Dynamics and risk assessment of pesticides in cucumber through field experiments and model simulation

2021 ◽  
Vol 773 ◽  
pp. 145615
Author(s):  
Xiaoxiao Feng ◽  
Lixiang Pan ◽  
Jing Jing ◽  
Jingcheng Zhang ◽  
Ming Zhuang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Field Experiments ◽  
Model Simulation

scholarly journals Incorporating biomarkers in ecological risk assessment of chemical contaminants of soils

2007 ◽  
Vol 26 (2) ◽  
pp. 120-137
Author(s):  
A. J. Reinecke ◽  
S. A. Reinecke ◽  
M. S. Maboeta ◽  
J. P. Odendaal ◽  
R. Snyman
Keyword(s):  
Risk Assessment ◽  
South African ◽  
Field Experiments ◽  
Early Stage ◽  
Population Level ◽  
Diagnostic Tools ◽  
Future Research ◽  
Chemical Contaminants ◽  
Toxic Response ◽  
Future Research Directions

Soil is an important but complex natural resource which is increasingly used as sink for chemicals. The monitoring of soil quality and the assessment of risks posed by contaminants have become crucial. This study deals with the potential use of biomarkers in the monitoring of soils and the assessment of risk resulting from contamination. Apart from an overview of the existing literature on biomarkers, the results of various of our field experiments in South African soils are discussed. Biomarkers may have potential in the assessment of risk because they can indicate at an early stage that exposure has taken place and that a toxic response has been initiated. It is therefore expected that early biomarkers will play an increasing role as diagnostic tools for determining exposure to chemicals and the resulting effects. They may have predictive value that can assist in the prevention or minimising of risks. The aim of this study was to investigate the possibilities of using our results on biomarker responses of soil dwelling organisms to predict changes at higher organisational levels (which may have ecological implications). Our recent experimental results on the evaluation of various biomarkers in both the laboratory and the field are interpreted and placed in perspective within the broader framework of response biology. The aim was further to contribute to the development and application of biomarkers in regulatory risk assessment schemes of soils. This critical review of our own and recent literature on biomarkers in ecotoxicology leads to the conclusion that biomarkers can, under certain conditions, be useful tools in risk assessment. Clear relationships between contamination loads in soil organisms and certain biomarker responses were determined in woodlice, earthworms and terrestrial snails. Clear correlations were also established in field experiments between biomarker responses and changes at the population level. This indicated that, in spite of the fact that direct mechanistic links are still not clarified, biomarkers may have the potential to provide early indications of forthcoming changes at higher organisational levels. Ways are proposed in which biomarkers could be used in the future in risk assessment schemes of soils and future research directions are suggested. 

scholarly journals Sensitivity and uncertainty analysis for river quality modelling

2004 ◽  
Vol 6 (2) ◽  
pp. 83-99 ◽  
Author(s):  
Mona Radwan ◽  
Patrick Willems ◽  
Jean Berlamont
Keyword(s):  
Water Quality ◽  
Risk Assessment ◽  
Uncertainty Analysis ◽  
Measurement Errors ◽  
Model Simulation ◽  
Public Awareness ◽  
Water Quality Management ◽  
Total Uncertainty ◽  
Uncertainty Sources ◽  
Uncertainty Model

Uncertainty analysis for model simulation is of growing importance in the field of water quality management. The importance of this concern is provided by recent public awareness over health risks from improper disposal of toxic wastes as well as by the continuing emphasis on risk assessment. The first step in the chain of risk assessment is the quantification of the error in predicting water quality. In each mathematical modelling application, different uncertainties are involved. The uncertainty sources can be classified into different categories (in this study, as model-input uncertainty, model-structure uncertainty, model-parameter uncertainty and measurement errors). These different types of uncertainty sources determine collectively the total uncertainty in the model results. In this paper, the relative contributions of uncertainties associated with each source are studied for the physico-chemical water quality modelling of a river in Belgium. This provides information as to where available modelling resources should be focused.

scholarly journals Potential surrogate plants for use in semi-field pesticide risk assessment with Megachile rotundata

PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e6278
Author(s):  
Andrew J. Frewin ◽  
Angela E. Gradish ◽  
Graham R. Ansell ◽  
Cynthia D. Scott-Dupree
Keyword(s):  
Risk Assessment ◽  
Release Rate ◽  
Field Experiments ◽  
Field Testing ◽  
Field Studies ◽  
Solitary Bees ◽  
Assessment Process ◽  
Foraging Activity ◽  
Megachile Rotundata ◽  
Release Rates

Background Current regulatory pesticide risk assessments for bees are based primarily on the honey bee (Apis mellifera) and may not always be protective of solitary bees. To incorporate solitary bees into the risk assessment process, standardized methods to assess the hazard of pesticides under semi-field (Tier II) conditions will be needed. We conducted a series of experiments over 2 years to assess potential surrogate plants and adult release rates for use in semi-field experiments with the alfalfa leafcutting bee (ALB, Megachile rotundata). Methods We compared ALB foraging activity and reproduction on 12 m2 plots of flowering alfalfa (Medicago sativa) and buckwheat (Fagopyrum esculentum) at low (10♀/20♂) and high (20♀/40♂) adult release rates. The following year, we assessed the same endpoints on plots of purple tansy (Phacelia tanacetifolia) at a release rate of 10♀/15♂. Results Although ALB foraging activity was high on buckwheat plots, fewer adults were produced compared to alfalfa plots. On alfalfa, there were no differences in foraging activity, nesting, or reproduction between the low and high release rates. ALB readily foraged from purple tansy flowers, but females avoided purple tansy leaves for leaf cell construction. Discussion Our study suggests that buckwheat alone cannot support ALB during semi-field studies on small plots. For alfalfa, we recommend a maximum release rate of 10♀/20♂ in 12 m2 plots. Further study of higher ALB release rates on purple tansy is warranted. A mixed planting of purple tansy and a plant suitable for leaf piece collection (e.g., buckwheat) may provide favorable conditions for ALB activity and reproduction during semi-field testing.

scholarly journals Using a Distributed Recharge Model to Quantify Recharge Processes in a Semi-Arid Karst Catchment: An Example from Wadi Natuf, West Bank

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 276 ◽  
Author(s):  
Majdi Mansour ◽  
Denis Peach ◽  
Nick Robins ◽  
Andrew Hughes
Keyword(s):  
Conceptual Model ◽  
Field Experiments ◽  
Model Simulation ◽  
West Bank ◽  
Capital City ◽  
Historical Event ◽  
Threshold Method ◽  
The West ◽  
Semi Arid ◽  
Distributed Recharge

The Wadi Natuf catchment is situated to the west of the Palestinian capital city of Ramallah which is in the West Bank. The catchment has been instrumented since 2003 to identify and examine recharge processes in semi-arid upland karst terrain, in which both direct and indirect recharge are important. The key recharge processes are direct rainfall recharge, and indirect recharge via wadis including the lateral routing of potential recharge in the unsaturated zone to springs which supply the wadis. A conceptual model describing these processes was developed. A distributed recharge model was then employed to test this conceptual model and to calculate recharge. A semi-arid wetting threshold method, based on local field experiments was used for recharge estimation. The model was calibrated by comparing simulated wadi flows to those recorded during a relatively short historical event. The study demonstrates that short-term monitoring can enable a sensible validation of a conceptual model leading to the estimation of recharge. Confidence in the model simulation requires further field work to strengthen the understanding of processes taking place in semi-arid climates and karstic flow environments.

scholarly journals Wind farm simulations using an overset hp-adaptive approach with blade-resolved turbine models

2019 ◽  
Vol 33 (5) ◽  
pp. 897-923 ◽  
Author(s):  
Andrew C Kirby ◽  
Michael J Brazell ◽  
Zhi Yang ◽  
Rajib Roy ◽  
Behzad R Ahrabi ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Field Experiments ◽  
Model Simulation ◽  
Unsteady Aerodynamics ◽  
Adaptive Finite Element ◽  
Computational Framework ◽  
Energy Applications ◽  
Nrel Phase Vi ◽  
Microscale Modeling

Blade-resolved numerical simulations of wind energy applications using full blade and tower models are presented. The computational methodology combines solution technologies in a multi-mesh, multi-solver paradigm through a dynamic overset framework. The coupling of a finite volume solver and a high-order, hp-adaptive finite element solver is utilized. Additional technologies including in-situ visualization and atmospheric microscale modeling are incorporated into the analysis environment. Validation of the computational framework is performed on the National Renewable Energy Laboratory (NREL) 5MW baseline wind turbine, the unsteady aerodynamics experimental NREL Phase VI turbine, and the Siemens SWT-2.3-93 wind turbine. The power and thrust results of all single turbine simulations agree well with low-fidelity model simulation results and field experiments when available. Scalability of the computational framework is demonstrated using 6, 12, 24, 48, and 96 wind turbine setups including the 48 turbine wind plant known as Lillgrund. The largest case consisting of 96 wind turbines and a total of 385 overset grids are run on 44,928 cores at a weak scaling efficiency of 86%. Demonstration of the coupling of atmospheric microscale and Computational Fluid Dynamics (CFD) solvers is presented using the National Center for Atmospheric Research (NCAR) Weather Research and Forecasting Model (WRF) solver and the NREL Simulator fOr Wind Farm Applications (SOWFA) solver.

Quantitative microbial risk assessment applied to irrigation of salad crops with waste stabilization pond effluents

2013 ◽  
Vol 67 (6) ◽  
pp. 1208-1215 ◽  
Author(s):  
D. M. S. Pavione ◽  
R. K. X. Bastos ◽  
P. D. Bevilacqua
Keyword(s):  
Risk Assessment ◽  
Field Experiments ◽  
Daily Intake ◽  
Assessment Model ◽  
Sensitivity Analyses ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Risk Estimates ◽  
Log Normal

A quantitative microbial risk assessment model for estimating infection risks arising from consuming crops eaten raw that have been irrigated with effluents from stabilization ponds was constructed. A log-normal probability distribution function was fitted to a large database from a comprehensive monitoring of an experimental pond system to account for variability in Escherichia coli concentration in irrigation water. Crop contamination levels were estimated using predictive models derived from field experiments involving the irrigation of several crops with different effluent qualities. Data on daily intake of salad crops were obtained from a national survey in Brazil. Ten thousand-trial Monte Carlo simulations were used to estimate human health risks associated with the use of wastewater for irrigating low- and high-growing crops. The use of effluents containing 103–104E. coli per 100 ml resulted in median rotavirus infection risk of approximately 10−3 and 10−4 pppy when irrigating, respectively, low- and high-growing crops; the corresponding 95th percentile risk estimates were around 10−2 in both scenarios. Sensitivity analyses revealed that variations in effluent quality, in the assumed ratios of pathogens to E. coli, and in the reduction of pathogens between harvest and consumption had great impact upon risk estimates.

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