Publication

Estimation of Organic and Elemental Carbon using FT-IR absorbance spectra from PTFE Filters

2015
Posters

Abstract

Organic carbon and elemental carbon are major components of atmospheric PM. Typically they are measured using destructive and relatively expensive methods (e.g., TOR). We aim to reduce the operating costs of large air quality monitoring networks using FT-IR spectra of ambient PTFE filters and PLS regression. We achieve accurate predictions for models (calibrated in 2011) that use samples collected at the same or different sites of the calibration data set and in a different year (2013).

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2015
Posters

Abstract

Official source

Related concepts (32)

Carbon

Carbon () is a chemical element with the symbol C and atomic number 6. It is nonmetallic and tetravalent—its atom making four electrons available to form covalent chemical bonds. It belongs to group 14 of the periodic table. Carbon makes up about 0.025 percent of Earth's crust. Three isotopes occur naturally, ^12C and ^13C being stable, while ^14C is a radionuclide, decaying with a half-life of about 5,730 years. Carbon is one of the few elements known since antiquity.

Near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum (from 780 nm to 2500 nm). Typical applications include medical and physiological diagnostics and research including blood sugar, pulse oximetry, functional neuroimaging, sports medicine, elite sports training, ergonomics, rehabilitation, neonatal research, brain computer interface, urology (bladder contraction), and neurology (neurovascular coupling).

Principal component regression

In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model. In PCR, instead of regressing the dependent variable on the explanatory variables directly, the principal components of the explanatory variables are used as regressors.

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