Characterization of phosphate rock and phosphogypsum from Gabes phosphate fertilizer factories (SE Tunisia): high mining potential and implications for environmental protection

Environmental Science and Pollution Research - Since the establishment of the coastal industrial complex in Gabes city (Gulf of Gabes, SE Tunisia), hundred million tons of untreated phosphogypsum...     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Carbon dioxide capture and recovery by means of TSA and/or VSA

Experimental work is performed with a 5A zeolite on a small laboratory column with heating from the wall. Carbon dioxide adsorption occurs at atmospheric pressure and different CO₂ concentrations in nitrogen. Comparisons of different methods of desorption by heating, purge and/or vacuum are studied. Desorption by heating only leads to almost pure CO₂ (around 99% purity) and a recovery nearly linear to the heating temperature, ranging from 45% at 130 °C to 79% at 210 °C. Recovery can be subsequently increased with a nitrogen purge to more than 98% but the recovered carbon dioxide is diluted due to the dispersive character of the desorption wave and the operation time is long. Increasing the flow rate decreases the desorption time but has no effect on the purity because the total purge volume remains about the same. Substitution of the purge step with a vacuum step leads to pure CO₂ and almost total recovery. Desorption under vacuum only without heating leads to pure CO₂ (around 99% purity) but limited recovery (85% in the present work).Desorption under vacuum seems to be more simple for large-scale applications. When using a water liquid ring pump, the temperature of the ring must be kept as low as possible to provide a high operating capacity.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.     

Developing new approaches and strategies to promote sustainability and environmental integration in the Mediterranean region

Environmental Science and Pollution Research -     

Evaluation of Rio Grande Management Alternatives Using a Surface‐Water/Ground‐Water Model1

Abstract: Previous investigations observed significant seepage losses from the Rio Grande to the shallow aquifer between Socorro and San Antonio, New Mexico. High‐resolution telescopic modeling was used along a 10‐km reach of the Rio Grande and associated drains and canals to evaluate several management alternatives aimed at improving river conveyance efficiency. Observed data consisted of ground‐water and surface‐water elevations, seepage rates along the Rio Grande and associated canals and drains, and borehole geology. Model calibration was achieved by adjusting hydraulic conductivity and specific storage until the output matched observed data. Sensitivity analyses indicated that the system was responsive to changes in hydrogeologic properties, especially when such alterations increased vertical connectivity between layers. The calibrated model predicted that removal of the low flow conveyance channel, a major channel draining the valley, would not only decrease river seepage by 67%, but also decrease total flow through the reach by 75%. The decreased flow through the reach would result in increased water logging and an average increase in ground‐water elevations of 1.21 meter. Simulations of the system with reduced riparian evapotranspiration rates or a relocated river channel also predicted decreased river seepage, but to a much lesser degree.     

Removal of Pb(II) and Cd(II) ions from water by Fe and Ag nanoparticles prepared using electro-exploding wire technique

Purpose

This work aimed at investigating the adsorption of lead and cadmium onto Fe and Ag nanoparticles for use as a water contaminant removal agent as a function of particle type, sorbent concentration, and contact time.

Methods

Fe and Ag spherical nanoparticles were prepared in water by the lab-made electro-exploding wire (EEW) system and were investigated for their structure properties. Adsorption experiments were carried out at room temperature and pH 8.3 water solutions.

Results

The removal/adsorption of both Pb(II) and Cd(II) ions was found to be dependent on adsorbent dosage and contact time. Pb(II) adsorption onto Fe and Ag nanoparticles showed more or less similar efficiency and behavior. The kinetic data for the adsorption process obeyed pseudo second-order rate equations. The calculated equilibrium adsorption capacities (q _e) were 813 and 800 mg/g for Pb sorption onto Fe and Ag nanoparticles, respectively. Cd(II) ion adsorption onto Fe nanoparticles obeyed pseudo second-order rate equations with q _e equal to 242 mg/g, while their adsorption onto Ag nanoparticles obeyed pseudo first-order rate equations with q _e of 794 mg/g. The calculated q _es are in quite agreement with the experimental values. The removal/uptake mechanisms of metal ions involved interaction between the metal ion and the oxide/hydroxyl layer around the spherical metallic core of the nanoparticle in water medium.

Conclusion

Fe and Ag nanoparticles prepared using the EEW technique exhibited high potentials for the removal of metal ions from water with very high adsorption capacities, suggesting that the EEW technique can be enlarged to generate nanoparticles with large quantities for field or site water purification.     

Ginkgo biloba mitigates silver nanoparticles-induced hepatotoxicity in Wistar rats via improvement of mitochondrial biogenesis and antioxidant status

Environmental Science and Pollution Research - Silver nanoparticles (AgNPs) are noble metal nanoparticles, due to their good physicochemical properties, which have been exploited in biological...     

Making the Business Case for Sustainability: How to Account for Intangible Benefits—A Case Study Approach

Sustainability is continuing to change the way businesses operate. Stakeholders are insisting that corporations implement more responsible business practices, and they are holding them increasingly accountable for their associated environmental and social impacts. Research has provided significant contributions toward sustainability‐related tools and best practices, allowing sustainability to be integrated even farther across business operations. However, challenges still exist, preventing many companies from fully integrating sustainability. Although intangible benefits are not commonly included in business case assessments, such benefits can be derived through sustainability initiatives and may offer additional value in evaluating the business case for sustainability. In this article, we review current literature on accounting methods for the business case for sustainability as well as currently available methods or tools that are capable of estimating intangible benefits. In addition, we use case studies to illustrate if, and how, companies are accounting for intangible benefits, and we identify best methods for accounting for intangible benefits.     

Arsenic and lead in the indoor residential settings of different socio-economic status; assessment of human health risk via dust exposure

Environmental Science and Pollution Research - In the present study, occurrence of arsenic (As) and lead (Pb) is reported in rural and urban household dust (floor and AC filter dust) of the Kingdom...