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

Sampling Plans01:23

Sampling Plans

334
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...
334

You might also read

Related Articles

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

Sort by
Same author

[Differences of Three Methods in Determining Ozone Sensitivity in Nanjing].

Huan jing ke xue= Huanjing kexue·2024
Same author

[Seasonal Variations, Size Distributions, and Sources of Chemical Components of Submicron Particulate Matter in Nanjing].

Huan jing ke xue= Huanjing kexue·2023
Same author

[Variations in PM<sub>2.5</sub> Composition and Sources During 2020-2021 COVID-19 Epidemic Periods in Nanjing].

Huan jing ke xue= Huanjing kexue·2023
Same author

[Multi-omics analysis of regulating effects of hyperoside on lipid metabolism in high-fat diet mice].

Sheng li xue bao : [Acta physiologica Sinica]·2023
Same author

[Light-absorbing Properties and Sources of PM<sub>2.5</sub> Organic Components at a Suburban Site in Northern Nanjing].

Huan jing ke xue= Huanjing kexue·2021
Same author

Comparisons of the restoring and reinforcement effects of carboxymethyl chitosan-silk fibroin (Bombyx Mori/Antheraea Yamamai/Tussah) on aged historic silk.

International journal of biological macromolecules·2018

Related Experiment Video

Updated: Oct 18, 2025

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
05:45

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions

Published on: January 7, 2019

11.5K

[Continuous PM2.5 Composition Measurements for Source Apportionment During Air Pollution Events].

Fan-Tao Cai1, Yue Shang1, Wei Dai1

  • 1Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science & Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Huan Jing Ke Xue= Huanjing Kexue
|September 28, 2021
PubMed
Summary

Using high-temporal-resolution data for PM2.5 source apportionment during pollution events provides more accurate results. Analyzing specific events like fireworks or sandstorms improves understanding of emission sources compared to long-term data.

Keywords:
PM2.5PMF source apportionmentcontinuous monitoringcontribution distributionpollution event

More Related Videos

Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers
10:29

Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers

Published on: March 21, 2016

12.5K
Production and Measurement of Organic Particulate Matter in a Flow Tube Reactor
13:29

Production and Measurement of Organic Particulate Matter in a Flow Tube Reactor

Published on: December 15, 2018

7.7K

Related Experiment Videos

Last Updated: Oct 18, 2025

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
05:45

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions

Published on: January 7, 2019

11.5K
Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers
10:29

Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers

Published on: March 21, 2016

12.5K
Production and Measurement of Organic Particulate Matter in a Flow Tube Reactor
13:29

Production and Measurement of Organic Particulate Matter in a Flow Tube Reactor

Published on: December 15, 2018

7.7K

Area of Science:

  • Environmental Science
  • Atmospheric Chemistry
  • Air Quality Monitoring

Background:

  • Particulate Matter (PM2.5) significantly impacts air quality and human health.
  • Accurate source apportionment is crucial for effective pollution control strategies.
  • Traditional long-term monitoring may obscure short-term pollution event dynamics.

Purpose of the Study:

  • To evaluate the application of high-temporal-resolution data for PM2.5 source apportionment during specific air pollution events.
  • To compare source apportionment results derived from event-specific data versus full-year data.
  • To assess the timeliness and accuracy of source identification using continuous monitoring.

Main Methods:

  • Continuous hourly monitoring of PM2.5 components (elements, ions, carbonaceous) in Nanjing, 2017.
  • Application of Positive Matrix Factorization (PMF) on datasets from specific pollution events (fireworks, sandstorm, haze) and the full year.
  • Comparison of PMF-derived source contributions and component concentrations between different datasets.

Main Results:

  • Source profiles and contributions differed significantly between event-specific and full-year PMF analyses.
  • Event-specific analyses (e.g., fireworks, sandstorms) provided more accurate estimations for characteristic components (e.g., K, Fe, Si, Ti) compared to full-year analyses.
  • Full-year PMF underestimated contributions from event-specific sources due to assumed constant source profiles.

Conclusions:

  • High-temporal-resolution data from pollution events enhance the accuracy of PM2.5 source apportionment.
  • Event-based PMF analysis captures short-term variations in PM2.5 sources more effectively than long-term analysis.
  • This approach improves the timeliness and reliability of air pollution source identification for targeted interventions.