Characterization of the Toxicities of Cd-Ni and Cd-Cr Binary Mixtures Using Combination Index Method

Direct equipartition ray design was used to construct Cd-Ni and Cd-Cr binary mixtures. Microplate toxicity analysis was used to evaluate the toxicity of individual substance and the Cd-Ni and Cd-Cr mixtures on Chlorella pyrenoidosa and Selenastrum capricornutum. The interacting toxicity of the mixture was analyzed with concentration addition (CA) model. In addition, combination index method (CI) was proposed and used to quantitatively characterize the toxicity of the binary mixtures of CdNi and Cd-Cr observed in experiment and find the degree of deviation from the predicted outcome of the CA model, that is, the intensity of interacting toxicity. Results indicate that most of the 20 binary mixtures exhibit enhancing and synergistic effect, and only Cd-Cr-R4 and Cd-Cr-R5 mixtures have relatively high antagonistic effects against C. pyrenoidosa. Based on confidence interval, CI can compare the intensities of interaction of the mixtures under varying levels of effect. The characterization methods are applicable for analyzing binary mixture with complex interaction

Construction of Ideological and Political Education Innovation and Development Platform of Colleges and Universities Based on Big Data Technology under the Concept of Green Ecological Development

This paper combines association rules and collaborative filtering algorithms to build a course recommendation method that considers personalized learning characteristics on the innovative development platform of Civic and Political Education in colleges and universities. The related algorithms in the association rules are used to visualize and analyze the association of the 10 main contents of the Civic and Political courses and give the combination of the contents of the Civic and Political courses. By analyzing the mastery and interest of students on the platform, we push the combination of courses that meet the personalized needs of students according to their knowledge, ability and interest. The constructed personalized teaching platform is used in actual teaching, and the application of association rules in course analysis and personalized push function is analyzed to prove the effectiveness of the platform. The impact of the platform on teaching is evaluated by comparing the students’ performance under platform learning to that under traditional teaching. The results show that the average scores of the Civics course content of group D1 are all above 80, and the significance value of the difference between group D1 and D2 is 4.21% < less than 5%, indicating that there is an obvious achievement difference between the two groups. In the recommended course content of Student 2, the score of the combination course A4 and A7 was 8.2158, and the learning interest rating was 17.326, which was 0.769 higher than the sum of the interest ratings of the two courses alone

Prediction and Evaluation of the Mixture Toxicity of Twelve Phenols and Ten Anilines to the Freshwater Photobacterium Vibrio qinghaiensis sp.-Q67

Twelve substituted phenols and ten substituted anilines were chosen to investigate if the dose addition and independent action models can be used to evaluate the mixture toxicity of phenolic and aniline derivatives (PADs). Their photobacterium toxicity to the freshwater luminescent bacterium Vibrio qinghaiensis sp.-Q67 showed that the two-parameter Weibull or Logit function could be effectively applied to describe the dose-response relationships. The joint toxicity of three equivalent-effect concentration ratio (EECR) mixtures and twelve uniform design concentration ratio (UDCR) mixtures could be well evaluated using the dose addition (DA) or the independent action (IA) model within 95% confidence intervals

Synchronous organics removal and copper reduction in semiconductor wastewater with energy recuperation via photocatalytic fuel cell

An effective PFC constructed from ZnO/Zn photoanode and carbon cloth cathode has been proposed to oxidatively degrade organics and reductively treat Cu (II) in the semiconductor wastewater accompanied with electricity production. The cell electrical performance with open circuit voltage of 835 V, maximum power density of 0.003623 mW cm-2 and short circuit current density of 0.0506 mA cm-2 can be obtained using optimized catalyst loading of 1.0 g L-1 and semiconductor wastewater concentration of 10 mg L-1. Under the optimal test, more photogenerated electrons will be facilitated for charge carrier separation in the photoanode, accelerating the organics degradation on anode, and subsequently the electron migrating to cathode for Cu (II) reduction. A complete mineralization with 10 mg L-1 COD and more than 70% Cu (II) removal efficiency can be attained within 180 min. A good reproducibility test has been also witnessed because of the stable photoanode and cathode materials. This work may pave an effective and sustainable approach to concurrently eliminate two kinds of contaminants with energy recuperation in a single chamber

peel extract mediated eco-friendly synthesis of solar light-active ZnO nanosponge for enhanced dyeing wastewater degradation

ZnO nanosponge was synthesized for the first time via a green method using Musa acuminata peel extract. The X-ray diffraction, Raman, energy dispersive X-ray and fourier-transform infrared analyses demonstrated that the synthesized sample was well crystallized and possessed hexagonal wurtzite pure ZnO. The field-emission scanning electron microscopy observation revealed that the ZnO nanosponge was assembled by aggregated spherical particles with sizes of 30-128 nm. Under simulated solar light irradiation, the ZnO nanosponge acted as an excellent photocatalyst for methylene blue and rhodamine B mixtures degradation compared to commercially available TiO2-P25. The enhanced photocatalytic activities of ZnO sample can be attributed to the high generation of hydroxyl radicals as a result of its unique sponge-like porous structure with large surface area. Furthermore, the ZnO nanosponge can be used effectively on the photodegradation of real textile dye wastewater. These characteristics showed that the biosynthesized ZnO nanosponge can be employed as a photocatalyst for environmental remediation

Degradation Characteristics and Remediation Ability of Contaminated Soils by Using &beta;-HCH Degrading Bacteria

Three degradation strains that can utilize &beta;-Hexachlorocyclohexanes (&beta;-HCH) as the sole carbon source were isolated from the soil substrate of constructed wetland under long-term &beta;-HCH stress, and they were named A1, J1, and M1. Strains A1 and M1 were identified as Ochrobactrum sp. and strain J1 was identified as Microbacterium oxydans sp. by 16S rRNA gene sequence analysis. The optimum conditions for degradation with these three strains, A1, J1, and M1, were pH = 7, 30 &deg;C, and 5% inoculum amount, and the degradation rates of 50 &mu;g/L &beta;-HCH under these conditions were 58.33%, 51.96%, and 50.28%, respectively. Degradation characteristics experiments showed that root exudates could increase the degradation effects of A1 and M1 on &beta;-HCH by 6.95% and 5.82%, respectively. In addition, the degradation bacteria A1 and J1 mixed in a ratio of 1:1 had the highest degradation rate of &beta;-HCH, which was 69.57%. An experiment on simulated soil remediation showed that the compound bacteria AJ had the best effect on promoting the degradation of &beta;-HCH in soil within 98 d, and the degradation rate of &beta;-HCH in soil without root exudates was 60.22%, whereas it reached 75.02% in the presence of root exudates. The addition of degradation bacteria or degradation bacteria-root exudates during soil remediation led to dramatic changes in the community structure of the soil microorganisms, as well as a significant increase in the proportion of aerobic and Gram-negative bacterial groups. This study can enrich the resources of &beta;-HCH degrading strains and provided a theoretical basis for the on-site engineering treatment of &beta;-HCH contamination

Degradation Characteristics and Remediation Ability of Contaminated Soils by Using <i>β</i>-HCH Degrading Bacteria

Three degradation strains that can utilize β-Hexachlorocyclohexanes (β-HCH) as the sole carbon source were isolated from the soil substrate of constructed wetland under long-term β-HCH stress, and they were named A1, J1, and M1. Strains A1 and M1 were identified as Ochrobactrum sp. and strain J1 was identified as Microbacterium oxydans sp. by 16S rRNA gene sequence analysis. The optimum conditions for degradation with these three strains, A1, J1, and M1, were pH = 7, 30 °C, and 5% inoculum amount, and the degradation rates of 50 μg/L β-HCH under these conditions were 58.33%, 51.96%, and 50.28%, respectively. Degradation characteristics experiments showed that root exudates could increase the degradation effects of A1 and M1 on β-HCH by 6.95% and 5.82%, respectively. In addition, the degradation bacteria A1 and J1 mixed in a ratio of 1:1 had the highest degradation rate of β-HCH, which was 69.57%. An experiment on simulated soil remediation showed that the compound bacteria AJ had the best effect on promoting the degradation of β-HCH in soil within 98 d, and the degradation rate of β-HCH in soil without root exudates was 60.22%, whereas it reached 75.02% in the presence of root exudates. The addition of degradation bacteria or degradation bacteria-root exudates during soil remediation led to dramatic changes in the community structure of the soil microorganisms, as well as a significant increase in the proportion of aerobic and Gram-negative bacterial groups. This study can enrich the resources of β-HCH degrading strains and provided a theoretical basis for the on-site engineering treatment of β-HCH contamination

Predictive QSAR Models for the Toxicity of Disinfection Byproducts

Several hundred disinfection byproducts (DBPs) in drinking water have been identified, and are known to have potentially adverse health effects. There are toxicological data gaps for most DBPs, and the predictive method may provide an effective way to address this. The development of an in-silico model of toxicology endpoints of DBPs is rarely studied. The main aim of the present study is to develop predictive quantitative structure–activity relationship (QSAR) models for the reactive toxicities of 50 DBPs in the five bioassays of X-Microtox, GSH+, GSH−, DNA+ and DNA−. All-subset regression was used to select the optimal descriptors, and multiple linear-regression models were built. The developed QSAR models for five endpoints satisfied the internal and external validation criteria: coefficient of determination (R2) &gt; 0.7, explained variance in leave-one-out prediction (Q2LOO) and in leave-many-out prediction (Q2LMO) &gt; 0.6, variance explained in external prediction (Q2F1, Q2F2, and Q2F3) &gt; 0.7, and concordance correlation coefficient (CCC) &gt; 0.85. The application domains and the meaning of the selective descriptors for the QSAR models were discussed. The obtained QSAR models can be used in predicting the toxicities of the 50 DBPs

Purification Effects on β-HCH Removal and Bacterial Community Differences of Vertical-Flow Constructed Wetlands with Different Vegetation Plantations

This study aimed to investigate the removal of β-hexachlorocyclohexane (β-HCH) at realistic concentration levels (10 µg/L) in different plant species in constructed wetlands (Acorus calamus, Canna indica, Thalia dealbata, and Pontederia cordata) and the structure of the rhizosphere microbial community response of each group during summer and winter. Results showed that all groups of constructed wetlands had very good decontamination efficiency against β-HCH in water (90.86–98.17%). The species that most efficiently purified β-HCH in water was A. calamus in summer (98.17%) and C. indica in winter (96.64%). Substrate sorption was found to be the major pathway for β-HCH removal from water in the constructed wetlands. The ability of the wetland plants to absorb and purify β-HCH was limited, and C. indica had the strongest absorptive capacity among the four plant species. The mean β-HCH removal from the matrix of the planted plants increased by 5.8% compared with that of the control treatment (unplanted plants). The average β-HCH content in the plant rhizosphere substrate was 4.15 µg/kg lower than that in the non-rhizosphere substrate. High-throughput sequencing analysis revealed significant differences (P Actinobacteria and Sphingomonas remarkably increased over time in summer

Efficient performance of magnesium oxide loaded biochar for the significant removal of Pb2+ and Cd2+ from aqueous solution

Lead (Pb) and cadmium (Cd) are considered as a typical heavy metals in aqueous solution, which may pose adverse health effects on human beings. For the removal of these two pollutants, magnesium oxide (MgO) was successfully immobilized onto eucalyptus biochar (BC) matrix via simple and cost-effective pyrolysis process of MgCl2-pretreated eucalyptus biomass under high temperature (500 °C). Synthesized MgO nanoparticles-biochar composites (MBC) exhibited superior removal performance for target pollutants, and achieve 99.9% removal efficiency for Pb(II) and Cd(II) at optimum conditions (0.02 g, pH in range of 4–7, and reaction time 120, 240 min). Furthermore, the maximum theoretical adsorbing amount of MBC was 829.11 mg/g for Pb(II) and 515.17 mg/g for Cd(II). Pseudo-second-order model and Langmuir models were well-determined for isotherm and adsorption kinetics. FTIR, XRD, and XPS analysis revealed that precipitation and ion exchange was of great importance for the removal of contaminants. Besides, cation-π interaction and complexation from the carbon-containing functional groups should not be neglected. Considering the advantage of low-cost, facile preparation, and brilliant adsorption capacity, it is anticipated that MBC has a promising prospect for the broad application in Pb(II)/Cd(II)-containing wastewater treatment