Avicenna Journal of Environmental Health Engineering

Review Article

30/6/2017

Cyanobacteria Characteristics and Methods for Isolation and Accurate Identification of Cyanotoxins: A Review Article

Tengku Nadiah Yusof, Mohd Rafatullah, Rohaslinda Mohamad, Norli Ismail, Zarina Zainuddin, Japareng Lalung

Cyanobacteria are bacteria found in different ecosystems, such as lakes and rocks. These bacteria, capable of photosynthesis, are important sources of oxygen. However, some cyanobacterial strains can produce toxins, which are harmful to humans and animals. Therefore, collection of epidemiological and surveillance data on cyanobacterial toxins in the environment is vital to ensure a low risk of exposure to toxins in other organisms. For presentation of accurate data on environmental cyanobacterial toxins, it is essential to understand their characteristics, including taxonomy, toxin proteins, and genomic structures, and determine their environmental effects on bacterial populations and toxin production. Taxonomy, which is the scientific classification of organisms, is important in identifying species producing toxins. The structure of toxin proteins and their stability in the environment allow researchers to detect toxins with analytical methods and discuss their limitations. On the other hand, identifying toxins via molecular typing enables researchers to investigate toxic cyanobacteria by detecting toxin-encoding genes and toxin gene expression. Meanwhile, environmental factors, such as nutrient level, light intensity, and biotic factors, allow researchers to predict the suitable time and location for accurate sampling. In this review, these cyanobacterial features, which are important for accurate detection of cyanobacterial toxins, will be discussed.

Review Article

30/6/2017

A Review of Groundwater Pollution Potential Threats from Municipal Solid Waste Landfill Sites: Assessing the Impact on Human Health

Priyanka Kumari, N.C. Gupta, A. Kaur

An attempt has been made in this paper to review various studies associated with groundwater contamination near landfill sites, basically caused by non-engineered landfills or open dumps in India and overseas, and its impact on human health. Landfill leachate contains different kinds of municipal toxic wastes as well as heavy metal, which finally percolates into the ground and joins the groundwater table. Consuming such water results in severe health hazards and may sometimes be fatal if consumed for long periods. Several studies have shown evidence on the high concentration of heavy metals in leachate as well as in nearby groundwater sources. Moreover, various studies have confirmed the fact that there is an increased threat of adverse health effects (low birth weight, birth defects, and certain types of cancers), congenital malformations in children, and higher risks for malformations of the nervous and musculoskeletal systems for skin, hair, and nails in local residents. Pregnant women and children are more vulnerable to these pollutants, and newborn children are more prone to the health risk. These findings may signify the real health risks associated with residents residing near landfill sites.

Research Article

30/6/2017

Comparison Between the Performance of Activated Carbon and Graphene in Removal of Reactive Red 198

Mohammad Reza Samarghandi, Ali Poormohammadi, Samane Shanesaz, Kazem Godini

The current study aimed at comparing the performances of activated carbon and graphene in the removal of reactive red 198. The experiments were conducted in a batch reactor and the effects of some operational parameters including initial dye concentration, pH, contact time, and different doses of activated carbon and graphene on the removal efficiency of dye were investigated. The results showed that the adsorption efficiency was affected by initial dye concentration. In general, with increasing contact time up to 180 minutes, the removal efficiency increased significantly. The removal efficiency of reactive red 198 increased with increasing contact time, and after 60 minutes of contact time, adsorption phase reached the equilibrium. When activated carbon was used, the maximum removal efficiency happened at pH 3. At this pH value, reactive red 198 was removed completely (100%) after 120 minutes, whereas the minimum efficiency was observed at pH 10. A similar trend was also observed for graphene as an adsorbent. Moreover, the removal efficiency of the dye by both adsorbents increased with the increase of the adsorbent dosage. The experimental data showed that the adsorption of reactive red198 on both active carbon and graphene fitted well into the second-order kinetic model. Active carbon and graphene fitted well Langmuir 1 model. According to the results, graphene acts as suitable adsorbent and can be applied in treating several industrial effluents and contaminated water in greater scales. The main upside of grapheme, in comparison with activated carbon, is that it reaches the equilibrium in a shorter time. Further, grapheme adsorbed the dye nearly completely (98% to 100%).

Research Article

30/6/2017

Evaluation of the Efficiency of Wastewater Treatment Plants in the Removal of Common Antibiotics from Municipal Wastewater in Hamadan, Iran

Reza Shokoohi, Abdollah Dargahi, Razieh Khamutian, Yaser Vaziri

The presence of antibiotics in the environment, especially aquatic environments, is a major health and environmental concern. Wastewater treatment plants play an important role in the treatment of municipal and industrial wastewater and removal of contaminants. The aim of this study was to determine the concentration of prevalent antibiotics in municipal wastewater of Hamadan, Iran and to evaluate the removal efficiency of wastewater treatment plants. During 3 months (April, May, and June 2016), a total of 12 composite influent and effluent samples were collected from the wastewater treatment plants. Solid-phase extraction (SPE) was used for preparing the samples, which were then analyzed using high-performance liquid chromatography (HPLC) with UV detection. Based on the analysis of 6 antibiotics, three antibiotics, including amoxicillin, imipenem, and cefixime, were detected, and their concentrations were measured at 1.6, 10.7, and 5.8 ug/L, respectively. The removal efficiency of these antibiotics in wastewater treatment plants was 55.66%, 34.01%, and 24.33%, respectively. Due to the presence of examined antibiotics in the effluent and influent wastewater treatment plants, they might cause direct and indirect effects on human health and environment if proper measures are not taken by the authorities. Since the removal of these antibiotics from wastewater treatment plants is relatively poor, it is suggested to use advanced wastewater treatment plants to reduce antibiotics in effluent wastewater and decrease the adverse effects of these micropollutants.

Research Article

30/6/2017

Adsorption of Arsenite from Aqueous Solutions Using Granola Modified Lemon Peel

Mohammad Hossien Salmani Nodoushan, Zinab Parvizi, Fatemah Mirzai Nodoushan, Mohammad Taghi Ghaneian

The arsenite species is a common form of arsenic in nature and ground waters and is categorized as a major public health group. In the present study, the arsenite ions from contaminated solutions were removed by adsorption on the granola modified lemon peel. The arsenite adsorption on lemon peel was investigated by various concentrations of arsenite with 0.2 g/100 mL of adsorbent at a range of pH 3 - 10 and a constant temperature of 25°C for 0 to 240 minutes using batch experiments. Data of the adsorption experiment were analyzed by the pseudo-first and second- order kinetic equations. The Freundlich and Langmuir isotherm models were used to understand the adsorption relationship between the arsenite ions and functional groups on the lemon peel. pH equal to 5.2 was recorded as pH_zpc of this adsorbent in aqueous solution. The optimum condition was obtained at 60 minutes, pH value 8, and 2 mg/L of arsenite, with a removal efficiency of 88%. The maximum adsorption capacity of granola lemon peel was 27 mg.g^-1 in Langmuir model. Lemon peel adsorbent presented good removal efficiency for arsenite in contaminated aqueous solutions and real water.

Research Article

24/6/2017

A Comparison of Performance of Artificial Neural Networks for Prediction of Heavy Metals Concentration in Groundwater Resources of Toyserkan Plain

Meysam Alizamir, Soheil Sobhanardakani

Nowadays, about 50% the world’s population is living in dry and semi dry regions and has utilized groundwater as a source of drinking water. Therefore, forecasting of pollutant content in these regions is vital. This study was conducted to compare the performance of artificial neural networks (ANNs) for prediction of As, Zn, and Pb content in groundwater resources of Toyserkan Plain. In this study, two types of artificial neural networks (ANNs), namely multi-layer perceptron (MLP) and Radial Basis Function (RBF) approaches, were examined using the observations of As, Zn, and Pb concentrations in groundwater resources of Toyserkan plain, Western Iran. Two statistical indicators, the coefficient of determination (R²) and root mean squared error (RMSE) were employed to evaluate the performances of various models. The results indicated that the best performance could be obtained by MLP, in terms of different statistical indicators during training and validation periods.

Research Article

25/6/2017

Application of Poisson Hidden Markov Model to Predict Number of PM2.5 Exceedance Days in Tehran During 2016-2017

Fatemeh Sarvi, Azam Nadali, Mahmoud Khodadost, Melika Kharghani Moghaddam, Majid Sadeghifar

PM2.5 is an important indicator of air pollution. This pollutant can result in lung and respiratory problems in people. The aim of the present study was to predict number of PM2.5 exceedance days using Hidden Markov Model considering Poisson distribution as an indicator for people susceptible to that particular level of air quality. In this study, evaluations were made for number of PM2.5 exceedance days in Tehran, Iran, from Oct. 2010 to Dec. 2015. The Poisson hidden Markov model was applied considering various hidden states to make a two-year forecast for number of PM2.5 exceedance days. We estimated the Poisson Hidden Markov’s parameters (transition matrix, probability, and lambda) by using maximum likelihood method. By applying the Akaike Information Criteria, the hidden Markov model with three states was used to make the prediction. The results of forecasting mean, median, mode, and interval for the three states of Poisson hidden Markov model are reported. The results showed that the number of exceedance days in a month for the next two years using the third state of the model would be 5 to 16 days. The predicted mode and mean for the third months afterward at the third state were 11 and 11. These predictions showed that number of exceedance days (predicted mean of 6.87 to 11.39 days) is relatively high for sensitive individuals according to the PM2.5 Air Quality Index. Thus, it is essential to monitor levels of suspended particulate air pollution in Tehran.

Research Article

30/6/2017

Preparation of Magnetic Multi-Walled Carbon Nanotubes to Adsorb Sodium Dodecyl Sulfate (SDS)

Zahra Rahmani, Mohammad Taghi Samadi

Surfactants are one of the main groups of pollutants released into aqueous solutions due to human activities and their harmful effects have been proven on human. In this study, first, magnetic multi-walled carbon nanotubes (MMWCNTs) were synthesized and then, the effects of operating parameters such as surfactant concentration, adsorbent dosage, and pH values were analyzed on the adsorption process. MMWCNTs were characterized by means of X-ray diffraction (XRD) analysis and fourier transform infrared spectroscopy (FTIR). The optimal adsorption conditions were achieved at initial pH = 4.6, adsorbent concentration = 0.5 g/L, and initial SDS concentration = 15 mg/L. In addition, the equilibrium of sorption reached after 120 min and the maximum capacity of SDS for monolayer coverage was found to be 61 mg/g at 25°C. Kinetic studies were performed under optimal conditions and the sorption kinetics was described using the pseudo-second-order kinetic model. The experimental data were studied using Freundlich, Langmuir, and Sips models. Finally, the experimental data were fitted reasonably by Langmuir isotherm. The results demonstrated that MMWCNTs with respect to their high adsorption capacity, relatively low equilibrium time, and capability to be separated from aqueous solutions (after adsorption) could be applied to wastewater treatment.

Avicenna Journal of Environmental Health Engineering: Jun 2017, 4 (1), 8 articles.