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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Chemical Equilibria: Systematic Approach to Equilibrium Calculations01:21

Chemical Equilibria: Systematic Approach to Equilibrium Calculations

Equilibrium calculations for systems involving multiple equilibria are often complex. For example, to calculate the solubility of a sparingly soluble salt in an aqueous solution in the presence of a common ion, one must consider all the equilibria in this solution. Calculations for these systems can be complicated and tedious, so a systematic approach with a series of steps is often helpful. The process is detailed below.
The first step is to identify all the chemical reactions involved, The...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...

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Updated: Jun 6, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

An Integrated Framework for VOC Source Apportionment Based on Chemical Transport Modeling and Observation-Constrained

Yangjun Wang1, Yifei Chen1, Yongtao Hu2

  • 1School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.

Environmental Science & Technology
|June 5, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an integrated framework for volatile organic compound (VOC) source apportionment, improving accuracy by coupling chemical transport models with observation-constrained optimization. The method enhances understanding of atmospheric processing and source impacts in the Yangtze River Delta.

Keywords:
chemical transport model (CTM)integrated frameworkobservation-constrained optimizationsource apportionmentsource profilevolatile organic compounds (VOCs)

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Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction
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Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Published on: June 1, 2022

Area of Science:

  • Atmospheric Chemistry
  • Environmental Science
  • Air Quality Modeling

Background:

  • Volatile organic compounds (VOCs) are crucial air pollutants whose sources are difficult to quantify due to atmospheric processing.
  • Accurate source apportionment is essential for effective air quality management and policy development.

Purpose of the Study:

  • To develop and apply an integrated framework for VOC source apportionment using a chemical transport model (CTM) coupled with observation-constrained optimization.
  • To assess the impact of atmospheric processing on VOC profiles and improve source identification in the Yangtze River Delta (YRD).

Main Methods:

  • Coupling a chemical transport model (CTM) with observation-constrained optimization.
  • Application to five supersites in the Yangtze River Delta (YRD), China, from May to September 2018.
  • Analysis of VOC profiles, atmospheric aging, and comparison between emission and receptor-derived source profiles.

Main Results:

  • Significant improvements in source apportionment accuracy, with increased Index of Agreement (IOA) by 15-114% and decreased Root Mean Square Error (RMSE) by 18-71%.
  • Demonstrated substantial divergence between emission and receptor-derived profiles for natural sources at anthropogenically influenced sites due to atmospheric processing.
  • Observed enrichment of low-reactivity alkanes and depletion of highly reactive species (alkenes, isoprene) at receptor sites, indicating atmospheric aging.

Conclusions:

  • The integrated framework provides a more robust and environmentally representative basis for VOC source identification.
  • The methodology enhances the agreement between model simulations and observations, leading to improved source apportionment.
  • The framework shows potential for extension to PM2.5 source apportionment, particularly in systems with significant secondary aerosol formation.