Economic Analysis for the LT2ESWTR Proposal G 51 June 2003 Exhibit G. 50: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 65 55 3 0 0 0 0 0 0 0 0 7 0 S2 73 61 4 0 0 0 0 0 0 0 0 8 0 S3 26 22 0 0 0 0 0 0 0 0 0 4 0 S4 18 15 0 0 0 0 0 0 0 0 0 3 0 S5 6 5 0 0 0 0 0 0 0 0 0 1 0 M1 2 0 0 0 0 0 0 0 0 0 0 2 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 190 158 7 0 0 0 0 0 0 0 0 24 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 52 June 2003 Exhibit G. 51: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 333 279 17 0 0 0 0 0 0 0 0 36 0 S2 131 110 7 0 0 0 0 0 0 0 0 14 0 S3 22 18 0 0 0 0 0 0 0 0 0 3 0 S4 18 15 0 0 0 0 0 0 0 0 0 3 0 S5 8 7 0 0 0 0 0 0 0 0 0 1 0 M1 3 0 0 0 0 0 0 0 0 0 0 2 0 M2 1 0 0 0 0 0 0 0 0 0 0 1 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 515 430 24 0 0 0 0 0 0 0 0 60 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 53 June 2003 Exhibit G. 52: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 107 90 5 0 0 0 0 0 0 0 0 12 0 S2 213 179 11 0 0 0 0 0 0 0 0 23 0 S3 110 92 1 0 0 0 0 0 0 0 0 16 0 S4 268 225 1 0 0 0 1 1 1 0 0 39 0 S5 318 267 2 0 0 0 1 1 1 0 0 46 0 M1 306 0 0 37 7 3 5 11 7 0 0 240 0 M2 112 0 0 14 2 1 2 4 2 0 0 88 0 L1 102 0 0 16 6 1 2 4 2 0 0 76 0 L2 13 0 0 2 1 0 0 1 0 0 0 10 0 Total Plants 1,549 853 20 70 16 4 11 22 14 0 0 548 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 54 June 2003 Exhibit G. 53: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 65 55 3 0 0 0 0 0 0 0 0 7 0 S2 73 61 4 0 0 0 0 0 0 0 0 8 0 S3 26 22 0 0 0 0 0 0 0 0 0 4 0 S4 18 15 0 0 0 0 0 0 0 0 0 3 0 S5 6 5 0 0 0 0 0 0 0 0 0 1 0 M1 2 0 0 0 0 0 0 0 0 0 0 2 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 190 158 7 0 0 0 0 0 0 0 0 24 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 55 June 2003 Exhibit G. 54: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 333 279 17 0 0 0 0 0 0 0 0 36 0 S2 131 110 7 0 0 0 0 0 0 0 0 14 0 S3 22 18 0 0 0 0 0 0 0 0 0 3 0 S4 18 15 0 0 0 0 0 0 0 0 0 3 0 S5 8 7 0 0 0 0 0 0 0 0 0 1 0 M1 3 0 0 0 0 0 0 0 0 0 0 2 0 M2 1 0 0 0 0 0 0 0 0 0 0 1 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 515 430 24 0 0 0 0 0 0 0 0 60 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 56 June 2003 Exhibit G. 55: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10 CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 151 109 20 0 0 0 0 0 0 0 0 22 0 S2 302 217 41 0 0 0 0 0 0 0 0 45 0 S3 155 112 3 0 0 0 0 1 1 0 0 40 0 S4 380 273 7 1 0 0 1 2 2 0 0 97 0 S5 450 323 8 1 0 0 1 2 2 1 0 115 0 M1 436 0 0 45 8 3 5 12 13 4 0 345 0 M2 160 0 0 16 3 1 2 4 5 2 0 127 0 L1 145 0 0 20 7 1 2 5 3 1 0 110 0 L2 19 0 0 3 1 0 0 1 0 0 0 15 0 Total Plants 2,200 1,032 79 86 18 5 10 28 26 9 0 914 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 57 June 2003 Exhibit G. 56: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 92 66 12 0 0 0 0 0 0 0 0 14 0 S2 103 74 14 0 0 0 0 0 0 0 0 15 0 S3 37 27 1 0 0 0 0 0 0 0 0 9 0 S4 26 18 0 0 0 0 0 0 0 0 0 7 0 S5 8 6 0 0 0 0 0 0 0 0 0 2 0 M1 3 0 0 0 0 0 0 0 0 0 0 2 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 270 191 28 1 0 0 0 0 0 0 0 50 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 58 June 2003 Exhibit G. 57: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 471 338 64 0 0 0 0 0 0 0 0 70 0 S2 186 133 25 0 0 0 0 0 0 0 0 27 0 S3 31 22 1 0 0 0 0 0 0 0 0 8 0 S4 26 18 0 0 0 0 0 0 0 0 0 7 0 S5 12 8 0 0 0 0 0 0 0 0 0 3 0 M1 4 0 0 0 0 0 0 0 0 0 0 3 0 M2 1 0 0 0 0 0 0 0 0 0 0 1 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 730 520 90 1 0 0 0 1 0 0 0 118 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 59 June 2003 Exhibit G. 58: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 151 109 20 0 0 0 0 0 0 0 0 22 0 S2 302 217 41 0 0 0 0 0 0 0 0 45 0 S3 155 112 2 0 0 0 1 0 0 0 0 40 0 S4 380 273 6 1 0 0 3 1 1 0 0 97 0 S5 450 323 7 1 0 0 3 1 1 0 0 115 0 M1 436 0 0 45 8 3 11 14 9 0 0 345 0 M2 160 0 0 17 3 1 4 5 3 0 0 127 0 L1 145 0 0 20 7 1 4 5 2 0 0 110 0 L2 19 0 0 3 1 0 0 1 0 0 0 15 0 Total Plants 2,200 1,032 76 86 19 6 27 27 18 1 1 914 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 60 June 2003 Exhibit G. 59: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 92 66 12 0 0 0 0 0 0 0 0 14 0 S2 103 74 14 0 0 0 0 0 0 0 0 15 0 S3 37 27 1 0 0 0 0 0 0 0 0 9 0 S4 26 18 0 0 0 0 0 0 0 0 0 7 0 S5 8 6 0 0 0 0 0 0 0 0 0 2 0 M1 3 0 0 0 0 0 0 0 0 0 0 2 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 270 191 27 1 0 0 1 0 0 0 0 50 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 61 June 2003 Exhibit G. 60: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: High Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 471 338 64 0 0 0 0 0 0 0 0 70 0 S2 186 133 25 0 0 0 0 0 0 0 0 27 0 S3 31 22 0 0 0 0 0 0 0 0 0 8 0 S4 26 18 0 0 0 0 0 0 0 0 0 7 0 S5 12 8 0 0 0 0 0 0 0 0 0 3 0 M1 4 0 0 0 0 0 0 0 0 0 0 3 0 M2 1 0 0 0 0 0 0 0 0 0 0 1 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 730 520 90 1 0 0 1 0 0 0 0 118 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 62 June 2003 Exhibit G. 61: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10 CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 53 47 0 0 0 0 0 0 0 0 0 5 0 S2 106 94 1 0 0 0 0 0 0 0 0 11 0 S3 54 49 0 0 0 0 0 0 0 0 0 5 0 S4 133 119 0 0 0 0 0 0 1 0 0 13 0 S5 158 141 0 0 0 0 0 0 1 0 0 15 0 M1 152 0 0 19 3 1 1 5 5 0 0 118 0 M2 56 0 0 7 1 0 0 2 2 0 0 43 0 L1 50 0 0 9 3 0 0 2 1 0 0 37 0 L2 7 0 0 1 0 0 0 0 0 0 0 5 0 Total Plants 768 450 1 36 7 2 2 10 10 0 0 252 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 63 June 2003 Exhibit G. 62: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 32 29 0 0 0 0 0 0 0 0 0 3 0 S2 36 32 0 0 0 0 0 0 0 0 0 4 0 S3 13 12 0 0 0 0 0 0 0 0 0 1 0 S4 9 8 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 94 83 0 0 0 0 0 0 0 0 0 10 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 64 June 2003 Exhibit G. 63: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 165 147 1 0 0 0 0 0 0 0 0 16 0 S2 65 58 0 0 0 0 0 0 0 0 0 6 0 S3 11 10 0 0 0 0 0 0 0 0 0 1 0 S4 9 8 0 0 0 0 0 0 0 0 0 1 0 S5 4 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 256 227 2 0 0 0 0 0 0 0 0 27 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 65 June 2003 Exhibit G. 64: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 53 47 0 0 0 0 0 0 0 0 0 5 0 S2 106 94 1 0 0 0 0 0 0 0 0 11 0 S3 54 49 0 0 0 0 0 0 0 0 0 5 0 S4 133 119 0 0 0 0 0 0 1 0 0 13 0 S5 158 141 0 0 0 0 0 0 1 0 0 15 0 M1 152 0 0 19 3 1 2 6 3 0 0 118 0 M2 56 0 0 7 1 0 1 2 1 0 0 43 0 L1 50 0 0 9 3 0 1 2 1 0 0 37 0 L2 7 0 0 1 0 0 0 0 0 0 0 5 0 Total Plants 768 450 1 37 8 2 4 12 7 0 0 252 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 66 June 2003 Exhibit G. 65: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 32 29 0 0 0 0 0 0 0 0 0 3 0 S2 36 32 0 0 0 0 0 0 0 0 0 4 0 S3 13 12 0 0 0 0 0 0 0 0 0 1 0 S4 9 8 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 94 83 0 0 0 0 0 0 0 0 0 10 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 67 June 2003 Exhibit G. 66: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A3 Occurrence Distribution: Low Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 165 147 1 0 0 0 0 0 0 0 0 16 0 S2 65 58 0 0 0 0 0 0 0 0 0 6 0 S3 11 10 0 0 0 0 0 0 0 0 0 1 0 S4 9 8 0 0 0 0 0 0 0 0 0 1 0 S5 4 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 256 227 2 0 0 0 0 0 0 0 0 27 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 68 June 2003 Exhibit G. 67: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10 CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 86 78 0 0 0 0 0 0 0 0 0 9 0 S2 172 155 0 0 0 0 0 0 0 0 0 17 0 S3 89 80 0 0 0 0 0 0 0 0 0 8 0 S4 217 195 0 0 0 0 0 1 0 0 0 20 0 S5 257 231 0 0 0 0 0 1 1 0 0 23 0 M1 204 0 0 38 39 1 1 7 3 0 0 115 0 M2 75 0 0 14 14 0 0 3 1 0 0 42 0 L1 66 0 0 14 13 0 0 3 1 0 0 37 0 L2 9 0 0 2 2 0 0 0 0 0 0 5 0 Total Plants 1,175 739 0 69 68 2 2 16 6 0 0 276 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 69 June 2003 Exhibit G. 68: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 53 47 0 0 0 0 0 0 0 0 0 5 0 S2 59 53 0 0 0 0 0 0 0 0 0 6 0 S3 21 19 0 0 0 0 0 0 0 0 0 2 0 S4 15 13 0 0 0 0 0 0 0 0 0 1 0 S5 5 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 154 137 0 0 0 0 0 0 0 0 0 16 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 70 June 2003 Exhibit G. 69: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 269 242 0 0 0 0 0 0 0 0 0 27 0 S2 106 95 0 0 0 0 0 0 0 0 0 11 0 S3 18 16 0 0 0 0 0 0 0 0 0 2 0 S4 15 13 0 0 0 0 0 0 0 0 0 1 0 S5 7 6 0 0 0 0 0 0 0 0 0 1 0 M1 2 0 0 0 0 0 0 0 0 0 0 1 0 M2 1 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 416 372 0 0 0 0 0 0 0 0 0 42 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 71 June 2003 Exhibit G. 70: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 86 78 0 0 0 0 0 0 0 0 0 9 0 S2 172 155 0 0 0 0 0 0 0 0 0 17 0 S3 89 80 0 0 0 0 0 0 0 0 0 8 0 S4 217 195 0 0 0 0 0 1 0 0 0 20 0 S5 257 231 0 0 0 0 0 1 0 0 0 23 0 M1 204 0 0 39 39 1 2 8 2 0 0 115 0 M2 75 0 0 14 14 0 1 3 1 0 0 42 0 L1 66 0 0 14 13 0 1 3 0 0 0 37 0 L2 9 0 0 2 2 0 0 0 0 0 0 5 0 Total Plants 1,175 739 0 69 68 2 4 16 4 0 0 276 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 72 June 2003 Exhibit G. 71: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 53 47 0 0 0 0 0 0 0 0 0 5 0 S2 59 53 0 0 0 0 0 0 0 0 0 6 0 S3 21 19 0 0 0 0 0 0 0 0 0 2 0 S4 15 13 0 0 0 0 0 0 0 0 0 1 0 S5 5 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 154 137 0 0 0 0 0 0 0 0 0 16 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 73 June 2003 Exhibit G. 72: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICR Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 269 242 0 0 0 0 0 0 0 0 0 27 0 S2 106 95 0 0 0 0 0 0 0 0 0 11 0 S3 18 16 0 0 0 0 0 0 0 0 0 2 0 S4 15 13 0 0 0 0 0 0 0 0 0 1 0 S5 7 6 0 0 0 0 0 0 0 0 0 1 0 M1 2 0 0 0 0 0 0 0 0 0 0 1 0 M2 1 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 416 372 0 0 0 0 0 0 0 0 0 42 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 74 June 2003 Exhibit G. 73: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10 CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 41 36 0 0 0 0 0 0 0 0 0 4 0 S2 81 73 0 0 0 0 0 0 0 0 0 8 0 S3 42 37 0 0 0 0 0 0 0 0 0 4 0 S4 102 92 0 0 0 0 0 1 0 0 0 9 0 S5 121 108 0 0 0 0 0 1 0 0 0 11 0 M1 87 0 0 19 25 0 0 3 0 0 0 38 0 M2 32 0 0 7 9 0 0 1 0 0 0 14 0 L1 27 0 0 6 8 0 0 1 0 0 0 12 0 L2 4 0 0 1 1 0 0 0 0 0 0 2 0 Total Plants 535 347 0 34 44 1 1 7 0 0 0 101 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 75 June 2003 Exhibit G. 74: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 25 22 0 0 0 0 0 0 0 0 0 2 0 S2 28 25 0 0 0 0 0 0 0 0 0 3 0 S3 10 9 0 0 0 0 0 0 0 0 0 1 0 S4 7 6 0 0 0 0 0 0 0 0 0 1 0 S5 2 2 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 72 64 0 0 0 0 0 0 0 0 0 7 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 76 June 2003 Exhibit G. 75: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 126 114 0 0 0 0 0 0 0 0 0 13 0 S2 50 45 0 0 0 0 0 0 0 0 0 5 0 S3 8 7 0 0 0 0 0 0 0 0 0 1 0 S4 7 6 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 195 175 0 0 0 0 0 0 0 0 0 20 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 77 June 2003 Exhibit G. 76: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 41 36 0 0 0 0 0 0 0 0 0 4 0 S2 81 73 0 0 0 0 0 0 0 0 0 8 0 S3 42 37 0 0 0 0 0 0 0 0 0 4 0 S4 102 92 0 0 0 0 0 1 0 0 0 9 0 S5 121 108 0 0 0 0 0 1 0 0 0 11 0 M1 87 0 0 19 25 0 0 3 0 0 0 38 0 M2 32 0 0 7 9 0 0 1 0 0 0 14 0 L1 27 0 0 6 8 0 0 1 0 0 0 12 0 L2 4 0 0 1 1 0 0 0 0 0 0 2 0 Total Plants 535 347 0 34 44 1 1 7 0 0 0 101 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 78 June 2003 Exhibit G. 77: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 25 22 0 0 0 0 0 0 0 0 0 2 0 S2 28 25 0 0 0 0 0 0 0 0 0 3 0 S3 10 9 0 0 0 0 0 0 0 0 0 1 0 S4 7 6 0 0 0 0 0 0 0 0 0 1 0 S5 2 2 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 72 64 0 0 0 0 0 0 0 0 0 7 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 79 June 2003 Exhibit G. 78: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSL Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 126 114 0 0 0 0 0 0 0 0 0 13 0 S2 50 45 0 0 0 0 0 0 0 0 0 5 0 S3 8 7 0 0 0 0 0 0 0 0 0 1 0 S4 7 6 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 195 175 0 0 0 0 0 0 0 0 0 20 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 80 June 2003 Exhibit G. 79: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10 CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 56 51 0 0 0 0 0 0 0 0 0 6 0 S2 112 101 0 0 0 0 0 0 0 0 0 11 0 S3 58 52 0 0 0 0 0 0 0 0 0 5 0 S4 141 127 0 0 0 0 0 1 0 0 0 13 0 S5 167 151 0 0 0 0 0 1 0 0 0 15 0 M1 124 0 0 26 32 1 1 5 1 0 0 59 0 M2 45 0 0 10 12 0 0 2 0 0 0 22 0 L1 39 0 0 9 10 0 0 2 0 0 0 19 0 L2 5 0 0 1 1 0 0 0 0 0 0 3 0 Total Plants 749 481 0 47 56 1 1 10 1 0 0 152 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 81 June 2003 Exhibit G. 80: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10 NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 34 31 0 0 0 0 0 0 0 0 0 3 0 S2 38 34 0 0 0 0 0 0 0 0 0 4 0 S3 14 12 0 0 0 0 0 0 0 0 0 1 0 S4 10 9 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 100 89 0 0 0 0 0 0 0 0 0 10 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 82 June 2003 Exhibit G. 81: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10 TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 175 158 0 0 0 0 0 0 0 0 0 18 0 S2 69 62 0 0 0 0 0 0 0 0 0 7 0 S3 11 10 0 0 0 0 0 0 0 0 0 1 0 S4 10 9 0 0 0 0 0 0 0 0 0 1 0 S5 4 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 271 243 0 0 0 0 0 0 0 0 0 27 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 83 June 2003 Exhibit G. 82: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B CWS Technology Selection Forecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 56 51 0 0 0 0 0 0 0 0 0 6 0 S2 112 101 0 0 0 0 0 0 0 0 0 11 0 S3 58 52 0 0 0 0 0 0 0 0 0 5 0 S4 141 127 0 0 0 0 0 1 0 0 0 13 0 S5 167 151 0 0 0 0 0 1 0 0 0 15 0 M1 124 0 0 26 32 1 1 5 0 0 0 59 0 M2 45 0 0 10 12 0 0 2 0 0 0 22 0 L1 39 0 0 9 10 0 0 2 0 0 0 19 0 L2 5 0 0 1 1 0 0 0 0 0 0 3 0 Total Plants 749 481 0 47 56 1 2 10 1 0 0 152 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 84 June 2003 Exhibit G. 83: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B NTNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 34 31 0 0 0 0 0 0 0 0 0 3 0 S2 38 34 0 0 0 0 0 0 0 0 0 4 0 S3 14 12 0 0 0 0 0 0 0 0 0 1 0 S4 10 9 0 0 0 0 0 0 0 0 0 1 0 S5 3 3 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 0 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 100 89 0 0 0 0 0 0 0 0 0 10 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 85 June 2003 Exhibit G. 84: Technology Selection for Filtered Plants Conditions Regulatory Alternative: A4 Occurrence Distribution: ICRSSM Technology Selection Sensitivity: UV90 10B TNCWS Technology SelectionsForecast ( Number of Total Plants Selecting Different Technologies) Bag Filter 1.0 LOG Cartridge Filter 2.0 LOG CLO2 0.5 LOG Combined Filter Performance 0.5 LOG In bank Filtration 1.0 LOG MF/ UF 2.5 LOG O3 0.5 LOG O3 1.0 LOG O3 2.0 LOG Secondary Filter 1 LOG UV 2.5 LOG WS Control 0.5 LOG A B C D E F G H I J K L M S1 175 158 0 0 0 0 0 0 0 0 0 18 0 S2 69 62 0 0 0 0 0 0 0 0 0 7 0 S3 11 10 0 0 0 0 0 0 0 0 0 1 0 S4 10 9 0 0 0 0 0 0 0 0 0 1 0 S5 4 4 0 0 0 0 0 0 0 0 0 0 0 M1 1 0 0 0 0 0 0 0 0 0 0 1 0 M2 0 0 0 0 0 0 0 0 0 0 0 0 0 L1 0 0 0 0 0 0 0 0 0 0 0 0 0 L2 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Plants 271 243 0 0 0 0 0 0 0 0 0 27 0 Note: Sum of columns B through M may not add to column A. EPA Size Category Total Plants Affected ( Including Purchasers)

Economic Analysis for the LT2ESWTR Proposal G 86 June 2003 Economic Analysis for the LT2ESWTR Proposal H 1 June 2003 Appendix H Treatment Costs for Filtered and Unfiltered Plants Appendix H presents total costs of treatment for filtered and unfiltered plants. The methodology for estimating these costs is provided in Chapter 6 and supplemented by Appendix A, Appendix E, and Appendix F. Cost estimates are presented as present value, calculated with 3 and 7 percent discount rates. See Appendix O for annualized costs.

Below is an explanation of the abbreviations used in this appendix, and a brief explanation of each condition.

Regulatory Alternatives A1 A1 is across the board inactivation. All systems are required to achieve a 2.0 log reduction for Cryptosporidium.

A2 A2 is the alternative that requires the most reduction of Cryptosporidium. Systems with 0.03 0.1 oocysts/ L must achieve a 0.5 log reduction. Systems with 0.1 1.0 oocysts/ L must meet a 1.5 log reduction and systems with greater than 1.0 oocysts/ L must meet a 2.5 log reduction of Cryptosporidium.

A3 A3 is the Preferred Alternative. Under this option, systems that have 0.075 1.0 oocysts/ L must meet a 1.0 log reduction of Cryptosporidium. Systems with 1.0 3.0 oocysts/ L must achieve a 2.0 log reduction, and systems with greater than 3.0 oocysts/ L must meet a 2.5 log reduction.

A4 A4 is the alternative that requires the least reduction of Cryptosporidium. Systems that have 0.1 1.0 oocysts/ L must achieve a log reduction of 0.5 for Cryptosporidium. Systems that have greater than 1.0 oocysts/ L must meet a 1.0 log reduction for Cryptosporidium Occurrence Distribution ICR Modeling results based on the Information Collection Rule ( ICR) were used to predict plant binning ICRSSL Modeling results based on the Information Collection Rule Supplemental Survey for large systems ( ICRSSL) were used to predict plant binning ICRSSM Modeling results based on the Information Collection Rule Supplemental Survey for medium systems ( ICRSSM) were used to predict plant binning High Modeling results based on the ICR upper credible limit were used to predict binning for the high case scenario Low Modeling results based on the ICRSSL lower credible limit were used to predict binning for the low case scenario Economic Analysis for the LT2ESWTR Proposal H 2 June 2003 Sensitivity Analysis UV90 10 UV maximum usage = 90, Bromate maximum containment level ( MCL)= 10, No additional influent Bromide UV90 10B UV maximum usage = 90, Bromate MCL= 10, Additional influent Bromide= 50 parts per billion ( ppb)

Discount Rate 3% A 3 percent discount rate is used ( see Chapter 6).

7% A 7 percent discount rate is used ( see Chapter 6).

System Size S Systems serving 10,000 or fewer people.

L Systems serving greater than 10,000 people. Economic Analysis for the LT2ESWTR Proposal H 3 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F A1 5,960.96 $ 5,301.64 $ 6,635.16 $ 342.33 $ 304.46 $ 381.04 $

A2 1,842.51 $ 1,645.69 $ 2,044.34 $ 105.81 $ 94.51 $ 117.40 $

A3  Preferred alt. 1,508.51 $ 1,337.53 $ 1,678.76 $ 86.63 $ 76.81 $ 96.41 $

A4 620.88 $ 556.09 $ 687.12 $ 35.66 $ 31.94 $ 39.46 $

A1 5,960.96 $ 5,301.64 $ 6,635.16 $ 342.33 $ 304.46 $ 381.04 $

A2 1,466.36 $ 1,307.58 $ 1,624.82 $ 84.21 $ 75.09 $ 93.31 $ A3  Preferred alt. 1,090.19 $ 963.40 $ 1,220.11 $ 62.61 $ 55.33 $ 70.07 $

A4 355.58 $ 320.73 $ 390.65 $ 20.42 $ 18.42 $ 22.43 $

A1 5,960.96 $ 5,301.64 $ 6,635.16 $ 342.33 $ 304.46 $ 381.04 $

A2 1,240.50 $ 1,107.83 $ 1,372.81 $ 71.24 $ 63.62 $ 78.84 $

A3  Preferred alt. 876.73 $ 773.42 $ 982.51 $ 50.35 $ 44.42 $ 56.42 $

A4 242.04 $ 218.99 $ 265.13 $ 13.90 $ 12.58 $ 15.23 $ High A3  Preferred alt. 1,655.24 $ 1,470.18 $ 1,844.66 $ 95.06 $ 84.43 $ 105.93 $ Low A3  Preferred alt. 524.69 $ 461.83 $ 587.70 $ 30.13 $ 26.52 $ 33.75 $ ICR UV90 10B A3 1,694.66 $ 1,509.00 $ 1,878.50 $ 97.32 $ 86.66 $ 107.88 $ ICRSSM UV90 10B A3 1,182.56 $ 1,048.13 $ 1,316.32 $ 67.91 $ 60.19 $ 75.59 $ ICRSSL UV90 10B A3 940.03 $ 831.93 $ 1,048.00 $ 53.98 $ 47.78 $ 60.18 $

A1 690.92 $ 615.94 $ 767.38 $ 39.68 $ 35.37 $ 44.07 $

A2 233.72 $ 215.13 $ 252.29 $ 13.42 $ 12.35 $ 14.49 $

A3  Preferred alt. 152.05 $ 140.83 $ 163.16 $ 8.73 $ 8.09 $ 9.37 $

A4 73.99 $ 67.14 $ 80.79 $ 4.25 $ 3.86 $ 4.64 $

A1 690.92 $ 615.94 $ 767.38 $ 39.68 $ 35.37 $ 44.07 $

A2 181.32 $ 167.37 $ 195.31 $ 10.41 $ 9.61 $ 11.22 $

A3  Preferred alt. 99.72 $ 91.34 $ 107.96 $ 5.73 $ 5.25 $ 6.20 $ A4 47.99 $ 43.60 $ 52.42 $ 2.76 $ 2.50 $ 3.01 $

A1 690.92 $ 615.94 $ 767.38 $ 39.68 $ 35.37 $ 44.07 $

A2 154.88 $ 143.07 $ 166.69 $ 8.89 $ 8.22 $ 9.57 $

A3  Preferred alt. 78.15 $ 71.24 $ 85.00 $ 4.49 $ 4.09 $ 4.88 $

A4 34.51 $ 31.32 $ 37.71 $ 1.98 $ 1.80 $ 2.17 $ High A3  Preferred alt. 165.41 $ 152.98 $ 177.56 $ 9.50 $ 8.79 $ 10.20 $ Low A3  Preferred alt. 46.25 $ 42.13 $ 50.40 $ 2.66 $ 2.42 $ 2.89 $ ICR UV90 10B A3 154.98 $ 143.68 $ 166.46 $ 8.90 $ 8.25 $ 9.56 $ ICRSSM UV90 10B A3 101.11 $ 92.82 $ 109.41 $ 5.81 $ 5.33 $ 6.28 $ ICRSSL UV90 10B A3 79.17 $ 72.31 $ 86.02 $ 4.55 $ 4.15 $ 4.94 $ ICR 90 Percent Confidence Bound All System Sizes Small Systems ICR ICRSS Medium System ICRSS Large System ICRSS Medium System ICRSS Large System Mean 90 Percent Confidence Bound Mean Present Value of Capital & O& M Costs Annualized Value of Capital & O& M Costs Data Set Rule Alternative Exhibit H. 1 Present Value Costs at 3 Percent, Filtered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal H 4 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F A1 5,270.04 $ 4,685.70 $ 5,867.77 $ 302.65 $ 269.09 $ 336.97 $ A2 1,608.79 $ 1,430.56 $ 1,792.05 $ 92.39 $ 82.15 $ 102.91 $

A3  Preferred alt. 1,356.46 $ 1,196.70 $ 1,515.61 $ 77.90 $ 68.72 $ 87.04 $

A4 546.90 $ 488.95 $ 606.32 $ 31.41 $ 28.08 $ 34.82 $

A1 5,270.04 $ 4,685.70 $ 5,867.77 $ 302.65 $ 269.09 $ 336.97 $

A2 1,285.04 $ 1,140.21 $ 1,429.51 $ 73.80 $ 65.48 $ 82.09 $

A3  Preferred alt. 990.47 $ 872.06 $ 1,112.15 $ 56.88 $ 50.08 $ 63.87 $

A4 307.59 $ 277.13 $ 338.23 $ 17.66 $ 15.92 $ 19.42 $

A1 5,270.04 $ 4,685.70 $ 5,867.77 $ 302.65 $ 269.09 $ 336.97 $

A2 1,085.62 $ 964.76 $ 1,206.12 $ 62.35 $ 55.40 $ 69.27 $

A3  Preferred alt. 798.58 $ 702.18 $ 897.51 $ 45.86 $ 40.32 $ 51.54 $

A4 207.53 $ 187.68 $ 227.42 $ 11.92 $ 10.78 $ 13.06 $ High A3  Preferred alt. 1,489.83 $ 1,317.20 $ 1,667.10 $ 85.56 $ 75.64 $ 95.74 $ Low A3  Preferred alt. 478.44 $ 419.70 $ 537.29 $ 27.48 $ 24.10 $ 30.86 $ ICR UV90 10B A3 1,539.68 $ 1,365.32 $ 1,712.03 $ 88.42 $ 78.41 $ 98.32 $ ICRSSM UV90 10B A3 1,081.46 $ 955.31 $ 1,206.91 $ 62.11 $ 54.86 $ 69.31 $ ICRSSL UV90 10B A3 860.85 $ 759.62 $ 961.98 $ 49.44 $ 43.62 $ 55.24 $ Large Systems ICR ICRSS Medium System ICRSS Large System Data Set Rule Alternative Present Value of Capital & O& M Costs Annualized Value of Capital & O& M Costs Mean 90 Percent Confidence Bound Mean 90 Percent Confidence Bound Exhibit H. 1 ( Continued) Present Value Costs at 3 Percent, Filtered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal H 5 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F ICR A3  Preferred alt. 204.66 $ 175.80 $ 234.13 $ 11.75 $ 10.10 $ 13.45 $ ICRSSL A3  Preferred alt. 204.66 $ 175.80 $ 234.13 $ 11.75 $ 10.10 $ 13.45 $ ICRSSM A3  Preferred alt. 204.66 $ 175.80 $ 234.13 $ 11.75 $ 10.10 $ 13.45 $

ICR A3  Preferred alt. 14.42 $ 12.78 $ 16.06 $ 0.83 $ 0.73 $ 0.92 $ ICRSSL A3  Preferred alt. 14.42 $ 12.78 $ 16.06 $ 0.83 $ 0.73 $ 0.92 $ ICRSSM A3  Preferred alt. 14.42 $ 12.78 $ 16.06 $ 0.83 $ 0.73 $ 0.92 $

ICR A3  Preferred alt. 190.24 $ 163.02 $ 218.06 $ 10.93 $ 9.36 $ 12.52 $ ICRSSL A3  Preferred alt. 190.24 $ 163.02 $ 218.06 $ 10.93 $ 9.36 $ 12.52 $ ICRSSM A3  Preferred alt. 190.24 $ 163.02 $ 218.06 $ 10.93 $ 9.36 $ 12.52 $ Data Set Rule Alternative 90 Percent Confidence Bound 90 Percent Confidence Bound Mean Annualized Value of Capital & O& M Costs Mean Present Value of Capital & O& M Costs Large Systems Small Systems All System Sizes Exhibit H. 2 Present Value Costs at 3 Percent, Unfiltered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal H 6 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F A1 4,275.03 $ 3,779.02 $ 4,783.01 $ 366.84 $ 324.28 $ 410.43 $

A2 1,321.25 $ 1,171.86 $ 1,474.62 $ 113.38 $ 100.56 $ 126.54 $ A3  Preferred alt. 1,089.45 $ 959.02 $ 1,219.33 $ 93.49 $ 82.29 $ 104.63 $

A4 441.28 $ 392.21 $ 491.54 $ 37.87 $ 33.66 $ 42.18 $

A1 4,275.03 $ 3,779.02 $ 4,783.01 $ 366.84 $ 324.28 $ 410.43 $ A2 1,051.41 $ 930.54 $ 1,172.04 $ 90.22 $ 79.85 $ 100.57 $

A3  Preferred alt. 790.12 $ 693.39 $ 889.39 $ 67.80 $ 59.50 $ 76.32 $

A4 250.03 $ 223.74 $ 276.49 $ 21.46 $ 19.20 $ 23.73 $ A1 4,275.03 $ 3,779.02 $ 4,783.01 $ 366.84 $ 324.28 $ 410.43 $

A2 887.48 $ 786.49 $ 988.20 $ 76.16 $ 67.49 $ 84.80 $

A3  Preferred alt. 635.99 $ 557.20 $ 716.80 $ 54.58 $ 47.81 $ 61.51 $ A4 169.31 $ 151.96 $ 186.69 $ 14.53 $ 13.04 $ 16.02 $ High A3  Preferred alt. 1,195.76 $ 1,054.70 $ 1,340.35 $ 102.61 $ 90.50 $ 115.02 $ Low A3  Preferred alt. 380.80 $ 332.85 $ 428.86 $ 32.68 $ 28.56 $ 36.80 $ ICR UV90 10B A3 1,221.56 $ 1,080.89 $ 1,360.85 $ 104.82 $ 92.75 $ 116.78 $ ICRSSM UV90 10B A3 855.26 $ 752.91 $ 957.10 $ 73.39 $ 64.61 $ 82.13 $ ICRSSL UV90 10B A3 680.49 $ 598.13 $ 762.75 $ 58.39 $ 51.33 $ 65.45 $

A1 442.08 $ 391.17 $ 494.07 $ 37.94 $ 33.57 $ 42.40 $ A2 148.82 $ 136.20 $ 161.41 $ 12.77 $ 11.69 $ 13.85 $

A3  Preferred alt. 96.77 $ 89.22 $ 104.26 $ 8.30 $ 7.66 $ 8.95 $

A4 47.08 $ 42.50 $ 51.63 $ 4.04 $ 3.65 $ 4.43 $

A1 442.08 $ 391.17 $ 494.07 $ 37.94 $ 33.57 $ 42.40 $

A2 115.65 $ 106.21 $ 125.13 $ 9.92 $ 9.11 $ 10.74 $ A3  Preferred alt. 63.49 $ 57.87 $ 69.01 $ 5.45 $ 4.97 $ 5.92 $

A4 30.54 $ 27.59 $ 33.50 $ 2.62 $ 2.37 $ 2.87 $

A1 442.08 $ 391.17 $ 494.07 $ 37.94 $ 33.57 $ 42.40 $ A2 98.79 $ 90.81 $ 106.78 $ 8.48 $ 7.79 $ 9.16 $

A3  Preferred alt. 49.75 $ 45.13 $ 54.34 $ 4.27 $ 3.87 $ 4.66 $

A4 21.96 $ 19.82 $ 24.10 $ 1.88 $ 1.70 $ 2.07 $ High A3  Preferred alt. 105.28 $ 96.90 $ 113.45 $ 9.03 $ 8.32 $ 9.74 $ Low A3  Preferred alt. 29.44 $ 26.69 $ 32.22 $ 2.53 $ 2.29 $ 2.76 $ ICR UV90 10B A3 98.92 $ 91.31 $ 106.67 $ 8.49 $ 7.84 $ 9.15 $ ICRSSM UV90 10B A3 64.46 $ 58.90 $ 70.02 $ 5.53 $ 5.05 $ 6.01 $ ICRSSL UV90 10B A3 50.45 $ 45.85 $ 55.04 $ 4.33 $ 3.93 $ 4.72 $ All System Sizes Mean ICRSS Medium System ICRSS Large System ICRSS Medium System ICR Small Systems Annualized Value of Capital & O& M Costs ICRSS Large System ICR 90 Percent Confidence Bound Mean Present Value of Capital & O& M Costs Rule Alternative 90 Percent Confidence Bound Data Set Exhibit H. 3 Present Value Costs at 7 Percent, Filtered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal H 7 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F A1 3,832.95 $ 3,387.85 $ 4,288.94 $ 328.91 $ 290.71 $ 368.04 $

A2 1,172.43 $ 1,035.66 $ 1,313.21 $ 100.61 $ 88.87 $ 112.69 $

A3  Preferred alt. 992.68 $ 869.80 $ 1,115.06 $ 85.18 $ 74.64 $ 95.68 $ A4 394.21 $ 349.71 $ 439.90 $ 33.83 $ 30.01 $ 37.75 $

A1 3,832.95 $ 3,387.85 $ 4,288.94 $ 328.91 $ 290.71 $ 368.04 $

A2 935.76 $ 824.33 $ 1,046.91 $ 80.30 $ 70.74 $ 89.84 $

A3  Preferred alt. 726.63 $ 635.52 $ 820.38 $ 62.35 $ 54.53 $ 70.40 $

A4 219.49 $ 196.14 $ 242.99 $ 18.83 $ 16.83 $ 20.85 $ A1 3,832.95 $ 3,387.85 $ 4,288.94 $ 328.91 $ 290.71 $ 368.04 $

A2 788.69 $ 695.68 $ 881.41 $ 67.68 $ 59.70 $ 75.63 $

A3  Preferred alt. 586.24 $ 512.07 $ 662.46 $ 50.31 $ 43.94 $ 56.85 $

A4 147.35 $ 132.15 $ 162.59 $ 12.64 $ 11.34 $ 13.95 $ High A3  Preferred alt. 1,090.49 $ 957.80 $ 1,226.90 $ 93.58 $ 82.19 $ 105.28 $ Low A3  Preferred alt. 351.36 $ 306.16 $ 396.65 $ 30.15 $ 26.27 $ 34.04 $ ICR UV90 10B A3 1,122.63 $ 989.58 $ 1,254.18 $ 96.33 $ 84.92 $ 107.62 $ ICRSSM UV90 10B A3 790.81 $ 694.01 $ 887.07 $ 67.86 $ 59.55 $ 76.12 $ ICRSSL UV90 10B A3 630.04 $ 552.27 $ 707.71 $ 54.06 $ 47.39 $ 60.73 $ Large Systems ICR ICRSS Medium System ICRSS Large System Data Set Rule Alternative Present Value of Capital & O& M Costs Annualized Value of Capital & O& M Costs Mean 90 Percent Confidence Bound Mean 90 Percent Confidence Bound Exhibit H. 3 ( Continued) Present Value Costs at 7 Percent, Filtered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal H 8 June 2003 Lower ( 5th % ile) Upper ( 95th % ile) Lower ( 5th % ile) Upper ( 95th % ile)

A B C D E F ICR A3  Preferred alt. 148.60 $ 126.71 $ 170.97 $ 12.75 $ 10.87 $ 14.67 $ ICRSSL A3  Preferred alt. 148.60 $ 126.71 $ 170.97 $ 12.75 $ 10.87 $ 14.67 $ ICRSSM A3  Preferred alt. 148.60 $ 126.71 $ 170.97 $ 12.75 $ 10.87 $ 14.67 $

ICR A3  Preferred alt. 9.33 $ 8.21 $ 10.45 $ 0.80 $ 0.70 $ 0.90 $ ICRSSL A3  Preferred alt. 9.33 $ 8.21 $ 10.45 $ 0.80 $ 0.70 $ 0.90 $ ICRSSM A3  Preferred alt. 9.33 $ 8.21 $ 10.45 $ 0.80 $ 0.70 $ 0.90 $

ICR A3  Preferred alt. 139.27 $ 118.49 $ 160.52 $ 11.95 $ 10.17 $ 13.77 $ ICRSSL A3  Preferred alt. 139.27 $ 118.49 $ 160.52 $ 11.95 $ 10.17 $ 13.77 $ ICRSSM A3  Preferred alt. 139.27 $ 118.49 $ 160.52 $ 11.95 $ 10.17 $ 13.77 $ Large Systems Data Set Rule Alternative 90 Percent Confidence Bound Small Systems 90 Percent Confidence Bound Mean Annualized Value of Capital & O& M Costs All System Sizes Present Value of Capital & O& M Costs Mean Exhibit H. 4 Present Value Costs at 7 Percent, Unfiltered Systems Only Note: Detail may not add to total due to independent rounding. Economic Analysis for the LT2ESWTR Proposal I 1 June 2003 Appendix I Unit Costs for Uncovered Finished Water Reservoirs I. 1 Introduction This appendix presents unit cost tables for covering or treating uncovered finished water reservoirs. This appendix supports the discussion of these rule activities in Chapter 6. General assumptions are provided first, followed by a discussion of each treatment option.

I. 2 Assumptions and Conditions Data on the country's 138 on line uncovered finished water reservoirs were used to develop national costs for each of the three technology options for the Long Term 2 Enhanced Surface Water Treatment Rule ( LT2ESWTR): fixed covers, floating covers, and booster disinfection. For fixed and floating cover estimates, reservoir surface area data are used to assign costs. Where surface area information is unavailable for a reservoir, a depth is assumed to determine surface area for a given reservoir volume.

The data are then divided into 14 size categories for assessing technology costs according to mean values per size category. For each size category, an assumed average hydraulic residence time is used to calculate average daily and design flows. The average daily flow is then used to calculate mean surface area per size category. Exhibit I. 1 presents the data used in the costing efforts. Economic Analysis for the LT2ESWTR Proposal I 2 June 2003 Exhibit I. 1 Baseline Conditions for Uncovered Reservoirs by Size Category Reservoir Size Category ( MG) Number of Uncovered Reservoirs Estimated Average Hydraulic Residence Time ( day) Design Flow ( mgd) Average Flow ( mgd) Mean Volume ( MG) Mean Surface Area ( ft2)

0  0.1 25 1 0.04 0.01 0.01 176 > 0.1  1 7 1 1.30 0.43 0.43 2,952 > 1  5 44 1 7.78 2.59 2.59 14,127 > 5  10 12 2 12.82 4.27 8.55 45,703 > 10  20 10 3 15.32 5.11 15.32 84,165 > 20  40 9 3 28.68 9.56 28.68 213,890 > 40  60 4 3 52.99 17.66 52.99 283,353 > 60  80 4 3 71.44 23.81 71.44 365,472 > 80  100 6 3 93.57 31.19 93.57 517,699 > 100  150 6 4 94.01 31.34 125.34 670,246 > 150  200 2 4 140.25 46.75 187.00 999,934 > 200  250 4 4 158.06 52.69 210.75 1,126,931 > 250  1000 4 14 167.46 55.82 781.50 3,482,390 > 1000 1 21 473.40 157.80 3,313.80 7,666,876 TOTAL 138 Note: Average daily flow is assumed to be one third of design flow. Source: EPA Regions I. 3 Covers Uncovered finished water reservoirs are susceptible to contamination from bird and animal waste and airborne deposition. Covering the reservoirs can provide protection from water quality deterioration. In addition to providing public health protection, covers prevent algal growth and reduce the amount of chlorine lost during storage by excluding sunlight ( Griffith 1988).

A number of factors are involved in determining a suitable cover, including reservoir size and shape, geological stability of the area, estimated snow, wind and seismic loads put on the reservoir, length of time the reservoir would be taken off line for construction, existing reservoir rehabilitation, and construction and operations and maintenance ( O& M) costs. The rest of this section explains the estimated capital and O& M costs associated with fixed and floating covers. Fixed and floating cover costs do not include any costs associated with the design, re design, or rehabilitation of a reservoir. Economic Analysis for the LT2ESWTR Proposal I 3 June 2003 Exhibit I. 2 Floating Cover Costs for Uncovered Reservoirs Size Category ( MG) Costs per Reservoir Capital Cost ($) Annual O& M ($)

0  0.1 $ 476 $ 14 > 0.1  1 $ 7,970 $ 239 > 1  5 $ 38,143 $ 1,144 > 5  10 $ 123,397 $ 3,702 > 10  20 $ 227,245 $ 6,817 > 20  40 $ 577,502 $ 17,325 > 40  60 $ 765,053 $ 22,952 > 60  80 $ 986,776 $ 29,603 > 80  100 $ 1,397,787 $ 41,934 > 100  150 $ 1,809,663 $ 54,290 > 150  200 $ 2,699,821 $ 80,995 > 200 250 $ 3,042,713 $ 91,281 > 250  1,000 $ 9,402,453 $ 282,074 > 1,000 $ 20,700,565 $ 621,017 I. 3.1 Floating Covers Floating covers are flexible membrane structures, either air supported fabric or polypropylene material, that rest on the surface of open reservoirs. For drainage purposes, floating covers should be flexible as they tend to collect rainwater and washwater. Routine monitoring for damage and proper maintenance and cleaning of the cover will extend its useful life. For this Economic Analysis ( EA), floating cover material is assumed to be polypropylene. Material costs are estimated at $ 2.00/ sq. ft., and O& M cost estimates are 3 percent of total capital costs ( USEPA 1999c). For each size category, material costs are estimated for the mean surface area.

Based on best professional judgment, engineering contingencies ( construction, standby power, contractor overhead and profit ( O& P), legal, fiscal and administrative costs) are estimated to be 35 percent of material costs. Exhibit I. 2 presents capital and O& M costs associated with floating covers.

I. 3.2 Fixed Covers Fixed covers are permanent structures constructed to direct drainage away from the reservoir and prevent other contamination of the stored water ( USEPA 1999c). These permanent structures can be made from wood, steel, reinforced concrete, or aluminum. 1 As shown in the Report on Water Quality Issues at Sheffield Reservoir for the City of Santa Barbara ( Carollo 1999).

Economic Analysis for the LT2ESWTR Proposal I 4 June 2003 Exhibit I. 3 Fixed Cover Costs for Uncovered Reservoirs Size Category ( MG) Costs per Reservoir Capital Cost ($) Annual O& M ($)

0  0.1 $ 5,232 $ 5 > 0.1  1 $ 87,665 $ 88 > 1  5 $ 419,578 $ 420 > 5  10 $ 1,357,368 $ 1,357 > 10  20 $ 2,499,690 $ 2,500 > 20  40 $ 6,352,521 $ 6,353 > 40  60 $ 8,415,587 $ 8,416 > 60  80 $ 10,854,533 $ 10,855 > 80  100 $ 15,375,659 $ 15,376 > 100  150 $ 19,906,296 $ 19,906 > 150  200 $ 29,698,036 $ 29,698 > 200 250 $ 33,469,846 $ 33,470 > 250  1,000 $ 103,426,984 $ 103,427 > 1,000 $ 227,706,218 $ 227,706 Due to high capital costs, fixed covers are typically limited to smaller sized reservoirs, up to 20 million gallons. However, fixed covers require little or no O& M expenses.

For this EA, fixed cover material is assumed to be common concrete material. In the same manner as the floating cover cost model, costs are estimated for the mean surface area for each size category. Material costs are $ 22.00/ sq. ft. ( USEPA 1999c). O& M costs are assumed to be 0.1 percent of total capital cost. 1 As with floating cover cost estimates, engineering contingencies are included at 35 percent of capital costs. Exhibit I. 3 presents capital and O& M costs associated with fixed covers.

I. 4 Disinfection As stated previously, uncovered finished water reservoirs are susceptible to human and animal contamination. In order to maintain a potable water supply, systems may add a disinfectant to the Economic Analysis for the LT2ESWTR Proposal I 5 June 2003 reservoir if they do not cover the reservoir. For this EA, chlorination of finished water is estimated to achieve 4 log inactivation of viruses, and to be the least costly disinfection alternative.

To develop costs associated with disinfection, the analysis uses the Water Model ( USEPA 1984) and the Water and Wastewater ( W/ W) Costs and Design Criteria Guidelines Model ( CWC 1994). These cost models cover 45 different unit treatment processes. Since these reservoirs contain finished or already treated water, low dose gas chlorination is assumed to maintain sufficient disinfectant residual in the distribution system; hereafter, this is referred to as " booster chlorination." The Water Model is used to estimate capital and O& M costs for systems with average daily flow capacity less than or equal to 1 mgd; the W/ W Model is used for all average daily flow capacities greater than 1 mgd.

EPA evaluated CT requirements from the 1996 SWTR Guidance Manual and determined that a chlorine dose of 1.0 mg/ l would provide adequate virus inactivation in most cases. Other assumptions for booster chlorination are given in Exhibit I. 4.

Exhibit I. 4 Assumptions for Booster Chlorination Size Category ( MG) Number of Uncovered Reservoirs Design Flow ( mgd) Design Flow ( lb/ day) Avg. Daily Flow ( mgd) Avg. Daily Flow ( lb/ day) Booster Cl2 Dose ( mg/ L) Booster Cl2 Dose ( ton/ year)

0  0.1 25 0.04 0.33 0.01 0.11 1.00 0.02 > 0.1  1 7 1.30 10.87 0.43 3.62 1.00 0.66 > 1  5 44 7.78 64.90 2.59 21.63 1.00 3.95 > 5  10 12 12.82 106.92 4.27 35.64 1.00 6.50 > 10  20 10 15.32 127.74 5.11 42.58 1.00 7.77 > 20  40 9 28.68 239.20 9.56 79.73 1.00 14.55 > 40  60 4 52.99 441.94 17.66 147.31 1.00 26.88 > 60  80 4 71.44 595.77 23.81 198.59 1.00 36.24 > 80  100 6 93.57 780.34 31.19 260.11 1.00 47.47 > 100  150 6 94.01 784.03 31.34 261.34 1.00 47.70 > 150  200 2 140.25 1,169.69 46.75 389.90 1.00 71.16 > 200  250 4 158.06 1,318.24 52.69 439.41 1.00 80.19 > 250  1,000 4 167.46 1,396.65 55.82 465.55 1.00 84.96 > 1,000 1 473.40 3,948.16 157.80 1,316.05 1.00 240.18 Source: USEPA 1984, CWC 1994 Economic Analysis for the LT2ESWTR Proposal I 6 June 2003 Both cost models require standard indices and unit costs from the Bureau of Labor Statistics ( BLS) and the Engineering News Record ( ENR) to generate capital and O& M costs. For booster chlorination, these cost models take into account typical process equipment and chemical building costs and, therefore, do not require additional adjustments. As adapted from the Technology and Cost Document ( USEPA 2003a), values used in estimating booster chlorination costs are reported in Exhibit I. 5.

Exhibit I. 5 Cost Indices Used in the Cost Models Parameter Cost Index ENR Building Cost 3,505 ENR Skilled Labor 5,596 ENR Material Prices 2,228 Electricity $ 0.08/ k Wh Natural Gas $ 0.006/ ft3 Diesel Fuel $ 1.25/ ft2 Housing Costs $ 125/ ft2 Labor: 0 5 MG $ 14.5/ hr Labor: > 5 MG $ 28.0/ hr Engineering 15% of total equipment costs Sitework, Interface Piping 15% of total equipment costs Subsurface Considerations 10% of total equipment costs Standby Power 5% of total equipment costs Land Cost $ 0/ acre Interest Rate During Construction 7%

Number of Years 20 Chlorine, 1 ton cylinder (> 1MG, < 250 MG) $ 350/ ton Chlorine, bulk (> 250 MG) $ 280/ ton Economic Analysis for the LT2ESWTR Proposal I 7 June 2003 Exhibit I. 6 Booster Chlorination Costs for Uncovered Finished Water Reservoirs Size Category ( MG) Costs per Reservoir Capital Cost ($) Annual O& M ($)

0.0  1 $ 48,522 $ 3,838 > 0.1  1 $ 48,522 $ 3,838 > 1  5 $ 63,472 $ 11,039 > 5  10 $ 76,363 $ 18,210 > 10  20 $ 82,272 $ 18,767 > 20  40 $ 116,156 $ 21,896 > 40  60 $ 176,786 $ 27,539 > 60  80 $ 222,202 $ 31,801 > 80  100 $ 277,279 $ 36,939 > 100  150 $ 278,002 $ 37,025 > 150  200 $ 377,564 $ 47,792 > 200 250 $ 409,216 $ 51,907 > 250  1,000 $ 424,992 $ 54,068 > 1,000 $ 749,311 $ 99,960 Exhibit I. 6 presents cost model outputs for capital and O& M costs associated with booster chlorination for uncovered reservoirs.

I. 5 National Cost Estimate To determine national costs for covering or treating uncovered finished water reservoirs, the number of reservoirs selecting each technology uses a least cost approach, but assumes only 50 percent of reservoirs install booster chlorination. The technology selection for uncovered finished water reservoirs is presented in Exhibit I. 7. Economic Analysis for the LT2ESWTR Proposal I 8 June 2003 Exhibit I. 7 Technology Selection for Uncovered Finished Water Reservoirs Size Category ( MG) Number of Uncovered Reservoirs Floating Cover (%) Booster Chlorination (%)

0 0.1 25 100

> 0.1 1 7 100

> 1 5 44 100

> 5 10 12 100

> 10 20 10 100

> 20 40 9 50 50 > 40 60 4 50 50 > 60 80 4 50 50 > 80 100 6 50 50 > 100 150 6 50 50 > 150 200 2 50 50 > 200 250 4 50 50 > 250 1,000 4 50 50 > 1,000 1 50 50 To determine national costs to comply with the uncovered reservoir requirement of the LT2ESWTR, the number of reservoirs selecting each technology is multiplied by the capital and O& M costs for that technology. To account for uncertainty when the total costs are modeled, a triangular distribution of + 15 percent around the mean estimate is assumed for O& M costs; also a triangular distribution of + 30 percent around the mean estimate for capital costs is assumed. For each value 10,000 values are drawn to generate a distribution. Present value is calculated for the mean, 5th, and 95th percentile at both 3 and 7 percent discount rates, then annualized at those rates. Exhibit I. 8 shows the annual cost estimates for complying with the uncovered reservoir requirement of the LT2ESWTR. Economic Analysis for the LT2ESWTR Proposal I 9 June 2003 Capital O& M Total Capital O& M Total   £ 10,000 $ 3,520 $ 1,649 $ 5,169 $ 4,713 $ 1,552 $ 6,264 > 10,000 $ 3,349,320 $ 2,046,425 $ 5,395,745 $ 4,483,927 $ 1,925,203 $ 6,409,129 Total $ 3,352,840 $ 2,048,074 $ 5,400,915 $ 4,488,639 $ 1,926,754 $ 6,415,393 Annualized Cost at 3% Annualized Cost at 7% System Size ( Population Served) Exhibit I. 8 Annual National Cost Estimate for Uncovered Finished Water Reservoirs 1.6 Number of Households Expected To Incur Costs To determine the number of households incurring costs attributed to covering or treating the uncovered finished water reservoirs, the 14 reservoir volume categories are assigned to the nine population size categories. A CWS regression equation from the Model Systems Report ( USEPA 2000b) is used for this purpose. Using the average daily flow, calculated from the volume and assumed detention time, a population is calculated. Reservoirs are then assigned to size categories using this population. For these purposes, the flow through the reservoir is estimated to be the entire system flow. Although this may not be an accurate assumption in all cases, there is no basis on which to make another assumption. Exhibit I. 9 presents the categorization of the 138 reservoirs by population served.

Exhibit I. 9 Number of Uncovered Finished Water Reservoirs by Population Size Category System Size ( Population Served) Number of Reservoirs < 100 25 101  500 0 501  1,000 0 1,001  3,300 0 3,301  10,000 7 10,001  50,000 66 50,001  100,000 9 100,001  1 M 30 > 1 M 1 Total 138 Economic Analysis for the LT2ESWTR Proposal I 10 June 2003 To determine the number of households incurring costs, the number of systems is then multiplied by the average number of households per system. The average number of households per system is the ratio of the average number of people per system from the Baseline Handbook ( USEPA 2001c) to the average number of people per household ( 2.59). Exhibit I. 10 presents the total number of households incurring the cost of covering or treating the nation's uncovered finished water reservoirs.

Exhibit I. 10 Number of Households Incurring Costs for Uncovered Finished Water Reservoirs System Size ( Population Served) Number of Households < 100 574 101  500 0 501  1,000 0 1,001  3,300 0 3,301  10,000 13,469 10,001  50,000 541,715 50,001  100,000 133,227 100,001  1 M 2,002,187 > 1 M 320,762 Total 3,011,934 Economic Analysis for the LT2ESWTR Proposal J 1 June 2003 Average Number of People per Plant 1 Average Number of People per Household 2 Average Number of Households per Plant Number of Plants Subject to Rule Activity 3 Total Number of Households Incurring Costs Appendix J Estimation of Household Costs J. 1 Introduction The complexities involved in calculating the costs for the Long Term 2 Enhanced Surface Water Treatment Rule ( LT2ESWTR) make the derivation of household costs particularly difficult. Household costs are presented as average, or mean, household costs incurred for all systems and for those systems adding treatment. Distributions of household costs are also developed, graphically showing the variability in costs for households impacted by the rule. This appendix is intended to take the reader through the household cost calculation process.

J. 2 Calculation of Household Costs Step 1: Calculating the Number of Households Incurring Costs The first step in arriving at annual household cost estimates is calculating the total number of households subject to LT2ESWTR provisions for each system size category. The number of households per plant is calculated by dividing the average number of people served per plant by the average number of people per household ( 2.59 people per household) for each system size category ( U. S. Census Bureau 2001a). SDWIS data provides system populations for all community water systems ( CWSs) according to the established system population size categories ( this analysis is limited to CWSs because only those systems serve residential customers) ( USEPA 2000f). The average number of people served per plant ( presented in Chapter 4) is derived from the SDWIS data, while the number of people per household is the 2000 Census Bureau data estimate. This calculation results in the number of households per plant for a given size category. The following flowchart illustrates this calculation.

1 Average number of people per plant is derived from the 2000 SDWIS database and the Model Systems Report. 2 Average number of people per household is taken from 2000 U. S. Census data 3 Evaluated separately for filtered plants, unfiltered plants, and uncovered finished water reservoirs The number of households incurring costs is estimated separately for filtered plants, unfiltered plants and uncovered finished water reservoirs and for each rule activity ( implementation, monitoring, and treatment). Economic Analysis for the LT2ESWTR Proposal J 2 June 2003 Filtered Plants The total number of households subject to each rule activity is estimated by multiplying the average number of households per plant by the number of plants subject to the activity. The number of plants implementing the rule is the same for all regulatory alternatives but the number monitoring or adding treatment varies depending on the regulatory alternative and the modeled Cryptosporidium occurrence distribution. The percentage of plants conducting each activity is shown below and is derived from Chapter 6:

° Implementation  100 percent of plants ( Implementation is based on a system level, but 100 percent of systems perform implementation activities; therefore, 100 percent of plants would also incur implementation costs.)

° E. coli Monitoring  96 to 99.6 percent of plants ° Cryptosporidium Monitoring  34 to 99.6 percent of plants ° Future Monitoring for E. coli  70 to 90 percent of plants ° Future Monitoring for Cryptosporidium  27 to 71 percent of plants The baseline number of plants performing implementation and conducting E. coli monitoring is the number of nonpurchased plants ( EPA assumes that purchased plants do not have untreated source waters and that they buy all their water from another system). EPA expects that the nonpurchased plants will pass their costs onto all customers, including other systems that purchase water from them. Because purchased systems will experience wholesale cost increases that reflect implementation and monitoring, households in purchased systems are included in the household calculation as well. Below is an illustration that represents how monitoring and implementation costs are applied to households in purchased and nonpurchased systems. Economic Analysis for the LT2ESWTR Proposal J 3 June 2003 R i v e r T r e a t m e n t P l a n t S y s t e m A N o n p u r c h a s e d S y s t e m B P u r c h a s e d D i s t r i b u t i o n S y s t e m R e t a i l P o p u l a t i o n o f S y s t e m A R e t a i l P o p u l a t i o n o f S y s t e m B ( E q u a l s W h o l e s a l e P o p u l a t i o n o f S y s t e m A )

D i s t r i b u t i o n S y s t e m R e s e r v o i r / L a k e T o t a l N a t i o n a l I m p l e m e n t a t i o n a n d M o n i t o r i n g C o s t I n c r e a s e i n H o u s e h o l d C o s t s f r o m I m p l e m e n t a t i o n a n d M o n i t o r i n g Exhibit J. 1 Distribution of Costs Between Purchased and Nonpurchased Systems Treatment costs are estimated for both purchased and nonpurchased systems ( see Chapter 4 for explanation of why this is appropriate considering the system classification scheme).

To properly determine the impact of costs on households belonging to small purchased systems, the actual costs passed onto the purchased system from the nonpurchased system are taken into account. The costs incurred by the customers of these small purchased systems are included in the size category to which the purchaser belongs and not to the larger size category of the seller. To accomplish this, the number of households in each linked size category as described in Chapter 4 is determined. Then the percentage of households in a linked size category deriving from each of the unlinked size categories is determined. This percentage is multiplied by the total number of households in the linked size category. The resulting cost is then multiplied by the household water usage number for the unlinked size category to determine the household costs for households served by that purchased system.

For example, in the size category serving between 501 and 1,000 people ( S3), there are 120,915 people served by surface water or ground water under the direct influence of surface water ( GWUDI) systems. Of these, 1,690 come from purchased systems in the 101 to 500 people served category ( S2) and 132 people come from the systems in the < 100 people served size category ( S1). Therefore, 1 Detailed descriptions of the assumptions and processes used in the development of treatment capital and O& M costs can be found in " Technologies and costs for control of microbial contaminants and disinfection byproducts ( USEPA 2003a) as well as preceding sections of this document.

2 The Baseline Handbook breaks systems down into five categories   public, private, purchased public, purchased private, and other. These categories are combined to form two groups   public, which include public and purchased public water systems, and private, which include private and purchased private. Systems in the " other"

Economic Analysis for the LT2ESWTR Proposal J 4 June 2003 1.4 percent of the total population in the S3 category is associated with purchased systems in the S2 category and 0.1 percent with purchased systems in the S1 category. These percentages would then be multiplied by the total number of households in the size category to obtain the number of households incurring the cost for the S3 category. Therefore, for each technology cost in the S3 category, 98.5 percent would be allocated to the S3 category, 1.4 percent would be placed in the S2 category, and 0.1 percent would be placed in the S1 category. This step has no effect on the national household cost distributions but only affects analyses which are broken down by size category.

Unfiltered Plants The total number of households affected by the rule is estimated by multiplying the average number of households per plant by the number of unfiltered plants subject to the rule. The percentage of plants subject to each rule activity is the same for all regulatory alternatives and is derived from Chapter 6:

° Implementation  100 percent of plants ( Implementation is based on systems, but 100 percent of systems perform implementation activities, therefore, 100 percent of plants will also incur implementation costs.)

° Adding Treatment for Cryptosporidium Control  100 percent of plants ° Monitoring  100 percent of plants Implementation costs are applied to households in both purchased and nonpurchased systems in a manner similar to that for filtered plants.

Uncovered Finished Water Reservoirs The total number of households affected by the rule is estimated by determining the average daily flow for each reservoir size category and using flow per population regression equations from the Model Systems Report. The number of households affected by the rule is the same for all regulatory alternatives.

Step 2: Household Unit Costs for Each Treatment Technology The capital and operations and maintenance ( O& M) costs for applicable technologies and the average daily flow for each system size are used to calculate a household unit cost ( Appendix I) 1. Flows for CWSs are presented in Chapter 4. Costs are annualized according to system size and ownership at discount rates of about 5 to 6 percent ( see Exhibit J. 2 for specific rates). The percentage of plants publicly and privately owned is derived from SDWIS. 2 category are distributed among the remaining ownership categories based on the numbers of public and private systems in each category.

Economic Analysis for the LT2ESWTR Proposal J 5 June 2003 Household unit costs for each technology can be represented by the following equation   HHUC =( ACC+ O& M)/( ADF* 1,000* 365)

where: HHUC = Household Unit Cost ($/ 1000 gal) ACC = Annualized Capital Cost ($) ( as described in Chapter 6 and Appendix C) ADF = Average Daily Flow ( MGD) ( as presented in Chapter 4) O& M = Annual Operations and Maintenance Costs ( as described in Chapter 6 and Appendix C) ($/ 1000 gal)

Once average household unit costs for each treatment technology are determined, they are multiplied by the annual water usage per household to arrive at average annual household treatment costs. Annual water usage rates used in this calculation are derived from residential usage from the Baseline Handbook and are shown in Exhibit J. 2.

Exhibit J. 2 Data Used to Estimate Household Costs System Size ( population served) Average HH/ Plant Discount Rate Annual Water Usage per Household ( kgal/ yr) Public Private # 100 22 5.31% 6.22% 83 101 500 109 5.31% 6.22% 83 501 1,000 289 5.58% 6.22% 104 1,001 3,300 760 5.58% 6.22% 87 3,301 10,000 2,285 5.58% 6.22% 97 10,001 50,000 8,779 5.20% 5.66% 109 50,001 100,000 26,182 5.24% 6.27% 119 100,001 1 Million 95,969 5.24% 6.27% 125 > 1 Million 844,639 5.24% 6.27% 125 Source: Baseline Handbook ( USEPA, 2001c) Economic Analysis for the LT2ESWTR Proposal J 6 June 2003 Step 3: Distribution of Annual Household Treatment Costs ( cost per household)

Once the annual household costs for each technology are derived, they are paired with the number of households incurring costs for that specific treatment technology. For example, in the 101 500 population served size category, the number of households served by a plant installing microfiltration will be paired with the annual household cost for microfiltration as calculated above. This process is repeated for each treatment technology that is forecast to be employed within a given system size category. The end result of this process is a distribution of treatment costs across a given system size category.

Step 4: Distribution of Annual Household Implementation and Annual Household Monitoring Costs ( cost per household)

Annual household implementation and monitoring costs are estimated in the same manner as annual household treatment costs. Implementation costs as well as E. coli monitoring costs are assigned to all households. Costs for Cryptosporidium monitoring, future E. coli monitoring, future Cryptosporidium monitoring, and uncovered finished water reservoirs apply to just a percentage of the total plants and therefore to a percentage of the total households. The household unit cost for each size category and the percentage of plants in each size category that must pay that cost are used to generate the total national household cost distribution.

Step 5: Summation and Presentation of Results Implementation and E. coli monitoring household costs are applied to all households. Each technology unit cost is then added to the proportion of households using that technology as the proportion of overall households incurring that type of cost. The costs for Cryptosporidium monitoring, future E. coli and Cryptosporidium monitoring, and uncovered finished water reservoirs are added to a portion of households for each technology. For example, for the ICR occurrence distribution, 51 percent of plants are required to monitor Cryptosporidium. Therefore, in the household costs distribution, the unit cost for Cryptosporidium monitoring is added to 51 percent of the plants in each technology. Other types of costs are similarly apportioned. This procedure results in the non treatment costs being spread out randomly over all systems. EPA recognizes that this may not accurately reflect the true distribution of monitoring and reservoir costs, but the errors introduced are small and it is difficult to predict whether for example systems with uncovered reservoirs would have to install treatment on their plant as well.

J. 3 Household Costs EPA assumes that increases in system costs stemming from implementation of the LT2ESWTR will be passed onto customers. Exhibit J. 3 presents mean expected increases in yearly household costs by system size and source water category. These cost increases incorporate costs for rule implementation, monitoring for bin classification, uncovered filtered water reservoirs, future monitoring for bin changes, and treatment changes. Household costs are estimated separately for each of the three modeled Cryptosporidium occurrence distributions.

Households served by systems required to make treatment changes under the LT2ESWTR will face much larger increases in household water costs than other systems. Costs for only this subset of households are also presented in Exhibit J. 4 to enable separate evaluation. Cost increases to households served by systems making treatment changes are important for evaluating how the rule will affect annual household expenditures nationwide. Economic Analysis for the LT2ESWTR Proposal J 7 June 2003 System Type/ Size Households Mean Median 90th Percentile 95th Percentile Percent of Systems with Household Cost Increase < $ 12 Percent of Systems with Household Cost Increase < $ 120 All CWS 65,816,979 $ 1.68 $ 0.13 $ 4.06 $ 7.57 98.37% 99.99% All CWS £ 10,000 3,318,012 $ 4.61 $ 1.34 $ 13.04 $ 14.92 87.88% 99.88%

All CWS 65,816,979 $ 1.07 $ 0.03 $ 3.24 $ 5.43 99.31% 100.00% All CWS £ 10,000 3,318,012 $ 2.68 $ 0.80 $ 6.10 $ 9.39 95.71% 99.95%

All CWS 65,816,979 $ 1.28 $ 0.03 $ 3.48 $ 6.47 99.07% 100.00% All CWS £ 10,000 3,318,012 $ 3.27 $ 0.80 $ 6.62 $ 13.04 93.90% 99.93%

All CWS 65,816,978 $ 1.83 $ 0.14 $ 4.51 $ 7.58 98.25% 99.99% All CWS £ 10,000 3,318,012 $ 4.98 $ 1.43 $ 13.50 $ 15.78 87.15% 99.87%

All CWS 65,816,979 $ 0.73 $ 0.03 $ 2.81 $ 3.84 99.60% 100.00% All CWS £ 10,000 3,318,012 $ 1.76 $ 0.46 $ 5.37 $ 6.10 97.51% 99.98% All Systems  Low All Systems  ICR All Systems  ICRSSL All Systems  ICRSSM All Systems  High EPA estimates that 100 percent of the households served by surface and GWUDI sources will face some increase in household costs due to the LT2ESWTR ( except for those very few served by systems that have already installed 5.5 logs of treatment for Cryptosporidium ( see Chapter 4 for a summary of households served by systems affected by various LT2ESWTR provisions). Approximately 95 percent of the households potentially affected by the rule are served by systems serving at least 10,000 people; these systems experience the lowest increases in costs due to economies of scale. Households served by small systems that install advanced technologies will face the greatest increases in annual costs because they are not able to achieve the economies of scale of larger systems.

All households will face costs less than $ 389 per year. Ninety percent of all households are predicted to incur costs less than $ 4.51 per year. Exhibits J. 5 and J. 6 provide cumulative distributions of household costs for all systems and for those households in systems adding treatment. Cumulative distributions for households in small systems and for small systems adding treatment are shown in Exhibits J. 7 and J. 8.

Exhibit J. 3 Summary of Annual Household Cost Increases ($/ Year) Economic Analysis for the LT2ESWTR Proposal J 8 June 2003 System Type/ Size Households Mean Median 90th Percentile 95th Percentile Percent of Systems with Household Cost Increase < $ 12 Percent of Systems with Household Cost Increase < $ 120 All CWS 24,698,531 $ 4.07 $ 3.23 $ 7.58 $ 9.52 95.79% 99.99% All CWS £ 10,000 1,190,922 $ 10.47 $ 6.10 $ 18.01 $ 19.83 68.94% 99.72%

All CWS 17,533,865 $ 3.36 $ 3.22 $ 7.58 $ 8.10 97.59% 99.99% All CWS £ 10,000 788,519 $ 8.02 $ 6.00 $ 13.48 $ 17.79 85.55% 99.83%

All CWS 20,353,968 $ 3.59 $ 3.22 $ 7.58 $ 8.57 97.16% 99.99% All CWS £ 10,000 944,594 $ 8.63 $ 6.00 $ 13.67 $ 19.83 81.83% 99.80%

All CWS 26,854,217 $ 4.11 $ 3.23 $ 7.58 $ 9.52 95.83% 99.99% All CWS £ 10,000 1,309,992 $ 10.45 $ 6.10 $ 17.79 $ 20.05 69.95% 99.72%

All CWS 12,377,952 $ 2.86 $ 1.55 $ 7.58 $ 7.78 98.06% 99.99% All CWS £ 10,000 503,399 $ 7.30 $ 5.37 $ 13.04 $ 14.92 88.00% 99.87% All Affected Systems  ICR All Systems  ICRSSL All Systems  ICRSSM All Systems  High All Systems  Low Exhibit J. 4 Summary of Annual Household Cost Increases for Plants Adding Treatment ($/ Year) Economic Analysis for the LT2ESWTR Proposal J 9 June 2003 Economic Analysis for the LT2ESWTR Proposal J 10 June 2003 Economic Analysis for the LT2ESWTR Proposal J 11 June 2003 Economic Analysis for the LT2ESWTR Proposal J 12 June 2003 1 The effect of illness on the use of time is referred to as time losses in this report to separate these effects from the other social welfare impacts of illness that are evaluated separately. In reality, these losses are shifts in the use of time from its preferred use to illness related activities, and hence in economic terms can be more accurately described as one of the components of utility losses associated with illness.

2 This section provides a brief overview of several topics that are covered in more detail in EPA's Guidelines for Preparing Economic Analyses ( USEPA 2000e).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 1 Appendix K Additional Information on the Approach For Valuing Time Losses K. 1 Introduction As discussed in the main text of this report, the value of averting cryptosporidiosis related morbidity is estimated based on information on ( 1) the medical costs associated with the illness and ( 2) the value of time lost due to illness1. This appendix provides a more in depth discussion of this approach, describing both the overall selection of the cost of illness ( COI) method and the details of the approach used to value time losses. The appendix focuses on the rationale for the methodological choices made for this analysis; information on the specific numerical values used to apply this approach are described in Appendix L.

Appendix K begins by discussing the rationale for relying on COI methods rather than other measures of social welfare ( i. e., willingness to pay ( WTP) estimates) for valuing the reductions in risk from cryptosporidiosis morbidity. This discussion provides a brief introduction to the concept of WTP, then describes its relationship to COI methods. It next describes the potential applicability of the available WTP literature to the types of morbidity risks considered in this analysis and the problems with relying on this literature. EPA's Science Policy Council has also considered these issues and the reader can find more detail in its Handbook for Non Cancer Health Effects Valuation.

The appendix then introduces the two approaches used to value time losses in this Economic Analysis. One approach, the Traditional Cost of Illness ( COI), is based on the human capital approach typically applied in COI studies, focusing on the effect of illness on labor productivity ( as measured by work time lost, whether paid or unpaid). Another approach, the Enhanced COI, attempts to provide a more complete estimate of the social welfare impacts of time losses due to illness based on the existing data and literature. The subsequent sections of the appendix then discuss these approaches for valuing each type of time loss in more detail.

K. 2 WTP and COI Approaches In the context of benefit cost analysis, the valuation of human health risk reductions is based on the principles of neoclassical welfare economics2. These principles assume that each individual is the best judge of his or her own well being ( referred to as " utility" by economists), and that individual preferences should form the basis of valuing any changes that affect societal welfare. Economic Analysis for the LT2ESWTR Proposal June 2003 K 2 In theory, the dollar value of the benefits associated with a risk reduction is most appropriately measured by determining the change in income that has the same effect on utility ( or the level of individual well being) as the change in risk. Because utility is impossible to measure directly, economists typically rely instead on estimates of WTP or willingness to accept ( WTA) compensation. WTP is the maximum amount of money an individual would voluntarily exchange to obtain an improvement ( such as a risk reduction) given his or her budget constraints. WTA is the least amount of money an individual would accept to forego the improvement. These two measures are not necessarily equal. However, in practice, economists usually rely on measures of WTP because of concerns about the accuracy and reliability of the methods available for estimating WTA compensation.

WTP is a different concept than cost or price. " Cost" refers to the resources needed to produce a good or service; it does not measure the value of the good or service to members of society. " Price" is determined by the interactions of producers and consumers in the marketplace. For some individuals, the market price may exceed WTP, in which case they will not purchase the good. For other individuals, WTP may exceed the current price, in which case these individuals will benefit from the fact that the market price is less than they are willing to pay.

Estimates of WTP can be derived, however, from price and quantity data for goods that are bought and sold in the marketplace ( i. e., " market goods"). For other, " nonmarket," goods   such as health risk reductions, economists generally group methods for estimating WTP into two categories. The first category, " stated preference" methods, involves asking individuals what they would be willing to pay for a change in health risk or another nonmarket good. The most commonly used stated preference approach is the contingent valuation method, which involves surveying individuals and asking them how much they would be willing to pay for a hypothetical nonmarket good given their existing household budget.

The second category of valuation approaches for nonmarket goods includes " revealed preference" methods, and involves looking at behavior for related goods. One example of these methods is wage risk studies, which estimate the change in wages required for riskier jobs, using statistical methods to control for the many factors other than risk that affect wage levels. Another example of revealed preference methods is averting behavior models, which consider market goods that are purchased at least in part to achieve risk reductions   such as bottled water or home filters. These latter methods are rarely used in practice however, due to difficulties in sorting out the value of risk reductions from the values associated with other characteristics of the product ( e. g., improved taste or convenience).

COI studies differ from these stated and revealed preference methods in that they are a measure of cost rather than WTP. These studies examine the actual direct costs ( e. g., medical expenses such as doctor visits, medication, and hospital stays) incurred by individuals affected by the illness. The COI method is relatively easy to apply because: ( 1) it is well developed, widely used, and easily explained; ( 2) many of the types of costs it includes are easily measured; and ( 3) existing studies provide estimates for a large number of illnesses. For these reasons, this method is often used in economic analyses despite its shortcomings as a proxy for WTP.

In general, the logic for using COI methods is that, if illness imposes the costs of medical expenditures and foregone earnings, then a policy that reduces illness yields benefits equal, at a minimum, to the costs saved ( Tolley et al. 1994). However, COI estimates may underestimate individual WTP because they do not explicitly address the value of avoiding the pain and suffering associated with the illness ( especially the Traditional COI), nor the costs that individuals incur to avoid the illness ( often 3 COI estimates may, in some limited cases, overstate WTP   for example, because the availability of insurance may lead people to agree to treatments that they would not willingly finance themselves.

4 See, for example, EPA's Handbook for Non Cancer Health Effects Valuation ( USEPA 2000h). The literature review in the Handbook was updated and extended to include cancers in: Industrial Economics, Incorporated, ( unpublished).

5 Assuming that the estimate is for the year 1985, the year 2000 equivalent is $ 77 per additional day, inflated using the Consumer Price Index for all Urban Consumers ( CPI U).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 3 referred to as defensive or averting expenditures) 3. In addition, COI estimates do not reflect aversion to risk, i. e., the effect of fear of illness on WTP. In contrast to welfare measures based on ex ante WTP to avert health risks, COI measures examine the actual ex post costs to society associated with treating the health effects. Finally, in cases where treatment does not return people to their original health state, these methods will underestimate the benefit of avoiding the illness entirely.

COI studies sometimes include indirect as well as direct costs. These indirect costs usually include lost earnings due to missed market work time, and occasionally include costs associated with lost nonmarket work ( e. g., housekeeping), ( both are included in the Traditional COI and Enhanced COI estimates), and reduced productivity while at work ( which is included in the Enhanced COI). Typically, these costs are estimated using the human capital approach, which ( as discussed in more detail later in this appendix) focuses on the effect of time use on the production of goods and services and ignores other aspects of time use that affect individual well being.

Given these concerns, the COI method is an imperfect substitute that is applied in cases where suitable WTP studies are not available. The following section discusses the available WTP literature and its relevance to the health risks assessed in this report. It also summarizes studies that have explored the relationship between WTP and COI for specific health effects.

K. 3 Review of the Literature on WTP for Morbidity Risk Reductions This analysis uses a variant of the COI approach to value reductions in cryptosporidiosis morbidity risks because of the lack of suitable WTP studies of reasonable quality. EPA conducted several reviews of the valuation literature and found relatively few studies that address morbidity risks4. Many of these studies focus on relatively serious and often chronic conditions such as asthma, chronic bronchitis, or angina; a few consider very minor acute affects such as drowsiness, headache, or eye irritation. In general, these conditions appear significantly dissimilar to the effects of cryptosporidiosis and, hence, do not provide suitable valuation estimates for the purposes of this analysis.

Of particular interest are two inter related studies of nausea ( as well as other minor health symptoms) that were completed by overlapping groups of researchers in 1984 1985 in Chicago and Denver.

° Based on a contingent valuation survey, Berger et al. ( 1987) explored individual WTP to avoid one additional day of nausea. The authors report results only for the 17 individuals sampled who had experienced the symptom, and found a mean value of $ 48 per day ( dollar year not reported). 5 6 Assuming that the estimate is for the year 1985, the year 2000 equivalent is $ 80 per additional day, inflated using the CPI U.

7 See, for example, Chapter 7 of EPA's Guidelines for Preparing Economic Analyses ( USEPA 2000e) and Chapter 4 of EPA's Assessing the Benefits of Drinking Water Regulations ( USEPA 2001a).

8 EPA has used Tolley et al. ( 1986) to value respiratory effects associated with minor restricted activity days associated with air pollution; for these effects, other studies are available that appear to support the Tolley et al. findings. See, for example, the approach applied in EPA's Final Heavy Duty Engine/ Diesel Fuel Rule: Air Quality Estimation, Selected Health and Welfare Effects Methods, and Benefits Results ( USEPA 2000i), pp. 4 32.

9 See Appendix B of EPA's Handbook for Non Cancer Health Effects Valuation ( USEPA 2000h) for a review of these studies.

Economic Analysis for the LT2ESWTR Proposal June 2003 K 4 ° Another contingent valuation study by Tolley et al. ( 1986) also considered nausea, described as a " lingering urge to vomit" with strong distress, but no pain. The mean value for avoiding one additional day of nausea was $ 50 ( dollar year not reported) among the 176 respondents6. Both estimates appear unsuitable for the analysis of cryptosporidiosis morbidity risks in terms of both applicability and quality, based on EPA guidelines for determining whether benefits estimates are suitable for transfer to other contexts7. First, they describe a symptom that is substantially less severe than the suite of symptoms typically associated with cryptosporidiosis, which often involves several days of diarrhea, abdominal cramping, fever, and vomiting, as well as nausea. Second, Berger in particular relies on a small sample that may not be representative of the U. S. population ( or of the subset of this population affected by this rulemaking), and may be best described as a pilot or illustrative study8. Given the more severe symptoms associated with cryptosporidiosis, WTP to avoid cryptosporidiosis is likely to exceed the WTP values for nausea found in these studies.

Due to the lack of suitable WTP estimates, this report instead relies largely on COI estimates from the studies cited in the main text. These studies have the advantage of directly addressing cryptosporidiosis or illnesses that have very similar health effects ( i. e., giardiasis). However, they are likely to underestimate individual WTP for risk reductions. Research on the ratio of WTP to COI estimates suggests that the ratio of these values varies greatly depending on the nature of the health effect, the characteristics of the affected individuals, and the factors included in constructing each estimate. The resulting WTP to COI ratios for the illnesses studied range from about a factor of 2 to as much as a factor of 79 ( in one case); many of the ratios are between 3 and 69. In other words, the COI estimates are typically one third to one sixth of the WTP estimates. Much of this literature focuses on individual ( out of pocket) costs of illness rather than the full costs ( including costs paid by insurers), and considers relatively minor health effects ( where the costs borne by insurers may be minimal). Few of these studies include lost earnings or other indirect costs in the COI estimates, and instead focus largely on medical expenditures.

The approach used to estimate medical costs in constructing the COI estimates used in this report is discussed in detail in Chapter 5 and Appendix L. The remainder of this appendix focuses on the approaches used in this Economic Analysis to value lost time. As discussed below, this approach uses both a traditional approach ( that is, similar to other studies) and an " enhanced" approach, which is a significant departure from the approach typically used to value time losses in the COI literature because it attempts to provide a more complete measure of the effects of lost time on social welfare. 10 Paid care is included in the medical cost component of the analysis and, hence, is not discussed in the section on time losses.

11 This approach implicitly assumes that labor markets are in equilibrium and that there is little or no unemployment ( i. e., workers cannot be replaced).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 5 K. 4 Welfare Effects of Time Losses Due to Illness Much of the research on the value of time losses due to illness focuses on the effects of such losses on the production of goods and services by the affected individuals. In the context of benefit cost analysis, analysts are interested in a more complete measure of the welfare effects of these time losses. As discussed by A. Myrick Freeman III ( 1993) in his seminal work on benefits valuation:

The economic concept of value employed here has its foundation in neoclassical welfare economics. The basic premises of welfare economics are that the purpose of economic activity is to increase the well being of individuals who make up society, and that each individual is the best judge of how well off he or she is in a given situation. Each individual's welfare depends not only on that individual's consumption of private goods and of goods and services produced by the government, but also on the quantities and qualities each receives of nonmarket goods and service flows....

In this context, analysts are concerned with the effect of illness on foregone market production ( paid work), foregone nonmarket production ( e. g., volunteer or household activities), and any additional diminished utility ( or sense of well being) associated with work and nonwork activities. Analysts are also concerned with the impacts on other individuals such as dependent children or unpaid caregivers. 10 In contrast, most of the work on valuing time losses has been completed in the context of estimating the market impacts of illness, focusing on the ill individual. In this context, lost time generally has been measured using the human capital approach, which views individuals as mechanisms of production; i. e., as capital. Under this approach, an individual is valuable to the extent that he or she produces goods or services, and the value of his or her marginal product is equal to the compensation provided11. The analyst is generally not concerned with other ( nonmarket) factors affecting individuals' sense of well being ( except, of course, if they affect market productivity). To again cite Freeman ( 1993):

The human capital approach is fundamentally at odds with the individualistic perspective of welfare economics and the theory of value. By in effect asking what the individual is worth to society, the human capital approach ignores the individual's own well being, preferences, and willingness to pay.

One approach to developing a more complete measure of the value of lost time would be to rely on estimates of individual WTP to avoid the time losses. While the WTP literature includes some studies that address time losses directly or indirectly, these studies are of limited relevance to the types of time losses discussed in this report, as discussed below.

Some WTP studies include explicit information on time losses when eliciting the value of averting particular health effects. For example, Rowe and Chestnut ( 1986) surveyed 90 asthmatic individuals in 1983 to estimate their WTP for a program that would reduce their bad asthma days. The survey elicited 12 Travel cost studies are focused on the costs ( or negative impacts) associated with traveling longer distances. They assume that travel time has some positive effects ( or utility), otherwise time costs would be valued at the full wage rate ( i. e., as a complete loss).

13 See, for example, the approach ap plied in EPA's Final Heavy Duty Engine/ Diesel Fuel Rule: Air Quality Estimation, Selected Health and Welfare Effects Methods, and Benefits Results ( USEPA 2000i).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 6 information on the effects of asthma on work, school, chores, and leisure activities. However, the authors ask the respondents to report their WTP for a program to decrease bad asthma days; an estimate of WTP to avoid time losses is not reported separately.

Researchers interested in valuing the availability of recreational activities also consider time costs in the context of recreational demand, or travel cost, studies. These studies typically value time spent traveling to a recreation site at a fixed fraction of the individual's wage rate, which represents the disutility associated with travel12. The precise fraction of the wage rate used to value travel time costs has ranged from zero to one in published empirical studies. Unfortunately, these studies are focused on a particular use of leisure time, i. e., for travel. The resulting estimates are, therefore, not necessarily applicable to other types of leisure activities.

Another potentially relevant approach is assessing the value of restricted activity days. These days are generally defined as time periods when individuals find that their activities are more limited than normal due to illness or other factors. This concept is frequently applied in the context of assessing health effects associated with air pollution. For example, researchers have linked self reported data on activity restrictions to data on air pollution levels to estimate the effects of this pollution on normal activities. Information on WTP for avoiding these restrictions ( derived from studies of minor respiratory symptoms) is then applied to the estimates of activity restricted days to determine their value13. However, this value will vary depending on the type and severity of the activity limitations, as well as the nature of the health effects experienced. As noted earlier, sparse information is available on WTP to avoid the types of health effects or activity restrictions associated with cryptosporidiosis. In the absence of this information, it is not possible to apply this approach to the health effects considered in this report.

This analysis instead relies on wage and compensation data to estimate opportunity costs to the individual and society, due to the lack of applicable studies that estimate WTP for time losses due to illness. The opportunity cost approach recognizes that, because resources are limited, any decision to use resources for one purpose means that they cannot be used for other purposes. Hence, the value of the resource can be determined based on the value of its next best use. This approach is likely to understate the full value of time losses, since individuals may hold values that exceed the opportunity costs represented by measures of compensation.

The use of wage and compensation data to estimate opportunity costs is consistent with the basic principles of welfare economics and is explored in detail in the labor economics literature. For example, as summarized in the Gold et al. ( 1996) study of " best practices" for cost effectiveness analysis:

The fundamental assumption of this literature is that people will take their opportunity cost into account when allocating their time, choosing to devote it to the activities that produce the greatest utility. They will work an extra hour, for example, if the compensation they receive exceeds the value they place on their time in other activities. 14 For a more detailed and technical discussion of the use of opportunity costs, see Posnett et al. ( 1996).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 7 The application of the opportunity cost approach to estimate the value of lost market ( paid) work time is relatively clear, since compensation can be used to estimate these costs. For other ( unpaid) time spent in nonmarket work or leisure activities, wage data are also used based on the assumption that ( at the margin) the wage represents the opportunity cost of engaging in such activities14. To again cite Gold et al. ( 1996):

The labor leisure trade off, which is at the heart of the theory of labor supply, illustrates the method used to value time which is not spent at work: if there is perfect competition; if workers and employers are perfectly well informed; if the worker has declining marginal utility of leisure time ( i. e., the more time spent away from work, the lower the value of each incremental increase in leisure time) and diminishing marginal utility of income; and if the quantity of labor supplied in the market is continuously variable, then the worker " consumes" leisure time up to the point at which the value of an additional hour of leisure equals the ( hourly) wage that he or she can receive by working.

As indicated by this quote, the use of wage data to estimate opportunity costs is based on a number of simplifying assumptions regarding the operations of labor markets and the process by which individuals choose among different activities. In addition to the limitations cited above, this approach assumes that an individual has complete flexibility in choosing the number of hours he or she spends in paid work, whereas in reality employers may be willing to provide jobs only for set increments of time ( e. g., 40 hours per week). In its simplest form, it also does not take into account a number of complexities related to how individuals are actually compensated, such as the difference between hourly and salaried employees and variation in how benefits are determined.

In addition, relying on wage data for valuing lost time presents difficulties in the case of individuals for whom these data are not available, such as children, the unemployed who are seeking employment, and those out of the labor market. It also can be difficult to define a value when there are trade offs between two uncompensated activities. Perhaps most important, the use of wage rates may understate the total utility associated with the activity even in the case of paid work, because individuals may derive intrinsic pleasure from the activity above and beyond the income they receive.

The use of compensation data to value time losses and its limitations are explored in detail in the following sections of this appendix. The following section describes the compensation measures used for each time use category ( market work, nonmarket work, leisure, and sleep), the next section then considers issues related to those populations for whom wage data are not available.

K. 5 Approach for Each Time Loss Category This appendix discusses four types of normal time use:

° Market ( paid) work time ° Nonmarket ( unpaid) work time 15 Paid care is covered in the medical cost estimates rather than in the time loss estimates.

Economic Analysis for the LT2ESWTR Proposal June 2003 K 8 ° Leisure time ° Sleep time These time loss categories are briefly defined in Exhibit K. 1 below.

Exhibit K. 1 Definitions of Time Loss Categories Category Definition Market Work Time Time that an individual spends engaged in productive activity in exchange for a salary or wage at a price set in the labor market.

Nonmarket Work Time Time spent on productive work without monetary compensation in the home ( e. g., housework) or outside the home ( e. g., volunteer work).

Leisure Time Time spent engaged in activities other than market work, nonmarket work, or sleep.

Sleep Time Time spent sleeping.

As discussed in detail in the main text of this report, cryptosporidiosis often involves several days of diarrhea, abdominal cramping, fever, and vomiting, as well as nausea. Many characteristics of this illness are of particular importance when considering the approach to valuing time losses in each of these four categories. Specifically, the valuation approach needs to accomplish the following:

° Consider time losses associated with morbidity, not mortality because other, well established valuation methods are applied to mortality risks.

° Apply to acute, not chronic, illnesses, that generally result in a temporary rather than permanent change in activities.

° Address illnesses that may lead individuals to both spend fewer hours engaged in normal activities, and have a lower level of productivity or utility when they continue normal activities.

° Consider effects that may occur throughout the day, potentially affecting all types of time usage.

° Apply to individuals of all ages that may be affected by this illness, including the very old and the very young.

° Reflect the need of some ill individuals for the attention of a caretaker ( i. e., a friend or family member, not a paid health care provider) for a portion of the time while they are ill. 15 16 There are a number of simplifying assumptions inherent in the application of this approach that may lead it to further under or over state the value of time in its preferred use, related to factors such as the functioning of the labor market, the treatment of individuals who are not labor force participants, and the use of average or median, rather than marginal, earnings data. It is unclear whether, in total, these practical limitations serve to increase or decrease the bias that results from the sources discussed in this paragraph.

Economic Analysis for the LT2ESWTR Proposal June 2003 K 9 Because empirical research on the value of time is limited, this analysis relies primarily on data on compensation as a proxy for the value of lost time. The specific approach for each of the four time loss categories is summarized in Exhibit K. 2.

Exhibit K. 2 Overview of Valuation Approach Time Loss Category Approach for Estimate of Value Enhanced COI Traditional COI Market work time Gross ( pre tax) wage plus benefits, reflecting both the wages received by the individual and the value of his or her product to the employer and society Nonmarket work time Net ( post tax) wage, based on the opportunity costs to the individual Half the net ( post tax) wage, based on the replacement cost of labor Leisure time Net ( post tax) wage, based on the opportunity costs to the individual Not included Sleep time Zero, due to lack of information on the dollar value In this analysis, lost market work time is valued at the pre tax wage rate plus benefits. Using the Enhanced COI estimate, lost nonmarket work and leisure time are valued at the post tax wage rate. The Traditional COI estimate values nonmarket work time at half the net post tax wage rate, and does not include a value for leisure time. Lost sleep time is conservatively valued at " zero." Losses are assessed for unpaid caretakers whose normal activities are affected by illness as well as for the ill individual.

In the Enhanced COI estimate, these values are applied to both complete losses of time ( time spent in illness related activities rather than normal activities), as well as to partial losses ( time spent in normal activities that are less productive or pleasurable than in the absence of illness). In the latter case, however, the dollar value of the loss is prorated to reflect the fact that the individual does not completely lose the productivity or utility associated with the activity. In the Traditional COI estimate, these values are applied only to complete losses of time ( time spent in illness related activities rather than normal activities), because less productive time is not included.

Both of these approaches are likely to understate the utility of time spent in its preferred use ( i. e., of normal activities in the absence of illness) for variety of reasons16. Individuals may place a value on market work that exceeds total compensation because of the effect of working on their sense of wellbeing For nonmarket work and leisure, the value of the activity to the individual may exceed the opportunity cost for similar reasons. In addition, nonmarket work and other activities can provide benefits to other members of society that are not reflected in the individual wage rate. Finally, neither approach includes the value of sleep. 17 Embedded in this approach are a number of assumptions ( discussed earlier) regarding the operations of the labor market and the factors that influence individual choice. In addition, the actual effect of missed work time will vary depending on how individuals are compensated; e. g., on whether they are salaried or hourly employees and on whether they receive sick leave or disability payments. For example, if the individual has access to paid sick leave, a marginal loss of work time ( within certain limits) will not result in an immediate loss of income. However, a loss will accrue to the employer, who must pay wages without the benefit of the worker's productivity. The individual also has the ability to save this sick leave for another time.

18 A number of COI studies use lost earnings to estimate indirect costs. For example, the total compensation approach is used in Buzby et al. ( 1996), Rice et al. ( 1992), and Waitzman et al. ( 1996).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 10 However, it is unclear whether the use of these estimates over or under state the disutility, or loss, associated with illness; i. e., the loss associated with spending time in illness related, rather than normal, activities. In some cases, it seems reasonable to assume that the illness related activity represents a complete loss of utility ( e. g., time spent coping with a bout of diarrhea rather than working). For these losses, the approaches used in this report will understate the value of the loss, as discussed in the prior paragraph. In other cases, the illness related activity may have some utility ( e. g., time spent watching TV or reading instead of working) that is less than the utility of the preferred activity, but greater than " zero." Even in this case, there would likely be some offsetting utility losses from the discomfort and stress of being sick. In these cases, the actual amount of the loss could conceivably be less than the estimates used in this analysis. The basis for these approaches is described in more detail below.

K. 5.1 Lost Market Work Time In a social welfare context, the value of marginal changes in market work time has two components: ( 1) the value of the time loss to that individual, and ( 2) any additional value to the rest of society. In this analysis, lost market work is valued at the median gross ( pre tax) wage rate plus benefits, also referred to as total compensation or employer's costs17. This approach is most representative of the full social impact of lost work time because it incorporates both the loss to the individual in terms of lost income and the loss to society in terms of reduced tax revenue or decreased production of goods and services.

This approach recognizes that, when an individual misses work or is less productive due to illness, he or she loses the associated utility. This loss is, in part, measured by income, which the individual can trade for goods and services. However, income is an incomplete measure of value, because the individual may derive utility from working that exceeds post tax wages or take home pay. Hence the post tax wage rates provide a lower bound estimate of the value of paid work time from the individual perspective.

This approach also recognizes that the employer ( and society) loses the value of the individual's productivity, and that this value exceeds the value of the post tax wages received by the employee. From the employer's perspective, the value of the individual's productivity is equal at minimum to his or her total compensation ( pre tax wages plus benefits). This perspective is similar to that of the human capital approach, which assumes that an employer would not pay more to an employee, in salary plus benefits, than that employee is worth to the company ( i. e., the value of the employee's marginal product) and hence to society18. Some of this value is reflected in the employee's take home pay, the remainder 19 For a recent discussion that indicates that illness related losses of work time can substantially exceed the wage rate, see: Pauley et al. ( 2002).

20 Hartunian et al. ( 1981) and others argue that average wages are a reasonable approximation of the value of lost production in most industrialized countries.

21 A number of groups have been working on approaches for measuring and categorizing different types of time usage, as summarized in National Research Council ( 2000).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 11 accrues in terms of taxes paid and reflects the value of product created above and beyond what is reflected in pre tax wages. 19 Ideally, the estimates used in this analysis would reflect the value of marginal changes in work time, since the impacts of cryptosporidiosis related morbidity are likely to be acute and temporary. In other words, affected individuals may work fewer hours or be less productive while working for a limited period of time, but are not likely to change employment or become unemployed as a result of the illness. Empirically, analysts generally use estimates of average or median compensation as a proxy for marginal rates due to difficulties inherent in determining the marginal rates relevant to the particular impact under consideration20. Data on average and median U. S. compensation rates are easily accessible and frequently updated in a number of publications.

K. 5.2 Lost Nonmarket Work, Leisure Time, and Sleep Time In this analysis, two alternative measures are used to value nonmarket work time and leisure time. In the Enhanced COI estimate, net ( post tax) wages are used to estimate the value of both lost nonmarket work and leisure time. In the Traditional COI estimate, the value of lost nonmarket work time is half the post tax wage, and no value is assigned to leisure time.

While the distinctions between market work and sleep are relatively easy to distinguish, the line between nonmarket work and leisure is often difficult to draw21. In general parlance, nonmarket work refers to activities that are undertaken primarily because they are productive, whereas leisure refers to activities that are undertaken primarily for the pleasure of the individual. However, this distinction is hard to apply in practice. Some nonmarket tasks seem clearly productive, such as doing the laundry or vacuuming, but individuals may also derive pleasure from these tasks. Other activities, such as childcare or gardening, encompass aspects of both productive work and of leisure.

Nonmarket Work One of the two alternative measures used in this analysis to value nonmarket work time is the net ( post tax) wages, which are used to estimate the value of lost nonmarket work in the Enhanced COI estimate. If illness affects an individual's ability to engage in nonmarket work, he or she loses the value of his or her own productivity. Presumably, that individual chooses to engage in nonmarket rather than market work because, at the margin, the utility ( productivity plus any additional enjoyment) from performing nonmarket work was greater than the utility ( as represented by income) that he or she would 22 For more detailed surveys of different approaches for valuing nonmarket work time, see Goldschmidt Clermont ( 1982) and Gronau ( 1986).

23 Benefits are conservatively left out of this calculation, under that assumption that marginal changes in the number of hours worked would not affect the total amount of benefits received.

24 For example, a series of studies funded by the Australian Bureau of Statistics focus on adding the value of nonmarket work to national accounts and use the replacement cost method for this purpose. See, for example, Trewin ( October 2000).

25 As cited in Goldschmidt Clermont ( 1982), p. 4.

26 Time use researchers have been attempting to develop classification schemes that can be used internationally for these types of studies. Many refer to four general categories: contracted time ( paid work plus education and training), committed time ( unpaid work, including housework, shopping, and volunteer work), necessary time ( personal care, including sleep), and free time ( religious, cultural and civic participation, social time, sports, hobbies, and mass media). ( See, for example, Ministry of Women's Affairs, Statistics New Zealand ( 1999).) These classification schemes differ somewhat from the categories used in the report, and require more detailed data on the types of time uses affected than are available for this analysis.

Economic Analysis for the LT2ESWTR Proposal June 2003 K 12 have gained from market work22. Therefore, that individual must value a marginal hour of his or her nonmarket work time at a rate at least equal to the marginal net wage per hour he or she could have earned in the job market23. It is not unreasonable to assume that on average ( across all these individuals), the opportunity costs for these individuals would be similar to the opportunity costs for employed individuals. To a large extent, these individuals may choose to be out of the labor market because they value their time at a rate that exceeds the compensation they would receive by working. More research would be needed to confirm the extent to which this assumption is supported by detailed studies of the factors that affect decision making by these groups. As before, this approach involves a number of simplifying assumptions regarding the functioning of labor markets and the choices faced by individuals, but provides one reasonable proxy for how this time is valued. This is the basis used in the Enhanced COI estimate.

The Traditional COI estimate has a different basis. The approach advocated most frequently in the literature to distinguish between market and nonmarket work, particularly in the context of adjusting national accounts to include unpaid work, relies on estimates of replacement costs rather than estimates of opportunity costs and is known as the " third person" or " market replacement" criterion. This approach is used largely because of the emphasis of these studies on measuring productivity rather than utility24. Under the human capital approach, time spent engaged in nonmarket labor activities is considered productive, due to the fact that activities such as childcare, cooking, and general home maintenance   if not performed by a member of the household   could be performed by a professional in return for compensation ( i. e., as market labor). As defined by Reid ( 1934), " If an activity is of such a character that it might be delegated to a paid worker, then that activity shall be deemed productive." 25 Tasks that can only be performed by the individual himself ( or herself) are included in the leisure category. Therefore, gardening and childcare would be viewed as nonmarket work, whereas watching television would be considered a leisure activity. 26 27 A pioneering example of this approach is presented in Rice ( 1966). A more recent example, which uses data on the value of housekeeping services based on Current Population Survey data from the Bureau of Labor statistics, is Ray et al. ( 1998).

28 A pioneering example of this approach is Rice 1966; a more recent example is Thamer et al. ( 1998).

29 One early demonstration of this market value approach is Cooper et al. ( 1976). A more recent approach is provided in Hoffman et al. ( 1976), which uses values based on research reported in Douglas et al. ( 1990). Another recent example is Ray et al. ( 1998).

30 Trewin ( 2000, p. 24) notes that the replacement cost approach "... is based on the key assumption that household members and market replacements are equally productive in their work activities.... In practice it is difficult to identify exact matches between household work activities and occupations...."

31 See, for example, Trewin ( 2000).

Economic Analysis for the LT2ESWTR Proposal June 2003 K 13 In some studies, housekeeper wage rates are used to value the productivity of nonmarket labor27. This is the measure used to value lost unpaid work time for the Traditional COI. The value used is half of the after tax wage. The use of 50 percent of the wage rate is consistent with a practice common in the human capital literature of valuing nonmarket work time at the market rate for domestic workers28. Because this approach may undervalue the true productivity of this labor due to the wide range of activities undertaken in addition to housekeeping ( e. g., cooking, childcare, and home repairs), other studies use market value composite rates. This alternative approach would involve developing a composite of the wage rates paid to individuals employed in the labor market to perform the various activities typically associated with nonmarket labor ( e. g., cooks, daycare providers, maids, nannies, and handymen). 29,30 In some applications, this approach has been expanded to also include volunteer work31.