Academic literature on the topic '4-Chlorophenol (4-CP)'

Adsorption and catalytic decomposition of 3- and 4-chlorophenols in the presence of hydrogen peroxide were studied for estimation of efficiency of the adsorption and catalytic methods for purification of solutions from chlorophenols related to special group of the priority toxic water pollutants. Activated carbon fiber and fiber modified with iron/iron oxide having highly developed surface and porous structure were used as the adsorbents. It was shown that adsorption of chlorophenols on the initial carbon fiber was higher as compared to the modified one and equaled to 309 mg/g for 3-chlorophenol and 301 mg/g for 4-chlorophenol. The sorption isotherm of 4-chlorophenol on the initial fiber is described by Langmuir equation with constant equals to 0.065 L/mg, while for composite sorbent constant equals to 0.037 L/mg. It was discovered that removal of chlorophenols from aqueous solutions in the processes of catalytic oxidation in the presence of a heterogeneous catalyst was more efficient than that in the adsorption process. Experimental data have been obtained on the dependence of the concentration of 3-and 4-chlorophenols on the time of destruction at specified pH values and the ratios of the pollutant and hydrogen peroxide. With an increase in the 4-chlorophenol: H2O2 ratio from 1:1 to 1:6, the degree of chlorophenol destruction increases from 75% to 88% (pH 3); when the pH changes from 1 to 9, the greatest degree of destruction is 70% (3-CP) and 87% (4-CP) was achieved at pH 3 (chlorophenol: H2O2 1:4). It was shown that in the system chlorophenol / H2O2 / catalyst there are optimal parameters (pH is 3 and chlorophenol : H2O2 ratio is 1:6), which provide the most complete removal of chlorophenol from solution. The results of chromatography-mass spectrometry analysis show that during contact with the modified fiber, the content of 4-CP decreases dramatically and degradation products are formed (for example, maleic acid), which is consistent with the known schemes for the oxidative destruction of chlorophenols.

To address problems associated with the potential toxicity of sludge when it is applied in land utilization, this study investigated the variations by which activated sludge becomes toxic when fed with wastewater containing mixed chlorophenols, and compared variations in sludge toxicity due to inputs of mixed chlorophenols and single chlorophenol groups. In this study, 4-chlorophenol (4-CP), 2,4,6-trichlorophenol (2,4,6-TCP) and mixed chlorophenols which consist of both 4-CP and 2,4,6-TCP were studied in sequencing batch reactors (SBR). The results indicate that in 0-30 d, the toxicity of sludge fed with mixed chlorophenols is higher than that of sludge fed with single chlorophenol groups. During 50-100 d, the toxicity of sludge fed with mixed chlorophenols ranged between two single chlorophenol groups. EPS and protein in EPS had a significant relationship with sludge toxicity, but there was no significant relationship between polysaccharide in EPS and sludge toxicity.

Electrooxidation of 4-chlorophenol in acidic solution was studied by cyclic voltammetry and in situ FTIR spectroscopy. Compared with platinum (Pt) and glassy carbon (GC) electrodes, carbon electrode exhibited a high electrocatalytic activity during the electrooxidation reaction of 4-chlorophenol. The possible mechanism of 4-chlorophenol on carbon electrode was studies by in situ FTIR. At first, 4-chlorophenol was electrooxidized to 4-chlorophenolic radical, and then to phenoxylic radical. Then, the radical was electrooxidized to hydroquinone, benzoquinone or unsaturated carboxylic acids with potential increasing. In addition, with the reaction of phenoxyl radicals, the insoluble aromatic ether oligomer generated on the carbon electrode surface and prevented the further oxidation reaction of 4-CP in some degree.

The combination of solar irradiation and Fenton reagent have been used to enhance the biodegradability (BOD5/COD) of chlorophenol wastewater, including 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), and 2,4-dichlorophenol (2,4-DCP). Results showed that the solar photo-Fenton process improved significantly the biodegradability of chlorophenol wastewater. Basically, increasing initial H2O2 dosage was much more beneficial for increasing biodegradability of wastewater than increasing initial Fe2 + dosage. Among the conditions studied, the optimum condition of increasing biodegradability of chlorophenol wastewater was found with a [H2O2]0/[Fe2 + ]0/[chlorophenol]0 ratio of 10.0/0.2/1.0, 10.0/0.3/1.0, and 10.0/0.2/1.0 for 2-CP, 4-CP, and 2,4-DCP, respectively. As a result, the value of BOD5/COD was increased from 0 for untreated solution up to 0.231, 0.248, and 0.193 for 2-CP, 4-CP, and 2,4-DCP, respectively with a 15-min treatment. Under the operation of optimum conditions, the oxidative state of chlorophenol wastewater could be easily controlled into a higher biodegradability stage. The COD and TOC degradation efficiency could be in excess of 90% on the whole as the preoxidized chlorophenol solution was treated by a following batch-type biological unit. In the meanwhile, the microtoxicity of wastewater reduced more than 95%.

Abstract Chlorophenols are extremely toxic to the environment and recalcitrant to biological degradation. Herein chemical degradation of 4-chlorophenol (4-CP) from aqueous solutions by zero-valent aluminum (Al), zero-valent iron (Fe), Al and Fe mixtures (Al/Fe mass ratio 90/10, labeled as Al/Fe10) and Al-Fe alloy (Al/Fe mass ratio 90/10, labeled as Al-Fe10) were investigated. No removal was found for 50 mg·L−1 4-CP under anoxic conditions at initial pH 2.5 during a period of 10 hrs while 56%, 83%, 78% and 99% of 4-CP were removed by Fe, Al, Al/Fe10 and Al-Fe10, respectively under aeration conditions. The removal of 4-CP by Al/Fe10 mixtures was primarily in the Fe mode in the beginning 4 h and then transitioned to the Al mode. The removal of 4-CP by Al-Fe10 alloy was accomplished via two intermediate products, hydroquinone (HQ) and 4-chlorocatechol (4-CC), and it was speculated that reactive oxygen species and hydroxyl radicals (·OH) play an important role in the degradation of 4-CP and that Al-Fe intermetallic compounds might catalyze the reactions. This study demonstrates that alloying Al with Fe offers a promising strategy for developing new materials for water and wastewater remediation.

Biodegradation of phenol and monochlorophenols (CPs) by a yeast strain of Rhodotorula glutinis was examined. The strain completely degraded 5 mM of phenol and utilized phenol as a sole carbon source. The strain may degrade phenol by the “ortho” type of ring fission because muconolactone was observed in the cultured broth. 3-Chlorophenol (3-CP) and 4-chlorophenol (4-CP) were well degraded and stoichiometric release of chloride ion was observed, but degradation of 2-chlorophenol was low with a small quantity of chloride ions. Biodegradability of 3-CP and 4-CP was increased by the addition of phenol or CPs to the medium at the cell cultivation. Since 4-chlorocatechol and maleylacetic acid were determined as metabolites of 3-CP and 4-CP by GC/MS analysis, dechlorination may take place between the formation of 4-chlorocatechol and maleylacetic acid.

The electrochemical oxidation of 4-chlorophenol (4-CP) in aqueous solution was studied by electrochemical oxidation using modified PbO2 electrode as anode. The influence of several operating parameters, such as initial 4-CP concentration, applied current density, and supporting electrolyte (Na2SO4) concentration was investigated. Ultraviolet spectroscopy and total organic carbon (TOC) measurements were conducted to study the kinetics of 4-CP electrochemical reaction and the mineralization efficiency of 4-CP. The experimental results showed that the 4-CP degradation always followed a pseudo-first-order kinetics. The higher mineralization of 4-CP and the lower current efficiency (CE) were obtained by the lower initial 4-CP concentration. The applied current density showed a positive influence on the degradation of 4-CP and the removal of TOC, but a higher applied current density led to a lower CE. Although Na2SO4 concentration of 0.05 M resulted in a higher 4-CP and TOC removal, the result of one-way analysis of variance (ANOVA) indicates that Na2SO4 concentration is not the significant parameter for 4-CP removal in electrochemical oxidation.

Uncertainty is pervasive in risk assessment. In ecotoxicological risk assessments, it arises from such sources as a lack of data, the simplification and abstraction of complex situations, and ambiguities in assessment endpoints (Burgman 2005; Suter 1993). When evaluating and managing risks, uncertainty needs to be explicitly considered in order to avoid erroneous decisions and to be able to make statements about the confidence that we can place in risk estimates. Although informative, previous approaches to dealing with uncertainty in ecotoxicological modelling have been found to be limited, inconsistent and often based on assumptions that may be false (Ferson & Ginzburg 1996; Suter 1998; Suter et al. 2002; van der Hoeven 2004; van Straalen 2002a; Verdonck et al. 2003a). In this thesis a Generalised Linear Modelling approach is proposed as an alternative, congruous framework for the analysis and prediction of a wide range of ecotoxicological effects. This approach was used to investigate the results of toxicity experiments on the effect of 2,4-Dichlorophenoxyacetic Acid (2,4-D) formulations and 4-Chlorophenol (4-CP, an associated breakdown product) on Daphnia carinata. Differences between frequentist Maximum Likelihood (ML) and Bayesian Markov-Chain Monte-Carlo (MCMC) approaches to statistical reasoning and model estimation were also investigated. These approaches are inferentially disparate and place different emphasis on aleatory and epistemic uncertainty (O'Hagan 2004). Bayesian MCMC and Probability Bounds Analysis methods for propagating uncertainty in risk models are also compared for the first time. For simple models, Bayesian and frequentist approaches to Generalised Linear Model (GLM) estimation were found to produce very similar results when non-informative prior distributions were used for the Bayesian models. Potency estimates and regression parameters were found to be similar for identical models, signifying that Bayesian MCMC techniques are at least a suitable and objective replacement for frequentist ML for the analysis of exposureresponse data. Applications of these techniques demonstrated that Amicide formulations of 2,4-D are more toxic to Daphnia than their unformulated, Technical Acid parent. Different results were obtained from Bayesian MCMC and ML methods when more complex models and data structures were considered. In the analysis of 4-CP toxicity, the treatment of 2 different factors as fixed or random in standard and Mixed-Effect models was found to affect variance estimates to the degree that different conclusions would be drawn from the same model, fit to the same data. Associated discrepancies in the treatment of overdispersion between ML and Bayesian MCMC analyses were also found to affect results. Bayesian MCMC techniques were found to be superior to the ML ones employed for the analysis of complex models because they enabled the correct formulation of hierarchical (nested) datastructures within a binomial logistic GLM. Application of these techniques to the analysis of results from 4-CP toxicity testing on two strains of Daphnia carinata found that between-experiment variability was greater than that within-experiments or between-strains. Perhaps surprisingly, this indicated that long-term laboratory culture had not significantly affected the sensitivity of one strain when compared to cultures of another strain that had recently been established from field populations. The results from this analysis highlighted the need for repetition of experiments, proper model formulation in complex analyses and careful consideration of the effects of pooling data on characterising variability and uncertainty. The GLM framework was used to develop three dimensional surface models of the effects of different length pulse exposures, and subsequent delayed toxicity, of 4-CP on Daphnia. These models described the relationship between exposure duration and intensity (concentration) on toxicity, and were constructed for both pulse and delayed effects. Statistical analysis of these models found that significant delayed effects occurred following the full range of pulse exposure durations, and that both exposure duration and intensity interacted significantly and concurrently with the delayed effect. These results indicated that failure to consider delayed toxicity could lead to significant underestimation of the effects of pulse exposure, and therefore increase uncertainty in risk assessments. A number of new approaches to modelling ecotoxicological risk and to propagating uncertainty were also developed and applied in this thesis. In the first of these, a method for describing and propagating uncertainty in conventional Species Sensitivity Distribution (SSD) models was described. This utilised Probability Bounds Analysis to construct a nonparametric 'probability box' on an SSD based on EC05 estimates and their confidence intervals. Predictions from this uncertain SSD and the confidence interval extrapolation methods described by Aldenberg and colleagues (2000; 2002a) were compared. It was found that the extrapolation techniques underestimated the width of uncertainty (confidence) intervals by 63% and the upper bound by 65%, when compared to the Probability Bounds (P3 Bounds) approach, which was based on actual confidence estimates derived from the original data. An alternative approach to formulating ecotoxicological risk modelling was also proposed and was based on a Binomial GLM. In this formulation, the model is first fit to the available data in order to derive mean and uncertainty estimates for the parameters. This 'uncertain' GLM model is then used to predict the risk of effect from possible or observed exposure distributions. This risk is described as a whole distribution, with a central tendency and uncertainty bounds derived from the original data and the exposure distribution (if this is also 'uncertain'). Bayesian and P-Bounds approaches to propagating uncertainty in this model were compared using an example of the risk of exposure to a hypothetical (uncertain) distribution of 4-CP for the two Daphnia strains studied. This comparison found that the Bayesian and P-Bounds approaches produced very similar mean and uncertainty estimates, with the P-bounds intervals always being wider than the Bayesian ones. This difference is due to the different methods for dealing with dependencies between model parameters by the two approaches, and is confirmation that the P-bounds approach is better suited to situations where data and knowledge are scarce. The advantages of the Bayesian risk assessment and uncertainty propagation method developed are that it allows calculation of the likelihood of any effect occurring, not just the (probability)bounds, and that the same software (WinBugs) and model construction may be used to fit regression models and predict risks simultaneously. The GLM risk modelling approaches developed here are able to explain a wide range of response shapes (including hormesis) and underlying (non-normal) distributions, and do not involve expression of the exposure-response as a probability distribution, hence solving a number of problems found with previous formulations of ecotoxicological risk. The approaches developed can also be easily extended to describe communities, include modifying factors, mixed-effects, population growth, carrying capacity and a range of other variables of interest in ecotoxicological risk assessments. While the lack of data on the toxicological effects of chemicals is the most significant source of uncertainty in ecotoxicological risk assessments today, methods such as those described here can assist by quantifying that uncertainty so that it can be communicated to stakeholders and decision makers. As new information becomes available, these techniques can be used to develop more complex models that will help to bridge the gap between the bioassay and the ecosystem.