From: “Important Instrumentation and Methods for the Detection of Chemicals in the Field”. Chapter 8 on FTIR Gas
Measurement by the real time detection chapter of the AIHA
ISBN-13: 978-1-935082-41-5
Chapter 8
Field-Portable Fourier Transform Infrared (FTIR)
Spectroscopy for Gas and Vapor Analysis
Antii Heikkila, MSc
Introduction
Fourier Transform Infrared (FTIR) spectrometers are widely
used in various analytical applications ranging from
qualitative identification of solid and liquid samples, to
qualitative and quantitative analysis of trace gases and
vapors in complex matrices such as contaminated air or
process gas streams. The FTIR measurement technique
relies on an optical modulator known as an interferometer.
The first interferometer design by A.A. Michelson near the
turn of the 20th century(1,2) predates infrared spectroscopy.
Michelson’s interferometer was built to prove or disprove
the existence of ether in space, and Michelson and Morley
used interferometer measurements to show that the speed
of light was uniform in all directions. This exposed a major
flaw in the ether theory of light, and paved the way for
future work to describe the theory of relativity by Einstein.(3)
Michelson was awarded the 1907 Nobel Prize in physics “for
his optical precision instruments and the spectroscopic and
metrological investigations carried out with their aid.”(4) While
Rayleigh made an early suggestion to Michelson that the
interferometer could be used to measure the wavelengths of
light(5), the prevalent method at that time (and for the next
half century) to measure an optical spectrum was based on
wavelength dispersion using a prism or a grating.
In 1949, Fellgett performed an approximate Fourier
transformation of interferometer data to obtain absorbance
information across a range of wavelengths (an absorbance
spectrum).(3) Fellgett recognized that during collection of an
interferogram, data from all spectral wavelengths are obtained
simultaneously, whereas collection of a spectrum using a
prism or series of IR filters allows measurement of only a single
wavelength band at any given instant. The ability to collect a
wide range of wavelength information simultaneously reduces
the time required for measurement of a spectrum with an FTIR
instrument compared to a dispersion or filter instrument, and
this improved performance is known as “Fellgett’s advantage.”
The FTIR spectrometer was limited by the relatively slow
computation methods of the Fourier transformation with
available computers and algorithms until Cooley and Tukey
described the fast Fourier transform in 1965.(6) Instrumentation
for FTIR analysis became commercially available soon
afterwards. The introduction of cube corner mirrors into FTIR
spectrometers by Mattson in 1983(7) represented a major
improvement, and allowed requirements for precise alignment
of moving optical components to be relaxed, making FTIR
suitable for industrial and field measurement applications.
IR Theory and Instrumentation
The majority of infrared (IR) gas analyzers operate in the
mid-IR region (about 2 to 15 µm wavelengths). Spectra are
usually plotted as absorbance or per cent transmission on the
y axis against wavenumber on the x axis. The wavenumber
47
Important Instrumentation and Methods for Detection of Chemicals in the Field
is related to IR wavelength as the reciprocal of wavelength
(expressed in units of cm), and thus has units of cm-1. The
wavenumber describes the number of complete waves
for a particular wavelength across a distance of 1 cm, and
wavenumbers are directly related to energy levels. The
mid-IR wavelengths between 2 and 15 µm correspond to
wavenumbers 5000 cm-1 to 670 cm-1. Instruments operating
at higher wavenumbers (shorter wavelengths) are termed
near-IR analyzers and are used mainly for analysis of liquids
in various process applications. The lower wavenumbers
(longer wavelengths) of far IR are mainly used in research
applications with solid samples.
Absorption of mid-IR energy occurs at specific wavelengths
depending on the molecular structure of a vibrating
molecule. While light energy at these wavelengths is not
sufficient to cause electronic transitions, this region does
encompass the resonant frequencies of molecular bonds.
When the energy of an incoming photon matches the energy
difference between two vibrational levels of a molecule
the molecule can absorb the photon and transfer from a
lower to a higher vibrational energy level. This results in a
reduction of IR light arriving at a detector. A dipole moment
in a molecule (separate regions of differing electric charge)
that will change as the molecule vibrates is required for
IR absorption. The probability of the molecule absorbing
incoming IR light increases with the magnitude of dipole
moment, and vibrations in homonuclear molecules with
zero dipole moment do not absorb IR light. This means that
diatomic molecules composed of only a single element such
as nitrogen (N2) and oxygen (O2) will not absorb IR energy.
Figure 8.1 shows a gas phase IR spectrum for a volatile
organic compound, with characteristic IR absorption features
due to the presence of different functional groups.
Three general types of IR absorption instruments are
commonly encountered for field use. These are the nondispersive IR (NDIR), dispersive or filter IR (FIR), and FTIR
instruments. The NDIR instruments are typically used to
detect and quantify only a single pre-selected gas or vapor
analyte, while dispersive or FIR instruments are more capable.
The field-portable FTIR group includes instrumentation
dedicated to the analysis of gases and vapors, as well as other
types that may analyze solid and liquid materials. The primary
differences between dispersive and FTIR instruments will be
described below.
Single-Analyte IR Instruments
The simplest IR absorption detector uses only a single
wavelength (or narrow wavelength band) and the different
48
Figure 8.1 – Infrared spectrum for 200 ppm cis-1,2-dichloroethylene vapor
with absorbance features due to various functional groups as noted. A 980
cm multipass gas cell was used (1.0 atm, 51°C). The spectrum was recorded
using a Gasmet FTIR instrument operating with 7.72 cm-1 spectral resolution.
wavelengths of IR light produced from a source are not
dispersed. Dispersion is not needed if absorbance at only a
single dedicated wavelength is to be measured, and either a
monochromatic light source is used or a filter is used to limit
the transmission of light to a desired frequency.
Single-gas analyzers for either carbon monoxide (CO) or
carbon dioxide (CO2) are common examples of the simple
NDIR detection approach. For an NDIR instrument used to
measure CO, all absorption at a specified wavelength (near
4.8 µm in this example) must be assumed to be due to the
target analyte, although this assumption may give rise to
cross-sensitivity interference if an unexpected component of
the gas phase sample absorbs IR energy at or very near the
same region of the spectrum. For example, nitrous oxide (N2O,
which absorbs strongly near 4.5 µm) could be an interferent
to NDIR measurement of CO.
Dispersive and Filter IR Instruments
A more complicated IR detection approach that may provide
more information will take into account more than a single
absorbance wavelength. If a full-spectrum IR scan is required,
it is necessary for a non-FTIR instrument to separately measure
the different wavelength values in the spectrum. This may
be accomplished by dispersing the IR light with a pivoting
reflective grating that causes different wavelengths to strike a
detector at different times. Another approach is to sequentially
place different filters in the optical path to collect absorbance
data over time for a number of discrete IR wavelengths.
The Miran Sapphire 205B instrument operates as a FIR
instrument, employing seven fixed wavelength filters to
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
measure mid-IR absorbance at specific wavelengths between
about 1.8 and 4.7 µm, and a variable filter for wavelengths
between 7.7 and 14.1 µm. Absorbance information may be
obtained over a period of several minutes for the portions
of a mid-IR spectrum corresponding to the available filters
(if desired) by sequentially scanning with the various
filters placed in the optical path. While this approach
provides significant capability beyond that of a simple
NDIR instrument, the need to sequentially scan makes
this approach slow relative to FTIR spectroscopy where
absorbance data are simultaneously collected across a range
of wavelengths. For detection of a pre-determined gas the
FIR instrument may be operated analogously to the NDIR
detector using only absorbance at a relevant wavelength,
although it is subject to the same types of interferences as a
simple NDIR detector when it is used in this way.
possible to calculate from it the absorbance peaks due to the
sample present between the interferometer and the detector.
For many years the main factor preventing FTIR analysis from
becoming more commonplace was the computation time
of the Fourier transformation, but following the invention
of a fast Fourier transform algorithm discussed previously,
and with advances in digital signal processing it has become
practical to build small, low-cost FTIR spectrometers capable
of rapidly measuring a complete mid-IR spectrum with
moderate or high resolution and very good signal-to-noise
ratio. Coupled with advanced algorithms for identification
and quantification of the chemical species represented in the
spectrum, modern gas and vapor FTIR analyzers may identify
multiple unknowns, and quantify components of complex
gas phase mixtures containing dozens of volatile organic
compounds.
Fourier Transform IR Instruments
In contrast to NDIR and dispersive or FIR instruments, with an
FTIR instrument the signal for all relevant wavelengths arrives
at the detector nearly simultaneously, and IR absorbance
information for the different wavelengths is separated
through computation. This allows for nearly instantaneous
scanning of a wide wavelength range, and greater sensitivity
due to the Fellgett advantage. In 1989, Levine et al.(8)
discussed the relative advantages and disadvantages of FTIR
compared to FIR for monitoring gases and vapors of concern
to the industrial hygienist. At that time, field-portable FIR
instruments were available, but FTIR was still mostly confined
to the laboratory. Levine et al. predicted that “FTIR systems
will get smaller and cheaper and will compete with the FIR
systems for transportable air monitoring applications.” In
the roughly twenty intervening years this has occurred. The
remainder of this chapter discusses FTIR analysis, mostly
regarding field analysis of gas phase compounds.
The IR radiation from a light source in an FTIR spectrometer
is collected into a collimated beam, which is then split in
two branches with different optical path lengths. The length
of one or both of these branches is varied with a moving
mirror, and the two branches are brought together so that
depending on the position of the moving mirror the beams
undergo either constructive or destructive interference. The
resulting beam with constantly varying intensity is passed
from the interferometer through a sample compartment
where absorbance occurs, and then to a detector, where
the signal is recorded as a function of time. The result is an
interferogram, and through Fourier transform analysis it is
Fourier Transform IR Gas and Vapor
Analyzer Components
IR Source
For portable mid-IR instruments a common type of light
source is a black body radiator relying on thermal emission
of IR light from a hot filament (e.g. kanthal™, a Ni-Cr-Al alloy)
or small ceramic rod (for example, a 5 mm diameter x 50 mm
silicon carbide ceramic “globar” rod). Both of these simple
light sources demonstrate continuous emission over the midIR wavelengths, with low cost and long operational lifespan
(years).
Interferometer
The interferometer is the heart of an FTIR spectrometer,
and the traditional design by Michelson is shown in Figure
8.2, in simplified form. Light emitted from the IR source is
directed to a thin reflective metal disk (beamsplitter, typically
positioned at a 45 degree angle) which is sandwiched
between two windows transparent to IR wavelengths. In
the example shown in Figure 8.2 a portion of the radiation
(ideally 50%) passes through the beamsplitter towards m2,
while the rest is reflected towards m1. Both branches of the
beam are then reflected back to the beamsplitter, where
the two beams converge and a part of the IR radiation exits
the interferometer into the sample compartment while
another part is directed back at the light source and is lost.
A small amount of light is lost in the optics, meaning that at
most only 50% of the original IR radiation actually exits the
interferometer for transmission through the sample.
49
Important Instrumentation and Methods for Detection of Chemicals in the Field
Figure 8.2 – The Michelson Interferometer. LS = lightsource, BS =
beamsplitter, m1 = moving mirror, m2 = stationary mirror, b1 = infrared beam
with varying path length, b2 = infrared beam with fixed path length.
The modulation of the IR beam is achieved by moving one
of the mirrors (m1 in Figure 8.2) so that the distance travelled
by the beam b1 becomes longer than that of the beam b2
directed towards the stationary mirror m2. When the moving
mirror is displaced by one quarter of the wavelength of IR
light at a specific wavelength, the distance travelled by the
beam b1 becomes one half of the wavelength longer than
that of b2 and as a result the peaks and troughs of the two
waves line up and the resulting beam has zero intensity as
shown where optical density (OPD) ≈ λ/2 in Figure 8.3. When
the mirror m1 is displaced further, the peaks of the two waves
will be closer to each other until perfect alignment and
maximum intensity for the beam exiting the interferometer
is reached when the mirror m1 is displaced by a distance of
one half of the wavelength and the optical path difference
of beams b1 and b2 is equal to the wavelength. As the mirror
moves continuously at a steady rate, the modulated output
beam intensity will change as a cosine wave over time if there
is only one wavelength present in the IR beam. As the beam
contains all mid-IR wavelengths and no attempt is made to
disperse or filter them, the resulting interference pattern will
be more complex than in the example above, but the details
of the resulting interferogram hold the information required
to calculate the IR spectrum for the sample of interest.
In order to record the interferogram with the IR detector, a
means for determining the position of the moving mirror
is needed. In most commercial FTIR instruments the mirror
position is measured using a Helium-Neon gas laser which
emits a monochromatic and very stable radiation at 632.08
nm in the visible range. This laser beam is made to pass
through the interferometer co-axially with the IR beam, with
a dedicated laser detector inside the interferometer. The
interferogram recorded for the laser is a cosine wave and
the wavelength of the laser beam is constant, allowing the
position of the moving mirror to be tracked using the laser
signal. This internal calibration of the moving mechanism
50
Figure 8.3 – Interference patterns for two waves (e.g., b1 and b2 of Figure
8.2) of constant and equal frequency, offset by various distances related to
λ (wavelength), with corresponding sum waves (b1 + b2) immediately below
each distinct interference pattern. The sum waves b1 + b2 represent the beam
exiting the interferometer; OPD = optical path difference. When OPD ≈ zero,
the sum wave is at its strongest, and when OPD ≈ λλ/2, it is at its weakest.
is one of the strengths of FTIR. With a suitably rugged and
rapidly scanning mirror design an FTIR instrument can be
reliably used in a wide temperature range of 0 to 40°C,
while carried in a backpack, while mounted directly on a
smokestack, or inside a moving off-road vehicle. In all of these
situations, the wavenumber scale of the instrument remains
stable and calibration is maintained remarkably well.
Interferometer designs used today differ from Michelson’s
original approach. One of the shortcomings of the original
design was reliance on plane mirrors, which must remain
perfectly perpendicular to the beams. A second limitation
was the need to move one mirror over relatively long
distances while keeping all other parts stationary. The first
shortcoming is most often corrected by using cube corner
mirrors(7), which consist of three plane mirrors at 90° angles
to each other (see Figure 8.4). Such mirrors reflect light back
to the original direction regardless of the mirror orientation,
which makes it much easier to develop robust and simple
moving mechanisms for the interferometer. The second
Figure 8.4 – The geometry of the inner mirrored surfaces of the corner of
a cube is the basis for a retroreflector that returns the incoming beam back
to its original direction after three reflections, regardless of the orientation
of the cube corner itself. The original positions where the beam struck the
mirror surfaces prior to tilting the top of the cube corner slightly to the left
are depicted by the black dots in the panel to the right.
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
Figure 8.5 – Modern interferometer designs used in FTIR instrumentation: left, Michelson interferometer design with cube corner mirrors (used by various
manufacturers); right, Gasmet Technologies GICCOR interferometer.
shortcoming has been addressed by a variety of advanced
interferometer designs, where the motion of the mirror
is either rotary, or both mirrors m1 and m2 are made to
move in unison. Figure 8.5 illustrates two different modern
interferometer designs used for FTIR instrumentation.
Sample Cell
Compared to solid and liquid samples, IR measurements of air
samples must account for the lower density of IR absorbing
molecules in the gas phase, and the fact that the primary
constituents of air, nitrogen and oxygen, do not absorb IR
light. For this reason the optical density or absorbance per
unit length of optical beam is always much lower in gas and
vapor samples than in solids and liquids. This requires long
path length designs, for example where the beam is reflected
multiple times within a gas sample cell using mirrors.
A number of approaches have been used to increase optical
path length in a compact sample cell, including the Herriott
cell design, but the best known folded-path gas sample
cell design is the White cell.(9) Three spherical mirrors are
used in this design, as shown in Figure 8.6. The beam from
the interferometer is focused into an image at the entrance
window of the cell, which is located in an opening on mirror
m2. The beam is collected at the opposite wall of the cell by
a spherical mirror m1, which refocuses the beam onto the
mirror m2 between the entrance and exit windows. From
mirror m2 the beam diverges onto the third mirror m3 from
where the beam returns to a different spot on the mirror m2
than in the first pass. Different optical paths can be achieved
by selecting the radius of curvature and its origin for the
three mirrors, and depending on these specifics the beam
will make a certain number of passes back and forth before
focusing on the exit window of mirror m2, from where the
beam passes to the detector. Optical paths up to 10 m are
Figure 8.6 – Schematic drawing of a White cell design with folded beam
path to provide an interface for FTIR analysis of gas phase samples. Focusing
mirrors outside of the cell guide the beam from the interferometer to the cell
and from the cell to the detector.
routinely achieved in a relatively low sample cell volume of 0.5 L,
while physically bigger cells can provide path lengths >100 m.
Depending on the gas or vapor to be detected and its IR
absorptivity, concentrations down to 100 ppb or less can be
measured with a 10 m optical path length, and the use of a
folded path is critical to attain this performance in a fieldportable system.
Sample cell mirrors are typically coated with gold as it is a
material with excellent IR reflectivity and is resistant to most
chemicals. The windows in such cells are selected so that they
do not absorb the wavelengths of light being measured, and
they must also be resistant to the sampled gases and vapors.
This precludes the use of hygroscopic materials otherwise in
widespread use in many laboratory FTIR instruments, with
zinc selenide (ZnSe) and barium fluoride (BaF2) available
as possible choices. Light at wavenumbers below about
900 cm-1 is absorbed by BaF2, limiting its usefulness in
some applications, e.g. for measurement of chlorinated
organic compounds such as carbon tetrachloride. A wider
51
Important Instrumentation and Methods for Detection of Chemicals in the Field
wavenumber area is available when ZnSe is used, but due to
its high index of refraction it suffers from signal loss due to
reflectance. However when an antireflection coating is used,
ZnSe is a durable and versatile material that is often used for
gas cell windows.
An open path approach is an alternative to a closed sample
cell for detecting gas and vapor analytes and measuring their
concentrations by FTIR. In an open path system an IR beam
is transmitted through the ambient atmosphere. A bistatic
open path FTIR instrument employs an IR source kept at a
distance from the detector and interferometer, with the path
length (in the simplest case) determined by the distance
between the source and detector. A monostatic open path
FTIR instrument uses a mirror placed at a distance from the
source to reflect the IR beam back to a detector which is
located with the source and interferometer.
In addition to measuring gases and vapors with FTIR
spectroscopy using a multipass transmission cell or open
path design as explained above, it is possible to use an FTIR
instrument to measure IR absorption from solid and liquid
samples with the attenuated total reflection (ATR) technique.
As the density of IR absorbing molecules in a solid or liquid is
much higher than in the gas phase, it is not necessary to use
a long path length design (as with an instrument designed
for gas phase measurements). The ATR sample interface
occurs at the surface of a crystal material (e.g., a diamond
material which is transparent to IR radiation). The geometry
and relatively high refractive index of a reflectance element
is chosen so that the IR beam transmitted into a crystal
undergoes internal reflection and does not directly enter the
external sample (see Figure 8.7). However, a small portion of
the IR wavefront extends into the sample at the point where
the beam is reflected, and this indirect interaction with the
sample is enough to cause a measurable attenuation of the
IR beam, hence the name “attenuated total reflection.” The
use of an ATR sample interface allows for direct placement of
a liquid or solid material to be tested above the reflectance
element with no special sample preparation requirements.
This allows an operator to potentially identify sample
components present in solids, liquids or pastes at relatively
high (i.e., percent) concentrations by automated comparison
of FTIR spectra obtained with those from a reference library.
Detector
Detectors for IR fall into two main categories, thermal detectors
and semiconductor detectors, which in turn may be further
divided to photoconductive and photovoltaic detectors.
Radiation in the IR wavelengths changes the temperature of
a thermal detector and causes a measurable change in either
voltage (thermocouple type) or resistance (bolometer type)
across a detector element. The most commonly-encountered
thermal detector is the bolometer type, which is typically
known by the type of material used, such as deuterated
triglycine sulfate (DTGS) or deuterated l-alanine-doped
triglycine sulfate (DLATGS). Thermal detectors have a good
linearity of response across a wide wavelength range, but their
overall peak detectivity is lower than that of semiconductor
detectors. Also, a measurable response time is required for
a detector which relies on the temperature change in a bulk
material. For this reason the semiconductor detectors are
favored in gas and vapor analyzers capable of rapidly scanning
the IR spectrum (as fast as several scans per second).
Figure 8.7 – Close contact between a solid or liquid material and the protective coating that covers the internal reflective element of an ATR-FTIR instrument
allows absorption (attenuation) of IR light that evanesces into the sample.
52
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
Semiconductor detectors employ a junction between
two pieces of semiconductor material chosen so that the
band gap or the energy needed to jump an electron in the
semiconductor from the valence band (bound state) to the
conduction band (free state) corresponds to the energy of
the IR photons being measured. When IR light falls on such
a semiconductor, some of the electrons are raised to the
conduction band and the result is a small electrical current
which can be measured. The selection of the semiconductor
material determines the wavelength band where the
detector may be used, and a common selection is mercury
cadmium telluride (MCT), which is a mixture of HgTe and
CdTe. The bandpass frequency where the detector starts
to respond to photons can be determined by the mixing
ratio of HgTe and CdTe in the detector material. Detectors
with a higher bandpass frequency are insensitive to long
wavelength radiation but have higher peak detectivity. This
produces a trade-off between being able to measure long
wavelengths (e.g. a wideband detector) or better sensitivity
at short wavelengths (narrowband detector). See Figure 8.8
for a comparison of detectivity as a function of wavelength
for semiconductor detectors. In a semiconductor detector
random thermal motion of electrons occasionally causes
electrons to shift into the conduction band, producing
measurable thermal noise in the detector signal. For this
reason it can be beneficial to cool semiconductor detectors
to minimize this source of noise. For instruments used in
laboratories the cooling medium is typically liquid nitrogen
(-196°C). The use of cryogen is impractical for a portable field
instrument, however thermoelectric detector cooling down
to -35°C may be used in a field-portable instrument within
the constraints of available power and size limitations.
Fourier Transform IR Data Processing
After the interferogram has been recorded with the
spectrometer, it must be converted into an absorption
spectrum with the Fourier transform algorithm and
associated signal processing steps (truncation, zero filling,
filtering). The resulting spectrum must also be interpreted
in order to perform either qualitative analysis (analyte
identification) or quantitative analysis (determination of
analyte concentration). This interpretation is typically
performed using a computer integrated within the analyzer,
a handheld computing device, or with a laptop computer.
It is also possible to split the computation into two steps, so
that the interferogram is converted into an IR spectrum with
dedicated electronics inside the analyzer while the spectral
interpretation is carried out in an external computer. The
Figure 8.8 – Detector response as a function of wavelength for various IR
detectors. The detectors in question are all thermoelectrically cooled MCT
semiconductor devices differing in the mixing ratio of Mercury, Cadmium,
and Telluride. The quantity D* is specific detectivity, a figure of merit inversely
proportional to noise-equivalent power normalized to detector surface area
and bandwidth. Figure courtesy of Teledyne Judson Technologies.
following paragraphs deal solely with the analysis of the IR
spectrum, and although the Fourier transformation is an
important part of FTIR data processing, it is not discussed in
detail in this chapter and the interested reader is invited to
consult Griffiths and de Haseth(10) for more information.
Qualitative Analysis
Identification of a gas or vapor from its IR spectrum involves
comparing the spectrum produced from an unknown
sample with a library of spectra for known analytes using
one of several available library search routines. The sample
spectrum is typically corrected for baseline slope and shift
before conducting the library search, and the spectrum may
be screened so that the use of those wavelength regions with
very strong water and CO2 absorbance is avoided.
In its simplest form the library search consists of calculating
the correlation between a sample spectrum and each of the
library spectra after absorption peak heights are normalized.
The numerical correlation may be used as a quality control
parameter, as higher correlation values correspond to more
certain analyte identification. When a sample contains only
a single IR-active component for which a corresponding
library entry is available the library spectrum with the highest
correlation is the most likely identification for the unknown
analyte. However, in the case of analytes with spectra that are
not included in the library, or for samples containing mixtures
this approach would fail, and the calculated correlation to
53
Important Instrumentation and Methods for Detection of Chemicals in the Field
the closest reference spectrum found in the search would be
lower than in the case of a successful search.
This basic library search routine may be completed several
different ways, (e.g. using the correlation of first derivatives
instead of absorbance spectra), by calculation of Euclidean
distance of a sample spectrum against library spectra, or
by calculation of Mahalanobis distance between a sample
spectrum and library spectra. The specifics related to these
approaches are beyond the scope of this chapter, but in each
case the result is a search for a single library spectrum that
best fits the sample, leaving the identification of unknown
mixtures problematic. Some spectral search routines enable
subtraction of the best fitting library spectra from the sample
spectrum, so that the process can be repeated for the next
unknown in the mixture and so on. Another approach to
identifying the unknown components of mixtures makes
use of multicomponent analysis originally developed for
quantitative analysis (explained below). A multicomponent
library search starts by analyzing the unknown spectrum with
a small subset of the search library, and more spectra from
the library are added to the analysis and removed from the
analysis automatically so that the best fitting group of library
spectra is found. This type of analysis can identify several
unknown analytes from a mixture in one run at the cost of
somewhat longer searches, typically tens of seconds with a
5,000 compound search library, compared to a fraction of a
second for a simple correlation search.
Quantitative Analysis
The use of an FTIR spectrometer as a quantitative gas and
vapor analyzer relies on the integration of spectrometry with
chemometric or multivariate data handling approaches.
These techniques extract information from a measured
spectrum that can be linked directly or indirectly to the
concentrations of IR-absorbing gases and vapors in the
sample that produced the spectrum. The term “multivariate
analysis” highlights the fact that the absorbance information
at multiple wavelengths is obtained in a single measurement
and the complete spectrum is used as the input data, which is
in contrast with narrow waveband NDIR and dispersive or IR
methods.
Beer’s law
Beer’s law (also known as the Beer-Lambert law) is defined by
Equation 8-1:
54
Ai (ν)
˜ = ai (ν)
˜ b ci (8-1)
is the absorbance caused by gas or vapor i at
where
wavenumber , and ˜ is the molar absorption coefficient
or absorptivity of the same gas at the same wavenumber.
The constant b is the optical path length through the
sample cell and ci is the concentration of gas or vapor i. If
the absorbance (peak height) is not so large as to cause
nonlinearity and the absorbance is all due to a single gas or
vapor, the concentration of the gas or vapor in question can
be calculated very easily. In practice strong absorbance bands
of different analytes may overlap to varying degrees, and a
multicomponent method of assessing the absorbance due
to each gas or vapor, and the concentration of each is thus
required.
In the Beer’s law equation, absorbance A is taken from the
measured spectrum and concentration c is unknown, while
path length b is a constant determined by the hardware
used. The undefined term in the equation above is the molar
absorption coefficient, and this link is provided by a set of
reference spectra with known concentration(s) of one or
more gases/vapors in each spectrum. This set of reference
spectra is called a reference library or training set depending
on the type of analysis being performed.
Classical Least Squares Analysis
Classical least squares (CLS) analysis is based on the
assumption that the absorbance A of a gas and vapor mixture
is the sum of individual component absorbance values,
which in turn are linked to concentrations by Beer’s law. This
assumption holds true for dilute gas and vapor mixtures (for
instance, occupational hygiene-relevant concentrations of
volatile organic compounds in air), while for solid and liquid
mixtures with strong interaction between IR absorbing
molecules the assumption does not necessarily apply.
Beer’s law can be written for multiple gases and vapors
(denoted by index n) absorbing at multiple wavelengths
(denoted by the index m) in the following way, with the
parameters a and b being combined in a single parameter k:
A1 = k11C1 + k12C2 + … + k1nCn + noise
A2 = k21C1 + k22C2 + … + k2nCn + noise
(8-2)
Am = km1C1 + km2C2 + … + kmnCn + noise
The absorbance values A1 to Am in Equation 8-2 often
comprise the complete sample spectrum or at least large
sections of it (the areas with very strong water vapor and
carbon dioxide peaks would likely be excluded), and the
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
Partial least squares analysis
values for k parameters are obtained from the library of
reference spectra.
If m = n so that there are as many A values as there are
concentrations to be determined, a single solution would
exist for this group of equations if not for the noise which
is invariably present in FTIR spectra. For this reason the
number of absorbance values (data points) from the sample
spectrum always exceeds the number of concentrations
to be determined and the best solution is found by a CLS
regression. As the number of A, k, and C parameters is likely to
be large, it is more convenient to express the above equations
in matrix form:
A = K • C + residual
(8-3)
In Equation 8-3, A is a matrix vector containing the
absorbance values of the sample spectrum, K is a matrix
(n by m), and C is a matrix vector containing the unknown
concentrations. The K matrix is computed by fitting the
reference spectra against the sample spectrum so that
the residual term is minimized. Once the best values for
K are found, the above equation is easily solved for the C
values. The above equation explains why the CLS analysis is
sometimes referred to as the K-matrix method. An attractive
feature of CLS analysis is that each row of the K matrix
represents the spectrum of a pure gas or vapor in the library.
If spectra for new gases or vapors are added to the library,
there will simply be another column in the K matrix, which
does not affect other components of the matrix. This means
that a CLS method is easy to expand with the addition of
more gases and vapors, as long as there are more absorbance
data points (rows in A) than there are unknown gases
(columns in K and C).
In practice, the CLS method can be applied to 25 or more
gases and vapors simultaneously when an entire spectrum is
recorded from e.g. 900 cm-1 to 4000 cm-1, and the underlying
assumptions about additive absorbance do not cause
significant analysis errors. One of the main limitations is that
all gases and vapors absorbing in the wavelengths A must
be included in the method. If an unknown gas or vapor is
present, then the CLS regression will fail, but this results in the
spectrum of the unknown being shown in the residual. This
can be used as a starting point for identification of the gas or
vapor in question. Alternatively, the wavelengths A used for
analysis can be selected so that only the gases of interest and
a limited number of overlapping or interfering gases are likely
to be included in the model.
The partial least squares (PLS) analysis model is
mathematically more complex than the CLS analysis
model, and it is capable of interpreting samples where
the absorbance of a mixture is not the sum of component
absorptions. The PLS method was developed to counter
the limitations of CLS analysis, and it is in widespread use in
the analysis of liquid sample spectra recorded with near IR
spectrometers. The PLS method may also be applied to the
analysis of gaseous mixtures with absorbance measured in
the mid-IR spectrum.
The PLS equations are omitted from this short review, but the
key concept is that both the A and C matrices are analyzed
together to give score and loading vectors, from which the
concentrations of the unknowns are finally calculated. In
order to achieve this, a larger number of reference spectra,
usually called a training set in this context, are needed
compared to a CLS approach. These spectra are frequently
from mixtures of various gases and vapors and they can be
real sample spectra containing different gas-phase analytes
in concentrations determined by independent analysis. The
PLS models are more complex to build than CLS models, and
adding another component into a PLS model requires more
extensive changes to the library of reference spectra than for
CLS models. On the other hand, a correctly parametrized PLS
model is a robust analytical tool for complex mixtures as long
as the training set covers the range of variation in the sample
spectra which will be analyzed with the PLS model.
Capabilities and Limitations of
Fourier Transform IR Instrumentation
A correctly-selected FTIR instrument can be an ideal tool for
analysis of complex gas and vapor mixtures, or unknown
solid and liquid samples. Compared with non-IR techniques
such as gas chromatography (Chapter 9), FTIR has an
advantage in that a gas or vapor sample may be drawn
directly into a transmission cell, or a solid or liquid may
be placed on a diamond interface directly above an ATR
internal reflectance element with no need for further sample
handling or preparation. When compared with a filter IR gas
and vapor analyzer that often measures absorbance for a
pre-determined analyte using only a single wavelength band,
the capability to rapidly measure a complete IR spectrum
with medium to high resolution offers several advantages.
Molecules with very similar spectra (isomers and molecules
with identical functional groups) can be distinguished
from each other, interference from water vapor can be
55
Important Instrumentation and Methods for Detection of Chemicals in the Field
effectively minimized, and overlapping spectral peaks can
be distinguished as the FTIR spectrum contains enough data
to use sophisticated multivariate analysis methods. Lastly,
the Fellgett advantage provides both improved speed and
sensitivity compared to a filter IR method when a scan of a
number of wavelengths is needed.
An FTIR instrument does have some limitations. Gas phase
analytes exist that cannot be measured with any IR technique,
namely the elements that occur as diatomic gases: O2,
N2, hydrogen (H2), and chlorine (Cl2) for example. Also, for
solid and liquid samples, metals and inorganic salts are not
detectable. While FTIR can differentiate absorbance bands
that overlap to some degree, it cannot do so if one of the
components present in a mixture has sufficient absorbance
strength to block nearly all light in the wavenumber area
where the measurement of another analyte is to be made.
This means that in some cases a ppm-level component can
be masked by a percent-level component, especially if the
two are chemically similar. A further limitation deals with
the chemometric models used. In a CLS-based model the
library should contain all of the gases and vapors expected
to be present in the sample spectrum, and in a PLS-based
model the training set should be based on samples that are
sufficiently similar to the sample being measured. A recorded
FTIR spectrum can be post-analyzed in many cases by
modifying the method, but this may not be practical for field
analysis unless the FTIR instrument contains multiple preloaded methods which can be rapidly changed by the user.
Example Instrumentation and Case
Studies Demonstrating the use of
Field-Portable Fourier Transform IR
Analyzers
Attenuated Total Reflectance (ATR)-Fourier
Transform IR Instruments
Norman, et al. described an ATR-FTIR instrument designed for
rapid field identification of chemical compounds amenable
to IR analysis that are present in solids, powders, pastes, gels,
or liquids.(11) The currently available version of the instrument
described (Smiths Detection HazMatID™, Figure 8.9) weighs
about 10 kg. This instrument incorporates an internal path
length of 24 cm and operates in the mid-IR range (4000 to
650 cm-1). A low power diode laser is incorporated in the
design to measure the location of the moving mirror within
the interferometer, along with an electrothermally-cooled
DTGS detector providing resolution of 4 cm-1. Analysis times
56
Figure 8.9 – HazMatID™, ATR-FTIR instrument used to identify unknown
components of solid and liquid samples placed on the diamond internal
reflectance element interface (1). The sample press (2) is used to compress
solid materials to the surface of the internal reflectance element in order
to maximize the potential for the wavefront of the internally reflected IR
radiation to interact with the sample.
of 2 min are routine, and wireless communication capability
allows transmission of spectra and results to a computer at a
distance from the spectrometer. In the years since Norman et
al. described an early configuration of this instrument several
additional manufacturers have produced ATR-FTIR instruments
that are compatible with field use that were introduced in
2012, including a handheld version weighing < 2 kg.
While the ATR sample interface is primarily used for the
FTIR analysis of solid and liquid samples Bryant et al.(12) used
an ATR-FTIR spectrometer to demonstrate an FTIR analysis
approach for organic vapors that didn’t depend on a White
cell sample interface. The exterior surface of the instrument’s
diamond sample interface was coated with a thin layer of
liquid polymer sorbent to concentrate airborne nerve agent
simulants as contaminated air was moved past the coated
element. Spectral interpretation showed that the airborne
simulant compounds could be identified by their unique FTIR
spectra when absorbed into the polymer coating, and that
ATR-FTIRabsorbance was correlated with the airborne analyte
concentration.
Fourier Transform IR Instrumentation for Gas and
Vapor Analysis
The relevant characteristics for the DX4040™ FTIR instrument
(the most current version of the instruments used in the
following applications(13-15)) are described below. The 12 kg
person-portable instrument features a silicon carbide (globar)
IR source, He-Ne laser source to determine mirror position,
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
and moisture resistant ZnSe beamsplitter and windows.
The interferometer scans at a rate of 10 scans/s with a
medium resolution of 8 cm-1. This choice of scan speed and
resolution is made to reduce sensitivity to vibration, shock
and temperature change as the mirror movement is very
short and the movement is rapid. When the IR spectrum is
used for quantitative analysis, the relatively small number of
data points in the spectrum (1024) is not a disadvantage as
the number of gases or vapors to be analyzed is much smaller
(no more than 25 simultaneously) and it is desirable to keep
spectrum file size at manageable levels (about 5 kilobytes).
The White type gas and vapor sample cell provides a 9.8 m
optical path, enabling quantitative detection of sub-ppm
volatile organic compound concentrations with a cell volume
of 0.45 L and 2 L/min sample flow provided by a built-in
sample pump. This provides a short response time, typically
≤ 1 min. The materials in contact with a gas phase sample
are either polytetrafluoroethylene (PTFE) or Tygon® outside
the sample cell, and the sample cell body and mirrors are
coated with a corrosion resistant gold layer so that reactive
gases and vapors may be analyzed. The IR detector is a
thermoelectrically-cooled MCT type with response from 900
cm-1 to higher wavenumbers, giving good sensitivity over a
fairly large wavelength range. The IR signal is digitized to give
the interferogram and the interferogram is converted into an
IR spectrum using dedicated digital signal processing circuits
within the analyzer.
The IR spectra obtained may be transferred to a rugged
handheld computer through a wireless link. The handheld
computer serves as the user interface to the FTIR instrument
and it may perform CLS analysis for up to 25 components.
Several different predefined methods are stored on the
computer and the operator can quickly switch between
methods if the samples to be measured are too diverse to
be analyzed with a single method. Spectra are also stored on
the handheld device and can be transferred to a computer
running advanced analytical software for identification
of unknowns and analysis of complex gas mixtures. The
analyzer can be carried with a shoulder strap or backpackstyle harness and the interferometer can operate in any
orientation, also when carried by a moving person.
Biomedical Screening
A number of examples may be cited where portable FTIR
instruments were used to complete quantitative field
measurements for gas and vapor analytes. In 2004, Laakso et
al. described the use of a portable FTIR instrument to screen
exhaled breath of patients seen at hospital emergency rooms
in Finland.(13) The Gasmet FTIR instrument used in this study
was fully portable, with a weight of 18 kg, and was capable of
operation on battery power for up to 8 h. It employed a 200
mL multipass White cell interface, and an electrothermallycooled MCT detector. This work demonstrated the capability
for a portable FTIR instrument to rapidly provide data
that could be used either clinically, or for biomedical
research. Elevated carbon monoxide CO was detected in
the exhaled breath of most smokers, providing a method
to systematically differentiate patients who smoke from
those who do not (Figure 8.11) based on empirical noninvasive measurements that may be obtained very quickly.
The quantitative data provided by these researchers also
showed that relatively high methane (CH4) concentration in
exhaled breath correlated with increasing age. In addition to
the ethanol concentrations measured in the exhaled breath
of numerous patients who had consumed alcohol (which
can be correlated to blood concentration), methyl ethyl
ketone was also detected in the breath of a patient who had
apparently consumed alcohol that had been denatured with
this compound.
Measurement of Anthropogenic Influence on
Atmospheric Gases
Figure 8.10 – Gasmet DX4040™ person-portable FTIR instrument in use for
identification of unknown gas-phase analytes in the field.
In 2008, Guérin et al. studied the impact of reservoir
construction in tropical regions on the net emission of
nitrous oxide (N­2O) compared to natural “pre-flooding” N2O
emission rates. This information was desired as N2O is known
to have greenhouse gas properties. These researchers used a
plastic chamber floating on the surface of reservoirs located
in a tropical region to collect gases emitted from the water.
57
Important Instrumentation and Methods for Detection of Chemicals in the Field
two open path monostatic FTIR instruments to sequentially
scan eight retroreflectors positioned around an area where
sulfur hexafluoride (SF6) had been released.(16) Approximately
sixteen open path measurements were obtained every
five minutes, and the spectral data were processed using
tomographic reconstruction software to create twenty five
sequential two-dimensional concentration maps.
Conclusion
Figure 8.11 – Relative frequency polygons for exhaled carbon monoxide
concentrations of nonsmokers (shaded area, n = 363) and smokers (no
shading, n = 207). The y-axis values represent the proportion of patients in
each 0.5-ppm (nonsmokers) or 4-ppm (smokers) interval. From Laakso et
al.,(13) copyright Oxford Journals, used with permission.
On-site analysis of the chamber gases to determine N2O
and CH4 concentrations was completed using a portable
FTIR instrument similar to that described by Laakso et al.
immediately above. Measurements at the air/soil interface
in the same region completed with the same instrument
(by using a stainless steel gas collection chamber in contact
with soil) allowed the researchers to estimate the change in
N2O emission with construction of the reservoirs, relative to
emission from undisturbed soil in the same region.(14)
Building Air Quality
Teye and Hautala used a similar field-portable FTIR
instrument with a gas cell interface to measure airborne
ammonia (NH3), CH4, CO2, and water vapor concentrations
in a dairy building. The primary purpose of this part of their
study was to quantitatively measure NH3 emissions as “high
ammonia concentrations in animal buildings are known to
affect the welfare of animals, workers, and the life span of the
building.”(15)
Concentration Mapping
Where dangerous chemicals are routinely handled with the
possibility for unintentional release to the open atmosphere,
concentration mapping could provide important information
to emergency responders and civil authorities. However, for
emergency situations where this type of instrumentation
was not already set up, little would be known initially about
potentially dangerous atmosphere conditions and technicians
could be exposed to unknown hazards in order to set up such
a system. In order to demonstrate the potential to obtain
2-dimensional concentration plots for airborne gases or vapors
amenable to FTIR detection, Todd simultaneously operated
58
Person-portable FTIR instruments have become widely
available in the recent past, and have seen use in many
applications. These portable FTIR spectroscopy instruments
are available in configurations to identify unknown chemicals
in liquid and solid samples (ATR-FTIR instruments) and to
identify unknowns and measure organic and inorganic gas
and vapor concentrations (FTIR instruments employing a gas
cell interface). The primary strengths of FTIR are the ability
to adapt to a wide range of measurement tasks by simply
changing the spectral library and analysis settings on a
computer, and the ability to operate without carrier gases or
calibration reference materials.
When an FTIR instrument is operated for identification of
unknown gases or vapors spectral library matching may
provide the identity of the most prominent component in
the sample (but not necessarily its concentration). When used
for quantitative measurements it is possible to accurately
determine concentrations for multiple gases and vapors in
the ppm concentration range. The two modes of operation
can be combined in a single instrument with the quantitative
analysis relying on a chemometric model that includes data
for substances of interest, against which the sample is to be
compared. The recorded IR spectra are saved together with
the analysis results, which makes it possible to verify the
analysis results later and to recover data from measurements
where the sample contains gases or vapors that were not
initially included in the instrument library.
Due to continued development efforts handheld ATR-FTIR
instruments are now available to support military chemical
detection and identification missions, and civilian hazardous
material incident responders. In comparison to well-known
filter IR instruments designed to measure airborne gas and
vapor hazards FTIR instrumentation has greatly expanded
the capabilities for rapid identification of airborne hazards.
Both types of FTIR instrumentation may provide high quality
information in the field to exposure assessment professionals,
improving our ability to protect workers and the general
public.
Chapter 8 — Field-Portable Fourier Transform Infrared (FTIR) Spectroscopy for Gas and Vapor Analysis
References
1. Michelson, A.A.: On the application of interferencemethods to spectroscopic measurements, I. Philos. Mag.
31:338–46 (1891).
2. Michelson, A.A.: On the application of interferencemethods to spectroscopic measurements, II. Philos. Mag.
34:280–99 (1892).
3. Ferraro, J.R.: History of Fourier transform-infrared
spectroscopy, Spectroscopy 14:28–40 (1999).
4. Michelson, A.A.: Recent advances in spectroscopy. Nobel
lecture, December 12, 1907.
5. Rayleigh, L.: On the interference bands of approximately
homogeneous light: in a letter to Prof. A. Michelson.
Philos. Mag. 34:407–11 (1892).
attending emergency departments. J. Anal. Toxicol.
28:111–17 (2004).
14. Guerin, F., G. Abril, A. Tremblay, and R.
Delmas: Nitrous oxide emissions from tropical
hydroelectric reservoirs. Geophys. Res. Lett. 35:L06404,
doi:10.1029/2007GL033057 (2008).
15. Teye, F.K. and M. Hautala: A comparative assessment
of four methods for estimating ammonia emissions
at microclimatic locations in a dairy building. Int. J.
Biometeorol. 54:63-74 (2010).
16. Todd, L.A.: Mapping the air in real-time to visualize
the flow of gases and vapors: occupational and
environmental applications. Appl. Occup. Environ. Hyg.
15:106–13 (2000).
6. Cooley, J.W. and J.W. Tukey: An algorithm for the
machine calculation of complex Fourier series. Math.
Comput. 19:297–301 (1965).
7. White, R.L., P.J. Coffey, and D.R. Mattson: High
performance FTIR using a corner cube interferometer.
Am. Lab. 15:90–93 (1983).
8. Levine, S.P., Y. Li-Shi, C. Strang, and X. Hong-Kui:
Advantages and disadvantages in the use of Fourier
transform infrared (FTIR) and filter infrared (FIR)
spectrometers for monitoring airborne gases and vapors
of industrial hygiene concern. Appl. Ind. Hyg. 4:180–87
(1989).
From: “Important Instrumentation and Methods
for the Detection of Chemicals in the Field”.
Chapter 8 on FTIR Gas Measurement by the real
time detection chapter of the AIHA
ISBN-13: 978-1-935082-41-5
9. White, J.U.: Long optical paths of large aperture. J. Opt.
Soc. Am. 32:285–88 (1942).
10. Griffiths, P.R. and J.A. de Haseth: Fourier Transform
Infrared Spectrometry, 2nd edition. Hoboken, NJ: John
Wiley and Sons, Inc., 1986.
11. Norman, M.L., A.M. Gagnon, J.A. Reffner, D.W.
Schiering, and J.D. Allen: An FT-IR point sensor for
identifying chemical WMD and hazardous materials. SPIE
Proc. Ser. 5269:143–49 (2004).
12. Bryant, C.K., P.T. LaPuma, G.L. Hook, and E.J. Houser:
Chemical agent identification by field-based attenuated
total reflectance infrared detection and solid-phase
microextraction. Anal. Chem. 79:2334–40 (2007).
13. Laakso, O., M. Haapala, T. Kuitunen, and J.-J.
Himberg: Screening of exhaled breath by low-resolution
multicomponent FT-IR spectrometry in patients
ETA Process Instrumentation
119 Foster Street, Bldg #6
Peabody, MA 01960
Tel: (978) 532-1330
Fax: (978) 532-7325
w ww . e t a p i i . c o m
sales@etapii.com
59