Experimental and economic evaluation of nitrate removal by a nanofiltration membrane

Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose

This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe0-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characterization results, the specific surface area of Fe0-CMC measured by the Brunauer-Emmett-Teller analysis were 39.6 m2/g. In addition, Scanning Electron Microscopy images displayed that spherical nano zero-valent iron particles (nZVI) with an average particle diameter of 80 nm are surrounded by carboxymethyl cellulose and no noticeable aggregates were detected. Batch experiments assessed Fe0-CMC's effectiveness in nitrate removal under diverse conditions including different adsorbent dosages (Cs, 2-10 mg/L), contact time (t, 10-1440 min), initial pH (pHi, 2-10), temperature (T, 10-55 °C), and initial concentration of nitrate (C0, 10-500 mg/L). Results indicated decreased removal with higher initial pHi and C0, while increased Cs and T enhanced removal. The study of nitrate removal mechanism by Fe0-CMC revealed that the redox reaction between immobilized nZVI on the CMC surface and nitrate ions was responsible for nitrate removal, and the main product of this reaction was ammonium, which was subsequently completely removed by the synthesized nanocomposite. In addition, a stable deviation quantum particle swarm optimization algorithm (SD-QPSO) and a least square error method were employed to train the ANFIS parameters. To demonstrate model performance, a quadratic polynomial function was proposed to display the performance of the SD-QPSO algorithm in which the constant parameters were optimized through the SD-QPSO algorithm. Sensitivity analysis was conducted on the proposed quadratic polynomial function by adding a constant deviation and removing each input using two different strategies. According to the sensitivity analysis, the predicted removal efficiency was most sensitive to changes in pHi, followed by Cs, T, C0, and t. The obtained results underscore the potential of the ANFIS model (R2 = 0.99803, RMSE = 0.9888), and polynomial function (R2 = 0.998256, RMSE = 1.7532) as accurate and efficient alternatives to time-consuming laboratory measurements for assessing nitrate removal efficiency. These models can offer rapid insights and predictions regarding the impact of various factors on the process, saving both time and resources.

Advancing towards electro-bioremediation scaling-up: On-site pilot plant for successful nitrate-contaminated groundwater treatment

The potential of nitrate electro-bioremediation has been fully demonstrated at the laboratory scale, although it has not yet been fully implemented due to the challenges associated with scaling-up bioelectrochemical reactors and their on-site operation. This study describes the initial start-up and subsequent stable operation of an electro-bioremediation pilot plant for the treatment of nitrate-contaminated groundwater on-site (Navata site, Spain). The pilot plant was operated under continuous flow mode for 3 months, producing an effluent suitable for drinking water in terms of nitrates and nitrites (<50 mg NO3- L-1; 0 mg NO2- L-1). A maximum nitrate removal rate of 0.9 ± 0.1 kg NO3- m-3 d-1 (efficiency 82 ± 18 %) was achieved at a cathodic hydraulic retention time (HRTcat) of 2.0 h with a competitive energy consumption of 4.3 ± 0.4 kWh kg-1 NO3-. Under these conditions, the techno-economic analysis estimated an operational cost of 0.40 € m-3. Simultaneously, microbiological analyses revealed structural heterogeneity in the reactor, with denitrification functionality concentrated predominantly from the centre to the upper section of the reactor. The most abundant groups were Pseudomonadaceae, Rhizobiaceae, Gallionellaceae, and Xanthomonadaceae. In conclusion, this pilot plant represents a significant advancement in implementing this technology on a larger scale, validating its effectiveness in terms of nitrate removal and cost-effectiveness. Moreover, the results validate the electro-bioremediation in a real environment and encourage further investigation of its potential as a water treatment.

Characteristics of polycyclic aromatic hydrocarbons (PAHs) removal by nanofiltration with and without coexisting organics

Polycyclic aromatic hydrocarbons (PAHs) are contaminants of great concern owing to their persistence, toxicity, and bioaccumulation in aquatic environments. In this study, nanofiltration (NF) was used to investigate the removal of naphthalene (NAP) and phenanthrene (PHE) using three membranes of NF270, NF90, and DK. Subsequently, we examined the effects of coexisting organics on PAHs removal. Based on the results, DK was determined to be the optimal membrane for removing PAHs by comparing the membrane flux and pollutant rejection. The membrane flux reached 34.32 L/m2·h, and the NAP and PHE rejections were 92.21% and 97.85%, respectively, at transmembrane pressure (TMP) of 5 bar using DK. Coexisting organics decreased the membrane fluxes of NF270 and DK in the following order: protein > glucose > humic acid. The NAP and PHE rejections were obviously improved using NF270 in the following order: humic acid > protein > glucose. The PHE rejection was slightly improved using DK. A low concentration of organics could reduce the NAP rejection using DK; however, the NAP rejection could be restored at high concentrations of organics, except for humic acid. Coexisting organics could cause severe membrane fouling. The order of the effect of different coexisting organics on membrane fouling was protein > humic acid > glucose. The total investment and operating costs were about 1.47 and 0.187 million dollars, respectively, for treating PAHs solution using DK when the feed flow was 300 m3/d.