Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Phytosulfokine peptide regulates growth-immunity tradeoff through CAMTA3-mediated transcriptional signaling in Arabidopsis.

Plant communications·2026
Same author

G protein-biased signaling activates PKCβII by outcompeting arrestin3 for Mdm2-mediated ubiquitination.

Life sciences·2026
Same author

3D Segment Anything Model With Visual Mamba for Diagnosing Placenta Accreta Spectrum.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Structure-Activity Relationships and Ligand-Dependent Arrestin Bias in μ-Opioid Receptor-Mediated ERK Activation.

Biomolecules & therapeutics·2026
Same author

Interpretable neural network for risk stratification and drug target discovery based on PBMC transcriptomes.

iScience·2026
Same author

Correction: Corneal Asymmetry Contributes Decentration in Both Spherical and Toric Orthokeratology Lenses.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)·2026

Related Experiment Video

Updated: Jun 3, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
11:19

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

Published on: October 21, 2016

Robust contaminant plume estimation for risk assessment.

Lulu Peng1, Eric G Lamb1, Lidong Huang2

  • 1University of Saskatchewan, Canada.

Journal of Hazardous Materials
|June 1, 2026
PubMed
Summary

Accurate soil contaminant plume estimation is crucial for cost-effective remediation. A new INLA-SPDE model effectively estimates plume volume and mass, even with limited, zero-inflated data, outperforming traditional methods.

Keywords:
BiostimulationINLA-SPDE modelPetroleum hydrocarbonPlume estimationRisk assessment

More Related Videos

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
08:42

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

Published on: August 29, 2014

Speciation and Bioavailability Measurements of Environmental Plutonium Using Diffusion in Thin Films
12:22

Speciation and Bioavailability Measurements of Environmental Plutonium Using Diffusion in Thin Films

Published on: November 9, 2015

Related Experiment Videos

Last Updated: Jun 3, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
11:19

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

Published on: October 21, 2016

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
08:42

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

Published on: August 29, 2014

Speciation and Bioavailability Measurements of Environmental Plutonium Using Diffusion in Thin Films
12:22

Speciation and Bioavailability Measurements of Environmental Plutonium Using Diffusion in Thin Films

Published on: November 9, 2015

Area of Science:

  • Environmental Science
  • Geostatistics
  • Risk Management

Background:

  • Accurate soil contaminant plume volume estimation is vital for cost-effective remediation, but limited and zero-inflated datasets pose challenges for traditional geostatistical methods like Kriging.
  • Traditional methods struggle with heterogeneity and preferential flow, often inadequately characterizing contaminant plumes.

Purpose of the Study:

  • To adapt and evaluate the Integrated Nested Laplace Approximation with a Stochastic Partial Differential Equation (INLA-SPDE) framework for estimating petroleum hydrocarbon (PHC) plume volume and mass.
  • To incorporate a tracer covariate within the INLA-SPDE framework to account for preferential flow effects.
  • To compare the performance of INLA-SPDE against Hurdle and Kriging models using synthetic and real-world contaminated site data.

Main Methods:

  • The study adapted the INLA-SPDE framework, a Bayesian geostatistical approach, for contaminant plume estimation.
  • A tracer covariate was integrated into the model to represent preferential flow.
  • Performance was evaluated using three synthetic plumes and two real remediation sites over 100 Monte Carlo simulations, comparing INLA-SPDE with Hurdle and Kriging models.

Main Results:

  • The INLA-SPDE model provided robust plume volume and mass estimates with minimal data (as few as five boreholes) under specific conditions, including high vertical resolution and the presence of high-concentration boreholes.
  • Addressing vertical heterogeneity was found to be more impactful for plume estimation accuracy than increasing borehole density.
  • The tracer covariate improved predictions for the CCME F1 fraction but had less impact on the more mobile benzene.

Conclusions:

  • The INLA-SPDE framework offers a powerful and robust solution for contaminant plume estimation, particularly effective under conditions of limited and zero-inflated data.
  • This approach enhances the accuracy of volume and mass estimations, supporting more cost-effective remediation planning and regulatory decision-making.
  • The study highlights the importance of vertical sampling and demonstrates the utility of INLA-SPDE for complex environmental site characterization.