implication of applying calpuff to demonstrate compliance with the regional haze

Modeling Software for EHS Professionals

Implication of Applying CALPUFF to Demonstrate Compliance with the Regional Haze Rule

Paper #651

Prepared By:

Weiping Dai, Ph.D. Hung-Ming (Sue) Sung, Ph.D., P.E.

Curtis V. DeVore

BREEZE SOFTWARE 12700 Park Central Drive,

Suite 2100 Dallas, TX 75251

+1 (972) 661-8881 breeze-software.com

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Implication of Applying CALPUFF to Demonstrate Compliance with the Regional Haze Rule

651

Weiping Dai, Ph.D.

Trinity Consultants, 12801 North Central Expressway, Suite 1200, Dallas, TX 75243

Hung-Ming (Sue) Sung, Ph.D., P.E.


Curtis V. DeVore


ABSTRACT

The U.S. Environmental Protection Agency promulgated the final Regional Haze Rule in July 1999 to protect Class I areas from visibility impairment. Industrial sources may be required to conduct modeling analysis to demonstrate their potential impact on nearby Class I areas during air permit applications. Although the widely used Industrial Source Complex Short-Term model (ISCST3) can be applied (and it may be recommended as the first step screening tool by state agencies), its results may not pass the strict criteria, which are set to protect the Class I areas. Moreover, regional haze is generally a long-range transport phenomenon. Theoretically, the ISCST3 model is not appropriate for a long-range transport (e.g., greater than 50 kilometers from the emission sources). Variations of the meteorological and geophysical conditions in such a distance require sophisticated temporal and spatial treatments of meteorological data, geophysical data, and plume dispersions. The CALPUFF modeling system is designed to handle long-range transport of various pollutants with consideration of chemical transformation.

For regional haze analysis, different states may have different modeling approach and guidance. Colorado proposes a 3-tier approach: Tier 1 – ISCST3 modeling analysis; Tier 2 – CALPUFF Screen analysis; and Tier 3 - Full CALPUFF analysis. CALPUFF Screen analysis is a simplified approach with flat terrain assumption and meteorological data from one station. In this paper, a case study of applying the CALPUFF modeling for regional haze analysis is conducted for an industrial source with potential impact on a nearby Class I area. Results for a base case are discussed and influences of several variables (e.g., distance between the source and the Class I area, emission rates, stack parameters, and background ozone and ammonia concentrations) on modeling results are evaluated. Modeling results indicate that control of NOX and SO2 is most effective in reducing extinction change while stack parameters have small effects on extinction change. Extinction change may also be a strong function of distance for distances less than certain values (e.g., 80 km). In addition, it seems typical background ozone concentrations affect the extinction change more than typical background ammonia concentrations.

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INTRODUCTION

The U.S. Environmental Protection Agency (USEPA) promulgated the final Regional Haze Rule in July of 1999 in order to protect the 156 Class I areas from any future visibility impairment and remedy any existing visibility impairment due to manmade air pollution.1 Class I Areas are defined as national parks over 6,000 acres and wilderness areas and memorial parks over 5,000 acres in the Clean Air Act. According to the Regional Haze Rule, visibility impairment means any humanly perceptible change in visibility (e.g., light extinction, visual range, contrast, and coloration) from that which would have existed under natural conditions. Regional haze means visibility impairment that is caused by the emissions of air pollutants from numerous sources located over a wide geographic area. Such sources include, but are not limited to, major and minor stationary sources, mobile sources, and area sources.

Visual air quality in Class I areas has been significantly degraded due to various anthropogenic sources. The current visual range is only 30 – 90 miles in the West and 14 – 24 miles in the East while the natural visual range should be approximately 140 miles in the west and 90 miles in the east.2 Visibility impairment is primarily caused by the scattering and absorption of light due to airborne fine particulate matter such as sulfates, nitrates, organic carbon, elemental carbon, and soil dust. Ammonium sulfate and ammonium nitrate typically are secondary pollutants formed from the oxidation of sulfur dioxide (SO2) and nitrogen oxides (NOX) in the presence of ammonia gas (NH3) during processes of transport and dispersion. Anthropogenic sources emit significant amount of SO2 and NOX.

For new source permit applications, applicants may be required to perform regional haze analysis to assess the impact of emissions from the proposed sources on nearby Class I areas. Several dispersion models such as VISCREEN, PLUVUE II, ISCST3, AERMOD, and CALPUFF can be utilized for this modeling analysis purpose. Different states may have different modeling analysis guidance. For example, Colorado recommends a 3-tier approach for long-range transport modeling analysis: Tier 1 – ISCST3 modeling analysis; Tier 2 – CALPUFF Screen analysis; and Tier 3 - Full CALPUFF analysis.3 CALPUFF Screen analysis is a simplified approach with flat terrain assumption and meteorological data from one station. Although the widely used ISCST3 can be applied (and it may be recommended as the first step screening tool by state agencies), its results may not pass the strict criteria, which are set to protect the Class I areas. Moreover, ISCST3 is not appropriate for long-range transport (e.g., greater than 50 kilometers from the emission sources) because variations of the meteorological and geophysical conditions in such a distance require sophisticated temporal and spatial treatments of meteorological data, geophysical data, and plume dispersions. Regional haze is generally a long-range transport phenomenon. The CALPUFF modeling system is designed to handle long-range transport of various pollutants with consideration of chemical transformation.

The CALPUFF modeling system consists of three major components: CALMET, CALPUFF, and CALPOST.4 CALMET is a meteorological model for generating hourly three-dimensional wind and temperature fields and various two-dimensional fields (mixing height, surface characteristics, and dispersion properties) on a gridded modeling domain. These meteorological fields developed by CALMET are used by CALPUFF. CALPUFF is a non-steady state transport and dispersion model for calculating hourly pollutant concentrations and deposition fluxes at selected receptors due to various emission sources. CALPOST is used to process the CALPUFF

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results for performing visibility, deposition, or concentration analysis for selected averaging periods. Typically, a 24-hour averaging period is used for visibility analysis.

This study focuses on the application of full CALPUFF modeling analysis for regional haze analysis. A case study is conducted for assessing the impact of SO2, NOX, and PM10 emissions from a hypothetical industrial source on the nearby Class I area. Results for a base case are discussed and influences of several variables (distance between the source and the Class I area, emission rates, stack parameters, and background ozone and ammonia concentrations) on modeling results are evaluated. Results from CALPUFF Screen analysis are also compared and discussed. Finally, implication of applying ISCST3 and AERMOD for regional haze analysis is also briefly discussed.

VISIBILITY ANALYSIS AND ANALYSIS THRESHOLDS

Visibility can be characterized by the light-extinction coefficient, which represents the attenuation of light per unit distance (e.g., million meters [Mm]) due to scattering and absorption by various chemicals such as ammonium sulfate, ammonium nitrate, soil, and other particulate matter in the atmosphere. Visibility analysis is used to evaluate the extent of change of the extinction coefficient in the areas of interest due to the emissions of various pollutants such as SO2, NOX, and PM10. SO2 and NOX can be transformed to sulfate and nitrate during plume transport and dispersion and then sulfate and nitrate combine with available ammonia in the atmosphere to form ammonium sulfate [(NH4)2SO4] and ammonium nitrate (NH4NO3). The change of extinction due to the emission source can be calculated as follows:

100 ,

, bext

sext

b

b) Change (%Extinction , (1)

where bext,s is the extinction coefficient due to the emission source(s) and bext,b is the background extinction coefficient under natural conditions. Note that the scattering and absorption of light by gases also contribute to the light extinction coefficient. In general, bext,b is affected by various background chemical species and the Rayleigh scattering phenomenon and can be calculated as follows:5, 6

rayapcoarsesoilOCNOSObext bbbbbbbMmb 34

1, )( , (2)

where )RH(fSO)(NH3b 4244SO , )RH(fNONH3b 343NO , OC4bOC , Soil1bsoil ,

MassCoarse6.0bcoarse , ]CarbonElemental[10bap , rayb Rayleigh scattering, )RH(f relative

humidity adjustment factor, and ][ concentration in g/m3. Note that these chemical species can be divided into two categories – hygroscopic chemicals [(NH4)2SO4 and NH4NO3] and non-hygroscopic chemicals (organic carbon [OC], soil, coarse mass, and elemental carbon). Visibility is normally much better in dry conditions than in wet conditions because fine particles absorb moisture in the atmosphere and scatter light more efficiently due to the increased size.7 The extinction due to hygroscopic chemicals is a function of the relative humidity factor, which has a nonlinear relationship with the ambient relative humidity.

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The Draft Phase I Report of the Federal Land Managers’ Air Quality Related Values Workgroup (FLAG) lists the site-specific background extinction under natural conditions for Class I areas.6 Note that many of the natural background extinction coefficients in Table 2.B-1 of the Draft FLAG Report are in error. For example, all of the “Hygro” values for the eastern U.S. should be 0.9 Mm-1, but some of them are incorrectly reported as 0.6 Mm-1.

According to the guidance developed by FLAG, the following analysis thresholds of extinction change due to sources located at least 50 km from the Class I areas will be applied in New Source Review Visibility Analysis: (1) if the extinction change due to the proposed source is greater than 10% for at least one modeled day, the federal land managers (FLM) will consider the magnitude, frequency, duration, and other factors to assess the impact. However, the FLM is likely to object to the issuance of the permit; (2) if the extinction change due to the proposed source is less that 5% for all days, the FLM is not likely to object to the issuance of the permit; (3) if the extinction change due to the proposed source is greater than 5% but less than 10%, a cumulative analysis including the new source and all new source growth will be requested; (4) if cumulative analysis results indicate that the effects from the combined sources are expected to cause an extinction change less than 10% for all modeled 24-hour periods, the FLM is not likely to object to the issuance of the permit; however, (5) if cumulative analysis results shows that the cumulative extinction change is greater than 10% and the contribution from the proposed source is not less than 0.4%, the FLM is likely to object to the issuance of the permit, even though the magnitude, frequency, duration, and other factors will be considered.6 Note that the above criteria are not yet final and may be revised in response to public comments.

In this study, three visibility-related pollutants (SO2, NOX, and PM10) are considered to be emitted from a hypothetical industrial source. The SO2 and NOX are transformed to (NH4)2SO4 and NH4NO3 during transport and dispersion. Therefore, the chemicals with contribution to visibility change are (NH4)2SO4, NH4NO3, and PM10. The extinction coefficient due to these three chemicals (bext,s) can be expressed as follows:

PMNOSOsext bbbMmb 34

1, )( , (3)

where )RH(fSO)(NH3b 4244SO , )RH(fNONH3b 343NO , and 10PM PM6.0b .

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CASE STUDY: EMISSION SOURCE AND MODELING SETUP

Hypothetical Industrial Source

In this study, it is assumed that a new industrial source is proposed to be built east of a Class I area. The facility will emit SO2, NOX, and PM10 from a stack. Parameter values for a base case are listed in Table 1. For the base case, the facility is approximately 50 km away from the closest edge of the Class I area. The distance of 50 km is chosen because it is a general criterion distance to distinguish near-field modeling from long-range transport modeling, although CALPUFF is not technically subject to this criterion.

Table 1. Parameter Values for the Base Case

Parameter Value

Source UTM Coordinates Easting: 506 km Northing: 4180 km

Zone: 13 Emission Rate SO2 (tons per year) 500

NOX (tons per year) 500

PM10 (tons per year) 500

Stack Parameter Stack Height (m) 100

Stack Diameter (m) 3

Exit Velocity (m/s) 15

Exit Temperature (K) 400

Background Concentration

Ozone (ppb) 40

Ammonia (ppb) 10

CALPUFF Modeling Setup

Figure 1 shows the Class I area location and its surrounding terrain characteristics. A mountain range is between the source and the Class I area. The terrain is quite flat near the source and the terrain elevation increases as approaching the Class I area. Figure 2 shows the modeling domain setup, the location of the source relative to the Class I area, and the placement of receptors. The gray color scale represents the terrain elevation. The modeling domain contains a 45 25 grid with a spacing of 4 km. Eight vertical layers are defined with the cell face heights at 20, 40, 100, 250, 500, 1000, 2000, and 3500 m.

In this study, CALMET is used to develop one year of gridded meteorological data in the modeling domain. The input data includes four surface stations, two upper air stations, five precipitation stations, geophysical data, and the prognostic wind field developed by the Mesoscale Model with four-dimensional data assimilation (MM4). MM4 data are used as the initial guess wind field. MM4 gridded prognostic wind field data are extracted from the 1990 National Climatic Data Center (NCDC) MM4 CDs. Appropriate values are chosen for input

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parameters such as interpolation and radius of influence of surface data, upper air data, precipitation data, and terrain by judging the terrain characteristics and following recommendations from available guidance documents.4, 5, 6

For CALPUFF modeling setup, six species (i.e., SO2, SO4, NOX, nitric acid (HNO3), NO3, and PM10) are modeled. The MESOPUFF II chemical transformation scheme is used. The background concentration is 40 ppb for ozone and 10 ppb for ammonia for the base case. The default nighttime conversion rates are used (i.e., 0.2 %/hr for SO2 loss, 2 %/hr for NOX loss, and 2 %/hr for HNO3 gain). Gas-phase dry deposition is modeled for SO2, NOX, and HNO3. Particulate-phase dry deposition is modeled for SO4, NO3, and PM10. Wet deposition is modeled for SO2, SO4, HNO3, NO3, and PM10. Default dry and wet deposition parameter values are used. Stacktip downwash, vertical wind shear above stack top, and partial plume penetration is modeled with inversion strength computed from temperature gradients. Building downwash is not considered in this study. Plumes are modeled as puffs with Pasquill-Gifford (PG) coefficients for rural areas. When the lateral size of a plume exceeds 550 m, Heffter Equation is used to switch from distance-dependent to time-dependent lateral dispersion coefficients.4 Puff splitting is also allowed in this study. The partial plume path adjustment method is used with default plume path coefficients. In this study, CALPOST is used to perform the extinction change calculation with the CALPUFF output of hourly concentration and relative humidity. Background concentrations for both the hygroscopic chemicals and the non-hygroscopic chemicals are 0.54 g/m3 as (NH4)2SO4 and 5.06 g/m3 as soil, respectively. The background extinction derived from these concentrations match the reference level for Class I areas in the western U.S.6

Figure 1. Class I Area and Terrain Characteristics (the source is out of the view of this picture to the east of the Class I area)

Class I Area

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Figure 2. CALPUFF Modeling Domain and Receptor Setup (Elevation increases as the shading becomes darker.)

CASE STUDY: RESULTS AND DISCUSSION

Base Case Results

The base case has an emission rate of 500 tons per year (tpy) for each pollutant (SO2, NOX, and PM10). Daily maximum extinction change (averaged over 24 hours) for the base case is shown in Figure 3. All daily maximum extinction changes are below 3% except for four days. The highest extinction change is 6.2% and there are two days have extinction change above 5%. In air permit application, these results may result in request for accumulative analysis.

Three observations are made from the results. First, for the worst day, NOX contributes 58% to the extinction while SO2 and PM10 contributes 35% and 7%, respectively. This implies that for the same amount of emission, NOX contribute more than 1.5 times to the extinction change than SO2 while SO2 contributes more than 8 times than PM10 under the modeling conditions. This is reasonable because nitrate and sulfate oxidized from SO2 and NOX absorb moisture in the air and form NH4NO3 and (NH4)2SO4 with available ammonia in the air and the oxidation of NOX is typically faster than the oxidation of SO2. The NH4NO3 and (NH4)2SO4 aerosols scatter light more effectively than PM10. Second, high extinction change typically occurs on the days with high relative humidity (e.g., greater than 90%). This is reasonable because the relative humidity factor increases dramatically for relative humidity higher than about 90%. Third, the visibility-related pollutants can accumulate in the Class I area for more than one days and thus cause high extinction change with the aid of relatively high relative humidity. For example, the highest extinction change for the base case occurs at the second day of the accumulation with a relative humidity of about 89%. Of course, the pollutant accumulation strongly depends on terrain

400 420 440 460 480 500 520 540 560 580

UTM Easting (km)

4,130

4,150

4,170

4,190

4,210

4,230

UT

M N

orth

ing

(km

)

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characteristics and wind patterns.

Figure 3. Daily Maximum Extinction Change for the Base Case

Sensitivity Analysis of Distance between Source and Class I Area

A sensitivity analysis is performed for distances of 30, 40, 50, 60, 70, 80, 90, and 100 km between the source and Class I area. Note that the base elevation of the stack does not change for these cases. Other parameter values are kept the same as those for the base case. The results are presented in Figure 4.

The results show that as distance between the source and Class I area increases, the maximum extinction change decreases. The rate of change increases when the source gets closer to the Class I area and levels off for distances greater than 80 km. The maximum extinction change is almost 11% for a distance of 30 km while the maximum extinction change is about 4% for distances greater than 80 km. It seems distances less than 50 km a have significant impact on the maximum extinction change. Moderate effects are expected for distances between 50 km and 80 km while the maximum extinction change becomes insensitive for distances greater than 80 km. Note that the observations here may not be true for other cases due to the complicated nature of many factors such as terrain effects.

0

1

2

3

4

5

6

7

1 30 59 88 117 146 175 204 233 262 291 320 349

Julian Day of 1990

Ext

inct

ion

Cha

nge

(%)

9

Figure 4. Effects of Distance on Maximum Extinction Change

Sensitivity Analysis of Emission Rate

A sensitivity analysis is performed by changing the emission rates of SO2, NOX, and PM10

separately from 100 tpy to 1500 tpy. Other parameter values are kept the same as the base case. The results are presented in Figure 5.

The results show that the rate of maximum extinction change is approximately linear to the change of the emission rate. Extinction change increases approximately 0.75% (note that this is an absolute change of the extinction change) for an increase of 100 tpy for NOX, 0.44% for SO2, and 0.09% for PM10. These results are quite consistent with the contributions of NOX, SO2, and PM10 to the maximum extinction change shown in the base case. The results imply that reduction in NOX emissions may be most effective for improving visibility quality, followed by reduction in SO2 emissions under certain modeling conditions.

0

2

4

6

8

10

12

30 40 50 60 70 80 90 100

Distance (km)

Ext

inct

ion

Cha

nge

(%)

Cases

5% Threshold

10% Threshold

10

Figure 5. Effects of Emission Rates on Maximum Extinction Change

Sensitivity Analysis of Stack Parameters

A sensitivity analysis is performed by changing the stack height, stack exit temperature, and stack exit velocity while other parameter values are kept the same as the base case. The results are shown in Figures 6, 7, and 8. Stack height is changed from 40 to 120 m. Stack exit temperature is changed from 300 to 500 K and stack exit velocity is changed from 5 to 25 m/s.

In general, individually increasing stack height, stack exit temperature, or stack exit velocity decreases the maximum extinction change. However, the rate of decrease is small. On average, the extinction change decreases about 0.06% for a 10-m increase of stack height and 0.14% for a 5 m/s increase of stack exit velocity. Changes in stack exit temperature seem to have a greater impact on visibility change at the lower end of the investigated temperature range.

0

2

4

6

8

10

12

14

16

18

0 200 400 600 800 1000 1200 1400 1600

Emission Rates (tons per year)

Ext

inct

ion

Cha

nge

(%)

SO2 CasesNOX CasesPM10 Cases5% Threshold10% Threshold

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Figure 6. Effects of Stack Height on Maximum Extinction Change

Figure 7. Effects of Stack Temperature on Maximum Extinction Change

4

6

8

10

12

40 60 80 100 120

Stack Height (m)

Ext

inct

ion

Cha

nge

(%)

Cases

5% Threshold

10% Threshold

4

6

8

10

12

300 350 400 450 500

Stack Temperature (K)

Ext

inct

ion

Cha

nge

(%) Cases

5% Threshold

10% Threshold

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Figure 8. Effects of Stack Exit Velocity on Maximum Extinction Change

Sensitivity Analysis of Background Ozone and Ammonia Concentration

Background ozone and ammonia concentrations contribute to the visibility quality because these two chemicals are involved in the chemical transformation of SO2 and NOX during transport and dispersion. A sensitivity analysis is conducted by changing ozone concentration from 10 ppb to 100 ppb and changing ammonia concentration from 0.1 ppb to 20 ppb. Other parameter values are kept the same as the base case. The results are presented in Figures 9 and 10. It seems that change in background ozone concentration has noticeable impact on maximum extinction change. On average, the maximum extinction change increases 0.26% for each 10-ppb increase of ozone concentration. Results indicate that the maximum extinction change is relatively insensitive to ammonia background concentration unless it is very low (e.g., 0.1-1 ppb).

4

6

8

10

12

5 10 15 20 25

Stack Exit Velocity (m/s)

Ext

inct

ion

Cha

nge

(%)

Cases

5% Threshold

10% Threshold

13

Figure 9. Effects of Background Ozone Concentration on Maximum Extinction Change

Figure 10. Effects of Background Ammonia Concentration on Maximum Extinction Change

4

6

8

10

12

0 20 40 60 80 100 120

Background Ozone Concentration (ppb)

Ext

inct

ion

Cha

nge

(%)

Cases

5% Threshold

10% Threshold

4

6

8

10

12

0 5 10 15 20

Background Ammonia Concentration (ppb)

Ext

inct

ion

Cha

nge

(%) Cases

5% Threshold

10% Threshold

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Other Considerations in Visibility Analysis

Quality Control of Modeled Wind Fields CALMET output is the gridded meteorological data in an unformatted data file. In order to confirm the reasonableness of the final wind fields developed by CALMET, hourly wind vector plots are developed and visually evaluated for wind field characteristics such as downslope flow during nighttime and upslope flow during daytime. Figure 11 presents an hourly wind vector plot for demonstration purpose. The figure clearly shows the downslope flow and the wind vector follows the terrain reasonably well.

Figure 11. Wind Vector Plots for Checking Final Modeled Wind Fields

Comparison of CALPUFF Screen Analysis and Full CALPUFF Analysis The major difference between CALPUFF Screen analysis and full CALPUFF analysis is the way to generate meteorological data and place receptors. Full CALPUFF analysis utilizes CALMET to develop gridded meteorological data by using multiple meteorological (surface, upper air, and precipitation) stations and accounting for terrain effects. CALMET can even make use of sophisticated prognostic wind fields developed by other mesoscale models (e.g., MM4 and MM5). In addition, receptors are placed only on the Class I Area of concern. However, performing full CALPUFF analysis requires tremendous efforts and computer resources.

CALPUFF Screen analysis uses an ISC-type meteorological data from a single meteorological data. It also assumes flat terrain. The conservatism in CALPUFF Screen analysis comes from the placement of receptors. Instead of looking at receptors on the Class I area, rings of discrete receptors (1-degree apart) are placed between the closest and farthest distance from the source to the Class I area. Extinction change at each receptor is considered. This conservatism is based on the fact that no terrain effects are taken into account and therefore no directional distinction should be considered.

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Table 2 compares results from full CALPUFF analysis with those from CALPUFF Screen analysis for the base case. The maximum extinction change from the Screen analysis is almost three times higher than that from the full analysis. Moreover, the frequency exceeding the threshold values (5% and 10%) significantly increases.

Table 2. Comparison of Results from CALPUFF Screen Analysis and Full CALPUFF Analysis

Parameter Full Analysis Screen Analysis

Maximum Extinction Change (%) 6.2 17.5

Days with Extinction Change > 5 % 2 50

Days with Extinction Change >10% 0 8

Application of ISCST3 or AERMOD for Visibility Analysis Both ISCST3 and AERMOD are steady-state dispersion models. Theoretically, both ISCST3 and AERMOD are not suitable for long-range transport modeling analysis. However, according to Colorado modeling guidance, ISCST3 is acceptable as a screening step for long-range transport modeling analysis even though it is also mentioned that the ISCST3 Screen Analysis may eventually be replaced with the CALPUFF Screen.

Nevertheless, ISCST3 is the regulatory model for near-field (less than 50 km) analysis and AERMOD is expected to be the replacement of ISCST3 in the future. Therefore, if it is desirable to conduct visibility analysis for near-field sources, ISCST3 and AERMOD may be the options.

SUMMARY

This study has focused on performing full CALPUFF analysis for long-range transport regional haze analysis. Extinction change can be affected by many factors (e.g., relative humidity, distance between the emission source and Class I area, emission rates, stack parameters, and background ozone and ammonia concentrations). Modeling results indicate that control of NOX and SO2 is most effective in reducing extinction change while stack parameters have small effects on extinction change. Extinction change may also be a strong function of distance for distances less than certain values (e.g., 80 km). In addition, it seems typical background ozone concentrations affect the extinction change more than typical background ammonia concentrations.

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REFERENCES

1. U.S. Environmental Protection Agency, Regional Haze Regulations (Final Rule), Federal Register, Vol. 63, No. 126, July 1, 1999, pp.35714-35774.

2. U.S. Environmental Protection Agency, Fact Sheet: Final Regional Haze Regulations for Protection of Visibility in National Parks and Wilderness Areas, June 2, 1999.

3. Colorado Department of Public Health and Environment, Long-Range Transport Model Selection and Application, Air Pollution Control Division/Technical Services Program, May 21, 1999.

4. Earth Tech Inc., A User’s Guide for the CALPUFF Dispersion Model, Concord, MA, May 1999.

5. Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for Modeling Long Range Transport, U.S. EPA, Office of Air Quality Planning and Standards, EPA-454/R-98-019, December 1998.

6. U.S. Forest Service – Air Quality Program, National Park Service – Air Resources Division, U.S. Fish and Wildlife Service – Air Quality Branch, Draft Phase I Report of the Federal Land Managers’ Air Quality Related Values Workgroup (FLAG), October 1999.

7. N.D. Nevers, Air Pollution Control Engineering, McGraw-Hill, 1995, p506.