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Demonstration of a Method to Determine Atmospheric GasConcentration from Infrared Emission Spectra

David W. DuBois

Semester Project for Spring 1997 ATMS Radiation Transfer

Abstract

The measurement techniques of trace gas pollutants such as O3, CO and NH3 in theatmosphere near the ground have matured enough to ensure reliable human exposureassessments. However, no practical method has been identified to quantify the verticalextent of gaseous pollutants near the ground. One method, based upon passive remotesensing, might prove practical in measuring the amount of trace pollutants in somecircumstances. This method involved comparing a measured thermal emission spectralradiance to a theoretically based estimation. A demonstration of the method was done onApril 25, 1997 in Stead, Nevada. The calculated thermal emission spectra will beproduced from FASCOD3 using the HITRAN96 spectral line database. The firsttheoretical prediction was that of the thermal emission of all atmospheric constituents asseen against an object radiating as a black body. This prediction will be subtracted fromthe measured spectral to arrive at the measured radiance of the trace gas. The secondtheoretical prediction will be of the radiance of just the trace gas. This calculation wasperformed using FASCOD3 by allowing the atmosphere to be composed of only the tracegas and no other gases or aerosols. By comparing the measured trace gas radiance to thecalculated radiance of the trace gas, the effective concentration can be estimated byvarying the model results until the calculated spectra shows a best fit to themeasurements. This project involved using FASCOD3 and HITRAN96 software on a PCplatform and some relatively simple data manipulation techniques using data analysissoftware Matlab and MS Excel. Successful evaluation of this method was found to besubject to the availability of good FTIR spectrometer spectra.

INTRODUCTION

The use of spectral emission measurements with a FTIR spectrometer has been usedto infer the trace gaseous species in the atmosphere (Evans and Puckrin, 1997). Bymaking some simplifications, the emission spectrum of naturally occurring gases can beobtained through the use of sophisticated numerical computations based on knownabsorption lines compiled over the years. One such method, used in this paper, is toemploy the HITRAN96 spectral database in the FASCOD3P atmospherictransmission/radiance model. By controlling the presence or absence of a particulargaseous species emission from an emission spectrum, the concentration of the gas inquestion can be iteratively determined. This paper serves the purpose of presenting and

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demonstrating the methodology of estimating the gas concentration based on a singleemission measurement.

The HITRAN96 (HIgh resolution TRANsmission) spectroscopic databaseoriginates from the U.S. Air Force Geophysics Laboratory, now the Phillips Laboratory inHanscom, Air Force Base (McClatchey et al, 1973). The database includes 36 molecularspecies along with values for absorption cross-sections of heavy-molecules (e.g. CFCs)based on the work of Varanasi (Varanasi and Nemtchinov, 1994). Figure 1 Shows theentire spectral coverage of the database.

Figure 1. Spectral Coverage of HITRAN96 Database

The spectral absorption, transmission and emission of radiation in the atmosphere arecharacterized by the shape, location and intensity of the absorption line. The HITRAN96database supplies the following information: line position (cm-1), the intensity of thetransition (cm-1 molec-1 cm2), air-broadened halfwidth (cm-1 atm-1) and energy of thelower state of the transition (cm-1).

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PROCEDURE

The HITRAN96 database has evolved into a more manageable and understood userinterface when compared with its predecessors. The first step was to install the softwaretools that were provided to accomplish the emission calculations. The database isdistributed on a CD-ROM and software was provided for both MS-Windows and UNIXoperating systems. The Windows version was installed on a 133 MHz Pentium PCrunning MS Windows95 with 40 Mb of RAM.

The MS Windows application called HAWKS was provided to browse and selectpertinent spectral information from the HITRAN database. The FASCOD3P code usesthe HITRAN line parameter database directly through the use of a translation programcalled LNFL92. Before making the line file, the gaseous species must be chosen based onthe available list of molecules. The list includes, H2O, CO2, O3, N2O, CO, CH4, O3, N2O,SO2, NO2, NH3, HNO3, OH, HF, HCl, HBr, HI, ClO, OCS, H2CO, HOCl, N2, HCN,CH3Cl, H2O2, C2H2, C2H6, PH3, COF2, SF6, H2S and HCOOH. The HAWKS interfaceallows the user to plot out the selected emission lines in the spectral interval defined.One such test case was to gather all of the O3 lines in the spectral interval 1000 to 1083cm-1. The resulting line coverage is shown below in Figure 2 from the HAWKS package.

Figure 2. Ozone Transitions in the 1000 to 1082 cm-1 Region

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FASCOD3P has a rigid input/output file structure and is documented in the user’smanual. There are several options to specify the ambient conditions in the code. Thefirst try at using the code involved a simple test to calculate the spectral emission of ablack body at standard conditions over a short horizontal path. The emission parametersrequired are the temperature of the starting and ending points in the path, boundaryspectral emissivity coefficients and the boundary spectral reflectivity coefficients. Afterthis was shown to be successful, the more general situation was simulated with a slantpath to some altitude, and user supplied meteorological conditions.

The spectrometer was a modified Bomem MB100 that has been used earlier toperform laboratory ice and water emission and transmission measurements (Schmitt andArnott 1999; Arnott et al 1997; Schmitt 1998). The spectrometer's emission port faced amovable uncoated front surface gold mirror in order to aim it at the target. Calibrationprocedures were done according to Schmitt, 1998. FTIR spectrometer measurementswere collected at the Desert Research Institute's SAGE building parking lot on April 25between 2 and 3 p.m. local time. The FTIR collected atmospheric emission spectra from500 to 2000 cm-1 in 0.48 cm-1 increments. Four individual spectra were obtained andused to compare with the HITRAN96/FASCOD3P model. The four different spectralscans of the Peavine Mountain were collected in sequential order. Figure 3 shows theestimated field of view the FTIR looked at when it acquired the data.

Figure 3. Estimated field of views looking toward Peavine Mountain,

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The field of view of this instrument was estimated from laboratory measurements andintroduced an uncertainty in the pointing accuracy and as a result the inability todetermine the exact modeling scenario. Since the objective of this study was not arigorous experiment to determine accurate concentrations of trace gases, it does provide ademonstration of the method and an assessment of the limitations of such an experiment.

Figure 4. April 25, 1997 FTIR Spectra from the Four Positions.

The first spectra, labeled 1 (dark blue) in Figure 4 represents the near horizon skyradiance over the mountain and served as a base line measurement. The remaining scans,labeled 2 and 3, were done for decreasing elevation angles. The last scan, labeled 4, wasroughly parallel to the ground and collected a wide range of objects and surfaces thatincluded objects both far and near. The field of view was estimated to be about fourdegrees which covers a large area of land for a range of several kilometers.

Vertical profiles of temperature and water vapor mixing ratio were retrieved froma radiosonde closest to the measurement area. The Reno WSFO radiosonde for 0z 26April, 1997 was collected from the University of Wyoming web server and translated intothe format required for FASCOD3P. The sounding included 33 heights ranging from1.515 km to 30.477 km. This sounding is shown in Figure 5.

The range from the FTIR instrument to the Peavine Mountain was estimated froma USGS topographical map. The horizontal range from Peavine Mountain to the SAGEbuilding was estimated at 7.38 km.

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April 26, 0z Reno Sounding

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Figure 5. Temperature and Water Vapor Sounding Using in the Calculation

The geometry of the measurement is shown in Figure 3. The elevation of theSAGE building was estimated to be about 4970 feet (1.51 km) while Peavine was about8240 to 8250 feet (2.512 to 2.515 km). A small patch of snow was located in a ravinebelow the peak at an elevation of about 7400 feet (2.26 km). Given these elevations, theFASCOD3P was run with an initial height (H1) of 1.515 km, a final height (H2) of 2.26km and a zenith angle (ANGLE) of 5.7 degrees.

FASCOD3P was run in one primary spectral region, 700-1000 cm-1 to find amatch to the measurement data since this region contains the major water vapor and some

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CO2 emission. A small spectral region was also chosen since FASCOD3P limits thespectral range of each calculation to 500 cm-1. A match was defined when the magnitudeof the H2O vapor matched the measured spectrum. The effective black body temperatureof the hill side was then at that temperature, T (TBOUND), of the best fit. The ozoneemission was ignored for the moment. In order to get a match, the temperature of thestart and end path were both adjusted so that the magnitude of the spectrum from 700 to1000 cm-1 was close to the measurement data. To simplify the calculations and analysis,only the first seven molecules were included in the emission calculations. This wassuggested as the default by the authors of FASCOD3P. The first seven molecules areH2O, CO2, O3, N2O, CO and CH4. Although other molecule species are important inatmospheric processes, they were not significant IR absorbers in this spectral range.Detailed description of all the required input parameters for FASCOD3P and theHITRAN96 line code are included in Appendix A. The code was run successively until abest fit was found. The use of PC Matlab was of great help in the comparison of thespectra and its manipulation. Matlab was helpful in repetitive operations by defining m-files which contain commands and can be called in the same fashion as a separateexecutable program.

After running the model many times and trying many combinations of temperatureand water mixing ratios, a best fit was not possible for the scene in position 4 in Figure 3.This spectrum was least affected by the sky emission of the four taken on April 25. Theother spectra showed the effects of sky emission by noticing the low radiance in the 800to 1000 cm-1 region compared to the all ground measurement. Measurements 2 and 3also showed a significant amount of ozone emission which could not be due only to thecolumn amount from the FTIR to the mountain but also from the stratosphere.

To demonstrate the technique in this paper, the spectrum measurement 4 was usedbut the range was assumed to be much less than the actual measurement. Since themeasurement’s range parameters didn’t provide an adequate test case to evaluate thetechnique, a hypothetical scenario was tested. This hypothetical scenario used rangeparameters that produced emissivities that matched the measurement spectrum withminimum error. A range was chosen at 1.515 km for an elevated measurement atH1=1.615 looking down at a black body at H2=1.515 km. The Reno 0z, April 26sounding was again used for the vertical profile of temperature and water vapor mixingratio. After finding a best fit to the measured spectrum, FASCOD3P was run with theozone turned-off. In practice any molecular species can be turned-off by substitutingzeroes in for the values of volume mixing ratio. The “measured” ozone emissionspectrum was then obtained by subtracting this calculated emission, without ozonepresent, from the measured spectrum. The ozone concentration was then estimated byrunning a case where all molecules except ozone are turned-off and providing a best fit.This spectrum is shown in Figure 5 and 6. Two ozone concentrations near a best fit werecompared to visualize the affect of a incremental amount of ozone concentration had onthe results.

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Figure 5. Comparison of Measurement and Ozone Emission Calculation for 20ppbv

Figure 6. Comparison of Measurement and Ozone Emission Calculation for 25ppbv

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DISCUSSION OF METHOD

The Peavine Mountain scenario was modeled first. The analysis of this scenariobrings to light some of the problems of this technique. The success of this technique restson how well the measurement scenario matches the modeled scenario. The ideal scenarioconsists of the FTIR spectrometer facing a surface that emits efficiently as a black body(emissivity near one) and a path length of a kilometer or more. The path can be slantedfrom one height to another or a horizontal path. In addition, the atmospheric profile mustbe known with minimal uncertainty over the path length. Inhomogeneties in temperature,H2O mixing ratio and trace gas concentrations along the path will add error into theestimation. The ideal measurement would involve an instrument with a narrow field ofview such that it looks at a homogeneously emitting surface. The main problem with thedata taken of Peavine Mountain was that the field of view of the FTIR was large enoughto include a complex assortment of thermal sources at varying distances. By includingmany sources of unknown properties, it was impossible to model the scene with a simplemodel.

Selecting a black body source appropriate for this method is crucial for estimatingtrace gas concentrations. Examples of sources can be large buildings, portions ofmountain sides consisting of homogeneous material, asphalt roads, homogeneous cloudlayers of known height, and temperature inversion layers. Many investigators havecharacterized soils and rock formation thermal infrared signatures for use in satelliteimagery interpretation (Snyder et al, 1997; Hipps, 1989; Barton and Takashima, 1986).Utilizing a background that has been well characterized in the thermal infrared wouldprovide a candidate source for this remote sensing technique. The most preferable sourcewould maximize the signal to noise ratio, where the signal is the trace gas emissionsignature and the background blackbody source as noise. Both angular dependentreflectivity and a frequency dependent emissivity are important parameters to consider inselecting a source. Typical values for several sources are shown in Appendix B (Zissis,1993). To estimate the vertical profile of a trace gas throughout the atmosphere, such asozone, the FTIR spectrometer can be pointed skyward and the resulting measurement fitto a standard atmosphere (Anderson, 1986) and adjusted to provide a best fit. The resultof this exercise would be limited to calculating a column amount without additionalinformation since there would be many solutions to this problem (i.e. many profileswould yield the same result). Figure 7 shows a how close a standard atmosphere modelcalculation with FASCODE matches a FTIR spectrometer measurement well. The bluecurve represents the measured spectral radiance.

The sources of error have not been measured quantitatively. It should be notedalso for long paths, the inhomogeneity of gaseous species (particularly in the verticaldimension) must be considered in the analysis. Basically, the measurement andcalculations for long horizontal paths are column integrated and may not represent theconcentration at every point along the path. On the other hand, if the measurementscenario involves a long slant path, the model calculations would require a good firstguess in estimating a vertically distributed trace gas distribution. If one divides up the

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vertical path into several layers, the problem becomes how to construct an accurate tracegas profile. Several profiles may exist that gives the same spectral emittance signature. Ifone only cares about an average concentration, then the vertical path can be divided intoat most two layers for the technique to work. It was found that FASCOD3P needs at leasttwo vertical atmospheric levels to allow enough flexibility for a best-fit analysis.

The evaluation of the technique using the measurement number four provided asuccessful demonstration of ozone concentration estimation technique. Using themeasured spectrum and designing a scenario to fit the data, the ozone concentration wasdetermined to be between 20 and 25 ppbv. This is an acceptable concentration at theground in a unpolluted atmosphere. Normal ground-level ozone concentrations vary from20 to 70 ppbv in this geographic area during this time of year. Occasionally higherconcentrations may be measured during clear skies in the winter right after a snow-falland when the atmospheric conditions permit very little horizontal advection. In previousyears, the Reno area came close and eventually exceeded the EPA ozone NationalAmbient Air Quality Standard during these conditions. This is in contrast to othermetropolitan areas such as San Francisco and Los Angeles where high ozoneconcentrations can be observed only during the summer when photochemical reactionsreach their greatest activity.

Figure 7. Clear Sky Radiance Model and Measurement Comparison

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CONCLUDING REMARKS

The method to outlined in this paper has demonstrated the estimation of gasconcentration based on spectral data from an FTIR spectrometer. By using a terrestrialsurface as a thermal black body source, this method would be applicable for clear orcloudy skies, providing that the source temperature can be measured accurately. This isan improvement over other methods (Evans and Puckrin, 1997) which rely on highlypolluted inversion layers or clouds in order to provide a stable thermal background.

This method also provides a method to calibrate and subtract-out laboratorymeasurements that are in the CO2, H2O vapor and particulate absorption regions. TheFASCOD3P model allows a spectrally varying scattering and absorption coefficient tomodel aerosol radiation transfer effects.

REFERENCES

Anderson, G.P., S.A. Clough, F.X. Kneizys, J.H. Chetwynd and E.P. Shettle (1986)AFGL Atmospheric Constituent Profiles (0-120km), AFGL-TR-86-0110.

Barton, I.J. and T. Takashima (1986) An AVHRR investigation of Surface EmissivityNear Lake Eyre, Australia, Remote Sens. Environ., 20, 151.

DeSlover D.H. (1996) Analysis of Visible and Infrared Cirrus Cloud Optical PropertiesUsing High Spectral Resolution Remote Sensing, M.S. Thesis, University of Wisconsin,Madison.

Evans W.F.J., E. Puckrin (1997) Remote sensing measurements of tropospheric airpollutants by ground-based thermal emission FTIR, in Optical Remote Sensing of theAtmosphere, Vol. 5, 1997 OSA Technical Digest Series (Optical Society of America,Washington DC, 1997), pp. 212-215.

Hipps, L.E. (1989) The infrared emissivites of soil and artemesia tridentata andsubsequent temperature corrections in a shrub-steppe ecosystem, Remote Sens. Environ.,27, 337.

Kneizys F.X., E.P. Shettle, L.W. Abreu, J.H. Chetwynd, G.P. Anderson, W.O. Gallery,J.E.A. Selby, and S.A. Clough (1988) Users Guide to LOWTRAN 7, AFGL-TR-88-077.

McClatchey R.A., W.S. Benedict, S.A. Clough, D.E. Burch, R.F. Calfee, K. Fox, L. S.Rothman, and J.S. Garing (1973) AFCRL Atmospheric Absorption Line ParametersCompilation, AFCRL-TR-0096 (AFCRL, Bedford, MA).

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Schmitt, C. and Arnott, W.P. (1999) Infrared Emission (500 - 2000 cm-1) of LaboratoryIce Clouds. J. of Quantitative Spectroscopy and Radiative Transfer, submitted November1998.

Schmitt, C. (1998) Infrared Emission (500 - 2000 cm-1) of Laboratory Ice Clouds. M.S.Thesis. University of Nevada, Reno.

Snell H.E., G.P. Anderson, J.H. Chetwynd, S. Miller, FASCODE for the Environment(FASE), presented at the 1996 Battlespace Atmospherics Conference, 3-5 December,1996, NraD, San Diego, CA.

Snyder, W.C., W. Zhengming, Y. Zhang, Y.-Z. Feng, (1997) Thermal Infrared (3-14 µm)Bidirectional Reflectance Measurements of Sands and Soils, Remote Sens. Environ. 60,101.

Varanasi P. and V. Nemtchinov (1994) Thermal Infrared Absorption Coefficients ofCFC-12 at Atmospheric Conditions, Journ. Quan. Spect. Rad. Trans., 51, 679.

Wang J., G.P. Anderson, H.E. Revercomb, and R.O. Knutsen (1996) Validation ofFASCOD3 and MODTRAN3: Comparison of Model Calculations with Ground-Basedand Airborne Interferometer Observations under Clear-Sky Conditions, Applied Optics,35, 6028.

Zissis, J. (1992) Editor of The Infrared and Electro-Optical Systems Handbook, Volume1, J.S. Acetta and D.L. Shumaker, Exec. Ed., Sources of Radiation, EnvironmentalResearch Institute of Michigan-Infrared Information Analysis Center and SPIE.

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APPENDIX A

FASCOD3P input file for modeling the Peavine Mountain scene from the SAGEbuilding.

$ 25April, 0z, 270K HI=1 F4=1 CN=1 AE=1 EM=1 SC=1 FI=0 PL=0 TS=0 AT=1 MG=0 LS=0 MS=1 XS=0 285.000 1.000 640.000 1140.00 270.000 1.000 .000 .0000 .000 .000 .000 0 2 12 0 0 7 1 .000 .000 .000350.000 1.515 2.26 80.00 1.515 1.585 2.560 2.837 2.962 3.124 4.6685.800 6.716 7.470 9.510 10.740 12 4/26/97 0Z REV sounding1.515 850.0 18.8 AB CAA6666 3.70 360.0 0.0401.585 843.0 15.8 AB CAA6666 2.70 360.0 0.0402.560 750.0 6.0 AB CAA6666 2.79 360.0 0.0402.837 725.0 4.2 AB CAA6666 2.71 360.0 0.0402.962 714.0 7.0 AB CA66666 2.71 360.0 0.0003.124 700.0 6.0 AB CA66666 2.55 360.0 0.0004.668 578.0 -2.5 AB CA66666 1.82 360.0 0.0005.800 500.0 -10.9 AB CA66666 1.21 360.0 0.0006.716 443.0 -16.9 AB CA66666 0.87 360.0 0.0007.470 400.0 -23.1 AB CA66666 0.44 360.0 0.0009.510 300.0 -39.1 AB CA66666 0.20 360.0 0.00010.74 250.0 -48.5 AB CA66666 0.07 360.0 0.000 10 0 0 0 0 0 40.0 1.0 0.0 0.01.515.48 0645. 1140. 1 1 0 0 134

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FASCOD3P input file for slant path test (1.615 to 1.515 km) case

$ Test slant path HI=1 F4=1 CN=1 AE=1 EM=1 SC=1 FI=0 PL=0 TS=0 AT=1 MG=0 LS=0 MS=1 XS=0 284.000 1.000 500.000 1000.00 283.000 1.000 .000 .0000 .000 .000 .000 0 2 12 0 0 7 1 .000 .000 .000350.000 1.615 1.515 91.00 1.515 1.585 2.560 2.837 2.962 3.124 4.6685.800 6.716 7.470 9.510 10.740 12 4/26/97 0Z REV sounding1.515 850.0 18.8 AB CAA6666 3.39 365.0 0.0651.585 843.0 15.8 AB CAA6666 2.49 365.0 0.0602.560 750.0 6.0 AB CAA6666 2.68 360.0 0.0452.837 725.0 4.2 AB CAA6666 2.71 360.0 0.0452.962 714.0 7.0 AB CA66666 2.71 360.0 0.0003.124 700.0 6.0 AB CA66666 2.55 360.0 0.0004.668 578.0 -2.5 AB CA66666 1.82 360.0 0.0005.800 500.0 -10.9 AB CA66666 1.21 360.0 0.0006.716 443.0 -16.9 AB CA66666 0.87 360.0 0.0007.470 400.0 -23.1 AB CA66666 0.44 360.0 0.0009.510 300.0 -39.1 AB CA66666 0.20 360.0 0.00010.74 250.0 -48.5 AB CA66666 0.07 360.0 0.000 10 0 0 0 0 0 40.0 1.0 0.0 0.01.515.48 0500. 1000. 1 1 0 0 134

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APPENDIX B

Spectral Reflectance and Emittance Properties of Some Materials