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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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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...
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Related Experiment Video

Updated: May 5, 2026

Automated, High-resolution Mobile Collection System for the Nitrogen Isotopic Analysis of NOx
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Estimating mobile source pollutant emission: Methodological comparison and planning implications.

T J Kim1, N G Hoskote

  • 1University of Illinois at Urbana-Champaign, USA.

Environmental Monitoring and Assessment
|November 22, 2013
PubMed
Summary
This summary is machine-generated.

Estimating mobile source emissions involves different methods that can yield significantly different results. Choosing the right zonal speed aggregation is crucial for accurate transportation planning and air quality control strategies.

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Area of Science:

  • Environmental Science
  • Transportation Engineering
  • Air Quality Management

Background:

  • The Clean Air Act Amendments of 1977 mandate air quality assessments for non-attainment areas.
  • Transportation controls, particularly those affecting vehicular speed, are key to meeting National Ambient Air Quality Standards.
  • Mobile source emissions are a significant contributor to air pollution in metropolitan areas.

Purpose of the Study:

  • To compare two distinct methods for estimating mobile source emissions.
  • To analyze the impact of different zonal speed aggregation procedures on emission estimates.
  • To highlight the implications of these methods for transportation planning and air quality control.

Main Methods:

  • Utilized two alternative methodologies for calculating mobile source emissions within a specific metropolitan area.
  • Examined various zonal speed aggregation techniques and their influence on emission calculations.
  • Assessed the underlying assumptions of each aggregation procedure.

Main Results:

  • Identified substantial discrepancies in mobile source emission estimates based on the chosen aggregation method.
  • Demonstrated that alternative zonal speed aggregation procedures can produce widely diverging results.
  • Highlighted the sensitivity of emission calculations to the specific aggregation approach employed.

Conclusions:

  • The selection of zonal speed aggregation methods significantly impacts mobile source emission estimations.
  • Inaccurate emission data can lead to flawed transportation planning for air quality.
  • Careful consideration of aggregation assumptions is essential for effective implementation of the Clean Air Act.