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.     

Adsorption/desorption of arsenite and arsenate on chitosan and nanochitosan

Equilibrium sorption studies of anionic species of arsenite, As(III) ions and arsenate As(V) ions onto two biosorbents, namely, chitosan and nanochitosan, have been investigated and compared. The results and trends in the sorption behavior are novel, and we have observed during the sorption process of the As(III) and As(V) on chitosan, a slow process of desorption occurred after an initial maximum adsorption capacity was achieved, before reaching a final but lower equilibrium adsorption capacity. The same desorption trend, however, is not observed on nanochitosan. The gradual desorption of As(III) and As(V) in the equilibrium sorption on chitosan is attributed to the different fractions of the dissociated forms of arsenic on the adsorbent surface and in solution and the extent of protonation of chitosan with the changing of solution pH during sorption. The change of solution pH during the sorption of arsenite ions on chitosan was also influenced by the interaction between the buffering effect of the arsenite species in the aqueous medium and the physical properties of chitosan. The final equilibrium adsorption capacity of chitosan for As(III) and As(V) was found to be around 500 and 8000 μg/g, respectively, whereas the capacities on nanochitosan are 6100 and 13,000 μg/g, respectively.

     

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.     

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.     

Processing and Morphology Impacts on Mechanical Properties of Fungal Based Biopolymer Composites

Fungal based biopolymer matrix composites with lignocellulosic agricultural waste as the filler are a viable alternative for some applications of synthetic polymers. This research provides insight into the impact of the processing method and composition of agriwaste/fungal biopolymer composites on structure and mechanical properties. The impact of nutrition during inoculation and after a homogenization step on the three-point bend flexural modulus and strength was determined. Increasing supplemental nutrition at inoculation had little effect on the overall composite strength or modulus; however, increasing carbohydrate loading after a homogenization step increased flexural stress at yield and bulk flexural modulus. The contiguity of the network formed was notably higher in the latter scenario, suggesting that the increase in modulus and strength of the final composite after homogenization was the result of contiguous hyphal network formation, which improves the integrity of the matrix and the ability to transfer load to the filler particles.     

Fly ash from biomass combustion as replacement raw material and its influence on the mortars durability

Journal of Material Cycles and Waste Management - Several types of industrial solid waste have been used as byproducts in the construction and materials industries. Some of the applications seem to...     

High Toughness and Fast Crystallization Poly(Lactic Acid)/Polyamide 11/SiO<Subscript>2</Subscript> Composites

A poly(lactic acid) (PLA)/polyamide 11 (PA11)/SiO₂ composite was mixed from PLA, PA11, and nanosilica particles through twin-screw extrusion. The PLA/PA11/SiO₂ composite was evaluated with tensile and Izod impact tests, light transmission and haze measurement, and isothermal and nonisothermal crystallization behavior determinations. The PLA/PA11/SiO₂ (97.0/3.0) composite had approximately 10.8% less ultimate tensile strength than neat PLA, but it had greater ductility and approximately ninefold greater elongation at break. A dimple morphology was observed on the fractural surface of the PLA/PA11/SiO₂ composite, indicating that the incorporation of PA11 and nanosilica particles increased the ductility of the PLA matrix. PLA with less than 3 wt% of PA11 and 0.5 phr of nanosilica particles had an Izod impact strength of 8.72 kJ/m². PA11 and nanosilica particles effectively toughened this PLA polymer; they accelerated both isothermal and nonisothermal crystallization rates and increased the crystallinities of the resulting composites under isothermal and nonisothermal crystallization processes.     

Towards an assessment of the influence of climate on wet acidic deposition in Europe

The EMEP precipitation composition network is used to examine relationships between non-marine SO4(2-), NO3-, NH4+, H+ concentrations and precipitation amount and a local zonal pressure index (an index of the atmospheric circulation). The pattern of the relationships changes across Europe with the zonal pressure gradient explaining more of the variance in ion concentrations in the west, and precipitation amount explaining relatively more of the variance in the east. There is some predictive capability for precipitation composition in the zonal pressure gradient for restricted regions in Europe; R2 values are up to 40% on a daily basis but in some seasons/months attain >60%. The zonal pressure gradient is an index which appears to include pertinent information on transport and wet removal. Preliminary analysis indicates that this approach can be useful in assessing the contributions of changing atmospheric circulation to time-trends of wet acidic deposition in an area stretching from the UK over the North Sea to Denmark. The zonal pressure gradient is known to have varied on time-scales of decades, and the simple index may be one appropriate approach to assessing future deposition patterns from future climate projections.     

Social-ecological system resonance: a theoretical framework for brokering sustainable solutions

Sustainability science is a solution-oriented discipline. Yet, there are few theory-rich discussions about how this orientation structures the efforts of sustainability science. We argue that Niklas Luhmann’s social system theory, which explains how societies communicate problems, conceptualize solutions, and identify pathways towards implementation of solutions, is valuable in explaining the general structure of sustainability science. From Luhmann, we focus on two key concepts. First, his notion of resonance offers us a way to account for how sustainability science has attended and responded to environmental risks. As a product of resonance, we reveal solution-oriented research as the strategic coordination of capacities, resources, and information. Second, Luhmann’s interests in self-organizing processes explain how sustainability science can simultaneously advance multiple innovations. The value logic that supports this multiplicity of self-organizing activities as a recognition that human and natural systems are complex coupled and mutually influencing. To give form to this theoretical framework, we offer case evidence of renewable energy policy formation in Texas. Although the state’s wealth is rooted in a fossil-fuel heritage, Texas generates more electricity from wind than any US state. It is politically antagonistic towards climate-change policy, yet the state’s reception of wind energy technology illustrates how social and environmental systems can be strategically aligned to generate solutions that address diverse needs simultaneously. This case demonstrates that isolating climate change—as politicians do as a separate and discrete problem—is incapable of achieving sustainable solutions, and resonance offers researchers a framework for conceptualizing, designing, and communicating meaningfully integrated actions.