Effectiveness and intermediates of microcystin-LR degradation by UV/H2O2 via 265 nm ultraviolet light-emitting diodes.

Although the degradation of cyanotoxins by 254 nm UV/H2O2 has been well elucidated, the efficiency and mechanism involved are not necessarily true for other UV wavelengths. The degradation of microcystin-LR (MC-LR), a representative cyanotoxin, was explored by UV/H2O2 using 265 nm ultraviolet light-emitting diode (UV-LED). The results indicated that 265 nm UV/H2O2 treatment had a high removal efficiency of MC-LR ([MC-LR] = 0.1 µM, apparent rate constants reached 0.2077 min-1, half-time at 3.3 min). The qualitative analyses demonstrated that three novel intermediates, C48H74N10O15 (molecular weight = 1030.5335), C36H58N10O14 (854.4134), and C33H54N10O14 (814.3821), were generated in 265 nm UV/H2O2. Five published intermediates were also confirmed. The generative pathway of these products mainly involved free hydroxyl radical oxidation, resulting in consecutive hydroxyl substitutions and hydroxyl additions of unsaturated bonds in MC-LR. The toxicity of MC-LR was weaken with a relative low mineralization. The electrical energy per order values were calculated to be in the range of 0.00447 to 0.00612 kWh m-3 order-1 for 100-5000 µg L-1 MC-LR. Overall, 265 nm UV-LED/H2O2 can be used as an alternative effective technology to improve the removal efficiency of MC-LR in water.

Degradation of ciprofloxacin by 280 nm ultraviolet-activated persulfate: Degradation pathway and intermediate impact on proteome of Escherichia coli.

In this study, the degradation of ciprofloxacin (CIP) was explored using ultraviolet activated persulfate (UV/PS) with 280 nm ultraviolet light-emitting diodes (UV-LEDs), and the toxicological assessment of degrading intermediates was performed using iTRAQ labeling quantitative proteomic technology. The quantitative mass spectrum results showed that 280 nm UV/PS treatment had a high transformation efficiency of CIP ([CIP] = 3 µM, [S2O82-] = 210 µM, apparent rate constants 0.2413 min-1). The high resolution mass spectrum analyses demonstrated that the primary intermediates included C15H16FN3O3 (m/z 306.1248) and C17H18FN3O4 (m/z 348.1354). The former one was formed by the cleavage of piperazine ring, while the later one was generated by the addition of a hydroxyl on the quinolone backbone. The toxicological assessment demonstrated that 56 and 110 proteins had significant up regulations and down regulations, respectively, in the Escherichia coli exposed to degraded CIP compared to untreated CIP. The majority of up-regulated proteins, such as GapA, SodC, were associated with primary metabolic process rather than responses to stress and toxic substance, inferring that the moderate UV/PS treatment can reduce the antibacterial activity of CIP by incomplete mineralization. Consequently, these results provided a novel insight into the application of UV-LED/PS treatment as a promising removal methodology for quinolones.

Sequential dynamic artificial neural network modeling of a full-scale coking wastewater treatment plant with fluidized bed reactors.

This study proposed a sequential modeling approach using an artificial neural network (ANN) to develop four independent models which were able to predict biotreatment effluent variables of a full-scale coking wastewater treatment plant (CWWTP). Suitable structure and transfer function of ANN were optimized by genetic algorithm. The sequential approach, which included two parts, an influent estimator and an effluent predictor, was used to develop dynamic models. The former parts of models estimated the variations of influent COD, volatile phenol, cyanide, and NH4 (+)-N. The later parts of models predicted effluent COD, volatile phenol, cyanide, and NH4 (+)-N using the estimated values and other parameters. The performance of these models was evaluated by statistical parameters (such as coefficient of determination (R (2) ), etc.). Obtained results indicated that the estimator developed dynamic models for influent COD (R (2) = 0.871), volatile phenol (R (2) = 0.904), cyanide (R (2) = 0.846), and NH4 (+)-N (R (2) = 0.777), while the predictor developed feasible models for effluent COD (R (2) = 0.852) and cyanide (R (2) = 0.844), with slightly worse models for effluent volatile phenol (R (2) = 0.752) and NH4 (+)-N (R (2) = 0.764). Thus, the proposed modeling processes can be used as a tool for the prediction of CWWTP performance.

Novel insights into anoxic/aerobic(1)/aerobic(2) biological fluidized-bed system for coke wastewater treatment by fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) was applied to investigate the contaminant removal efficiency and fluorescent characteristic variations in a full scale coke wastewater (CWW) treatment plant with a novel anoxic/aerobic(1)/aerobic(2) (A/O(1)/O(2)) process, which combined with internal-loop fluidized-bed reactor. Routine monitoring results indicated that primary contaminants in CWW, such as phenols and free cyanide, were removed efficiently in A/O(1)/O(2) process (removal efficiency reached 99% and 95%, respectively). Three-dimensional excitation-emission matrix fluorescence spectroscopy and PARAFAC identified three fluorescent components, including two humic-like fluorescence components (C1 and C3) and one protein-like component (C2). Principal component analysis revealed that C1 and C2 correlated with COD (correlation coefficient (r)=0.782, p<0.01 and r=0.921, p<0.01), respectively) and phenols (r=0.796, p<0.01 and r=0.914, p<0.01, respectively), suggesting that C1 and C2 might be associated with the predominating aromatic contaminants in CWW. C3 correlated with mixed liquor suspended solids (r=0.863, p<0.01) in fluidized-bed reactors, suggesting that it might represent the biological dissolved organic matter. In A/O(1)/O(2) process, the fluorescence intensities of C1 and C2 consecutively decreased, indicating the degradation of aromatic contaminants. Correspondingly, the fluorescence intensity of C3 increased in aerobic(1) stage, suggesting an increase of biological dissolved organic matter.

Principal component analysis to assess the efficiency and mechanism for enhanced coagulation of natural algae-laden water using a novel dual coagulant system.

A novel dual coagulant system of polyaluminum chloride sulfate (PACS) and polydiallyldimethylammonium chloride (PDADMAC) was used to treat natural algae-laden water from Meiliang Gulf, Lake Taihu. PACS (Aln(OH)mCl3n-m-2k(SO4)k) has a mass ratio of 10 %, a SO4 (2-)/Al3 (+) mole ratio of 0.0664, and an OH/Al mole ratio of 2. The PDADMAC ([C8H16NCl]m) has a MW which ranges from 5 × 10(5) to 20 × 10(5) Da. The variations of contaminants in water samples during treatments were estimated in the form of principal component analysis (PCA) factor scores and conventional variables (turbidity, DOC, etc.). Parallel factor analysis determined four chromophoric dissolved organic matters (CDOM) components, and PCA identified four integrated principle factors. PCA factor 1 had significant correlations with chlorophyll-a (r=0.718), protein-like CDOM C1 (0.689), and C2 (0.756). Factor 2 correlated with UV254 (0.672), humic-like CDOM component C3 (0.716), and C4 (0.758). Factors 3 and 4 had correlations with NH3-N (0.748) and T-P (0.769), respectively. The variations of PCA factors scores revealed that PACS contributed less aluminum dissolution than PAC to obtain equivalent removal efficiency of contaminants. This might be due to the high cationic charge and pre-hydrolyzation of PACS. Compared with PACS coagulation (20 mg L(-1)), the removal of PCA factors 1, 2, and 4 increased 45, 33, and 12 %, respectively, in combined PACS-PDADMAC treatment (0.8 mg L(-1) +20 mg L(-1)). Since PAC contained more Al (0.053 g/1 g) than PACS (0.028 g/1 g), the results indicated that PACS contributed less Al dissolution into the water to obtain equivalent removal efficiency.

Principal component analysis to assess the composition and fate of impurities in a large river-embedded reservoir: Qingcaosha Reservoir.

Qingcaosha Reservoir (QR) is the largest river-embedded reservoir in east China, which receives its source water from the Yangtze River (YR). The temporal and spatial variations in dissolved organic matter (DOM), chromophoric DOM (CDOM), nitrogen, phosphorus and phytoplankton biomass were investigated from June to September in 2012 and were integrated by principal component analysis (PCA). Three PCA factors were identified: (1) phytoplankton related factor 1, (2) total DOM related factor 2, and (3) eutrophication related factor 3. Factor 1 was a lake-type parameter which correlated with chlorophyll-a and protein-like CDOM (r = 0.793 and r = 0.831, respectively). Factor 2 was a river-type parameter which correlated with total DOC and humic-like CDOM (r = 0.668 and r = 0.726, respectively). Factor 3 correlated with total nitrogen and phosphorus (r = 0.864 and r = 0.621, respectively). The low flow speed, self-sedimentation and nutrient accumulation in QR resulted in increases in PCA factor 1 scores (phytoplankton biomass and derived CDOM) in the spatial scale, indicating a change of river-type water (YR) to lake-type water (QR). In summer, the water temperature variation induced a growth-bloom-decay process of phytoplankton combined with the increase of PCA factor 2 (humic-like CDOM) in the QR, which was absent in the YR.