Issue 3, 2015

Characterization of fine particulate matter in ambient air by combining TEM and multiple spectroscopic techniques – NMR, FTIR and Raman spectroscopy

Abstract

This paper reports a systematic study of the microstructures and spectroscopic characteristics of PM2.5 and its potential sources in Beijing by combining transmission electron microscopy and multiple spectroscopic techniques: nuclear magnetic resonance, Fourier transform infrared and Raman spectroscopy. TEM images showed that dominant components of PM2.5 are airborne organic substances with many trace metal elements which are associated with combustion sources. NMR spectra precisely determined the percentage of carbonaceous speciation in both PM2.5 (with spatial and temporal distribution) and its potential sources, and distinguished the similarities and differences among them. In FTIR spectra, a remarkable peak at 1390 cm−1 that appeared only in PM2.5 samples was attributed to NH4NO3, representing the occurrence of secondary processes. Raman spectra revealed certain inorganic compounds including sulfate and nitrate ions. Based on the analysis of the decomposition of Raman spectra, spectral parameters provided structural information and helped to find potential sources of PM2.5. In the space of carbon aromaticity index and ID1/IG, PM2.5 points followed a linear distribution which may also be useful in source tracing. The result shows that the combined non-destructive methods are efficient to trace the sources of PM2.5.

Graphical abstract: Characterization of fine particulate matter in ambient air by combining TEM and multiple spectroscopic techniques – NMR, FTIR and Raman spectroscopy

Supplementary files

Article information

Article type
Paper
Submitted
12 Dec 2014
Accepted
22 Dec 2014
First published
22 Dec 2014

Environ. Sci.: Processes Impacts, 2015,17, 552-560

Author version available

Characterization of fine particulate matter in ambient air by combining TEM and multiple spectroscopic techniques – NMR, FTIR and Raman spectroscopy

Z. Ji, R. Dai and Z. Zhang, Environ. Sci.: Processes Impacts, 2015, 17, 552 DOI: 10.1039/C4EM00678J

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