Removal of Mn2+ ions from drinking water by using Clinoptilolite and a Clinoptilolite-Fe oxide system

Clinoptilolite, a natural zeolite, was used for the synthesis of a high surface area Clinoptilolite-Iron oxide system, in order to be used for the removal of Mn2+ ions from drinking water samples. The new system was obtained by adding natural clinoptilolite in an iron nitrate solution under strongly basic conditions. The Clin-Fe system has specific surface area equal to 151.0 m2/g and is fully iron exchanged (Fe/Al = 1.23). Batch adsorption experiments were carried out to determine the effectiveness of the Clin and the Clin-Fe system in removal of manganese from drinking water. Adsorption experiments were conducted by mixing 1.00 g of each of the substrates with certain volume of water samples contaminated with 10 different Mn concentrations (from 3.64 x 10(-6) to 1.82 x 10(-2) M or from 0.2 to 1000 ppm). For the present experimental conditions, the Mn adsorption capacity of Clin was 7.69 mg/g, whereas, of Clin-Fe system was 27.12 mg/g. The main factors that contribute to difference adsorption capacity of the two solids are due to new surface species and negative charge of Clin-Fe system. In addition, the release of counterbalanced ions (i.e., Ca2+, Mg2+, Na+ and K+) was examined as well as the dissolution of framework Si and Al. It was found that for the most of the samples the Clin-Fe system releases lower concentrations of Ca, Mg and Na and higher concentrations of K than Clin, while the dissolution of Si/Al was limited. Changes in the composition of water samples as well as in their pH and conductivities values were reported and explained.     

Simultaneous removal of Cu, Mn and Zn from drinking water with the use of clinoptilolite and its Fe-modified form

Zeolites have been widely used in water treatment and especially clinoptilolite, due to its low cost and high abundance. It has large cation-exchange capacity and is capable of removing large quantities of heavy metals from contaminated water samples. By loading the surface of clinoptilolite with amorphous Fe-oxide species, a total improvement in adsorption capacity could be achieved. Thus, the Clin–Fe oxide system is capable of adsorbing significantly higher heavy metal concentrations than untreated clinoptilolite with simultaneous noticeable decrease in water hardness. Batch adsorption experiments have shown that Clin–Fe system has very large Cu, Zn and Mn adsorption capacity and for most of the cases the treated water samples were suitable for human consumption or agricultural use. New experiments were conducted to study the effectiveness of clinoptilolite and of the Clin–Fe system in removal of Cu, Mn, Zn, present simultaneously in water samples, so that the study of metal–sorbent chemical behavior and of the adsorption selectivity would be feasible. Desorption of metals was also examined and an integrated approach of the effectiveness of such materials in drinking water treatment is presented.     

Remediation of pharmaceutical contaminated water by use of magnetic functionalized metal organic framework. Physicochemical study of doxycycline adsorption

The presence of pharmaceutical pollutant, doxycycline (DOC) in water and waste streams has negative impact on the environment. In this research, metal organic framework was synthesized and functionalized by potassium nickel ferrocyanide (KNiFC). After characterisation, the functionalized adsorbent was used for removal of DOC from aqueous solutions. The adsorbent containing 80% of KNiFC exhibited the high adsorption capacity of 100 mg/g. The adsorption process was kinetically fast and the equilibration was established within 30 min. The used adsorbent retained 90% of its initial capacity after regeneration. The magnetic susceptibility of the adsorbent measured by VSM technique was 35 emu/g and sufficient for separation of the used adsorbent by external magnetic field. Isotherm models including Langmuir, Freundlich, Tempkin, Redlich‐Peterson, and Sips were applied to correlate the experimental equilibrium data. To evaluate the fitness of the isotherm equations error analysis methods, residual root mean square error and average relative error were used.     

Formation, modeling and validation of trihalomethanes (THM) in Malaysian drinking water: a case study in the districts of Tampin, Negeri Sembilan and Sabak Bernam, Selangor, Malaysia

A modeling procedure that predicts trihalomethane (THM) formation from field sampling at the treatment plant and along its distribution system using Tampin district, Negeri Sembilan and Sabak Bernam district, Selangor as sources of data were studied and developed. Using Pearson method of correlation, the organic matter measured as TOC showed a positive correlation with formation of THM (r=0.380,P=0.0001 for Tampin and r=0.478,P=0.0001 for Sabak Bernam). Similar positive correlation was also obtained for pH in both districts with Tampin (r=0.362,P=0.0010) and Sabak Bernam (r=0.215,P=0.0010). Chlorine dosage was also found to have low correlation with formation of THM for the two districts with Tampin (r=0.233,P=0.0230) and Sabak Bernam (r=0.505,P=0.0001). Distance from treatment plant was found to have correlation with formation of THM for Tampin district with r=0.353 and P=0.0010. Other parameters such as turbidity, ammonia, temperature and residue chlorine were found to have no correlation with formation of THM. Linear and non-linear models were developed for these two districts. The results obtained were validated using three different sets of field data obtained from own source and district of Seremban (Pantai and Sg. Terip), Negeri Sembilan. Validation results indicated that there was significant difference in the predictive and determined values of THM when two sets of data from districts of Seremban were used with an exception of field data of Sg. Terip for non-linear model developed for district of Tampin. It was found that a non-linear model is slightly better than linear model in terms of percentage prediction errors. The models developed were site specific and the predictive capabilities in the distribution systems vary with different environmental conditions.     

Probability of detecting and quantifying faecal contaminations of drinking water by periodically sampling for E. coli: a simulation model study

Drinking water supply companies monitor the presence of Escherichia coli in drinking water to verify the effectiveness of measures that prevent faecal contamination of drinking water. Data are lacking, however, on the sensitivity of the monitoring programmes, as designed under the EU Drinking Water Directive. In this study, the sensitivity of such a monitoring programme was evaluated by hydraulic model simulations of contamination events and calculations of the detection probability of the actual sampling programme of 2002. In the hydraulic model simulations of 16-h periods of 1l h(-1) ingress of untreated domestic sewage, the spread of the contamination through the network and the E. coli concentration dynamics were calculated. The results show that when large parts of the sewage reach reservoirs, e.g. when they originate from the treatment plant or a trunk main, mean detection probabilities are 55-65%. When the contamination does not reach any of the reservoirs, however, the detection probability varies from 0% (when no sampling site is reached) to 13% (when multiple sites are reached). Mean detection probabilities of nine simulated ingress incidents in mains are 5.5% with an SD of 6.5%. In reality, these detection probabilities are probably lower as the study assumed no inactivation or clustering of E. coli, 100% recovery efficiency of the E. coli detection methods and immediate mixing of contaminations in mains and reservoirs. The described method provides a starting point for automated evaluations and optimisations of sampling programmes.