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

Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
Partial Fractions01:28

Partial Fractions

A partial fraction is a component of a rational expression represented as the sum of simpler fractions. When a rational function is expressed as a ratio of two polynomials, it can often be decomposed into a sum of fractions whose denominators are simpler polynomials, typically linear or irreducible quadratic factors. This process is called partial fraction decomposition, and it is used to simplify complex expressions for integration, solving equations, or analysis.Partial fraction decomposition...

You might also read

Related Articles

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

Sort by
Same author

Short term air pollution exposure during pregnancy and associations with maternal immune markers.

Environmental research·2024
Same author

Common and distinct pollution sources identified from ambient PM<sub>2.5</sub> concentrations in two sites of Los Angeles Basin from 2005 to 2019.

Environmental pollution (Barking, Essex : 1987)·2023
Same author

Evaluation of air quality changes in a Chinese megacity over a 15-year period (2006-2021) using PM<sub>2.5</sub> receptor modelling.

Environmental pollution (Barking, Essex : 1987)·2023
Same author

Sources, variability and parameterizations of intra-city factors obtained from dispersion-normalized multi-time resolution factor analyses of PM<sub>2.5</sub> in an urban environment.

The Science of the total environment·2020
Same author

Speciation of organic fractions does matter for aerosol source apportionment. Part 3: Combining off-line and on-line measurements.

The Science of the total environment·2019
Same author

Ambient black carbon particulate matter in the coal region of Dhanbad, India.

The Science of the total environment·2017
Same journal

Friction-Mediated Transfer of Low Molecular Weight Chemicals from Consumer Mats to Fabrics: Insights for Dermal Exposure.

Environmental science & technology·2026
Same journal

Molecular Drivers of Contrasting Photoreactivity in Extracellular versus Intracellular Organic Matter from Chlorophyta and Cyanobacteria.

Environmental science & technology·2026
Same journal

Effective Precipitate Cleaning with a Reversible Flow Cell Sustains Stable Energy Intensity for Oceanic CO<sub>2</sub> Removal.

Environmental science & technology·2026
Same journal

The Efficiencies and Products of Dilute Methane Oxidation in a Chlorine Radical Photoreactor.

Environmental science & technology·2026
Same journal

Investigating Ultrafine Aerosol Turbulent Fluxes during Atmospheric New Particle Formation Events.

Environmental science & technology·2026
Same journal

Occurrence, Sources, and Export Rates of Ti-Bearing and Ce-Bearing (Nano)particles in the Seine River Where Engineered Nanoparticles Reach Natural Background Levels.

Environmental science & technology·2026
See all related articles

Related Experiment Video

Updated: Jun 16, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

PCDD/F source apportionment in the Baltic Sea using positive matrix factorization.

K L Sundqvist1, M Tysklind, P Geladi

  • 1Department of Chemistry, Umeå University, SE-90187 Umeå, Sweden. kristina.sundqvist@chem.umu.se

Environmental Science & Technology
|February 4, 2010
PubMed
Summary
This summary is machine-generated.

Atmospheric deposition is the main source of dioxins and furans (PCDD/F) in the Baltic Sea. Coastal sources like historical chlorophenol use and pulp production also contribute, with regional variations observed.

Related Experiment Videos

Last Updated: Jun 16, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Area of Science:

  • Environmental Chemistry
  • Marine Pollution Studies

Background:

  • Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) are persistent organic pollutants of concern in marine environments.
  • The Baltic Sea, a semi-enclosed sea, is susceptible to contamination from various sources, necessitating source apportionment studies.

Purpose of the Study:

  • To identify and quantify the sources of PCDD/F in Baltic Sea surface sediments.
  • To differentiate between offshore and coastal contamination pathways and assess their relative importance.

Main Methods:

  • Positive Matrix Factorization (PMF) analysis was applied to sediment samples from offshore and coastal areas of the Baltic Sea.
  • Source apportionment was conducted to identify candidate sources contributing to PCDD/F pollution.

Main Results:

  • Atmospheric deposition was identified as the dominant PCDD/F source in offshore and pristine Baltic Sea regions.
  • Historical chlorophenol use and pulp and paper industry activities were significant coastal sources.
  • Chlorine bleaching of pulp was a minor source in modern sediments, contrary to previous assumptions.
  • Local and regional coastal sources impacted offshore areas, and incineration/high-temperature processes were more significant in the southern Baltic Sea.

Conclusions:

  • Source identification of PCDD/F in the Baltic Sea requires considering both atmospheric deposition and localized coastal industrial activities.
  • Regional variations in PCDD/F sources highlight the need for geographically specific pollution management strategies.
  • Future research should include diverse offshore sediments to comprehensively understand PCDD/F sources impacting the Baltic Sea.