Related Experiment Video

Updated: Mar 7, 2026

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

3.0K

Reflection of Sectoral Emissions on Air Quality, Mortality, and Air Pollution Exposure Inequalities in a Metropolitan

Sara Torbatian1, Daniel Yazgi2, Shayamila Mahagammulla Gamage1

  • 1Department of Civil and Mineral Engineering, University of Toronto, Toronto, Ontario M5S 1A4, Canada.

Environmental Science & Technology
|March 6, 2026
PubMed

Keywords:
air pollution exposurechemical transport modelenvironmental justicesector-specific emissions

More Related Videos

Measuring Carbon Content in Airway Macrophages Exposed to Carbon-Containing Particulate Matters05:18

Measuring Carbon Content in Airway Macrophages Exposed to Carbon-Containing Particulate Matters

Published on: July 12, 2024

903
Quantification of three DNA Lesions by Mass Spectrometry and Assessment of Their Levels in Tissues of Mice Exposed to Ambient Fine Particulate Matter12:15

Quantification of three DNA Lesions by Mass Spectrometry and Assessment of Their Levels in Tissues of Mice Exposed to Ambient Fine Particulate Matter

Published on: May 29, 2019

9.2K

Related Concept Videos

Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
914
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.5K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
503
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K