Loading (50 kb)...'
(continued)
[FNFOOTNOTE:] 4 Refer to Step 1 for terrain adjustment data. Note that the distance from the source to the outer radii of each range is used. For example, for the range >0.5-2.5 km, the maximum terrain rise in the range 0.0-2.5 km is used.
Table 5.0-1. -Estimated Plume Rise (in Meters) Based on Stack Exit Flow Rate
and Gas Temeprature
Exhaust Temperature ( [FNo] K)
Flow rate (m [FN3]/s) <325 325- 350- 400- 450- 500- 600- 700- 800- 1000- >1499
399 449 499 599 699 799 999 1499
<0.5 0 0 0 0 0 0 0 0 0 0 0
0.5-0.9 0 0 0 0 0 0 0 0 1 1 1
1.0-1.9 0 0 0 0 1 1 2 3 3 3 4
2.0-2.9 0 0 1 3 4 4 6 6 7 8 9
3.0-3.9 0 1 2 5 6 7 9 10 11 12 13
4.0-4.9 1 2 4 6 8 10 12 13 14 15 17
5.0-7.4 2 3 5 8 10 12 14 16 17 19 21
7.5-9.9 3 5 8 12 15 17 20 22 22 23 24
10.0-12.4 4 6 10 15 19 21 23 24 25 26 27
12.5-14.9 4 7 12 18 22 23 25 26 27 28 29
15.0-19.9 5 8 13 20 23 24 26 27 28 29 31
20.0-24.9 6 10 17 23 25 27 29 30 31 32 34
25.0-29.9 7 12 20 25 27 29 31 32 33 35 36
30.0-34.9 8 14 22 26 29 31 33 35 36 37 39
35.0-39.9 9 16 23 28 30 32 35 36 37 39 41
40.0-49.9 10 17 24 29 32 34 36 38 39 41 42
50.0-59.9 12 21 26 31 34 36 39 41 42 44 46
60.0-69.9 14 22 27 33 36 39 42 43 45 47 49
70.0-79.9 16 23 29 35 38 41 44 46 47 49 51
80.0-89.9 17 25 30 36 40 42 46 48 49 51 54
90.0-99.9 19 26 31 38 42 44 48 50 51 53 56
100.0-119.9 21 26 32 39 43 46 49 52 53 55 58
120.0-139.9 22 28 35 42 46 49 52 55 56 59 61
140.0-159.9 23 30 36 44 48 51 55 58 59 62 65
160.0-179.9 25 31 38 46 50 54 58 60 62 65 67
180.0-199.9 26 32 40 48 52 56 60 63 65 67 70
>199.9 26 33 41 49 54 58 62 65 67 69 73
Table 5.0-2 -Selection of Generic Source Number
______________________________________
Effective stack height (m) Generic
source No.
______________________________________
<10.0 1
10.0-14.9 2
15.0-19.9 3
20.0-24.9 4
25.0-30.9 5
31.0-41.9 6
42.0-52.9 7
53.0-64.9 8
65.0-122.9 9
113.0+ 10
Downwash 11
______________________________________
Table 5.0-3 -Classification of Land Use Types
_________________________________________________________
Type Description Urban or
rural
designation
_________________________________________________________
I1 Heavy Industrial Urban
I2 Light/Moderate Industrial Urban
Cl Commercial Urban
R1 Common Residential (Normal Easements) Rural
R2 Compact Residential (Single Family) Urban
R3 Compact Residential (Multi-Family) Rural
R4 Estate Residential (Multi-Acre Plots) Rural
A1 Metropolitan Natural Rural
A2 Agricultural Rural
A3 Undeveloped (Grasses/Weeds) Rural
A4 Undeveloped (Heavily Wooded) Rural
A5 Water Surfaces Rural
_________________________________________________________
[FNFOOTNOTE:] 1 US EPA, Guideline on Air Quality Models (Revised), EPA-450/2-78-027R, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina, July, 1986.
[FNFOOTNOTE:] 2 Auer, August H. Jr., "Correlation of Land Use and Cover with Meteorological Anomalies," Journal of Applied Meteorology, pp. 636-643, 1978.
_______________________________________________________________________________
Distance range Effective stack- - Maximum terrain- = TAESH (m)
(km) height (m) [see rise (m) (see
step step
5(B)] 1)
_______________________________________________________________________________
0.0-05 _____ - _____ = _____
>0.5-2.5 _____ - _____ = _____
>2.5-5.0 _____ - _____ = _____
If The terrain rise for any of the distance ranges is greater than the effective stack height, set the TAESH equal to zero and use generic source number 1 for that distance range.
Record the generic source numbers from Table 5.0-2 based on each of the TAESH values.
______________________________________________________________
Distance range (km) Generic source No. (after terrain
adjustment)
______________________________________________________________
0.0 - 0.5 _______ _____
>0.5 - 2.5 _______ _____
>2.5 - 5.0 _______ _____
______________________________________________________________
Step 6. Classify the Site as Urban or Rural
(A) Classify the land use near the facility as either urban or rural by determining the percentage of urban land use types (as defined in Table 3; for further guidance see the footnoted references) that fall within 3 km of the facility [FN5].
[FNFOOTNOTE:] 5 The delineation of urban and rural areas, can be difficult for the residential-type areas listed in Table 5.0-3. The degree of resolution in Table 5.0-3 for residential areas often cannot be identified without conducting site area inspections. This process can require extensive analysis, which, for many applications, can be greatly streamlined without sacrificing confidence in selecting the appropriate urban or rural classification. The fundamental simplifying assumption is based on the premise that many applications will have clear-cut urban/rural designations, i.e., most will be in rural settings that can be definitively characterized through a review of aerial photographs, zoning maps, or U.S. Geological Survey topographical maps.
Method Used to Visual Planimeter
Estimate Percent
Urban Land Use: _____ _____
_____ _____
Estimated Urban Rural
Percentages _____ _____
If the urban land use percentage is less than or equal to 30 percent based on a visual estimate, or 50 percent based on a planimeter, the local land use is considered rural. Otherwise, the local land use is considered urban.
Classification (check Urban Rural
applicable space.) ______ _______
(B) Based on the TAESH and the urban/rural classification of surrounding land use, use the following table to determine the threshold distance between any stack and the nearest facility boundary.
Distance (m)
Terrain adjusted effective stack Urban Rural
height range (m)
1-9.9 200 200
10-14.9 200 250
15-19.9 200 250
20-24.9 200 350
25-30.9 200 450
31-41.9 200 550
42-52.9 250 800
53-64.9 300 1000
65-112.9 400 1200
113+ 700 2500
Record the following information:
Threshold distance from the table (m):
Minimum distance from any stack to property boundary (m):
If the minimum distance between any stack and the nearest facility boundary is greater than the threshold distance, the surrounding buffer distance is considered significant and the facility is likely to benefit from use of the HWCAQSP relative to the Tier I and II limits (see discussion of benefits from using HWCAQSP in Introduction section).
Step 7. Determine Maximum Dispersion Coefficients
(A) Determine maximum average hourly dispersion coefficients. Based on the results of Step 6(A), select either Table 5.0-4 (urban) or Table 5.0-5 (rural) to determine the maximum average hourly dispersion coefficient [FN6]. For flat terrain [defined in Step 5(D)] and for all sites with generic source numbers 1 or 11, use Step 7(A)(1). For rolling or complex terrain (excluding generic sources numbers 1 and 11), use Step 7(A)(2).
[FNFOOTNOTE:] 6 For the distance range 6 to 20 kilometers, generic source number 1 is used to conservatively represent the maximum dispersion coefficient.
(1) Search down the appropriate generic source number column [based on Step 5(C)], beginning at the minimum fenceline distance listed in Step 6(B) [FN7]. Record the maximum average hourly dispersion coefficient encountered.
[FNFOOTNOTE:] 7 Exclude all distances that are closer to the facility than the property boundary. For example, if the actual distance to the nearest property boundary is 265 meters, begin at the 300 meter distance in Tables 5.0- 4 and 5.0-5.
Maximum Average Hourly Dispersion
Coefficient = (m/m [FN3] /g/sec)
(2) For each of the three distance-based generic source numbers listed in Step 5(E), search down the appropriate generic source number columns, beginning at the minimum fenceline distance listed in Step 6(B). Note that different columns may be used for each of the three distance ranges if there is a need for terrain adjustment. Record the maximum dispersion coefficient for each generic source number.
Distance Generic source No. Maximum dispersion
range (from Step 5(E)] coefficient (<>g/m [FN3]/m/sec)
(km)
0.0-0.5 _____ _______
>0.5-2.5 _____ _______
>2.5-5.0 _____ _______
>5.0-20.0 _____ _______
Table 5.0-4 -ISCST Predicted Maximum Concentrations (mg/m [FN3]) [FNa]
for Hazardous Waste Combustors Using Urban Conditions
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Distance Generic Generic Generic Generic Generic Generic Generic
(KM) Source Source Source Source Source Source Source
#1 #2 #3 #4 #5 #6 #7
(<10M) (10M) (15M) (20M) (25M) (31M) (42M)
0.20 680.1 517.5 368.7 268.7 168.5 129.8 63.4
0.25 521.9 418.2 303.6 232.6 163.0 124.2 67.6
0.30 407.7 351.7 256.2 199.0 147.0 118.3 63.5
0.35 326.2 304.2 221.6 172.7 130.2 107.9 60.0
0.40 268.5 268.5 195.6 152.5 115.7 97.1 59.6
0.45 240.8 240.7 175.4 136.7 103.9 87.6 56.6
0.50 218.5 218.5 159.2 124.1 94.4 79.7 52.9
0.55 200.3 200.3 145.9 113.8 86.5 73.1 49.2
0.60 185.1 185.1 134.9 105.1 80.0 67.6 45.8
0.65 172.2 172.2 125.5 97.8 74.4 62.9 42.7
0.70 161.2 161.2 117.4 91.6 69.6 58.9 40.1
0.75 151.6 151.6 110.5 86.1 65.5 55.4 37.7
0.80 143.2 143.2 104.4 81.4 61.9 52.3 35.6
0.85 135.8 135.8 99.0 77.2 58.7 49.6 33.8
0.90 129.2 129.2 94.2 73.4 55.8 47.2 32.1
0.95 123.3 123.3 89.9 70.1 53.3 45.0 30.7
1.00 118.0 118.0 86.0 67.0 51.0 43.1 29.4
1.10 108.8 108.0 79.3 61.8 47.0 39.7 27.1
1.20 101.1 101.1 73.7 57.4 43.7 36.9 25.2
1.30 94.6 94.6 68.9 53.7 40.9 34.5 23.5
1.40 89.0 89.0 64.8 50.6 38.5 32.5 22.1
1.50 84.1 84.1 61.3 47.8 36.3 30.7 20.9
1.60 79.8 79.8 58.2 45.4 34.5 29.2 19.9
1.70 76.0 76.0 55.4 43.2 32.9 27.8 18.9
1.80 72.7 72.7 53.0 41.3 31.4 26.5 18.1
1.90 69.6 69.6 50.7 39.6 30.1 25.4 17.3
2.00 66.9 66.9 48.8 38.0 28.9 24.4 16.7
2.25 61.1 61.1 44.5 34.7 26.4 22.3 15.2
2.50 56.4 56.4 41.1 32.1 24.4 20.6 14.0
2.75 52.6 52.6 38.3 29.9 22.7 19.2 10.0
3.00 49.3 49.3 35.9 28.0 21.3 18.0 9.4
4.00 40.2 40.2 29.3 22.8 17.4 14.7 7.6
5.00 34.5 34.5 25.2 19.6 14.9 12.6 6.6
6.00 30.7 30.7 30.7 30.7 30.7 30.7 30.7
7.00 27.8 27.8 27.8 37.8 27.8 27.8 27.8
8.00 25.5 25.5 25.5 25.5 25.5 25.5 25.5
9.00 23.8 23.8 23.8 23.8 23.8 23.8 23.8
10.00 22.3 22.3 22.3 22.3 22.3 22.3 22.3
15.00 17.6 17.6 17.6 17.6 17.6 17.6 17.6
20.00 15.0 15.0 15.0 15.0 15.0 15.0 15.0
1...+...10....+...20....+...30....+...40....+...50....+...60....+...70....+
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Generic Generic Generic Generic
Source Source Source Source
#8 #9 #10 #11
(53M) (65M) (113M) (Down-
wash)
30.1 18.4 1.6 662.3
38.5 19.8 3.2 500.0
41.5 25.0 4.2 389.3
40.5 27.3 5.4 311.9
37.8 27.4 5.8 268.5
37.2 26.3 5.8 240.8
36.7 24.7 5.8 218.5
35.4 24.5 6.6 200.3
33.8 24.3 7.1 185.1
32.0 23.7 7.4 1 72.2
30.2 22.9 7.5 1 61.2
28.6 22.0 7.5 1 51.6
27.1 21.1 7.4 1 43.2
25.7 20.2 7.2 13 5.8
24.5 19.3 7.0 12 9.2
23.4 18.5 6.8 12 3.3
22.4 17.7 6.5 11 8.0
20.6 16.4 6.5 10 8.8
19.2 15.2 6.4 10 1.1
18.0 14.2 6.3 94.6
16.9 13.4 6.1 89.0
16.0 12.7 5.9 84.1
15.2 12.0 5.6 79.8
14.4 11.4 5.4 76.0
13.8 10.9 5.2 72.7
13.2 10.5 5.0 69.6
12.7 10.1 4.8 66.9
11.6 9.2 4.4 61.1
10.7 8.5 4.1 56.4
10.0 7.9 3.8 52.6
9.4 7.4 3.6 49.3
7.6 6.1 2.9 40.2
6.6 5.2 2.5 34.5
30.7 30.7 30.7 30. 7
27.8 27.8 27.8 27. 8
25.5 25.5 25.5 25. 5
23.8 23.8 23.8 23. 8
22.3 22.3 22.3 22 .3
17.6 17.6 17.6 17 .6
15.0 15.0 15.01 1 5.0
76.......+...90....+....0....+...10.
[FNFOOTNOTE:] 3 Based on a 1 Gram/Second Emission Rate
Table 5.0-5. -ISCST Predicted Maximum Concentrations (mg/m [FN3]) [FNa]
for Hazardous Waste Combustors Using Rural Conditions
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******** This is piece 1. -- It begins at character 1 of table line 1. ********
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Distance Generic Generic Generic Generic Generic Generic Generic
(KM) Source Source Source Source Source Source Source
#1 #2 #3 #4 #5 #6 #7
(<10M) (10M) (15M) (20M) (25M) (31M) (42M)
0.20 1771.1 670.3 308.6 176.8 102.8 76.5 28.0
0.25 1310.6 678.4 316.9 183.6 104.6 71.8 38.0
0.30 1022.3 629.2 303.4 199.1 100.4 75.0 39.7
0.35 798.4 569.6 282.3 200.7 117.0 71.1 36.3
0.40 656.9 516.5 278.7 194.4 125.2 82.7 25.3
0.45 621.5 471.1 277.6 184.3 127.5 89.7 35.6
0.50 633.5 432.4 272.0 172.7 125.7 92.9 34.4
0.55 630.1 399.2 263.8 168.0 121.6 93.3 38.6
0.60 616.6 370.4 254.0 169.1 116.2 91.8 42.6
0.65 596.7 345.4 243.6 168.1 110.3 89.2 45.3
0.70 573.2 323.4 232.9 165.6 104.5 85.8 47.0
0.75 546.9 304.0 222.3 162.0 98.8 82.2 47.7
0.80 520.9 286.8 212.1 157.7 98.8 78.5 47.8
0.85 495.7 271.5 202.4 153.0 99.0 74.9 47.4
0.90 471.5 257.8 193.3 148.1 98.6 71.4 46.6
0.95 448.5 245.4 184.7 143.1 97.6 72.3 45.6
1.00 426.8 234.2 176.8 138.1 96.3 72.6 44.4
1.10 387.5 214.7 162.5 128.2 91.9 71.1 41.8
1.20 353.5 198.4 150.3 119.3 87.4 69.1 39.1
1.30 323.0 189.6 139.9 111.5 82.9 66.7 36.6
1.40 296.6 182.2 130.8 104.5 78.7 64.2 34.3
1.50 273.3 174.6 122.9 98.3 74.7 61.6 32.3
1.60 252.7 167.0 115.9 92.8 71.0 59.1 31.8
1.70 234.5 159.6 109.7 87.9 67.6 56.7 31.6
1.80 218.3 152.4 104.1 83.5 64.4 54.3 31.3
1.90 203.7 145.6 99.1 79.5 61.5 52.1 30.9
2.00 190.7 139.1 94.6 75.9 58.8 50.0 30.4
2.25 164.4 124.5 85.1 68.3 53.0 45.4 28.9
2.50 143.7 112.1 77.3 62.1 48.2 41.4 27.2
2.75 127.0 101.5 70.9 56.9 38.1 38.1 25.6
3.00 113.4 92.4 65.6 52.6 35.2 35.2 24.0
4.00 78.8 67.3 50.6 40.6 27.2 27.2 29.0
5.00 59.1 54.6 41.4 33.2 22.2 22.2 15.6
6.00 56.7 46.7 46.7 46.7 46.7 46.7 46.7
7.00 40.4 40.4 40.4 40.4 40.4 40.4 40.4
8.00 35.8 35.8 35.8 35.8 35.8 35.8 35.8
9.00 32.2 32.2 32.2 32.2 32.2 32.2 32.2
10.00 9.4 29.4 29.4 29.4 29.4 29.4 29.4
15.00 20.5 20.5 20.5 20.5 20.5 20.5 20.5
20.00 15.9 15.9 15.9 15.9 15.9 15.9 15.9
1...+...10....+...20....+...30....+...40....+...50....+...60....+...70....
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Generic Generic Generic Generic
Source Source Source Source
#8 #9 #10 #11
(53M) (65M) (113M) (Down-
wash)
10.1 3.5 0.0 1350.8
17.6 7.9 0.2 1227.3
24.0 12.6 0.8 1119.3
25.9 16.8 1.9 1023.8
24.6 18.1 3.1 938.9
21.7 17.6 4.3 851.8
21.6 15.9 5.5 787.8
22.1 13.6 6.5 730.6
21.7 14.3 6.7 676.4
20.9 14.7 6.4 633.4
23.3 14.6 5.9 592.0
25.5 14.3 5.5 554.6
27.1 13.8 5.1 522.1
28.3 15.0 4.7 491.8
29.1 16.3 4.5 464.2
29.6 17.3 4.2 438.9
29.8 18.2 4.0 415.8
29.5 19.3 3.9 375.0
28.6 19.8 4.1 340.3
27.5 19.8 4.2 310.4
26.2 19.5 4.2 284.6
24.9 19.0 4.2 2 62.0
23.6 18.4 4.2 2 42.2
22.5 17.7 4.3 2 24.7
21.4 17.0 4.5 2 11.9
20.4 16.3 4.8 19 8.4
19.5 15.7 5.1 18 6.3
18.1 14.2 5.4 16 0.8
17.9 12.9 5.5 14 0.7
17.5 11.8 5.4 12 4.5
17.0 11.2 5.2 112 .5
14.3 10.4 4.3 78.3
12.0 9.3 3.5 58.8
46.7 46.7 46.7 46. 7
40.4 40.4 40.4 40. 4
35.8 35.8 35.8 35. 8
32.2 32.2 32.2 32. 2
29.4 29.4 29.4 29. 4
20.5 20.5 20.5 20 .5
15.9 15.9 15.9 15 .9
75..80....+...90....+....0....+...1
[FNFOOTNOTE:] a Based on a 1 Gram/Second Emission Rate
(B) Determine annual/hourly ratio for rural analysis. The maximum average annual dispersion coefficient is approximated by multiplying the maximum hourly dispersion coefficient (identified in Step 7(A) by the appropriate ratio selection from Table 5.0-6. The generic source number(s) [from Steps 5(C) or 5(E)], urban/rural designation (from Step 6), and the terrain type are used to select the appropriate scaling factor. Use the noncomplex terrain designation for all sources located in flat terrain, for all sources where the physical stack height of the worst-case stack is less than or equal to 10 m, for all sources where the worst-case stack is less than the minimum GEP, and for those sources where all of the TAESH values in Step 5(E) are greater than zero. Use the complex terrain designation in all other situations.
(C) Determine maximum average annual dispersion coefficient. The maximum average annual dispersion coefficient is determined by multiplying the maximum hourly dispersion coefficient (Step 7(A)) by its corresponding annual/hourly ratio (Step 7(B)).
Terrain Distance from Generic Maximum hourly Annual Maximum
stack (m) source
No. dispersion co- hourly annual
efficient ratio dispersion
(<>g/m coefficient
[FN3]/g/sec)
(<>g/m
[FN3]/g/sec)
Flat 0-20.0
0-0.5
>0.5-2.5
Rolling >2.5-5.0
or
Complex >5.0-20.0
[FNFOOTNOTE:] 1 Maximum hourly dispersion coefficient times annual/hourly ratio.
Step 8: Estimate Maximum Ambient Air Concentrations -see procedures prescribed in article 8 of chapter 16.
Step 9: Determine Compliance with Regulatory Limits -see procedures prescribed in article 8 of chapter 16.
Step 10: Multiple Stack Method (Optional)
This option is a special case procedure that may be helpful when (1) the facility exceeded the regulatory limits for one or more pollutants, as detailed in Step 9, and (2) the facility has multiple stacks with substantially different emission rates and effective release heights. Only those pollutants that fail the Step 9 screening limits need to be addressed in this exercise.
This procedure assesses the environmental impacts from each stack and then sums the results to estimate total impacts. This option is conceptually the same as the basic approach (Steps 1 through 9) and does not involve complex calculations. However, it is more time-consuming and is recommended only if the basic approach fails to meet the risk criteria. The procedure is outlined below.
(A) Compute effective stack heights for each stack. [FN8]
[FNFOOTNOTE:] 8 Follow the procedure outlined in Step 4 of the basic screening procedure to determine the GEP for each stack. If a stack's physical height exceeds the maximum GEP, use the maximum GEP values. If a stack's physical height is less than the minimum GEP, use generic source number 11 in the subsequent steps of this analysis. Follow the procedure in Steps 5(A) and 5(B) to determine the effective height of each stack.
Stack GEP Flow rate Exit temp Plume rise Effective
No. stack (<>K) (m) stack
height (m [FN3]/sec) height (m)
1 _____ _____ _____ _____
2 _____ _____ _____ _____
3 _____ _____ _____ _____
Add an additional page if more than three stacks are involved. Circle the
maximum and minimum effective stack heights.
(B) Determine if this multiple-stack screening procedure will likely produce less conservative results than the procedure in Steps 1 through 9. To do this, compute the ratio of maximum-to-minimum effective stack height:
TABULAR OR GRAPHIC MATERIAL SET AT THIS POINT IS NOT DISPLAYABLE
Maximum Effective Stack Height
-------------------------------- = ___________________
Minimum Effective Stack Height
If the above ratio is greater than 1.25, proceed with the remaining steps. Otherwise, this option is less likely to significantly reduce the degree of conservatism in the screening method.
(C) Determine if terrain adjustment is needed and select generic source numbers. Select the shortest stack height and maximum terrain rise out to 5 km from Step 1 and determine if the facility is in flat terrain.
Shortest stack height (m) =
Maximum terrain rise in meters out to 5 km =
TABULAR OR GRAPHIC MATERIAL SET AT THIS POINT IS NOT DISPLAYABLE
Terrain Rise (m)
--------------------------- X 100 = __________%
Shortest Stack Height (m)
If the value above is greater than 10 percent, the terrain is considered nonflat; proceed to Step 10(D). If the ratio is less than or equal to 10 percent, the terrain is considered flat. Identify the generic source numbers based on effective stack heights computed in Step 10(A). Refer to Table 5.0-2 provided earlier to identify generic source numbers. Record the generic source numbers identified and proceed to Step 10(F).
TABULAR OR GRAPHIC MATERIAL SET AT THIS POINT IS NOT DISPLAYABLE
1 2 3
Generic Source Number
(D) Compute the TAESH and select generic source numbers (four sources located in nonflat terrain).
1. Compute the TAESH for all remaining stacks using the following equation:
HE - TR = TAESH
where:
HE = effective stack height (m)
TR = maximum terrain rise for each distance range (m)
TAESH = terrain-adjusted effective stack height (m)
Use the Table Below To Calculate the TAESH for Each Stack [FN9].
TABULAR OR GRAPHIC MATERIAL SET AT THIS POINT IS NOT DISPLAYABLE
[FNFOOTNOTE:] 9 Refer to Step 1 for terrain adjustment data. Note that the distance from the source to the outer radii of each range is used. For example, for the range >0.5-2.5 km, the maximum terrain rise in the range 0.0-2.5 km is used.
For those stacks where the terrain rise within a distance range is greater than the effective stack height (i.e., HE-TR is less than zero), the TAESH for that distance range is set equal to zero, and generic source number 1 should be used for that distance range for all subsequent distance ranges. Additionally, for all stacks with a physical stack height of less than or equal to 10 meters, use generic source number 1 for all distance ranges [FN10]. For the remaining stacks, proceed to Step 10(D)(2).
[FNFOOTNOTE:] 10 This applies to all stacks less than or equal to 10 meters regardless of the terrain classification.
2. For the remaining stacks, refer to Table 5.0-2 and, for each distance range, identify the generic source number that includes the TAESH. Use the values obtained from Steps 10(D)(1) and 10(D)(2) to complete the following summary worksheet;
Generic Source Number After Terrain Adjusted (if Necessary)
TABULAR OR GRAPHIC MATERIAL SET AT THIS POINT IS NOT DISPLAYABLE
Stack No. 0-0.5 km >0.5-2.5 km >2.5-5.0 km
1_____ _____ _____ _____
2_____ _____ _____ _____
3_____ _____ _____ _____
(E) Identify maximum average hourly dispersion coefficients. Based on the land use classification of the site (e.g., urban or rural), use either Table 5.0-4 or Table 5.0-5 to determine the appropriate dispersion coefficient for each distance range for each stack. Begin at the minimum fenceline distance indicated in Step 7(B) and record on Worksheet 5.0-1 the dispersion coefficient for each stack/distance range. For stacks located in facilities in flat terrain, the generic source numbers were computed in Step 10(C). For stacks located in facilities in rolling and complex terrain, the generic source numbers were computed in Step 10(D). For flat terrain applications and for stacks with a physical height of less than or equal to 10 meters, only one generic source number is used per stack for all distance ranges. For other situations up to three generic source numbers may be needed per stack (i.e., a unique generic source number per distance range). In Tables 5.0-4 and 5.0- 5, the dispersion coefficients for distances of 6 km to 20 km are the same for all generic source numbers in order to conservatively represent terrain beyond 5 km (past the limits of the terrain analysis).
Worksheet 5.0-1 Dispersion Coeffificent by Downwind Distance [FN1]
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[FN1]1 Note: This procedure places all stacks at the same point, but allows for consideration of different effective stack heights. The distance to the closest boundary (extracted from Step 1) should be the closest distance to any stack.
(F) Estimate maximum hourly ambient air concentrations. In this step, pollutant-specific emission rates are multiplied by appropriate dispersion coefficients to estimate ambient air concentrations. For each stack, emissions are multiplied by the dispersion coefficient selected in Step 10(E) and summed across all stacks to estimate ambient air concentrations at various distances from the facility. From these summed concentrations, the maximum hourly ambient air concentration is selected. First, select the maximum emission rate of the pollutant [FN11]. Record these data in the spaces provided below [FN12].
[FNFOOTNOTE:] 11 Recall that it is recommended that this analysis be performed for only one or two pollutants. The pollutants chosen for this analysis should be those that show the most significant exceedances of the risk threshold.
[FNFOOTNOTE:] 12 Refer to Step 8 of the basic screening procedure. At this point in the screening procedure, annual emissions are used to represent hourly average emission rates. These values will be adjusted by the annual/hourly ratio to estimate annual average concentrations.
Maximum Annual Emission Rates (G/Sec)
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____________________________________
Pollutant Stack 1 Stack 2 Stack 3
____________________________________
_______ _____ _____ _____
_______ _____ _____ _____
_______ _____ _____ _____
Complete a separate copy of Worksheet 5.0-2 for each pollutant and select the highest hourly concentration from the summation column at the far right of the worksheet. Record the maximum hourly air concentration for each pollutant analyzed (add additional lines if needed):
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Pollutant Maximum hourly air
concentration
_______ ___________
_______ ___________
_______ ___________
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(G) Determine the complex/noncomplex designation for each stack. For each stack, subtract the maximum terrain rise within 5 km of the site from the physical stack height and designate the stack as either complex or noncomplex. If the stack height minus the maximum terrain rise (within 5 km) is greater than zero or if the stack is less than 10 meters in physical height, then assign the stack a noncomplex designation. If the stack height minus the maximum terrain rise (within 5 km) is less than or equal to zero, then assign the stack a complex designation.
Perform the following computation for each stack and record the information in the spaces provided. Check in the spaces provided whether the stack designation is complex or noncomplex.
_______________________________________________________________________________
Stack No. Stack Maximum Complex Noncomplex
height (m) terrain rise
(m)
_______________________________________________________________________________
1_______ _______ - _______ = (m)_______ _______
2_______ _______ - _______ = (m)_______ _______
3_______ _______ - _______ = (m)_______ _______
_______________________________________________________________________________
(H) Identify annual/hourly ratios. Extract the annual/hourly ratios for each stack by referring to Table 5.0-6. Generic source numbers (from Steps 10(C) or 10(D), urban/rural designation (from Step 6)), and complex or noncomplex terrain designations (from Step 10(G)) are used to select the appropriate scaling factor needed to convert hourly maximum concentrations to estimates of annual average concentrations.
Complete the following table [FN13].
[FNFOOTNOTE:] 13 If any stack (excluding generic stack number 1 and 11) in Step 10(D) shows a negative terrain adjusted stack height, use the complex terrain annual/hourly ratios.
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Generic source No. steps 10 (C or Annual hourly ratio (from table
D) 5.0-6)
Stack Distance ranges (km) Distance ranges (km)
No.
0-0.5 >0.5-2.4 >2.5-5.0 0-0.5 >0.5-2.5 >2.5-5.0
1_____ _____ _____ _____ _____ _____ _____
2_____ _____ _____ _____ _____ _____ _____
3_____ _____ _____ _____ _____ _____ _____
(I) Select the highest annual/hourly ratio among all of the stacks [FN14], and then estimate the maximum annual average ambient air concentrations for each pollutant by completing the following table, where:
[FNFOOTNOTE:] 14 As an option, the user can identify the stack with the highest ratio for each distance range (rather than the absolute highest). In this case, extra sheets would be needed to show estimated annual average concentrations from each stack by multiplying emission rate times maximum hourly dispersion coefficient times maximum annual/hourly ratio for applicable distance range. Then sum across all stacks for each downwind distance.
C = Maximum total hourly ambient air concentration (mg/m [FN3]) for pollutant "N" from Step 10(F).
C a = Maximum annual average air concentration for pollutant "N" (mg/m [FN3]),
R = Annual/hourly ratio.
Table 5.0-6. -95th Percentile of Annual/Hourly Ratios
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Noncomplex Terrain 4Complex Terrain
____________________________________
Source Urban Rural Source Urban Rural
____________________________________________
1 0.019 0.014 1 0.020 0.053
2 0.033 0.019 2 0.020 0.053
3 0.031 0.018 3 0.030 0.057
4 0.029 0.017 4 0.051 0.047
5 0.028 0.017 5 0.067 0.039
6 0.028 0.017 6 0.059 0.034
7 0.031 0.015 7 0.036 0.031
8 0.030 0.013 8 0.026 0.024
9 0.029 0.011 9 0.026 0.024
10 0.029 0.008 10 0.017 0.013
11 0.018 0.015 11 0.020 0.053
____________________________________________
__________________________________________________________________
Pollutant C(<>g/m [FN3]) X R = Ca (<>g/m [FN3])
__________________________________________________________________
__________ _____ X ____ = _______
__________ _____ X ____ = _______
__________________________________________________________________
(J) Use the maximum annual average concentrations from Step 10(I) to determine compliance with regulatory requirements.
SECTION 6.0-SIMPLIFIED LAND USE CLASSIFICATION PROCEDURE FOR COMPLIANCE WITH TIER I AND AND TIER II LIMITS
6.1 Introduction
This section provides a simplified procedure to classify areas in the vicinity of boilers and industrial furnace sites as urban or rural in order to set risk-based emission limits under article 8 of chapter 16. Urban/rural classification is needed because dispersion rates differ between urban and rural areas and thus, the risk per unit emission rate differs accordingly. The combination of greater surface roughness (more buildings/structures to generate turbulent mixing) and the greater amount of heat released from the surface in an urban area (generates buoyancy-induced mixing) produces greater rates of dispersion. The emission limit tables in the regulation, therefore, distinguish between urban and rural areas.
US EPA guidance (EPA 1986) [FN1] provides two alternative procedures to determine whether the character of an area is predominantly urban or rural. One procedure is based on land use typing and the other is based on population density. Both procedures require consideration of characteristics within a 3-km radius from a source, in this case the facility stack(s). The land use typing method is preferred because it more directly relates to the surface characteristics that affect dispersion rates. The remainder of this discussion is, therefore, focused on the land use method.
While the land use method is more direct, it can also be labor-intensive to apply. For this discussion, the land use method has been simplified so that it is consistent with US EPA guidance (EPA 1986; Auer 1978), while streamlining the process for the majority of applications so that a clear-cut decision can be made without the need for detailed analysis. Table 6.0-1 summarizes the simplified approach for classifying areas as urban or rural. As shown, the applicant always has the option of applying standard (i.e, more detailed) analyses to more accurately distinguish between urban and rural areas. However, the procedure presented here allows for simplified determinations, where appropriate, to expedite the permitting process.
Table 6.0-1. -Classification of Land Use Types
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Type [FN1] Description Urban or rural
designation [FN2]
I1 Heavy industrial Urban.
I2 Light/Moderate Industrial Urban.
C1 Commercial Urban.
R1 Common Residential (Normal Easements) Rural.
R2 Compact Residential (Single Family) Urban.
R3 Compact Residential (Multi-Family) Urban.
R4 Estate Residential (Multi-Acre Plots) Rural.
A1 Metropolitan Natural Rural.
A2 Agricultural Rural.
A3 Undeveloped (Grasses/Weeds) Rural.
A4 Undeveloped (Heavily Wooded) Rural.
A5 Water Surfaces Rural.
[FNFOOTNOTE:] 1 US EPA, Guideline on Air Quality Models (Revised), EPA-450/2-78-027R, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina, July, 1986.
[FNFOOTNOTE:] 2 Auer, August H. Jr., "Correlation of Land Use and Cover with Meteorological Anomalies," Journal of Applied Meteorology, pp. 636-643, 1978.
6.2 Simplified Land Use Process
The land use approach considers four primary land use types: industrial (I), commercial (C), residential (R), and agricultural (A). Within These primary classes, subclasses are identified, as shown in table 6.0-1. The goal is to estimate the percentage of the area within a 3-km radius that is urban type and the percentage that is rural type. Industrial and commercial areas are classified as urban; agricultural areas are classified as rural.
The delineation of urban and rural areas, however, can be more difficult for the residential type areas shown in table 6.0-1. The degree of resolution shown in table 6.0-1 for residential areas often cannot be identified without conducting site area inspections and/or referring to zoning maps. This process can require extensive analysis, which, for many applications, can be greatly streamlined without sacrificing confidence in selecting the appropriate urban or rural classification.
The fundamental simplifying assumption is based on the premise that many applications will have clear-cut urban/rural designations, i.e., most will be in rural settings that can be definitively characterized through a brief review of topographical maps. The color coding on USGS topographical maps provides the most effective means of simplifying the typing scheme. The suggested typing designations for the color codes found on topographic maps are as follows:
Green Wooded areas (rural).
White White areas generally will be treated as rural. This code applies to areas that are unwooded and do not have densely packed structures which would require the pink code (house omission tint). Parks, industrial areas, and unforested rural land will appear as white on the topographical maps. Of these categories, only the industrial areas could potentially be classified as urban based on EPA 1986 or Auer 1978. Industrial areas can be easily identified in most cases by the characteristics shown in Figure 6.0-1. For this simplified procedure, white areas that have an industrial classification will be treated as urban areas.
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SECTION 7.0 STATISTICAL METHODOLOGY FOR BEVILL RESIDUE DETERMINATIONS
This section describes the statistical comparison of waste-derived residue to normal residue for use in determining eligibility for the Bevill exemption under section 662666.112.
7.1 Comparison of Waste-derived Residue with Normal Residue
To be eligible for the Bevill exclusion from the definition of hazardous waste under section 66266.112(b)(1), waste-derived residue must not contain Appendix VIII, Chapter 11, constituents that could reasonably be attributable to the hazardous waste (toxic constituents) at concentrations significantly higher than in residue generated without burning or processing hazardous waste (normal residue). Concentrations of toxic constituents in normal residue are determined based on analysis of a minimum of 10 samples representing a minimum of 10 days of operation. The statistically- derived concentrations in normal residue are determined as the upper tolerance limit (95% confidence with a 95% proportion of the sample distribution) of the normal residue concentrations. The upper tolerance limit is to be determined as described in Section 7.2 below. If changes in raw materials or fuels could lower the statistically-derived concentrations of toxic constituents of concern, the statistically-derived baseline must be re-established for any such mode of operation with the new raw material or fuel.
Concentrations of toxic constituents in waste-derived residue are determined based on the analysis of one or more samples collected over a compositing period of not more than 24 hours. Multiple samples of the waste-derived residue may be analyzed or subsamples may be composited for analysis, provided that the sampling period does not exceed 24 hours. If more than one sample is analyzed to characterize the waste-derived residue generated over a 24-hour period, the arithmetic mean of the concentrations must be used as the waste-derived concentration for each constituent.
The concentration of a toxic constituent in the waste-derived residue is not considered to be significantly higher than in the normal residue (i.e., the residue passes the Bevill test for that constituent) if the concentration in the waste-derived residue does not exceed the statistically-derived concentration.
7.2 Calculation of the Upper Tolerance Limit
The 95% confidence with 95% proportion of the sample distribution (upper tolerance limit) is calculated for a set of values assuming that the values are normally distributed. The upper tolerance limit is a one-sided calculation and is an appropriate statistical test for cases in which a single value (the waste-derived residue concentration) is compared to the distribution of range of values (the minimum of 10 measurements of normal residue concentrations). The upper tolerance limit value is determined as follows:
UTL = X + (K)(S)
where
X = mean of the normal residue concentration, X = X i /n,
K = coefficient for sample size n, 95% confidence and 95% proportion,
S = standard deviation of the normal residue concentrations,
S = <>(Xi-X) [FN2] /(n-1)) [FN0.5], and
n = sample size.
The values of K at the 95% confidence and 95% proportion, and sample size n are given in Table 7.0-1.
For example, a normal residue test results in 10 samples with the following analytical results for toxic constituent A:
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Sample No. Concentration of
compound A (ppm)
1 10
2 10
3 15
4 10
5 7
6 12
7 10
8 16
9 15
10 10
The mean and standard deviation of these measurements, calculated using equations above, are 11.5 and 2.9 respectively. Assuming that the values are normally distributed, the upper tolerance limit (UTL) is given by:
UTL = 11.5 + (2.911)(2.9) = 19.9 ppm
Table 7.0-1,. -K Values for 95% Confidence and 95% Proportion
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Sample size (n) K
10 2.911
11 2.815
12 2.736
13 2.670
14 2.614
15 2.566
16 2.523
17 2.486
18 2.458
19 2.423
20 2.396
21 2.371
22 2.350
23 2.329
24 2.303
25 2.292
Thus, if the concentration of constituent A in the waste-derived residue is below 19.9 ppm, then the waste-derived residue is eligible for the Bevill exclusion for constituent A.
7.3 Normal Distribution Assumption
As noted in section 7.2 above, this statistical approach (use of the upper tolerance limit) for calculation of the concentration in normal residue is based on the assumption that the concentration data are distributed normally. The Department is aware that concentration data of this type may not be distributed normally, particularly when concentrations are near the detection limits. There are a number of procedures that can be used to test the distribution of a data set. For example, the Shapiro-Wilk test, examination of a histogram or plot of the data on normal probability paper, and examination of the coefficient of skewness are methods that may be applicable, depending on the nature of the data (Reference 1 and 2).
If the concentration data are not adequately represented by a normal distribution, the data may be transformed to attain a near normal distribution. The Department has found that concentration data, especially when near detection levels, often exhibit a lognormal distribution. The assumption of a lognormal distribution has been used in various programs at US EPA, such as in the Office of Solid Waste Land Disposal Restrictions program for determination of BDAT treatment standards. The transformed data may be tested for normality using the procedures identified above. If the transformed data are better represented by a normal distribu-
tion than the untransformed data, the transformed data should be used in determining the upper tolerance limit using the procedures in section 7.2 above.
In all cases where the applicant for the Bevill exemption wishes to use other than an assumption of normally distributed data, or believes that use of an alternate statistical approach is appropriate to the specific data set, the applicant must provide supporting rationale and demonstrate to the Director or permitting authority that the data treatment is based upon sound statistical practice. (continued)