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

Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

1.5K
The instrumentation of atomic emission spectrometry (AES) involves various components, including atomization devices that convert samples into gas-phase atoms and ions. There are two main types of atomization devices: continuous and discrete atomizers.  Continuous atomizers, like plasmas and flames, introduce samples in a constant stream, while discrete atomizers inject individual samples using syringes or autosamplers. The most common discrete atomizer is the electrothermal atomizer.
1.5K
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

770
AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
770
Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

4.1K
Atomic emission spectroscopy (AES) is an analytical technique used to determine the elemental composition of a sample by analyzing the light emitted from excited atoms. In AES, atoms in a sample are excited to higher energy levels by thermal energy from high-temperature sources, such as plasma, arcs, or sparks. When these excited atoms return to lower energy states, they emit light at specific wavelengths characteristic of each element. The resulting atomic emission spectrum, which consists of...
4.1K
Emission Spectra02:39

Emission Spectra

77.4K
When solids, liquids, or condensed gases are heated sufficiently, they radiate some of the excess energy as light. Photons produced in this manner have a range of energies, and thereby produce a continuous spectrum in which an unbroken series of wavelengths is present.
77.4K
Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

919
Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
919
Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

725
In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...
725

You might also read

Related Articles

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

Sort by
Same author

Prenatal exposure to wildfire PM2.5 and pregnancy loss in Colorado, USA, 2007-2018.

International journal of epidemiology·2026
Same author

Individual and combined effects of indoor home exposures and ambient PM<sub>2.5</sub> during early life on childhood asthma in us birth cohort studies.

Environmental epidemiology (Philadelphia, Pa.)·2025
Same author

Residential proximity to nuclear power plants and cancer incidence in Massachusetts, USA (2000-2018).

Environmental health : a global access science source·2025
Same author

Subgroup analyses and effect modification with Bayesian kernel machine regression.

American journal of epidemiology·2025
Same author

Variability of menstrual cycles by age, polycystic ovary syndrome, and early-life cycle irregularity in the apple Women's Health Study.

American journal of obstetrics and gynecology·2025
Same author

Preconception, gestation, and childhood exposure to air pollution and risk of polycystic ovary syndrome (PCOS) in a US girls cohort study.

Environment international·2025

Related Experiment Video

Updated: Mar 14, 2026

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System
08:59

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System

Published on: May 22, 2020

6.0K

Developing particle emission inventories using remote sensing (PEIRS).

Chia-Hsi Tang1, Brent A Coull2, Joel Schwartz1

  • 1a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA.

Journal of the Air & Waste Management Association (1995)
|September 23, 2016
PubMed
Summary
This summary is machine-generated.

A new remote sensing method accurately maps fine particulate matter (PM2.5) emissions across the northeastern US. This cost-effective approach improves emission inventories, aiding air quality regulations and health risk assessments.

More Related Videos

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

4.6K
Additive Manufacturing-Enabled Low-Cost Particle Detector
06:05

Additive Manufacturing-Enabled Low-Cost Particle Detector

Published on: March 24, 2023

2.5K

Related Experiment Videos

Last Updated: Mar 14, 2026

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System
08:59

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System

Published on: May 22, 2020

6.0K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

4.6K
Additive Manufacturing-Enabled Low-Cost Particle Detector
06:05

Additive Manufacturing-Enabled Low-Cost Particle Detector

Published on: March 24, 2023

2.5K

Area of Science:

  • Environmental Science
  • Atmospheric Science
  • Remote Sensing

Background:

  • Accurate particulate matter (PM2.5) emission data is vital for effective regulations and risk assessment.
  • Current methods for emission inventories are costly, time-consuming, and often omit smaller sources.
  • Existing inventories are aggregated at large spatial scales, limiting detailed analysis.

Purpose of the Study:

  • To develop and evaluate a novel method using remote sensing data for spatially resolved PM2.5 emission inventories.
  • To overcome limitations of traditional methods by accounting for all sources within a defined area.
  • To enable cost-effective generation of comprehensive emission datasets.

Main Methods:

  • Developed the Particle Emission Inventories Using Remote Sensing (PEIRS) method.
  • Utilized high-resolution 1 km x 1 km aerosol optical depth (AOD) data.
  • Applied the method to predict PM2.5 emissions in the northeastern United States (2002-2013).

Main Results:

  • Emission estimates showed moderate agreement with the EPA National Emission Inventory (R² = 0.66-0.71).
  • Predicted emissions correlated with land use parameters, indicating capture of land-use-related sources.
  • The method distinguished small-scale intra-urban variations, reflecting metropolitan source distributions.

Conclusions:

  • The novel remote sensing approach provides spatially resolved PM2.5 emission inventories cost-effectively.
  • PEIRS captures both primary emissions and secondary formations at high spatial resolution.
  • This method has significant potential to inform air quality regulations and improve emission data.