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Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.
Fluorescence and Phosphorescence: Instrumentation01:25

Fluorescence and Phosphorescence: Instrumentation

Fluorometers and spectrofluorometers are two types of instruments used for measuring molecular fluorescence. These instruments differ in how they select excitation and emission wavelengths and the type of light sources they utilize. Fluorometers use absorption interference filters to choose excitation and emission wavelengths. The excitation source in a fluorometer is typically a low-pressure mercury vapor lamp that emits intense lines distributed throughout the ultraviolet and visible regions.

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Related Experiment Video

Updated: May 31, 2026

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Regression Models Enhance Fluorescence Spectra for Smart Surface Water Surveillance.

Jiukai Tang1,2,3,4,5, Zhaoyin Wang6, Mengzhen Xu6

  • 1State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.

Analytical Chemistry
|May 28, 2026
PubMed
Summary
This summary is machine-generated.

New regression models enhance fluorescence spectroscopy for water analysis. Weighted linear regression identifies dissolved organic carbon, while multivariable linear regression traces pharmaceutical wastewater, aiding smart water surveillance.

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Last Updated: May 31, 2026

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Area of Science:

  • Environmental Chemistry
  • Analytical Chemistry
  • Spectroscopy

Background:

  • Conventional fluorescence spectroscopy methods for aquatic dissolved organic matter analysis are limited.
  • Advanced analytical toolkits are needed for real-time water monitoring and wastewater tracing.

Purpose of the Study:

  • To develop easily implementable regression models for advanced fluorescence spectra analysis.
  • To establish a correlation map between fluorescence EEMs and DOC.
  • To identify pharmaceutical wastewater in surface water.

Main Methods:

  • Weighted linear regression (WLR) was used to create a fluorescence intensity (FI) and dissolved organic carbon (DOC) correlation map.
  • Multivariable linear regression (MLR) was developed to detect pharmaceutical wastewater.
  • 191 surface water samples from diverse aquatic environments were analyzed.

Main Results:

  • Humic-like FI at 300-380/440-490 nm excitation/emission wavelengths reliably indicates aquatic DOC.
  • The MLR model achieved 10-20% fitting errors in identifying pharmaceutical wastewater, even with fluorescence quenching.
  • Novel regression-based toolkits were established for fluorescence spectra analysis.

Conclusions:

  • Regression-based toolkits advance the application of fluorescence spectroscopy in environmental protection.
  • Developed methods offer improved capabilities for smart water surveillance.
  • The study provides reliable indicators for aquatic DOC and tools for wastewater tracing.