Water Remediation: PVA-Based Magnetic Gels as Efficient Devices to Heavy Metal Removal

Scientific and technological researches are devoted to obtain materials capable of retaining different kinds of pollutants, contributing to contamination solutions. In this context, hydrogels have emerged as great candidates because of their excellent absorption properties as well as good mechanical, thermal and chemical properties. More specifically, ferrogels (magnetic gels) present the extra advantage of being easily manipulated by a permanent magnet. Here, we present the results derived from the application of ferrogels as efficient tools to extract heavy metal pollutants from wastewater samples. The gels were prepared following the method of freezing and thawing of a polyvinyl alcohol aqueous solution with magnetic nanoparticles coated with polyacrylic acid. Ferrogels were fully characterized and their ability to retain Cu²⁺ and Cd²⁺, as model heavy metals, was studied. Thus kinetics and mechanisms of adsorption were evaluated and modeled. The concentration of MNPs on the PVA matrix was key to improve the adsorption capability (approximately the double of retention is improved by the MNPs addition). The adsorption kinetics was determined as pseudo-second order model, whereas the Langmuir model was the most appropriate to explain the behavior of the gels. Finally reuse ability was evaluated to determine the real potential of these materials, the ferrogels demonstrated high efficiency up to about five cycles, retaining about 80–90% of their initial adsorption capability. All the results indicated that the materials are promising candidates able to compete with the commercial technology regarding to water remediation.     

Integrating drivers influencing the detection of plant pests carried in the international cut flower trade

This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals, as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers from Kenya between 1996 and 2004.There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied, efforts allocated to inspection have a significant influence on the probability of pest detection. However, by better targeting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as Carthamus and Veronica, the volume of flowers traded has a significant and positive impact on the likelihood of pest detection. We conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.