Electrospun and functionalized PVDF/PAN nanocatalyst-loaded composite for dechlorination and photodegradation of pesticides in contaminated water

A novel approach for the electrospinning and functionalization of nanocatalyst-loaded polyvinylidene fluoride/polyacrylonitrile (PVDF/PAN) composite grafted with acrylic acid (AA; which form polyacrylic acid (PAA) brush) and decorated with silver (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd) designed for the dechlorination and photodegradation of pesticides was carried out. PAN was used both as a nitrogen dopant as well as a co-polymer. Smooth nanofibers were obtained by electrospinning a solution of 12:2 wt.% PVDF/PAN blend using dimethylformamide (DMF) as solvent. The nanofibers were grafted with AA by free-radical polymerization using 2,2′azobis(2-methylpropionitrile) (AIBN) as initiator. Both bimetallic iron–palladium (Fe–Pd) and titania (TiO₂) nanoparticles (NP) were anchored on the grafted nanofibers via the carboxylate groups by in situ and ex situ synthesis. The Fe–Pd and nitrogen-doped TiO₂ nanoparticles were subsequently used for dechlorination and oxidation of target pollutants (dieldrin, chlorpyrifos, diuron, and fipronil) to benign products. Structural and chemical characterizations of the composites were done using various techniques. These include surface area and porosity analyzer (ASAP) using the technique by Brunner Emmett Teller (BET), Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscope (TEM) analyses were done. After dechlorination, the transformation products (TPs) for dieldrin, chlorpyrifos, diuron, and fipronil were obtained and identified using two-dimensional gas chromatography (time-of-flight) with a mass spectrometer detector (GCxGC-TOFMS). Analysis of total organic carbon (TOC) was carried out and used to extrapolate percentage mineralization. Experimental results showed that dechlorination efficiencies of 96, 93, 96, and 90 % for 1, 2, 2, and 3 h treatment period were respectively achieved for 5 ppm solutions of dieldrin, chlorpyrifos, diuron, and fipronil. The dechlorination of dieldrin, diuron, and fipronil follows first-order kinetics while that of chlorpyrifos followed pseudo-first order. Mineralization performance of 34 to 45 % were recorded when Fe–Pd was used, however upon electrospinning, doping, and grafting (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd composite); it significantly increased to 99.9999 %. This composite reveals great potential for dechlorination and mineralization of pesticides in contaminated water.     

Release of PCBs from Silvretta glacier (Switzerland) investigated in lake sediments and meltwater

This study is part of our investigations about the release of persistent organic pollutants from melting Alpine glaciers and the relevance of the glaciers as secondary sources of legacy pollutants. Here, we studied the melt-related release of polychlorinated biphenyls (PCBs) in proglacial lakes and glacier streams of the catchment of the Silvretta glacier, located in the Swiss Alps. To explore a spatial and temporal distribution of chemicals in glacier melt, we combined two approaches: (1) analysing a sediment record as an archive of past remobilization and (2) passive water sampling to capture the current release of PCBs during melt period. In addition, we determined PCBs in a non-glacier-fed stream as a reference for the background pollutant level in the area. The PCBs in the sediment core from the Silvretta lake generally complied with trends of PCB emissions into the environment. Elevated concentrations during the most recent ten years, comparable in level with times of the highest atmospheric input, were attributed to accelerated melting of the glacier. This interpretation is supported by the detected PCB fractionation pattern towards heavier, less volatile congeners, and by increased activity concentrations of the radioactive tracer ¹³⁷Cs in this part of the sediment core. In contrast, PCB concentrations were not elevated in the stream water, since no significant difference between pollutant concentrations in the glacier-fed and the non-glacier-fed streams was detected. In stream water, no current decrease of the PCBs with distance from the glacier was observed. Thus, according to our data, an influence of PCBs release due to accelerated glacier melt was only detected in the proglacial lake, but not in the other compartments of the Silvretta catchment.     

The impact of global change on economic values of water for Public Irrigation Schemes at the São Francisco River Basin in Brazil

Economic values of water for the main Public Irrigation Schemes in the sub-middle region of the São Francisco River Basin, in northeastern Brazil, are determined in this study using an integration of a global agro-economic land and water use (MAgPIE) with a local economic model (Positive Mathematical Programming). As in the latter, the water values depend on the crops grown, and as Brazilian agriculture is strongly influenced by the global market, we used a regionalized version of the global model adapted to the region in order to simulate the crop land use, which is in turn determined by changes in global demand, trade barriers, and climate. The allocation of sugarcane and fruit crops projected with climate change by the global model, showed an impact on the average yields and on the water costs in the main schemes resulting in changes in the water values locally. The economic values for all schemes in the baseline year were higher than the water prices established for agricultural use in the basin. In the future, these water values will be higher in all the schemes. The highest water values currently and in the future were identified in municipalities with a significant proportion of area growing irrigated sugarcane. Being aware of current water values of each user in a baseline year and in a projected future under global climate and socioeconomic changes, decision makers should improve water allocation policies at local scale, in order to avoid conflicts and unsustainable development in the future.     

A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

Development and implementation of eco-genomic tools for aquatic ecosystem biomonitoring: the SYNAQUA French-Swiss program

The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators’ communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017–2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

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.     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...