Fugitive coke oven gas emission profile by continuous line averaged open-path Fourier transform infrared monitoring

Although most coke oven research is focused on the emission of polycyclic aromatic hydrocarbons, well-known carcinogens, little has been done on the emission of volatile organic compounds, some of which are also thought to be hazardous to workers and the environment. To profile coke oven gas (COG) emissions, we set up an open-path Fourier transform infrared (OP-FTIR) system on top of a battery of coke ovens at a steel mill located in Southern Taiwan and monitored average emissions in a coke processing area for 16.5 hr. Nine COGs were identified, including ammonia, CO, methane, ethane, ethylene, acetylene, propylene, cyclohexane, and O-xylene. Time series plots indicated that the type of pollutants differed over time, suggesting that different emission sources (e.g., coke pushing, quench tower, etc.) were involved at different times over the study period. This observation was confirmed by the low cross-correlation coefficients of the COGs. It was also found that, with the help of meteorological analysis, the data collected by the OP-FTIR system could be analyzed effectively to characterize differences in the location of sources. Although the traditional single-point samplings of emissions involves sampling various sources in a coke processing area at several different times and is a credible profiling of emissions, our findings strongly suggest that they are not nearly as efficient or as cost-effective as the continuous line average method used in this study. This method would make it easier and cheaper for engineers and health risk assessors to identify and to control fugitive volatile organic compound emissions and to improve environmental health.     

Applications of open-path Fourier transform infrared for identification of volatile organic compound pollution sources and characterization of source emission behaviors

An open-path Fourier transform infrared spectroscopy (OP-FTIR) system was set up for 3-day continuous line-averaged volatile organic compound (VOC) monitoring in a paint manufacturing plant. Seven VOCs (toluene, m-xylene, p-xylene, styrene, methanol, acetone, and 2-butanone) were identified in the ambient environment. Daytime-only batch operation mode was well explained by the time-series concentration plots. Major sources of methanol, m-xylene, acetone, and 2-butanone were identified in the southeast direction where paint solvent manufacturing processes are located. However, an attempt to uncover sources of styrene was not successful because the method detection limit (MDL) of the OP-FTIR system was not sensitive enough to produce conclusive data. In the second scenario, the OP-FTIR system was set up in an industrial complex to distinguish the origins of several VOCs. Eight major VOCs were identified in the ambient environment. The pollutant detected wind-rose percentage plots that clearly showed that ethylene, propylene, 2-butanone, and toluene mainly originated from the tank storage area, whereas the source of n-butane was mainly from the butadiene manufacturing processes of the refinery plant, and ammonia was identified as an accompanying reduction product in the gasoline desulfuration process. Advantages of OP-FTIR include its ability to simultaneously and continuously analyze many compounds, and its long path length monitoring has also shown advantages in obtaining more comprehensive data than the traditional multiple, single-point monitoring methods.     

A tunable diode laser system for ammonia flux measurements over multiple plots

This paper reports on the field testing of a tunable diode laser trace gas analyzer system for micrometeorological monitoring of ammonia fluxes. This system uses infrared absorption spectroscopy to measure atmospheric ammonia concentrations and the fluxgradient method to relate the measured concentration gradient to a flux of ammonia. For the field tests, we monitored ammonia fuxes over three plots receiving different manure applications. Each plot was sampled for 15 or 30 min of each hour, producing a high-temporal resolution data set. Analysis of the system response showed that ammonia adsorption to the tubing walls was greatly reduced by the system design and did not interfere with the flux measurement.     

The Odor Impact Model

Abstract

This paper presents the simulation and field evaluation results of two approaches to localize pollutant emission sources with open-path Fourier transform infrared (OPFTIR) spectroscopy. The first approach combined the plume’s peak location information reconstructed from the Smooth Basis Function Minimization (SBFM) algorithm and the wind direction data to calculate source projection lines. In the second approach, the plume’s peak location was determined with the Monte Carlo methodology by randomly sampling within the beam segment having the largest path-integrated concentration. We first conducted a series of simulation studies to investigate the sensitivity of using different basis functions in the SBFM algorithm. It was found that fitting with the beta and Weibull basis functions generally gave better estimates of the peak locations than with the normal basis function when the plumes were mainly within the OP-FTIR’s monitoring line. However, for plumes that were symmetric to the peak position or spread over the OP-FTIR, fitting with the normal basis function gave better performance. In the field experiment, two tracer gases were released simultaneously from two locations and the OP-FTIR collected data downwind from the sources with a maximum beam path length of 97 m. For the first approach, the release locations were within the 0.25- to 0.5-probability area only after the uncertainty of the peak locations was included in the calculation process. The second approach was easy to implement and still performed as satisfactorily as the first approach. The distances from the sources to the best-fit lines (i.e., the regression lines) of the estimated locations were smaller than 10 m.     

Developing and evaluating techniques for localizing pollutant emission sources with open-path Fourier transform infrared measurements and wind data

This paper presents the simulation and field evaluation results of two approaches to localize pollutant emission sources with open-path Fourier transform infrared (OP-FTIR) spectroscopy. The first approach combined the plume's peak location information reconstructed from the Smooth Basis Function Minimization (SBFM) algorithm and the wind direction data to calculate source projection lines. In the second approach, the plume's peak location was determined with the Monte Carlo methodology by randomly sampling within the beam segment having the largest path-integrated concentration. We first conducted a series of simulation studies to investigate the sensitivity of using different basis functions in the SBFM algorithm. It was found that fitting with the beta and Weibull basis functions generally gave better estimates of the peak locations than with the normal basis function when the plumes were mainly within the OP-FTIR's monitoring line. However, for plumes that were symmetric to the peak position or spread over the OP-FTIR, fitting with the normal basis function gave better performance. In the field experiment, two tracer gases were released simultaneously from two locations and the OP-FTIR collected data downwind from the sources with a maximum beam path length of 97 m. For the first approach, the release locations were within the 0.25- to 0.5-probability area only after the uncertainty of the peak locations was included in the calculation process. The second approach was easy to implement and still performed as satisfactorily as the first approach. The distances from the sources to the best-fit lines (i.e., the regression lines) of the estimated locations were smaller than 10 m.     

Comparing estimates of fugitive landfill methane emissions using inverse plume modeling obtained with Surface Emission Monitoring (SEM), Drone Emission Monitoring (DEM), and Downwind Plume Emission Monitoring (DWPEM)

ABSTRACT

As part of the global effort to quantify and manage anthropogenic greenhouse gas emissions, there is considerable interest in quantifying methane emissions in municipal solid waste landfills. A variety of analytical and experimental methods are currently in use for this task. In this paper, an optimization-based estimation method is employed to assess fugitive landfill methane emissions. The method combines inverse plume modeling with ambient air methane concentration measurements. Three different measurement approaches are tested and compared. The method is combined with surface emission monitoring (SEM), above ground drone emission monitoring (DEM), and downwind plume emission monitoring (DWPEM). The methodology is first trialed and validated using synthetic datasets in a hand-generated case study. A field study is also presented where SEM, DEM and DWPEM are tested and compared. Methane flux during two-days measurement campaign was estimated to be between 228 and 350 g/s depending on the type of measurements used. Compared to SEM, using unmanned aerial systems (UAS) allows for a rapid and comprehensive coverage of the site. However, as showed through this work, advancement of DEM-based methane sampling is governed by the advances that could be made in UAS-compatible measurement instrumentations. Downwind plume emission monitoring led to a smaller estimated flux compared with SEM and DEM without information about positions of major leak points in the landfill. Even though, the method is simple and rapid for landfill methane screening. Finally, the optimization-based methodology originally developed for SEM, shows promising results when it is combined with the drone-based collected data and downwind concentration measurements. The studied cases also discovered the limitations of the studied sampling strategies which is exploited to identify improvement strategies and recommendations for a more efficient assessment of fugitive landfill methane emissions.

Implications: Fugitive landfill methane emission estimation is tackled in the present study. An optimization-based method combined with inverse plume modeling is employed to treat data from surface emission monitoring, drone-based emission monitoring and downwind plume emission monitoring. The study helped revealing the advantages and the limitations of the studied sampling strategies. Recommendations for an efficient assessment of landfill methane emissions are formulated. The method trialed in this study for fugitive landfill methane emission could also be appropriate for rapid screening of analogous greenhouse gas emission hotspots.     

Theoretical evaluation of a method for locating gaseous emission hot spots

This paper describes and theoretically evaluates a recently developed method that provides a unique methodology for mapping gaseous emissions from non-point pollutant sources. The horizontal radial plume mapping (HRPM) methodology uses an open-path, path-integrated optical remote sensing (PI-ORS) system in a horizontal plane to directly identify emission hot spots. The radial plume mapping methodology has been well developed, evaluated, and demonstrated. In this paper, the theoretical basis of the HRPM method is explained in the context of the method's reliability and robustness to reconstruct spatially resolved plume maps. Calculation of the condition number of the inversion's kernel matrix showed that this method has minimal error magnification (EM) when the beam geometry is optimized. Minimizing the condition number provides a tool for such optimization of the beam geometry because it indicates minimized EM. Using methane concentration data collected from a landfill with a tunable diode laser absorption spectroscopy (TDLAS) system, it is demonstrated that EM is minimal because the averaged plume map of many reconstructed plume maps is very similar to a plume map generated by the averaged concentration data. It is also shown in the analysis of this dataset that the reconstructions of plume maps are unique for the optimized HRPM beam geometry and independent of the actual algorithm applied.     

Eddy flux measurements of methane over the fen “Murnauer Moos”, 11°11′E, 47°39′N,using a fast tunable diode laser spectrometer

Eddy covariance measurements of methane were carried out over the fen “Murnauer Moos” in the south of Germany in order to evaluate the performance of a newly developed eddy covariance measurement system, based on a frequency-modulated tunable diode laser spectrometer as a fast chemical sensor. During a six-day period, an average daytime methane emission of (5.4±1.8) mg CH₄ m⁻² h⁻¹ was measured. We find this value moderate, considering the favorable meteorological and soil conditions for methane emission. Diurnal cycles of the fluxes of methane and carbon dioxide as well as of sensible and latent heat are presented. Results are discussed in terms of relevant micrometeorological quantities, and quality control procedures based on Allan variance and spectral analysis are discussed.     

Overview and assessment of techniques to measure ammonia emissions from animal houses: the case of the Netherlands

In order to comply with the ammonia (NH(3)) emission reduction assigned to the Netherlands development of new measures are needed, which should be supported by fast and accurate measurements to arrive at new estimates of the NH(3) emission from each agricultural source. This paper gives an overview of the current methods used in the Netherlands to measure NH(3) emissions from animal houses, and provides alternative methods for some particular situations. For mechanically ventilated animal houses, passive flux samplers placed in the ventilation shafts of the animal house are presented as alternative to measure a larger number of animal houses (replicates) with the same housing system at a low price. For naturally ventilated animal houses, when mixing in the animal house is not good enough to allow measurements within the animal house (internal tracer gas ratio method), two measurement methods are discussed: the Gaussian plume dispersion model, which is usually not suitable for agricultural situations, and the flux frame method, which is not always applicable because of distortion of the flow around the building. Finally, for animal houses with outside yards for the animals, there are at this moment no methods available to measure the NH(3) emissions from these complex situations, although quick box methods (for the outside yards) and a combination of a backward Lagrangian stochastic model with open-path concentration measurements with a tunable diode laser (TDL), look promising.     

基于可调二极管激光技术的汽车尾气遥感监测系统

汽车尾气排放已成为最主要的城市污染源之一。汽车尾气的遥感监测系统作为一种高效实时监测汽车正常运行状况下的尾气排放方法已越来越受到人们的广泛关注。本文主要介绍基于可调二极管激光（TDL）技术的汽车尾气遥感监测系统。首先介绍遥感监测系统的产生与发展以及TDL技术的基本原理，其次阐述遥感监测系统的组成、关键技术以及系统的优点，并分析遥感监测系统在国内外的应用现状，最后提出目前应用中尚待解决的若干关键技术问题。     

基于可调二极管激光技术的汽车尾气遥感监测系统

汽车尾气排放已成为最主要的城市污染源之一。汽车尾气的遥感监测系统作为一种高效实时监测汽车正常运行状况下的尾气排放方法已越来越受到人们的广泛关注。本文主要介绍基于可调二极管激光(TDL)技术的汽车尾气遥感监测系统。首先介绍遥感监测系统的产生与发展以及TDL技术的基本原理,其次阐述遥感监测系统的组成、关键技术以及系统的优点,并分析遥感监测系统在国内外的应用现状,最后提出目前应用中尚待解决的若干关键技术问题。     

Time-resolved ammonia measurement in vehicle exhaust

The objective of this study was to identify the influence of sampling and analytical approach on the quality of NH3 emission data of a gasoline-fuelled three-way catalyst vehicle. NH₃ concentration measurements have been performed in the tailpipe and in the diluted exhaust after a constant volume sampling (CVS) system during five different test cycles. Chemical ionisation mass spectrometry (CI-MS) and Fourier transform infrared spectroscopy (FTIR) were used to acquire ammonia concentrations in real-time. Independently, NH₃ emission rates were determined by continuous absorption of a flow-proportional sample of exhaust gas in diluted sulphuric acid and subsequent ion chromatography (IC). Ammonia emission rates ranged from 22–94 mg km^-1. The results of the three compared techniques are in good agreement. Furthermore, time-resolved ammonia emission profiles recorded by CI-MS and FTIR coincided with respect to emission levels as well as emission dynamics. However, in the dilution tunnel, severe ammonia adsorption was observed leading to long lasting memory effects or even analyte loss. Therefore, neither ammonia real-time emission data nor NH₃ emission rates should be acquired after a CVS system.     

Multi-pollutant concentration measurements around a concentrated swine production facility using open-path FTIR spectrometry

Open-path Fourier transform infrared (OP/FTIR) spectrometry was used to measure the concentrations of ammonia, methane, and other atmospheric gases around an integrated industrial swine production facility in eastern North Carolina. Several single-path measurements were made over an 8-day period from 11 to 22 January 1999. Nine different monitoring paths were configured to determine the concentration ranges of ammonia and methane throughout this facility, with an emphasis on isolating the emissions from the farrowing/nursery barns, the finishing barns, and the waste lagoon. A series of sequential measurements was made on 13 January 1999, to estimate the target gas concentrations downwind from each of these sources and at an upwind background site under similar meteorological conditions. The path-averaged concentration (mean±standard deviation) of ammonia during these measurements was below the estimated method detection limit of 0.003 ppm at the background site, 0.328±0.044 ppm between the farrowing/nursery and finishing barns, 2.063±0.140 ppm perpendicular to the airflow from the exhaust fans of the finishing barns, 0.488±0.110 ppm along the western berm of the lagoon, and 0.722±0.659 ppm along the eastern berm of the lagoon. The mean-path-averaged concentration of methane during this same time period was 1.89±0.03 ppm at the background site, 2.58±0.11 ppm between the farrowing/nursery and finishing barns, 2.70±0.05 ppm perpendicular to the airflow from the exhaust fans of the finishing barns, 2.27±0.06 ppm along the western berm of the lagoon, and 11.02±9.69 ppm along the eastern berm of the lagoon as the prevailing westerly winds died down. The concentration measurements made along different monitoring paths during this study indicate that the confinement barns can be a significant source of ammonia, while the lagoon is a major source of methane. Attempts to apply tracer-based dispersion modeling techniques to the single-path OP/FTIR data to estimate emission rates of ammonia and methane from the different sources present at this facility were met with limited success.     

Innovative approach for estimating fugitive gaseous fluxes using computed tomography and remote optical sensing techniques.

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70 degrees range of wind directions under extremely large measurement error conditions.     

Measurement of ammonia emissions using various techniques in a comparative tunnel study

A field-based intercomparison study for ammonia measurements was conducted using seven analytical methods. It included sulphuric acid impinger, citric acid denuder, differential optical absorption spectroscopy (DOAS), Fourier transform infrared spectroscopy (FTIR), photoacoustic spectroscopy (PAS), and continuous aqueous extraction followed by measurement of conductivity (Airrmonia). Measurements were done at the entrance and the exit of the Gubrist highway tunnel near Zurich, Switzerland. For DOAS, FTIR, PAS and Airrmonia, 24 hour means were calculated based on a time resolution of 10 minutes. At the tunnel exit, all 24 hour averages were within 13%, and the continuous data of the time-resolved methods agreed well. At the tunnel entrance, a slightly reduced method comparison included four methods, and daily mean values agreed within 23%. Ammonia emission factors, based on 4 weeks of continuous measurements with the Airrmonia, were 31 ± 4 mg km^-1 for light-duty vehicles and 14 ± 7 mg km^-1 for heavy-duty vehicles.     

Methane and carbon dioxide emissions from Shan-Chu-Ku landfill site in northern Taiwan

To investigate the methane and carbon dioxide emissions from landfill, samples were taken of material up to 5 years old from Shan-Chu-Ku landfill located in the northern part of Taiwan. Atmospheric concentrations of carbon dioxide, methane and nitrous oxide ranged from 310 to 530, 2.64 to 20.16 and 0.358 to 1.516 ppmv with the measurement of gas-type open-path Fourier transform infra-red (FTIR) spectroscopy during February 1998 to March 2000, respectively. Average methane emission rate was 13.17, 65.27 and 0.99 mgm(-2)h(-1) measured by the gas chromatography chamber method in 1-2, 2-3 and 5 year-old landfill, respectively. Similarly, average carbon dioxide emission rate was 93.70, 314.60 and 48.46 mgm(-2)h(-1), respectively. About 2-3 year-old landfill had the highest methane and carbon dioxide emission rates among the tested areas, while 5 year-old landfill was the least. Methane emission rate at night in most tested locations was higher than that in the daytime. Total amount of methane and carbon dioxide emission from this landfill was around 171 and 828 ton in 1999, respectively.     

Innovative Approach for Estimating Fugitive Gaseous Fluxes Using Computed Tomography and Remote Optical Sensing Techniques

ABSTRACT

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70° range of wind directions under extremely large measurement error conditions.     

Laboratory testing of a continuous emissions monitor for hydrochloric acid

Continuous monitoring of exhaust flue gas has become a common practice in power plants in response to Federal Mercury and Air Toxics Standards (MATS) standards. Under the current rules, hydrochloric acid (HCl) is not continuously measured at most plants; however, MATS standards have been proposed for HCl, and tunable diode laser (TDL) absorption spectroscopy is one method that can be used to measure HCl continuously. The focus of this work is on the evaluation and verification of the operation performance of an HCL TDL over a range of real-world operating environments. The testing was conducted at the University of California at Riverside (UCR) spectroscopy evaluation laboratory. Laboratory tests were conducted at three separate temperatures, 25ºC, 100ºC, and 200ºC, and two distinct moisture levels for the enhanced temperatures, 0%, (2 tests) and 4%, over a concentration range from 0 ppmv to 25 ppmv-m at each of the elevated temperatures. The results showed good instrument accuracy as a function of changing temperature and moisture. Data analysis showed that the average percentage difference between the ammonia concentration and the calibration source was 3.33% for varying moisture from 0% to 4% and 2.69% for varying temperature from 25 to 100/200ºC. An HCl absorption line of 1.742 μm was selected for by the manufacturer for this instrument. The Hi Tran database indicated that CO₂ is probably the only major interferent, although the CO₂ absorption is very weak at that wavelength. Interference tests for NO, CO, SO₂, NH₃, and CO₂ for a range of concentrations typical of flue gasses in coal-fired power plants did not show any interference with TDL HCl measurements at 1.742 μm. For these interference tests, CO₂ was tested at a concentration of 11.9% concentration in N₂ for these tests. Average precision over the entire range for all 10 tests is 3.12%.

Implications: The focus of this study was an evaluation of the operation performance of a tunable diode laser (TDL) for the measurement of hydrochloric acid (HCl) over a range of real-world operating environments. The results showed good instrument accuracy as a function of changing temperature from 25ºC to 200ºC and moisture from 0% to 4%. Such as an instrument could be used for continuous monitoring of exhaust flue gas in power plants once the Federal Mercury and Air Toxics Standards (MATS) standards have been fully implemented.     

Characterizing and locating air pollution sources in a complex industrial district using optical remote sensing technology and multivariate statistical modeling

Emissions of volatile organic compounds (VOCs) are most frequent environmental nuisance complaints in urban areas, especially where industrial districts are nearby. Unfortunately, identifying the responsible emission sources of VOCs is essentially a difficult task. In this study, we proposed a dynamic approach to gradually confine the location of potential VOC emission sources in an industrial complex, by combining multi-path open-path Fourier transform infrared spectrometry (OP-FTIR) measurement and the statistical method of principal component analysis (PCA). Close-cell FTIR was further used to verify the VOC emission source by measuring emitted VOCs from selected exhaust stacks at factories in the confined areas. Multiple open-path monitoring lines were deployed during a 3-month monitoring campaign in a complex industrial district. The emission patterns were identified and locations of emissions were confined by the wind data collected simultaneously. N,N-Dimethyl formamide (DMF), 2-butanone, toluene, and ethyl acetate with mean concentrations of 80.0?±?1.8, 34.5?±?0.8, 103.7?±?2.8, and 26.6?±?0.7 ppbv, respectively, were identified as the major VOC mixture at all times of the day around the receptor site. As the toxic air pollutant, the concentrations of DMF in air samples were found exceeding the ambient standard despite the path-average effect of OP-FTIR upon concentration levels. The PCA data identified three major emission sources, including PU coating, chemical packaging, and lithographic printing industries. Applying instrumental measurement and statistical modeling, this study has established a systematic approach for locating emission sources. Statistical modeling (PCA) plays an important role in reducing dimensionality of a large measured dataset and identifying underlying emission sources. Instrumental measurement, however, helps verify the outcomes of the statistical modeling. The field study has demonstrated the feasibility of using multi-path OP-FTIR measurement. The wind data incorporating with the statistical modeling (PCA) may successfully identify the major emission source in a complex industrial district.     

Analytical solutions to compartmental indoor air quality models with application to environmental tobacco smoke concentrations measured in a house

This paper derives the analytical solutions to multi-compartment indoor air quality models for predicting indoor air pollutant concentrations in the home and evaluates the solutions using experimental measurements in the rooms of a single-story residence. The model uses Laplace transform methods to solve the mass balance equations for two interconnected compartments, obtaining analytical solutions that can be applied without a computer. Environmental tobacco smoke (ETS) sources such as the cigarette typically emit pollutants for relatively short times (7-11 min) and are represented mathematically by a "rectangular" source emission time function, or approximated by a short-duration source called an "impulse" time function. Other time-varying indoor sources also can be represented by Laplace transforms. The two-compartment model is more complicated than the single-compartment model and has more parameters, including the cigarette or combustion source emission rate as a function of time, room volumes, compartmental air change rates, and interzonal air flow factors expressed as dimensionless ratios. This paper provides analytical solutions for the impulse, step (Heaviside), and rectangular source emission time functions. It evaluates the indoor model in an unoccupied two-bedroom home using cigars and cigarettes as sources with continuous measurements of carbon monoxide (CO), respirable suspended particles (RSP), and particulate polycyclic aromatic hydrocarbons (PPAH). Fine particle mass concentrations (RSP or PM3.5) are measured using real-time monitors. In our experiments, simultaneous measurements of concentrations at three heights in a bedroom confirm an important assumption of the model-spatial uniformity of mixing. The parameter values of the two-compartment model were obtained using a "grid search" optimization method, and the predicted solutions agreed well with the measured concentration time series in the rooms of the home. The door and window positions in each room had considerable effect on the pollutant concentrations observed in the home. Because of the small volumes and low air change rates of most homes, indoor pollutant concentrations from smoking activity in a home can be very high and can persist at measurable levels indoors for many hours.