Summary report of the corech (COGAR) workshop on the evaluation of air pollution episodes and associated control measures

Discussions within COGAR during 1981 indicated that collective information on the types of meteorological conditions when large, single sources like power stations contributed to pollution episodes, the frequency with which they occurred and the implications for intermittent control procedures, was important to all member utilities. This paper summarizes the findings of a working group set up by COGAR to study these problems.The investigation was concerned with SO₂ episodes and how feasible it would be to reduce their intensity by such measures as a substitution of low sulphur fuel or switching generation to areas where the probability of an episode developing is less.There has been a considerable reduction in SO₂ emissions in most urban areas in the last two decades. Nevertheless, in many locations, 24-h air pollution episodes can still be attributed to small or medium-sized emissions from low or medium level stacks, rather than to power stations and other large industrial sources with tall stacks. The worst cases in flat terrain where power stations do contribute for many hours are either stagnant conditions persisting for 24 h or a steady wind blowing consistently from an area containing several power stations. Single stations can present problems when topography interferes with dispersion or the stack height is inadequate for the emissions.Data on the frequency with which episodes occur in a given location and the ability to forecast episode conditions in advance, so that if appropriate, preventative measures may be taken, are the desired objectives. Achievement of these objectives requires a detailed understanding of the role of each type of source in relation to different meteorological situations and the local topography. The end product of such studies should be either;

• 1.(a) the specification of a procedure for implementing intermittent emission control
• 2.(b) a demonstration that intermittent control is not an effective option in the area under study.

In case (a), input data required are

• 1.(i) the vertical structure of the atmosphere
• 2.(ii) ground level concentrations of pollutant plus, in complicated topography
• 3.(iii) the three-dimensional distribution of pollutant.

COGAR is a group set up to coordinate atmospheric research in the electrical supply industry in Europe.     

NO2 and SO2dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area,Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO₂ and SO₂ was conducted using the AERMOD model. The area-specific emission inventories of NO_x and SO₂ were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO₂, on-road mobile emissions were found to be the largest contributor in the two residential areas (36–38% of total AC-NO₂), while petrochemical-industry emissions play the most important role in the two industrialized areas (34–51%). For AR-NO₂, biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO₂, the petrochemical industry contributes most in all impacted areas (38–56%). For AR-SO₂, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.

Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO₂ and SO₂. By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas.     

Atmospheric Pollution Considerations Affecting the Ultimate Capacity of a Thermal-Electric Power Plant Site

The power plant designer today has the tools at hand which enable him to predict with an adequate degree of accuracy the effect of different stack heights on ground level concentrations of the gaseous pollutants emitted from power plant stacks. Use of tall stacks will make it possible in most cases to build larger power plants at any particular site than are in service now and still operate them satisfactorily from the standpoint of air pollution. On the other hand, atmospheric pollution considerations may make it necessary at some sites to put a finite limitation on the maximum capacity that can be installed.     

Improvement of Ambient Sulfur Dioxide Concentrations by Conversion from Low to High Stacks

A study of the “before” and “after” ground-level S0₂ concentrations near the Muskingum River Plant of the American Electric Power System shows that the conversion from low to high stacks has accomplished marked reductions in ambient concentrations. These reductions are in reasonable agreement with theoretical calculations and are most apparent within 5 km of the source. EPA Standards are now being met in this area despite the presence of the 1440 MW power plant burning 5% sulfur fuel with no treatment of the stack gas.     

Estimates of Ground Level TSP,S02 and HCI for a Municipal Waste Incinerator to be Located at Tynes Bay—Bermuda

The computer model Industrial Source Complex Short Term (ISCST) was used to study the stack emissions from a refuse Incinerator proposed for the island of Bermuda. The model predicts that the highest ground level pollutant concentrations will occur near Prospect, 800 m to 1000 m due south of the stack. We installed a portable laboratory and instruments at Prospect to begin making air quality baseline measurements. By comparing the model’s estimates of the incinerator contribution to the background levels measured at the site we predict that stack emissions will not cause an Increase In TSP or SO₂. The incinerator will be a significant source of HCI to Bermuda air with ambient levels approaching air quality guidelines.     

Total SO2 emission control strategies for the management of air pollution in ulsan industrial complex

Since emission regulations in Korea concentrate mainly on the limitation of pollutant concentration in the stack gas, it is difficult to achieve a desirable air quality in a heavily industralized city like Ulsan. To ensure a suitable air quality in the future, a total emission control method is proposed with a stack height formula of H = 10.6 q^0.5, where H is the stack height (m) and q is the SO₂ emission rate (m³ h⁻¹ reduced to 0°C). The total emission permitted can be allocated to industries

• 1.(1) at an uniform reduction rate,
• 2.(2) by the formula Q = aQ_o^0.925, where Q is the emission allowed (g s⁻¹), a is a constant, and Q_o is the emission before control (g s⁻¹), or
• 3.(3) by using a linear programming technique.

The above three approaches were evaluated using the TCM 2 air quality model. In order to achieve the air quality goal set for the area, the first approach requires 38.7 % reduction of SO₂ emission from industries, the second 53.3 %, and the third 4.3 %. The linear programming method is found to be very economical, but there are some administrative difficulties in enforcement.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Nonmethane Organic Compound to Nitrogen Oxide Ratios and Organic Composition in Cities and Rural Areas

The observed ranges in nonmethane organic compound (NMOC) concentrations, NMOC composition and nitrogen oxides (NO_X) concentrations have been evaluated for urban and nonurban areas at ground level and aloft of the contiguous United States. The ranges in NMOC to NO_X ratios also are considered. The NMOC composition consistently shifts towards less reactive compounds, especially the alkanes, in air parcels over nonurban areas compared to the NMOC composition near ground level within urban areas. The values for the NMOC to NO_X ratios, 1.2 to 4.2, in air aloft over nonurban areas are lower than in air at ground level urban sites, ≥8, and much lower than in air at ground level nonurban sites, ≥20.

The layers of air aloft over a number of nonurban areas of the United States tend to accumulate NO_X emissions from the tall stacks of large fossil fuel power plants located at nonurban sites. During the night into the morning hours, the air aloft is isolated from any fresh NMOC emissions predominately coming from near surface sources. Conversely, during this extended period of restricted vertical mixing, air near the surface accumulates NMOC emissions while this air is isolated from the major NO_X sources emitting aloft. These differences in the distribution of NMOC and NO_X sources appear to account for the much larger NMOC to NO_X ratios reported near ground level compared to aloft over nonurban areas.

Two types of experimental results are consistent with these conclusions: (1) observed increases in surface rural NO_X concentrations during the morning hours during which the mixing depth increases to reach the altitude at which NO_X from the stacks of fossil fuel power plants is being transported downwind; (2) high correlations of total nitrate at rural locations with Se, which is a tracer for coal-fired power plant NO_X emissions.

The implications of these conclusions from the standpoint of air quality strategies are suggested by use of appropriate scenarios applied to both urban and regional scale photochemical air quality models. The predictions from urban model scenarios with NMOC to NO_X ratios up to 20 are that NO_X control will result in the need for the control of more NMOC emissions than necessary in the absence of NO_X control, in order to meet the O₃ standard. On a regional scale, control of NO_X emissions from fossil fuel power plants has little overall effect regionally but does result on a more local scale in both small decreases and increases in O₃ concentrations compared to the baseline scenario without NO_X control. The regional modeling results obtained to date suggest that NO_X control may be effective in reducing O₃ concentrations only for a very limited set of conditions in rural areas.     

Simulation of Stack Plume Opacity

ABSTRACT

The visual impact of primary particles emitted from stacks is regulated according to stack opacity criteria. In-stack monitoring of the flue gas opacity allows plant operators to ensure that the plant meets U.S. Environmental Protection Agency opacity regulations. However, the emission of condensable gases such as SO₃ (that hydrolyzes to H₂SO₄), HCl, and NH₃, which may lead to particle formation after their release from the stack, makes the prediction of stack plume opacity more difficult.

We present here a computer simulation model that calculates the opacity due to both primary particles emitted from the stack and secondary particles formed in the atmosphere after the release of condensable gases from the stack. A comprehensive treatment of the plume rise due to buoyancy and momentum is used to calculate the location at which the condensed water plume has evaporated (i.e., where opacity regulations apply).

Conversion of H₂SO₄ to particulate sulfate occurs through nucleation and condensation on primary particles. A thermodynamic aerosol equilibrium model is used to calculate the amount of ammonium, chloride, and water present in the particulate phase with the condensed sulfate. The model calculates the stack plume opacity due to both primary and secondary particles. Examples of model simulations are presented for three scenarios that differ by the emission control equipment installed at the power plant: (1) electrostatic precipitators (ESP), (2) ESP and flue gas desulfurization, and (3) ESP and selective catalytic reduction. The calculated opacity is most sensitive to the primary particulate emissions. For the conditions considered here, SO₃ emissions showed only a small effect, except if one assumes that most H₂SO₄ condenses on primary particles. Condensation of NH₄Cl occurs only at high NH₃ emission rates (about 25 ppm stack concentration).     

APCA Financial Statements for 1975-1976

Abstract

A wind tunnel study was completed to determine the effects the presence of a parapet and raised intake configurations have on the dilution of a pollutant between a rooftop stack and building intake. This study was the first to address the effects of building parapets and varying intake configurations. A study of this kind is desirable because it is common practice for architects to attempt to hide stacks with the use of a parapet in order to make industrial buildings more aesthetically pleasing. This is done with no thought to the effect it may have on the intended function of the stacks, which is dispersing gases away from the building to avoid contamination of ventilation air.

Three parapet configurations (no parapet and two different parapet heights) and two intake configurations (flush and raised) were investigated. The relative effects of the parapets and the raised intake configurations were also compared and contrasted for five stack heights, two stack locations, and four intake locations.

The parapets were found to produce a cavity zone that extends above the building's roof by as much as two times the physical height of the parapet; increasing stack height had little effect on dispersion until the stack extended beyond this cavity region. The independent use of the parapets and raised intake configuration decreased the number of dilutions occurring between stack and intake when compared to the no parapet and flush intake configurations in all cases. Also substantiated in this study is the widely accepted view that the effect of the parapet addition is to decrease the effective stack height by the parapet height itself.

The results of this investigation were then compared to existing wind tunnel-derived empirical models. The models tested were not able to predict the effects of varying stack height and of varying the relative distance between stack and intake on the dilution of a pollutant between stack and intake under the tested configurations.     

CALPUFF and AERMOD Model Validation Study in the Near Field: Martins Creek Revisited

ABSTRACT

This paper describes a near-field validation study involving the steady-state, U.S. Environmental Protection Agency (EPA) guideline model AERMOD and the nonsteady-state puff model CALPUFF. Relative model performance is compared with field measurements collected near Martins Creek, PA—a rural, hilly area along the Pennsylvania-New Jersey border. The principal emission sources in the study were two coal-fired power plants with tall stacks and buoyant plumes. Over 1 yr of sulfur dioxide measurements were collected at eight monitors located at or above the two power plants' stack tops. Concurrent meteorological data were available at two sites. Both sites collected data 10 m above the ground. One of the sites also collected sonic detection and ranging measurements up to 420 m above ground. The ability of the two models to predict monitored sulfur dioxide concentrations was assessed in a four-part model validation. Each part of the validation applied different criteria and statistics to provide a comprehensive evaluation of model performance. Because of their importance in regulatory applications, an emphasis was placed on statistics that demonstrate the model's ability to reproduce the upper end of the concentration distribution. On the basis of the combined results of the four-part validation (i.e., weight of evidence), the performance of CALPUFF was judged to be superior to that of AERMOD.

IMPLICATIONS Use of the nonsteady-state CALPUFF model in the near field (<50 km) for regulatory applications has been limited because of the lack of appropriate model validation studies. Considered an alternative model by EPA, use of CALPUFF for regulatory purposes in the near field must be supported by a relevant performance evaluation using measured air quality data. This validation study should help address the lack of information on the performance of CALPUFF in near-field applications. The potential problem with the use of the robust high concentration as a metric in model validations is also examined.     

The Validity of Several Plume Rise Formulas

The ground level concentration of pollutants downwind of a tall chimney decreases as the effective height of the stack increases. The effective height of the stack is the actual height plus the rise of the plume center-line due to momentum and buoyancy of the effluent. Over twenty formulas to predict plume rise from stack and meteorological parameters have been proposed; none is uniformly accepted. In this paper, 711 plume rise observations were used to test the ability of fifteen of the published and commonly used formulas to predict plume rise. The plume rise data were obtained from single stacks whose heat emission rate varied over four orders of magnitude. None of the formulas tested was found to be significantly better than the others. Research was performed under the auspices of the U.S. Atomic Energy Commission.     

Assessment of PCDD/F risk after implementation of emission reduction at a MSWI

Municipal solid waste incinerators (MSWIs) have been shown to be important sources of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). The emission of PCDD/Fs by MSWIs is a controversial subject in human health risk assessment. In this study the effect of a MSWI on a residential area was assessed before and after the installation of an additional treatment system for flue gas. This additional treatment system resulted in a dramatic decrease in PCDD/F concentrations in stack flue gas samples by 99.98%, while the concentrations in air decreased by approximately 50% (36,500 and 0.75 pg I-TEQ m(-3) for air in 1999; 3.5 and 0.38 pg I-TEQ m(-3) in 2002; 1.6 and 0.076 pg I-TEQ m(-3) in 2005 for stack gas and air, respectively). Considering the congener distributions of PCDD/Fs between stack flue gas and air samples, the study area seemed to have been contaminated by other urban sources as well as the MSWI. ISC3 model results support the conclusion that this incinerator became only a minor contributor to the study area after installation of the supplementary systems. This resulted from both proper MSWI operation using modern technology and additional sources of contaminants in this region. Finally, PCDD/F uptake by humans through inhalation of contaminated air was estimated. Assuming that inhalation exposure contributes 10% of total exposure, total exposure was lower than WHO guidelines. These results confirm that proper operation and maintenance of the incinerator led to a reduction in emissions and potential health impacts of PCDD/Fs.     

Water flume study of the enhancement of buoyant rise in pairs of merging plumes

When multiple stacks are grouped or ganged together at a site, the effluent plumes are often observed to merge downwind, forming a single buoyant plume whose rate of rise is enhanced relative to the rise of the plumes individually. The magnitude of this rise enhancement depends on many factors, and the few available models for rise enhancement do not always agree with one another. In the present study the rise behaviour of pairs of merging, buoyant plumes was studied by physical modelling in a water flume at 1:500 scale. The experiments were conducted at several stack separation distances and various exit velocity ratios for stack pairs aligned with, or perpendicular to, the ambient flow. Limited experiments were also done with the stacks aligned at other angles to the flow. The stack releases were made buoyant by heating the source water, and the resulting plumes were measured with an array of sensitive temperature probes. From these measurements it was possible to determine the plume structure and rise rates. For small stack separations when the stacks are aligned with the ambient flow, the experimental results show that the enhanced rise is close to, and sometimes above, the maximum theoretical rise enhancement factor of 2^1/3. For the perpendicular orientation there is little or no rise enhancement. The rise enhancement for other stack orientations is somewhere between these two extremes. A plausible physical explanation for the observed behaviour is given, based on initial momentum shielding and line vortex dynamics in the merging plumes.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

An Evaluation of Flare Combustion Efficiency Using Open-Path Fourier Transform Infrared Technology

ABSTRACT

Open-path Fourier transform infrared (OP-FTIR) technology was used to evaluate the combustion efficiency of a flare for comparison to several combustion models. Most flares have been considered an effective method for destroying organic compounds and anything that burns. As the Btu content of the flare gas is reduced, the combustion efficiency may also be reduced. Recent studies have suggested that lower Btu flares may have efficiencies as low as 65%. In addition, models have been developed to predict the effect of wind speed and stack discharge velocity on the combustion efficiency. This study was conducted on a low-Btu flare gas that is primarily CO. While the models would predict efficiencies as low as 30%, the sampling using OP-FTIR showed most combustion efficiencies well above 90%. Three methods were used to track combustion efficiency: monitoring the ratio of CO to CO₂, monitoring the ratio of CO to tracer gas, and dispersion modeling. This study was complicated by the presence of two flare stacks, thus two tracer gases were used—SF₆ and CF₄. A method was developed for distinguishing between the two stacks and quantifying the efficiency in each stack.     

NO2 and SO2 dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area, Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO2 and SO2 was conducted using the AERMOD model. The area-specific emission inventories of NOx and SO2 were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was Jbund, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration overfour selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations Jbfor each individual area, respectively. For AC-NO2, on-road mobile emissions were found to be the largest contributor in the two residential areas (36-38% of total AC-NO2), while petrochemical-industry emissions play the most important role in the two industrialized areas (34-51%). For AR-NO2, biomass burning has the most influence in all impacted areas (>90%) exceptJor one residential area where on-road mobile is the largest (75%). For AC-SO2, the petrochemical industry contributes most in all impacted areas (38-56%). For AR-SO2, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.     

Combined analysis of modeled and monitored SO2 concentrations at a complex smelting facility

Vale Canada Limited owns and operates a large nickel smelting facility located in Sudbury, Ontario. This is a complex facility with many sources of SO₂ emissions, including a mix of source types ranging from passive building roof vents to North America's tallest stack. In addition, as this facility performs batch operations, there is significant variability in the emission rates depending on the operations that are occurring. Although SO₂ emission rates for many of the sources have been measured by source testing, the reliability of these emission rates has not been tested from a dispersion modeling perspective. This facility is a significant source of SO₂ in the local region, making it critical that when modeling the emissions from this facility for regulatory or other purposes, that the resulting concentrations are representative of what would actually be measured or otherwise observed. To assess the accuracy of the modeling, a detailed analysis of modeled and monitored data for SO₂ at the facility was performed. A mobile SO₂ monitor sampled at five locations downwind of different source groups for different wind directions resulting in a total of 168 hr of valid data that could be used for the modeled to monitored results comparison. The facility was modeled in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model) using site-specific meteorological data such that the modeled periods coincided with the same times as the monitored events. In addition, great effort was invested into estimating the actual SO₂ emission rates that would likely be occurring during each of the monitoring events. SO₂ concentrations were modeled for receptors around each monitoring location so that the modeled data could be directly compared with the monitored data. The modeled and monitored concentrations were compared and showed that there were no systematic biases in the modeled concentrations.

Implications:

This paper is a case study of a Combined Analysis of Modelled and Monitored Data (CAMM), which is an approach promulgated within air quality regulations in the Province of Ontario, Canada. Although combining dispersion models and monitoring data to estimate or refine estimates of source emission rates is not a new technique, this study shows how, with a high degree of rigor in the design of the monitoring and filtering of the data, it can be applied to a large industrial facility, with a variety of emission sources. The comparison of modeled and monitored SO₂ concentrations in this case study also provides an illustration of the AERMOD model performance for a large industrial complex with many sources, at short time scales in comparison with monitored data. Overall, this analysis demonstrated that the AERMOD model performed well.     

Principal Plume Dispersion Models: TVA Power Plants

The body of information presented in this paper is directed to those individuals who may be concerned with principal plume dispersion models at coal-burning power plants. About 20 years of comprehensive field surveillance and documentation of dispersion of power plant emissions for a varied range of unit sizes, stack heights, and meteorological conditions have determined the Tennessee Valley Authority’s interpretation of principal plume dispersion models. TVA’s experience indicates that as unit sizes are increased and taller stacks are constructed, the plume dispersion model associated with maximum surface concentrations changes. Maximum surface concentrations for principal plume dispersion models were approximately equal for the early small plants. However, the coning model was considered the critical plume dispersion model because the frequency of recurrence of surface concentrations from this model was appreciably greater than other models.

There were progressive changes because of an increase in unit sizes and stack heights; the magnitude of maximum surface concentrations from the coning model decreased, and the magnitude (relative to the coning model) of concentrations from the inversion breakup model increased. However, with plumes from newer and larger units with higher stacks, the trapping dispersion model became prominent. Finally, by the time unit size had increased to 900 mw and stack height to about 245 meters, as at Bull Run Power Plant, the magnitude of surface concentrations associated with trapping had increased to such a degree that it became the critical dispersion model identified with power plants of this size.     

Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 μm; PM₁₀) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a “Very Clear Air Zone” to a “Polluted Air Zone.” Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM₁₀ pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM₁₀ levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.

Implications: The evaluation of air quality profiles of specific regions is important in the development and/or application of an effective air quality management strategy. Factor analysis (FA), together with correlation analysis (CA), provides useful information to classify air pollution management areas over regional networks that have historical time-series air quality data. In this study, which relied on a FA- and CA-based methodology, the coherent air pollution management zones of Turkey after using a GIS-based model were suggested. Policy makers and scientist can use these suggested zones to construct better air quality management strategies.