Abstract. 1 Introduction

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1 Determination of emission sources by remote sensing K. Schafer,* R. Haus,* J. Heland,* CH. Werner' "Fraunhofer Institute for Atmospheric Environmental Research (IFU), Kreuzeckbahnstrafie 19, D Garmisch-Partenkirchen, Germany *Rudower Chaussee 5, D Berlin, Germany *DLR Institute of Optoelectronics, D Wefiling, Germany Abstract In the SANA programme unknown emission sources are inspected and emission rates of different gas releases are validated using FTIRspectroscopy. Gaseous emission rates from industrial and agricultural areas, highways, garbage deposits, open-cast lignite minings, compost heaps and an ensemble of small-building smoke stacks are estimated. COj, ^O, CH*, NH), CO, NO, H2O, and HCHO are determined from measured absorption spectra in extended area plumes. Effluent concentrations such as CO, CO2, H%O, NO, N2O, NO2, SOz, and HC1 from smoke stacks and flares as well as temperature of plumes are quantified from measured emission spectra with the multi-component spectra analysis software MAPS developed at the IFU. Mass fluxes were determined combining a FTIR-spectrometer and a Doppler-lidar which measured the chimney plume velocity. 1 Introduction There are many sources of gaseous emissions which result from human activities in industry and agriculture. To develop strategies for reducing and avoiding environmental impacts and damages, regional emission inventories have to be build-up which not only include emissions from point sources (e.g. smoke stacks), but also contain data of diffuse emissions from anthropogenic as well as biogenic sources. In most cases, diffuse gas releases are caused by more or less extended areas. Rapid, mobile, and multi-component measurement techniques as well as new environmental monitoring strategies are needed for a representative source identification and quantification completing conventional point sampling techniques which

2 356 Air Pollution Engineering and Management are unpractical or even not possible to use in many cases. Fourier-Transform-Infrared (FTIR)-spectroscopy can be performed in a passive or active way depending on the measuring tasks. The most costeffective aspect is the possibility to determine a large number of compounds simultaneously. Basic ideas of this method and some results of measurements with consideration of validation will be presented. 2 Theory 2.1. Calculation of gas concentrations Open-path measurements by absorption spectroscopy The propagation of radiation in an atmospheric layer L extending from s% to 82 is described by the equation of radiative transfer where I&, is the wavenumber-integrated intensity for a defined spectral interval AJ>, 1^ the source intensity behind the layer, B^ the Planck function characterizing the layer self emission features, and r^ the transmittance which is given by (v) %. 1] dv * T%, t = S f (2) with kj(*>) monochromatic absorption coefficient of gas i, S intensity and f form factor of a spectral line, n^ is the corresponding number density, N the number of gases, and r^/" the broad band aerosol transmittance. The direct calculation of gaseous absorption coefficients on the basis of a line-by-line procedure from known data on atmospheric absorption line parameters offers the possibility to include current atmospheric and geometrical parameters as well as spectroscopic features of the instrument (spectral resolution, line shape function) and to study interferences of spectral signatures of different compounds in gas mixtures. In open-path FTIR-spectroscopy, a high-temperature blackbody source (glowbar) is used. The thermal self radiation of the observed layer can be neglected then. Eqn (1) reduces to the Beer-Lambert law, = c B(7 T(a,GB). (3) TGB is the temperature of the glowbar with emissivity s, R and GB are the positions of receiver (spectrometer) and glowbar, respectively. Gas concentrations are determined by a differential absorption method which has the great advantage that calibration gas measurements are not required and all broad band effects (aerosol influence, temperature

3 Air Pollution Engineering and Management 357 variation) are eliminated. The concentrations are calculated from the transmittance ratio of the absorbing (V<J and non-absorbing (v^) part of an isolated spectral line (which is possible due to the high spectral resolution of the instrument used), Passive measurement by emission spectroscopy To describe the radiation emission from distant warm sources, a radiative transfer simulation algorithm is used taking into consideration different atmospheric layers along the radiation path and their mutual influences, Av with I&, radiation intensity at spectral resolution Ay, B, monochromatic Planck function, r, monochromatic transmittance, (JL cosine of zenith angle of incoming radiation, z^ upper level of the model atmosphere, 1^ intensity part of aerosol scattering, 7= 1-w, w albedo of an atmospheric layer. For passive remote sensing of smoke stack gas emissions, the telescope of the spectrometer is adjusted in the way that it receives the radiation from the slant path passing the plume directly above the stack top. The measured difference radiation P (difference of radiation with and without the plume in the field of view (FOV)) can be simulated by the following equation '. (6) The indices s and fg denote source and foreground contribution, respectively. M, M ^ are the measured radiances with and without the plume in the FOV. So, the information about the atmospheric background influencing the plume measurements is included in the measured quantities M and M ^. Foreground parameters are obtained from active mode openpath FTIR-spectroscopy using an infrared light source. Plume temperature and gas concentrations can be determined from the line-by-line simulation of the plume transmittances Determination of emission rates The source attribution is the difference of two measurements carried out perpendicular to the prevailing wind direction at an upwind and downwind position of the source. Path-averaging of contributions of heterogeneous release points across an area source is an advatage of absorption spectroscopy. The propagation of a pollutant plume behind an emission

4 358 Air Pollution Engineering and Management source can be described using Gaussian dispersion theory. The main conditions to use such a model are a homogeneous wind field in horizontal and vertical direction. The emission rate of the source must be a factor of 10 minimum higher by the source than emissions in the surroundings. To determine the difference of upwind and downwind concentrations with high precision the detection limit of the investigated components by FTIRspectroscopy must be a factor of 10 minimum smaller than the downward concentration of this component. The concentration in a certain downwind position from a continuously emitting ground-based point source is given by exp (7) with Q concentration (mg/nf), x, y alongwind and crosswind distance to a receptor (m), E emission rate (mg/s), (Ty, o% standard deviation of plume concentration (dispersion coefficient) in horizontal and vertical direction at x (m), u mean wind speed (m/s). cjy und ^ depend on atmospheric stability, wind speed, and distance from the source. The values can be determined from handbooks or tracer gas experiments (US-EPA*^). Integration of eqn (7) over y direction yields a crosswind-integrated concentration C (mg/nf), 2 E (8) The emission resulting from an area source is composed from emissions of a large number of sub-areas, which are determined by emissions of single points. The concentration distribution Q* along a measuring path at distance x behind the source can be obtained by integrating eqn (7) over the alongwind and crosswind dimensions of the source (a, b) y+6/2 (9) where =y-b. E* is assumed to be the unity emission rate, 1 mg/(s-nf), because there is a complete mixing of air at sufficient distance behind the source. The integration over the crosswind direction b can only be performed by numerical procedures. The integration over dimension a has to take into account the Oy, o% variations with x(a). Thus, the integration over dimension b must be performed for several grid points x'=x+a; to give a mean profile Q*(x,y). This is characterized by using the quantity x in eqn (9). The concentration profile along the measuring path must now be integrated over y to obtain the path-integrated concentration C^ (mg/nf)

5 Air Pollution Engineering and Management 359 which would have been measured if the area source had the emission rate E* = 1 mg/s-nf. The real source emission rate E (mg/s-nf) or total emission rate E? (mg/s) can then be obtained from the actual measured FTIR concentration C* by the following simple equation, /- FTIR E = E', E* = E -a -b. (10) 3 Instrumentation and data analysis The measurements were performed using a van which is equiped with the commercial double pendulum interferometer K300 (Kayser-Threde). A flat tracking mirror reflects radiation from distant sources into the interferometer telescope. Signal optimization is achieved by observing the spectrum on a PC screen and adjusting the mirror. Meteorological parameters are recorded using an automatic working small meteorology station. An initial setup of the complete system takes about 15 minutes. The multi-component software MAPS to interpret the measured spectra and the emission rate code AREA have been developed at the IFU. MAPS (Haus et al.\ Schafer et al/) is based on line-by-line radiative transfer calculations using the HITRAN database to determine the gaseous absorption coefficients and least-squares fitting procedures to compare measured and simulated spectra. Spectra are measured with a spectral resolution of 0.2 cm"* normally and 0.06 cm"* maximum. The concentration calculation is performed on-line on board the mobile laboratory to give the actual values of concentrations every 5 minutes and is possible for any mixture of air pollutants provided their spectroscopic data are known. CC>2, CO, NO, N2O, H?O, CH,, NHg, and HCHO are retrieved from absorption measurements. The detection limits are in the range from 1 to 10 ppb. CO?, CO, NO, NO?, N?O, SO,, HC1, H,O, CH,, NH,, and HCHO can retrieved from emission measurements with detection limits in the range from 1 to 10 ppm depending on plume temperature except of NOz (20 ppm) and SO, (100 ppm). This spectra analyses software was further developed with a multi-layer model to investigate aircraft engine exhausts (Heland et al.*) in frame of the programme "Impact of aircraft and spacecraft upon the atmosphere" supported by the German Science Foundation (DFG). 4 Measurement results 4.1. Highways The distance of the downwind measuring path to the area source must not have any influence on the calculated emission rates, because they are a unique function of the source. The investigation of this condition should be

6 360 Air Pollution Engineering and Management a good validation of the AREA code. CO and NO emission rate measurements were performed near a highway during a time period with continuous vehicle traffic (30 ±5 vehicles per minute). The FTIR path length was 250 m. At distances from 30 to 500 m, the open-path concentration differences of CO (NO) to the background values 169 ppb (< 1 ppb) varied between 181 and 30 (56-0) ppb and the connected emission rates between 151 and 163 (36-40) /xg/snf). Thus, the expected distance invariance could be verified. A total source emission rate can only be given for a defined part of the highway. Thus, the vehicle traffic on an 1 km segment caused a CO (NO) emission of 3.2 (0.8) g/s during the time of measurements Slurry spreading on grassland NH) concentrations and emission rates were determined before, during, and after slurry spreading on a grassland area of 150 x 150 m^ carried out by two tank cars. The FTIR path length was 200 m at a downwind distance of 85 m to the centreline of the area. Data were recorded over a 7.5 hours period. The maximum concentration of 410 ppb (emission rate 56 jug/s-nf) was detected 15 minutes before the end of spreading activities followed by a nearly exponential decrease down to 200 ppb (15 /ig/s-nf) seven hours later. This result is in coincidence with in situ measurements giving a 50 % loss of NHg at the same meteorological conditions (Sciborski*). Upon mechanical ploughing of the remaining substance the concentration fell down to 80 ppb which was still an unexpected high value. Nevertheless, the total emission rate was small (around 1 //g/s-nf = 22 mg/s) at this time. Wind speeds varied from 1.3 to 2.8 m/s during the volatilization process, but very calm conditions (u=0.5 m/s) occured in the evening. The atmospheric stability class varied from A to C and was D upon ploughing. Thus, stable atmospheric conditions were responsible for the recording of comperatively high NH% concentrations upon ploughing while the emission rate was small Power plant smoke stacks Numerous measurements and quantitative gas analyses of smoke stack emissions have been performed at power plants with different types of fireing (lignite, hard coal, oil, gas) to compare the FTIR concentration results with data from CEM (Continuous Emission Monitoring) sensors which were installed inside the stacks of some modern power plants. The mean deviations of FTIR and CEM data rarely exceed 25 %. This is a very satisfying result for a remote sensing system where the smoke stack plumes are measured from a distance of some 100 meters. Successful measurements were realized for distances of more than 1 km. The main applications of this technique should be unannounced emission control, supervision of system breakdown, or data sampling for stacks having no CEM technique inside, therefore. The deviations mainly occur because of

7 Air Pollution Engineering and Management 361 unknown wind influence on the plume diameter which is one of the input parameters for the analysis software. Unfortunately, there is no chance to measure 62 with a FTIRspectrometer. Thus, the transformation of measured concentrations to norm cubic meters (usually 6 % Cy is not possible. At Munich-Nord power station in addition to the FTIR-spectrometer a cw-doppler-lidar of the DLR was used to measure the streaming velocity in the chimney plume. This Doppler-lidar measured the line-of-sight wind components. Focussing in different altitudes and performing full azimuth scans gives the wind profile. To estimate the tracer velocity of the chimney plume a sector scan in the level near the chimney top where the field of view of the FTIR-spectrometer is located also was necessary. With an additional sector scan of the undisturbed wind field one can estimate the influence of the chimney in the wind field. The velocity and the concentration in the plume give the mass fluxes of the plume. Fluxes of CO2, CO, NO, and HC1 were determined. The results differ by about 10 % in relation to the fluxes measured by the CEM sensors of the power station Diffuse emissions from small-building smoke stack ensembles The estimation of integral pollutant inputs (diffuse emissions) of heating systems from a residential area or from a small town was possible using FTIR open-path absorption measurements. During a first trial, measurements were performed at the small town Ruhla located in a narrow valley in the Thuringian Forest. Thus, there is a good opportunity to make open-path measurements from one mountain slope to the other above the roofs. The main part of buildings was already equiped with modern oil or gas heatings. The open-path measurements were performed during a 24 hours period at a downwind position where contributions of emission sources of the entire town were expected. The prevailing wind direction and strength were nearly constant during the trial so that almost identical air flow conditions can be assumed. Maximum CO concentrations occured at the two subsequent evenings from 4:00 to 6:00 pm. Other, smaller maxima were observed from 5:00 to 9:00 am. The contribution of vehicle exhausts was small. Because of low ambient temperature (-7 C) the heating systems of most detached houses were working, particularly during the early morning and evening hours. The effect of pollutant enhancement resulting from fuel combustion could be observed for CH*, but mainly in the morning hours. No systematic COz and NO enhancements were measured, on the other hand. CO2 concentrations varied between 360 and 380 ppm, NO was below the K300 detection limit of 5 ppb. To determine emission rates additional measurements were performed enclosing only a small part of the town (12 detached houses occupying an area of approximately 60 x 80 nf). The prevailing wind direction guaranteed an unaffected upwind (background) level. With concurrent

8 362 Air Pollution Engineering and Management measurements of meteorological parameters and the use of a Gaussian plume dispersion model the following emission rates were determined: CC^ 3.93 mg/(s-nf), CO mg/(s-nf), and CH, mg/(s-m^). However, more measurements are needed to establish a reliable data base on diffuse emissions from small-building smoke stacks. 5 Conclusion Open-path FTIR-Spectroscopy using the K300 interferometer and the concentration retrieval software MAPS are well suited to quantify atmospheric pollutants emitted from industrial and agricultural facilities and traffic. In some applications, optical methods are without a feasible alternative as in the case of flare emission measurements. Results of further measurements are reported by Haus et al/ and Schafer et ala Further investigations are necessary to use FTIR spectroscopy in other fields. Acknowledgement This work was supported by the German ministry of education, science, research, and technology in frame of the program SANA. References 1. US-EPA. Industrial source complex (ISC) dispersion model user's guide, second edition (revised), Vol.1, U.S. Environmental Protection Agency, OAQPS, Research Triangle Park, NC, EPA-450/ a, US-EPA. Guideline on air quality models, (revised), U.S. Environmental Protection Agency, OAQPS, Research Triangle Park, NC, EPA- 450/ , Haus, R., Schafer, K., Bautzer, W., Mosebach, H., Bittner, H. & Eisenmann, T. Mobile FTIS-monitoring of air pollution, Appl. Opt., 1994, 33, Schafer, K., Haus, R., & Heland J. Inspection of non-co2 greenhouse Gases from emission sources and in ambient air by Fourier- Transform-Spectrometry: Measurements with FTIS-MAPS, Environmental Monitoring and Assessment, 1994, 31, Heland, J., Haus, R. & Schafer, K. Remote sensing and analysis of trace gases from hot aircraft engine plumes using FTIR-emissionspectroscopy, Sci. Total Environ., 1994, 158, Sciborski, J. Jahresbericht 1993, SANA - Wissenschaftliches Begleitprogramm zur Sanierung der Atmosphare iiber den neuen Bundeslandern, Fraunhofer-Institut fur Atmospharische Umweltforschung, Garmisch-Partenkirchen, 1994.