Predicting the occurrence of antagonism within ternary guanidine mixture pollutants based on the concentration ratio of components.

The widespread prevalence and coexistence of diverse guanidine compounds pose substantial risks of potential toxicity interactions, synergism or antagonism, to environmental organisms. This complexity presents a formidable challenge in assessing the risks associated with various pollutants. Hence, a method that is both accurate and universally applicable for predicting toxicity interactions within mixtures is crucial, given the unimaginable diversity of potential combinations. A toxicity interaction prediction method (TIPM) developed in our past research was employed to predict the toxicity interaction, within guanidine compound mixtures. Here, antagonism were found in the mixtures of three guanidine compounds including chlorhexidine (CHL), metformin (MET), and chlorhexidine digluconate (CDE) by selecting Escherichia coli (E. coli) as the test organism. The antagonism in the mixture was probably due to the competitive binding of all three guanidine compounds to the anionic phosphates of E. coli cell membranes, which eventually lead to cell membrane rupture. Then, a good correlation between toxicity interactions (antagonisms) and components' concentration ratios (pis) within binary mixtures (CHL-MET, CHL-CDE, MET-CDE) was established. Based on the correlation, the TIPM was constructed and accurately predicted the antagonism in the CHL-MET-CDE ternary mixture, which once again proved the accuracy and applicability of the TIPM method. Therefore, TIPM can be suggested to identify or screen rapidly the toxicity interaction within ternary mixtures exerting potentially adverse effects on the environment.

Alginate capped and manganese doped ZnS quantum dots as a phosphorescent probe for time-resolved detection of copper(II).

A method is described for the detection of Cu(II). It is based on the use of a room-temperature phosphorescent probe consisting of alginate-capped and manganese(II)-doped ZnS quantum dots. The carboxy groups at the surface of the probe strongly coordinate Cu(II) to form a complex. As a result, the 4T1-6A1 transition of the Mn(II) ions in the probe is quenched, and the long decay time (~2.1 ms in the unquenched state) is accordingly reduced. At excitation/emission wavelengths of 316/590 nm and a delay time of 0.1 ms, the probe shows a linear response in the 0.01 to 12 µM Cu(II) concentration range. The detection limit is 6.0 nM and the RSD is 3.2% (for n = 5). Graphical Abstract A two-step procedure is described to synthesize alginate capped manganese doped ZnS QDs. These coordinate with Cu(II) to form an absorbent complex and can be used as a phosphorescent probe for time-resolved detection of Cu(II).

Characterizing the Existence of Fluorescence Quenching Agents Using EEM Fluorescence and UV Spectra: Taking the Interaction of Humic Acid and Fe(â ¢) as an Example.

The fluorescence quenching agents was characterized with three-dimensional fluorescence and ultraviolet (UV) spectra. When there was Fe (Ⅲ) in the sample, the humic fluorescence would be quenched and their UV spectra were not affected. The variation of fluorescence intensity (I) at Ex/Em=300/510 nm and UV absorbance(A) at UV300 were investigated in the article. The smaller the ratio of fluorescence intensity versus UV absorbance (I/A) is, the higher the fluorescence quencher Fe(Ⅲ) concentration is. According to Stern-Volmer equation I/I0=1-fc×Kc×[c] /(1+Kc×[c] ) and fitted function I/A=f×[k/(cFe3++c)+b] , the fitted fluorescent quenching constant Kc was ranged between 1.08 to 1.15, the ratio of bounded fluorophores versus total fluorophores, i.e. fc, was ranged between 1.10 to 1.14. The ratio of fluorescence intensity and absorbance of humic acid was fitted with Fe(Ⅲ) concentration and the constants were acquired as following: f=0.83～1.19, k=587.19～612.19, c=0.87～0.92, b=-87.09～-46.36. The correlation curve values were 0.99. The Stern-Volmer formula was used to describe the quenching effect of humic acid fluorescence by Fe (Ⅲ). However, due to the fact that the fluorescence intensity I0 without quencher was difficult to acquire during the analysis of practical samples, the fitted function between the ratio of I/A and Fe(Ⅲ) was used to reflect the quenching effect of Fe(Ⅲ) on the fluorescence of humic acid, which was based on the correlations between the fluorescence intensity I0 and ultraviolet absorbance A. The fitted formula was used to predict the iron ions concentration of the resin separated and concentrated samples from wastewater treatment plant and receiving waters. The predicted values were in good accordance with those determined with inductively coupled plasma atomic emission spectroscopy(ICP-AES) method when the iron ion concentration was above 0.4 mg·L-1, which could be used to ascertain the existence of fluorescence quenching agent and their corresponding concentration.

Near Infrared Spectroscopy Study on Nitrogen in Shortcut Nitrification and Denitrification Using Principal Component Analysis Combined with BP Neural Networks.

To achieve efficient nitrogen removal and rapid detection of ammonia nitrogen and nitrite nitrogen, principal component analysis and neural networks were used to establish quantitative analysis model of ammonia nitrogen and nitrite nitrogen in shortcut nitrification and denitrification based on near infrared spectroscopy­BP neural networks model. The results showed that ammonia nitrogen concentration decreased from 45.3 to 2.7 mg·L-1 after aerobic, and nitrite nitrogen concentration increased from 0.01 to 19.6 mg·L-1, while nitrite nitrogen concentration decreased from 19.6 to 1.2 mg·L-1 after anoxic, which means that rapid nitrification and denitrification are successfully achieved. The principal component analysis of the original near infrared spectra for water samples showed the first 13 principal components represented the information of the original spectrum data, with cumulative contribution rate being 95.04%. In this way, redundant information can be eliminated to reduce the number of dimensions in the model. The spectral data matrix is accordingly reduced from 192×2203 to 192×13, which contributes greatly to easier calculations and improves the accuracy of the model. The correction results of BP neural networks model showed the coefficient of determination for ammonia nitrogen and nitrite nitrogen concentration was 0.950 4 and 0.976 2 respectively, with the root mean square error of calibration being 0.016 6 and 0.010 9. BP neural networks model yields predicted values fitting well with the expected values for ammonia nitrogen and nitrite nitrogen concentration, with R2 being 0.974 0 and 0.981 4 respectively, with the root mean square error of prediction being 0.033 7 and 0.028 7, suggesting that BP neural networks model had a good prediction results for ammonia nitrogen and nitrite nitrogen concentration. The study demonstrated that ammonia nitrogen and nitrite nitrogen concentration can be rapidly predicted with BP neural networks based analysis of the near infrared spectroscopy of the water sample in shortcut nitrification and denitrification, which may provide timely and flexible control to shortcut nitrification and denitrification operation according to the ammonia nitrogen and nitrite nitrogen concentration changes, and makes a quick and effective detection technique for denitrification.

Analysis of poly-ß-hydroxyalkonates (PHA) during the enhanced biological phosphorus removal process using FTIR spectroscopy.

Enhanced biological phosphorus removal (EBPR) is the main phosphorus removal technique for wastewater treatment. During the anaerobic-aerobic alternative process, the activated sludge experienced the anaerobic storage of polyhydroxy-ß-alkonates (PHA) and aerobic degradation, corresponding the infrared peak intensity of sludge at 1 740 cm(-1) increased in the aerobic phase and declined in the anaerobic phase. Compared with PHA standard, this peak was indentified to attribute the carbonyl of PHA. The overlapping peaks of PHA, protein I and II bands were separated using Gaussian peak fitting method. The infrared peak area ratios of PHA versus protein I had a good relationship with the PHA contents measured by gas chromatography, and the correlation coefficient was 0.873. Thus, the ratio of the peak area of PHA versus protein I can be considered as the indicator of the PHA content in the sludge. The infrared spectra of 1 480-1 780 cm(-1) was selected, normalized and transferred to the absorption data. Combined with the chromatography analysis of PHA content in the sludge sample, a model between the Fourier-transform infrared spectroscopy (ETIR) spectra of the sludge and PHA content was established, which could be used for the prediction of the PHA content in the unknown sample. The PHA content in the sludge sample could be acquired by the infrared spectra of the sludge sample and the established model, and the values fitted well with the results obtained from chromatograph. The results would provide a novel analysis method for the rapid characterization and quantitative determination of the intracellular PHA content in the activated sludge.

Identifying the component responsible for antagonism within ionic liquid mixtures using the up-to-down procedure integrated with a uniform design ray method.

Various chemicals in the environment always exist as mixtures. Toxicity interaction within mixtures may pose potential hazards and risks to the environmental safety and human health. Recent studies showed that toxicity interaction by ionic liquid (IL) mixtures can be related to a certain component. To identify the component, we developed a novel procedure integrating an up-to-down process with the uniform design-based ray method (UDUD) and applied it into an IL mixture system of four 1-butyl-3-methylimidazolium ILs (simply [bmim]X) where X=Cl(-), Br(-), CH3OSO3(-) and CH3(CH2)7OSO3(-). It was shown that two mixture rays in the quaternary system exhibited significant antagonistic interaction. In this paper, the UDUD was first employed to design four ternary mixture systems. The microplate toxicity analysis was used to determine the toxicities of various mixtures to a freshwater photobacterium Vibrio qinghaiensis sp.-Q67. The concentration addition was taken as an additive reference to assess the toxicity interactions taking place in mixtures. The results revealed that some ternary mixture rays including [bmim]CH3(CH2)7OSO3 display antagonism while the ternary rays without [bmim]CH3(CH2)7OSO3 exhibit additivity. On these grounds, we again designed all binary mixtures containing [bmim]CH3(CH2)7OSO3, determined their toxicities and assessed toxicity interaction. The results showed that three binary mixture systems produce antagonism. Thus, it may be concluded that [bmim]CH3(CH2)7OSO3 is indeed a key component inducing mixture antagonism.

Preparation and characterization of visible-light-active nitrogen-doped TiO2 photocatalyst.

A visible-light photocatalyst was prepared by calcination of the hydrolysis product of Ti(SO4)2 with ammonia as precipitator. The color of this photocatalyst was vivid yellow. It could absorb light under 550 nm wavelength. The crystal structure of anatase was characterized by XRD. The structure analysis result of X-ray fluorescence (XRF) shows that doped-nitrogen was presented in the sample. The photocatalytic activities were evaluated using methyl orange and phenol as model pollutants. The photocatalytic activities of samples were increasing gradually with calcination temperature from 400 degrees C to 700 degrees C under UV irradiation. It can be seen that the degradation of methyl orange follows zero-order kinetics. However, the calcination temperatures have no significant influence on the degradation of phenol under sunlight. The N-doped catalyst shows higher activity than the bare one under solar irradiation.