Methylene blue removal using prepared activated carbon from grape wood wastes: adsorption process analysis and modeling

An adsorption study has been conducted for activated carbon obtained from grape wood wastes to assess their capability to remove methylene blue (MB) from the aqueous solutions. The properties of prepared activated carbon were characterized using FTIR, BET and SEM analyses. The effects of independent variables such as initial concentration of MB (100–500 mg L−1), initial pH of solution (3–11), adsorbent dosage (0.25–12.25 g L−1) and contact time (10–90 min) on the MB adsorption have been optimized using response surface methodology. The highest MB removal efficiency was 98% when pH, MB and adsorbent dosage were 11, 100 mg L−1 and 12.25 g L−1, respectively. The experimental data have been tested using Langmuir and Freundlich isotherm models, and the achieved data were fully fitted with the Langmuir model (R2 = 0.99), which indicates the monolayer adsorption. The adsorption kinetics well followed by the pseudo-second-order model with R2 of 0.99. This prepared activated carbon as a low-cost and eco-friendly adsorbent can be used widely for water and wastewater treatment.

Predicting H2S emission from gravity sewer using an adaptive neuro-fuzzy inference system

A predictive model to estimate hydrogen sulfide (H2S) emission from sewers would offer engineers and asset managers the ability to evaluate the possible odor/corrosion problems during the design and operation of sewers to avoid in-sewer complications. This study aimed to model and forecast H2S emission from a gravity sewer, as a function of temperature and hydraulic conditions, without requiring prior knowledge of H2S emission mechanism. Two different adaptive neuro-fuzzy inference system (ANFIS) models using grid partitioning (GP) and subtractive clustering (SC) approaches were developed, validated, and tested. The ANFIS-GP model was constructed with two Gaussian membership functions for each input. For the development of the ANFIS-SC model, the MATLAB default values for clustering parameters were selected. Results clearly indicated that both the best ANFIS-GP and ANFIS-SC models produced smaller error compared with the multiple regression models and demonstrated a superior predictive performance on forecasting H2S emission with an excellent R2 value of >0.99. However, the ANFIS-GP model possessed fewer rules and parameters than the ANFIS-SC model. These findings validate the ANFIS-GP model as a potent tool for predicting H2S emission from gravity sewers.

Seasonal hydrological and water quality performance of individual and in-series stormwater infrastructures as treatment trains in cold climate

The performance of stormwater treatment trains and of their individual green infrastructure was evaluated near Montreal, Canada. Three treatment trains were studied: Train 1 – five bioretention cells in series with a wet retention pond; Train 2 – an infiltration trench in series with a dry detention pond and Train 3 – Train 2 in series with a wet retention pond. A total of 47 rain events were monitored to quantity the hydrological performance, while water quality samples were taken during 24 rainfall events. During the summer, the bioretention cells led to a reduction in runoff volumes varying from 8 to 100%. Overall, the three studied treatment trains and all of the individual infrastructures, except for the dry pond, provided reductions in the mean concentrations of total suspended solids, chemical oxygen demand, total nitrogen and total phosphorous. Results also showed that the use of a train of stormwater infrastructures can be more effective to reach Quebec's legislated targets than single infrastructures to remove those four contaminants, but only if the infrastructures are sequenced properly. Indeed, the addition of a dry basin at the end of Train 2 reduced the removal efficiency of the four studied contaminants.

A review on adsorbent parameters for removal of dye products from industrial wastewater

Industrial effluents are usually one of the major industries polluting the environment and surface water. It is estimated that the worldwide production of dyes is about 70 tons/year. To overcome this problem, innovative processes are suggested for the treatment of industrial effluents containing dyes and heavy metals. The goal of the processes is often to reduce the toxicity of these pollutants in order to meet treatment standards. Recently, great attention has been paid to innovative processes for physical and chemical removal techniques such as adsorption on new adsorbents, biomass adsorption, membrane filtration, irradiation, and electrochemical coagulation. In this study, the application of adsorbents in the adsorption process to remove dye pollutants from industrial effluents has been studied. Factors affecting dye adsorption such as pH, temperature, initial dye concentration, and adsorbent amount are also presented. The obtained results revealed that more than 80% of the dye adsorption on the surface of adsorbents are endothermic processes and more than 95% of the processes obey the pseudo-second-order kinetic model.

Predicting water quality trends resulting from forest cover change in an agriculturally dominated river basin in Eastern Ontario, Canada

Agricultural extensification and forest cover loss can significantly impact aquatic ecosystems. This study considered the conversion of forests to agriculture (and vice versa) in an agriculturally dominated watershed in Eastern Ontario, Canada. A series of de- and reforestation scenarios were developed, and water quantity/quality simulations were executed using the Soil and Water Assessment Tool (SWAT) using 30 years of real-world weather observations. Results indicated that streamflow and sediment loads were not sensitive to forest loss, while continuing the recent rate of deforestation of 0.8% (0.2% of the watershed area) per year would, by 2032, increase annual loads of nitrate by 5.6%, total nitrogen by 1.5%, and total phosphorus by 6.8%. Additionally, the same land-use scenarios were simulated with the inclusion of vegetated filter strips (VFS) and grassed waterways. Some reforestation scenarios were sufficient to reduce total nitrogen concentrations below water quality guidelines, particularly under the combined effect of VFSs along all river reaches. However, meeting water quality guidelines for total phosphorus concentrations requires additional improvements to management practices beyond those simulated here.

Emerging pollutants and antibiotics removed by conventional activated sludge followed by ultraviolet radiation in a municipal wastewater treatment plant in Mexico

Different groups of emerging pollutants (EPs) were identified (drugs, pesticides, hormones, illicit drugs, and fire retardant), and the removal of four antibiotics was determined (sulfamethoxazole 62.2–94.4%, ciprofloxacin 71–83.1%, norfloxacin 82–89%, and ofloxacin 78–97.9%) in a municipal wastewater treatment plant (WWTP) in Acapulco, Gro. Mexico. The compounds were extracted from influent and effluent samples by solid phase extraction (SPE). The identification of non-target EPs was performed by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). The antibiotic quantification was performed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Most of the non-target compounds were detected only in the influent samples. Antibiotics levofloxacin and nalidixic acid, the anticonvulsants carbamazepine and oxycarbamazepine, the local anesthetic lidocaine, and the pesticide tridemorph were the main EPs not removed by the WWTP. In this study, it was shown that the Aguas Blancas WWTP does not manage to remove 100% of the various EPs identified in the effluent, although the elimination degree is high in most cases, despite being one of the model plants in Mexico.

Antibiotic resistance in predominantly occurring gram-negative bacterial community from treated sewage Jaipur to assess the need for going beyond coliform standards

Antibiotic resistance surveillance is an objective of global action plan on antimicrobial resistance endorsed by the World Health Organization. The current study reports the identification of frequently occurring Gram-negative bacterial community (GNBC) previously isolated from municipal treated wastewater and their antibiotic resistance profiles. Further, the genes responsible for extended-spectrum beta lactamases (ESBL) activity were identified in ESBL-positive organisms. The isolates were characterized using biochemical assays and identification was confirmed by VITEK®2 automated system. Antibiotic susceptibility testing against seven different classes of antibiotics was also performed on the same system using AST-N280 cards. The most dominant isolates identified were Acinetobacter baumannii, Morganella morganii, Kluyvera intermedia, Stenotrophomonas maltophilia, Escherichia coli, Aeromonas hydrophila/caviae, Klebsiella pneumoniae, Enterobacter cloacae and Citrobacter freundii. The isolates were observed to be significantly resistant against the antibiotics amoxicillin-clavulanic acid, cefuroxime, cefuroxime axetil and colistin. Two of the isolates, E. cloacae sp. dissolvens and S. maltophilia, were found to be positive for ESBL activity encoded by blaCTX-M gene. The possible intrusion of hospital wastewater in domestic sewage is also discussed. This study may help assess the risk of wastewater reuse by detecting dominant bacteria as a step towards the development of new microbiological standards.

Evaluation of Yangon city tap water quality and the efficacy of household treatment

Yangon was one of the first cities in Asia to establish a tap water system. However, the city's water supply infrastructure now lags far behind those of other regions as a consequence of political instability over the last six decades. The installation of disinfection facilities in the tap water system and the enactment of the Myanmar National Drinking Water Quality Standard (MNDWQS) were accomplished only recently during the short period of democratic government. Due to the lack of reliable published information, the suitability of the tap water for drinking remains unclear to city residents. The quality of tap water and bottled water in the central business district was examined to assess compliance with the MNDWQS. The results showed that 95% of tap water delivered to homes was contaminated with Escherichia coli or coliform bacteria. Only 14% of bottled water was free of E. coli and coliform contamination. The efficacy of household treatment devices was tested, and ceramic purifiers (CPs) and reverse osmosis (RO) devices were found to be highly (>99%) effective for E. coli elimination. RO devices performed better in terms of dissolved organic carbon reduction at 60% compared with 43% reduction with CPs.

A genetic algorithm-based support vector machine to estimate the transverse mixing coefficient in streams

Transverse mixing coefficient (TMC) is known as one of the most effective parameters in the two-dimensional simulation of water pollution, and increasing the accuracy of estimating this coefficient will improve the modeling process. In the present study, genetic algorithm (GA)-based support vector machine (SVM) was used to estimate TMC in streams. There are three principal parameters in SVM which need to be adjusted during the estimating procedure. GA helps SVM and optimizes these three parameters automatically in the best way. The accuracy of the SVM and GA-SVM algorithms along with previous models were discussed in TMC estimation by using a wide range of hydraulic and geometrical data from field and laboratory experiments. According to statistical analysis, the performance of the mentioned models in both straight and meandering streams was more accurate than the regression-based models. Sensitivity analysis showed that the accuracy of the GA-SVM algorithm in TMC estimation significantly correlated with the number of input parameters. Eliminating the uncorrelated parameters and reducing the number of input parameters will reduce the complexity of the problem and improve the TMC estimation by GA-SVM.

Soil phosphorus composition, loss risk and contribution to the aquatic environment in a typical agricultural area

River eutrophication risk increased significantly in agricultural areas. In this paper, spatial variability of soil phosphorus (P) and loss risk in the Jialu River Basin, China, were analyzed using a geostatistical approach. The correlation between soil and river sediment P was analyzed to identify the main aquatic P source. The results showed that inorganic phosphorus (IP) was the main form of soil TP (82.13%), but the ratio of apatite phosphorus (AP) and non-apatite phosphorus (NAIP) varied between different soil types. AP was the primary form of IP in fluvo-aquic cinnamon soil, while NAIP dominated in meadow aeolian sandy soil. Calculated soil total dissolvable P (TDP, 94–622 mg/kg) exceeded the environmental threshold. High TDP (>400 mg/kg) in mixed soil and sandy soil indicated a high P loss risk. The spatial variability of soil P was moderate to weak, indicating a low heterogeneity. In sediment, IP and AP showed a significant correlation with total organic carbon (p < 0.05), indicating a P source of soil erosion. Sediment AP had a significant positive correlation with soil AP (p < 0.05), confirming soil as the main source of sediment P. Furthermore, an accumulation of sediment P along the Jialu River and its consistency with water TP was revealed.