Evaluation of heavy metal pollution in sediments, water and macrobenthos of Hur Al-Azim wetland (Khuzestan)

Background and Objectives: Chemical storage of water cannot provide complete information about the extent of bioavailability of metals in the environment, while the study of this storage in the chain of water, sediment and macrobenthos can make the rate of rotation and storage risk more visible in ecosystems. Hur Al-Azim wetland is located in the west of Khuzestan Province. Large parts of it have dried up due to the development of Azadegan oil field and the spread of heavy metal pollution in its environment, which can provide serious risks to this ecosystem and the people around it. Therefore, the present study aimed to evaluate the concentrations of heavy metals cadmium, nickel, lead and vanadium in water, sediments and macrobenthos of Hur Al-Azim wetland, as a region with high oil activity. Methods: This study was conducted in winter 2017 to investigate the concentrations of heavy metals cadmium, nickel, lead and vanadium in 8 stations in Hur Al-Azim wetland. The statistical population for measuring heavy metals with three replications included 24 water samples, 24 sediment samples and 24 macrobenthos samples. Among them, the species in macrobenthos samples were identified after washing in a 0.5-micron sieve. After digestion of the samples, the concentration of the elements was measured by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) model Vista Pro Axial. Comparison of heavy metal data from water and sediment samples was performed using SPSS23 software. Shapiro-Wilk test was also used to investigate the normal distribution of results. One-way analysis of variance was used for general comparisons and Tukey test was used for multiple comparisons and differences were significant at 95% level. Findings: The concentration of heavy metals in sediments was higher than that of water and macrobenthos, While the concentration of these metals in macrobenthos was higher compared to water (P <0.05). Heavy metals had the lowest concentration in station 1 (Chazabeh) as a station without oil activity and the highest level in station 4 (between pad 3 to pad 12) as a station with high oil activity (P <0.05). Pad 3 to Pad 12, along with Pad 9 to Pad 12, had the highest enrichment index for all metals. The lowest index of nickel, vanadium and cadmium enrichment index was measured in Chazabeh station and the lowest level of lead enrichment index was measured in Shatt Ali station. Regarding the index of heavy metal pollution factor, the distance station of Pad 3 to Pad 12 with values ​​of 4, 1.16, 0.86 and 3.41 for cadmium, nickel, lead and vanadium had the highest value of this index. Also, Chazabeh station with values ​​of 3.25, 0.18 and 0.54 for cadmium, nickel and vanadium metals and Shatt Ali station with values ​​of 0.58 for lead metal showed the lowest value of this index. The distance between Pad 3 and Pad 12 with a value of 1.92 also had the highest PLI index. In the studied stations in Hur Al-Azim wetland, 10 macrobenthos families (Valvatidae, Vnionidae, Thiaridae, Hydrobiidae, Physidae, Chironomidae, Ceratopogonidae, Sinmuliidae, Gomphidae and Tipulidae) and 11 genera were identified. Among them, Chadabeh station with 43.8 showed the highest bio-index of BMWP and with 4.86 the highest bio-index of ASPT. Conclusion: Finally, it was found that due to the continuation of oil extraction activities and discharge of toxic pollutants into Hur Al-Azim wetland, there is great potential for rapid and cumulative increase in the concentration of metals, especially vanadium and cadmium and their crossing the critical limit. Indicators for measuring the severity of sediment pollution showed the station between Pad 3 and Pad 12 as the most polluted station in Hur al-Azim wetland compared to Chazabeh station. The correlation between the concentration of heavy metals in sediment and macrobenthos, in addition to emphasizing the uptake and transport of metals along the food chain, showed that macrobenthos can be used as the best biological indicators.