# PM 2.5 

# SIP

Appendix D

Meteorological Evaluation of Liberty-Clairton

Area

### {This page left blank for printing purposes}

## The Processing of CALMET Files for

Allegheny County’s PM2.5 SIP Analysis

Submitted to:

Jayme Graham

Allegheny County Health Department

301 39 th Street

Pittsburgh, PA 15201

Submitted by:

Sullivan Environmental Consulting, Inc.

1900 Elkin Street, Suite 200

Alexandria, VA 22308

Contract #5404

‐ 07

November 9, 20072 

### Table of Contents

1.0 Introduction.................................................................................................................6

2.0 Existing Meteorological Monitoring Sites within the Greater Pittsburgh Area................10

3.0 Surface Characteristics within the Modeling Domain.....................................................19

4.0 Heat Analysis of USX Clairton Sources ...........................................................................28

5.0 Coordinate Problems / Resolution.................................................................................31

6.0 Potential for Low

‐ Level Convergence During Stable Nocturnal Conditions.....................32

7.0 Model Options ..............................................................................................................42

8.0 Inclusion of USX Clairton Meteorological Data...............................................................45

9. 0 Results ..........................................................................................................................57

10.0 Statistical Review of Model Performance Based on METSTAT......................................88

11.0 Recommendations for Follow

‐ On CALPUFF Modeling..................................................88

12.0 References ..................................................................................................................89

Appendix A: Full 1

‐ Year (2002) Set of CALMET Predicted Wind Vector Flow Fields ..............90

Appendix B: Special Meteorological Study of 1996 ..............................................................91

Appendix C: Final Version of the Seasonal CALMET In put File..............................................92

Appendix D: Regression Analysis Spreadsheet for USX Clairton ...........................................933 

### List of Figures

Figure 1: Clairton/Liberty Non

‐ Attainment Area ..................................................................6

Figure 2: Topographic Map of the Liberty/Clairton Area ......................................................8

Figure 3: Liberty Site Aerial View ........................................................................................11

Figure 4: Liberty Site View from the South of the Tower ....................................................11

Figure 5: Aerial View of the Greater Pittsburgh International Airport ................................12

Figure 6: South Fayette Site (View from No rtheast) ...........................................................13

Figure 7: Buildings to the East of the Avalon Site ...............................................................14

Figure 8: Avalon Site ...........................................................................................................14

Figure 9: Hammer Field Site View from the South ..............................................................15

Figure 10: Aerial View of Hammer Field Site ......................................................................15

Figure 11: Existing USX Clairton Works Meteorological Monitoring Site ............................16

Figure 13: Allegheny County Airport View from th e South .................................................18

Figure 14: Sub

‐ regions within the Modeling Domain That Were Evaluated for Surface

Roughness ..........................................................................................................................20

Figure 15: Location of Heat Sources and Area Sources Defined by Grid Area .....................29

Figure 16: Flow Vectors (12/5/1995 0530) .........................................................................33

Figure 17: Flow Vectors 12/8/1995 0100 ............................................................................34

Figure 18: Observed Flow Vectors March 26, 19 96 ............................................................35

Figure 19: Wind Direction Frequencies during Nocturnal Non

‐ Overcast Conditions with

Wind Speeds < 6 mph .........................................................................................................36

Figure 20: Wind Direction Frequencies during Nocturnal Non

‐ Overcast Conditions with

Wind Speeds < 3 mph .........................................................................................................37

Figure 21: Wind Direction Frequencies during Nocturnal Non

‐ Overcast Conditions with

Wind Speeds < 1 mph

......................................................................................................... 38

Figure 22: General Domain within Study Area ...................................................................39

Figure 23: Wind Rose Plot for USX Clairton Meteorological Monitoring Site for August 13

–

December 31, 2002 ............................................................................................................46

Figure 24: Wind Rose Plot for Liberty Meteorological Monitoring Site for August 13

–

December 31, 2002 ............................................................................................................47

Figure 26: Low

‐ level 10

‐ meter AG L Wind Vector Plot for July 11, 2002 0500 LST ...............50

Figure 28: Regression Plot for Wind Direction and Wind Speed Based on Low Wind Speeds

(>2

‐ 3 mph) at Liberty ........................................................................................................52

Figure 29: Regression Plot for Wind Direction and Wind Speed Based on Moderate Wind

Speeds (>8

‐ 9 mph) at Liberty

............................................................................................ 53

Figure 30: Regression Plots for Temperature for Hours 06 and 12 .....................................54

Figure 31: Regression Plots for Temperature for Hours 18 and 24 .....................................55

Figure 32: Regression Plots of the Observed versus Predicted Wind Directions and Wind

Speeds for USX Clairton for 2002 ........................................................................................56

Figure 33: Daily Measured Total Particulate Concentrations (μ g/m 3 ) at Liberty for 2002 ..58

Figure 34: 10

‐ meter AGL Wind Vector Plot for 0600LST January 28, 2002 ..........................59

Figure 35: 10

‐ meter AGL Wind Vector Plot for 1200LST January 28, 2002 ..........................60

Figure 36: 10

‐ meter AGL Wind Vector Plot for 1800LST January 28, 2002 ..........................61

Figure 37: 10

‐ meter AGL Wi nd Vector Plot for 0600LST April 17, 2002 ...............................624 

### List of Figures (continued)

Figure 38: 10

‐ meter AGL Wind Vector Plot for 1200LST April 17, 2002 ...............................63

Figure 39: 10

‐ meter AGL Wind Vector Plot for 1800LST April 17, 2002 ...............................64

Figure 40: 10

‐ meter AGL Wind Vector Plot for 0600LST June 25, 2002 ...............................65

Figure 41: 10

‐ meter AGL Wind Vector Plot for 1200LST J une 25, 2002 ...............................66

Figure 42: 10

‐ meter AGL Wind Vector Plot for 1800LST June 25, 2002 ...............................67

Figure 43: 10

‐ meter AGL Wind Vector Plot for 0600LST September 10, 2002 .....................68

Figure 44: 10

‐ meter AGL Wind Vector Plot for 1200LST September 10, 2002 .....................69

Figure 45: 10

‐ meter AGL Wind Vector Plo t for 1800LST September 10, 2002 .....................70

Figure 46: 10

‐ meter AGL Wind Vector Plot for 0000LST January 31, 2002 ..........................72

Figure 47: 30

‐ meter AGL Wind Vector Plot for 0000LST January 31, 2002 ..........................73

Figure 48: 60

‐ meter AGL Wind Vector Plot for 0000LST January 31, 2002 ..........................74

Figure 49: 120

‐ me ter AGL Wind Vector Plot for 0000LST January 31, 2002 ........................75

Figure 50: 10

‐ meter AGL Wind Vector Plot for 0000LST March 25, 2002 ............................76

Figure 51: 30

‐ meter AGL Wind Vector Plot for 0000LST March 25, 2002 ............................77

Figure 52: 60

‐ meter AGL Wind Vector Plot for 0000LST March 25, 2002 ............................78

Fig ure 53: 120

‐ meter AGL Wind Vector Plot for 0000LST March 25, 2002 ..........................79

Figure 54: 10

‐ meter AGL Wind Vector Plot for 0000LST July 24, 2002 ................................80

Figure 55: 30

‐ meter AGL Wind Vector Plot for 0000LST July 24, 2002 ................................81

Figure 56: 60

‐ meter AGL Wind Vector Plot for 0000LST Ju ly 24, 2002 ................................82

Figure 57: 120

‐ meter AGL Wind Vector Plot for 0000LST July 24, 2002 ..............................83

Figure 58: 10

‐ meter AGL Wind Vector Plot for 0000LST October 12, 2002 .........................84

Figure 59: 30

‐ meter AGL Wind Vector Plot for 0000LST October 12, 2002 .........................85

Figure 60: 60

‐ meter AGL Wind Vect or Plot for 0000LST October 12, 2002 .........................86

Figure 61: 120

‐ meter AGL Wind Vector Plot for 0000LST October 12, 2002 .......................875 

### List of Tables

Table 1: Comparison of Point Source PM 2.5 Emissions (tons/year) from Key Emission

Sources in Allegheny County (Hochhauser, 2004) ................................................................7

Table 2: Computational Spreadsheet for Regions (Sheet 1 of 2) .........................................21

Table 2: Computational Spreadsheet for Regions (Sheet 2 of 2) .........................................22

Table 3: Annual Average CALMET Default Surface Characteristics (Sheet 1 of 2) ...............23

Table 3: Annual Average CALMET Default Su rface Characteristics (Sheet 2 of 2) ...............24

Table 4: AERMET Averages for All Seasons .........................................................................24

Table 5: Seasonal Scaling Factors for LAI ............................................................................26

Table 6: Spring ....................................................................................................................27

Table 7: Summer ................................................................................................................27

Table 8: Autumn .................................................................................................................27

Table 9: Winter ...................................................................................................................27

Table 10: Summary Heat Release Estimates .......................................................................30

Table 11: Summary of PM2.5 Emissions by Major Sou rce Category ...................................40

Table 12: Summary of Boiler Stack Specifications and Computed Plume Rise ...................41

Table 13: Key CALMET Input Parameter Options ................................................................44

Table 14: Percent of Occurrence of NE Regional Wind flow Reported at Liberty ................716 

## 1.0 Introduction

Regulatory Background

‐ On April 5, 2005, the U.S. EPA designated the Liberty/Clairton area

(Boroughs of Liberty, Lincoln, Port Vue, Glassport, and the City of Clairton) as non

‐ attainment

for the fine particulates (PM

2.5 ) National Ambient Air Quality Standard (NAAQS). This non

‐

attainment area is outlined in Figure 1. This designation requires the Allegheny County Health

Department to submit a State Implementation Plans (SIP) by April 5, 2008. Sullivan

Environmental provided support on processing the meteorological data for the Liberty/Clairton

non

‐ attainment area SIP. Th is report documents the CALMET modeling that was performed

through this contract.



### Figure 1: Clairton/Liberty Non

­ Attainment Area

( http://envirohealth.law.pitt.edu/journal/1_1/Luneburg.pdf )

Key Sources of PM2.5 Within Non

‐ Attainment Area

‐ The SIP demonstration will be based

on calendar year 2002. The Allegheny County Health Department compiled a county

‐ wide point

source emission inventory report covering the period 1996

‐ 2003, which includes the base year

of 2002. This inventory provides background on the magnitude and location of the key PM 2.5

sources in the Liberty/Clairton non

‐ attainment area. Table 1 provides a summary of these key US Steel Clairton Works US Steel Irvin Works7 sources, with the USX Clairton Works facility shown as the largest source within the boundary in

Figure 1, and the USX Irvin plant (industrial source located just to the northwest of the non

‐

attainment boundary in Figure 1) as a distant second based on total emissions. The other key

sources i dentified in Table 1 are located well outside of the non

‐ attainment area.



### Table 1: Comparison of Point Source PM 2.5 

### Emissions (tons/year) from Key

Emission Sources in Allegheny County (Hochhauser, 2004)

Year USS

–

Clairton

Works

(Clairton) USX Irvin Plant

(Dravosburg) Allegheny

Ludlum

(Brackenridge) USS

– Edgar

Thompson

(Braddock) Cheswick

Power

Station

(Cheswick) Total for

Allegheny

County

1999 351 29 327 266 196 1,768

2000 331 31 265 257 152 1,548

2001 311 26 211 194 117 1,218

2002 319 26 204 291 89 1,394

2003 328 24 211 308 187 1,551

Complexity of Modeling Domain

‐ Figure 2 presents a topographic map of the complex

terrain of the Liberty/Clairton area, including the river valleys of the Monongahela and

Youghiogheny Rivers. The Monongahela River valley with bluffs to the northeast in the direction

of the prevailing southwesterly wind flow is one of the most significant complicating factors,

particularly for th e transport of emissions from the Clairton Works Facility.

From our previous work in this area, we have hypothesized that the Youghiogheny River

valley may create a blocking effect that results in the Monangahela filling and not draining like a

standard river valley. Based on the complexity of wind fl ow, and the need to account for the

tremendous heat flux from the Clairton Works and the potential for low

‐ level convergence

flows, this non

‐ attainment area is likely one of the most complex SIPs that will be prepared for

PM 2.5 throughout the U.S. For this reason, CALMET needs to be set

‐ up in a manner that most

realistically represents the complex flows within the non

‐ attainment area.8 

### Figure 2: Topographic Map of the Liberty/Clairton Area

Use of the CALPUFF / CALMET Modeling System

‐ CALPUFF (Scire et. al., 2000a) is a multi

‐ layer, multi

‐ species, non

‐ steady

‐ state puff dispersion model recommended by U.S. EPA within

the Guideline for Air Quality Models for assessing long

‐ range transport of pollutants and on a

case by case basis for near

‐ field applications involving complex meteorological conditions. First

de veloped by Earth Tech, Inc. in the late 1980’s, the model is maintained by the Atmospheric

Studies Group (ASG) of TRC Companies Inc. (http://www.src.com/index.htm).

Allegheny County Health Department obtained a full year (2002) of Penn State/National Center

for Atmospheric Research (NCAR) Mesoscale Modeling System

‐ 5 th Generation (MM5) data for

the Ohio Valley region including eastern Ohio and western Pennsylvania. The MM5

temperature and wind profile data were primarily developed for weather forecasting. Use of

more accurate Land Use Land Cover (LULC) data has the potential to improve the ability of this

model to simulate heat flux and wi nd flow at a finer spatial scales of analysis. This can lead to

improved exposure assessment and public health management.

Geophysical data required by CALMET (Scire et. al., 2000b) includes elevation, LULC type,

surface roughness length, albedo, Bowen ratio, soil heat flux, vegetation leaf area index and

anthropogenic heat fl ux. The data are incorporated within CALMET through various processors,

which determine the average surface elevation, fractional and dominant land use, as well as the 

### Clairton

Coke Works Monangahela

River Youghiogheny

River9 weighted surface parameters for each grid cell. The model is capable of processing 52

‐ category

USGS LULC data in which land use code is defined at the center point of each cell which are

spaced 100 meters apart.

High (30m) resolution 1992 United States Geological Society (USGS) National Land Use

Co ver Data (NLCD) were obtained and processed through the CALMET CTGPROC geophysical

preprocessor to derive the fractional land use types within each 100m grid block within the

model domain.

CALMET is flexible enough to allow the user to specify LULC

‐ dependent values for each

surface parameter. It also allows the user to de fine new LULC categories by remapping the USGS

LULC categories. For example, the USGS land use category system has seven types of urban or

built

‐ up land and these would have been mapped to one land use category for urban or built

‐ up

land in CALMET, if using the 14

‐ ca tegory LULC.10 

## 2.0 Existing Meteorological Monitoring Sites within the Greater

Pittsburgh Area

During the period of April 29

‐ 30, 2007 and Jun 16, 2007, Sullivan Environmental inspected

the following meteorological sites in the greater Pittsburgh area:

• Liberty

• South Fayette

• Avalon

• Hammer Field

• Clairton USC

• Allegheny County Airport

• Greater Pittsburgh International Airport

The following summarizes the rev iew of each site:11 Liberty

– This site is located within the non

‐ attainment area. The meteorological tower is

positioned on the roof of a two

‐ story school building. The roof level is 24 ft AGL. The sensor

exposure height is 43 ft above the roof, and 67 ft AGL. The exposure height is beyond the 2. 5

building height zone. Therefore, no significant building influences are expected with this data

set. Some deciduous trees were observed towards the south side of the school, which may have

a marginal effect on the representativeness of wind data from this sector.



### Figure 3: Liberty Site Aerial View

Figure 4: Liberty Site View from the South of the Tower12 Greater Pittsburgh International Airport

– During the site visit, we were not able to locate

the tower. Subsequent review based on Google

‐ Earth, showed the following location (based on

NWS stated coordinates 40 o 30’ 5” and 80 o 13’ 52”. This location is in an open area to the North

and East of most of the airport operations, and is well removed from buildings. There are some

trees evident to the East. Otherwise the location appears to be clear. This location, however, is

well removed from the modeling domain of th e CALMET analyses.

Height

= 12 m



### Figure 5: Aerial View of the Greater Pittsburgh International Airport13 South Fayette

‐ The South Fayette site is located at a school building in a very rural area and

at a relatively high elevation. The monitors are on top of a short (~6 ft mast) that was placed on

a ~27 foot rooftop. The monitors are positioned at the Northeast corner of the rooftop.

Alt hough this general location is well sited to cover regional flow, the sensor height above

rooftop is a concern. There will be some adverse influence from flow over the structure. The

site is also located well outside of the 20 km model domain. For this reason, this site was not

c onsidered to have data of sufficient quality to support the CALMET analysis.



### Figure 6: South Fayette Site (View from Northeast)14 Avalon

– The Avalon site is a suburban location embedded within a community with tightly

packed residences, with a high surface roughness value, e.g. in the estimated range of

approximately 60

‐ 80 cm. The wind sensors appear to be set at a 10m height. There is a church

approximately 20m to the west and a b uilding about 40m to the east. Both of these structures

are approximately at the same height as the sensors. There will be some reduction in wind flow

caused by these structures, but this area would be expected to have lower wind speeds than for

more open areas. Th e site is representative, however of this type of setting. Avalon is located,

however, outside of the CALMET modeling domain.



### Figure 7: Buildings to the East of the Avalon Site

Figure 8: Avalon Site15 Hammer Field

– The Hammer Field site is overgrown with tree cover that precludes the use

of the data from this site for CALMET. There is a deciduous tree line to the East that would

adversely affect the wind flow from North through the Southeast, especially during the period of

May through October wh en there is substantial leaf area.



### Figure 9: Hammer Field Site View from the South

Figure 10: Aerial View of Hammer Field Site16 Current USX Clairton Meteorological Monitoring Site

Data from the current USX Clairton meteorological monitoring station (see Figure 11) was

initially reviewed based on daily processed averages. Figure 12 shows an example of wind

direction frequencies for calendar year 2002. As shown, the wind direction data are heavily

clustered within flow from 210 to 270 degrees (about 68 pe rcent of the total flow). No

prevailing daily flow is shown on this basis for 1 through 120 degrees, and only 2 percent of the

days with prevailing daily flow from 300 through 360 degrees. Cursory review of 2001 and 2003

showed similar heavy weighting from the southwest.

Hourly data from th e USX Clairton for the period of August 13

‐ December 31, 2002 as well as

a full

‐ year of 2003 was later provided to Sullivan Environmental for review. A more detailed

description of this hourly data and its use is provided in Section 8.0 of this report.

Height

= 10 m



### Figure 11: Existing USX Clairton Works Meteorological Monitoring Site17 

### Figure 12: Histogram of Daily Predominant Flow for Calendar Year 200218 Allegheny County Airport

– The ASOS meteorological tower is located among the runway areas

with a very open exposure. The area is generally flat and rural. This location provides excellent

data for use in CALMET.

Height

= 12 m



### Figure 13: Allegheny County Airport View from the South

In summary, the Liberty and Allegheny County Airport meteorological monitoring sites were

selected for use as input data sets to CALMET. Avalon and the Greater Pittsburgh International

Airport sites were evaluated and found to be reasonably representative of flow within the

region, but these locations were outside of the final, sel ected modeling grid for CALMET. The

Hammer Field and South Fayette sites were not judged to be of suitably quality for use in the

analysis. The hourly USX Clairton meteorological was later chosen for use in the model analysis

and the details of that data inclusion is presented in Section 8.0 of th is report.19 

## 3.0 Surface Characteristics within the Modeling Domain

This section is subdivided into two major subsections: (a) surface roughness estimates, and

(b) other surface characteristics.

a. Land Use

The Lettau, 1969 1 method was used to estimate roughness length. The Lettau method is

based on the following formula:



## ( )

A aH

z ))((2/1

0 

### =

Where:

Z 0 = aerodynamic roughness length (m)

H = average obstacle height (m)

a = average silhouette area (m 2 )

A = average lot area (m 2 )

= (total area evaluated / number of representative obstacles)

Figure 14 shows the modeling domain subdivided into 41 relatively homogenous zones. The

following analysis was conducted for those zones that had significant residential, commercial, or

industrial property, which was amenable to the method:

1 Lettau, H., “Note on Aerodynamic Roughness

‐ Parameter Estimation on the Basis of Roughness

‐

Element Description,” Journal of Applied Meteorology, 1969, Pages 828

– 832.20 

### Figure 14: Sub

­ regions within the Modeling Domain That Were Evaluated for

Surface Roughness21 A representative subsection was selected within each zone, i.e. 300m by 300m

. The number

of buildings within the sample area was identified, and then the “A” and “a” terms were

computed based on the preceding formula. An average building height of 8m was assigned for

the residential areas, and 10 m fo r industrial areas, respectively.

. Table 2 presents the

computational spreadsheet that was used for this analysis.



### Table 2: Computational Spreadsheet for Regions (Sheet 1 of 2)

Region Type Perimeter (mi) Total Area

m^2 Total Area

mi^2 Sample

Area Buildings in

Sample Area Sample Building

area (m^2)

1 Mixed Residential/Forest 1.82 383,033 0.15 n/a n/a n/a

2 Residential 4.43 2,741,661 1.06 46,694 50 146

3 Mixed Residential/Barren 1.44 303,641 0.12 n/a n/a n/a

4 Industrial 4.53 1,416,015 0.55 991,211 40 600

5 Mostly Residential/Woods 3.47 1,120,812 0.43 34,669 29 146

6 Mixed Industrial/Coal Pile 1.65 275,980 0.11 n/a n/a n/a

7 Residential 3.96 1,200,000 0.5 17,734 44 146

8 Forest 2.91 718,299 0.28 n/a n/a n/a

9 Residential 5.76 2,748,582 1.06 49,855 54 146

10 Mixed Forest/Barren/Residential 5.15 3,087,656 1.19 287,031 11 146

11 Residential 3.18 1,291,405 0.5 38,619 38 146

12 Mostly Residential 1.3 239,288 0.09 n/a n/a n/a

13 Forest 7.85 4,499,925 1.74 4,499,925 40 146

14 Mixed Forest/Residential 1.21 122,785 122,785 22 146

15 Mixed Forest/Residential 5.41 4,134,633 1.6 4,134,633 80 146

16 Forest/Hills 4.24 3,198,926 1.24 n/a n/a n/a

17 Forest/Cropland/Residential 4.86 2,801,357 1.08 114,250 21 146

18 Residential 19.45 34,958,895 13.5 39,706 54 146

19 Forest/Residential 14.19 11,938,847

20 Residential/Forest/Barren 4.62 3,180,327 73,514 59 111

21 Barren/Runways/Airport 8.3 6,849,235

22 Industrial 6.92 1,699,197 339,839 6976

23 Residential 11.83 14,695,522 28,218 37 146

24 Barren/Industrial 2.27 454,283

25 Residential/Wooded 8.07 7,609,588 74,561 81 146

26 Wooded/Cropland/Residential 6.67 5,197,661 66,715 8 146

27 Golf Course 1.63 419,115

28 Residential 7.63 7,733,346 16,856 18 146

29 Residential/Wooded 2.26 536,265 15,469 13 146

30 Industrial 2.04 509,617

31 Wooded/Cropland 24.47 82,882,447 1,470,939 103 146

32 Industrial 7.66 1,776,918 355,384

33 Residential 4.24 2,215,515 26,368 13 146

34 Barren 2.36 892,996

35 Wooded/Cropland 36.49 70,638,199 341,298 29 146

36 Residential/Cropland/Wooded 6.37 5,574,775 84,988 21 146

37 Wooded/Cropland/Residential 8.79 12,644,486 211,502 49 146

38 Residential Mostly 10.27 15,907,104 25,685 15 146

39 Residential Mostly 3.24 1,599,206 51577 21 146

40 Residential/Wooded 0.63 63,351 63351 25 146

41 Woods/Residential 13.59 15,840,865 308,674 64 14622 

### Table 2: Computational Spreadsheet for Regions (Sheet 2 of 2)

Type A a H Zo

Mixed Residential/Forest n/a n/a n/a

Residential 933.88 96.66 8 0.41

Mixed Residential/Barren n/a n/a n/a n/a

Industrial 24,780.26 195.96 10 0.21

Mostly Residential/Woods 1,195.48 96.66 8 0.32

Mixed Industrial/Coal Pile n/a n/a 10 n/a

Residential 403.05 96.66 8 0.96

Forest n/a n/a n/a n/a

Residential 923.24 96.66 8 0.42

Mixed Forest/Barren/Residential 26,093.73 96.66 8 0.01

Residential 1,016.29 96.66 8 0.38

Mostly Residential n/a n/a n/a n/a

Forest 112,498.13 96.66 8 0.00

Mixed Forest/Residential 5,581.14 96.66 8 0.07

Mixed Forest/Residential 51,682.91 96.66 8 0.01

Forest n/a n/a n/a n/a

Forest/Cropland/Residential 5,440.48 96.66 8 0.07

Residential 735.30 96.66 8 0.53

Forest/Residential n/a n/a n/a n/a

Residential/Forest/Barren 1,246.00 84.29 8 0.27

Barren/Runways/Airport n/a n/a n/a n/a

Industrial n/a n/a n/a n/a

Residential 762.65 96.66 8 0.51

Barren/Industrial n/a n/a n/a n/a

Residential/Wooded 920.51 96.66 8 0.42

Wooded/Cropland/Residential 8,339.38 96.66 8 0.05

Golf Course n/a n/a n/a n/a

Residential 936.44 96.66 8 0.41

Residential/Wooded 1,189.92 96.66 8 0.32

Industrial n/a n/a n/a n/a

Wooded/Cropland 14,280.96 96.66 8 0.03

Industrial n/a n/a n/a n/a

Residential 2,028.31 96.66 8 0.19

Barren n/a n/a n/a n/a

Wooded/Cropland 11,768.90 96.66 8 0.03

Residential/Cropland/Wooded 4,047.05 96.66 8 0.10

Wooded/Cropland/Residential 4,316.37 96.66 8 0.09

Residential Mostly 1,712.33 96.66 8 0.23

Residential Mostly 2,456.05 96.66 8 0.16

Residential/Wooded 2,534.04 96.66 8 0.15

Woods/Residential 4,823.03 96.66 8 0.08

As described above, the Lettau method (Lettau, 1969) was applied to compute surface

roughness values for residential, commercial, and industrial area based on silhouette area, and

plot area for representative samples in the common zones shown in Figure 14. Some areas,

however, such as forested areas, pasture land, etc., are not am enable to this method and

defaults were established that are appropriate for the modeling domain. The average

residential, commercial, and industrial land use types were established based on assigning

representative values from the Lettau analysis. Note that it is not feasible to account for the23 differences in the treatment of residential, commercial, or industrial within the 41 zones

throughout the study area. This would require manual manipulation of 160,000 cells

(approximately 40,000 grid cells by four seasons). Although some refinements clearly could be

made, the averaging approach was deemed representative and appropriate for the specific

mo deling domain. Rather, representative values were selected from the surface roughness

analysis, as well as for the other surface characteristics required in CALMET.

The Clairton plant industrial site sub

‐ region (applicable to primary location of buoyant

sources) was used to represent the surface roughness of the overall Clairton Works, as ot her

industrial areas within the modeling domain.

b. Other Surface Characteristics

The CALMET user’s guide (Scire et. al., 2000b) shows in Table 4

‐ 45 the default data to define

surface characteristics (Table 3). These values, complemented by relative seasonal factors

based on the AERMET user’s guide (EPA, 2004) were used to define annual average values for

the modeling domain (Table 4). As a st arting basis, the following annual defaults were compiled

for each significant land use category within the modeling domain:



### Table 3: Annual Average CALMET Default Surface Characteristics (Sheet 1 of 2)

Bowen Soil Heat Anthropogenic Leaf

Ratio Flux Heat Flux Area

11 RESIDENTIAL 0.19 1.20 0.19 5.00 1.68

13 INDUSTRIAL 0.18 1.50 0.25 30.00 0.00

15 INDUSTRIAL AND COMMERCIAL COMPLEXES 0.18 1.50 0.25 5572.73 0.00

21 CROPLAND AND PASTURE 0.15 1.00 0.15 0.00 3.00

41 DECIDUOUS FOREST LAND 0.10 1.00 0.15 0.00 7.00

42 EVERGREEN FOREST 0.10 1.00 0.15 0.00 7.00

43 MIXED FORESTLAND 0.10 1.00 0.15 0.00 7.00

52 LAKES (RIVERS) 0.10 0.00 1.00 0.00 0.00

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.30 1.00 0.15 0.00 0.05

76 TRANSITIONAL AREAS 0.22 1.25 0.20 0.00 0.35 CALMET DEFAULTS

Land Use

Type Description Albedo24 

### Table 3: Annual Average CALMET Default Surface Characteristics (Sheet 2 of 2)

Surface roughness (m)

Defaults

0.6200 40% Urban/40% Rangeland/20% Forest



### 0.2060 Urban



### 0.2060 Clairton map user-calculated values



### 0.2500 Agricultural Land - Unirrigated



### 1.0000 Forest Land



### 1.0000 Forest Land



### 1.0000 Forest Land



### 0.0010 Small Water Body



### 0.0500 Barren Land



### 0.5250 50% Urban/50% Rangeland 

### CALMET Classification Types



### Table 4: AERMET Averages for All Seasons

Bowen Soil Heat Anthropogenic Leaf

Ratio Flux Heat Flux Area

11 RESIDENTIAL 0.23 1.18 0.19 5.00 1.64

13 INDUSTRIAL 0.22 1.70 0.25 30.00 0.00

15 INDUSTRIAL AND COMMERCIAL COMPLEXES 0.22 1.70 0.25 5572.73 0.00

21 CROPLAND AND PASTURE 0.24 0.63 0.15 0.00 3.00

41 DECIDUOUS FOREST LAND 0.19 0.80 0.15 0.00 7.00

42 EVERGREEN FOREST 0.18 0.70 0.15 0.00 5.50

43 MIXED FORESTLAND 0.19 0.75 0.15 0.00 6.25

52 LAKES (RIVERS) 0.18 0.23 1.00 0.00 0.00

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.31 4.75 0.15 0.00 0.04

76 TRANSITIONAL AREAS 0.24 1.28 0.20 0.00 0.58 AERMET ANNUAL AVERAGES

Land Use

Type Description Albedo



### Surface roughness (m)

averaged to domain



### 0.6070 40% Urban/40% Grassland/20% Deciduous Forest



### 0.2060 Urban



### 0.2060 Clairton map user-calculated values



### 0.0550 Cultivated Land



### 0.9500 Deciduous Forest



### 1.3000 Coniferous Forest



### 1.1250 Mixed Forest (50% Deciduous/50% Coniferous)



### 0.0010 Water (Fresh and Sea)



### 0.2625 Desert Shrubland



### 0.5213 50% Urban/50% Grassland 

### AERMET Classification Types25 The following default assumptions were made:

• Transportation / communication corridors were treated as range land (CALPUFF

guidance) and grass land (AERMET guidance)

• Cropland and pasture were treated as agricultural land unirrigated (CALPUFF guidance)

and grassland (AERMET guidance)

• Mixed forests were treated as the averages of de ciduous and evergreen forests)

• Forested wetlands (just 1 grid cell) was defaulted to deciduous forest values

• Strip mines / quarries was defaulted to barren land (CALPUFF guidance)



### The annual average anthropogenic heat flux value was based on Piringer & Joffre 2



### , which shows typical urban/suburban values of 15 watts / m 2 

### . This value was considered

excessive for the population density in the Clairton area. Under the conditions specified

for discussion temperate climate, summer)typical daily average values of QF

(anthropogenic heat flux) range from about 5 watts / m2 in the suburb to 50 w / m2 in the

city centre, and show about a three-fold increase from night to daytime (e.g. Kalma et. al,

1972 for Syndey, Austrailia). On most occasions such figures will lie within the

precision to which the balance can be evaluated and can therefore be neglected. We used

Five watts / m 2 

### as a default value to represent residential areas within the model domain.

The industrial surfaces (with the exception of the USX Clairton Works, which was assigned a

separate category) were assigned an anthropogenic heat flux of 30 watts / m 2

, which is

consistent with city periphery from Piringer & Joffre. This is a relatively insensitive term, but

was included for completeness. Oke, 1978 3 was used as the basis to assign seasonal heat flux

factors (using New York City, which has a similar latitude as Pittsburgh), which resulted in

seasonal scaling factors as follows:

Season Seasonal Scaling

Factor

Anthropogenic

Heat Flux

Spring 1.0

Summer 0.3

Autumn 1.0

Winter 1.7

2 Piringer, Martin, and Sylvain Joffre, Urban Surface Energy Budget in European Cities, Final Report of

Working Group 2 of Cost 715 Action, 2005

3 Oke, T.R., “Boundary Layer Climates,” Methuen & Co. Ltd, Table 8.1, 1978.26 The leaf area index is generally computed based on the ratio of the upper leaf surface over

the total area evaluated. The annual estimates were based on the CALMET user’s guide, as

shown in Table 5. The annual estimated value for residential areas was defaulted to the

average of agricultural l and–un

‐ irrigated and urban (to account for partial vegetation within

residential properties (grass, trees, gardens, shrubs, etc.).

The seasonal estimates were defaulted based on interpretation of seasonal variability

shown in the Hanson, 2005. Coniferous forests were assigned seasonal scalars of 1.0 for all

seasons. The following seasonal scalars for deciduous t rees were developed from Hanson,

2005:



### Table 5: Seasonal Scaling Factors for LAI

Season Seasonal Scaling Factor

LAI

Spring 2.0

Summer 1.0

Autumn 1.0

Winter 0.0

The grassland seasonal values were used to represent residential, crops / pastures, and

transportation corridors. Urban, commercial, industrial, water, and strip mines / quarries were

set to seasonal factors of 1.0 as defaults (i.e. not applicable in this case).

The annual average values were then adjusted on a seasonal basis p rimarily based on

review of AERMET seasonal ratios. Many of the input terms are adjusted in winter to account

for snow cover. For example, the winter values in AERMET assume snow/ice covered conditions

during the winter months. In Allegheny County, the snow/ice cover category occurs

approximately one

‐ third of the time, i.e

. 33 days during the winter season based on

climatological data from 1941 through 1970. As a first approximation, weighting of winter

conditions was assigned a double weighting for autumn and single weighting for winter for all of

the surface parameters. The annual average values were adjusted by seasonal scaling fac tors

based on the ratio of the specific seasonal average over the annual average. Note that the

transitional land use category was assigned default values that were representative of average

values within the modeling domain.

Wetlands data shown in Table 1 above are representative of non

‐ forested wetlands.

Based on rev iew of the modeling domain, it is evident that the assignment of wetlands in the

NLCD LULC data

‐ base is not correct in terms of current land use. Many of these areas are now

used for industrial and recreational purposes. To refine the analysis, these areas were manually

reassigned to transitional areas (c ategory 76) as a more appropriate default. One grid cell

within the 40,000 was assigned as forested wetlands. This cell was not reassigned.

Transportation corridors were reassigned to be more representative of the modeling

domain. These corridors were defaulted to rangeland characteristics with the exception that

the surface roughness in th is setting was defaulted to 0.25 m to account for mixed27 characteristics of natural grass surfaces and larger obstructions to flow that would be

encountered at the fringes of the corridors.

Tables 6 through 9 present the seasonal tables that were used in the seasonal input files

to CALMET:



### Table 6: Spring

AERMET Estimated AERMET Estimated AERMET Estimated AERMET

Albedo Albedo Bowen Ratio Bowen Ratio Leaf Index Leaf Index Surface Roughness

11 RESIDENTIAL 0.15 0.13 0.70 0.71 1.68 1.72 0.62

13 INDUSTRIAL 0.14 0.12 1.00 0.88 0.00 0.00 0.20

15 INDUSTRIAL AND COMMERCIAL COMPLEXES 0.14 0.12 1.00 0.88 0.00 0.00 0.21

21 CROPLAND AND PASTURE 0.14 0.09 0.30 0.48 3.00 3.00 0.03

41 DECIDUOUS FOREST LAND 0.12 0.06 0.70 0.88 7.00 7.00 1.00

42 EVERGREEN FOREST 0.12 0.07 0.70 1.00 7.00 8.91 1.30

43 MIXED FORESTLAND 0.12 0.06 0.70 0.93 7.00 7.84 1.15

52 LAKES (RIVERS) 0.12 0.07 0.10 0.00 0.00 0.00 0.001

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.30 0.29 3.00 0.63 0.05 0.07 0.30

76 TRANSITIONAL AREAS 0.16 0.15 0.70 0.69 0.35 0.21 0.53 Land Use Type Description



### Table 7: Summer

AERMET Estimated AERMET Estimated AERMET Estimated AERMET

Albedo Albedo Bowen Ratio Bowen Ratio Leaf Index Leaf Index Surface Roughness

11 RESIDENTIAL 0.16 0.14 1.18 1.20 3.20 3.28 0.70

13 INDUSTRIAL 0.16 0.13 2.00 1.76 0.00 0.00 0.20

15 INDUSTRIAL AND COMMERCIAL COMPLEXES 0.16 0.13 2.00 1.76 0.00 0.00 0.21

21 CROPLAND AND PASTURE 0.20 0.12 0.50 0.80 6.00 6.00 0.10

41 DECIDUOUS FOREST LAND 0.12 0.06 0.30 0.38 14.00 14.00 1.30

42 EVERGREEN FOREST 0.12 0.07 0.30 0.43 7.00 8.91 1.30

43 MIXED FORESTLAND 0.12 0.06 0.30 0.40 10.50 11.76 1.30

52 LAKES ( RIVERS ) 0.10 0.06 0.10 0.00 0.00 0.00 0.001

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.28 0.27 4.00 0.84 0.05 0.07 0.30

76 TRANSITIONAL AREAS 0.17 0.15 1.40 1.37 1.35 0.82 0.55 Land Use Type Description



### Table 8: Autumn

AERMET Estimated AERMET Estimated AERMET Estimated AERMET

Albedo Albedo Bowen Ratio Bowen Ratio Leaf Index Leaf Index Surface Roughness

11 RESIDENTIAL 0.18 0 .15 1.40 1.42 1.68 1.72 0.56

13 INDUSTRIAL 0.18 0.15 2.00 1.76 0.00 0.00 0.20

15 INDUSTRIAL AND COMMERCIAL COMPLEXES 0.18 0.15 2.00 1.76 0.00 0.00 0.21

21 CROPLAND AND PASTURE 0.18 0.11 0.70 1.12 3.00 3.00 0.05

41 DECIDUOUS FOREST LAND 0.12 0.06 1.00 1.25 7.00 7.00 0.80

42 EVERGREEN FOREST 0.12 0.07 0.80 1.14 7.00 8.91 1.30

43 MIXED FORESTLAND 0.12 0.06 0.90 1.20 7.00 7.84 1.05

52 LAKES (RIVERS) 0.14 0.08 0.10 0.00 0.00 0.00 0.001

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.28 0.27 6.00 1.26 0.05 0.07 0.30

76 TRANSITIONAL AREAS 0.19 0.17 1.50 1.47 0.60 0.37 0.51 Land Use Type Description



### Table 9: Winter

AERMET Estimated AERMET Estimated AERMET Estimated AERMET

Albedo Albedo Bowen Ratio Bowen Ratio Leaf Index Leaf Index Surface Roughness

11 RESIDENTIAL 0.42 0.35 1.44 1.46 0.00 0.00 0.54

13 INDUSTRIAL 0.39 0.32 1.80 1.59 0.00 0.00 0.20

15 INDUSTRIAL AND COMME RCIAL COMPLEXES 0.39 0.32 1.80 1.59 0.00 0.00 0.21

21 CROPLAND AND PASTURE 0.45 0.28 1.00 1.60 0.00 0.00 0.04

41 DECIDUOUS FOREST LAND 0.40 0.21 1.20 1.50 0.00 0.00 0.70

42 EVERGREEN FOREST 0.37 0.20 1.00 1.43 1.00 1.27 1.30

43 MIXED FORESTLAND 0.38 0.21 1.10 1.47 0.50 0.56 1.00

52 LAKES ( RIVERS ) 0.34 0.19 0.60 0.00 0.00 0.00 0.001

75 STRIP MINES, QUARRIES, AND GRAVEL PITS 0.39 0.38 6.00 1.26 0.00 0.00 0.15

76 TRANSITIONAL AREAS 0.42 0.39 1.50 1.47 0.00 0.00 0.51 Land Use Type Description28 

## 4.0 Heat Analysis of USX Clairton Sources

The areas of the boilers and batteries and the area where the railcars transport the coke to

the quench towers were summed and the heat flux values from the plant and from the

combustion of the coke in air were calculated. From these values, the anthropogenic heat flux

values were calculated in te rms of watts/square meter. This was applied only to the areas

within the plant the generated large amounts of heat (see Figure 15). The heat flux values

calculated were based on calculations provided by the Clairton USX plant (see Table 10) and

converted to watts/square meter.29 

### Figure 15: Location of Heat Sources and Area Sources Defined by Grid Area

594.8 595.0 595.2 595.4 595.6 595.8 596.0 596.2 596.4 596.6 596.8 594.8 595 595.2 595.4 595.6 595.8 596 596.2 596.4 596.6 596.8

4461.6 4461.8 4462.0 4462.2 4462.4 4462.6 4462.8 4463.0 4463.2

4461.6 4461.8 4462 4462.2 4462.4 4462.6 4462.8 4463 4463.2 

### Plot of Combustion Sources and Heat Flux Areas30 

### Table 10: Summary Heat Release Estimates

SUMMARY HEAT RELEAS ESTIMATES PUSHING,

SOAKING & DECARB

June 27, 2007

MMBTU / DAY EQUIVALENT COG

GROSS NET (MMCFD) 1

PUSHING 2,237 2,053 4.56

SOAKING 331 285 0.66

DECARB 1,907 1,907 4.24

TOTAL 4,474 4,244 9.46

-----------------

Comparative Value:

Small Battery Underfiring Consumption Rate:

Coke Prod'n - tons / day 830

Coal Cons - tons / day 1,186

UF consumption - Btu / lb coal 1,100

UF Heating Value - Btu/CF 500

UF consumption - MMCF / day 5.22 1 EQUIVALENT COG EXPRESSED AS MILLION CUBIC

FEET AT 500 GROSS BTU PER CUBIC FOOT31 Calculations are provided below for the area sources that are the sources of the heat fluxes,

including the amount of heat produced by the plant during the coking operation plus the heat

produced by combustion from the pushing operation.

Total Area of Plant 142500 square meters

Total Heat Produced 794114206 Watts

Heat Flux 5572.73 Watts/m^2



## 5.0 Coordinate Problems / Resolution

The original emission inventory data for the model domain was developed using older

NAD27 coordinate system for the Universal Transverse Mercator (UTM) coordinates of the

source locations. The most current USGS mapping systems use NAD83 coordinates. In order to

maintain consistency among all mapping system, land use and terrain data, all CAL MET

preprocessors were set to derive the NAD83 coordinates during the data processing. The

coordinates for the emission inventory data within CALPUFF was also converted into the NAD83

coordinate system.32 

## 6.0 Potential for Low

­ Level Convergence During Stable Nocturnal

Conditions

Two sources of information were reviewed to evaluate the potential for low

‐ level

convergence caused by the rising heat plumes, which would be expected to be most evident

during light wind speed, nocturnal conditions: (1) the special meteorological study of 1996; and

(2) data from the USX site for the period of 19 95 through 1996.

Special Meteorological Study of 1996

– Appendix B contains this study report. Although a

very short

‐ term study and based on visual evidence rather than an intensive array of

meteorological sensors, some useful information can be obtained by reviewing these historical

records. Review of limited streamlines (see Fi gures 16 and 17 as examples) shows the potential

for up

‐ valley flow towards the heat sources at the coke facility. Down

‐ valley flow would be

towards the northwest at the Clairton Works. Note that the most westerly flow vector is located

at the approximate location of the USX Clairton m eteorological monitoring site. The limited

data showed intermittent periods with flow up

‐ river towards the heat sources. The SODAR data

that were available concurrent to this study showed that any convergence was below the 50m

level.

Figure 18 represents visual observations taken during the early morning hours of March 26,

1996. During this stable period strong down

‐ valley flow was observed at the Youghiogheny

River but weak up

‐ valley flow down river from the USX Clairton facility. It has been

hypothesized that blocking flow by the Youghiogheny River possibly coupled with low

‐ level

convergence near the plant (likely caused by the ri sing heat plumes) is creating the complex low

‐

level flow during nocturnal conditions. Site

‐ specific meteorological monitoring with low

threshold wind systems would be needed to refine the available data

‐ base, with coverage within

both the Youghiogheny and Monongahela valley floors.33 

### Figure 16: Flow Vectors (12/5/1995 0530)34 

### Figure 17: Flow Vectors 12/8/1995 010035 

### Figure 18: Observed Flow Vectors March 26, 199636 Long

‐ Term Meteorological Monitoring At USX Clairton Works

‐ Meteorological data were

collected from 1995 through 2001 just downriver from the northwest extreme of the Clairton

Works coal pile. These data were reviewed to display the most common wind directions

associated with light flow periods during nighttime periods with non

‐ overcast conditions.

Figures 19 through 21 provide frequency plots for su ch periods with wind speeds less than 6, 3,

and 1 mph respectively. As the wind speeds decrease, peak frequencies become more tightly

clustered within the range of 240 through 260 degrees. Minimal flow is shown from 315

degrees; however, which would approximately up

‐ river flow towards the heat sources. Fi gure

22 provides a general perspective on the river valley orientations in the vicinity of the Clairton

Works.



### Figure 19: Wind Direction Frequencies during Nocturnal Non

­ Overcast

Conditions with Wind Speeds < 6 mph37 

### Figure 20: Wind Direction Frequencies during Nocturnal Non

­ Overcast

Conditions with Wind Speeds < 3 mph38 

### Figure 21: Wind Direction Frequencies during Nocturnal Non

­ Overcast

Conditions with Wind Speeds < 1 mph39 

### Figure 22: General Domain within Study Area

Although it is likely that at least on an intermittent basis there is up

‐ valley flow towards the

rising heat plums near the coke ovens and quench towers, there is insufficient available data to

quantitatively incorporate this feature into the CALMET analysis, beyond accounting for heat

flux

‐ induced convergence near th e Clairton Works. Our recommendation is to evaluate model

performance in the CALPUFF modeling to be subsequently done with and without consideration

for treating low

‐ level fugitives near the heat sources by testing varying degrees of heat assigned

to the buoyant area sources

.40 The available emissions inventory for the non

‐ attainment area was reviewed to evaluate the

magnitude of emissions at the Clairton Works that have a high potential for being transported in

the low

‐ level flow. The following emissions spreadsheets were used for this review:

• USS CL 2002 Emis Inven for mo deling (emission rates)

• NEI 2002 PM 2.5 modeling inventory (stack specifications)

As an overall summary, Table 11 shows PM 2.5 (PM

2.5 filterable plus condensibles) as a

function of major source category within USX Clairton Works:



### Table 11: Summary of PM2.5 Emissions by Major Source Category

Source Numbers Type of Source PM 2.5

(Tons/Yr) Percent of

Total

Emissions

1

‐ 29 Batteries 285.4 67.0

30

‐ 34 Quench Towers 58.25 13.7

35

‐ 54 Boilers 43.38 10.2

63

‐ 77 Trans / Storage 16.33 3.8

78

‐ 91 Miscellaneous 4 22.65 5.3

Total 426.01 100.0

The SODAR data that is available for the non

‐ attainment area shows that from 50 m and

higher (the lowest vertical level with quantifiable data) that the general flow during critical

nighttime stable periods is consistent with regional flow.

Consideration of heat influences on subsequent CALPUFF modeling will need to address th e

issue of which sources within USX Clairton Works will enter the regional flow, compared to

sources that are more likely to be transported and dispersed in the localized flow. Review of

Table 12 can be interpreted as follows:

• Quench towers and battery stacks clearly have sufficient plume rise to en ter the

regional flow

• Transportation, storage, and the miscellaneous emissions have a high potential to enter

localized flow, although the subset in close proximity to the coke batteries could be

lofted into the regional flow as well. Fortunately in terms of addressing this uncertainty,

the total emissions in th is category are only approximately 9 percent of the total

emissions.

4 Note that miscellaneous includes emissions associated with paved and unpaved roads, emissions

from heavy

‐ duty vehicles, and other more minor categories.41 • Considering the very substantial heat source at the batteries (>5,000 watts/square

meter), it is likely that there is sufficient lift at the batteries to allow these emissions to

enter the regional flow. As a starting point in the CALPUFF analysis, this would be

recommended, pending confirmation during model performance eval uation.

• In order to evaluate the boilers, SCREEN 3 was used to roughly estimate effective plume

height during nighttime stable conditions and 1 m / sec wind speeds. Table 11 presents

the results of this analysis. As shown, there is sufficient lift for all of the boilers that will

adv ect this material into the regional flow.



### Table 12: Summary of Boiler Stack Specifications and Computed Plume Rise

Boiler # Stack # PM2.5

(g/sec) Height

(m) Exhaust

Temp(K) Exit

Vel

(m/sec) Dia (m) Calculated

Plume

Rise (m)

1 31 23.24 57.93 477.4 30.4 2.74 164

2 32 18.22 57.93 477.4 29.7 2.16 148

13 34 26.52 616.3 15.8 1.98 115

14 35 26.52 616.3 15.8 1.98 115

R

‐ 1 36 0.67 50.3 450.2 7.5 2.59 114

R

‐ 2 0.43

T

‐ 1 38 0.41 26.52 444.1 9.9 1.46 80

T

‐ 2 39 0.41 26.52 444.1 9.9 1.46 80

.42 

## 7.0 Model Options

Major features of the CALMET application and input data preparation are as follows

• The 12

‐ km MM5 winds for January 2002 through December 2002 were used to

initialize the three

‐ dimensional wind field predictions.

• CALMET objective procedures were used with local terrain and land use data to

adjust the MM 5 12

‐ km wind fields to 0.1 km mesh size grid. The pressure

‐ based

vertical level MM5 fields will be reduced and layer

‐ averaged resulting in 11 vertical

levels from the surface to 3,000 m.

• The “no observations” option (NOOBS=1) in the beta version of CALMET was used to

ext ract hourly precipitation and upper air temperature lapse rates from the MM5

data set.

• The relative humidity data was extracted from the MM5 simulations (rather than

using the nearest observation, generally from lowland areas) by setting IRHPROG=1.

• Surface observations from Allegheny County Airport within the study domain were

used to prov ide hourly cloud cover and ceiling height data

• The datum used for MM5 data by CALMET is “NWS

‐ 84”. The CALMET coordinate

system will be output as NAD83 based on datum as NAR

‐ C.

Besides the adjustments to albedo, Bowen ratio, surface roughness, anthropogenic heat

flux, and leaf area in dex parameters, the following seven key CALMET settings were also

carefully addressed:

• BIAS

‐ affects how the initial Step 1 winds are interpolated to each grid cell in each

vertical layer based on upper air and surface observations. The BIAS value ranges from

‐

1 to +1, and a value is input for each vertical layer.

• IEXTRP

‐ affects vertical extrapolation of surface winds, and whether layer 1 data from

upper air stations are ignored, and is normally is set to

‐ 4.

• TERRAD

‐ Is used in computing the kinematic effects (IKINE), the slope flow effects

(ISLOPE), and the blocking effects (IFRADJ) on the wind field. If TERRAD is too small, then

the nearby valley wall will not be seen. If TERRAD is too large, then the hill three valleys

away is seen, instead of th e one nearby. We recommend using a value of 0.5 km based43 on iterative model performance testing with CALMET and expected wind flow patterns

both within and outside of the valleys.

• R1 and R2

‐ are used in the construction of the Step 2 wind field, where the observed

winds are 'blended' in with the Step 1 winds. R1 represents the distance from a surface

observation station at which the surface observation and the Step 1 wind field are

weighted equally. R2 represents the comparable distance for w inds aloft. Typically, R1

and R2 are set to fairly small values, on the order of the grid scale size or less. Both R1

and R2 values of 1.5 km are recommended.

• RMAX1 and RMAX2

‐ are also used in the construction of the Step 2 wind field, where

the observed winds are 'blended' in with the Step 1 winds. Both RMAX1 and RMAX2

values of 1.5 km is recommended.

Based on the planned project goals, the CALMET default options were used in most cases

except for th e following example options provided in Table 13.44 

### Table 13: Key CALMET Input Parameter Options

CALMET Variable Selected value Rationale

NOOBS 1 Use MM5 upper air data

NPSTA

‐ 1 Use MM5 precipitation

data (to consider wet

deposition)

IEXTRP

‐ 4 Using MM5 for upper

levels, extrapolate

observed surface winds

aloft to account for valley

wind effects based on BIAS.

ZFACE 0.,20.,40.,80.,160.,320.,640.,

1000.,1500.,2000.,2500.,3000. Define 11 cell face heights

(m) in vertical grid

BIAS ‐ 1,

‐ 1,

‐ 1,

‐ 1, .5, .8, 1,

1, 1, 1, 1 Heavily weight surface

observations below valley

wall height of 200m and

then increase weighting of

upper air observations

above valley wall.

RMIN2

‐ 1 Not used since NOOBS=1;

IEXTRP=

‐ 1

IPROG 14 Use MM5 as a first guess

but allow CALMET to adjust

for terrain

TERRAD 0.5 Using formula of terrain

ridge to ridge distance

divided by 2 plus some

small factor

R1 & R2 1.5 This adjustment was data

dependent and projected

wind patterns were

compared to observed

wind flows (feedback

mechanism)

RMAX1 & RMAX2 1.5 This adjustment was

dependent on met data

sites relative to terrain

valley/ridge features

ITPROG 1 Use surface stations and

MM5 for upper air

IRHPROG 1 Use MM5 relative humidity

SIGMAP 12 Set radius to the MM5grid

spacing45 

## 8.0 Inclusion of USX Clairton Meteorological Data

A 10

‐ meter tower meteorological monitoring station has been operating inside the USX Clairton

facility grounds since 2002 and is located just to the southwest of the main operations (see

Figure 11). This monitoring station is considered important to the modeling analysis as it is the

only site that likely represents th e low

‐ level wind flows in the Monongahela Valley in and around

the key USX Clairton facility. The meteorological monitoring station has been operated and

maintained by onsite USX environmental engineering personnel. Calibration data concerning

this monitoring instruments and quality assurance of the collected data are not available at the

ti me of this writing but should be incorporated into the total SIP documentation



### .

Data for the first half of 2002 is missing and the first day of data starts on August 13, 2002.

Review of this data found that two separate periods of data was determined to be invalid (data

values held constant). These two periods are September 25

‐ 29 and December 2

‐ 12.

A wi nd rose plot of the August 13

‐ December 31 period (taking out the invalid data) is

provided in Figure 23. As can be noted, the predominant flow at this site is from the WSW with

equal percentage from the south and NW components. It is also obvious from this wi nd rose

that there are no reported occurrences of wind direction from NE quadrant. It is conjectured,

although not independently confirmed, that the Lincoln hill located on the NE bank of the

Monongahela River just to the NE of the USX Clairton Facility is blocking the NE regional flow as

represented by th e Liberty site wind rose in Figure 24. A full year of hourly data for the USX site

for 2003 was also reviewed and it also showed this same pattern of predominant WSW winds

with no reported winds from the NE quadrant.

In relation to this comparison of USX Cla irton to the Liberty monitoring site, a scatter plot of

the corresponding hourly wind directions for these two sites was examined. This scatter plot is

presented in Figure 25. As can be noted, there is good correlation between the two sites for the

regional (represented by Liberty) SW and NW wind quadrant s. There appears to be a

divergence for the regional NE and SE wind quadrants and the observations at the USX Clairton

site. Again there are no reported NE winds at the USX Clairton site. When there is a regional NE

or SE quadrant flow pattern, the winds at USX Cla irton separate into either SE or a SW direction.

Based on discussions with our modeling group and further data review, this SE or SW wind

divergence appears to be dependent on the regional wind speed reported at Liberty. In other

words, the winds at USX Clairton tended to be more SE unde r stronger NE to SE regional flow,

while the lighter regional NE to SE winds tended to result in more frequent SW winds at USX

Clairton. This is consistent with the hypothesis that the predominant SW wind direction at the

USX Clairton site is enhanced by nocturnal drainage flow coming dow n a broader valley opening

located the SW of the site as well as thermal convergence towards the heated facility under light

regional winds.46 

### Figure 23: Wind Rose Plot for USX Clairton Meteorological Monitoring Site for

August 13

– December 31, 200247 

### Figure 24: Wind Rose Plot for Liberty Meteorological Monitoring Site for

August 13

– December 31, 200248 

### Figure 25: Wind Direction Scatter Plot for USX Clairton and Liberty Sites for

200249 In order to more fully document the USX Clairton site meteorological data, 10

‐ meter level

wind vector plots from the CALMET preprocessor and analyzed with CALVIEW were produced

for two separate time periods within the 2002 calendar year. One set was for data in early July

(where there is no dat a from the USX site) and the other set in late November (where USX data

is included). Example plots for these two periods are presented in Figures 26 and 27. The plot

for July 11, 2002 in Figure 26 shows a moderate NE regional flow that appears to be carried right

in to the Monongahela River valley without the influence of the USX site data. However, the plot

for November 12, 2002 (see Figure 27) shows the influence of including the USX Clairton site as

the wind flow within the valley is from the SW while there is a predominant NE regional wi nd

flow.

The preliminary data comparisons, representative wind vector plots, and some CALPUFF

model results were presented to the Region III meteorologist (Denny Lohman) regarding the

importance of the inclusion of this data set. After discussions with Region III, agreement was

reached that a regression analysis would be conducted for th e full

‐ year 2003 data set for both

the USX Clairton and Liberty sites to derive methodologies in order to fill

‐ in the missing 2002

data records for USX Clairton.

The regression analysis of the 2002 data was performed using an EXCEL spreadsheet with

various regression options available to properly correlate th e two data sets. This regression

analysis spreadsheet is included as Appendix D. The regional wind speeds at Liberty was used

as a guiding factor for the regression curves of wind direction based on the earlier findings of

our PM2.5 modeling workgroup. The regional wind speed regression plots were in 1 mp h

increments from 1 mph to 15 mph. Fifth

‐ order polynomial equations were found to reasonably

represent the wind direction variation for each of these plots when wind speed was 4 mph or

larger. Some example plots of these regression curves are provided in Figures 28 and 29. The

predicted US X Clairton wind directions are dependent on the observed wind direction at Liberty

based on this variance of Liberty wind speed. Because wind speed at USX Clairton is believed to

be highly dependent on the wind directions within the Monongahela Valley, the regression

curves used the predicted USX wind direction as th e dependent variable. As can be noted by

both wind speed regression analyses, wind speeds are shown to be lower for the SW (cross

valley direction) as opposed to the NW or SE (along valley directions). Similar regression curves

for temperature were also created based on hourly Liberty and USX Cla irton temperatures, but

were factored based on the hour of the day. Example temperature regression plots for various

hours of the day are presented in Figures 30 and 31.

From the regression analysis it was noted that the r

‐ squared values for the predicted USX

Clairton wind directions was well be low 0.5 for Liberty wind speeds less than 4 mph. It was

determined that for those lower wind speeds, the regression curves would not be applicable.

Therefore we applied the simple methodology of taking the average of the predicted wind

directions and then using the standard deviation (Monte Carlo) to develop a rang e of hourly

wind directions around that average. For wind speeds of 4 mph or greater the regression

equations were directly applied with no Monte Carlo variance.50 

### Figure 26: Low

­ level 10

­ meter AGL Wind Vector Plot for July 11, 2002 0500

LST51 

### Figure 27: Low

­ level 10

­ m Wind Vector Plot for November 12, 2002 0600 LST52 

### Figure 28: Regression Plot for Wind Direction and Wind Speed Based on Low

Wind Speeds (>2

­ 3 mph) at Liberty53 

### Figure 29: Regression Plot for Wind Direction and Wind Speed Based on

Moderate Wind Speeds (>8

­ 9 mph) at Liberty54 

### Figure 30: Regression Plots for Temperature for Hours 06 and 1255 

### Figure 31: Regression Plots for Temperature for Hours 18 and 2456 The regression curves (and Monte Carlo variance for the lower (<4 mph) wind speeds) for

both wind direction and wind speed based on the Liberty wind speed were then incorporated

into a FORTRAN program. The FORTRAN program integrated the 2002 hourly Liberty wind and

temperature data to fill

‐ in the mis sing hourly wind and temperature data of the original 2002

hourly USX SAMSON format data file used in the CALMET preprocessor. Comparison of the

August 13

‐ December 31, 2002 predicted versus observed wind direction and wind speed data is

provided in Figure 32.



### Figure 32: Regression Plots of the Observed versus Predicted Wind Directions

and Wind Speeds for USX Clairton for 200257 

### 9.0 Results

This results section presents example processed predicted 10

‐ meter AGL wind vector plots,

based on the final version of the CALMET input files (see Appendix C), for two separate

scenarios: 1) total particulate concentration days in each of the four seasons, and 2) nighttime

regional NE wind flows also for each of th e four seasons. The full 1

‐ year set of the predicted

wind vector flow fields within the 20

‐ km model domain are provided in Appendix A.

For this first scenario, the 10

‐ meter AGL Wind vector plots were chosen for four separate

days, one for each season, in which th e maximum observed total particulate concentration at

the Liberty site. Figure 33 provides the plot of the measured daily concentrations. Based on

that plot, the following days were chosen: 1) January 28, 2) April 17, 3) June 25, and 4)

September 10. These conditions represent the predominant SW regional flow in wh ich the

emissions from the major source at USX Clairton are blown NE towards the Liberty site.

The 10

‐ meter AGL Wind vectors, plotted every 200m, are represented by arrows that point

to the direction of the wind flow movement with the width and length of the arrow indicating

the rel ative wind speed. There are three wind vector plots for each day based on the

observation times of 0600, 1200, and 1800 local standard time (LST). Figures 34

‐ 36 are for the

January 28, 2002 conditions, Figures 37

‐ 39 are for the April 17, 2002 conditions, Figures 40

‐ 42

are for th e June 25, 2002 conditions, and Figures 43

‐ 45 are for the September 10, 2002

conditions.

In each case, you can note the consistent pattern of the SW flow across the full domain,

even in the river valley regions. In cases of the lightest SW wind in the early morning or even ing

hours, some bending of the wind vectors can be noted can be noted within the river valleys.58 

### Figure 33: Daily Measured Total Particulate Concentrations (μg/m 3 

### ) at Liberty

for 200259 

### Figure 34: 10

­ meter AGL Wind Vector Plot for 0600LST January 28, 200260 

### Figure 35: 10

­ meter AGL Wind Vector Plot for 1200LST January 28, 200261 

### Figure 36: 10

­ meter AGL Wind Vector Plot for 1800LST January 28, 200262 

### Figure 37: 10

­ meter AGL Wind Vector Plot for 0600LST April 17, 200263 

### Figure 38: 10

­ meter AGL Wind Vector Plot for 1200LST April 17, 200264 

### Figure 39: 10

­ meter AGL Wind Vector Plot for 1800LST April 17, 200265 

### Figure 40: 10

­ meter AGL Wind Vector Plot for 0600LST June 25, 200266 

### Figure 41: 10

­ meter AGL Wind Vector Plot for 1200LST June 25, 200267 

### Figure 42: 10

­ meter AGL Wind Vector Plot for 1800LST June 25, 200268 

### Figure 43: 10

­ meter AGL Wind Vector Plot for 0600LST September 10, 200269 

### Figure 44: 10

­ meter AGL Wind Vector Plot for 1200LST September 10, 200270 

### Figure 45: 10

­ meter AGL Wind Vector Plot for 1800LST September 10, 200271 The second scenario of wind vector plots is for the occurrence of NE regional wind flow over

the model domain. This scenario provides the comparison of the wind differences between the

Liberty monitor and the USX Clairton monitor under this particular wind regime as defined in

Section 8.0 of this report

.

The percentage of time that this NE regional wind flow is observed at the Liberty monitoring

site is presented in Table14. As can be noted in this table, there is a higher frequency of NE

winds during the summer and autumn months with an overall annual percentage of 12 % for th e

full year.



### Table 14: Percent of Occurrence of NE Regional Wind flow Reported at Liberty

Period of Year Percent of Occurrence

ANNUAL 12%

WINTER 8%

SPRING 8%

SUMMER 15%

AUTUMN 16%

The wind vector plots are presented as a group of four figures per chosen day, one day per

season. Figures 46

‐ 49 are for 0000 LST January 31, 2002 for 10

‐ meters AGL, 30

‐ meters AGL, 60

‐

meters AGL, and 120

‐ meters AGL respectively. Figures 50

‐ 53 are for 0000 LST Ma rch 25, 2002

for 10

‐ meters AGL, 30

‐ meters AGL, 60

‐ meters AGL, and 120

‐ meters AGL respectively. Figures

54

‐ 57 are for 0000 LST July 24, 2002 for 10

‐ meters AGL, 30

‐ meters AGL, 60

‐ meters AGL, and

120

‐ meters AGL respectively. Figures 58

‐ 61 are for 0000 LST Oc tober 12, 2002 for 10

‐ meters

AGL, 30

‐ meters AGL, 60

‐ meters AGL, and 120

‐ meters AGL respectively.

The pattern to notice in all of these cases is the rotation of the low

‐ level 10

‐ meter AGL west

or southwesterly wind flow in the USX Clairton location within the Monongahela Ri ver Valley

into the regional northeasterly regional flow in the 60

‐ 120 meter AGL levels. This pattern is a

consistent pattern observed by the onsite personnel observations of the quench tower plumes

of the USX Clairton facility. Based on those observations, the lower portions of the plume were

typically moving NE tow ards the valley walls on the opposite side of the river while the upper

portions would blow towards the SW as the plume moves at or above the valley walls. We

would recommend a thorough documentation of this northeast regional flow and southwesterly

return flow along the valley floor to con firm this event in order to provide more confidence in

the CALMET wind vector patterns being noted under these conditions.72 

### Figure 46: 10

­ meter AGL Wind Vector Plot for 0000LST January 31, 200273 

### Figure 47: 30

­ meter AGL Wind Vector Plot for 0000LST January 31, 200274 

### Figure 48: 60

­ meter AGL Wind Vector Plot for 0000LST January 31, 200275 

### Figure 49: 120

­ meter AGL Wind Vector Plot for 0000LST January 31, 200276 

### Figure 50: 10

­ meter AGL Wind Vector Plot for 0000LST March 25, 200277 

### Figure 51: 30

­ meter AGL Wind Vector Plot for 0000LST March 25, 200278 

### Figure 52: 60

­ meter AGL Wind Vector Plot for 0000LST March 25, 200279 

### Figure 53: 120

­ meter AGL Wind Vector Plot for 0000LST March 25, 200280 

### Figure 54: 10

­ meter AGL Wind Vector Plot for 0000LST July 24, 200281 

### Figure 55: 30

­ meter AGL Wind Vector Plot for 0000LST July 24, 200282 

### Figure 56: 60

­ meter AGL Wind Vector Plot for 0000LST July 24, 200283 

### Figure 57: 120

­ meter AGL Wind Vector Plot for 0000LST July 24, 200284 

### Figure 58: 10

­ meter AGL Wind Vector Plot for 0000LST October 12, 200285 

### Figure 59: 30

­ meter AGL Wind Vector Plot for 0000LST October 12, 200286 

### Figure 60: 60

­ meter AGL Wind Vector Plot for 0000LST October 12, 200287 

### Figure 61: 120

­ meter AGL Wind Vector Plot for 0000LST October 12, 200288 

### 10.0 Statistical Review of Model Performance Based on METSTAT

Testing of the METSTAT program with example CALMET files produced errors that could not

be resolved in time to complete this analysis. In lieu of the METSTAT statistical analysis, a

thorough comparison analysis was completed using visual observation of the CALMET predicted

wind vector flow patterns based on the changing of th e key variables described in Table 13. This

comparison analysis resulted in the final values of these key variables described in Table 13

based on the best results of the wind vector flow fields both within and outside of critical the

river valleys within the 20

‐ km model domain. The fi nal wind vector plots from the final values of

these key variables are presented in Section 9.0 and Appendix A.



### 11.0 Recommendations for Follow

­ On CALPUFF Modeling

If and when an updated set of CALMET pre

‐ processors are created by the CALPUFF model

developers for the use of the 2001 NLCD land use data format, then we would recommend

updating the entire CALMET geophysical data base with this more recent format. The use of this

more recent 2001 dat a format would enhance the land use definition within the 20

‐ km model

domain and would result in better definition of dispersion characteristics.

We would encourage a follow

‐ up investigation on the wind flow patterns within the

Monongahela River Valley in and around the USX Clairton facility during NE regional wi nd flow.

Documentation of this apparent vertical vortex of winds around and through the valley at this

critical location could be used to provide a firm basis in which to verify the predicted wind

patterns noted in this region.89 

### 12.0 References

EPA (U.S. Environmental Protection Agency), 2004: User’s Guide for the AERMOD

Meteorological Preprocessor (AERMET). EPA

‐ 454/B

‐ 03

‐ 002, U.S. Environmental Protection

Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. November

2004.

EPA (U.S. Environmental Protection Agency), 2003: Guideline on Air Quality Models

(Revised). U.S. Environmental Protection Agency, 40 CF R 51 Appendix W, Office of Air Quality

Planning and Standards, Research Triangle Park, NC.

40 CFR Part 51, Appendix W. Guidelines on Air Quality Models

Hanson, P. J., 2005: Relative Leaf Area Index (LAI) Data. Oak Ridge National Laboratory,

http://tde.ornl.gov/rellai.html

, July 5, 2005.

Hochhauser, M.L., 2004: Allegheny County Health Department Air Quality Program Point

Source Emission Inventory Report for 2003. December 10, 2004.



### Lettau, H., “Note on Aerodynamic Roughness

‐ Parameter Estimation on the Basis of

Roughness

‐ Element Description,” Journal of Applied Meteorology, 1969, Pages 828

–

832.

Oke, T.R., 1982: The Energetic Basis of the Heat Island Effect, Quarterly Journal of the Royal

Meteorological Society, Volume 108, No. 455, pp. 1

‐ 24. January 1982.

Oke, T.R., “Boundary Layer Climates,” Methuen & Co. Ltd, Table 8.1, 1978

Piringer, Martin, and Sylvain Joffre, 2005: Urban Surface Energy Budget in European Cit ies,

Final Report of Working Group 2 of Cost 715 Action, 2005

Scire, J.S., D.G. Strimaitis, and R.J. Yamartino, 2000a: A User’s Guide for the CALPUFF

Dispersion Model (Version 5). Earth Tech, Inc., Concord, MA, January, 2000, 521 pp.

Scire J., Robe F.R., Fernau M.E., Yamartino R.J., 2000b: A User's Gui de for the CALMET

Meteorological Model (Version 5). Earth Tech, Inc., Concord, MA, January, 2000, 332 pp.90 

### Appendix A: Full 1

­ Year (2002) Set of CALMET Predicted Wind Vector Flow

Fields

The attached file called “APPENDIX_A.ZIP” contains a full set of seasonal zipped files

contains the predicted wind vector fields for the lowest 6

‐ levels (10m, 30m, 60m, 120m, 240m,

and 480m).

The seasonal zip files included in this main zip file are named:

1. WINT

‐ JF.ZIP (January and February)

2. SPRN.ZIP (M arch, April, and May)

3. SUMM.ZIP (June, July, and August)

4. AUTM.ZIP (September, October, and November)

5. WINT

‐ D.ZIP (December)

Two additional files are also included for plotting purposes within CALVIEW:

1. LIBCMN.CMN (common grid file for CALVIEW)

2. BASE.SRF (base map for CALVIEW)91 

### Appendix B: Special Meteorological Study of 1996

The attached zip File named “APPENDIX_B.ZIP” contains summary report named “Meteorology

– Clairton Area 1996.pdf”92 

### Appendix C: Final Version of the Seasonal CALMET Input File

The attached zipped file named “APPENDIX_C.ZIP” contains the following CALMET input

files:

1. WINT

‐ JF.INP ( January and February)

2. SPRN.INP (March, April, and May)

3. SUMM.INP (June, July, and August)

4. AUTM.INP (September, October, and November)

5. WINT

‐ D.INP (December)93 

### Appendix D: Regression Analysis Spreadsheet for USX Clairton

The attached zip file named “APPENDIX_D.ZIP” contains the EXCEL Spreadsheet named

“LIB_USX_2003_MET_REV.XLS”.