The Use of Artificial Neural Network (ANN) for Modeling of Ammonia Nitrogen Removal from Landfill Leachate by the Ultrasonic Process

Background: The study examined the implementation of artificial neural network (ANN) for the prediction of Ammonia nitrogen removal from landfill leachate by ultrasonic process.Methods: A three-layer backpropagation neural network was optimized to predict Ammonia nitrogen removal from landfill leachate by ultrasonic process. Considering the smallest mean square error (MSE), The configuration of the backpropagation neural network was three-layer ANN with tangent sigmoid transfer function (Tansig) at hidden layer with 14 neurons, linear transfer function (Purelin) at output layer and Levenberg–Marquardt backpropagation training algorithm (LMA).Results: ANN predicted results were very close to the experimental results with correlation coefficient (R2) of 0.993 and MSE 0.000334. The sensitivity analysis showed that all studied variables (Contact time, ultrasound frequency and power and pH) had strong effect on Ammonia nitrogen removal. In addition, pH was the most influential parameter with relative importance of 44.9%.Conclusions: The results showed that neural network modeling could effectively predict Ammonia nitrogen removal from landfill leachate by ultrasonic process

The Use of Artificial Neural Network (ANN) for Modeling of Ammonia Nitrogen Removal from Landfill Leachate by the Ultrasonic Process

Background: The study examined the implementation of artificial neural network (ANN) for the prediction of Ammonia nitrogen removal from landfill leachate by ultrasonic process.Methods: A three-layer backpropagation neural network was optimized to predict Ammonia nitrogen removal from landfill leachate by ultrasonic process. Considering the smallest mean square error (MSE), The configuration of the backpropagation neural network was three-layer ANN with tangent sigmoid transfer function (Tansig) at hidden layer with 14 neurons, linear transfer function (Purelin) at output layer and Levenberg–Marquardt backpropagation training algorithm (LMA).Results: ANN predicted results were very close to the experimental results with correlation coefficient (R2) of 0.993 and MSE 0.000334. The sensitivity analysis showed that all studied variables (Contact time, ultrasound frequency and power and pH) had strong effect on Ammonia nitrogen removal. In addition, pH was the most influential parameter with relative importance of 44.9%.Conclusions: The results showed that neural network modeling could effectively predict Ammonia nitrogen removal from landfill leachate by ultrasonic process

The effect of industrial development on health hazard risk posed by drinking water containing heavy metals with HRAEPA index, Case study; Semnan province

Background: Developmental activities especially the establishment of more than 20 industrial units in Semnan province caused the officers worries about increased concentration of heavy metals in drinking water supplies and probably increasing of health risk at consumers. The aim of the study was to investigate the effect of Semnan province industrial development on the health risk level caused by drinking waters heavy metals with HRAEPA index.Methods: For this descriptive-analytical study, sampling from 17 wells was perfumed at first. Then the heavy metals concentrations were measured at laboratory with Standard methods (Arsenic, Cadmium and Mercury with Atomic Absorption GTA-95 - Lead and Chromium with Atomic Absorption Spectrophotometry). Meantime, HRAEPA index was calculated with three step process of health risk assessment. Statistical analysis was performed by Repeated Measure، One sample T-test and One-Way ANNOVA methods. Finally, zoning map of heavy metals in Semnan province has been prepared with GIS.Results: Results showed that the levels of all heavy metals are at national, WHO and EU standard ranges. HRAEPA indexes was 4.48Í10-4, 4.36Í10-4 and 4.46Í10-4 for 2001-2011, 2012-2015 and 2015 period, respectively. Also, the highest and lowest HRAEPA index was for 2001-2011 and 2015, respectively.Conclusions: The study showed that the heavy metals concentrations in groundwater resources were lower than threshold toxic level. However with the industrial development started at Semnan province, water resources quality must be protected by law enforcement and tight supervision on industrial and mining-excavation activities.

The effect of industrial development on health hazard risk posed by drinking water containing heavy metals with HRAEPA index, Case study; Semnan province

Background: Developmental activities especially the establishment of more than 20 industrial units in Semnan province caused the officers worries about increased concentration of heavy metals in drinking water supplies and probably increasing of health risk at consumers. The aim of the study was to investigate the effect of Semnan province industrial development on the health risk level caused by drinking waters heavy metals with HRAEPA index.Methods: For this descriptive-analytical study, sampling from 17 wells was perfumed at first. Then the heavy metals concentrations were measured at laboratory with Standard methods (Arsenic, Cadmium and Mercury with Atomic Absorption GTA-95 - Lead and Chromium with Atomic Absorption Spectrophotometry). Meantime, HRAEPA index was calculated with three step process of health risk assessment. Statistical analysis was performed by Repeated Measure، One sample T-test and One-Way ANNOVA methods. Finally, zoning map of heavy metals in Semnan province has been prepared with GIS.Results: Results showed that the levels of all heavy metals are at national, WHO and EU standard ranges. HRAEPA indexes was 4.48Í10-4, 4.36Í10-4 and 4.46Í10-4 for 2001-2011, 2012-2015 and 2015 period, respectively. Also, the highest and lowest HRAEPA index was for 2001-2011 and 2015, respectively.Conclusions: The study showed that the heavy metals concentrations in groundwater resources were lower than threshold toxic level. However with the industrial development started at Semnan province, water resources quality must be protected by law enforcement and tight supervision on industrial and mining-excavation activities.

Protein Recovery from Dairy Sludge by Fenton Process

Background: Holding excessive amount of sludge has turned into a major problem for the wastewater treatment plants. Nucleic acids, enzymes, proteins, and polysaccharides are some organic materials which could be found in the sludge. The main objective of this study was to investigate the efficiency of Fenton process in protein recovery from dairy sludge.Methods: Our case for the study was the waste activated sludge produced at the wastewater treatment plant of Fajr dairy industry in Shahrood, Iran. Fenton process was applied to a 1.5 L sludge sample. At first, the pH of the sludge was adjusted to 3 using H2SO4. The second step was the addition of Fe(II) at certain concentrations. Then, different H2O2 concentrations were added to the sample. The mixed sample was stirred at 120 rpm for 6 h and was neutralized with Ca(OH)2.The sludge was dewatered in the pilot-scale filter press and filtered. The soluble protein content in the supernatant of the disintegrated sludge derived from the Fenton process was recovered by dialysis and dried at −40°C for 24 h.Results: The results showed that after the Fenton process, SSi, TCODi, SCODi, and SCODa levels were 11275, 13800, 115, and 3450 mg/L respectively. Also, after the Fenton process, the concentration of the soluble proteins increased from 52.48 to 1732 mg/L, whereas after subsequent protein recovery, its concentration in the supernatant was 1180 mg/L.Conclusions: Based on the findings, the protein recovered from the excess sludge throughout the Fenton process can be used as animal feed

Protein Recovery from Dairy Sludge by Fenton Process

Background: Holding excessive amount of sludge has turned into a major problem for the wastewater treatment plants. Nucleic acids, enzymes, proteins, and polysaccharides are some organic materials which could be found in the sludge. The main objective of this study was to investigate the efficiency of Fenton process in protein recovery from dairy sludge.Methods: Our case for the study was the waste activated sludge produced at the wastewater treatment plant of Fajr dairy industry in Shahrood, Iran. Fenton process was applied to a 1.5 L sludge sample. At first, the pH of the sludge was adjusted to 3 using H2SO4. The second step was the addition of Fe(II) at certain concentrations. Then, different H2O2 concentrations were added to the sample. The mixed sample was stirred at 120 rpm for 6 h and was neutralized with Ca(OH)2.The sludge was dewatered in the pilot-scale filter press and filtered. The soluble protein content in the supernatant of the disintegrated sludge derived from the Fenton process was recovered by dialysis and dried at −40°C for 24 h.Results: The results showed that after the Fenton process, SSi, TCODi, SCODi, and SCODa levels were 11275, 13800, 115, and 3450 mg/L respectively. Also, after the Fenton process, the concentration of the soluble proteins increased from 52.48 to 1732 mg/L, whereas after subsequent protein recovery, its concentration in the supernatant was 1180 mg/L.Conclusions: Based on the findings, the protein recovered from the excess sludge throughout the Fenton process can be used as animal feed

Assessment and Spatial Distribution of Mineral Groundwater Quality in Ardabil Province, Iran

Background: The present study was conducted to determine the quality of mineral ground waters and analyze their spatial distribution in Ardabil Province of Iran.Methods: This descriptive analytical study was carried out on natural mineral water wells in Ardabil Province over one year. Samples of water were taken from a total of 44 wells in this province every season, from April 2016 to February 2017. They were then transferred to Khak Azmay-e Moghan Laboratory and their Total Dissolved Solids (TDS), chloride, calcium, magnesium, sulfate, sodium and bicarbonate were measured based on the instructions presented in Standard Methods. The Ground Water Quality Index (GWQI) was then determined based on the measured parameters. The spatial distribution of the ground waters based on the GWQI was then also determined in a Geographic Information System (GIS).Results: The GWQI varied extensively in the natural mineral water wells of Ardabil Province, from 24.88 to 312.58. The best physicochemical quality based on the GWQI was observed in Hammam-e Sangi and the poorest quality in Saghezji-Mardaneh. According to the index, 2.5% of the wells were of very good quality, 30% were of good quality, 32% of moderate quality, 13.5% of poor quality and 22% were of inappropriate quality.Conclusions: According to the results, the most important quality problems included high levels of TDS, chlorine and sulfate and low pH values. Considering that these wells supply people’s drinking water in this region, consumers should be warned of their water quality, and purification procedures should also be carried out to allow the hygienic use of these valuable resources

Assessment and Spatial Distribution of Mineral Groundwater Quality in Ardabil Province, Iran

Background: The present study was conducted to determine the quality of mineral ground waters and analyze their spatial distribution in Ardabil Province of Iran.Methods: This descriptive analytical study was carried out on natural mineral water wells in Ardabil Province over one year. Samples of water were taken from a total of 44 wells in this province every season, from April 2016 to February 2017. They were then transferred to Khak Azmay-e Moghan Laboratory and their Total Dissolved Solids (TDS), chloride, calcium, magnesium, sulfate, sodium and bicarbonate were measured based on the instructions presented in Standard Methods. The Ground Water Quality Index (GWQI) was then determined based on the measured parameters. The spatial distribution of the ground waters based on the GWQI was then also determined in a Geographic Information System (GIS).Results: The GWQI varied extensively in the natural mineral water wells of Ardabil Province, from 24.88 to 312.58. The best physicochemical quality based on the GWQI was observed in Hammam-e Sangi and the poorest quality in Saghezji-Mardaneh. According to the index, 2.5% of the wells were of very good quality, 30% were of good quality, 32% of moderate quality, 13.5% of poor quality and 22% were of inappropriate quality.Conclusions: According to the results, the most important quality problems included high levels of TDS, chlorine and sulfate and low pH values. Considering that these wells supply people’s drinking water in this region, consumers should be warned of their water quality, and purification procedures should also be carried out to allow the hygienic use of these valuable resources