Industrial Source Complex Short Term Research Articles

A SIMULATED APPROACH TO ESTIMATING PM10 AND PM2.5 CONCENTRATIONS DOWNWIND FROM COTTON GINS

Cotton gins are required to obtain operating permits from state air pollution regulatory agencies (SAPRA), whichregulate the amount of particulate matter that can be emitted. Industrial Source Complex Short Term version 3 (ISCST3) isthe Gaussian dispersion model currently used by some SAPRAs to predict downwind concentrations used in the regulatoryprocess in the absence of field sampling data. The maximum ambient concentrations for PM10 and PM2.5 are set by theNational Ambient Air Quality Standard (NAAQS) at 150 .g/m3 and 65 .g/m3 (24 h average), respectively. Some SAPRAs usethe NAAQS concentrations as property line concentrations for regulatory purposes. This article reports the results of a uniqueapproach to estimating downwind PM10 and PM2.5 concentrations using Monte Carlo simulation, the Gaussian dispersionequation, the Hino power law, and a particle size distribution that characterizes the dust typically emitted from cotton ginexhausts. These results were then compared to a 10 min concentration (C10) and the concentrations that would be measuredby an FRM PM10 and PM2.5 sampler. The total suspended particulate (TSP) emission rate, particle size distributions, andsampler performance characteristics were assigned to triangular distributions to simulate the real-world operation of the ginand sampling systems. The TSP emission factor given in AP-42 for cotton gins was used to derive the PM mass emission ratefrom a 40 bale/h plant. The Gaussian equation was used to model the ambient TSP concentration downwind from the gin.The performance characteristics for the PM10 and PM2.5 samplers were then used to predict what the measured concentrationwould be for two PSD conditions. The first PSD assumption was that the mass median diameter (MMD) and geometricstandard deviation (GSD) were constant at 12 .m and 2, respectively, and the second scenario assigned a triangulardistribution to the MMD and GSD of {15, 20, 25} .m and {1.8, 2.0, 2.2}, respectively. The results show that the PM2.5 fractionof the dust emitted under either PSD condition was negligible when compared to the NAAQS for PM2.5 of 65 .g/m3. The resultsalso demonstrate that correcting for wind direction changes within the hour using the power law reduces the ambientconcentration by a factor of 2.45.

Assimilative capacity and dispersion of pollutants due to industrial sources in Visakhapatnam bowl area

Abstract The assimilative capacity and the dispersion of pollutants due to industrial sources have been studied in the Visakhapatnam bowl area situated in coastal Andhra Pradesh, India. Visakhapatnam hosts several major industries. These industries contribute significantly to the air pollution in this coastal city. The assimilative capacity of the Visakhapatnam bowl area's atmosphere has been studied using two different approaches in two seasons, namely, summer and winter of 2002–2003. The first approach is based on ventilation coefficient, which is determined through micro-meteorological data, and the second approach is based on pollution potential in terms of concentration of pollutants determined using air pollution dispersion models. The concentrations of two gaseous pollutants sulphur dioxide and oxides of nitrogen have been computed using two models, namely, Gaussian Plume Model (GPM) and Industrial Source Complex Short Term (ISCST-3) model in the Visakhapatnam bowl area in the summer and winter seasons, respectively. The concentrations of the gaseous pollutants have been measured as 8-h averages at 10 monitoring stations in summer season and at 12 monitoring stations in winter season. The computed 8-h averaged concentrations have been compared with those monitored concentrations at different receptors in both the seasons. The validation of the models has been carried out through quantile–quantile (Q–Q) plots and by computing several statistical errors. The results indicate that both models’ predictions have shown a similar trend with those observed concentrations in the study area. The GPM shows a slight overprediction whereas the ISCST-3 model shows an underprediction in comparison with the observed concentrations.

Evaluation of the Industrial Source Complex Short-Term Model: Dispersion over Terrain

Terrain around an air discharge source can have several influences on diffusion, the pattern of plume dispersion, the wind flow, and the turbulence characteristics. The Industrial Source Complex Short-Term (ISCST) model contains simple algorithms to attempt to account for the effects of terrain. The model has the ability to analyze concentrations in any type of terrain by using the terrain options available for running the model. In this study, the ISCST model was adopted to predict the concentration of sulfur dioxide (SO2) in and around the Mina Al-Fahal refinery in Oman. The central purpose of the study was to examine the performance of the ISCST model in predicting SO2 concentrations under two different scenarios: (1) when flat terrain was assumed; and (2) when the terrain descriptions were addressed. The results of these two scenarios were validated against SO2 monitoring data. The comparison showed that the model underestimated the observed concentrations for the two scenarios. However, the predicted concentrations of SO2 in the absence of the terrain scenario were in better agreement with the observations. Furthermore, the predicted SO2 concentrations were found to be lower than the World Health Organization guideline values, with the maximum concentrations found to occur relatively close to the sources of emission.

Allocation of onroad mobile emissions to road segments for air toxics modeling in an urban area

Dispersion models are useful tools for setting emission control priorities and developing strategies for reducing air toxics emissions. Previous methodologies for modeling hazardous air pollutant emissions for onroad mobile sources are based on using spatial surrogates to allocate county level emissions to grid cells. A disadvantage of this process is that it spreads onroad emissions throughout a grid cell instead of along actual road locations. High local concentrations may be underestimated near major roadways, which are often clustered in urban centers. Here, we describe a methodology which utilizes a Geographic Information System to allocate benzene emissions to major road segments in an urban area and model the segments as elongated area sources. The Industrial Source Complex Short Term dispersion model is run using both gridded and link-based emissions to evaluate the effect of improved spatial allocation of emissions on ambient modeled benzene concentrations. Allocating onroad mobile emissions to road segments improves the agreement between modeled concentrations when compared with monitor observations, and also results in higher estimated concentrations in the urban center.

Impact of Polycyclic Aromatic Hydrocarbon Emissions from Medical Waste Incinerators on the Urban Atmosphere

In this study, polycyclic aromatic hydrocarbon (PAH) emissions from two batch-type medical waste incinerators (MWIs), one with a mechanical grate and the other with a fixed grate, both operated by a medical center, were assessed. Both MWIs shared the same air-pollution control devices (APCDs), with an electrostatic precipitator and a wet scrubber installed in series. Results show that when APCDs were used, total PAHs and total benzo- [a]pyrene equivalent (total BaPeq) emission concentrations of both MWIs were reduced from 2220 to 1870 µg/m3 and 50 to 12.4 µg/m3, respectively. We used the Industrial Source Complex Short Term model (ISCST) to estimate the ground-level concentrations of the residential area and the traffic intersection located at the down-wind side of the two MWIs. For the traffic intersection, we found both total PAHs and total BaPeq transported from MWIs to both studied areas were not significant. For the residential area, similar results were found when APCDs were used in MWIs. When APCDs were not included, we found that total PAHs transported from MWIs accounted for <12%, but total BaPeq accounted for >90%, of the on-site measured concentrations. These results suggest that the use of proper APCDs during incineration would significantly reduce the carcinogenic potencies associated with PAH emissions from MWIs to the residential area.

An Application of Geographic Information System (GIS) to a Fictitous Thermal Power Plant in Mersin, Türkiye: An Application of Dispersion Modelling Coupled with GIS

In this study, local air quality impacts of a proposed conventionalcoal-fired power plant in the Icel region has been investigated using numerical dispersion modeling studies coupled with a GIS application. Within the impact area of the facility, Industrial Source Complex Short Term (ISCST2) dispersion model has been used to estimate ground-level concentrations of air pollutants originating from the power plant. For the same impact area, GIS applications have been utilised to determine the agricultural yield distribution. For this purpose, relevant satellite images were digitised, classified and statistically analyzed. Based on the predicted ground-level pollutant concentrations and sensitivity of the agricultural crops to the pollutants, agricultural yield loss was estimated for the impact area.The results have been quantified and valuated in monetary terms for the purpose of performing an environmental cost benefit analysis. Comparison of the conventional cost benefit analysis with the environmental cost benefit analysis showed the significance of the external cost of the proposed facility, resulting from the environmental damages.

Uncertainty analysis in air dispersion modeling

The Taylor series approach for uncertainty analyses is advanced as an efficient method of producing a probabilistic output from air dispersion models. A probabilistic estimate helps in making better-informed decisions when compared to results of deterministic models. In this work, the Industrial Source Complex Short Term (ISCST) model is used as an analytical model to predict pollutant transport from a point source. First- and second-order Taylor series approximations are used to calculate the uncertainty in ground level concentrations of ISCST calculations. The results of the combined ISCST and uncertainty calculations are then validated with traditional Monte Carlo (MC) simulations. The Taylor series uncertainty estimates are a function of the variance in input parameters (wind speed and temperature) and the model sensitivities to input parameters. While the input variance is spatially invariant, sensitivity is spatially variable; hence the uncertainty in modeled output varies spatially. A comparison with the MC approach shows that uncertainty estimated by first-order Taylor series is found to be appropriate for ambient temperature, while second-order Taylor series is observed to be more accurate for wind speed. Since the Taylor series approach is simple and time-efficient compared to the MC method, it provides an attractive alternative.

Monitoring of nitrogen dioxide in and around an Oman liquid natural gas plant using passive diffusion tubes: exposure and ISCST model study

Recognising that nitrogen dioxide (NO2) may be the primary air contaminant released from an Oman liquid natural gas (LNG) plant, this study has been designed with emphasis on this pollutant. The dispersion of NO2 was examined and compared with measured data during the period from 23 February to 1 April 2001. The observed concentrations were obtained by using NO2 diffusion tubes to monitor the spatial distribution of NO2 concentrations around at four sites downwind of the plant site. The Industrial Source Complex Short-Term (ISCST) dispersion model was used to predict concentrations at the same sites and for the same time period. Evaluation of the results showed that the model predicted concentrations lower than those observed. However, the comparisons showed that the relationship between the modelled and measured concentrations was consistent. The model also allows the detailed description of predicted concentrations in contour map form. Generally, the predicted concentrations were found to be lower than the permissible limit values, with the maximum ground-level concentrations being found much closer to the plant. On the basis of this study, it can be stated that the Oman LNG plant would not cause any significant deterioration in air quality.

Application of an ISCST3 model for predicting urban air pollution in the Izmir metropolitan area

A Gaussian atmospheric dispersion model, Industrial Source Complex Short Term (ISCST3), was used to estimate ground-level concentrations of sulphur dioxide (SO2) emitted from source categories of industrial and domestic heating in the city of Izmir, Turkey. Predictions were estimated for the year 2000 across a study area of 80 km x 100 km. Statistical analyses were carried out to evaluate the model performance by comparing predicted and observed SO2 concentrations at four ambient air quality monitoring stations using two main methods root mean square error (RMSE) and an index of agreement (d). The results showed that industry was found as the most air-polluting sector and industries located at outside of the metropolitan area were found to carry important risks for urban air quality. The most polluted area was found at a distance of about 1 km from a major petroleum refinery and a large petrochemical industry.

Patterns of SO 2 emissions: a refinery case study

Air quality modelling is an essential tool for most air pollution studies and the introduction of SO 2 standards creates a need for modelling the dispersion of SO 2. This work deals specifically with the use of the Industrial Source Complex Short Term (ISCST) model at a refinery. The study is performed over a period of 21 days. The first objective of this study was to measure the atmospheric levels of SO 2 and then to compare their values with the international standard limits. The second objective was to evaluate the ISCST model by comparing the calculated and measured concentrations. The third objective was to demonstrate the effect of wind regimes on the dispersion of SO 2 and to determine the spatial distribution of SO 2 over the modelled area. The results showed that the levels of SO 2 were well below the ambient air quality standard. Based on isopleths for SO 2 distribution in the study area (as output from the ISCST model), it can be stated that no health risk is present in areas adjacent to the refinery.

Environmental Impact Assessment For Oman LNG Expansion Project: NO 2 Air Quality Analysis with A Proposal For A Third Train

Oman entered the LNG market (liquefied Natural Gas) in April 2000 with the first shipment to South Korea. Oman LNG plant is currently producing 6.6 million metric tonne per annum from two trains. However, there are plans for expansion of the plant to increase its existing capacity by adding one more gas liquefaction train (train 3). The purpose of this study is to assess the potential environmental air quality impacts arising from the construction and operation of train 3. The article contains a baseline-survey of the existing environment, the proposed project description and prediction of the possible future air quality impacts of this project on the existing community and its environment. Recognizing that nitrogen dioxide (NO 2 ) may be the primary air contaminant released from Oman LNG plant, this work has been designed with emphasis on this pollutant. The environmental impact assessments including an air quality analysis in terms of NO 2 has been conducted by using the Industrial Source Complex Short-Term (ISCST) dispersion model. The results are presented in contour map forms to determine the spatial distribution of NO 2 to be produced when train 3 is operating. The study indicates that the highest NO 2 concentration values will be observed in the summer months (June, July and August). Generally, the predicted concentrations are found much lower than the permissible limit values with the maximum ground level concentrations being found much closer to the plant. On the basis of this study it can be stated that the Oman LNG plant, after the addition of train 3, is not likely to cause significant deterioration in air quality.

Odor investigation and control at a WWTP in orange county, florida

AbstractDue to occasional complaints of odors from residential and commercial neighbors, and the projected development of adjacent vacant land, an investigation was conducted at a county wastewater treatment plant (WWTP) Utilizing a physical survey of possible odor sources, an emissions measurement study, and dispersion modeling, the site was assessed for current and future odor impacts. The main compound contributing to odors was concluded to be hydrogen sulfide (H2S). Using the EPA dispersion model Industrial Source Complex Short Term (ISCST3) and ten years of meteorological data, the H2S emissions results were analyzed to estimate potential maximum H2S concentrations, as well as the annual frequency of occurrences of H2S above certain concentrations. The chief source of odor impacts was identified as fugitive emissions from the top of the grit chamber/flow splitter building, through openings for valve stems, flow gates, and the grit removal conveyor apparatus. Another ventilation fan was added, and the H2S‐laden air from the building was routed through new biofiltration units, which were being evaluated to replace an older caustic/chlorine scrubber. Since these units operated at an extremely high H2S removal efficiency, it was concluded that biofilters would replace caustic/chlorine scrubbing on a permanent basis.

PM10 Dispersion Modeling for Treasure Valley, Idaho

ABSTRACT The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.

Measured and predicted airshed concentrations of methyl bromide in an agricultural valley and applications to exposure assessment

A field study was conducted in September 1995 to measure the ambient atmospheric concentrations of methyl bromide (MeBr) in the Salinas Valley, California. Air concentrations of MeBr were measured at 11 sites located on the adjacent mountains, valley floor and at the Pacific Ocean coast over a 4-d period. The concentrations ranged up to 8.98 μg m −3. Industrial Source Complex Short Term 3 (ISCST3) and CALPUFF dispersion model simulations were performed with several fumigated fields serving as sources, using two estimates of source strengths from published flux values. CALPUFF was driven by 3D meteorology from CALMET. With the lower of the two estimates, the ISCST3 model underpredicted concentrations for 76% of data and averaged 66% of measured, and the CALPUFF model also underpredicted concentrations for 67% of observations and averaged 84% of measured. With the higher of the two estimates the ISCST3 overpredicted by a factor of two for 67% of data, and CALPUFF overpredicted concentrations by a factor of 1.6 for over 50% of data. Between the model predicted and measured concentrations, the coefficient of determination, R 2 , was ≈0.7 for both source strengths with ISCST3 model. The R 2 with CALPUFF model was 0.55 and 0.82 with source strength estimated from two prior flux studies. The margin of exposure (MOE) for the population of the city of Salinas was calculated based on the measured ambient concentrations and compared with the current benchmark used by US-EPA and California Department of Pesticide Regulation for acceptable human health risk. Based on the models predicted worst-case exposure concentration, the MOE for acute effects was approximately 10,000. For chronic effects it was approximately 100, indicating a need for attention to exposure to MeBr in areas of intense methyl bromide use.

Mapping the air in real-time to visualize the flow of gases and vapors: occupational and environmental applications.

This article describes a new method for measuring and mapping pollutants in air in real-time which can be used for visualizing the flow of gases and vapors in both indoor industrial and outdoor environmental applications. This method uses open-path Fourier Transform Infrared (OP-FTIR) spectrometry and computed tomography for real-time mapping of concentrations of chemicals in air. These maps may be used to evaluate human exposures, source emissions and air dispersion models; thus, this method can be used for both industrial and environmental sampling. It is being developed using computer simulations, and chamber and field studies. Computer simulations used simulated test concentration data to create maps; the original maps of concentrations were compared with the tomographic reconstructed maps. In the chamber studies, tracer gas was released into the chamber and measurements from a tomographic system were compared with point sample measurements taken at the same time. When sulfur hexafluoride was injected in a stable flow field position in the chamber, the concentrations reconstructed by the concentration maps were within +/- 15.9 percent of the measured point samples; overall, they were within +/- 27 percent of the measured point samples. On a 12-foot by 14-foot grid of cells used to model the chamber, the average peak location error was within one foot. The peak location error refers to the error involved in locating the point of highest concentration in the plume. For the field study, field-generated tomographic maps were compared with concentrations estimated using the Industrial Source Complex-Short Term (ISCST) model. Fairly good correlation (R2 = 0.67) was found between the five-minute overall-average cell concentrations in the tomographic and ISCST model maps. Overall, the tomographic map concentrations over-predicted the ISCST model concentrations by 24 percent. Optical remote sensing and computed tomography shows promise as a method to produce spatially and temporally resolved two-dimensional concentration maps indoors and outdoors. These maps would provide near real-time visualization of contaminant generation, movement, concentrations, and emission rates for multiple chemicals simultaneously at low limits of detection.

Development, Evaluation, and Application of a Primary Aerosol Model

ABSTRACT The Segmented-Plume Primary Aerosol Model (SPPAM) has been developed over the past several years. The earlier model development goals were simply to generalize the widely used Industrial Source Complex Short-Term (ISCST) model to simulate plume transport and dispersion under light wind conditions and to handle a large number of roadway or line sources. The goals have been expanded to include development of improved algorithm for effective plume transport velocity, more accurate and efficient line and area source dispersion algorithms, and recently, a more realistic and computationally efficient algorithm for plume depletion due to particle dry deposition. A performance evaluation of the SPPAM has been carried out using the 1983 PNL dual tracer experimental data. The results show the model predictions to be in good agreement with observations in both plume advection-dispersion and particulate matter (PM) depletion by dry deposition. For PM2.5 impact analysis, the SPPAM has been applied to the Rubidoux area of California. Emission sources included in the modeling analysis are: paved road dust, diesel vehicular exhaust, gasoline vehicular exhaust, and tire wear particles from a large number of roadways in Rubidoux and surrounding areas. For the selected modeling periods, the predicted primary PM2.5 to primary PM10 concentration ratios for the Rubidoux sampling station are in the range of 0.39–0.46. The organic fractions of the primary PM2.5 impacts are estimated to be at least 34–41%. Detailed modeling results indicate that the relatively high organic fractions are primarily due to the proximity of heavily traveled roadways north of the sampling station. The predictions are influenced by a number of factors; principal among them are the receptor locations relative to major roadways, the volume and composition of traffic on these roadways, and the prevailing meteorological conditions.

A field study using open-path FTIR spectroscopy to measure and map air emissions from volume sources

Open-path Fourier transform infrared (OP-FTIR) spectroscopy is a relatively new measurement technique offering advantages over traditional point samples for monitoring air contaminants and validating dispersion models. In addition, this technology has the potential to produce temporally and spatially resolved chemical concentration maps. In this study, OP-FTIR spectrometer measurements and point samplers were used to evaluate two short-term refined Gaussian dispersion models for predicting the fate of volume source emissions. Additionally, these data were used for a pilot Environmental CAT scanning system using two scanning OP-FTIR spectrometers and eight retroreflectors. An environmental CAT scanning system processes a network of intersecting OP-FTIR spectrometers using a tomographic reconstruction algorithm. When the algorithm is applied to these real-time measurements, two-dimensional chemical concentration maps are created of the area. This technique is noninvasive and is capable of providing real-time spatially and temporally resolved concentration maps of multiple chemicals simultaneously and at low limits of detection (ppb–low ppm). Near real-time chemical concentration maps were generated for the entire field site, and the concentration maps were compared with model maps with respect to plume location and plume shape. We evaluated the Industrial Source Complex–Short Term (Version 3) (ISCST) model and the American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee (AERMOD) model. Sulfur hexafluoride was released at known rates from a simulated volume source and was measured at various points in the study field with the use of a network of Tedlar® bag point samples and OP-FTIR spectrometer measurements. Both ISCST and AERMOD underpredicted SF6 concentrations when compared to the 5-min averaged OP-FTIR spectrometer measurements (1.3x) and the 1-h integrated Tedlar® bag samples (1.4x). For most time periods, the tomographic concentration maps compared fairly well with the model predictions in terms of plume shape and location. The tomographic maps tracked the impact of changing wind direction better than the model predictions. © 1999 John Wiley & Sons, Inc. Field Analyt Chem Technol 3: 69–79, 1999

A multiple source approach to acute human health risk assessments

The US Army Center for Health Promotion and Preventive Medicine (USACHPPM) has developed a three-tiered approach to perform an acute noncarcinogenic health risk assessment to comply with requirements contained in USEPA’s ‘Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions' (USEPA, Draft strategy for combustion of hazardous waste, May 1993). The addendum document drafted in November 1993 suggests evaluation of short-term emissions and exposures, but it does not provide necessary guidance or methodology. This evaluation becomes extremely complex when several sources contribute to the overall concentration of contaminants in the air. Because each source has a different emission rate, location, and dispersion profile, the compound-specific maximum concentrations are rarely located at the same receptor location, as determined by using the Industrial Source Complex Short Term (ISCST3) dispersion model. Furthermore, evaluation of hazard quotients at various receptor locations from a large number of contaminants from multiple sources is an extremely complex and tedious process. This paper will detail a three-tiered approach which was developed to perform the acute risk assessment, quantify possible advantages and disadvantages associated with each tier, and demonstrate the effects of contributing factors, such as distance, emission rate variability, population/exposure scenarios, and compound speciation. In order to accomplish this task, a sample facility with four different combustion sources was modeled and processed according to the three-tiered approach.

Evaluation of Three Air Dispersion Models: ISCST2, ISCLT2, and Screen2 for Mercury Emissions in an Urban Area

The goal of this paper is to compare and evaluate the performance of three air quality regulatory models for mercury releases. The models include Industrial Source Complex Short Term model (ISCST2), Industrial Source Complex Long Term model (ISCLT2), and SCREEN2. The evaluation is conducted in multiple point source urban environment using meteorological data, emission inventory and monitoring data for eight stations for the year 1990 to 1992. The performance of the models is evaluated using eight statistical parameters. The comparison of models results for both quarterly and annual averaging periods shows that ISCST2 predictions qualitatively match the observed concentrations; whereas SCREEN2 predicts highest concentrations and ISCLT2 the lowest concentrations. The summary of statistical analysis obtained by using three different methods of observed concentration (Co) and predicted concentrations (Cp) comparison show that the ISCST2 has a better overall performance than ISCLT2 and SCREEN2 models. However, none of the models met the criteria for a reasonable model. Summaries of 95% confidence limits on normalize mean square error (NMSE), geometric mean variance (VG) and geometric mean bias (MG) for each and among model indicate that of the three models, ISCST2 has the best overall performance indicators. Improved model performance may be achieved by incorporating different types of mercury forms into emission rate and air dispersion calculations.

Prediction of Methyl Bromide Flux from Area Sources Using the ISCST Model

AbstractGrowing concern about atmospheric exposure of humans to pesticides has led to increased air monitoring in California. Air monitoring data typically consist of measurements made downwind from point or area sources. The utility of monitoring at fixed stations is limited for establishing buffer zones to protect neighboring populations from pesticide exposure. A modeling approach designed to use these data would provide the flexibility needed to establish buffer zones. The Industrial Source Complex Short Term (ISCST) model is a gaussian plume dispersion model that predicts air concentrations around point or area sources using emission rates (flux) and meteorological conditions as model inputs. The flux data, however, are typically not collected in the field nor available in the literature. In order to use the field data currently available, we developed a procedure using methyl bromide (MeBr) concentrations around two area sources and the ISCST model, to back‐calculate flux. In addition, MeBr flux was measured concurrently by cooperators conducting an independent study. Air concentrations, together with actual meteorological data, were used as inputs to the ISCST model. Flux of MeBr was then back‐calculated using a two step process: (i) an arbitrary flux value of 100 µg m−2 s−1 was used as an initial input value. Resultant air concentrations predicted by the model were then regressed on air concentrations measured offsite and (ii) the resultant regression coefficient was then used to adjust the arbitrary flux to a back‐calculated flux. Using another regression analysis, back‐calculated and measured flux rates were found to be significantly correlated, indicating this approach may be suitable for indirect estimation of flux. Implications for the use of this method in establishing buffer zones designed to protect human health are discussed.