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Related Concept Videos

Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
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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...

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Conditional sampling for source-oriented toxicological studies using a single particle mass spectrometer.

K J Bein1, Y Zhao, A S Wexler

  • 1Air Quality Research Center, Mechanical and Aeronautical Engineering, Civil and Environmental Engineering, and Land, Air and Water Resources, University of California-Davis, Davis, California 95616, USA. kjbein@ucdavis.edu

Environmental Science & Technology
|December 17, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel system to selectively collect atmospheric particles based on their sources. This allows for more accurate toxicological studies by analyzing compositionally distinct particle samples.

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Area of Science:

  • Environmental Science
  • Atmospheric Chemistry
  • Toxicology

Background:

  • Current particulate matter (PM) regulations focus on mass concentration, overlooking the varying toxicity of different PM components.
  • Atmospheric transformations can alter the toxicity of primary and secondary PM, making source-specific analysis crucial.
  • Existing methods often neglect the impact of atmospheric processing on pollutant toxicity.

Purpose of the Study:

  • To develop and implement a system for conditionally sampling atmospheric particles based on predominant sources.
  • To enable comparative toxicological studies by collecting compositionally distinct PM samples.
  • To investigate the chemical composition of individual particles and identify contributing sources in real-time.

Main Methods:

  • Utilized a real-time single particle mass spectrometer (RSMS-II) for chemical composition analysis of 70-150 nm particles.
  • Employed an algorithm to identify dominant atmospheric sources based on RSMS-II mass spectra.
  • Controlled ten ChemVol samplers, each assigned to a specific source or source combination, based on real-time source identification.

Main Results:

  • Successfully demonstrated a system capable of conditionally sampling atmospheric particles based on predominant sources.
  • Collected sufficient sample mass for comparative toxicological studies through extended operation periods.
  • Provided initial data on particle composition and source contributions in Fresno, CA, during summer 2008 and winter 2009.

Conclusions:

  • The developed system enables targeted collection of PM for toxicological assessment, moving beyond mass-based regulations.
  • Real-time source identification coupled with conditional sampling is feasible for studying PM toxicity.
  • This approach facilitates a more nuanced understanding of air pollution impacts by linking specific sources to particle toxicity.