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.
INTRODUCTIONLocalizing (i.e., locating) toxic air pollutant sources is an important issue in many environment and health-related fields. To minimize the air pollutants' impact on the environment and the public health, it is necessary to identify the releasing sources in a timely fashion so that an effective control strategy can be implemented. For example, in homeland security applications, the release locations of harmful airborne contaminants usually are unknown. Their locations must be estimated from the postrelease concentration observations. 1 Another example is the leak detection of volatile organic compounds (VOCs) from the refinery or petrochemical industries. Detecting the source of a leak from thousands of possible components is always a challenging task; nevertheless, fixing the identified leaking components not only protects public health and the environment but also reduces waste and any potential liability.For a large area, one way to locate the fugitive emission source(s) of hazardous chemicals is placing a matrix of point samplers at the monitoring site. In Chen et al., 2,3 3-hr canister samples were taken from 25 sites inside a petrochemical plant, twice per season for 1 yr. These samples were then analyzed with gas chromatography/ mass spectrometry (GC/MS) according to the U.S. Environmental Protection Agency (E...