Adsorption of Cu(II) ions from aqueous solutions on biochars prepared from agricultural by-products

In this study, the adsorption of Cu(II) from aqueous solutions by agricultural by-products, such as rice husks, olive pomace and orange waste, as well as compost, was evaluated. The aim was to obtain sorbent materials (biochars) through hydrothermal treatment (300?°C) and pyrolysis (300?°C and 600?°C). The effect of adsorbent dose, pH, contact time and initial Cu(II) concentration in batch-mode experiments was investigated. The optimum Cu(II) adsorption conditions was found to occur at 5-12?g/L adsorbent dose, initial pH 5-6, and reaction time 2-4?h. Furthermore, the adsorption kinetics were best described by the pseudo-second order model for all the tested materials, while the adsorption equilibrium best fitted by the linear and Freundlich isotherms. Comparing rice husks and olive pomace, the higher adsorption capacity resulted after pyrolysis at 300?°C. With respect to the orange waste and compost, the highest adsorption capacity was observed using biochars obtained after hydrothermal treatment and pyrolysis at 300?°C.     

Production of hydroxytyrosol rich extract from Olea europaea leaf with enhanced biological activity using immobilized enzyme reactors

Environmental Science and Pollution Research - As olive leaves constitute the main by-product of the olive oil industry with important environmental and economic impact, there is an increasing...     

Copper uptake kinetics and toxicological effects of ionic Cu and CuO nanoparticles on the seaweed Ulva rigida

Environmental Science and Pollution Research - Copper ion (Cu2+) and copper oxide (CuO) nanoparticle (NP) ecotoxicity are of increasing concern as they are considered to be a potential risk to...     

An application of data mining tools for the study of shipping safety in restricted waters

The effectiveness of the enforcement of the ISM-Code and the examination of its role in the distribution of causes of shipping accidents between human and non-human error was studied. All accidents involving Greek-flagged ships from 1995 to 2006, a time-scale which spans over the pre- and post-ISM period in navigational regions of restricted waters, were analyzed.The accident data was processed through a classification tree analysis which enabled the classification of various accident factors. The analysis revealed that although the human error maintained its position as the dominant factor in shipping accidents, there is also substantial evidence in support of the ISM-Code effective control over shipping accidents during the post-ISM period. The implementation of the ISM-Code led to an overall reduction of human-induced accidents in total. Furthermore, in terms of location, the ISM-Code improved the human-induced accident record within restricted waters.Conclusively, the ISM-Code constitutes an effective policy measure for shipping safety. The results of the classification tree analysis reported in the present work can be used by decision makers in companies and international organizations to build knowledge-based expert systems and augment their information in the field of safety policy and management.     

Mechanistic insights into acetaminophen removal on cashew nut shell biomass-derived activated carbons

Environmental Science and Pollution Research - Activated carbons prepared from cashew nut shells by chemical activation with phosphoric acid were tested for the removal of acetaminophen. It was...     

Biotreatment and bacterial succession in an upflow immobilized cell bioreactor fed with fludioxonil wastewater

Environmental Science and Pollution Research - The large quantities and the persistent nature of fungicide wastewaters have increased the efforts towards a sustainable technological solution. In...     

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

ABSTRACT

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O₃ and NO₂ from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.