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{{#Wiki_filter:Project Records Management Site Specific MACCS2 Input Data Title: Site Specific MACCS2 Input Data for Indian Point Energy Center, Rev. 1 Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the revised site specific MACCS2 input data report and appendices for Indian Point Energy Center. The revisions incorporate the revised annual meteorological files (2000-2004) and the modified VNFRM. Document Review & Acceptance Preparer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapter 7, Appendices D and E 12/01/09 Project Manager / Date: 12/01/09 Project Records Management IPEC MACCS2 Meteorological Input Files Title: MACCS2 Meteorological Data Input Files Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the ASCII text file revision for the MACCS2 meteorological input files. This package includes the following: 1. METI00.inp - The 2000 ascii meteorological text file. 2. METI01.inp - The 2001 ascii meteorological text file. 3. METI02.inp - The 2002 ascii meteorological text file. 4. METI03.inp - The 2003 ascii meteorological text file. | {{#Wiki_filter:Project Records Management Site Specific MACCS2 Input Data Title: Site Specific MACCS2 Input Data for Indian Point Energy Center, Rev. 1 Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the revised site specific MACCS2 input data report and appendices for Indian Point Energy Center. The revisions incorporate the revised annual meteorological files (2000-2004) and the modified VNFRM. Document Review & Acceptance Preparer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapter 7, Appendices D and E 12/01/09 Project Manager / Date: 12/01/09 Project Records Management IPEC MACCS2 Meteorological Input Files Title: MACCS2 Meteorological Data Input Files Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the ASCII text file revision for the MACCS2 meteorological input files. This package includes the following: 1. METI00.inp - The 2000 ascii meteorological text file. 2. METI01.inp - The 2001 ascii meteorological text file. 3. METI02.inp - The 2002 ascii meteorological text file. 4. METI03.inp - The 2003 ascii meteorological text file. | ||
: 5. METI04.inp - The 2004 ascii meteorological text file. | : 5. METI04.inp - The 2004 ascii meteorological text file. | ||
Document Review & Acceptance Preparer / Date: 11/12/09 11/12/09 Technical Reviewers / Date: | Document Review & Acceptance Preparer / Date: 11/12/09 11/12/09 Technical Reviewers / Date: | ||
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The Severe Accident Mitigation Alternatives (SAMAs) for the Indian Point Energy Center (IPEC) uses the MELCOR Accident Consequence Code System, Version 2 (MACCS2), for estimating the health and economic consequences of severe accidents. Should a severe reactor accident occur, downwind populations, buildings, and crops would be exposed to radioactive materials. MACCS2 estimates the range and probability of the health effects and the economic costs and losses that would result from such an accident. Data used in this SAMA were imported and organized using ESRI ArcGIS 9.1 Geographic Information System (GIS) (Reference 1.1). ArcGIS 9.1 was used for all geographic processing, overlays, and map production occurred within the ArcGIS 9.1 framework. MACCS2 requires data in sixteen equiangular sectors centered on IPEC, extending to 50-mile radius. The sector grid is divided into spatial elements by superimposing fifteen circles of increasing diameter over sixteen sectors, for a total of 240 spatial elements. These circles are 0.2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, and 50 miles from IPEC. For the purposes of this report, the IPEC center point was determined as the center of the super-heater stack. Census 2000 Line Data via ESRI (Reference 1.2) for fourteen counties in New York, ten counties in New Jersey, three counties in Connec ticut, and one county in Pennsylvania within the IPEC 50-mile buffer were used as base map layers (Figure 1.1, Table 1.1). | The Severe Accident Mitigation Alternatives (SAMAs) for the Indian Point Energy Center (IPEC) uses the MELCOR Accident Consequence Code System, Version 2 (MACCS2), for estimating the health and economic consequences of severe accidents. Should a severe reactor accident occur, downwind populations, buildings, and crops would be exposed to radioactive materials. MACCS2 estimates the range and probability of the health effects and the economic costs and losses that would result from such an accident. Data used in this SAMA were imported and organized using ESRI ArcGIS 9.1 Geographic Information System (GIS) (Reference 1.1). ArcGIS 9.1 was used for all geographic processing, overlays, and map production occurred within the ArcGIS 9.1 framework. MACCS2 requires data in sixteen equiangular sectors centered on IPEC, extending to 50-mile radius. The sector grid is divided into spatial elements by superimposing fifteen circles of increasing diameter over sixteen sectors, for a total of 240 spatial elements. These circles are 0.2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, and 50 miles from IPEC. For the purposes of this report, the IPEC center point was determined as the center of the super-heater stack. Census 2000 Line Data via ESRI (Reference 1.2) for fourteen counties in New York, ten counties in New Jersey, three counties in Connec ticut, and one county in Pennsylvania within the IPEC 50-mile buffer were used as base map layers (Figure 1.1, Table 1.1). | ||
Data input into MA CCS2 code include: | Data input into MA CCS2 code include: | ||
: 1. Population in 2035-at the end of the license renewal period for 240 spatial elements. | : 1. Population in 2035-at the end of the license renewal period for 240 spatial elements. | ||
: 2. Land Fraction-proportion of each of the 240 spatial elements that is land, not water. 3. Watershed Index-indication of whether spatial element is drained by rivers or is a lake/water body. | : 2. Land Fraction-proportion of each of the 240 spatial elements that is land, not water. 3. Watershed Index-indication of whether spatial element is drained by rivers or is a lake/water body. | ||
: 4. Regional Economic Data-estimation of amount of farming and economic activities. | : 4. Regional Economic Data-estimation of amount of farming and economic activities. | ||
: 5. Agricultural Data-crop types, growing season, and percent of farmland for each crop. | : 5. Agricultural Data-crop types, growing season, and percent of farmland for each crop. | ||
Revision 1 December 1, 2009 1-2 Figure 1.1 US counties within 50-miles of IPEC. | Revision 1 December 1, 2009 1-2 Figure 1.1 US counties within 50-miles of IPEC. | ||
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*This economic region incorporates non-farm values from Bronx, Hudson, Queens, and New York counties in order to obtain a conservative value. | *This economic region incorporates non-farm values from Bronx, Hudson, Queens, and New York counties in order to obtain a conservative value. | ||
5.2.2 ASFP - Total Annual Farm Sales US Census of Agriculture Item Land in farms (acres) was downloaded and converted to hectares. US Census of Agriculture Item Market value of agricultural products sold ($1,000) was downloaded for each county, multiplied by 1000, and divided by land in farms (calculated above) to obtain ASFP (dollars/h ectare) (Table 5.2). One exception was Rockland County, which the US Census of Agriculture did not report total farmland acres due to privacy concerns. Total farmland acres for Rockland County were estimated by multiplying total county area by Farms and land in farms\Approximate land area\Proportion in farms (percent, 2002). | 5.2.2 ASFP - Total Annual Farm Sales US Census of Agriculture Item Land in farms (acres) was downloaded and converted to hectares. US Census of Agriculture Item Market value of agricultural products sold ($1,000) was downloaded for each county, multiplied by 1000, and divided by land in farms (calculated above) to obtain ASFP (dollars/h ectare) (Table 5.2). One exception was Rockland County, which the US Census of Agriculture did not report total farmland acres due to privacy concerns. Total farmland acres for Rockland County were estimated by multiplying total county area by Farms and land in farms\Approximate land area\Proportion in farms (percent, 2002). | ||
Revision 1 December 1, 2009 5-5 5.2.3 DPF - Fraction of Farm Sales Resulting from Dairy Production US Census of Agriculture Item Dairy products sold ($1,000) was downloaded for each county and divided by Census of Agriculture Item Market value of agricultural products sold | Revision 1 December 1, 2009 5-5 5.2.3 DPF - Fraction of Farm Sales Resulting from Dairy Production US Census of Agriculture Item Dairy products sold ($1,000) was downloaded for each county and divided by Census of Agriculture Item Market value of agricultural products sold | ||
($1,000) (Table 5.2). | ($1,000) (Table 5.2). | ||
5.2.4 VFRM - Farmland Property Value US Census of Agriculture Item Estimated market value of land and buildings: average per acre (dollars, 2002) and was downloaded for each county and converted to dollars/hectare (Table 5.2). US Census of Agriculture Item Estimated market value of all machinery and equipment ($1,000, 2002) was downloaded for each county, divided by hectares in farms (calculated in Section 5.2.1), and summed with market value of land and buildings (dollars/hectare) to obtain VFRM (dollars/hectare) (Table 5.2). | 5.2.4 VFRM - Farmland Property Value US Census of Agriculture Item Estimated market value of land and buildings: average per acre (dollars, 2002) and was downloaded for each county and converted to dollars/hectare (Table 5.2). US Census of Agriculture Item Estimated market value of all machinery and equipment ($1,000, 2002) was downloaded for each county, divided by hectares in farms (calculated in Section 5.2.1), and summed with market value of land and buildings (dollars/hectare) to obtain VFRM (dollars/hectare) (Table 5.2). | ||
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Pasture Stored Forage Grain Legumes & Nuts Leafy Green Vegetables Roots & Tubers Other FoodVarious grasses Alfalfa Wheat Soybeans Lettuce Potatoes Apples Clover Oats Peanuts Cabbage Carrots Grapes Sorghum Barley Snap beans Broccoli Beets Oranges Corn (incl. Sweet Corn) Dried beans Spinach Sugar Grapefruit Sorghum Peas Celery Onion Lemon Nuts Cauliflower Tomatoes Greens Cucumbers Peppers Acres for each Agriculture Census were downloaded for each county and were summed into seven crop categories. For the purposes of determining the fraction of farmland devoted to each crop type, US Census of Agriculture Item Land in farms (acres) was used as the total area of farmland. It should be noted that summing the percentage of farmland devoted to each of the seven crop categories does not necessarily add up to one. This is because significant farmland acres can be devoted to woodlands, idle cropland, cropland used for cover crops (not harvested and not pasture), cropland on which crops failed, cropland in summer fallow, and farmland in houses, ponds, and roads. Each crop category was weighted by the percentage of farmland each Revision 1 December 1, 2009 6-2 county has across the entire IPEC 50-mile area (Tab le 6.2). Final weighted average percentage of farmland devoted to each crop category is shown in Table 6.2. Table 6.2 Percent farmland devoted to crop categories. | Pasture Stored Forage Grain Legumes & Nuts Leafy Green Vegetables Roots & Tubers Other FoodVarious grasses Alfalfa Wheat Soybeans Lettuce Potatoes Apples Clover Oats Peanuts Cabbage Carrots Grapes Sorghum Barley Snap beans Broccoli Beets Oranges Corn (incl. Sweet Corn) Dried beans Spinach Sugar Grapefruit Sorghum Peas Celery Onion Lemon Nuts Cauliflower Tomatoes Greens Cucumbers Peppers Acres for each Agriculture Census were downloaded for each county and were summed into seven crop categories. For the purposes of determining the fraction of farmland devoted to each crop type, US Census of Agriculture Item Land in farms (acres) was used as the total area of farmland. It should be noted that summing the percentage of farmland devoted to each of the seven crop categories does not necessarily add up to one. This is because significant farmland acres can be devoted to woodlands, idle cropland, cropland used for cover crops (not harvested and not pasture), cropland on which crops failed, cropland in summer fallow, and farmland in houses, ponds, and roads. Each crop category was weighted by the percentage of farmland each Revision 1 December 1, 2009 6-2 county has across the entire IPEC 50-mile area (Tab le 6.2). Final weighted average percentage of farmland devoted to each crop category is shown in Table 6.2. Table 6.2 Percent farmland devoted to crop categories. | ||
County Pasture Stored Forage Grain Legume & Nuts Leafy Vegetables Roots & Tubers Other Food % of Area Farmland Connecticut Fairfield 0.22 0.55 0.05 0.00 0.00 0.00 0.09 2.8 Litchfield 1.07 4.15 0.34 0.00 0.01 0.01 0.08 8.48 New Haven 0.45 1.52 0.15 0.02 0.06 0.00 0.37 1.87 New Jersey Bergen 0.00 0.04 0.00 0.00 0.01 0.00 0.10 0.28 Essex 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.03 Hudson 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Middlesex 0.29 0.62 2.94 3.22 0.08 0.01 0.32 0.09 Morris 0.41 1.26 0.60 0.00 0.01 0.00 0.20 3.04 Passaic 0.09 0.00 0.03 0.00 0.01 0.00 0.04 0.33 Somerset 1.78 4.37 3.12 0.85 0.00 0.00 0.11 0.36 Sussex 2.01 6.35 0.73 0.04 0.01 0.01 0.24 15.48 Union 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.04 Warren 1.63 6.58 9.18 2.25 0.15 0.01 0.35 0.08 New York Bronx 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Dutchess 2.43 6.06 1.69 0.00 0.02 0.01 0.25 21.79 Kings 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Nassau 0.07 0.12 0.00 0.00 0.00 0.00 0.01 0.24 New York 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Orange 1.86 6.66 0.66 0.01 0.16 0.72 0.46 23.57 Putnam 0.20 0.64 0.00 0.00 0.00 0.00 0.00 1.47 Queens 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Richmond 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 Rockland 0.03 0.00 0.02 0.00 0.01 0.01 0.15 0.27 Suffolk 0.16 0.16 0.76 0.06 0.20 0.56 0.87 1.59 Sullivan 1.16 3.95 0.07 0.00 0.00 0.01 0.04 5.04 Ulster 1.31 2.44 0.63 0.00 0.02 0.00 1.09 10.58 Westchester 0.46 0.21 0.04 0.00 0.00 0.00 0.10 2.16 Pennsylvania Pike 0.03 0.37 0.00 0.00 0.00 0.00 0.00 0.41 Weighted Average 1.62 4.8 0.79 0.02 0.05 0.18 0.36 Growing season dates were the recommended MACCS2 values (Reference 4.1). Final agricultural input data for crop types, growing season, and fraction of farmland devoted to each crop are included in Appendix C. | County Pasture Stored Forage Grain Legume & Nuts Leafy Vegetables Roots & Tubers Other Food % of Area Farmland Connecticut Fairfield 0.22 0.55 0.05 0.00 0.00 0.00 0.09 2.8 Litchfield 1.07 4.15 0.34 0.00 0.01 0.01 0.08 8.48 New Haven 0.45 1.52 0.15 0.02 0.06 0.00 0.37 1.87 New Jersey Bergen 0.00 0.04 0.00 0.00 0.01 0.00 0.10 0.28 Essex 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.03 Hudson 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Middlesex 0.29 0.62 2.94 3.22 0.08 0.01 0.32 0.09 Morris 0.41 1.26 0.60 0.00 0.01 0.00 0.20 3.04 Passaic 0.09 0.00 0.03 0.00 0.01 0.00 0.04 0.33 Somerset 1.78 4.37 3.12 0.85 0.00 0.00 0.11 0.36 Sussex 2.01 6.35 0.73 0.04 0.01 0.01 0.24 15.48 Union 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.04 Warren 1.63 6.58 9.18 2.25 0.15 0.01 0.35 0.08 New York Bronx 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Dutchess 2.43 6.06 1.69 0.00 0.02 0.01 0.25 21.79 Kings 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Nassau 0.07 0.12 0.00 0.00 0.00 0.00 0.01 0.24 New York 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Orange 1.86 6.66 0.66 0.01 0.16 0.72 0.46 23.57 Putnam 0.20 0.64 0.00 0.00 0.00 0.00 0.00 1.47 Queens 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Richmond 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 Rockland 0.03 0.00 0.02 0.00 0.01 0.01 0.15 0.27 Suffolk 0.16 0.16 0.76 0.06 0.20 0.56 0.87 1.59 Sullivan 1.16 3.95 0.07 0.00 0.00 0.01 0.04 5.04 Ulster 1.31 2.44 0.63 0.00 0.02 0.00 1.09 10.58 Westchester 0.46 0.21 0.04 0.00 0.00 0.00 0.10 2.16 Pennsylvania Pike 0.03 0.37 0.00 0.00 0.00 0.00 0.00 0.41 Weighted Average 1.62 4.8 0.79 0.02 0.05 0.18 0.36 Growing season dates were the recommended MACCS2 values (Reference 4.1). Final agricultural input data for crop types, growing season, and fraction of farmland devoted to each crop are included in Appendix C. | ||
Revision 1 December 1, 2009 7-1 7.0 METEOROLOGICAL DATA The MACCS2 model requires meteorological data for wind speed, wind direction, atmospheric stability, accumulated precipitation, and atmospheric mixing heights (Reference 7.1). The required data were obtained from the IPEC meteorological monitoring system and regional National Weather Service stations 7.1 Site Specific Data Site specific meteorological data included 43,848 (two leap years) consecutive hourly values of wind speed, wind direction, and delta temperature recorded at the IPEC meteorological tower from January 2000 to December 2004. IPEC meteorological monitoring system includes both primary and backup systems. Parameters measured on the primary tower system include the following: | Revision 1 December 1, 2009 7-1 7.0 METEOROLOGICAL DATA The MACCS2 model requires meteorological data for wind speed, wind direction, atmospheric stability, accumulated precipitation, and atmospheric mixing heights (Reference 7.1). The required data were obtained from the IPEC meteorological monitoring system and regional National Weather Service stations 7.1 Site Specific Data Site specific meteorological data included 43,848 (two leap years) consecutive hourly values of wind speed, wind direction, and delta temperature recorded at the IPEC meteorological tower from January 2000 to December 2004. IPEC meteorological monitoring system includes both primary and backup systems. Parameters measured on the primary tower system include the following: | ||
: 1. Wind speed at 10, 60, and 122-meter elevations (mph), 2. Wind direction at 10, 60, and 122-meter elevations (degree from), 3. Temperature at 10-meter elevation (degree F), 4. Dew point at 10-meter elevation (degree F), 5. Delta temperature between the 10 and 60-meter (lower) elevations and between the 10 and 122-meter (upper) el evations (degree F), and | : 1. Wind speed at 10, 60, and 122-meter elevations (mph), 2. Wind direction at 10, 60, and 122-meter elevations (degree from), 3. Temperature at 10-meter elevation (degree F), 4. Dew point at 10-meter elevation (degree F), 5. Delta temperature between the 10 and 60-meter (lower) elevations and between the 10 and 122-meter (upper) el evations (degree F), and | ||
: 6. Precipitation (inches) at ground level (inches). | : 6. Precipitation (inches) at ground level (inches). | ||
The primary meteorological system was the data source for the MACCS2 input file. Based on a review of annual meteorological data collected at the site between 1995 and 2004, data from calendar years 2000 through 2004 were developed into individual yearly input files for the MACCS2 program. These meteorological files were considered to be the most recent data set available and reflected the meteorological conditions at the site. Over the five year period there was a successful capture rate of over 99% and missing data were replaced using approved data substitution methods. These methods include substitution of missing data by averaging valid data before and after the data gap, interpolation of before and after valid data values, and substitution of valid data collected from other elevations on the meteorological tower (see Appendix E). The Revision 1 December 1, 2009 7-2 meteorological raw data were provided by IPEC in text format files. An example of a meteorological data file is shown in Table 7.1. | The primary meteorological system was the data source for the MACCS2 input file. Based on a review of annual meteorological data collected at the site between 1995 and 2004, data from calendar years 2000 through 2004 were developed into individual yearly input files for the MACCS2 program. These meteorological files were considered to be the most recent data set available and reflected the meteorological conditions at the site. Over the five year period there was a successful capture rate of over 99% and missing data were replaced using approved data substitution methods. These methods include substitution of missing data by averaging valid data before and after the data gap, interpolation of before and after valid data values, and substitution of valid data collected from other elevations on the meteorological tower (see Appendix E). The Revision 1 December 1, 2009 7-2 meteorological raw data were provided by IPEC in text format files. An example of a meteorological data file is shown in Table 7.1. | ||
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===1.1 Copyright=== | ===1.1 Copyright=== | ||
© 2005 ESRI. All rights reserved. ArcGIS is a trademark, registered trademark, or service mark of ESRI in the US, the European Community, or certain other jurisdictions. www.esri.com. 1.2 Census 2000 TIGER/Line Shapefiles for Connecticut, New Jersey, New York and Pennsylvania. [online] ESRI ArcData. Available: http://arcdata.esri.com/data/tiger2000/tiger_county.cfm?sfips=36 [accessed May 12, 2005]. 2.1 Brown, W. Baseline Population Projections NYsis Projects SEP02. [online] New York Statistical Information System. Available: http://www.nysis.cornell.edu/data.html | © 2005 ESRI. All rights reserved. ArcGIS is a trademark, registered trademark, or service mark of ESRI in the US, the European Community, or certain other jurisdictions. www.esri.com. 1.2 Census 2000 TIGER/Line Shapefiles for Connecticut, New Jersey, New York and Pennsylvania. [online] ESRI ArcData. Available: http://arcdata.esri.com/data/tiger2000/tiger_county.cfm?sfips=36 [accessed May 12, 2005]. 2.1 Brown, W. Baseline Population Projections NYsis Projects SEP02. [online] New York Statistical Information System. Available: http://www.nysis.cornell.edu/data.html | ||
[accessed April 4, 2006]. 2.2 New Jersey Population Projections: 1990-2025. [online]. New Jersey Department of Labor and Workforce Development. Available: | |||
http://www.wnjpin.net/OneStopCareerCenter/LaborMarketInformation/lmi03 | http://www.wnjpin.net/OneStopCareerCenter/LaborMarketInformation/lmi03 | ||
[accessed April 4, 2006]. 2.3 Population Projections for Connecticut M unicipalities: 1990-2020. [online] Connecticut State Data Center (SDC). Available: http://www.opm.state. | |||
ct.us/pdpd3/data/sdc.htm | ct.us/pdpd3/data/sdc.htm | ||
[accessed April 4, 2006]. 2.4 Population Projections for Pennsylvania: | |||
1990-2020. [online] Pennsylvania State Data Center. Available: | 1990-2020. [online] Pennsylvania State Data Center. Available: | ||
http://pasdc.hbg.psu.edu/pasdc/Data_&_Information/Data/231a.html | http://pasdc.hbg.psu.edu/pasdc/Data_&_Information/Data/231a.html | ||
[accessed April 4, 2006]. 2.5 Annual population Estimates 2000-2005, all counties: [online] U.S. Census Bureau. | |||
Available: http://quickfacts.census.gov/qfd/ | Available: http://quickfacts.census.gov/qfd/ | ||
[accessed May 31, 2006]. 2.6 Barbara Cieplak Marketing Director, Connecticut for commission on Culture and Tourism - Personal Communication 2.7 2005 A Comprehensive Understanding of the Economic Contribution of Travel and Tourism in the State of New Jersey. [online] Department of New Jersey Tourism. | |||
Available: | Available: | ||
http://www.nj.gov/travel/ [accessed March 22, 2006]. 2.8 NYC Statistics. [online] NYC & Company. Available: | http://www.nj.gov/travel/ [accessed March 22, 2006]. 2.8 NYC Statistics. [online] NYC & Company. Available: | ||
http://www.nycvisit.com | http://www.nycvisit.com | ||
[accessed March 22, 2006]. 2.9 Robert Morin. New York State Tourism Department - Personal Communication 2.10 2003 Pennsylvania Travel Profile. [online] Pennsylvania Tourism Office: Experience Pennsylvania Available: http://media.experiencepa.com/default.aspx?site=ExperiencePA | |||
[accessed March 30, 2006]. 3.1 National Hydrography Dataset. [online] US Geological Survey. Available: | |||
http://nhd.usgs.gov/ | http://nhd.usgs.gov/ | ||
[accessed April 21, 2005]. | |||
Revision 1 December 1, 2009 9-2 4.1 J. L. Sprung, J.A. Rollstin, J.C. Helton, and H.N. Jow. 1990. Evaluation of Severe Accident Risks: Quantification of Major Input Parameters, MACCS Input. NUREG/CR-4551, SAND86-1309, Volume 2, Rev 1, Part 7. Sandia National | Revision 1 December 1, 2009 9-2 4.1 J. L. Sprung, J.A. Rollstin, J.C. Helton, and H.N. Jow. 1990. Evaluation of Severe Accident Risks: Quantification of Major Input Parameters, MACCS Input. NUREG/CR-4551, SAND86-1309, Volume 2, Rev 1, Part 7. Sandia National | ||
Laboratories, Albuquerque, NM. 5.1 D. I. Chanin, M. L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 5.2 2002 Census of Agriculture. [online]. US Department of Agriculture. Available: | Laboratories, Albuquerque, NM. 5.1 D. I. Chanin, M. L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 5.2 2002 Census of Agriculture. [online]. US Department of Agriculture. Available: | ||
http://www.nass.usda.gov/census/ | http://www.nass.usda.gov/census/ | ||
[accessed April 26, 2005]. 5.5 Bixler, N.E., S.A. Shannon, C.W. Morrow, B.E. Meloche, J.N. Ridgely. 2003. SECPOP00: Sector Population, Land Fraction, and Economic Estimation Program. | |||
NUREG/CR-6525, Revision 1. Sandia Nationa l Laboratories, Albuquerque, NM. 7.1 D.I. Chanin, M.L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 7.2 RG-1.23 Onsite Meteorological Programs, U.S. Nuclear Regulatory Commission April 1986 7.3 EM 200-1-5 Meteorological Monitoring Systems, The Environmental Monitoring Center, Corps of Engineers, U. S. Army, October 1991. 7.4 NCDC (National Climatic Data Center), Data set for mixing layer, via temporary ftp site and e-mail dated January 13, 2006 8.1 Entergy Nuclear Northeast. Indian Point Energy Center, Final Safety Analysis Report Update. 8.2 KLD Associates, Inc. October 2004. Re vision 2. Indian Point Energy Center Development of Evacuation Time Estimates. Report KLD TR-369. 422 pp. KLD Associates, Commack, NY | NUREG/CR-6525, Revision 1. Sandia Nationa l Laboratories, Albuquerque, NM. 7.1 D.I. Chanin, M.L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 7.2 RG-1.23 Onsite Meteorological Programs, U.S. Nuclear Regulatory Commission April 1986 7.3 EM 200-1-5 Meteorological Monitoring Systems, The Environmental Monitoring Center, Corps of Engineers, U. S. Army, October 1991. 7.4 NCDC (National Climatic Data Center), Data set for mixing layer, via temporary ftp site and e-mail dated January 13, 2006 8.1 Entergy Nuclear Northeast. Indian Point Energy Center, Final Safety Analysis Report Update. 8.2 KLD Associates, Inc. October 2004. Re vision 2. Indian Point Energy Center Development of Evacuation Time Estimates. Report KLD TR-369. 422 pp. KLD Associates, Commack, NY | ||
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: 6. 0. 271. 2059. 2501. 909. 931. 1223. | : 6. 0. 271. 2059. 2501. 909. 931. 1223. | ||
1389. 1503. 1696. 22955. 30654. 39620. 51057.0 | 1389. 1503. 1696. 22955. 30654. 39620. 51057.0 | ||
: 16. 7. 170. 1943. 2912. 2051. 1177. 1388. | : 16. 7. 170. 1943. 2912. 2051. 1177. 1388. | ||
Revision as of 22:20, 28 April 2019
| ML13045A852 | |
| Person / Time | |
|---|---|
| Site: | Indian Point |
| Issue date: | 12/01/2009 |
| From: | Enercon Services |
| To: | Atomic Safety and Licensing Board Panel, Entergy Nuclear Northeast |
| SECY RAS | |
| References | |
| RAS 24129, 50-247-LR, 50-286-LR, ASLBP 07-858-03-LR-BD01 | |
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Project Records Management Site Specific MACCS2 Input Data Title: Site Specific MACCS2 Input Data for Indian Point Energy Center, Rev. 1 Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the revised site specific MACCS2 input data report and appendices for Indian Point Energy Center. The revisions incorporate the revised annual meteorological files (2000-2004) and the modified VNFRM. Document Review & Acceptance Preparer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapters 1-7, Appendices A, B, C, D, E, F 12/01/09 Technical Reviewer / Date: Chapter 7, Appendices D and E 12/01/09 Project Manager / Date: 12/01/09 Project Records Management IPEC MACCS2 Meteorological Input Files Title: MACCS2 Meteorological Data Input Files Transmittal Letter Severe Accident Mitigation Alternatives Requested Information Attn: Kou-John Hong We have completed the ASCII text file revision for the MACCS2 meteorological input files. This package includes the following: 1. METI00.inp - The 2000 ascii meteorological text file. 2. METI01.inp - The 2001 ascii meteorological text file. 3. METI02.inp - The 2002 ascii meteorological text file. 4. METI03.inp - The 2003 ascii meteorological text file.
- 5. METI04.inp - The 2004 ascii meteorological text file.
Document Review & Acceptance Preparer / Date: 11/12/09 11/12/09 Technical Reviewers / Date:
11/24/09 Project Manager / Date:
11/24/09
SITE SPECIFIC MACCS2 INPUT DATA FOR INDIAN POINT ENERGY CENTER Revision 1
December 1, 2009
SITE SPECIFIC MACCS2 INPUT DATA FOR INDIAN POINT ENERGY CENTER Revision 1
Prepared for Entergy Nuclear Northeast White Plains, NY
Prepared by Enercon Services, Inc.
6525 N. Meridian Suite 400 Oklahoma City, OK 73116
December 1, 2009 Revision 1 December 1, 2009 i TABLE OF CONTENTS
1.0 INTRODUCTION
.................................................................................................................1-1 2.0 REGIONAL POPULATION.................................................................................................2-1 2.1 Projected Permanent Population..........................................................................2-1
2.2 Projected
Transient Population............................................................................2-2
2.3 Projected
Total Population...................................................................................2-5
2.4 Projected
Total Population by Spatial Element...................................................2-6 3.0 LAND FRACTION...............................................................................................................3-1 4.0 WATERSHED INDEX.........................................................................................................4-1
5.0 REGIONAL
ECONOMIC DATA.........................................................................................5-1 5.1 Region Index........................................................................................................5-1
5.2 Regional
Economic Data.....................................................................................5-3 5.2.1 FRMFRC - Fraction of Land Devoted to Farming.................................5-3 5.2.2 ASFP - Total Annual Farm Sales............................................................5-4 5.2.3 DPF - Fraction of Farm Sales Resulting from Dairy Production............5-5 5.2.4 VFRM - Farmland Property Value..........................................................5-5 5.2.5 VNFRM - Nonfarm Property Value........................................................5-5
5.2.6 VALWF
- Value of Farm Wealth...........................................................5-6
5.2.7 FRFIM
- Fraction of Farm Wealth due to improvements.......................5-6
5.2.8 VALWNF
- Value of Nonfarm Wealth...................................................5-6
5.2.9 FRNFIM
- Fraction of Nonfarm Wealth due to improvements..............5-7 6.0 AGRICULTURE DATA.......................................................................................................6-1
7.0 METEOROLOGICAL
DATA...............................................................................................7-1 7.1 Site Specific Data.................................................................................................7-1 7.1.1 Date and Time..........................................................................................7-2 7.1.2 Wind Direction.........................................................................................7-3 7.1.3 Wind Speed..............................................................................................7-3
7.1.4 Atmospheric
Stability Class.....................................................................7-3 Revision 1 December 1, 2009 TABLE OF CONTENTS (CONTINUED) ii 7.1.5 Accumulated Precipitation.......................................................................7-4 7.2 Regional Mixing Heights Data............................................................................7-4 7.3 Data Input Specifications.....................................................................................7-5 8.0 EMERGENCY RESPONSE ASSUMPTIONS.....................................................................8-1 8.1 Emergency Planning Zone Description...............................................................8-1
8.2 Evacuation
Delay Time........................................................................................8-1
8.3 Evacuation
Speed.................................................................................................8-4
9.0 REFERENCES
CITED..........................................................................................................9
-1 LIST OF APPENDICES APPENDIX A: Values for Spatial Elements APPENDIX B: Census of Agriculture Crop Types APPENDIX C: MACCS2 Input APPENDIX D: Meteorological Input Data Files APPENDIX E: Applied Data Substitution Reports APPENDIX F: VNFRM Estimates Including Economic Loss Report Revision 1 December 1, 2009 iii LIST OF TABLES Table 1.1 Counties within 50 miles of IPEC.......................................................................1-3 Table 2.1 Population projections.........................................................................................2-1 Table 2.2.1 State Tourism Offices and Reported Visitor Numbers........................................2-3 Table 2.2.2 2004 transient/permanent ratio for 28 reporting counties....................................2-5 Table 2.3 Projected total population (2035) by county--------------2-5 Table 2.4 2035 projected total population summarized by wind direction and buffer distance................................................................................................................2-6 Table 4.1 Water ingestion factors for selected radionuclides..............................................4-1 Table 5.1 Regional economic variable definitions...............................................................5-3 Table 5.2 Regional economic variables for counties within 50-mile radius of IPEC..........5-4 Table 6.1 Crop categories....................................................................................................6-1 Table 6.2 Percent farmland devoted to crop categories.......................................................6-2 Table 7.1 Example of a meteorological data file.................................................................7-2 Table 7.2 Lapse rate values and atmospheric stability classes............................................7-4 Table 7.3 An exaample of morning and afternoon mixing height values............................7-5 Table 7.4. Example of the text format for MACCS2 meteorological input file. For clarity, columns 32 through 80 and records 27 th rough 8762 are not shown. Input data are in bold font...........................................................................................................7-7 LIST OF FIGURES Figure 1.1 US counties within 50 miles of IPEC..................................................................1-2
Figure 2.1 2035 projected total population by spatial element.............................................2-7
Figure 3.1 Land fraction by spatial element..........................................................................3-2
Figure 4.1 Watershed index values for IPEC........................................................................4-2
Figure 5.1 Economic regions and spatial elements within a 50-mile radius of IPEC...........5-2
Figure 8.1 Region within a 50-mile radius of IPEC..............................................................8-2 Revision 1 December 1, 2009 1-1
1.0 INTRODUCTION
The Severe Accident Mitigation Alternatives (SAMAs) for the Indian Point Energy Center (IPEC) uses the MELCOR Accident Consequence Code System, Version 2 (MACCS2), for estimating the health and economic consequences of severe accidents. Should a severe reactor accident occur, downwind populations, buildings, and crops would be exposed to radioactive materials. MACCS2 estimates the range and probability of the health effects and the economic costs and losses that would result from such an accident. Data used in this SAMA were imported and organized using ESRI ArcGIS 9.1 Geographic Information System (GIS) (Reference 1.1). ArcGIS 9.1 was used for all geographic processing, overlays, and map production occurred within the ArcGIS 9.1 framework. MACCS2 requires data in sixteen equiangular sectors centered on IPEC, extending to 50-mile radius. The sector grid is divided into spatial elements by superimposing fifteen circles of increasing diameter over sixteen sectors, for a total of 240 spatial elements. These circles are 0.2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, and 50 miles from IPEC. For the purposes of this report, the IPEC center point was determined as the center of the super-heater stack. Census 2000 Line Data via ESRI (Reference 1.2) for fourteen counties in New York, ten counties in New Jersey, three counties in Connec ticut, and one county in Pennsylvania within the IPEC 50-mile buffer were used as base map layers (Figure 1.1, Table 1.1).
Data input into MA CCS2 code include:
- 1. Population in 2035-at the end of the license renewal period for 240 spatial elements.
- 2. Land Fraction-proportion of each of the 240 spatial elements that is land, not water. 3. Watershed Index-indication of whether spatial element is drained by rivers or is a lake/water body.
- 4. Regional Economic Data-estimation of amount of farming and economic activities.
- 5. Agricultural Data-crop types, growing season, and percent of farmland for each crop.
Revision 1 December 1, 2009 1-2 Figure 1.1 US counties within 50-miles of IPEC.
Revision 1 December 1, 2009 1-3 Table 1.1 Counties within 50-miles of IPEC.
State/CountyLand Area (square miles)Percent within 50-mile zoneConnecticutFairfield620100.0Litchfield90741.5New Haven59532.9New JerseyBergen 231100.0Essex122100.0Hudson44100.0Middlesex3061.8Morris45180.8Passaic185100.0Somerset3044.5Sussex51593.9Union10292.9Warren3560.5New YorkBronx41100.0Dutchess 79388.9Kings67100.0Nassau26997.9New York23100.0Orange812100.0Putnam226100.0Queens106100.0Richmond5665.4Rockland173100.0Suffolk89521.3Sullivan96736.3Ulster112358.1Westchester430100.0PennsylvaniaPike54018.7 Revision 1 December 1, 2009 2-1 2.0 REGIONAL POPULATION The population within a 50-mile radius of IPEC was estimated for the year 2035, the end of the proposed license renewal period, for each spatial element by combining total permanent (resident) population projections with tr ansient (tourist) population projections.
2.1 Projected
Permanent Population County level permanent population projections were obtained from the New York Statistical Information System from 2000 to 2030 (Reference 2.1), the New Jersey Department of Labor and Workforce Development from 2000 to 2025 (Reference 2.2), the Connecticut State Data Center from 2000 to 2020 (Reference 2.3), a nd the Pennsylvania State Data Center from 2000 to 2020 (Reference 2.4). Population estimates for Connecticut were provided by municipalities and converted to county to maintain consistency. Linear regression was used to extrapolate population projections (Table 2.1) to 2035, except for New York, Rockland and Westchester counties where polynomial regression was used.
Table 2.1 Population projections (2035 calculated from table).
County 2000 2004 2010 2015 2020 2025 2030 2035 Connecticut Fairfield 882,567 903,291 857,870874,730893,240 918,600Litchfield 182,193 189,246 192,290197,730203,280 217,309New Haven 824,008 845,694 838,340852,840868,690 896,364New Jersey
Bergen 884,118 902,998 949,100966,500997,8001,034,900 1,089,428Essex 793,633 796,684 816,400823,700834,400849,500 868,715Hudson 608,975 606,240 635,100641,000655,200668,700 690,981Middlesex 750,162 785,095 858,600881,400922,300968,900 1,053,511Morris 470,212 488,173 532,700547,200571,800603,400 653,201Passaic 489,049 500,427 515,500518,400525,200535,900 553,404Somerset 297,490 316,750 357,800371,000393,900422,700 470,131Sussex 144,166 152,218 167,500173,600185,400198,200 217,947Union 522,541 531,957 545,400550,600559,700573,300 590,616Warren 102,437 110,018 121,400125,900132,700140,700 156,074 Revision 1 December 1, 2009 2-2 County 2000 2004 2010 2015 2020 2025 2030 2035 New York Bronx 1,332,650 1,365,536 1,425,1701,469,2061,511,3221,550,580 1,586,661 1,634,750Dutchess 280,150 293,395 293,520299,468304,815309,007 311,809 319,391Kings 2,465,326 2,475,290 2,531,4242,554,5792,571,6022,580,325 2,580,903 2,618,418Nassau 1,334,544 1,339,641 1,312,1661,300,1251,290,3281,278,213 1,260,336 1,251,644New York 1,537,195 1,562,723 1,587,0981,600,3531,606,7181,605,202 1,595,353 1,570,657Orange 341,367 370,352 370,521386,015401,414415,973 429,580 445,234Putnam 95,745 100,570 103,786107,436110,891113,917 116,428 120,738Queens 2,229,379 2,237,216 2,452,1092,567,8982,685,2062,799,559 2,908,709 3,024,717Richmond 443,728 463,314 505,844537,493569,636600,954 630,683 662,838Rockland 286,753 293,626 291,706291,618290,732288,593 284,768 278,799Suffolk 1,419,369 1,475,488 1,456,1951,466,8081,474,7461,476,069 1,468,072 1,490,766Sullivan 73,966 76,110 79,52282,52485,51288,362 91,092 94,055Ulster 177,749 181,779 190,389197,153203,871210,096 215,719 222,655Westchester 923,459 942,444 926,798925,714924,149919,864 911,278 914,934 Pennsylvania Pike 46,302 54,117 60,05969,44779,170 103,437
2.2 Projected
Transient Population State tourism agencies were contacted to obtain the most recent tourist (transient) information (Table 2.2). Tourist informa tion for 2004 was not available for Pennsylvania therefore 2003 data was incorporated and was assumed to rema in constant for 2004. Fine geographical level tourism data (e.g. tourist per year per county) is not coll ected by states within 50-mile of IPEC. Connecticut and New Jersey only collect this data at a state level. New York breaks state level visitation numbers into five counties within New York City metropolitan area (defined as Bronx, Kings, New York, Queens, and Richmond counties) and the rest of New York state and Pennsylvania reports tour ist per year at a re gional level, (Pocono region which includes Carbon, Monroe, Pike and Wayne c ounties is the relevant region). To convert state visitation numbers into county visitation the ratio of estimated 2004 county population (Reference 2.5) to estimated 2004 state population was multiplied by total number visitors in state (Table 2.2.1).
Revision 1 December 1, 2009 2-3 Table 2.2.1 State Tourism Offices and Reported Visitor Numbers.
State - Region Department Data Year Reporting Visitor Numbers Reference Numbers Connecticut Connecticut Commission on Culture and Tourism 2004 19,254,000 2.6 New Jersey New Jersey Travel and Tourism 2004 71,741,000 2.7 New York - New York MSA NYC & Company 2004 41,000,000 2.8 New York New York Travel and Tourism 2004 96,000,000 2.9 Pennsylvania - Pocono Region Visit Pennsylvania - Pennsylvania Tourism Department 2003 17,726,400 2.10
Revision 1 December 1, 2009 2-4 Table 2.2.2 2004 Transient/permanent ratio for 28 reporting counties.
County 2004 Estimated Population 2004 Person Visits (per day) Transient/Permanent Ratio (per day) Connecticut Fairfield 903,29113,6180.015Litchfield 189,2462,8530.015New Haven 845,69412,7500.015New Jersey Bergen 902,99820,4350.023Essex 796,68418,0290.023Hudson 606,24013,7200.023Middlesex 785,09517,7670.023Morris 488,17311,0480.023Passaic 500,42711,3250.023Somerset 316,7507,1680.023Sussex 152,2183,4450.023Union 531,95712,0390.023Warren 110,0182,4900.023New York Bronx 1,365,53618,9270.014Dutchess 293,3956,9040.024Kings 2,475,29034,3090.014Nassau 1,339,64131,5250.024New York 1,562,72321,6610.014Orange 370,3528,7150.024Putnam 100,5702,3670.024Queens 2,237,21631,0100.014Richmond 463,3146,4220.014Rockland 293,6266,9100.024Suffolk 1,475,48834,7220.024Sullivan 76,1101,7910.024Ulster 181,7794,2780.024Westchester 942,44422,1780.024Pennsylvania Pike 54,1178,1120.150
Revision 1 December 1, 2009 2-5 2.3 Projected Total Population The projected total population within a 50-mile radius of IPEC was estimated for the year 2035, the end of the proposed license renewal period, by combining the 2035 extrapolated permanent population (Table 2.3) with 2035 extrapolated transient population. The 2035 extrapolated transient population was assumed to be the 2004 transient/population ratio multiplied by the extrapolated permanent population (Table 2.3).
Table 2.3 Projected total population (2035) by county.
County Transient/Permanent Ratio 2035 Projected Permanent Population 2035 Projected Total Population Connecticut Fairfield 0.015918,600932,828 Litchfield 0.015217,309220,675 New Haven 0.015896,364910,248 New Jersey Bergen 0.0231,089,4281,114,876 Essex 0.023868,715889,007 Hudson 0.023690,981707,121 Middlesex 0.0231,053,5111,078,120 Morris 0.023653,201668,459 Passaic 0.023553,404566,330 Somerset 0.023470,131481112 Sussex 0.023217,947223038 Union 0.023590,616604,412 Warren 0.023156,074159,719 New York Bronx 0.0141,634,7501,657,680 Dutchess 0.024319,391327,050 Kings 0.0142,618,4182,655,145 Nassau 0.0241,251,6441,281,658 New York 0.0141,570,6571,592,688 Orange 0.024445,234455,910 Putnam 0.024120,738123,633 Queens 0.0143,024,7173,067,143 Richmond 0.014662,838672,135 Rockland 0.024278,799285,484 Suffolk 0.0241,490,7661,526,514 Sullivan 0.02494,05596,310 Ulster 0.024222,655227,994 Westchester 0.024914,934936,873 Pennsylvania Pike 0.15103,437120,669 Revision 1 December 1, 2009 2-6 2.4 Projected Total Population by Spatial Element Areal weighting was used to transfer 2035 projected total population from source areas (county) to target areas (spatial elements) by converting county population to a density measure (e.g. number of people in county/acre) and multiplying this density by the area that county has in a spatial element. For spatial elements that are comprised of elements of more than one county, individual county densities were multiplied by areas of each county in a spatial element and summed. Total projected population of the 50-mile zone of analysis is 19,228,712 and the
distribution of 2035 total population is summarized in Table 2.4 and illustrated in Figure 2.2.
Table 2.4 2035 projected total population summari zed by wind direction and buffer distance.
Wind Direction 0 to 10 miles 11 to 20 miles 21 to 30 miles 31 to 40 miles 41 to 50 miles Total N 12,488 22,955 30,654 39,620 51,057 156,774 NNE 14,952 28,140 39,917 56,226 67,213 206,448 NE 23,377 29,419 53,692 62,559 41,261 210,308 ENE 40,386 74,856 119,073 152,175 176,338 562,828 E 41,290 118,335 156,720 200,581 208,394 725,320 ESE 37,861 121,515 144,267 54,180 34,361 392,184 SE 41,873 111,946 87,735 236,426 379,990 857,970 SSE 12,197 98,326 481,703 1,380,249 1,218,170 3,190,645 S 20,621 135,211 1,164,596 3,732,339 3,164,306 8,217,073 SSW 30,318 202,605 395,389 922,649 1,034,467 2,585,428 SW 30,796 183,372 276,902 197,362 246,076 934,508 WSW 27,723 64,428 209,197 109,102 85,849 496,299 W 16,925 32,026 50,974 61,380 57,384 218,689 WNW 14,036 32,528 54,577 57,977 29,719 188,837 NW 13,421 32,572 54,557 24,046 22,317 146,913 NNW 12,286 31,660 32,569 27,599 34,374 138,488 Totals 390,550 1,319,894 3,352,522 7,314,470 6,851,276 19,228,712
Revision 1 December 1, 2009 2-7 Figure 2.1 2035 projected tota l population by spatial element (dark red indicates highest population).
Revision 1 December 1, 2009 3-1 3.0 LAND FRACTION The percentage of each of the 240 spatial elements that is composed of land, not water, is required by MACCS2. National Hydrography Dataset (Reference 3.1) for the watersheds within the 50-mile radius area was used to calculate the extent of land and surface water coverage. Calculated values ranged from 0.00 to 1.00 (Figure 3.1, Appendix A). A value of 1.00 indicates the spatial element area is all land, with no significan t surface water.
Revision 1 December 1, 2009 3-2 Figure 3.1 Land fraction by spatial element (b rown indicates increasing land fraction).
Revision 1 December 1, 2009 4-1 4.0 WATERSHED INDEX Watershed Index is defined by MACCS2 as areas drained by rivers (Class 1) or large water bodies (Class 2) and for IPEC, no spatial elements were treated as large water bodies (Figure 4.1). IPEC identified four radionuclides as inputs to the MACCS2: Sr-89, Sr-90, Cs-134 and Cs-137. Base values for watershed ingestion factors are shown in Table 4.1 (Reference 4.1). Watershed index values and radionuclide ingestion factors are included in Appendix C (MACCS2 input).
Table 4.1 Water ingestion factor s for selected radionuclides.
Radionuclide Watershed Ingestion Factor - Rivers Sr-89 5 x 10
-6 Sr-90 5 x 10
-6 Cs-134 5 x 10
-6 Cs-137 5 x 10-6
Revision 1 December 1, 2009 4-2 Figure 4.1 Watershed index values for IPEC. Cl ass 1 (land drained by rivers) are shown in light blue.
Revision 1 December 1, 2009 5-1 5.0 REGIONAL ECONOMIC DATA
5.1 Region
Index Each spatial element was assigned to an economic region, defined in this report as a county. When a spatial element was comprised of more than one county, it was assigned to the county that had the most area in that spatial element. A few of the sectors near IPEC contain significant portions of water and a new economic region was created. Spatial elements with 10% or less land were assigned as "Water". Three counties in New Jersey (Middlesex, Somerset, and Warren), one county in New York (Richmond), and one county in Pennsylvania (Pike) were not assigned due to their small representation in any one spatial element. County GIS boundary data were geographically intersected with IPEC spatial elements and each spatial element was attributed accordingly (Figure 5.1, Appendix A).
Revision 1 December 1, 2009 5-2 Figure 5.1 Economic regions and spatial elements within a 50-mile radius of IPEC.
Revision 1 December 1, 2009 5-3 5.2 Regional Economic Data Definitions of regional economic variables have been provided by the client and the MACCS2 Manual (Reference 5.1). A summary of the variables and descriptions is shown in Table 5.1. Table 5.1 Regional economic variable definitions.
Variable Units Description Geographic Area FRMFRC fraction Fraction of land devoted to farming in region. Economic Region (county) ASFP dollars/hectare Total annual farm sales for the region. Economic Region (county)
DPF fraction Fraction of farm sales resulting from dairy production. Economic Region (county) VFRM dollars/hectare Farmland property value for the region. Economic Region (county) VNFRM dollars/person Nonfarm property value for the region. Economic Region (county) VALWF dollars/hectare Defines the value of farm wealth in the region. This value should include both publicly and privately owned grazing lands, farmland, farm buildings, and nonrecoverable farm machinery as well as any publicly owned infrastructure serving the farm industry. Average across 50-mile area FRFIM fraction Defines the fraction of farm wealth in the region due to improvements. This value includes farm buildings and nonrecoverable farm machinery as well as any infrastructure such as silos or irrigation, which is devoted exclusively to the support of farming. Average across 50-mile area VALWNF dollars/person Defines the value of nonfarm wealth in the region. Nonfarm wealth includes all public and private property not associated with farming that would be unusable if the region was rendered either temporarily or permanently uninhabitable. This value should include the cost of land, buildings, infrastructure, and the cost of any nonrecoverable equipment or
machinery. Average across 50-mile area FRNFIM fraction Defines the fraction of nonfarm wealth in the region due to improvements. This value includes buildings and infrastructure such as roads and utilities, as well as any nonrecoverable equipment or machinery. Average across 50-mile area County level economic data were obtained from the US Census of Agriculture (Reference 5.2) for 2002 the most recen t date for agriculture census.
5.2.1 FRMFRC
- Fraction of Land Devoted to Farming US Census of Agriculture item approximate land area, proportion in farms (percent, 2002) was used for each US County (Table 5.2).
Revision 1 December 1, 2009 5-4 Table 5.2 Regional economic variables for counties within 50-mile radius of IPEC.
County Economic Region FRMFRC(%) ASFP ($US/ha) DPF (%) VFRM ($US/ha) VNFRM ($US/person) Modified VNFRM ($US/person)Connecticut Fairfield 1 3.2 5,831 0.8 66,592 232,659 287,881 Litchfield 3 15.9 795 37.1 22,373 148,522 186,016 New Haven 4 6.7 5,439 2.9 36,942 144,105 192,427 New Jersey Bergen 2 0.9 14,568 0 124,496 205,863 262,186 Essex 5 0.2 11,903 0 120,139 147,351 197,400 Morris 7 5.7 6,005 0.6 67,365 213,389 277,661 Passaic 8 1.3 9,836 0 81,944 121,880 161,864 Sussex 9 22.6 483 31.1 18,496 136,197 165,741 Union 10 0.3 91646 0 243,939 160,860 209,708 New York Dutchess 6 21.9 698 20.7 16,206 129,000 169,417 Kings 11 0 0 0 0 104,714 123,701 Nassau 12 0.6 18,237 0 88,422 192,755 239,932 Orange 13 20.7 1516 28.8 13,148 113,976 148,873 Putnam 14 4.5 892 0 24,525 154,926 180,274 Queens* 15 0 0 0 0 169,126 226,728 Rockland 16 1.1 6,365 4.7 65,755 163,105 203,359 Suffolk 17 5.8 14,567 0 54,566 149,615 192,471 Sullivan 18 10.3 1466.0 23.3 7,911 104,859 139,374 Ulster 19 11.6 1019.0 4.3 9,908 104,090 138,739 Westchester 20 3.6 2206.0 0.9 39,116 217,278 263,389 Water 21 0 0 0 0 0
- This economic region incorporates non-farm values from Bronx, Hudson, Queens, and New York counties in order to obtain a conservative value.
5.2.2 ASFP - Total Annual Farm Sales US Census of Agriculture Item Land in farms (acres) was downloaded and converted to hectares. US Census of Agriculture Item Market value of agricultural products sold ($1,000) was downloaded for each county, multiplied by 1000, and divided by land in farms (calculated above) to obtain ASFP (dollars/h ectare) (Table 5.2). One exception was Rockland County, which the US Census of Agriculture did not report total farmland acres due to privacy concerns. Total farmland acres for Rockland County were estimated by multiplying total county area by Farms and land in farms\Approximate land area\Proportion in farms (percent, 2002).
Revision 1 December 1, 2009 5-5 5.2.3 DPF - Fraction of Farm Sales Resulting from Dairy Production US Census of Agriculture Item Dairy products sold ($1,000) was downloaded for each county and divided by Census of Agriculture Item Market value of agricultural products sold
($1,000) (Table 5.2).
5.2.4 VFRM - Farmland Property Value US Census of Agriculture Item Estimated market value of land and buildings: average per acre (dollars, 2002) and was downloaded for each county and converted to dollars/hectare (Table 5.2). US Census of Agriculture Item Estimated market value of all machinery and equipment ($1,000, 2002) was downloaded for each county, divided by hectares in farms (calculated in Section 5.2.1), and summed with market value of land and buildings (dollars/hectare) to obtain VFRM (dollars/hectare) (Table 5.2).
5.2.5 VNFRM
and Modified VNFRM - Non-farm Property Value VNFRM is the average non-farm value ($/person) and cannot be readily calculated with current data due to its dependence on reproducible tangible wealth, a data item which was last calculated by the US Bureau of Economic Analysis for the year 1995. In the absence of more recent data, the VNFRM (Table 5.2) is equal to the county (US) values provided by SECPOP2000 (Reference 5.3). The one exception was the Queens economic region, where the nonfarm property values (VNFRM) for four very small counties within New York City (New York, Hudson, Queens, Bronx counties) were combined as a weighted average (weighted by population) to be certain that economic informati on pertaining to New York City was included in this analysis. An evaluation was completed to supplement the VNFRM parameter and add the county economic output as an input to the MACCS2 model. Through this modification, of the VNFRM input parameter and subsequent analysis with the MACCS2 model, a better estimate is obtained to address the county and metropolitan area economic output losses (e.g., gross domestic product, indicators of tourism, business loss, lost wages, etc.) and thereby account more Revision 1 December 1, 2009 5-6 completely the impacts to overall regional economic activity. It is this modified VNFRM parameter that was incorporated into the la test MACCS2 site file (see Appendix F).
5.2.6 VALWF
- Value of Farm Wealth MACCS2 input requires VALWF, an average value of farm wealth (dollars/hectare) for the 50-mile radius area. This value is simply VFRM weighted by the area each 28 counties have in the IPEC 50-mile area (Table 1.1). VALWF is calculated as $50,071/hectare.
5.2.7 FRFIM
- Fraction of Farm Wealth Due to Improvements MACCS2 input requires FRFIM, input regarding an average fraction of farm wealth due to improvements (roads, buildings, ponds, etc.). The US Census of Agriculture could not be used to identify the required value, because the value of land and buildings cannot be separated. At the request of Entergy, a value of 25% was used. This value was reported to be a representative value for farms located in the northeastern US.
5.2.8 VALWNF
and Modified VALWNF - Value of Non-farm Wealth MACCS2 input requires a regional average value of non-farm wealth. This value is simply VNFRM weighted by the area each 28 counties have in the IPEC 50-mile area (Table 1.1) and is calcul ated as $163,631/person. An evaluation was completed to supplement the VALWNF parameter using the modified VNFRM values (inclusive of non-farm wealth and GCP - which includes tourism and business production) using the 2004 estimates of population of each county rather that the weighted area of the county within the 50-mile radius. The modified VALWNF, weighted by population of the county, is $208,838.49/person (see Appendix F).
Revision 1 December 1, 2009 5-7 5.2.9 FRNFIM - Fraction of Non-farm Wealth Due to Improvements MACCS2 input requires an average value of the fraction of non-farm wealth due to improvements. This value cannot be calculated from available data and the recommended value for use in MACCS2 is 0.8 (Reference 4.1).
Revision 1 December 1, 2009 6-1 6.0 AGRICULTURE DATA MACCS2 requires input regardi ng the crop type, growing seas on, and average fraction of farmland devoted to each crop type. Average values for the 50-mile radius area are used instead of specific values for each of the 240 spatial elements. Seven crop type groupings (Table 6.1) groupings are based on harvesting type (continuous vs. discrete), pathway for contamination of edible portion (direct vs. indirect), length of material exposed (rough vs. smooth), edible portion (seeds vs. roots), and whether the item is eaten by animals (forage) or humans (Reference 4.1). These crop categories were applied to the United States Census of Agriculture (Reference 5.2) using guidance from Table 6.1 and expert judgment. The reclassification of Census of Agriculture Items is show as Appendix B.
Table 6.1 Crop categories (Table 4.1 from Reference 4.1).
Pasture Stored Forage Grain Legumes & Nuts Leafy Green Vegetables Roots & Tubers Other FoodVarious grasses Alfalfa Wheat Soybeans Lettuce Potatoes Apples Clover Oats Peanuts Cabbage Carrots Grapes Sorghum Barley Snap beans Broccoli Beets Oranges Corn (incl. Sweet Corn) Dried beans Spinach Sugar Grapefruit Sorghum Peas Celery Onion Lemon Nuts Cauliflower Tomatoes Greens Cucumbers Peppers Acres for each Agriculture Census were downloaded for each county and were summed into seven crop categories. For the purposes of determining the fraction of farmland devoted to each crop type, US Census of Agriculture Item Land in farms (acres) was used as the total area of farmland. It should be noted that summing the percentage of farmland devoted to each of the seven crop categories does not necessarily add up to one. This is because significant farmland acres can be devoted to woodlands, idle cropland, cropland used for cover crops (not harvested and not pasture), cropland on which crops failed, cropland in summer fallow, and farmland in houses, ponds, and roads. Each crop category was weighted by the percentage of farmland each Revision 1 December 1, 2009 6-2 county has across the entire IPEC 50-mile area (Tab le 6.2). Final weighted average percentage of farmland devoted to each crop category is shown in Table 6.2. Table 6.2 Percent farmland devoted to crop categories.
County Pasture Stored Forage Grain Legume & Nuts Leafy Vegetables Roots & Tubers Other Food % of Area Farmland Connecticut Fairfield 0.22 0.55 0.05 0.00 0.00 0.00 0.09 2.8 Litchfield 1.07 4.15 0.34 0.00 0.01 0.01 0.08 8.48 New Haven 0.45 1.52 0.15 0.02 0.06 0.00 0.37 1.87 New Jersey Bergen 0.00 0.04 0.00 0.00 0.01 0.00 0.10 0.28 Essex 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.03 Hudson 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Middlesex 0.29 0.62 2.94 3.22 0.08 0.01 0.32 0.09 Morris 0.41 1.26 0.60 0.00 0.01 0.00 0.20 3.04 Passaic 0.09 0.00 0.03 0.00 0.01 0.00 0.04 0.33 Somerset 1.78 4.37 3.12 0.85 0.00 0.00 0.11 0.36 Sussex 2.01 6.35 0.73 0.04 0.01 0.01 0.24 15.48 Union 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.04 Warren 1.63 6.58 9.18 2.25 0.15 0.01 0.35 0.08 New York Bronx 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Dutchess 2.43 6.06 1.69 0.00 0.02 0.01 0.25 21.79 Kings 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Nassau 0.07 0.12 0.00 0.00 0.00 0.00 0.01 0.24 New York 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Orange 1.86 6.66 0.66 0.01 0.16 0.72 0.46 23.57 Putnam 0.20 0.64 0.00 0.00 0.00 0.00 0.00 1.47 Queens 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 Richmond 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 Rockland 0.03 0.00 0.02 0.00 0.01 0.01 0.15 0.27 Suffolk 0.16 0.16 0.76 0.06 0.20 0.56 0.87 1.59 Sullivan 1.16 3.95 0.07 0.00 0.00 0.01 0.04 5.04 Ulster 1.31 2.44 0.63 0.00 0.02 0.00 1.09 10.58 Westchester 0.46 0.21 0.04 0.00 0.00 0.00 0.10 2.16 Pennsylvania Pike 0.03 0.37 0.00 0.00 0.00 0.00 0.00 0.41 Weighted Average 1.62 4.8 0.79 0.02 0.05 0.18 0.36 Growing season dates were the recommended MACCS2 values (Reference 4.1). Final agricultural input data for crop types, growing season, and fraction of farmland devoted to each crop are included in Appendix C.
Revision 1 December 1, 2009 7-1 7.0 METEOROLOGICAL DATA The MACCS2 model requires meteorological data for wind speed, wind direction, atmospheric stability, accumulated precipitation, and atmospheric mixing heights (Reference 7.1). The required data were obtained from the IPEC meteorological monitoring system and regional National Weather Service stations 7.1 Site Specific Data Site specific meteorological data included 43,848 (two leap years) consecutive hourly values of wind speed, wind direction, and delta temperature recorded at the IPEC meteorological tower from January 2000 to December 2004. IPEC meteorological monitoring system includes both primary and backup systems. Parameters measured on the primary tower system include the following:
- 1. Wind speed at 10, 60, and 122-meter elevations (mph), 2. Wind direction at 10, 60, and 122-meter elevations (degree from), 3. Temperature at 10-meter elevation (degree F), 4. Dew point at 10-meter elevation (degree F), 5. Delta temperature between the 10 and 60-meter (lower) elevations and between the 10 and 122-meter (upper) el evations (degree F), and
- 6. Precipitation (inches) at ground level (inches).
The primary meteorological system was the data source for the MACCS2 input file. Based on a review of annual meteorological data collected at the site between 1995 and 2004, data from calendar years 2000 through 2004 were developed into individual yearly input files for the MACCS2 program. These meteorological files were considered to be the most recent data set available and reflected the meteorological conditions at the site. Over the five year period there was a successful capture rate of over 99% and missing data were replaced using approved data substitution methods. These methods include substitution of missing data by averaging valid data before and after the data gap, interpolation of before and after valid data values, and substitution of valid data collected from other elevations on the meteorological tower (see Appendix E). The Revision 1 December 1, 2009 7-2 meteorological raw data were provided by IPEC in text format files. An example of a meteorological data file is shown in Table 7.1.
Table 7.1 Example of a meteorological data file.
Jul Day Time (hours) 10-meter Wind Direction (degrees from) 10-meter Wind Speed (mph) Delta Temp / 100m (degrees C/100m)
Precipitation (inches) 1 1 189 3.50 0.9 0 1 2 136 4.14 0.2 0 1 3 222 4.75 0.3 0 1 4 232 4.85 -0.2 0 1 5 218 3.91 -0.4 0 1 6 199 3.47 0 0 1 7 223 3.56 -0.5 0 1 8 205 3.63 -0.6 0 1 9 200 4.48 -0.8 0 1 10 228 5.59 -1.2 0 1 11 234 5.93 -1.3 0 1 12 231 5.50 -1.4 0 1 13 226 5.31 -1.5 0 Processing of IPEC site meteorological data to conform to the MACCS2 input specifications was made using Microsoft Excel (Office 2003) spreadsheets. Data processing was performed as follows.
7.1.1 Date and Time The IPEC data format of "Year" and "Julian Day" was converted to "day of the year" format. Values ranged from 1 (January 1) through 365 (December 31). Hours were converted from 0 to 23 daily to 1 to 24, by adding 1 to every hour in the raw data file.
Revision 1 December 1, 2009 7-3 7.1.2 Wind Direction The IPEC raw data for wind direction was recorded as degrees "from." MACCS2 requires the data in terms of downwind sector values of 1 to 16 (N to NNW). This conversion was accomplished by assigning the mirrored directional bin (each 22.5 degrees wide) to the raw wind direction data. For example, a raw data wind direction value of 180 degrees (from), was converted to a sector value of 1 indicating the downwind direction was in sector 1 (north). The lower (10 meter elevation) wind direction data was used for the MACCS2 input.
7.1.3 Wind Speed The IPEC raw data for wind speed was recorded in miles per hour. MACCS2 requires the data in terms of tenths of a meter per second. The conversion of wind speed from miles per hour to tenths of meter per second was accomplished using a conversion factor of 4.47. The IPEC lower (10 meter elevation) wind speed was used for MACCS2 input.
7.1.4 Atmospheri
c Stability Class Atmospheric stability is usually given in terms of a Pasquill Stability Class index based on the adiabatic lapse rate, or rate of change of temperature with altitude (reference 7.2, 7.3). This value is normally negative unless there is a temperature inversion, which occurs when temperature increases with altitude. The Pasquill Stability Class index is alphabetic (letters A through G) where each letter denotes a specific lapse rate range. MACCS2 input requires the conversion of Pasquill Stability Class to numerical values 1 through 7. Table 7.2 shows the relationship between lapse rates, atmospheric stability, Pasquill classes, and MACCS2 input values. The IPEC meteorological raw data files included values of upper and lower delta temperatures. The upper delta temperature value was the difference between the temperature recorded at the 10m and 122m levels; the lower delta temperature value was the difference between the 10m and 60m levels. The lower delta temperature values were used to calculate stability class values, which were provided in the meteorological data files obtained from IPEC. The MACCS2 input value was developed according to the ranges shown in Table 7.2.
Revision 1 December 1, 2009 7-4 Table 7.2 Lapse rate values and atmospheric stability classes Lapse Rate (degrees C/100 meters) Atmospheric Stability Description Pasquill Stability Class MACCS2 Input Value T/z-1.9 Extremely unstable A 1
-1.9 <T/z -1.7 Moderately unstable B 2
-1.7< T/z -1.5 Slightly unstable C 3
-1.5< T/z -0.5 Neutral D 4
-0.5 <T/z 1.5 Slightly stable E 5 1.5< T/z 4.0 Moderately stable F 6 4.0<T/z Extremely stable G 7
7.1.5 Accumulated
Precipitation The IPEC raw meteorological data files provided hourly precipitation values in the format X.XX inches. These values were converted to the MACCS2 input format by multiplying each value by 100 to provide precipitation in hundredths of an inch. For example, an hourly precipitation value of 1.05 inches was converted to 105 hundredths of an inch.
7.2 Regional
Mixing Heights Data A key input to air quality models is the meteorological data required to compute the transport and dispersion of contaminants. One of the most important parameters to characterize the dispersion potential of the atmosphere is the mixing height. Mixing height is defined as the height of the atmosphere above ground level within which a released contaminant will become mixed (from turbulence) within approximately one hour. Mixing height values are computed using readily available ground-level and upper-air data from the National Weather Service. The MACCS2 requires a morning and afternoon mixing height value, in hundreds of meters, for each season of the year. Daily mixing height values (for morning and afternoon) for the vicinity of IPEC for the period 2000 through 2004 were obtained from the National Climatic Data Center (NCDC) (Reference 7.4). Average values for this period are considered sufficient to accurately represent seasonal mixing heights at IPEC. The morning values were calculated by NCDC using the lowest surface temperature which occurred from 0200 to 0600 hours0.00694 days <br />0.167 hours <br />9.920635e-4 weeks <br />2.283e-4 months <br /> each day. The afternoon values were calculated in a Revision 1 December 1, 2009 7-5 similar way, except the maximum surface temperature which occurred from 1200 to 1600 hours0.0185 days <br />0.444 hours <br />0.00265 weeks <br />6.088e-4 months <br /> was used. Upper atmospheric data from Albany, NY (National Weather Service Station No. 54775) and ground level data collected at White Plains, NY (National Weather Service Station No. 72503). The NCDC daily values for morning and afternoon mixing heights were averaged for each month, and then monthly values were averaged into seasonal values. Calculated seasonal mixing height values were rounded to the nearest hundred and divided by 100 to express values in hundreds of meters. An example of mixi ng height values are shown in Table 7.3.
Table 7.3 An example of morning and afternoon mixing height values.
Season Morning Mixing Height (m) MCCS2 Input Value (100 m)
Afternoon Mixing Height (m) MCCS2 Input Value (100 m) Winter 1037 10 1126 11 Spring 900 9 1392 14 Summer 748 7 1428 14 Fall 856 9 1188 12 7.3 Data Input Specifications Meteorological input data for IPEC were imported into an Excel spreadsheet and converted to the 8E10.0 formatted text file shown in Appendix D. The data file is composed of 8,763 meteorological records. The file format is consistent with the format specified in the MACCS2 manual, Appendix A (Reference 7.1). The first 26 records and the last record of an example MACCS2 meteorological input data file (in the 8E10.0 text format) are shown in Table 7.4. The first two records include file identification information. Beginning at record 3, 8,760 consecutive hourly meteorological input data files are listed. For each hourly record, the Julian day is shown in columns 2-4, hour of day in columns 6-7, down wind direction (sector) in columns 9-10, wind speed (tenths of m/s) in columns in 11-13, atmospheric stability class in column 14, and precipitation (hundred ths of inches) in columns 15-17. Regional mixing height values are listed at record 8,763. The values are in the following order: morning winter (columns 1-10), morning spring (columns 11-20), morning summer Revision 1 December 1, 2009 7-6 (columns 21-30), morning fall (columns 31-40), afternoon winter (columns 41-50), afternoon spring (columns 51-60), afternoon summer (columns 61-70), and afternoon fall (columns 71-80).
Revision 1 December 1, 2009 7-7 Table 7.4 Example of the text format for MACCS2 meteorological input file. For clarity, columns 32 through 80 and records 27 through 8,762 are not shown. Input data are in bold font.
Columns 1 2 3 4 5 6 7 8 9 1011121314151617181920212223 24 25 26 2728293031Records 1 I N D I A N P O I NT E NE RGY CE N T E R ME T E 2 I n p u t f i l e f o r t h e MACC S 2 mo d e l 3 1 1 1 0 1 6 5 0 4 1 2 1 5 0 1 9 5 0 5 1 3 3 0 2 1 5 0 6 1 4 3 0 2 2 5 0 7 1 5 3 0 1 7 5 0 8 1 6 2 0 1 6 5 0 9 1 7 3 0 1 6 4 0 10 1 8 2 0 1 6 4 0 11 1 9 2 0 2 0 4 0 12 1 1 0 3 0 2 5 4 0 13 1 1 1 3 0 2 7 4 0 14 1 1 2 3 0 2 5 4 0 15 1 1 3 3 0 2 4 3 0 16 1 1 4 4 0 2 3 3 1 17 1 1 5 4 0 2 3 4 1 18 1 1 6 4 0 2 2 4 1 19 1 1 7 4 0 2 0 4 5 20 1 1 8 3 0 2 2 5 3 21 1 1 9 4 0 2 2 5 2 22 1 2 0 1 5 0 2 4 5 1 23 1 2 1 1 0 2 5 5 4 24 1 2 2 1 5 0 2 4 5 3 25 1 2 3 1 5 0 2 1 5 5 26 1 2 4 1 6 0 2 2 5 6
-
-
8763 1 0 . 9 . 7 .
1 2 3 4 5 6 7 8 9 1011121314151617181920212223 24 25 26 2728293031
Revision 1 December 1, 2009 8-1 8.0 EMERGENCY RESPONSE ASSUMPTIONS
8.1 Emergency
Planni ng Zone Description IPEC is located on the east bank of the Hudson River about 24 miles north of the New York City, New York boundary line at Indian Po int, Village of Buchanan, in Upper Westchester County, New York (Figure 8.1). The Station is about 2.5 miles southwes t of the City of Peekskill, New York; 8.3 miles south of West Point; 1.5 mile north east of the Lovett generating station site; 4.6 miles no rth of the Bowline Poin t generating station site; and 2.3 miles north of Montrose Point. The site is approximately 239 acres and contains th ree pressurized water reactors owned by Entergy. The IPEC Emergency Planning Zone is composed of a 10-mile radius area divided into 51 Emergency Response Planning Areas (EPRA). The exclusion area for the site includes plant property within a 520-meter radius of the Unit 2 reactor containment. (Reference 8.1, Unit 2 FSAR Update, Section 2.4.4). A Security fence marks the perimeter of the protected area of the site Approximately 2,200 people live within one mile, approximately 84,000 people live within a five-mile radius and approximately 300,000 within a ten-mile radius of the site based on the 2000 US Census population. The site is accessible by several roads in the village of Buchanan. Land access to the plant site is possible from e ither Broadway Avenue or Bleakley Avenue (main entrance), both local roads. The existing wharf is used to receive heavy equipment as needed. The site is not served by rail.
8.2 Evacuation
Delay Time A detailed analysis of evacuation scenarios in EPZ were addressed in the IPEC evacuation travel time estimat e study (Reference 8.2). This study was conducted in 2004 and provides an analysis of the range and variation of public reaction to the evacuation notification process.
Revision 1 December 1, 2009 8-2 Figure 8.1 Region within a 50-mile radius of IPEC.
Revision 1 December 1, 2009 8-3 An ETE was also conducted for IPEC in 1994. The major factors contributing to differences in the ETE values obtained in the 2004 study and those of the 1994 study can be summarized as follows:
- An increase of approximately 10 percent in resident population, based on Census data.
- An increase in the number of evacuating vehicles per household of approximately 25 percent based on the results of the telephone survey.
- An increase of approximately 300 percent in the estimated number of employees commuting to the EPZ based on NYS trip-to-work data and employment statistics.
- Explicit consideration of the impact of Shadow Region traffic movement on evacuation time.
The time between the issuance of an evacuat ion notification and the beginning of the public evacuation is referred to as either "delay time" or "trip generation time." Evacuation delay time has four components:
Notification - the time period between the activation of the prompt public notification system and the receipt by the public of the message to evacuate; Prepare to leave work - the time period required to leave place of employment; Travel home-the time period required for the public to drive from work or shopping, etc. to home; and Prepare to leave home - the time period re quired to gather essential belongings and prepare home for absence.
The 2004 evacuation travel time study addressed numerous scenarios including time of day, normal and adverse weather conditions, resident and transient populations, special facilities (schools, West Point football or graduation, et c.), geography, transportation infrastructure, and other factors. The study concluded that the general public woul d be prepared to begin an evacuation within a minimum of 15 minutes to a maximum of 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> from activation of the evacuation notification process (Reference 8.2, Section 5, Table 5.1). The study addressed the time estimated for 100 percent of the populati on within the EPZ to begin an evacuation considering notification, employee time preparation to leave work and travel home, commuters Revision 1 December 1, 2009 8-4 from outside the EPZ to travel to homes within the EPZ prior to evacuation, the time for preparation to evacuate upon arrival home, and snow clearance from driveways. The maximum response time estimate was based on the worse case scenario which would occur during mid-day under adverse (winter, snow) w eather conditions. The worst case evacuation initiation was 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br />. The average response time was estimated to be about 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 40 minutes (Reference 8.2, Table 1.1).
8.3 Evacuation
Speed The 2004 evacuation travel time study concl uded that the genera l public within the 10-mile EPZ, could be evacuated within a total time of 7 hour8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> and 10 minutes to 12 hours1.388889e-4 days <br />0.00333 hours <br />1.984127e-5 weeks <br />4.566e-6 months <br /> from issuance of an Order to Evacuate (Reference 8.2, Table 7-1d). (Total evacuation time includes the delay time discussed in Section 8.2 above.) The longest travel time s were required for evacuation scenarios occurring mid-week days under winter adverse we ather (snow) conditions. Travel speed can be estimated using the following assumptions:
The maximum distance traveled by the general public from evacuated sites near the plant is 10 miles, and Evacuation travel time (total evacuation time minus the average evacuation delay time of 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> 40 minutes) for the general public within the 10-mile EPZ would range from about 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> and 30 minutes to 9 hours1.041667e-4 days <br />0.0025 hours <br />1.488095e-5 weeks <br />3.4245e-6 months <br /> and 20 minutes.
Evacuation travel speed, therefore, would range from 2.22 miles/hour (0.99 meters/second) to 1.07 mile/hour (0.48 mete rs/sec). The average evacuation speed was conservatively estimated to be approximately 1.65 miles/hour (0.73 meters/second).
Revision 1 December 1, 2009 9-1
9.0 REFERENCES
CITED
1.1 Copyright
© 2005 ESRI. All rights reserved. ArcGIS is a trademark, registered trademark, or service mark of ESRI in the US, the European Community, or certain other jurisdictions. www.esri.com. 1.2 Census 2000 TIGER/Line Shapefiles for Connecticut, New Jersey, New York and Pennsylvania. [online] ESRI ArcData. Available: http://arcdata.esri.com/data/tiger2000/tiger_county.cfm?sfips=36 [accessed May 12, 2005]. 2.1 Brown, W. Baseline Population Projections NYsis Projects SEP02. [online] New York Statistical Information System. Available: http://www.nysis.cornell.edu/data.html
[accessed April 4, 2006]. 2.2 New Jersey Population Projections: 1990-2025. [online]. New Jersey Department of Labor and Workforce Development. Available:
http://www.wnjpin.net/OneStopCareerCenter/LaborMarketInformation/lmi03
[accessed April 4, 2006]. 2.3 Population Projections for Connecticut M unicipalities: 1990-2020. [online] Connecticut State Data Center (SDC). Available: http://www.opm.state.
ct.us/pdpd3/data/sdc.htm
[accessed April 4, 2006]. 2.4 Population Projections for Pennsylvania:
1990-2020. [online] Pennsylvania State Data Center. Available:
http://pasdc.hbg.psu.edu/pasdc/Data_&_Information/Data/231a.html
[accessed April 4, 2006]. 2.5 Annual population Estimates 2000-2005, all counties: [online] U.S. Census Bureau.
Available: http://quickfacts.census.gov/qfd/
[accessed May 31, 2006]. 2.6 Barbara Cieplak Marketing Director, Connecticut for commission on Culture and Tourism - Personal Communication 2.7 2005 A Comprehensive Understanding of the Economic Contribution of Travel and Tourism in the State of New Jersey. [online] Department of New Jersey Tourism.
Available:
http://www.nj.gov/travel/ [accessed March 22, 2006]. 2.8 NYC Statistics. [online] NYC & Company. Available:
[accessed March 22, 2006]. 2.9 Robert Morin. New York State Tourism Department - Personal Communication 2.10 2003 Pennsylvania Travel Profile. [online] Pennsylvania Tourism Office: Experience Pennsylvania Available: http://media.experiencepa.com/default.aspx?site=ExperiencePA
[accessed March 30, 2006]. 3.1 National Hydrography Dataset. [online] US Geological Survey. Available:
[accessed April 21, 2005].
Revision 1 December 1, 2009 9-2 4.1 J. L. Sprung, J.A. Rollstin, J.C. Helton, and H.N. Jow. 1990. Evaluation of Severe Accident Risks: Quantification of Major Input Parameters, MACCS Input. NUREG/CR-4551, SAND86-1309, Volume 2, Rev 1, Part 7. Sandia National
Laboratories, Albuquerque, NM. 5.1 D. I. Chanin, M. L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 5.2 2002 Census of Agriculture. [online]. US Department of Agriculture. Available:
http://www.nass.usda.gov/census/
[accessed April 26, 2005]. 5.5 Bixler, N.E., S.A. Shannon, C.W. Morrow, B.E. Meloche, J.N. Ridgely. 2003. SECPOP00: Sector Population, Land Fraction, and Economic Estimation Program.
NUREG/CR-6525, Revision 1. Sandia Nationa l Laboratories, Albuquerque, NM. 7.1 D.I. Chanin, M.L. Young. 1997. Code Manual for MACCS2: Volume 1, User's Guide, SAND97-0594. Sandia National Labor atories, Albuquerque, NM. 7.2 RG-1.23 Onsite Meteorological Programs, U.S. Nuclear Regulatory Commission April 1986 7.3 EM 200-1-5 Meteorological Monitoring Systems, The Environmental Monitoring Center, Corps of Engineers, U. S. Army, October 1991. 7.4 NCDC (National Climatic Data Center), Data set for mixing layer, via temporary ftp site and e-mail dated January 13, 2006 8.1 Entergy Nuclear Northeast. Indian Point Energy Center, Final Safety Analysis Report Update. 8.2 KLD Associates, Inc. October 2004. Re vision 2. Indian Point Energy Center Development of Evacuation Time Estimates. Report KLD TR-369. 422 pp. KLD Associates, Commack, NY
APPENDIX A Values for Spatial Elements (Not Updated for Rev. 1)
A-1 VALUES FOR SPATIAL ELEMENTS Spatial Element Wind Direction Buffer Distance (miles) Total Projected Population (2035)
Land FractionWatershed Class Economic Region 0 1 50 51057 0.93 1 6 1 9 50 3164306 0.59 1 11 2 8 50 1218170 0.82 1 12 3 16 50 34374 0.96 1 19 4 7 50 379990 0.98 1 17 5 15 50 22317 0.96 1 18 6 6 50 34361 0.12 1 17 7 14 50 29719 0.95 1 18 8 5 50 208394 0.78 1 4 9 13 50 57384 0.97 1 9 10 4 50 176338 0.98 1 4 11 12 50 85849 0.94 1 9 12 2 50 67213 0.98 1 6 13 3 50 41261 0.96 1 3 14 11 50 246076 0.94 1 7 15 10 50 1034467 0.92 1 10 16 1 40 39620 0.94 1 6 17 9 40 3732339 0.81 1 15 18 8 40 1380249 0.79 1 12 19 16 40 27599 0.99 1 19 20 7 40 236426 0.48 1 12 21 15 40 24046 0.99 1 18 22 6 40 54180 0.27 1 1 23 14 40 57977 0.97 1 13 24 5 40 200581 0.97 1 1 25 13 40 61380 0.97 1 9 26 4 40 152175 0.95 1 1 27 12 40 109102 0.97 1 9 28 2 40 56226 0.99 1 6 29 3 40 62559 0.95 1 3 30 11 40 197362 0.9 1 7 31 10 40 922649 0.93 1 5 32 1 30 30654 0.94 1 6 33 9 30 1164596 0.87 1 2 34 8 30 481703 0.7 1 20 35 16 30 32569 0.96 1 19 36 7 30 87735 0.53 1 1 37 15 30 54557 0.99 1 13 38 6 30 144267 0.95 1 1 39 14 30 54577 0.99 1 13 40 5 30 156720 0.97 1 1 A-2 41 13 30 50974 0.98 1 13 42 4 30 119073 0.92 1 1 43 12 30 209197 0.93 1 8 44 2 30 39917 0.99 1 6 45 3 30 53692 0.94 1 6 46 11 30 276902 0.93 1 8 47 10 30 395389 0.99 1 2 48 1 20 22955 0.83 1 6 49 9 20 135211 0.84 1 16 50 8 20 98326 0.77 1 20 51 16 20 31660 0.96 1 13 52 7 20 111946 0.93 1 20 53 15 20 32572 0.98 1 13 54 6 20 121515 0.97 1 20 55 14 20 32528 0.98 1 13 56 5 20 118335 0.92 1 20 57 13 20 32026 0.97 1 13 58 4 20 74856 0.91 1 20 59 12 20 64428 0.94 1 13 60 2 20 28140 0.95 1 14 61 3 20 29419 0.91 1 14 62 11 20 183372 0.98 1 16 63 10 20 202605 0.99 1 2 64 1 10 1696 0.82 1 14 65 9 10 5138 0.83 1 16 66 8 10 3214 0.43 1 20 67 16 10 2028 0.97 1 13 68 7 10 8060 0.99 1 20 69 15 10 2093 1 1 13 70 6 10 7409 0.91 1 20 71 14 10 2071 0.99 1 13 72 5 10 8076 0.99 1 20 73 13 10 2030 0.97 1 13 74 4 10 7279 0.97 1 20 75 12 10 4335 0.94 1 16 76 2 10 1913 0.94 1 14 77 3 10 1915 0.94 1 14 78 11 10 6138 0.99 1 16 79 10 10 6159 1 1 16 80 1 9 1503 0.81 1 13 81 9 9 4455 0.81 1 16 82 8 9 1911 0.3 1 20 83 16 9 1787 0.95 1 13 84 7 9 7194 0.99 1 20 85 15 9 1781 0.95 1 13 86 6 9 6783 0.93 1 20 A-3 87 14 9 1756 0.94 1 13 88 5 9 7201 0.99 1 20 89 13 9 1775 0.95 1 13 90 4 9 6960 0.96 1 20 91 12 9 4255 0.92 1 16 92 2 9 1798 0.99 1 14 93 3 9 1998 1 1 14 94 11 9 5358 0.97 1 16 95 10 9 5517 1 1 16 96 1 8 1389 0.85 1 14 97 9 8 4129 0.85 1 16 98 8 8 948 0.16 1 20 99 16 8 1620 0.98 1 13 100 7 8 6284 0.98 1 20 101 15 8 1541 0.93 1 13 102 6 8 5734 0.89 1 20 103 14 8 1505 0.91 1 13 104 5 8 5587 0.87 1 20 105 13 8 1423 0.86 1 13 106 4 8 6140 0.96 1 20 107 12 8 4196 0.91 1 16 108 2 8 1577 0.98 1 14 109 3 8 2464 0.95 1 14 110 11 8 4361 0.89 1 16 111 10 8 4873 1 1 16 112 1 7 1223 0.87 1 14 113 9 7 3253 0.77 1 16 114 8 7 1442 0.26 1 20 115 16 7 1407 0.98 1 13 116 7 7 5279 0.95 1 20 117 15 7 1351 0.94 1 13 118 6 7 3857 0.69 1 20 119 14 7 1419 0.99 1 13 120 5 7 5513 0.99 1 20 121 13 7 1787 0.98 1 13 122 4 7 5282 0.95 1 20 123 12 7 4014 0.95 1 16 124 2 7 1388 1 1 14 125 3 7 3059 0.96 1 14 126 11 7 4188 0.99 1 16 127 10 7 4187 0.99 1 16 128 1 6 931 0.78 1 14 129 9 6 1538 0.43 1 16 130 8 6 15 0 1 21 131 16 6 1204 0.99 1 13 132 7 6 4537 0.96 1 20 A-4 133 15 6 1140 0.94 1 13 134 6 6 3698 0.79 1 20 135 14 6 1135 0.94 1 13 136 5 6 4424 0.94 1 20 137 13 6 2368 1 1 13 138 4 6 4507 0.96 1 20 139 12 6 3550 0.99 1 16 140 2 6 1177 1 1 14 141 3 6 3910 0.98 1 20 142 11 6 3574 1 1 16 143 10 6 3544 0.99 1 16 144 1 5 909 0.94 1 14 145 9 5 620 0.21 1 16 146 8 5 495 0.13 1 20 147 16 5 740 0.75 1 13 148 7 5 3808 0.99 1 20 149 15 5 972 0.98 1 13 150 6 5 3592 0.93 1 20 151 14 5 1341 0.99 1 13 152 5 5 3792 0.99 1 20 153 13 5 2815 1 1 16 154 4 5 3453 0.9 1 20 155 12 5 2924 1 1 16 156 2 5 2051 0.98 1 14 157 3 5 3843 1 1 20 158 11 5 2916 1 1 16 159 10 5 2882 0.99 1 16 160 1 4 2501 0.99 1 20 161 9 4 124 0.05 1 21 162 8 4 882 0.29 1 20 163 16 4 1587 0.65 1 20 164 7 4 2872 0.96 1 20 165 15 4 1933 0.99 1 16 166 6 4 2970 0.99 1 20 167 14 4 2245 1 1 16 168 5 4 2934 0.98 1 20 169 13 4 2267 1 1 16 170 4 4 2977 0.99 1 20 171 12 4 2197 0.97 1 16 172 2 4 2912 0.97 1 20 173 3 4 2964 0.99 1 20 174 11 4 2274 1 1 16 175 10 4 1700 0.75 1 16 176 1 3 2059 0.96 1 20 177 9 3 246 0.12 1 20 178 8 3 1645 0.77 1 20 A-5 179 16 3 1051 0.57 1 16 180 7 3 2138 1 1 20 181 15 3 1589 0.98 1 16 182 6 3 2136 1 1 20 183 14 3 1624 1 1 16 184 5 3 2138 1 1 20 185 13 3 1602 0.99 1 16 186 4 3 2132 1 1 20 187 12 3 1623 1 1 16 188 2 3 1943 0.91 1 20 189 3 3 2131 1 1 20 190 11 3 1566 0.96 1 16 191 10 3 500 0.31 1 16 192 1 2 271 0.23 1 20 193 9 2 701 0.55 1 20 194 8 2 1268 0.99 1 20 195 16 2 809 0.83 1 16 196 7 2 1274 0.99 1 20 197 15 2 974 1 1 16 198 6 2 1256 0.98 1 20 199 14 2 938 0.96 1 16 200 5 2 1218 0.95 1 20 201 13 2 855 0.88 1 16 202 4 2 1275 0.99 1 20 203 12 2 620 0.64 1 16 204 2 2 170 0.13 1 20 205 3 2 883 0.69 1 20 206 11 2 187 0.18 1 16 207 10 2 562 0.44 1 20 208 1 1 0 0 1 21 209 9 1 400 0.97 1 20 210 8 1 360 0.88 1 20 211 16 1 50 0.16 1 16 212 7 1 410 1 1 20 213 15 1 45 0.14 1 16 214 6 1 409 1 1 20 215 14 1 0 0 1 21 216 5 1 390 0.95 1 20 217 13 1 0 0 1 21 218 4 1 364 0.89 1 20 219 12 1 0 0 1 21 220 2 1 7 0.02 1 21 221 3 1 193 0.47 1 20 222 11 1 217 0.53 1 20 223 10 1 377 0.92 1 20 224 1 0.2 6 0.37 1 20 A-6 225 9 0.2 17 1 1 20 226 8 0.2 17 1 1 20 227 16 0.2 3 0.2 1 20 228 7 0.2 17 1 1 20 229 15 0.2 2 0.14 1 20 230 6 0.2 17 1 1 20 231 14 0.2 2 0.13 1 20 232 5 0.2 17 1 1 20 233 13 0.2 3 0.19 1 20 234 4 0.2 17 1 1 20 235 12 0.2 9 0.52 1 20 236 2 0.2 16 0.92 1 20 237 3 0.2 17 1 1 20 238 11 0.2 17 1 1 20 239 10 0.2 17 1 1 20
APPENDIX B Census of Agriculture Crop Types (Not Updated for Rev. 1)
CENSUS OF AGRICULTURE CROP TYPES Crop Type Census Item DRY EDIBLE BEANS, EXCLUDING LIMAS (CWT)
GREEN LIMA BEANS HAZELNUTS (FILBERTS) OTHER FRUITS AND NUTS SNAP BEANS Legume and Nuts SOYBEANS FOR BEANS (BUSHELS)
BEETS CARROTS DAIKON DRY ONIONS GARLIC POTATOES (CWT)
RADISHES SWEET POTATOES (CWT) Roots and Tubers TURNIPS ASPARAGUS BROCCOLI BRUSSELS SPROUTS CAULIFLOWER CELERY CHICORY CHINESE CABBAGE COLLARDS EGGPLANT ESCAROLE AND ENDIVE GREEN ONIONS HEAD CABBAGE HERBS, FRESH CUT (SEE TEXT)
KALE LETTUCE, ALL MUSTARD GREENS OKRA PARSLEY PEAS, GREEN (EXCLUDING SOUTHERN)
RHUBARB SPINACH TOBACCO (POUNDS)
TURNIP GREENS VEGETABLES, MIXED Leafy Green Vegetables VEGETABLES, OTHER Pasture Land in farms according to use \ Pastureland and rangeland, other than cropland and woodland pastured (see text) (acres, 2002)
Crop Type Census Item APPLES APRICOTS CANTALOUPS CHERRIES, SWEET (SEE TEXT) CHERRIES, TART (SEE TEXT)
CUCUMBERS AND PICKLES GRAPES HONEYDEW MELONS NECTARINES PEACHES, ALL PEARS, ALL PEPPERS, BELL (SEE TEXT)
PEPPERS, CHILE PLUMS AND PRUNES PUMPKINS SQUASH TOMATOES Other Foods WATERMELONS BARLEY FOR GRAIN (BUSHELS) BUCKWHEAT (BUSHELS) CORN FOR GRAIN (BUSHELS) OATS FOR GRAIN (BUSHELS) POPCORN (POUNDS, SHELLED) RYE FOR GRAIN (BUSHELS) SAFFLOWER (POUNDS) SORGHUM FOR GRAIN (BUSHELS) SUNFLOWER SEED, ALL (POUNDS)
SWEET CORN WHEAT FOR GRAIN, ALL (BUSHELS) WINTER WHEAT FOR GRAIN (BUSHELS) BARLEY FOR GRAIN (BUSHELS) BUCKWHEAT (BUSHELS) CORN FOR GRAIN (BUSHELS) OATS FOR GRAIN (BUSHELS) POPCORN (POUNDS, SHELLED) RYE FOR GRAIN (BUSHELS) SAFFLOWER (POUNDS) SORGHUM FOR GRAIN (BUSHELS) SUNFLOWER SEED, ALL (POUNDS)
SWEET CORN WHEAT FOR GRAIN, ALL (BUSHELS)
Grain WINTER WHEAT FOR GRAIN (BUSHELS) BIRDSFOOT TREFOIL SEED FIELD AND GRASS SEED CROPS, ALL FORAGE ORCHARDGRASS SEED RED CLOVER SEED RYEGRASS SEED Stored Forage TIMOTHY SEED
APPENDIX C MACCS2 Input (Updated for Rev. 1)
SITEIEC.inp MACCS2 Site Data File for Indian Point Energy Center
SITE FILE 15 SPATIAL INTERVALS
16 WIND DIRECTIONS
7 CROP CATEGORIES
4 WATER PATHWAY ISOTOPES
1 WATERSHEDS
21 ECONOMIC REGIONS
SPATIAL DISTANCES KILOMETERS
0.3219 1.6093 3.2187 4.8280 6.4374 8.0467 9.6561 11.2654
12.8748 14.4841 16.0935 32.1869 48.2804 64.3739 80.4674
POPULATION
- 6. 0. 271. 2059. 2501. 909. 931. 1223.
1389. 1503. 1696. 22955. 30654. 39620. 51057.0
- 16. 7. 170. 1943. 2912. 2051. 1177. 1388.
1577. 1798. 1913. 28140. 39917. 56226. 67213.0
- 17. 193. 883. 2131. 2964. 3843. 3910. 3059.
2464. 1998. 1915. 29419. 53692. 62559. 41261.0
- 17. 364. 1275. 2132. 2977. 3453. 4507. 5282.
6140. 6960. 7279. 74856. 119073. 152175. 176338.0
- 17. 390. 1218. 2138. 2934. 3792. 4424. 5513.
5587. 7201. 8076. 118335. 156720. 200581. 208394.0
- 17. 409. 1256. 2136. 2970. 3592. 3698. 3857.
5734. 6783. 7409. 121515. 144267. 54180. 34361.0
- 17. 410. 1274. 2138. 2872. 3808. 4537. 5279.
6284. 7194. 8060. 111946. 87735. 236426. 379990.0
- 17. 360. 1268. 1645. 882. 495. 15. 1442.
948. 1911. 3214. 98326. 481703. 1380249. 1218170.0
- 17. 400. 701. 246. 124. 620. 1538. 3253.
4129. 4455. 5138. 135211. 1164596. 3732339. 3164306.0
- 17. 377. 562. 500. 1700. 2882. 3544. 4187.
4873. 5517. 6159. 202605. 395389. 922649. 1034467.0
- 17. 217. 187. 1566. 2274. 2916. 3574. 4188.
4361. 5358. 6138. 183372. 276902. 197362. 246076.0
- 9. 0. 620. 1623. 2197. 2924. 3550. 4014.
4196. 4255. 4335. 64428. 209197. 109102. 85849.0
- 3. 0. 855. 1602. 2267. 2815. 2368. 1787.
1423. 1775. 2030. 32026. 50974. 61380. 57384.0
- 2. 0. 938. 1624. 2245. 1341. 1135. 1419.
1505. 1756. 2071. 32528. 54577. 57977. 29719.0
- 2. 45. 974. 1589. 1933. 972. 1140. 1351.
1541. 1781. 2093. 32572. 54557. 24046. 22317.0
- 3. 50. 809. 1051. 1587. 740. 1204. 1407.
1620. 1787. 2028. 31660. 32569. 27599. 34374.0
LAND FRACTION
0.37 0.00 0.23 0.96 0.99 0.94 0.78 0.87 0.85 0.81 0.82 0.83 0.94 0.94 0.93
0.92 0.02 0.13 0.91 0.97 0.98 1.00 1.00 0.98 0.99 0.94 0.95 0.99 0.99 0.98
1.00 0.47 0.69 1.00 0.99 1.00 0.98 0.96 0.95 1.00 0.94 0.91 0.94 0.95 0.96
1.00 0.89 0.99 1.00 0.99 0.90 0.96 0.95 0.96 0.96 0.97 0.91 0.92 0.95 0.98
1.00 0.95 0.95 1.00 0.98 0.99 0.94 0.99 0.87 0.99 0.99 0.92 0.97 0.97 0.78
1.00 1.00 0.98 1.00 0.99 0.93 0.79 0.69 0.89 0.93 0.91 0.97 0.95 0.27 0.12
1.00 1.00 0.99 1.00 0.96 0.99 0.96 0.95 0.98 0.99 0.99 0.93 0.53 0.48 0.98
1.00 0.88 0.99 0.77 0.29 0.13 0.00 0.26 0.16 0.30 0.43 0.77 0.70 0.79 0.82
1.00 0.97 0.55 0.12 0.05 0.21 0.43 0.77 0.85 0.81 0.83 0.84 0.87 0.81 0.59
1.00 0.92 0.44 0.31 0.75 0.99 0.99 0.99 1.00 1.00 1.00 0.99 0.99 0.93 0.92
1.00 0.53 0.18 0.96 1.00 1.00 1.00 0.99 0.89 0.97 0.99 0.98 0.93 0.90 0.94
0.52 0.00 0.64 1.00 0.97 1.00 0.99 0.95 0.91 0.92 0.94 0.94 0.93 0.97 0.94
0.19 0.00 0.88 0.99 1.00 1.00 1.00 0.98 0.86 0.95 0.97 0.97 0.98 0.97 0.97
0.13 0.00 0.96 1.00 1.00 0.99 0.94 0.99 0.91 0.94 0.99 0.98 0.99 0.97 0.95
0.14 0.14 1.00 0.98 0.99 0.98 0.94 0.94 0.93 0.95 1.00 0.98 0.99 0.99 0.96
0.20 0.16 0.83 0.57 0.65 0.75 0.99 0.98 0.98 0.95 0.97 0.96 0.96 0.99 0.96
REGION INDEX
202120202014141414131406060606 Page 1 SITEIEC.inp 202120202014141414141414060606
202020202020201414141414060303
202020202020202020202020010104
202020202020202020202020010104
202020202020202020202020010117
202020202020202020202020011217
202020202020212020202020201212
202020202116161616161616021511
202020161616161616161602020510
202016161616161616161616080707
202116161616161616161613080909
202116161616131313131313130909
202116161613131313131313131318
201616161613131313131313131818
201616162013131313131313191919
WATERSHED INDEX
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
CROP SEASON AND SHARE
1 PASTURE 90. 270. 0.0162
2 STORED FORAGE 150. 240. 0.0480
3 GRAINS 150. 240. 0.0079
4 GRN LEAFY VEGETABLES 150. 240. 0.0005
5 OTHER FOOD CROPS 150. 240. 0.0036
6 LEGUMES AND SEEDS 150. 240. 0.0002
7 ROOTS AND TUBERS 150. 240. 0.0018
WATERSHED DEFINITION -- INITIAL AND ANNUAL WASHOFF AND INGESTION FACTORS
1 Sr-89 5.00E-06
2 Sr-90 5.00E-06
3 Cs-134 5.00E-06
4 Cs-137 5.00E-06
REGIONAL ECONOMIC DATA
01 FAIRFIELD 0.032 .008 5831.0 66592.0 287881.0
02 BERGEN 0.009 .000 14568.0 124496.0 262186.0
03 LITCHFIELD 0.159 .371 795.0 22373.0 186016.0
04 NEWHAVEN 0.067 .029 5439.0 36942.0 192427.0
05 ESSEX 0.002 .000 11903.0 120139.0 197400.0
06 DUTCHESS 0.219 .207 698.0 16206.0 169417.0
07 MORRIS 0.057 .006 6005.0 67365.0 277661.0
08 PASSAIC 0.013 .000 9836.0 81944.0 161864.0
09 SUSSEX 0.226 .311 483.0 18496.0 165741.0
10 UNION 0.003 .000 91646.0 243939.0 209708.0
11 KINGS 0.000 .000 0.0 0.0 123701.0
12 NASSAU 0.006 .000 18237.0 88422.0 239932.0
13 ORANGE 0.207 .288 1516.0 13148.0 148873.0
14 PUTNAM 0.045 .000 892.0 24525.0 180274.0
15 QUEENS 0.000 .000 0.0 0.0 226728.0
16 ROCKLAND 0.011 .047 6365.0 65755.0 203359.0
17 SUFFOLK 0.058 .000 14567.0 54566.0 192471.0 Page 2 SITEIEC.inp 18 SULLIVAN 0.103 .233 1466.0 7911.0 139374.0
19 ULSTER 0.116 .043 1019.0 9908.0 138739.0
20 WESTCHESTR 0.036 .009 2206.0 39116.0 263389.0
21 WATER 0.000 .000 0.0 0.0 0.0 Page 3
APPENDIX D Meteorological Input Data Files (Updated for Rev. 1)
METI00.inp INDIAN POINT ENERGY CENTER METEORLOGICAL DATAFILE
Input file for the MACCS2 model using the year 2000
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10 9 8 9 11 15 15 13 Page 140 METI01.inp INDIAN POINT ENERGY CENTER METEORLOGICAL DATAFILE
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Input file for the MACCS2 model using the year 2003
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