :962-970
URL: http://jehsd.ssu.ac.ir/article-1-212-en.html
URL: http://jehsd.ssu.ac.ir/article-1-212-en.html
Environmental Health Research Centre, School of Health, Golestan University of Medical Sciences, Gorgan, Iran.
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Table 2: Pearson correlation coefficient between indicator bacteria and physicochemical parameters
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Figure 2: Seasonal variation of physicochemical parameters and indicator of bacteria
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Assessment of the Microbiological Quality of Caspian Seawater and the Role of Physicochemical Factors on Microbial Load
Ali Shahryari 1*, Hassan Safari 1, Bagher pahlavanzade 2
Ali Shahryari 1*, Hassan Safari 1, Bagher pahlavanzade 2
- Environmental Health Research Centre, School of Health, Golestan University of Medical Sciences, Gorgan, Iran.
- Department of Epidemiology and Biostatistics, School of Health, Golestan University of Medical Sciences, Gorgan, Iran.
| A R T I C L E I N F O | ABSTRACT | |
| ORIGINAL ARTICLE | Introduction: Analyzing the health risk associated with the microbial contamination of seawater is necessary to ensure that there is not any threat to human or environment. The aim of this study was to evaluate the microbiological quality of Caspian sea water using indicator bacteria. Some Physicochemical parameters were studied to assed their association with the contamination level of Caspian sea water due to the important role in the growth organisms in the seawater. Materials and Methods: In this study, 100 samples were collected from the northeastern zone of the Caspian sea, Iran, from November 2017 to December 2018. Total coliform, Fecal coliform, E.coli, Fecal Streptococcus and Clostridium perfringens were the indicator bacteria and temperature, pH, electrical conductivity, chloride and turbidity were water physicochemical factors according to standard methods. Results: The finding showed that the mean of Total coliform, Fecal coliform, E.coli, Fecal Streptococcus, and Clostridium perfringens were 614.72 ± 516.13, 62.11 ± 235.30, 49.69 ± 188.24, 348.02 ± 490.01 and 3.04 ± 5.76 MPN/100 ml, respectively. Furthermore, the mean and SD of temperature, pH, electrical conductivity, chloride, and turbidity were 13.84 oC ± 5.62, 8.27 ± 0.45, 17.96 ± 6.56 µs/cm, 5776.95 ± 1996.38 mg/l and 27.48 ± 15.82 NTU, respectively. Statistical analysis showed that microbial qualities were affected significantly by physicochemical factors, but the roles of water temperature were more than others. Conclusion: The microbiological results revealed that there was a remarkable level of contamination in some areas of Caspian sea. The results suggested that Clostridium perfringens provide better health risk prediction than other analyzed indicator bacteria, particularly in the warm season. |
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| Article History: Received: 09 November 2019 Accepted: 20 January 2020 |
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| *Corresponding Author: Ali Shahryari Email: Dr.shahryari@goums.ac.ir Tel: +981732454340 |
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| Keywords: Water Microbiology, Caspian Sea, Water Pollution, Seawater. |
Citation: Shahryari A, Safari H, pahlavanzade B . Assessment of the Microbiological Quality of Caspian Seawater and the Role of Physicochemical Factors on Microbial Load. J Environ Health Sustain Dev. 2020; 5(1): 962-70.
Introduction
Coastal seas are one of the most important natural environments both in terms of biological resources and the energy resources lying on its bed and in the coastal. A variety of parameters have all been combined to threaten its environment and especially its specific microbiological characteristic due to the dumping of urban and industrial wastewaters into the sea, with their high level of pathogens such as bacteria, protozoa, viruses, helminths worms and fungi, and thus the possibility water-related illness outbreaks 1-4. Gastroenteritis, diarrhea, typhoid, leptospirosis, primary amoebic meningoencephalitis, and acute respiratory infections have been identified as diseases commonly caused by these pathogens in water via both direct dermal contact and ingestion 5-6. Hence, the evaluation of the microbiological quality of seawater aims to protect consumers from illness due to both consumption and contact 5.
The microbiological quality of seawater is evaluated by the results obtained from fecal indicator bacteria (FIB) include total coliform, Fecal coliform, E.coli, and Fecal streptococci and Clostridium perfringens to determine the microbiological quality of these water 7. However, the lack of correlation between the number of some indicator bacteria and those of pathogenic microorganism has led to becoming unsuitable indicators, but the fact that indicator bacteria can be easily cultivated and is relatively inexpensive; therefore it is widely used as the indicators of fecal contamination by many countries and international organizations, including the European :union:, the United States, and the World Health Organization (WHO) 8-9. Of course, among the indicator bacteria, Clostridium perfringens, from spore-forming bacteria, are a better indicator for pathogens such as salmonella, cryptosporidium, Giardia, adenoviruses, and enteroviruses when comparing with the other indicators 10-12.
The Caspian sea is the largest inland body of water on the earth that it has a strategic and geopolitical position role for the governments of Iran, Russia, Azerbaijan, Turkmenistan, and Kazakhstan 13-14. It has provided a suitable environment for the recreational activities of Iranian people. For this reason, pressure on this area is rising by people through ecotourism facilities, industrial factories, agriculture’s drainage, etc., which in turn reduces the quality of water. Consequently, this study was designed to evaluate the microbiological quality of Caspian sea water and coastal environment according to the recommended methods. Furthermore, some physicochemical factors were studied such as temperature, pH, turbidity, electrical conductivity and chloride that might influence the microbial quality of Caspian seawater.
Materials and Methods
The study area and collection of water samples
In this cross-sectional study, 100 water samples were collected quarterly (25 samples per each season) along the northeastern zone of the Caspian sea, Iran, from November 2017 to December 2018, which were located at the southeastern of the Caspian sea near the city of Gorgan. It has a moderate climate with an average annual temperature of 17.7°C and an average annual rainfall of 601.0 mm. The spatial characteristics of the sampling stations is presented in Figure 1. At each site, 4 to 7 seawater samples were collected in sterile glass containers (2 Litter) by holding the bottles about 30 cm below the surface in a 2-meters-deep 15. All samples were immediately placed on ice, transported to the laboratory, and processed within two hours after collection. Moreover, quality assurance and quality control measures were used according to the Standard Methods for the Examination of Water and Wastewater 15.
Coastal seas are one of the most important natural environments both in terms of biological resources and the energy resources lying on its bed and in the coastal. A variety of parameters have all been combined to threaten its environment and especially its specific microbiological characteristic due to the dumping of urban and industrial wastewaters into the sea, with their high level of pathogens such as bacteria, protozoa, viruses, helminths worms and fungi, and thus the possibility water-related illness outbreaks 1-4. Gastroenteritis, diarrhea, typhoid, leptospirosis, primary amoebic meningoencephalitis, and acute respiratory infections have been identified as diseases commonly caused by these pathogens in water via both direct dermal contact and ingestion 5-6. Hence, the evaluation of the microbiological quality of seawater aims to protect consumers from illness due to both consumption and contact 5.
The microbiological quality of seawater is evaluated by the results obtained from fecal indicator bacteria (FIB) include total coliform, Fecal coliform, E.coli, and Fecal streptococci and Clostridium perfringens to determine the microbiological quality of these water 7. However, the lack of correlation between the number of some indicator bacteria and those of pathogenic microorganism has led to becoming unsuitable indicators, but the fact that indicator bacteria can be easily cultivated and is relatively inexpensive; therefore it is widely used as the indicators of fecal contamination by many countries and international organizations, including the European :union:, the United States, and the World Health Organization (WHO) 8-9. Of course, among the indicator bacteria, Clostridium perfringens, from spore-forming bacteria, are a better indicator for pathogens such as salmonella, cryptosporidium, Giardia, adenoviruses, and enteroviruses when comparing with the other indicators 10-12.
The Caspian sea is the largest inland body of water on the earth that it has a strategic and geopolitical position role for the governments of Iran, Russia, Azerbaijan, Turkmenistan, and Kazakhstan 13-14. It has provided a suitable environment for the recreational activities of Iranian people. For this reason, pressure on this area is rising by people through ecotourism facilities, industrial factories, agriculture’s drainage, etc., which in turn reduces the quality of water. Consequently, this study was designed to evaluate the microbiological quality of Caspian sea water and coastal environment according to the recommended methods. Furthermore, some physicochemical factors were studied such as temperature, pH, turbidity, electrical conductivity and chloride that might influence the microbial quality of Caspian seawater.
Materials and Methods
The study area and collection of water samples
In this cross-sectional study, 100 water samples were collected quarterly (25 samples per each season) along the northeastern zone of the Caspian sea, Iran, from November 2017 to December 2018, which were located at the southeastern of the Caspian sea near the city of Gorgan. It has a moderate climate with an average annual temperature of 17.7°C and an average annual rainfall of 601.0 mm. The spatial characteristics of the sampling stations is presented in Figure 1. At each site, 4 to 7 seawater samples were collected in sterile glass containers (2 Litter) by holding the bottles about 30 cm below the surface in a 2-meters-deep 15. All samples were immediately placed on ice, transported to the laboratory, and processed within two hours after collection. Moreover, quality assurance and quality control measures were used according to the Standard Methods for the Examination of Water and Wastewater 15.
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Determination of fecal indicator bacteria
The number of bacteria was estimated by the multiple-tube fermentation (MTF) method in a 9-tube MPN arrangement, and the result was expressed as most probable Number per 100 ml (MPN/100mL) according to the description in Standard Methods for the Examination of Water and Wastewater 15. Detection of total coliform and fecal coliform was achieved using the selective media, Brilliant Green Lactose Bile broth, and EC medium, respectively. Escherichia coli was quantified by using the media of lauryl Tryptose broth containing 4-methylumbelliferyl-B-D-glucuronide (LTB-MUG) 12. Fecal streptococci were also detected and enumerated using the media of Azide Dextrose broth and PSE agar as the presumptive and confirmation test, respectively 15. For the detection of Clostridium perfringens, water samples were inoculated into Thioglycolate broth and then incubated in an atmosphere containing 9 - 13 % CO2 at 37 °C for 24-48 h. The positive tubes were subculture on Tryptose Sulphite Cycloserine agar, incubating at 37°C for 24 h, anaerobically. Black, grey colonies were considered as presumptive Clostridium perfringens. The confirmation procedure consisting of gram staining, motility, and nitrate reduction was performed on suspected colonies 12.
Analysis of physicochemical parameter
Physicochemical parameters including pH, Electrical Conductivity (EC) and Turbidity of the samples were determined in the laboratory by digital pH meter (HT-1202 Digital PH), conductivity meter (SensIon7, Hach Company, USA) and turbidity meter (2100P, Hach Company, USA) according to instrument direction and standard methods for the examination of water. Water temperature was measured in the field at the time of sample collection with an electronic digital thermometer (TP101). The Mohr method was used to determine the chloride concentration in samples, using the chromate ions as an indicator in the titration of chloride ions with a silver nitrate standard solution 15.
Statistical analysis
Statistical analyses were performed using IBM SPSS statistics version 20 with a P-value of ≤ 0.05 which is statistically significant. The normality of data was checked by the Shapiro-Wilk test before analyzing it. Descriptive statistics were applied for the presentation of total coliform, fecal coliform, Escherichia coli, fecal streptococci, Clostridium perfringens, temperature, pH, electrical conductivity, chloride concentration and turbidity levels in seawater samples. The relationship between fecal bacteria and physicochemical parameters was analyzed using the Pearson correlation test. Additionally, analysis of variance (ANOVA) was used to compare fecal bacteria concentrations among seasons and sampling locations.
Ethical issues
This research was approved at the research ethics committee of Golestan University of Medical Sciences, Iran with the Ethics Code of IR. GOUMS.REC.1395.71.
Results
According to the findings, the mean and SD of total coliform, Fecal coliform, E.coli, Fecal Streptococcus, and Clostridium perfringens were 614.72 ± 516.13, 62.11 ± 235.30, 49.69 ± 188.24, 348.02 ± 490.01 and 3.04 ± 5.76 MPN/100 ml, respectively. The results showed that the variation in total coliform, Fecal streptococci, Fecal coliform, Escherichia coli, Fecal streptococci, and Clostridium perfringens level were not statistically significant at different stations. The results of physicochemical analysis also showed that the mean and SD for temperature, pH, electrical conductivity, chloride, and turbidity were 13.84 ± 5.62, 8.27 ± 0.45, 17.96 ± 6.56 µs/cm, 5776.95 ± 1996.38 mg/l and 27.48 ± 15.82 NTU, respectively. For physicochemical parameters, the only significant relation was observed between electrical conductivity across places (p = 0.45) in accordance with the ANOVA test. The distribution average value of physicochemical parameters also showed that there were notable changes during the four seasons (p < 0.001) except chloride (p = 0.158). The mean and SD values of bacterial indicators and physicochemical parameters in seawater samples of the Caspian Sea coastal for every sampling site are presented in table 1.
Statistical analysis showed that microbial qualities were affected significantly by physicochemical factors, but the roles of temperature and electrical conductivity were more than the others. The results of correlation analysis between measured parameters and the effect of seasonal variation on physicochemical and microbiological parameters of samples are shown in table 2 and figure 2.
The number of bacteria was estimated by the multiple-tube fermentation (MTF) method in a 9-tube MPN arrangement, and the result was expressed as most probable Number per 100 ml (MPN/100mL) according to the description in Standard Methods for the Examination of Water and Wastewater 15. Detection of total coliform and fecal coliform was achieved using the selective media, Brilliant Green Lactose Bile broth, and EC medium, respectively. Escherichia coli was quantified by using the media of lauryl Tryptose broth containing 4-methylumbelliferyl-B-D-glucuronide (LTB-MUG) 12. Fecal streptococci were also detected and enumerated using the media of Azide Dextrose broth and PSE agar as the presumptive and confirmation test, respectively 15. For the detection of Clostridium perfringens, water samples were inoculated into Thioglycolate broth and then incubated in an atmosphere containing 9 - 13 % CO2 at 37 °C for 24-48 h. The positive tubes were subculture on Tryptose Sulphite Cycloserine agar, incubating at 37°C for 24 h, anaerobically. Black, grey colonies were considered as presumptive Clostridium perfringens. The confirmation procedure consisting of gram staining, motility, and nitrate reduction was performed on suspected colonies 12.
Analysis of physicochemical parameter
Physicochemical parameters including pH, Electrical Conductivity (EC) and Turbidity of the samples were determined in the laboratory by digital pH meter (HT-1202 Digital PH), conductivity meter (SensIon7, Hach Company, USA) and turbidity meter (2100P, Hach Company, USA) according to instrument direction and standard methods for the examination of water. Water temperature was measured in the field at the time of sample collection with an electronic digital thermometer (TP101). The Mohr method was used to determine the chloride concentration in samples, using the chromate ions as an indicator in the titration of chloride ions with a silver nitrate standard solution 15.
Statistical analysis
Statistical analyses were performed using IBM SPSS statistics version 20 with a P-value of ≤ 0.05 which is statistically significant. The normality of data was checked by the Shapiro-Wilk test before analyzing it. Descriptive statistics were applied for the presentation of total coliform, fecal coliform, Escherichia coli, fecal streptococci, Clostridium perfringens, temperature, pH, electrical conductivity, chloride concentration and turbidity levels in seawater samples. The relationship between fecal bacteria and physicochemical parameters was analyzed using the Pearson correlation test. Additionally, analysis of variance (ANOVA) was used to compare fecal bacteria concentrations among seasons and sampling locations.
Ethical issues
This research was approved at the research ethics committee of Golestan University of Medical Sciences, Iran with the Ethics Code of IR. GOUMS.REC.1395.71.
Results
According to the findings, the mean and SD of total coliform, Fecal coliform, E.coli, Fecal Streptococcus, and Clostridium perfringens were 614.72 ± 516.13, 62.11 ± 235.30, 49.69 ± 188.24, 348.02 ± 490.01 and 3.04 ± 5.76 MPN/100 ml, respectively. The results showed that the variation in total coliform, Fecal streptococci, Fecal coliform, Escherichia coli, Fecal streptococci, and Clostridium perfringens level were not statistically significant at different stations. The results of physicochemical analysis also showed that the mean and SD for temperature, pH, electrical conductivity, chloride, and turbidity were 13.84 ± 5.62, 8.27 ± 0.45, 17.96 ± 6.56 µs/cm, 5776.95 ± 1996.38 mg/l and 27.48 ± 15.82 NTU, respectively. For physicochemical parameters, the only significant relation was observed between electrical conductivity across places (p = 0.45) in accordance with the ANOVA test. The distribution average value of physicochemical parameters also showed that there were notable changes during the four seasons (p < 0.001) except chloride (p = 0.158). The mean and SD values of bacterial indicators and physicochemical parameters in seawater samples of the Caspian Sea coastal for every sampling site are presented in table 1.
Statistical analysis showed that microbial qualities were affected significantly by physicochemical factors, but the roles of temperature and electrical conductivity were more than the others. The results of correlation analysis between measured parameters and the effect of seasonal variation on physicochemical and microbiological parameters of samples are shown in table 2 and figure 2.
Table 1: The mean ± SD Level of physicochemical parameters and FIB at the north-eastern zone of the Caspian Sea, Iran
| Station name |
Temperature (OC) |
pH | E.C (µS/cm) |
Chloride (mg/L) |
Turbidity (NTU) |
Total coliform (MPN/100ml) |
F. Coliform (MPN/100ml) |
E. coli (MPN/100ml) | Fecal streptococci (MPN/100ml) | Clostridium perfringens (MPN/100ml) |
| S1 | 11.50 ± 7.23 | 8.31 ± 0.27 | 15.69 ± 6.21 | 6483.19 ± 345.34 | 33.35 ± 17.29 | 603.50 ± 579.44 | 0.75 ± 1.50 | 0.50 ± 0.75 | 587.50 ± 594.94 | 4.03 ± 8.05 |
| S2 | 11.75 ± 6.99 | 8.34 ± 0.40 | 16.88 ± 5.49 | 5205.19 ± 697.14 | 33.18 ± 16.10 | 877.50 ± 445.00 | 0.75 ± 1.50 | 0.50 ± 0.75 | 551.75 ± 633.06 | 4.30 ± 7.88 |
| S3 | 12.00 ± 6.78 | 8.40 ± 0.35 | 15.78 ± 6.16 | 5604.56 ± 1681.67 | 33.55 ± 12.49 | 832.00 ± 536.00 | 0.00 ± 0.00 | 0.00 ± 0.00 | 568.75 ± 614.20 | 2.00 ± 3.31 |
| S4 | 14.17 ± 6.62 | 8.52 ± 0.45 | 17.41 ± 5.12 | 4954.03 ± 662.26 | 33.41 ± 15.39 | 453.67 ± 506.37 | 0.00 ± 0.00 | 0.00 ± 0.00 | 368.67 ± 566.50 | 5.35 ± 9.03 |
| S5 | 13.25 ± 6.90 | 8.62 ± 0.89 | 10.00 ± 11.49 | 4317.69 ± 254.93 | 33.18 ± 17.92 | 556.50 ± 627.63 | 115.00 ± 230.00 | 85.00 ± 110.00 | 283.00 ± 544.75 | 4.58 ± 7.70 |
| S6 | 13.25 ± 6.90 | 8.21 ± 0.54 | 9.77 ± 11.76 | 5169.69 ± 1913.30 | 29.17 ± 16.42 | 825.75 ± 548.50 | 115.00 ± 230.00 | 115.00 ± 230.00 | 551.00 ± 633.93 | 6.03 ± 11.33 |
| S7 | 14.57 ± 5.68 | 8.41 ± 0.40 | 18.56 ± 6.32 | 5777.88 ± 2501.55 | 18.55 ± 13.17 | 551.71 ± 534.95 | 17.00 ± 33.94 | 11.25 ± 18.55 | 472.43 ± 587.04 | 7.20 ±10.80 |
| S8 | 14.92 ± 6.17 | 8.21 ± 0.29 | 17.75 ±5.43 | 5936.78 ± 1229.48 | 16.95 ± 12.49 | 417.17 ± 533.99 | 0.50 ± 1.22 | 0.00 ± 0.00 | 369.00 ± 566.24 | 2.67 ± 3.32 |
| S9 | 14.74 ± 5.55 | 8.20 ± 0.59 | 18.47± 5.92 | 5975.66 ± 3009.27 | 22.81 ± 10.92 | 525.14 ± 542.57 | 161.29 ± 414.02 | 115.00 ± 230.00 | 393.71 ± 509.11 | 2.46 ± 3.90 |
| S10 | 14.89 ± 5.36 | 8.16 ± 0.48 | 18.71 ± 6.05 | 7202.95 ± 2133.84 | 36.36 ± 25.26 | 647.57 ± 545.55 | 163.71 ± 413.01 | 163.71 ± 413.01 | 227.00 ± 420.57 | 0.83 ± 1.33 |
| S11 | 14.50 ± 4.12 | 8.16 ± 0.53 | 20.40 ± 5.54 | 7105.33 ± 2495.19 | 29.33 ± 15.85 | 827.25 ± 545.50 | 280.75 ± 546.27 | 131.29 ± 214.02 | 11.25 ± 18.55 | 1.10 ± 0.90 |
| S12 | 14.50 ± 4.72 | 8.19 ± 0.38 | 22.13 ± 4.99 | 5569.95 ± 1010.10 | 17.69 ± 13.54 | 401.83 ± 543.34 | 4.33 ± 9.22 | 4.33 ± 9.22 | 367.17 ± 567.65 | 4.58 ± 6.64 |
| S13 | 13.25 ± 5.32 | 8.28 ± 0.53 | 27.00 ± 2.08 | 5889.45 ± 2073.23 | 34.43 ± 32.13 | 826.00 ± 548.00 | 275.75 ± 549.50 | 227.00 ± 420.57 | 17.00 ± 21.95 | 0.83 ± 1.05 |
| S14 | 13.13 ± 6.25 | 7.97 ± 0.49 | 17.83 ± 4.80 | 6216.94 ± 1601.13 | 21.93 ± 9.35 | 608.25 ± 572.93 | 0.00 ± 0.00 | 0.00 ± 0.00 | 390.75 ± 519.89 | 2.00 ± 3.31 |
| S15 | 13.93 ± 6.80 | 8.16 ± 0.44 | 16.69 ± 6.68 | 6207.94 ± 2537.86 | 26.77 ± 10.19 | 551.57 ± 535.52 | 0.00 ± 0.00 | 0.00 ± 0.00 | 212.86 ± 402.69 | 0.99 ± 1.28 |
| S16 | 13.88 ± 6.61 | 8.37 ± 0.59 | 22.92 ± 5.24 | 5356.06 ± 3013.35 | 29.43 ± 17.71 | 581.00 ± 601.16 | 0.75 ± 1.50 | 0.75 ± 1.50 | 312.50 ± 529.74 | 1.55 ± 2.42 |
| S17 | 13.88 ± 6.61 | 8.16 ± 0.49 | 17.58 ± 4.95 | 4956.69 ± 401.59 | 25.73 ± 6.78 | 827.25 ± 545.50 | 0.75 ± 1.50 | 0.75 ± 1.50 | 301.00 ± 534.26 | 2.30 ± 4.60 |
Table 2: Pearson correlation coefficient between indicator bacteria and physicochemical parameters
| Indicator Bacteria |
physicochemical parameters | ||||
| Temperature (oC) | pH | Cl (mg/L) | EC (µS/cm) | Turbidity (NTU) | |
| Total coliform | -0.371** | -0.560** | 0.193* | 0.178* | 0.285** |
| Fecal coliform | -0.068 | -0.129 | 0.055 | 0.286** | -0.061 |
| Fecal streptococci | -0.659** | -0.023 | 0.197* | 0.433** | 0.001 |
| Clostridium perfringens | 0.605** | 0.506** | -0.111 | -0.337** | -0.251** |
**Correlation is significant at the 0.01 level (2-tailed)
*Correlation is significant at the 0.05 level (2-tailed)
*Correlation is significant at the 0.05 level (2-tailed)
Figure 2: Seasonal variation of physicochemical parameters and indicator of bacteria
Discussion
The results of bacteriological analysis showed that there was microbial contamination above the permissible limit for recreational activity in some sampling locations. The presence of indicators of bacteria in seawater is dangerous to human health due to the potential presence of pathogens. Therefore, it is essential to routinely check the microbial contaminants threating seawater safety and to ensure compliance with quality standards and public health 16. The correlation analyses revealed that temperature as one of the most important physical characteristics of seawater had a negative significant effect on the fecal coliform and fecal streptococci population. A similar result was found in four seasons of a year, so far the lowest occurrence of indicator bacteria were observed in the summer, presumably due to high temperature and solar radiation. Moreover, a higher level of total coliform, Fecal coliform, Escherichia coli, and fecal streptococci were observed in autumn, it may be attributed to intense rainfall that occurs in this period. Previous studies have also shown that intense rainfall highly influenced the occurrence of fecal indicator bacteria 17-18. The results of the study showed that there was a significant association between autumn and spring seasons with summer (p < 0.001). However, the statistical analysis showed no significant difference between summer and winter. In addition, the average value of fecal coliform in autumn was significantly higher than in the winter, spring, and summer. Unlike to coliform bacteria, the highest and lowest Clostridium perfringens levels were detected in the summer, probably due to the greater resistance of the spores to environmental stresses such as osmotic, sunlight, and temperature. Based on the results, the bacteriological examination based on culturing Clostridium perfringens can be effective for assessing the public health safety of recreational water, especially in summer when the highest number of people are present for recreational activities. Skanavis and Yankoà reported that classic indicator bacteria had a little value in predicting the presence of pathogens and Clostridium perfringens are better indicators, due to their higher resistance to sunlight and longer survival under stressed environment condition 19.
Another important factor, which affected the occurrence of bacteria, was electrical conductivity. Correlation analyses showed that there was a significant positive association between electrical conductivity value and the number of Total coliforms, Fecal coliform, Escherichia coli and Fecal streptococci of samples (p < 0.001), while this significant association was negative between electrical conductivity and Clostridium perfringens level (p < 0.001). The data showed that with increasing electrical conductivity, a decrease was observed in the value of indicator bacteria in seawater. This may be due to the fact that specific characteristics of seawater, such as osmotic pressure and the toxicity of inorganic salts have a negative effect on the indicator bacteria population. Similarly, the result of Karbasdehi et al. study also showed that there was a negative association between the average number of fecal bacteria and inorganic salt 20.
The results of this study showed that chloride concentration was in a high degree of variability ranged from 2836.45 to 11533.95 mg/l. Statistical analysis showed that there was a significant association between Chloride level and an average number of total coliform and Fecal streptococci, but it had no effect on the growth of Fecal coliform and Clostridium perfringens. Shehane et al. reported that a negative correlation was found between salinity and F. Coliform and enterococci, while this effect was not significant for Clostridium perfringens 21-22.
In respect to pH as a key variable of the aquatic environment, the findings showed that the average values of pH were in the range between 7.35 and 9.93. The locations with the largest pH were found in the stations 5, 14, 4 and 3, respectively. The present study revealed that there was a reverse correlation between pH and the level of total coliform and Clostridium perfringens. Seawater with a pH range of 7.5-8.5 influenced the E. coli mortality, while in alkaline environments; fecal coliform decreased about 30% with the increase in one unit of pH 23.
Turbidity as a significant physical parameter does not have a health-based recommendation for seawater, but turbidity higher than 5 NTU may promote water contamination 15. The findings revealed that in 90.8%, 32.3%, 6.1%, 30.8% and 75.4% of samples were positive for total coliform, Fecal coliform, Escherichia coli, F. streptococci, and Clostridium perfringens, respectively, turbidity was above than 5 NTU. However, the finding showed there was no statistically significant association between turbidity and Fecal coliform and fecal streptococci level, but Clostridium perfringens and total coliform considerably affected by turbidity (Table 2).
In order to determine the sources of fecal contamination, fecal coliform to fecal streptococci ratio was used as an index to distinguish human fecal pollution from animal fecal pollution 15 in each station (data do not show). According to the findings of this study, only stations 11 and 13 had a fecal coliform to fecal streptococci ratio greater than 4, highlighting that human waste was the main source contamination. The result is in accordance with other studies that reported anthropogenic activities and land used had a high effect on the microbiological contamination of coastal environmental 20,24. While, Fecal coliform to the fecal streptococci ratio was ≤ 0.7 in other stations, indicating that non-human, animals and agricultural runoff were the dominant sources of pollution. However, the risk presented by fecal contamination from nonhuman sources was potentially less than human sources, but some documents indicate that some nonhuman fecal sources may pose risks, compared to those risks from human sources 19, 25.
Conclusions
The microbiological results revealed that there was a remarkable level of contamination in some areas; consequently, this area could be unsafe for recreational activities. The results suggested that Clostridium perfringens provide better health risk prediction than other analyzed indicator bacteria, particularly in the warm season.
Acknowledgments
The authors would like to thank the employers of Health Office of Bandar Torkaman City for their assistance in the sampling of water samples.
Funding
This work was supported by the Deputy of Research and Technology (Grant: 950304064) at Golestan University of Medical Sciences, Iran
Conflict of interest
The authors have declared no conflict of interest for the publication of this article.
This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work for commercial use.
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4. Venkatesharaju K, Ravikumar P, Somashekar R, et al. Physico-chemical and bacteriological investigation on the river cauvery of kollegal stretch in Karnataka. J Sci Eng Technol. 2010;6(1):50-9.
5. Pond K. Water recreation and disease: plausibility of associated infections: acute effects, sequelae, and mortality: World Health Organization; 2005.
6. Hlavsa MC, Roberts VA, Kahler AM, et al. Recreational water–associated disease outbreaks-United States, 2009–2010. Morb Mortal Wkly Rep. 2014;63(1):6-10.
7. WHO. Guidelines for safe recreational water environments: Coastal and fresh waters: World Health Organization; 2003.
8. Stewart JR, Gast RJ, Fujioka RS, et al. The coastal environment and human health: microbial indicators, pathogens, sentinels and reservoirs. Environ Health. 2008:7(2):3.
9. WHO. Guidelines for drinking-water quality: First addendum to third edition, Volume 1, recommendations: World Health Organization; 2006.
10. Vijayavel K, Kashian D. Evaluation of clostridium perfringens as a tracer of sewage contamination in sediments by two enumeration methods. Environ Monit Assess. 2014;186(9): 5617-24.
11. Skanavis C, Yanko WA. Clostridium perfringens as a potential indicator for the presence of sewage solids in marine sediments. Mar Pollut Bull. 2001;42(1):31-5.
12. Shahryari A, Nikaeen M, Khiadani M, et al. Applicability of universal bacteroidales genetic marker for microbial monitoring of drinking water sources in comparison to conventional indicators. Environ Monit Assess. 2014;186(11):7055-62.
13. Zeinolabedin Y, Yahyapoor M, Shirzad Z. The geopolitics of energy in the caspian basin. Int J Environ Res. 2011;5(2):501-8.
14.Naghipour D, Shaabaninezhad Z, Amouei A. Evaluation of heavy metal concentrations in rutilus frisii kutum on the southern coast of the Caspian sea (northern Iran). Environmental Health Engineering and Management Journal. 2016;3(2):55-9.
15. APHA. Standard methods for the examination of water and wastewater. American public health association; 2012.
16. Wuertz S, Miller W, Bambic D, et al. Quantification of pathogens and sources of microbial indicators for QMRA in recreational waters.UK:IWA publishing; 2011. [cited Jan 26,2020] Available from: https://www. iwapublishing. com/books/9781843395430/ quantification-pathogens-and-sources-microbial-indicators-qmra-recreational.
17.Giannoulis N, Maipa V, Konstantinou I, et al. Microbiological risk assessment of agios georgios source supplies in northwestern greece based on faecal coliforms determination and sanitary inspection survey. Chemosphere. 2005;58(9):1269-76.
18. Shahryari A, Mehdinejad M, Ahmadi N, et al. Impact of human activities on the rate of microbial contamination of the Gorgan Ziarat River, Iran. Ecology, Environment and Conservation. 2017;23(3):1291-7.
19. Schoen ME, Ashbolt NJ. Assessing pathogen risk to swimmers at non-sewage impacted recreational beaches. Environ Sci Technol. 2010:44(7):2286-91.
20. Karbasdehi VN, Dobaradaran S, Nabipour I, et al. Indicator bacteria community in seawater and coastal sediment: the Persian Gulf as a case. J Environ Health Sci Eng. 2017:15 (1):6.
21. Akhavan S, Ebrahimi S, Navabian M, et al. Significance of physicochemical factors in the transmission of Escherichia coli and Chloride. Environmental Health Engineering And Management Journal. 2018;5(2):115-22.
22. Shehane S, Harwood V, Whitlock J et al. The influence of rainfall on the incidence of microbial faecal indicators and the dominant sources of faecal pollution in a Florida river. J Appl Microbiol. 2005;98(5):1127-36.
23. Neger MK. Literature Review on the Survival of Fecal Coliform in Fresh and Saline waters, and Sediments. Lummi Indian Business Council, Funded By: Environment Protection Agency (Agreement No GA-97020501-0). 2002.
24. Hamilton MJ, Hadi AZ, Griffith JF, et al. Large scale analysis of virulence genes in Escherichia coli strains isolated from Avalon Bay, CA. Water Res. 2010;44(18):5463-73.
25. Soller JA, Bartrand T, Ashbolt NJ, et al. Estimating the primary etiologic agents in recreational freshwaters impacted by human sources of faecal contamination. Water Res. 2010;44(16):4736-47.
The results of bacteriological analysis showed that there was microbial contamination above the permissible limit for recreational activity in some sampling locations. The presence of indicators of bacteria in seawater is dangerous to human health due to the potential presence of pathogens. Therefore, it is essential to routinely check the microbial contaminants threating seawater safety and to ensure compliance with quality standards and public health 16. The correlation analyses revealed that temperature as one of the most important physical characteristics of seawater had a negative significant effect on the fecal coliform and fecal streptococci population. A similar result was found in four seasons of a year, so far the lowest occurrence of indicator bacteria were observed in the summer, presumably due to high temperature and solar radiation. Moreover, a higher level of total coliform, Fecal coliform, Escherichia coli, and fecal streptococci were observed in autumn, it may be attributed to intense rainfall that occurs in this period. Previous studies have also shown that intense rainfall highly influenced the occurrence of fecal indicator bacteria 17-18. The results of the study showed that there was a significant association between autumn and spring seasons with summer (p < 0.001). However, the statistical analysis showed no significant difference between summer and winter. In addition, the average value of fecal coliform in autumn was significantly higher than in the winter, spring, and summer. Unlike to coliform bacteria, the highest and lowest Clostridium perfringens levels were detected in the summer, probably due to the greater resistance of the spores to environmental stresses such as osmotic, sunlight, and temperature. Based on the results, the bacteriological examination based on culturing Clostridium perfringens can be effective for assessing the public health safety of recreational water, especially in summer when the highest number of people are present for recreational activities. Skanavis and Yankoà reported that classic indicator bacteria had a little value in predicting the presence of pathogens and Clostridium perfringens are better indicators, due to their higher resistance to sunlight and longer survival under stressed environment condition 19.
Another important factor, which affected the occurrence of bacteria, was electrical conductivity. Correlation analyses showed that there was a significant positive association between electrical conductivity value and the number of Total coliforms, Fecal coliform, Escherichia coli and Fecal streptococci of samples (p < 0.001), while this significant association was negative between electrical conductivity and Clostridium perfringens level (p < 0.001). The data showed that with increasing electrical conductivity, a decrease was observed in the value of indicator bacteria in seawater. This may be due to the fact that specific characteristics of seawater, such as osmotic pressure and the toxicity of inorganic salts have a negative effect on the indicator bacteria population. Similarly, the result of Karbasdehi et al. study also showed that there was a negative association between the average number of fecal bacteria and inorganic salt 20.
The results of this study showed that chloride concentration was in a high degree of variability ranged from 2836.45 to 11533.95 mg/l. Statistical analysis showed that there was a significant association between Chloride level and an average number of total coliform and Fecal streptococci, but it had no effect on the growth of Fecal coliform and Clostridium perfringens. Shehane et al. reported that a negative correlation was found between salinity and F. Coliform and enterococci, while this effect was not significant for Clostridium perfringens 21-22.
In respect to pH as a key variable of the aquatic environment, the findings showed that the average values of pH were in the range between 7.35 and 9.93. The locations with the largest pH were found in the stations 5, 14, 4 and 3, respectively. The present study revealed that there was a reverse correlation between pH and the level of total coliform and Clostridium perfringens. Seawater with a pH range of 7.5-8.5 influenced the E. coli mortality, while in alkaline environments; fecal coliform decreased about 30% with the increase in one unit of pH 23.
Turbidity as a significant physical parameter does not have a health-based recommendation for seawater, but turbidity higher than 5 NTU may promote water contamination 15. The findings revealed that in 90.8%, 32.3%, 6.1%, 30.8% and 75.4% of samples were positive for total coliform, Fecal coliform, Escherichia coli, F. streptococci, and Clostridium perfringens, respectively, turbidity was above than 5 NTU. However, the finding showed there was no statistically significant association between turbidity and Fecal coliform and fecal streptococci level, but Clostridium perfringens and total coliform considerably affected by turbidity (Table 2).
In order to determine the sources of fecal contamination, fecal coliform to fecal streptococci ratio was used as an index to distinguish human fecal pollution from animal fecal pollution 15 in each station (data do not show). According to the findings of this study, only stations 11 and 13 had a fecal coliform to fecal streptococci ratio greater than 4, highlighting that human waste was the main source contamination. The result is in accordance with other studies that reported anthropogenic activities and land used had a high effect on the microbiological contamination of coastal environmental 20,24. While, Fecal coliform to the fecal streptococci ratio was ≤ 0.7 in other stations, indicating that non-human, animals and agricultural runoff were the dominant sources of pollution. However, the risk presented by fecal contamination from nonhuman sources was potentially less than human sources, but some documents indicate that some nonhuman fecal sources may pose risks, compared to those risks from human sources 19, 25.
Conclusions
The microbiological results revealed that there was a remarkable level of contamination in some areas; consequently, this area could be unsafe for recreational activities. The results suggested that Clostridium perfringens provide better health risk prediction than other analyzed indicator bacteria, particularly in the warm season.
Acknowledgments
The authors would like to thank the employers of Health Office of Bandar Torkaman City for their assistance in the sampling of water samples.
Funding
This work was supported by the Deputy of Research and Technology (Grant: 950304064) at Golestan University of Medical Sciences, Iran
Conflict of interest
The authors have declared no conflict of interest for the publication of this article.
This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work for commercial use.
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5. Pond K. Water recreation and disease: plausibility of associated infections: acute effects, sequelae, and mortality: World Health Organization; 2005.
6. Hlavsa MC, Roberts VA, Kahler AM, et al. Recreational water–associated disease outbreaks-United States, 2009–2010. Morb Mortal Wkly Rep. 2014;63(1):6-10.
7. WHO. Guidelines for safe recreational water environments: Coastal and fresh waters: World Health Organization; 2003.
8. Stewart JR, Gast RJ, Fujioka RS, et al. The coastal environment and human health: microbial indicators, pathogens, sentinels and reservoirs. Environ Health. 2008:7(2):3.
9. WHO. Guidelines for drinking-water quality: First addendum to third edition, Volume 1, recommendations: World Health Organization; 2006.
10. Vijayavel K, Kashian D. Evaluation of clostridium perfringens as a tracer of sewage contamination in sediments by two enumeration methods. Environ Monit Assess. 2014;186(9): 5617-24.
11. Skanavis C, Yanko WA. Clostridium perfringens as a potential indicator for the presence of sewage solids in marine sediments. Mar Pollut Bull. 2001;42(1):31-5.
12. Shahryari A, Nikaeen M, Khiadani M, et al. Applicability of universal bacteroidales genetic marker for microbial monitoring of drinking water sources in comparison to conventional indicators. Environ Monit Assess. 2014;186(11):7055-62.
13. Zeinolabedin Y, Yahyapoor M, Shirzad Z. The geopolitics of energy in the caspian basin. Int J Environ Res. 2011;5(2):501-8.
14.Naghipour D, Shaabaninezhad Z, Amouei A. Evaluation of heavy metal concentrations in rutilus frisii kutum on the southern coast of the Caspian sea (northern Iran). Environmental Health Engineering and Management Journal. 2016;3(2):55-9.
15. APHA. Standard methods for the examination of water and wastewater. American public health association; 2012.
16. Wuertz S, Miller W, Bambic D, et al. Quantification of pathogens and sources of microbial indicators for QMRA in recreational waters.UK:IWA publishing; 2011. [cited Jan 26,2020] Available from: https://www. iwapublishing. com/books/9781843395430/ quantification-pathogens-and-sources-microbial-indicators-qmra-recreational.
17.Giannoulis N, Maipa V, Konstantinou I, et al. Microbiological risk assessment of agios georgios source supplies in northwestern greece based on faecal coliforms determination and sanitary inspection survey. Chemosphere. 2005;58(9):1269-76.
18. Shahryari A, Mehdinejad M, Ahmadi N, et al. Impact of human activities on the rate of microbial contamination of the Gorgan Ziarat River, Iran. Ecology, Environment and Conservation. 2017;23(3):1291-7.
19. Schoen ME, Ashbolt NJ. Assessing pathogen risk to swimmers at non-sewage impacted recreational beaches. Environ Sci Technol. 2010:44(7):2286-91.
20. Karbasdehi VN, Dobaradaran S, Nabipour I, et al. Indicator bacteria community in seawater and coastal sediment: the Persian Gulf as a case. J Environ Health Sci Eng. 2017:15 (1):6.
21. Akhavan S, Ebrahimi S, Navabian M, et al. Significance of physicochemical factors in the transmission of Escherichia coli and Chloride. Environmental Health Engineering And Management Journal. 2018;5(2):115-22.
22. Shehane S, Harwood V, Whitlock J et al. The influence of rainfall on the incidence of microbial faecal indicators and the dominant sources of faecal pollution in a Florida river. J Appl Microbiol. 2005;98(5):1127-36.
23. Neger MK. Literature Review on the Survival of Fecal Coliform in Fresh and Saline waters, and Sediments. Lummi Indian Business Council, Funded By: Environment Protection Agency (Agreement No GA-97020501-0). 2002.
24. Hamilton MJ, Hadi AZ, Griffith JF, et al. Large scale analysis of virulence genes in Escherichia coli strains isolated from Avalon Bay, CA. Water Res. 2010;44(18):5463-73.
25. Soller JA, Bartrand T, Ashbolt NJ, et al. Estimating the primary etiologic agents in recreational freshwaters impacted by human sources of faecal contamination. Water Res. 2010;44(16):4736-47.
Type of Study: Original articles |
Subject:
Environmental pollution
Received: 2019/11/9 | Accepted: 2020/01/20 | Published: 2020/03/20
Received: 2019/11/9 | Accepted: 2020/01/20 | Published: 2020/03/20
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