1 Document Prepared for the US EPA by:

UNISEARCH Associates Inc.

CEMTEK Environmental

June 2012



### UNISEARCH ASSOCIATES INC.

www.unisearch

- associates.com

CEMTEK ENVIRONMENTAL

www.cemteks.com 

# TDL Performance Specification

Notes for In

- situ HCl Monitoring2 

### Table of Contents

A. Introduction

................................ ................................ ................................ ........................ 3

B

. Detection Limit and Identification of Gasses by NIR Spectroscop y

............................. 3

B .1 Detection Limit Description

................................ ................................ .................. 3

B .2 HCl Minimum Detectio n Limits Determined in the Lab u nder Simulated

Flue Gas Conditions

................................ ................................ .............................. 4

B .3 NH 3 Minimum Detection Limits determined in the Lab under Simulated Flue

Gas Conditions as Well as in the Field

................................ ................................ 6

C

. Background Subtraction and Zeroing Considerations in TDLAS Spectroscopy

................................ ................................ ................................ ...................... 8

C .1 Background Subtraction

................................ ................................ ....................... 8

C .2 TDL Laboratory Evaluation fo r Measurement of HCl

................................ .... 10

C .3 Curve fitting Techniques for IR Spectroscopy

................................ .................. 11

C .4 In

- situ zeroing of TDLAS for Direct Absorption Measurements

.................... 15

C

. 5 Determination of In

- situ Minimum Detection Limits

................................ ....... 18

D

. In

- situ SPAN Checks for NIR TDLAS Spectroscopy

................................ .................. 23

D .1 In

- situ Span Checks

................................ ................................ ............................. 23

D .2 Audit Cell Verification

................................ ................................ ........................ 24

E

. References

................................ ................................ ................................ ......................... 2 63 

### A



## . Introduction

This report is intended to address the technical issues posed by Ray Merrill and his team from

recent stakeholder conference call s conducted by the USEPA . This elaboration of the original

comments made b y Cemtek and Unisearch Associates is to augment the draft performance speciation for HCl CEMS. At issue is how do I ntegrated P ath ( IP ) Continuous Emission

Measurements ( CEMs ) perform a span and zero drift check in an in

- situ measurement mode.

S ince there will be no practical way to remove or be certain th at HCl gas i s not present in the in

situ measurement path the zero and span of the system need to be addressed differently. For the span, a spike t est with certified gas through an inline cell can be used to verify the measurement range of the system. T o obtain a measurement system zero

, Unisearch has developed a method that we believe will meet the intent of the performance specification for evalua ting zero drift. This method uses generally accepted curve fit techniques that are primarily used in FTIR and proprietary algorithms. The basis for these techniques is presented here for your evaluation. Another issue posed in the same stakeholder discussi on was how we would conduct a field determination of the Limit of Detection (LOD). Using this zero check method developed and subsequently described here and then by taking replicates of zero checks , the zero numbers can be used to establish the LOD.



### B. Dete ction limit and identification of gases by NIR TDLAS Spectroscopy

B .1 Detection Limit Description:

According to the accepted convention the limit of detection (LOD) is the lowest analyte concentration that is significantly different from the blank which is a known sample that does not have any of the analyte (basically zero).

The signal intensity (y

D ) corresponding to the detection limit represents the size of the signal that is equivalent to the blank value.

The signal is determined by the mean valu e **μ** B and the standard deviation 

### σ b of a blank signal described in equation (1)

, (Grant et al, 1992)

y D = **μ** B + K D **σ** b (1)

where K

D = 3.

Because the values 

### μ B and 

### σ b are not known, their estimates are used, i.e. the average blank value



### ‹ y b 

### › and the corresponding standard deviation s b

.

Although the LOD is defined in the signal domain, the main objective in trace analysis is to obtain a concentration value of LOD, [C] D

.4 Because the values of the signal are to be corrected for the blank/zero experiment, the corrected linear calibration dependence should theoretically pass through zero. Thus the uncorrected
dependence provides on the signal axis the value of the intercept 

### μ B , estimated as y b

.

Then the usual method of obtaining concentration [C] D is based on the use of equation:

[C] D = ( (y

D )

- 

### ‹ y b x 

### › )b 1 (2)

If we substitute into equation (2) equation (1) given above, with the replaced values of 

### μ B and



### σ b , we obtain for the concentration detection limit the following relationship

[C] D = 3s b /b 1 (3)

Where

s b is the standard deviation

b 1 is the slope of the calibration curve, analytically identified as sensitivity.

The estimate of the standard deviation is possible by the analysis of repeated measurements of the blank/zero experiments.

This approach was adopted to evaluate the limit of detection for ne ar infrared tunable diode laser spectroscopy (NIR TDLAS) at lab oratories at the University of California at Riverside (UCR) under The Electric Power Research (EPRI) funding for HCl and NH 3 . (Dene et al., Himes et al.)

A blank signal was obtained by introducing zero gas with equivalent moisture levels as well as possi ble interfering gasses (CO 2 , NO, SO 2 ) expected in typical flue gasses known at coal

- fired power plants at temperatures typical of flue gas exhaust.

The true detection limit then is evaluated as possible interferences from flue gas constituents as

well as any thermal bias was accounted for by simulating conditions expected in the sampling

environment.

Linearity checks were also done on the instrument response to evaluate the intercept.

B 2

. HCl Minimum Detectio n Limits determined in the Lab u nder Simulated Flue Gas

Conditions

The University of California at Riverside has built a laboratory specifically designed to evaluate spectroscopic techniques and instrumentation typically used for the measurement of trace gases emitted in combustion processes. This h as been funded by EPRI ; for a complete description of the laboratory as it pertains to HCl please refer to EPRI publication (Dene et al., EPRI, Palo Alto, CA: 2011 1022083)

.5 For HCl the evaluation of minimum detection limits accounted for possible biases f rom interference gasses listed on table 1 as well as moisture (8%) and temperature.

Table 1 : Interference testing gas concentrations

Interference NO= 1510 ppmV
Testing CO= 1220 ppmV

Gas CO2=11.9%

Concentrations SO2=2050 ppmV
NH3=100ppmV

The Unisearch S

- series LasIR SM410 instrument was tested.

Linearity is expressed in terms of slope, intercept, and coefficient of determination (R 2 ) and is shown in figure 1.

Figure 1

Linear Regression, of the measured response, from the Unisearch S Series LasIR SM410 as compared to the source calibration value. The measured responses are averaged from

all 10 tests at each source calibration value that encompassed the range of moistures and temperatures used in this evaluation.6 Since the system was linear and the intercept was 0.0261 and the response to zero gas combined with all the possible interfering gasses wi th moisture at thermal levels typical of coal

- fired flue gasses the minimum detection limit is reported at three times the average standard deviation of

all the one

- minute zero measurements made at each of the temperatures used in the evaluation

when the i nstrument was evaluated over the entire range of tests and b 1 is 1.

The three temperatures were 25 oC (1 set of measurements, 15 points), 100 oC (3 sets of measurements, 45 points) and 200 oC (6 set s of measurements, 90 points).

T he numbers are reported in ppmV

- meter, and are also shown with a 5 meter path, typical to power plant installations as detection limits were found to improve with longer path lengths.

Table 2 : HCl MDL’s as a Function of Temperature

Temperature Minimum Minimum

Detection Detection

Limit Limit

D egrees °C 5

- meters
ppmV

- m ppmV

25 0.35 0.07

100 0.66 0.13

200 1.10 0.22

To evaluate minimum detection limits in the field for HCl would require a stable blank, either knowing that there is no HCl present or a value of HCl very low near the laboratory determined

MDL so we could establish an average value for y b.

B .3 NH 3 Minim um Detection Limits determined in the Lab under Simulated Flue Gas

Conditions as Well as in the field

Prior to the HCl tests, similar tests were done on 6 TDLAS instruments from various

manufacturers for NH 3

.

The goal was to determine minimum detection limits, instrument response; tests were also done

in the field.

Refer to EPRI publications for results of these tests (Himes et al.).

The goal of these instruments is to measure as accurately as possible from 0.5 to 20 ppmV NH 3 slip as observed from post SNCR (Selective non

- catalytic) or SCR (selective catalytic) NOx reduction processes.7 The test done in the field was to measure the NH 3 blank response when no urea or NH 3 was injected into the SNCR or SCR.

Field measurements corroborated the laboratory es timates of the minimum detection limits.

Typical results for a similar Unisearch instrument configured for NH 3 instead of HCl were also at 3 times the standard deviation and are listed as a function of temperature in table 3.

Table 2 : NH 3 MDL’s as a Function of Temperature

Temperature Minimum Minimum

Detection Detection

Limit Limit

D egrees ° C 10

- meters

ppmV

- m ppmV

20 2.12 0.21

200 2.56 0.26

300 2.78 0.28

400 3.33 0.33



### C. Background Subtraction and Zeroing Considerations in TDLAS Spectroscopy

C .1 Background Subtraction

The objective of background subtraction is to remove a constant offset from the signal which may include an underlying spectral feature that may bias the measured signal. It is critical when doing background subtraction that in this process, we want to be consistent in our approach and be accurate in our methodology so as to avoid altering the true character of the measured

spectrum.8 There are three modes when considering the backgrounds observed in TDLAS: They are:

1. Empirical backgrounds which arise wit h no consideration to the theoretical rational behind them. Few if any background shapes used in TDLAS are purely empirical in

nature.

2. Semi

- empirical backgrounds arise from some consideration of the underlying principles that give rise to a background sign al in the spectrum.

3. Analytical backgrounds arise from direct consideration of the underlying principles that give rise to a background signal in the spectrum and measure the background when a zero or null is present in the signal path.

One of the first c onsiderations is to determine the range over which the background will be fit.

1. The Entire Spectrum: This is the usual choice when we have only one feature of interest (a peak) in the entire spectrum.

2. A Portion of the Spectrum This choice is made because w e have a) multiple features in the spectrum, b) abrupt changes in background shape, or c) both

At the endpoints (where the background meets the data), we will typically want to decide whether to have the background match the values of the data points exac tly or be the expected value of the signal at those points

For any data outside of the chosen range, we will typically want to decide whether to

1. Use the raw data values

2. Set everything to a pre

- determined value

3. Extrapolate the behavior of the background

The background shape will typically be determined by

1. How easy it is to apply

2. How close it is to theoretical principles

3. How it compares to observed backgrounds during null or zero target gas present in the signal path.

A typical algorithm for background subtraction might be

1. Determine the range 2. Determine the shape 3. Determine the endpoint values 4. Apply the background 5. Consider whether your choices were suitable

Background subtraction can be an iterative process.9 A constant background removes a constant value from the spectrum in the selected range. This is typically the standard approach with the background taken during a period of null or zero target gas in the path. This background typically arises from optical noise inherent to the laser based system which accounts for the following:

1) Laser based noise, typically very low 2) Optical noise from optical components as beam splitter, multiplexers, lenses, mirrors or other optical components that are in the signal path 3) Optical etalons which are si nusoidal in nature and are typically caused by transmission of the optical beam through lenses 4) Electrical noise which may be present from the detector back to the instrument

The major advantage for this is that all spectra typically have a constant underl ying offset in the signal throughout their range and this technique is relatively easy to apply. The major disadvantage is that in many optical systems this is not always the end of the story and further background subtraction may be needed over time if t he background deviates.

So we have discussed background subtraction as a way to determine the null or zero response of

the instrument.

The major advantages to the TDLAS technique are:

1) That we are observing a signal response over a very narrow band (typi cally a few tenths

of a nm or less). 2) So making the assumption that where the backgrounds meet the signal on both sides of the response is fairly constant can be measured and evaluated and has merit as the bandwidth of the response is so narrow. 3) Backgrounds are typically linear, this alludes to the background over the narrow range from points prior to where the measured signal is to points past the measured signal can be predicted absorption range mathematically. 4) Scanning the entire absorption fea ture leads to being able to measure the background response to where the point of signal as well as the range point 5) The TDLAS technique is very fast, typically thousands of scans of the total response a second, so perturbations in the region where there i s no target gas response can clearly

be detected 6) The TDLAS technique scans the entire absorption feature as well as significant portions prior to and after the absorption feature. 7) Taking a background with the majority of TDLAS instruments is a relatively s imple

process. 8) Spectral analysis techniques developed primary for FTIR analysis can determine residual values that can be used to minimize spectral interferences from other gasses, as well as a methodology to deal with multiple lines of absorption of the s ame target gas. Such analysis can similarly be applied to TDALS spectroscopy, but since it is a single line it basically will observe the residual as a background to the measured signal and by10 subtracting this residual will improving the zeroing of the me asurement and subsequently enhance the minimum detection limits.

C .2 TDL Laboratory Evaluation for Measurement of HCl

Work has been completed for the evaluation of TDLAS measurements of HCl, basically with methodology concurrent to extractive sampling. In this testing an inert (Teflon lined 1 meter sample cell) was used to investigate the primary response of the TDL instrument to HCl in environments that simulated coal fired power plants flue gasses. The funding of this work was through EPRI (Contact: Ch uck Dene, Principal Investigator and Project Manager, 650

- 855

- 2425) at a laboratory specifically constructed to test spectroscopic techniques at the University of California at Riverside (Contact: John Pisano, Senior Research Engineer, 951

- 660

- 0585). An

EP RI report describing all these tests and results was published and is available, the EPRI report

and number is: A Continuous Emission Monitor For Hydrochloric Acid: Tunable Diode Laser Test Report, Unisearch LasIR S Series . EPRI, Palo Alto, CA: 2011 102208 3, December 2011. Chuck Dene of EPRI is currently working with the legal department of EPRI to provide this document to EPA in support of this performance specification.

The instrument was tested for the following:

**•** Zero response

**•** Minimum detection limits

**•** Z ero drift

**•** Linearity

**•** Precision

**•** Accuracy

**•** Possible interferences to known power plant flue gasses, as NO, SO 2 , CO, CO 2 , H 2 O and

NH 3

.

Tests were conducted over a range of temperatures known to exist at typical coal fired power plant flue gas sampling locations for CEMS applications.

The overall testing clearly showed that the TDL technique is viable for low level, non

- interfered measurements of HCl, in power plant applications of typical flue gasses for CEMS applications, but these tests were done in a sample cell.

The major advantage to the TDL technique is because it is an extremely narrow wavelength measuring technique in the near infrared, at wavelengths that are typically used for optical communication; it is easy to make a system that can measure the flue gas in

- situ . However this opens up complexities on how to verify zero and span when the instrument is measuring in a cross duct configuration and not extractive into a sampling cell.

An examination the TDL technique for coal fired power plant applications follows. TDLAS (Tunable diode laser spectroscopy) makes use of very narrow wavelength measurements and was11 shown not to respond to the major known other gasses in the flue stream, this is significantly different than FTIR or NDIR which being broadband techniques are known to be affected by these other gasses, and must inherently be corrected for perturbations caused by response to these possible interfering gasses.

It is our opinion that these technique s should be zeroed with gasses that are representative of actual flue gas constituents, especially at least H 2 O which has such a strong and wide infrared signature.

C .3 Curve fitting Techniques for IR Spectroscopy

Curve

- fitting methods yield significant information of complex spectra provided that the bands measured in the system can be isolated (FTIR technique), or there are single line measurements, which is the case for HCl, used in this TDL approach.

Typically for FTIR analysis there are a number of bands and their positions can be accurately determined by fitting a highly deconvoluted spectrum

. The procedure for FTIR used is in effect:

1. Fourier self

- deconvolution of the experimental spectrum after base line correction,

2. Curve fitting of the (highly) deconvoluted spectrum,

3. Curve fitting of the original spectrum using the data set obtained from the previous

step,

4. Check for similarity between the deconvoluted fitted and deconvoluted experimental spectrum using the similar parameters.12 Figure 2

Show the Hi Tran Database Spectra, for HCl, in the 5500 to 6000 cm - 1 NIR spectral r ange , showing discrete absorption lines.

This technique results in minimizing the residuals which are primarily from the effect of having possible interfering gasses as well as l ooking at multiple lines, however in the TDL case if there are no interfering gasses and it is a single line measurement, th e n the residual is primarily noise from the detector, or optical noise which may include laser noise, etalon fringing from optical

e lements or other noise generating effects from inlin e optical elements as multiplexe rs, beam splitters lenses and mirrors.

As previously discussed, FTIR analysis requires the incorporation of curve fitting routines to minimize residuals that are likely fr o m interfering gasses as well as having a spectral response of the target gas that incorporates many absorption lines.

In spectroscopy , the Voigt profile is a line profile resulting from the convolution of two broadening mechanisms, one of which alone would produce a Gaussian profile (usually, as a

result of the Doppler broadening ), and the other would produce a Lorentzian profile. Voigt profiles are common in many branches of spectroscopy

All normalized line profiles can be considered to be probability distributions . The Gaussian profile is equivalent to a Gaussian or normal distribution and a Lorentzian profile is equivalent to

a Lorentz or Cauchy distribution

.13 Without loss of generality, we can consider only centered profiles which peak at zero. The Voig t profile is then a convolution of a Lorentz profile and a Gaussian profile:

(4)

where x is frequency from line center, is the centered Gaussian profile:

(5)

and is the centered Lorentzian profile:

(6)

The defining integral can be evaluated as:

(7)

where Re[ w(z) ] is the real part of the complex error function of z and

(8)

Figure 3 shows the difference between a Gaussian, a Lorentzian and a Voigt profile using the

same values for Y 0 , x 0 and Δx (linewidth) ( Bradley, TECO App. Note 50733) . The sharper maximum and long wings of the Lorentzian are clearly seen. Typically the Lorentzian profile works best for gases, The Voigt profile is similar to the G

- L, except that the line width Δx of the Gaussian and Lorentzian parts are allowed to vary independently.14 Figure 3 Show the difference between a Gaussian, a Lorentzian and a Voigt profile, using the same

values for Y 0 , x 0 and Δx (linewidth).

Figure 4 shows the influence of altering the percent Lorentzian character of a G

- L profile, leaving everything else unchanged. The wings grow with A, and the line narrows near the top. ( Bradley, TECO App. Note 50733 ).

So these curve fitting routines minimi zing the residual, similar to that used in FTIR analysis, can easily be applied to TDLAS as long as the signal analyzed is a direct absorption signal.

Many TDL instruments look at derivative spectroscopy, employing modulation techniques as wavelength mod ulation (WMS) or two tone FM modulation (TTFM), which improve signal to noise but would obviate the use of this curve fitting technique.15 Figure 4 Shows the influence of altering the percent Lorentzian character of a G

- L profile, leaving everything else unchanged.

By applying these curve fitting techniques to a direct absorption TDL measurement, it is possible to approximate zero even if there is always some HCl present in the flue gas, which leads to a way to do in

- situ zeroing as well as estimation of the minimum detection limits from the data recorded during the in

- situ zeroing.

C .4 In

- situ zeroing of TDLAS for Direct Absorption Measurements

I n the case of a direct absorption TDL measurement the following can alter the zero response:

**•** Interfering ga sses, but the TDL response has been shown to be unaffected by the other gasses in the coal

- fired power plant stream

**•** Optical noise type 1, as etalons, which are inherently periodic. Such noise is fairly consistent to wavelengths just prior to the HCl absorp tion, through the HCl absorption and just past the HCl absorption. Therefore looking at the signal just prior and just after the HCl wavelength should approximate a background which can be subtracted from the whole spectrum, and yield a close approximation to zero.

**•** Optical noise type 2, as from the laser itself and the optical elements in the system, this noise is consistent from measurement to measurement, as the laser conditions are the same as are the physical properties of the optical elements including their location within the optical stream.

**•** Electrical noise, basically the detector itself and coaxial return line, however we know that the detector response is fairly flat over the narrow band that we are measuring at so16 looking at noise prior to the HCl absorption and after should also be consistent from the detector at the peak HCl absorption wavelength.

Spectroscopy can be defined as the investigation of the interaction that occurs between a defined source of electromagnetic radiation with a target sam ple. The way the emissive properties of the radiant source, usually some sort of light emitter, are perturbed depends upon the sample investigated. For example, molecules of gas can absorb electromagnetic radiation leading to

molecular vibrations or rotati ons, with the frequencies that are absorbed by quantum theory being unique to each different type of molecule in the target sample. Therefore each molecule has its own characteristic absorption pattern over the electromagnetic spectrum.

Spectroscopic meth ods basically evaluate the concentration of the molecule investigated through

Beer

- Lambert’s Law, which states that the fraction of light intensity transmitted through a gas is given by:

I(λ)/Io(λ) = exp (

- φ(λ))NL) (9)

Where I and I o are the transmitted and incident powers respectively, L is the absorption path length (cm), and N would then be the concentration of the absorbing molecules in number of molecules per cubic centimeter. In this example φ(λ) is the wavenumber dependent absorption cross section in square centimeters per molecule.

For direct absorption measurements, equation (9) is solved directly

Tunable diode laser spectroscopy tunes the laser by locking the temperature of the laser and changes the emission wavelength by changing the current in small discrete steps (current ramp) y(I), that permit scanning the absorption feature prior to the absorption, into the absorption and after the absorption. In this manner the whole absorption feature is scanned. Si nce the laser output power changes as well as the emission wavelength with the current ramp, this requires that a function be applied to normalize the I

o (λ) over the whole tuning range during each individual ramp cycle. This is achieved by fitting a polyn omial f(λ) using a standard Least Squares Fit. This polynomial, however, will only fit for the I 0 background of the laser, and to achieve a better fit when there is target gas present, ensuring the I(λ), measured in solving the

beer

- lambert law (equation 9) is normalized over the ramp scan cycle, both a polynomial for I 0 and the Lorentzian component of the Voigt profile, are employed to generate a better fit. In this manner when solving the beer

- lambert law we are employing a best fit for I(λ) (which requi res the polynomial and Lorentzian) fit to I

o (λ) (which has just the polynomial fit). The full mathematics showing how this is done is proprietary at this time but to elaborate, the relationship y(I)/f(λ) is minimized which results that the data is normali zed for I

o (λ). Subsequently the measured response I(λ) is then fit with the same polynomial and the Lorentzian function to yield comparable results used in the solving of the beer

- lambert equation. What is significant from this is the residual component o ver the region where there is no target gas absorption is similar in both size and nature to the region where there would be target absorption.17 Basically by monitoring the residual as a function of wavelength R i (λ) and subtracting this from

the next resi dual measured R i+1 (λ) which is currently done as with each scan a residual is obtained, than this previous residual can be removed from the next scan and values can be calculated from this. By removing the previous residual from the current spectrum after the values have been calculated, systemic errors that are introduced by keeping a running average of the perceived background are prevented. This in effect leads to having a zero measurement for each scan which is just a subtraction of the measured residu als. This has been shown to be similar whether there is HCl present or not, simply by comparing residuals when there is no HCl (true zero) to when there is HCl (residual over the range where there is no HCl absorption only).

Since the major source of noi se which can bias the zero is optical noise, and this tends to be more random, and is a sum of differing sine waves, th e n the source of any perturbation of zero will be minimized by looking at these residuals.

Applying the t esting to establish how close the residuals from background subtraction of the observed response at nominal values of HCl for a typical measurement path in a power plant compares to having a sample with zero HCl only have been performed and are shown in fi gure 5

. If anything when there is indeed signal present the residuals are smaller. This is likely an artifact of the fitting routine but does indicate that the residuals may be employed as a measure of the background variation due to optical and electronic components of the noise. Results have shown an enhanced minimum detection limit as defined in section A of this report.18 Figure 5 Shows the case of applying the residual determination using the described technique and how close the residuals from backg round subtraction of the observed response at nominal values of HCl for a typical measurement path in a power plant compares to having a sample with zero HCl only

.

C

. 5 Determination of In

- situ Minimum Detection Limits

As discussed in section B1, the lim it of detection we obtain for the concentration detection limit

has the following relationship

[C] D = 3s b /b 1 ( 10 )

Where

s b is the standard deviation19 b 1 is the slope of the calibration curve, analytically identified as sensitivity.

The estimate of the standard deviation is possible by the analysis of repeated measurements of the blank/zero experiments.

For the way described to measure the zero in

- situ , this approach was adopted to evaluate the

limit of detection for near infrared tunable diode la ser spectroscopy (NIR TDLAS) but not just for zero values of HCl but over the range of expected HCl concentrations. In this way we can present results of zero with and without HCl present, noting how they compare and in summation yield minimum detection limits. This is the only w ay to validate whether in

- situ zeroing as described achieves consistent levels whether HCl is present or not.

The experimental proce dure was to inject standard calibration gas through a dilution system into a sample cell to generate four levels of HCl gas as listed in Table 3 below. The temperature was

ambient 25°C into a 3

- meter sample cell.

Table 3 : HCl Levels Chosen for In

- situ Z eroing Analysis

HCl HCl measured Reason for

generated measured level chosen

(ppmV) (ppmV)

0.0 -0.03 Zero

0.4 0.39 Low Level

3.8 3.77 Mid-level

15.0 14.97 High Level

F our values, 0.0 ppmV (zero gas), 0.4 ppmV (approximating low level measurements observed at a power plant site), 3.8 ppmV (approximating high levels observed at a power plant site), and 15 ppm V (approximating the high end of the range of measurements used to verify calibration at a power plant site) were selected to do the evaluation.

Figure 6 shows the measurement of the 15 ppmV value along with the residual measured concurrently at the 15 pp mV value, so in effect it shows the instrument response to 15 ppmV of HCl in the sample cell and the residual value after doing the curve fitting described in C4.

Looking at the plots, the blue spectra represent s the measured H C l spectrum on the lef t side, and

on the righ t shows the residual of the measured spectra after doing the curve fitting routine.

As can be seen we see a strong response to the 15 ppmV sample cell value, measured to be 14.97

ppm V , the correlation coefficient R, which is how clo se the measured sample fits via a least squares analysis over the entire measured response to that of the reference (which is in red) is 1.00 indicating a virtually perfect fit. Also indicated is the full width height maximum, FWHM,20 of the measured spectr um for HCl (7.81 in this case). Also note the parameters for the reference signal in red, are also listed for each measurement. The reference cell has a known amount of HCl to yield an average ppmV level, it is concurrently measured with the signal as a check, this is easily done in a fiber coupled system as the laser output is beam split 5% to the reference and 95% to the signal path. The reference parameters are laser temperature 26.705

- 26.709 °C, laser

current 66.958

- 66.966 mA, reference cell value (t he reference has a known value of HCl and is always cross checked concurrently with the measured signal) 8.96 to 8.98 ppmV

. The slight differences in the reference parameters shown are that the residual shown included the previous

measurement of the resid ual to the measured signal, basically if the sampling interval is 1 second, then when the signal is measured at time (t 1 ), then the residual shown would be at time t 1 as well but includes the subtracting of the residual at time t 1

- i where i is the sampling interval. The parameters listed then include the average of both in that short interval on the right side.

Figure 6 Shows the case of applying the residual determination using the described technique and comparing it to a real

- time measurement of HCl. The concentration for this case of HCl is at the high end , being approximately 15 ppmV.

The residual value is not shown on the display, only the HCl measured in the sample cell is shown, but the residual is recorded in the software.

For this measurement the residual was measured to be 0

. 017 ppmv.

Figure 7 shows typical residual plots for all concentrations used in this analysis, again the blue numbers indicate the measured concentration observed and do not list the residual values, but these are stored in the data. As can be observed in the plots the magnitude and form of the residuals are very similar independent of the amount of HCl that is present, the standard zero measurement (top left, with zero air injected) was of the same order as the residual Measured 14.97 ppmV signal (blue) Measured 0.017 ppmV residual (blue) Measured

reference 8.96 ppmv (red) Measured

reference 8.98 ppmv (red)21 measurements taken when HCl was present , (top right 0.4 ppmV, bottom left 3.8 ppmV and bottom right 15 ppmV). This proves a strong argument that by looking at the residual for these very narrow single line TDL direct absorption measurements, zeroes can be evaluated independently of the amount of HCl within the prescribed dynamic range of the system.

Figure 7 Shows the case of applying the residual determination using the described technique and comparing it to a real

- time measurement of HCl , over the four levels of HCl chosen, these being the standard zero measurement (top left, with zero air injected) 0.4 ppmV

H Cl (top right), 3.8 ppmV HCl ( bottom left) and 15 ppmV HCl (bottom right).22 Since most power plant applications require 1

- minute averages, two tests are included in this

report.

The first shows o ne

- minute averages for each of the four levels of HCl chosen to investigate for

one

- hour periods, an example of this test for the 0

. 4 ppmV is included in figure 8. From the data compiled from these tests, with 60 one

- minute samples, table 4 was generated. The second shows normal zero drift data taken during the EPRI evaluation which was for ten tests over a

one

- week period.

Figure 8 Shows the case of applying the residual determination using the described technique and comparing it to a real

- time measurement of HCl , over the 0.4 ppmV HCl for one

- hour period taking measurements every minute. This was done for all four HCl measured

values with results listed in T able 4.23 Table 4 : HCl Results for Minimum Detection Limit Determin ation With and Without HCL present over the Four Chosen HCl Values.

Average Average Minimum Maximum St. Dev. MDL MDL

HCl HCl measured HCl residual HCL residual HCl residual HCl residual from from

generated measured measured measured measured measured St. Dev. St. Dev.

(ppmV) (ppmV) (ppmV) (ppmV) (ppmV) (ppmV) (ppmV) (ppmV-m)

0.0 -0.17 -0.17 -0.22 -0.14 0.02 0.06 0.18

0.4 0.41 0.02 0.00 0.07 0.02 0.06 0.18

3.8 3.83 0.01 0.00 0.04 0.02 0.06 0.18

15.0 14.93 0.02 -0.01 0.04 0.02 0.06 0.18

The since the tests were done in a 3

- meter sample cell at 25 °C , the results are listed in the last column of the table as ppmV per meter, basically as the pathlength of the sample is extended, the system becomes more sensitive. These results show that independent of the HCl concentration, the minimum detection limit is 0.18 ppmV

- meter of path sampled, the same as arrived at with the zero sample gas. These results al so show by using this technique it almost doubles the sensitivity at the low end as compared to the laboratory tests (refer back to table 2) where the MDL’s at 25 °C per meter were determined to 0.35 ppmV which did not incorporate the residual algorithm. .

The zero drift results over a 1

- week period, for 10 independent tests of zero, showed no greater drift than 1.7% on an average zero at each of the temperature ranges measured, these being at 25 °C, 100 °C and 200 °C (refer to the EPRI HCl report)

.



### D. In

- situ SPAN Checks for NIR TDLAS Spectroscopy

D .1 In

- situ Span Checks

Span is relatively easy, since the laser output is fiber coupled, inserting a flow through cell (calibration cell) in the path is a viable procedure, the cell having a pathlength x

c , a t a temperature T
c can trivially be ratioed to the pathlength x

s of the in

- situ measurement (stack) which is at a temperature T

s by spiking the cell over the typical measurement range with the introduction of certified HCl gas. A background would be taken just prior to the spike test, eliminating any external HCl contribution, since the response is extremely fast the contribution from the flow through cell would only be measured. This also tests the integrity of the whole optical system.24 D

. 2 Audit Cell Verification

Sealed audit cells are available for most gasses, which are designed to be added as a n in

- line

audit module to typically verify calibration, but are typically not used for daily span checks. The

reason is it is difficult to make an audit cell better than 5% accuracy.

Here is an example of an audit cell used for NH 3 verification of calibration. A Unisearch Model:

LAS

- AM

- NH 3 was used in this project to conduct on

- site verification of calibration. The audit module was designed to allow the user to check the sensitivity of the analyzer without the need for calibration gas cylinders and flowing gas streams. The audit module concentration was

warranted to be within +/

- 5% of the stated value for a period of at least one year from date of shipment. T he cell was expected to be stable for a minimum of five years for ammonia.

As shown in Figure 9 , the audit module has two FC/APC ports on the front panel. In order to perform an in

- line audit of the system the laser beam was directed through both the audi t module and the measurement path in series. The ammonia concentration measured on the monitor display represents both the ammonia concentration in the measurement path plus the ammonia in the audit cell. Thus, the audit module introduces an ammonia ‘spike ’ to the measurement path, which can then be compared against a known response based on measurement and audit cell temperature, pressure, measurement path length, and ammonia concentration within the audit

cell.

Figure 9

Audit cell Linked in Series with LasIR Ammonia Monitor

The ammonia concentration value displayed on the ammonia monitor with the audit cell inserted in series with the measurement path will then be the sum of the concentration of the gas in the flue gas stream plus the audit cell va lue, corrected to the same temperature, pressure, and path25 length. Thus, if the flue gas ammonia concentration was 1 ppm V , the total ammonia concentration displayed with the audit cell inserted used for this example would be 30 .6 ppm V

.

The insertion of th e audit cell in line does cause a significant loss in signal return power of approximately 30%.

A background was taken prior to insertion of the audit cell, with background subtraction used to correct resultant ammonia slip readings with measured ammonia s lip values of 0.40 ppm V

. The insertion of the audit cell showed high confidence in the calibration of the system, as it went to a value of 29.43 ppm V (Figure 4

- 2), which means the audit cell added 29.03 ppm V of NH 3

. This is well within the 5% stated accur acy value of the audit cell, which was calculated to add 29.6 ppm V of NH 3

. Although this is not a substitute for a continuous in

- line module that can do spans by simply adding calibration gas, it has been shown to be accurate within 5% in numerous applicat ions and may be worth considering as an alternative for systems where having certified calibration gas on site may be difficult.26 

### E: References:

Bradley M

. , Curve Fitting in Raman and IR Spectroscopy: Basic Theory of Line Shapes and Applications

, Thermo Fisher Scientific Application Note 50733 , Madison, WI, USA

Dene C., J. Pisano, K. Bumiller, T. Durbin, “ Continuous Emission Monitor For Hydrochloric Acid: Tunable Diode Laser Test Report

- Unisearch LasIR S Series” ( EPRI, Palo Alto, CA: 2011 1022083)

Grant WB

, Kagann RH

, McClenny WA

. “ Optical remote measurement of toxic gases ” J Air Waste Manage Assoc. 1992 Jan;42(1):18

- 30.

Himes R

., J.Pisano and T. Durbin, “ Ammonia Lab Test Verification

– LTG Lightwise TDL

Monitor ” ( EPRI, Palo Alto, CA: 2009 1019372)

Himes R ., J.Pisano and T. Durbin, “ Ammonia Lab Test Verification

– Siemens LDS 6 ” (EPRI, Palo Alto, CA: 2007 1014745)

Himes R

., J.Pisano and T. Durbin, “ Ammonia Lab Test Verification

– Norsk Electo Optik’s (NEO) LaserGas II ” (EPRI, Palo Alto, CA: 2007 1015315)

Himes R ., J.Pisano and T. Durbin, “ Ammonia Lab Test Verification

– Opsis LD500” (EPRI, Palo Alto, CA: 2007 1016116)

Him es R ., J.Pisano and T. Durbin, “ Ammonia Lab Test Verification

– Unisearch LasIR SM410 ” (EPRI, Palo Alto, CA: 2006 1014664)