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.

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.

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.

Efficacy of using multiple open-path Fourier transform infrared (OP-FTIR) spectrometers in an odor emission episode investigation at a semiconductor manufacturing plant.

This study evaluated the efficacy of simultaneously employing three open-path Fourier transform infrared (OP-FTIR) spectrometers with 3-day consecutive monitoring, using an odor episode as an example. The corresponding monitoring paths were allocated among the possible emission sources of a semiconductor manufacturing plant and the surrounding optoelectronic and electronic-related factories, which were located in a high-tech industrial park. There was a combined total odor rate of 43.9% for the three monitoring paths, each comprised of 736 continuous 5-minute monitoring records and containing detectable odor compounds, such as ammonia, ozone, butyl acetate, and propylene glycol monomethyl ether acetate (PGMEA). The results of the logistic regression model indicated that the prevailing south wind and the OP-FTIR monitoring path closest to the emission source in down-wind direction resulted in a high efficacy for detecting odorous samples with odds ratios (OR) of 3.8 (95% confidence interval (CI): 2.9-5.0) and 5.1 (95% CI: 3.6-7.2), respectively. Meanwhile, the odds ratio for detecting ammonia odorous samples was 7.5 for Path II, which was downwind closer to the possible source, as compared to Path III, downwind far away from the possible source. PGMEA could not be monitored at Path II but could be at Path III, indicating the importance of the monitoring path and flow ejection velocities inside the stacks on the monitoring performance of OP-FTIR. Besides, an odds ratio of 5.1 for odorous sample detection was obtained with south prevailing wind comprising 65.0% of the monitoring time period. In general, it is concluded that OP-FTIR operated with multiple paths simultaneously shall be considered for investigation on relatively complicated episodes such as emergency of chemical release, multiple-source emission and chemical monitoring for odor in a densely populated plant area to enhance the efficacy of OP-FTIR monitoring.

Applying open-path Fourier transform infrared spectroscopy for measuring aerosols.

This paper examines the feasibility of using Open-Path Fourier Transform Infrared Spectroscopy (OP-FTIR) to measure aerosols. The extinction spectra of water, ammonium nitrate, and ammonium sulfate aerosols were first simulated with various particle size distributions (geometric mean ranged from 2 to 10 microm; geometric standard deviation ranged from 1.1 to 2.5) based on the Mie theory. An optimization procedure was developed to retrieve the geometric mean and standard deviation of the aerosols size distributions from the spectra, assuming that the complex refractive index is known. To test sensitivity, we also added 4%, 7%, and 10% noise levels to the spectra and compared the reconstruction results. In the experimental study, water aerosols were generated by a two-fluid nozzle inside a cylindrical chamber (3325 cm(3)). The extinction spectrum was collected with a modified FTIR and the size distribution information was retrieved following the same optimization procedure as the one used in the simulation study. The optimization procedure developed in this study reconstructed the size distribution reasonably well for particles with known refractive index (i.e. homogeneous or internally mixed aerosols). The results were robust with the added noise levels up to 10%, after removing inaccurate estimates with the use of the censoring criteria for reconstructed GSD < 1.3, reconstructed GM < 2.5 microm and GSD < 1.5, and reconstructed GM > 10 microm. With regard to externally mixed aerosols, the reconstructed results were sensitive to the noise within the measuring systems, although most ambient aerosols were internally mixed. The reconstructed size distribution in the chamber experiment had a GM of 3.85 microm and GSD of 1.70. The simulation results were applied to support this reconstruction result. We conclude that OP-FTIR can be used to measure aerosols and screen for the right region for a more detailed aerosol measurement campaign.