scholarly journals Mechanistic modeling of persistent organic pollutant exposure among indigenous Arctic populations: motivations, challenges, and benefits

2017 ◽  
Vol 25 (4) ◽  
pp. 396-407 ◽  
Author(s):  
F. Wania ◽  
M.J. Binnington ◽  
M.S. Curren
Keyword(s):  
Mechanistic Model ◽  
Organic Pollutant ◽  
Temporal Trends ◽  
Chemical Properties ◽  
Mechanistic Modeling ◽  
The Arctic ◽  
Contaminant Exposure ◽  
Beluga Whales ◽  
Sequence Of Events ◽  
Food Species

Indigenous Arctic populations experience elevated exposures to many environmental contaminants compared with groups residing in southern Canada. This is largely due to consumption of traditional foods, some of which (ringed seals, beluga whales, narwhals, etc.) have relatively high concentrations of persistent organic pollutants. Models of contaminant fate, transport, and bioaccumulation represent powerful tools to explore this exposure issue, wherein combined models can be used to mechanistically and dynamically describe the entire sequence of events linking chemical emissions into the environment to ultimate contaminant concentrations in indigenous Arctic populations. In this review, various approaches adapted and applied to understanding indigenous Arctic contaminant exposure are explored, including early models describing body burdens in single traditional food species to more recent approaches holistically examining uptake and bioaccumulation in entire food chains. The applications of these models are also discussed, including attempts to (i) identify chemical properties favouring transport to, and bioaccumulation in, the Arctic; (ii) clarify the main determinants of temporal trends observed in indigenous Arctic biomonitoring; (iii) explore the impacts of permanent and temporary dietary transitions on current and future indigenous Arctic contaminant exposures; and (iv) correlate modeled early-life pollutant exposures with measured health impacts. The review demonstrates the effectiveness of mechanistic model approaches in investigating indigenous Arctic contaminant exposure, and confirms their utility in continued improvements to understanding associated risk in this unique population context.

scholarly journals Mechanistic modeling of pesticide uptake with a 3D plant architecture model

2021 ◽  
Author(s):  
Helena Jorda ◽  
Katrin Huber ◽  
Asta Kunkel ◽  
Jan Vanderborght ◽  
Mathieu Javaux ◽  
...  
Keyword(s):  
Root Zone ◽  
Mechanistic Model ◽  
Chemical Properties ◽  
Mechanistic Modeling ◽  
The European Union ◽  
Architecture Model ◽  
Solute Uptake ◽  
Uptake Process ◽  
Set Up ◽  
Pesticide Registration

AbstractMeaningful assessment of pesticide fate in soils and plants is based on fate models that represent all relevant processes. With mechanistic models, these processes can be simulated based on soil, substance, and plant properties. We present a mechanistic model that simulates pesticide uptake from soil and investigate how it is influenced, depending on the governing uptake process, by root and substance properties and by distributions of the substance and water in the soil profile. A new root solute uptake model based on a lumped version of the Trapp model (Trapp, 2000) was implemented in a coupled version of R-SWMS-ParTrace models for 3-D water flow and solute transport in soil and root systems. Solute uptake was modeled as two individual processes: advection with the transpiration stream and diffusion through the root membrane. We set up the model for a FOCUS scenario used in the European Union (EU) for pesticide registration. Considering a single vertical root and advective uptake only, the root hydraulic properties could be defined so that water and substance uptake and substance fate in soil showed a good agreement with the results of the 1D PEARL model, one of the reference models used in the EU for pesticide registration. Simulations with a complex root system and using root hydraulic parameters reported in the literature predicted larger water uptake from the upper root zone, leading to larger pesticide uptake when pesticides are concentrated in the upper root zone. Dilution of root water concentrations at the top root zone with water with low pesticide concentration taken up from the bottom of the root zone leads to larger uptake of solute when uptake was simulated as a diffusive process. This illustrates the importance of modeling uptake mechanistically and considering root and solute physical and chemical properties, especially when root-zone pesticide concentrations are non-uniform.

Suspect and Nontarget Screening Revealed Class-Specific Temporal Trends (2000–2017) of Poly- and Perfluoroalkyl Substances in St. Lawrence Beluga Whales

2021 ◽  
Vol 55 (3) ◽  
pp. 1659-1671
Author(s):  
Holly Barrett ◽  
Xuan Du ◽  
Magali Houde ◽  
Stéphane Lair ◽  
Jonathan Verreault ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Perfluoroalkyl Substances ◽  
Beluga Whales ◽  
Nontarget Screening

scholarly journals Nano-PAA-CuCl2 Composite as Fenton-Like Reusable Catalyst to Enhanced Degrade Organic Pollutant MB/MO

Catalysts ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 10
Author(s):  
Yang Dang ◽  
Yu Cheng ◽  
Yukun Zhou ◽  
Yifei Huang ◽  
Kaige Wang
Keyword(s):  
Photoelectron Spectroscopy ◽  
Self Assembly ◽  
Organic Pollutant ◽  
Energy Dispersive Spectrometer ◽  
Chemical Properties ◽  
Anodic Alumina ◽  
Alumina Substrate ◽  
Reusable Catalyst ◽  
X Ray ◽  
Nanoporous Anodic Alumina

The treatment of organic dye contaminants in wastewaters has now becoming more imperative. Fenton-like degradation of methylene blue (MB) and methyl orange (MO) in aqueous solution was investigated by using a nanostructure that a layer of CuCl2 nanoflake film grown on the top surface of nanoporus anodic alumina substrate (nano-PAA-CuCl2) as catalyst. The new nano-PAA-CuCl2 composite was fabricated with self-assembly approach, that is, a network porous structure film composed of CuCl2 nanoflake grown on the upper surface of nanoporous anodic alumina substrate, and the physical and chemical properties are characterized systematically with the X-ray diffraction (XRD), field emission scanning electron microscope (FE-SEM), and high-resolution transmission electron microscopy (HRTEM), Energy Dispersive Spectrometer (EDS), X-ray photoelectron spectroscopy (XPS). The experimental results showed that the nano-PAA-CuCl2 catalyst presented excellent properties for the degradation of two typical organic pollutants such as MB and MO, which were almost completely degraded with 8 × 10−4mol/L nano-PAA-CuCl2 catalyst after 46 min and 60 min at reaction conditions of H2O2 18 mM and 23 mM, respectively. The effects of different reaction parameters such as initial pH, H2O2 concentration, catalyst morphology and temperature were attentively studied. And more, the stability and reusability of nano-PAA-CuCl2 were examined. Finally, the mechanism of MB and MO degradation by the nano-PAA-CuCl2/H2O2 system was proposed, based on the experimental data of the BCA and the temperature-programmed reduction (H2-TPR) and theoretical analysis, the reaction kinetics belonged to the pseudo-first-order equation. This new nanoporous composite material and preparation technology, as well as its application in Fenton-like reaction, provide an effective alternative method with practical application significance for wastewater treatment.

scholarly journals Modeling the marine chromium cycle: new constraints on global-scale processes

2021 ◽  
Vol 18 (19) ◽  
pp. 5447-5463
Author(s):  
Frerk Pöppelmeier ◽  
David J. Janssen ◽  
Samuel L. Jaccard ◽  
Thomas F. Stocker
Keyword(s):  
Biological Activity ◽  
Chemical Properties ◽  
Global Scale ◽  
Oxidation States ◽  
The Arctic ◽  
Great Promise ◽  
Concentration Gradients ◽  
Oxygen Minimum Zones ◽  
Cr Concentration ◽  
Critical Regions

Abstract. Chromium (Cr) and its isotopes hold great promise as a tracer of past oxygenation and marine biological activity due to the contrasted chemical properties of its two main oxidation states, Cr(III) and Cr(VI), and the associated isotope fractionation during redox transformations. However, to date the marine Cr cycle remains poorly constrained due to insufficient knowledge about sources and sinks and the influence of biological activity on redox reactions. We therefore implemented the two oxidation states of Cr in the Bern3D Earth system model of intermediate complexity in order to gain an improved understanding on the mechanisms that modulate the spatial distribution of Cr in the ocean. Due to the computational efficiency of the Bern3D model we are able to explore and constrain the range of a wide array of parameters. Our model simulates vertical, meridional, and inter-basin Cr concentration gradients in good agreement with observations. We find a mean ocean residence time of Cr between 5 and 8 kyr and a benthic flux, emanating from sediment surfaces, of 0.1–0.2 nmol cm−2 yr−1, both in the range of previous estimates. We further explore the origin of regional model–data mismatches through a number of sensitivity experiments. These indicate that the benthic Cr flux may be substantially lower in the Arctic than elsewhere. In addition, we find that a refined representation of oxygen minimum zones and their potential to reduce Cr yield Cr(III) concentrations and Cr removal rates in these regions in much improved agreement with observational data. Yet, further research is required to better understand the processes that govern these critical regions for Cr cycling.

scholarly journals Inverse mechanistic modeling of transdermal drug delivery for fast identification of optimal model parameters

2020 ◽  
Author(s):  
Thijs Defraeye ◽  
Flora Bahrami ◽  
Rene M Rossi
Keyword(s):  
Drug Delivery ◽  
Inverse Modeling ◽  
Transdermal Drug Delivery ◽  
Drug Transport ◽  
Mechanistic Model ◽  
Mechanistic Modeling ◽  
Drug Uptake ◽  
Added Value ◽  
Model Parameters ◽  
Transdermal Drug Delivery Systems

Transdermal drug delivery systems are a key technology to administer drugs with a high first-pass effect in a non-invasive and controlled way. Physics-based modeling and simulation are on their way to become a cornerstone in the engineering of these healthcare devices since it provides a unique complementarity to experimental data and insights. Simulations enable to virtually probe the drug transport inside the skin at each point in time and space. However, the tedious experimental or numerical determination of material properties currently forms a bottleneck in the modeling workflow. We show that multiparameter inverse modeling to determine the drug diffusion and partition coefficients is a fast and reliable alternative. We demonstrate this strategy for transdermal delivery of fentanyl. We found that inverse modeling reduced the normalized root mean square deviation of the measured drug uptake flux from 26 to 9%, when compared to the experimental measurement of all skin properties. We found that this improved agreement with experiments was only possible if the diffusion in the reservoir holding the drug was smaller than the experimentally-measured diffusion coefficients suggested. For indirect inverse modeling, which systematically explores the entire parametric space, 30 000 simulations were required. By relying on direct inverse modeling, we reduced the number of simulations to be performed to only 300, so a factor 100 difference. The modeling approach's added value is that it can be calibrated once in-silico for all model parameters simultaneously by solely relying on a single measurement of the drug uptake flux evolution over time. We showed that this calibrated model could accurately be used to simulate transdermal patches with other drug doses. We showed that inverse modeling is a fast way to build up an accurate mechanistic model for drug delivery. This strategy opens the door to clinically-ready therapy that is tailored to patients.

Year-long observations of chemical properties of organic aerosols and cloud residuals at the Zeppelin Observatory, Svalbard

2021 ◽  
Author(s):  
Yvette Gramlich ◽  
Sophie Haslett ◽  
Karolina Siegel ◽  
Gabriel Freitas ◽  
Radovan Krejci ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Trace Gases ◽  
Chemical Properties ◽  
Radiative Properties ◽  
Cloud Formation ◽  
The Arctic ◽  
Arctic Clouds ◽  
Clear Sky ◽  
Air Inlet

<p>The number of cloud seeds, e.g. cloud condensation nuclei (CCN) and ice nucleation particles (INP), in the pristine Arctic shows a large range throughout the year, thereby influencing the radiative properties of Arctic clouds. However, little is known about the chemical properties of CCN and INP in this region. This study aims to investigate the chemical properties of aerosol particles and trace gases that are of importance for cloud formation in the Arctic environment, with focus on the organic fraction.</p><p>Over the course of one full year (fall 2019 until fall 2020), we deployed a filter-inlet for gases and aerosols coupled to a chemical ionization high-resolution time-of-flight mass spectrometer (FIGAERO-CIMS) using iodide as reagent ion at the Zeppelin Observatory in Svalbard (480 m a.s.l.), as part of the Ny-Ålesund Aerosol Cloud Experiment (NASCENT). The FIGAERO-CIMS is able to measure organic trace gases and aerosol particles semi-simultaneously. The instrument was connected to an inlet switching between a counterflow virtual impactor (CVI) inlet and a total air inlet. This setup allows to study the differences in chemical composition of organic aerosol particles and trace gases at molecular level that are involved in Arctic cloud formation compared to ambient non-activated aerosol.</p><p>We observed organic signal above background in both gas and particle phase all year round. A comparison between the gas phase mass spectra of cloud-free and cloudy conditions shows lower signal for some organics inside the cloud, indicating that some trace gases are scavenged by cloud hydrometeors whilst others are not. In this presentation we will discuss the chemical characteristics of the gases exhibiting different behavior during clear sky and cloudy conditions, and the implications for partitioning of organic compounds between the gas, aerosol particle and cloud hydrometeor (droplet/ice) phase.</p>

scholarly journals Unveiling the Efficiency of Vermicompost Derived from Different Biowastes on Wheat (Triticum aestivum L.) Plant Growth and Soil Health

Agronomy ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 791 ◽  
Author(s):  
Zubair Aslam ◽  
Safdar Bashir ◽  
Waseem Hassan ◽  
Korkmaz Bellitürk ◽  
Niaz Ahmad ◽  
...  
Keyword(s):  
Plant Growth ◽  
Temporal Trends ◽  
Soil Health ◽  
Chemical Properties ◽  
Test Plant ◽  
Cow Dung ◽  
Aphid Infestation ◽  
Physico Chemical ◽  
Chemical Attributes ◽  
The Impact

The present study was conducted to explore the role of different types of vermicomposts (VCs) prepared from different substrates to improve soil health (physical and chemical properties) and wheat plant growth under field conditions. Different combinations of vermicompost prepared from different substrates (cow dung, paper waste, and rice straw) and inorganic fertilizers were applied in soil using wheat as a test plant. The impact of three different VCs on physico-chemical characteristics and nutrient availability in soil was evaluated to examine their efficacy in combination with chemical fertilizers. Temporal trends in vermicomposting treatments at various stages showed significant improvement in physico-chemical attributes of the VCs substrates. All the plant physiological attributes showed significant response where N:P:K 100:50:50 kg ha−1 + 10 t ha−1 cow dung vermicompost was applied. In addition, post-harvest analysis of soil not only revealed that different combinations of the vermicomposting treatments improved the soil health by improving the physico-chemical attributes of the soil. Conclusively, application of cow dung vermicompost along with recommended NPK not only improved crop yield, soil health, reduced insect (aphid) infestation but also fortified grains with Zn and Fe.

Mechanistic Modeling of Five-Axis Machining With a Flat End Mill Considering Bottom Edge Cutting Effect

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Zhou-Long Li ◽  
Li-Min Zhu
Keyword(s):  
Cutting Forces ◽  
Mechanistic Model ◽  
Mechanistic Modeling ◽  
End Mill ◽  
Bottom Edge ◽  
Radial Line ◽  
Bottom Part ◽  
Lead Angle ◽  
Cutting Effect ◽  
Five Axis

In five-axis milling, the bottom edge of a flat end mill is probably involved in cutting when the lead angle of tool axis changes to negative. The mechanistic model will lose accuracy if the bottom edge cutting effect is neglected. In this paper, an improved mechanistic model of five-axis machining with a flat end mill is presented to accurately predict cutting forces by combining the cutting effects of both side and bottom edges. Based on the kinematic analysis of the radial line located at the tool bottom part, the feasible contact radial line (FCRL) is analytically extracted. Then, boundaries of the bottom cutter-workpiece engagements (CWEs) are obtained by intersecting the FCRL with workpiece surfaces and identifying the inclusion relation of its endpoints with the workpiece volume. Next, an analytical method is proposed to calculate the cutting width and the chip area by considering five-axis motions of the tool. Finally, the method of calibrating bottom-cutting force coefficients by conducting a series of plunge milling tests at various feedrates is proposed, and the improved mechanistic model is then applied to predict cutting forces. The five-axis milling with a negative lead angle and the rough machining of an aircraft engine blisk are carried out to test the effectiveness and practicability of the proposed model. The results indicate that it is essential to take into account the bottom edge cutting effect for accurate prediction of cutting forces at tool path zones where the tool bottom part engages with the workpiece.

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