Refining emission rate estimates using a coupled receptor–dispersion modeling approach

Receptor modeling techniques like chemical mass balance are used to attribute pollution levels at a point to different sources. Here we analyze the composition of particulate matter and use the source profiles of sources prevalent in a region to estimate quantitative source contributions. In dispersion modeling on the other hand the emission rates of various sources together with meteorological conditions are used to determine the concentrations levels at a point or in a region. The predictions using these two approaches are often inconsistent. In this work these differences are attributed to errors in emission inventory. Here an algorithm for coupling receptor and dispersion models is proposed to reduce the differences of the two predictions and determine the emission rates accurately. The proposed combined approach helps reconcile the differences arising when the two approaches are used in a stand-alone mode. This work is based on assuming that the models are perfect and uses a model-to-model comparison to illustrate the concept.     

An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

Modelling base cations in Europe—sources,transport and deposition of calcium

The deposition of the base cations calcium, magnesium and potassium from the atmosphere needs to be quantified in the calculation of the total deposited acidity in the critical loads approach. Of these base cations, calcium has been found to be the most important in terms of mass deposited. However, the sources of calcium to the atmosphere are not well understood. Recently, the first spatially disaggregated inventory of industrial calcium emissions for Europe was presented by Lee and Pacyna (1998) who estimated a total European emission of 0.7–0.8 Mt yr^-1. However, it is thought that wind blown dust from soils contributes a substantial fraction to the deposition of calcium. In this work, the source strength of calcium from arid regions within the EMEP modelling domain was estimated using the global mineral dust emission data base of Tegen and Fung (1994) and an estimation of the calcium content of soils. This results in a “natural” calcium emission of 6 Mt yr^-1. A long-range transport model, TRACK, was used to calculate the wet and dry deposition of calcium arising from these industrial and natural sources to the UK which resulted in a total deposition of 29–30 kt yr^-1. Of this annual deposition, 0.6–0.7 kt arises from cement manufacturing, 0.02–0.03 kt from iron and steel manufacturing, 0.8–0.83 kt from a large point source power generation, and 28 kt from power generation from a small boiler plant. The natural emissions of calcium from arid regions result in a deposition of calcium to the UK of 0.5 kt yr^-1. The measured wet deposition of calcium to the UK is 89 kt yr^-1 and the estimated dry deposition 14 kt yr^-1. The short-fall in the modelled deposition of calcium is thus of the order of 70 kt yr^-1, which is suggested to arise from wind-blown dust from agricultural land in the UK and mainland Europe. The estimated emissions, and thus modelled deposition are rather uncertain, such that estimating deposition of calcium attributable to agricultural soil emissions by differencing has a large uncertainty. However, this is the first such study of its kind for Europe and represents a first step towards understanding the sources of calcium and their contribution to mitigating deposited acidity from acidifying pollutants such as sulphur dioxide, nitrogen oxides and ammonia.     

Approaches for quantifying reactive and low-volatility biogenic organic compound emissions by vegetation enclosure techniques - part A

The high reactivity and low vapor pressure of many biogenic volatile organic compounds (BVOC) make it difficult to measure whole-canopy fluxes of BVOC species using common analytical techniques. The most appropriate approach for estimating these BVOC fluxes is to determine emission rates from dynamic vegetation enclosure measurements. After scaling leaf- and branch-level emission rates to the canopy level, these fluxes can then be used in models to determine BVOC influences on atmospheric chemistry and aerosol processes. Previously published reports from enclosure measurements show considerable variation among procedures with limited guidelines or standard protocols to follow. This article reviews this literature and describes the variety of enclosure types, materials, and analysis techniques that have been used to determine BVOC emission rates. The current review article is followed by a companion paper which details a comprehensive enclosure technique that incorporates both recommendations from the literature as well as insight gained from theoretical calculations and practical experiences. These methods have yielded new BVOC emission data for highly reactive monoterpenes (MT) and sesquiterpenes (SQT) from a variety of vegetation species.     

Optimizing best management practices to control anthropogenic sources of atmospheric phosphorus deposition to inland lakes

Excessive phosphorus loading to inland freshwater lakes around the globe has resulted in nuisance plant growth along the waterfronts, degraded habitat for cold-water fisheries, and impaired beaches, marinas, and waterfront property. The direct atmospheric deposition of phosphorus can be a significant contributing source to inland lakes. The atmospheric deposition monitoring program for Lake Simcoe, Ontario, indicates roughly 20% of the annual total phosphorus load (2010–2014 period) is due to direct atmospheric deposition (both wet and dry deposition) on the lake. This novel study presents a first-time application of the genetic algorithm (GA) methodology to optimize the application of best management practices (BMPs) related to agriculture and mobile sources to achieve atmospheric phosphorus reduction targets and restore the ecological health of the lake. The novel methodology takes into account the spatial distribution of the emission sources in the airshed, the complex atmospheric long-range transport and deposition processes, cost and efficiency of the popular management practices, and social constraints related to the adoption of BMPs. The optimization scenarios suggest that the optimal overall capital investment of approximately $2M, $4M, and $10M annually can achieve roughly 3, 4, and 5 tonnes reduction in atmospheric P load to the lake, respectively. The exponential trend indicates diminishing returns for the investment beyond roughly $3M per year and that focusing much of this investment in the upwind, nearshore area will significantly impact deposition to the lake. The optimization is based on a combination of the lowest cost, most beneficial and socially acceptable management practices that develops a science-informed promotion of implementation/BMP adoption strategy. The geospatial aspect to the optimization (i.e., proximity and location with respect to the lake) will help land managers to encourage the use of these targeted best practices in areas that will most benefit from the phosphorus reduction approach.

Implications: Excessive phosphorus loading to inland freshwater lakes around the globe has resulted in nuisance plant growth along the waterfronts, degraded habitat for cold water fisheries, and impaired beaches, marinas and waterfront property. This novel study presents a first-time application of the Genetic Algorithm methodology to optimize the application of best management practices related to agriculture and mobile sources to achieve atmospheric phosphorus reduction targets and restore the ecological health of the lake. The novel methodology takes into account the spatial distribution of the emission sources in the airshed, the complex atmospheric long-range transport and deposition processes, cost and efficiency of the popular management practices and social constraints related to the adoption of BMPs.     

A Simple Neural Network for Estimating Emission Rates of Hydrogen Sulfide and Ammonia from Single Point Sources

Abstract

Neural networks have shown tremendous promise in modeling complex problems. This work describes the development and validation of a neural network for the purpose of estimating point source emission rates of hazardous gases. This neural network approach has been developed and tested using experimental data obtained for two specific air pollutants of concern in West Texas, hydrogen sulfide and ammonia. The prediction of the network is within 20% of the measured emission rates for these two gases at distances of less than 50 m. The emission rate estimations for ground level releases were derived as a function of seven variables: downwind distance, crosswind distance, wind speed, downwind concentration, atmospheric stability, ambient temperature, and relative humidity. A backpropagation algorithm was used to develop the neural network and is also discussed here. The experimental data were collected at the Wind Engineering Research Field Site located at Texas Tech University in Lubbock, Texas. Based on the results of this study, the use of neural networks provides an attractive and highly effective tool to model atmospheric dispersion, in which a large number of variables interact in a nonlinear manner.     

Air Levels and Mutagenicity of PM-10 in an Indoor Ice Arena

Abstract

Hazardous waste sites and industrial facilities contain area sources of fugitive emissions. Emission rate measurements or estimates are necessary for air pathway assessments for these sources. Emission rate data can be useful for the design of emission control and remediation strategies as well as for predictive modeling for population exposure assessments. This paper describes the use of a direct emission measurement approach – the enclosure approach using an emission isolation flux chamber – to measure emission rates of various volatile organic compounds (VOCs) from contaminated soil and water. A variety of flux chamber equipment designs and operating procedures have been employed by various researchers. This paper contains a review of the design and operational variables that affect the accuracy and precision of the method. Guidance is given as to the optimum flux chamber design and operating conditions for various types of emission sources. Also presented is a generic quality control program that gives the minimum number of duplicate, blank, background, and repeat samples that should be performed.     

Correlating Emissions with Time and Temperature to Predict Worst-Case Emissions from Open Liquid Area Sources

Abstract

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry’s law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H₂S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H₂S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85–90 °F), the constant emission rate underestimated odor impact significantly (by 73%).     

Odor measurements for manure spreading using a subsurface deposition applicator

Odor emissions during manure spreading events have become a source of concern, particularly where farms are located nearby urban areas. The objective of the present study was to compare odor concentrations and odor emission rates due to pig manure application using two different types of applicators, a sub-surface deposition system and a conventional splash-plate applicator. Air samples were collected using a Surface Isolation Flux Chamber and the "bag-in-vacuum chamber" techniques, at 0.5, 1.5 and 2.5 hours after manure application. A three-station forced-choice dynamic dilution olfactometer was used by an odor panel for determining odor concentration. Preliminary results indicated that with the sub-surface deposition system applicator odor emission rate was reduced by 8% to 38% compared to that of the conventional splash-plate applicator. The highest reduction in odor strength and odor emission rate was observed in the most offensive period after manure application. The sub-surface deposition system may be a solution for hog producers who wish to reduce odor complaints from applying manure without the cost and problems associated with deep injection systems.     

Quantification of sources of PCBs to the atmosphere in urban areas: A comparison of cities in North America, Western Europe and former Yugoslavia

We present estimated emission source strengths of seven polychlorinated biphenyl (PCB) congeners for Banja Luka, a city that was affected by the civil war in Bosnia and Hercegovina (former Yugoslavia) in the 1990s. These emission estimates are compared to PCB emission rates estimated for the cities of Zurich, Switzerland, and Chicago, USA using an approach that combines multimedia mass balance modeling and measurement data. Our modeled per-capita emission estimates for Banja Luka are lower by a factor of ten than those for Zurich and Chicago, which are similar. This indicates that the sources of PCB emissions in Banja Luka are likely to be weaker than in the Western European and North American cities which show relatively high PCB emissions. Our emission rates from the three cities agree within a factor of ten with emission estimates from a global PCB emission inventory derived from production and usage estimates and emission factors.     

Transient analysis of volatile organic compound concentrations for estimating emission rates

While emission rates of volatile organic compounds (VOCs) have been obtained for building materials, furnishings and processes in chambers, field measurements are more difficult. Procedures to estimate emission rates using transient analysis of VOC concentrations are described and applied in a two-story classroom/office building. The analysis employs semi-real-time VOC concentrations determined with a portable GC/FID and simultaneous air change rate measurements using tracer gas decay. The results of the analysis yield consistent values of emission rates for building materials ranging from 0.20 to 0.40 mg m⁻² h⁻¹ when normalized by floor area. Occupancy-related emissions were more difficult to estimate and covered a wider range from roughly 0.1 to 1.5 mg m⁻² h⁻¹. The test data were also analyzed in an attempt to determine sink parameters, but these efforts were not particularly successful. Furthermore, in these tests, the inclusion of sink effects did not significantly impact the estimated emission rates. While this paper offers a transient analysis approach that may lead to improved field estimates of VOC emission rates, it is not presented as a definitive methodology. Nevertheless, transient analysis has potential for use in other buildings, but simultaneous air change rate measurements are critical in its application in estimating VOC emission rates in the field.     

Source attribution for mercury deposition in the contiguous United States: regional difference and seasonal variation

Quantifying the contribution of emission sources responsible for mercury deposition in specific receptor regions helps develop emission control strategies that alleviate the impact on ecosystem and human health. In light of the maximum available control technology (MACT) rules proposed by U.S. Environmental Protection Agency (EPA) and the ongoing intergovernmental negotiation coordinated by United Nations Environmental Programme (UNEP) for mercury, the Community Multiscale Air Quality Modeling System (CMAQ-Hg) was applied to estimate the source contribution in six subregions of the contiguous United States (CONUS). The considered source categories include electric generating units (EGU), iron and steel industry (IRST), other industrial point sources excluding EGU and IRST (OIPM), the remaining anthropogenic sources (RA), natural processes (NAT), and out-of-boundary transport (BC). It is found that, on an annual basis, dry deposition accounts for two-thirds of total annual deposition in CONUS (474 Mg yr(-1)), mainly contributed by reactive gaseous mercury (about 60% of total deposition). The contribution from large point sources can be as high as 75% near the emission sources (< 100 km), indicating that emission reduction may result in direct deposition decrease near the source locations. Out-of-boundary transport contributes from 68% (Northeast) to 91% (West Central) of total deposition. Excluding the contribution from out-of boundary transport, EGU contributes to about 50% of deposition in the Northeast, Southeast, and East Central regions, whereas emissions from natural processes are more important in the Pacific and West Central regions (contributing up to 40% of deposition). This suggests that the implementation of the new EPA MACT standards will significantly benefit only these three regions. Emission speciation is a key factor for local deposition. The source contribution exhibits strong seasonal variation. Deposition is greater in warm seasons due to stronger Hg0 oxidation. However, the contribution from anthropogenic sources is smaller in warm seasons because of larger emissions from natural processes and stronger vertical mixing that facilitates transport.     

The effect of variable sub-grid deposition factors on the results of the lagrangian long-range transport model of EMEP

The EMEP/MSC-W routine model for long-range atmospheric transport of sulphur and nitrogen includes a correction for the unresolved sub-grid-scale deposition in emission grid-squares. A constant fraction of the emissions is assumed to be directly deposited inside the first grid-square. Experiments have been performed to estimate the effects of using factors which vary with emission height and meteorological conditions. Results indicate that the constant local deposition factor used for sulphur dioxide in the routine model, is an overestimate, in particular for high-level emission sources. The change in annual deposition caused by the new local deposition factor for sulphur dioxide, is most clearly seen as a decreased deposition in the grid-squares with the largest emissions such as due for the former German Democratic Republic. The amount of this decrease strongly depends on the source height distribution. With the presently available emission data, a decrease of maximum 36% can be expected in individual grid squares. In grid-squares dominated by transboundary deposition, the increase is typically lower than 10%.     

A modal approach to vehicular emissions and fuel consumption model development

This study reports on the analysis of emissions and fuel consumption from motor vehicles using a modal approach. The four standard driving modes are idling, accelerating, cruising, and decelerating. On-road data were collected using instrumented test vehicles traveling many times through the urban areas of Hong Kong. A model was developed for estimating vehicular fuel consumption and emissions as a function of instantaneous speed and driving mode. Piecewise interpolation functions were proposed for each nonidling driving mode. Idling emission and fuel consumption rates were estimated as negative exponential functions of idling time. Preliminary modeling results showed good agreements for the test vehicles and indicated that the on-road measurements are feasible for the development of modal emission and fuel consumption models.     

Real-world emissions of in-use off-road vehicles in Mexico

Off-road vehicles used in construction and agricultural activities can contribute substantially to emissions of gaseous pollutants and can be a major source of submicrometer carbonaceous particles in many parts of the world. However, there have been relatively few efforts in quantifying the emission factors (EFs) and for estimating the potential emission reduction benefits using emission control technologies for these vehicles. This study characterized the black carbon (BC) component of particulate matter and NOx, CO, and CO₂ EFs of selected diesel-powered off-road mobile sources in Mexico under real-world operating conditions using on-board portable emissions measurements systems (PEMS). The vehicles sampled included two backhoes, one tractor, a crane, an excavator, two front loaders, two bulldozers, an air compressor, and a power generator used in the construction and agricultural activities. For a selected number of these vehicles the emissions were further characterized with wall-flow diesel particle filters (DPFs) and partial-flow DPFs (p-DPFs) installed. Fuel-based EFs presented less variability than time-based emission rates, particularly for the BC. Average baseline EFs in working conditions for BC, NOx, and CO ranged from 0.04 to 5.7, from 12.6 to 81.8, and from 7.9 to 285.7 g/kg-fuel, respectively, and a high dependency by operation mode and by vehicle type was observed. Measurement-base frequency distributions of EFs by operation mode are proposed as an alternative method for characterizing the variability of off-road vehicles emissions under real-world conditions. Mass-based reductions for black carbon EFs were substantially large (above 99%) when DPFs were installed and the vehicles were idling, and the reductions were moderate (in the 20–60% range) for p-DPFs in working operating conditions. The observed high variability in measured EFs also indicates the need for detailed vehicle operation data for accurately estimating emissions from off-road vehicles in emissions inventories.

Implications: Measurements of off-road vehicles used in construction and agricultural activities in Mexico using on-board portable emissions measurements systems (PEMS) showed that these vehicles can be major sources of black carbon and NO_X. Emission factors varied significantly under real-world operating conditions, suggesting the need for detailed vehicle operation data for accurately estimating emissions inventories. Tests conducted in a selected number of sampled vehicles indicated that diesel particle filters (DPFs) are an effective technology for control of diesel particulate emissions and can provide potentially large emissions reduction in Mexico if widely implemented.     

Resolving neighborhood scale in air toxics modeling: a case study in Wilmington, CA

Air quality modeling is useful for characterizing exposures to air pollutants. Whereas models typically provide results on regional scales, new concerns regarding the potential for differential exposures among racial/ethnic populations and income strata within communities are driving the need for increasingly refined modeling approaches. These approaches need to be capable of resolving concentrations on the scale of tens of meters, across modeling domains 10-100 km2 in size. One approach for refined air quality modeling is to combine Gaussian and regional photochemical grid models. In this paper, the authors demonstrate this approach on a case study of Wilmington, CA, focused on diesel exhaust particulate matter. Modeling results suggest that pollutant concentrations in the vicinity of emission sources are elevated, and, therefore, an understanding of local emission sources is necessary to generate credible modeling results. A probabilistic evaluation of the Gaussian model application indicated that spatial allocation, emission rates, and meteorological data are important contributors to input and parameter uncertainty in the model results. This uncertainty can be substantially reduced through the collection and integration of site-specific information about the location of emission sources and the activity and emission rates of key sources affecting model concentrations.     

Determination of PM10 emission rates from street sweepers

The use of street sweepers to clean paved roads, particularly after high-wind events, has been proposed as a PM10 control method. Using an artificial tunnel, the emission rates for several street sweepers were quantified under actual operating conditions. The tunnel was a tent enclosure, 6.1 x 4.3 x 73 m, open on both ends. PM10 concentrations were measured at the inlet and outlet while a sweeper removed sand deposited along the length. Measurements were made using a specialized low-volume filter sampler and an integrating nephelometer. The volume of air passing through the tunnel was measured by releasing an inert tracer, sulfur hexafluoride, at the inlet and measuring its concentration at the outlet. A large difference in emission rates between vacuum-type sweepers was observed, with rates varying from 5 to 100 mg m-1 swept. For the cleanest sweepers, the background rates (collected by sweeping clean pavement) were about half of the total PM10 emission rate. These background emission rates likely were from diesel exhaust; background rates for the single gasoline-powered sweeper were below detection. Particle light scattering data confirmed the filter collection results. The artificial tunnel approach would be useful in measuring total emissions from other mobile and stationary sources.     

Evaluating sources of indoor air pollution

Evaluation of indoor air pollution problems requires an understanding of the relationship between sources, air movement, and outdoor air exchange. Research is underway to investigate these relationships. A three-phase program is being implemented: 1) Environmental chambers are used to provide source emission factors for specific indoor pollutants; 2) An IAQ (Indoor Air Quality) model has been developed to calculate indoor pollutant concentrations based on chamber emissions data and the air exchange and air movement within the indoor environment; and 3) An IAQ test house is used to conduct experiments to evaluate the model results. Examples are provided to show how this coordinated approach can be used to evaluate specific sources of indoor air pollution. Two sources are examined: 1) para-dichlorobenzene emissions from solid moth repellant; and 2) particle emissions from unvented kerosene heaters. The evaluation process for both sources followed the three-phase approach discussed above. Para-dichlorobenzene emission factors were determined by small chamber testing at EPA's Air and Energy Engineering Research Laboratory. Particle emission factors for the kerosene heaters were developed in large chambers at the J. B. Pierce Foundation Laboratory. Both sources were subsequently evaluated in EPA's IAQ test house. The IAQ model predictions showed good agreement with the test house measurements when appropriate values were provided for source emissions, outside air exchange, in-house air movement, and deposition on "sink" surfaces.     

Evaluating Sources of Indoor Air Pollution

Evaluation of Indoor air pollution problems requires an understanding of the relationship between sources, air movement, and outdoor air exchange. Research is underway to investigate these relationships. A three-phase program is being implemented: 1) Environmental chambers are used to provide source emission factors for specific indoor pollutants; 2) An IAQ (Indoor Air Quality) model has been developed to calculate indoor pollutant concentrations based on chamber emissions data and the air exchange and air movement within the indoor environment; and 3) An IAQ test house is used to conduct experiments to evaluate the model results. Examples are provided to show how this coordinated approach can be used to evaluate specific sources of indoor air pollution. Two sources are examined: 1) para-dichlorobenzene emissions from solid moth repellant; and 2) particle emissions from unvented kerosene heaters.

The evaluation process for both sources followed the three-phase approach discussed above. Para-dichlorobenzene emission factors were determined by small chamber testing at EPA’s Air and Energy Engineering Research Laboratory. Particle emission factors for the kerosene heaters were developed In large chambers at the J. B. Pierce Foundation Laboratory. Both sources were subsequently evaluated in EPA’s IAQ test house. The IAQ model predictions showed good agreement with the test house measurements when appropriate values were provided for source emissions, outside air exchange, in-house air movement, and deposition on “sink” surfaces.     

Correlating emissions with time and temperature to predict worst-case emissions from open liquid area sources

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry's law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H2S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H2S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85-90 degrees F), the constant emission rate underestimated odor impact significantly (by 73%).