Section 9.0 Human Receptor Data

1 A setting is defined for each unique WMU type/site co mbination. Thus, a site with a landfill and a waste pile would make up two settings. See Section 2 for additiona l information on the 419 settings used in this analysis. 9-1 

# 9.0 Human Receptor Data
The 3MRA modeling system uses a site-based approach to characterizing, on a national basis, the human health and ecological risks that could result from management of hazardous wastes in industrial nonhazardous waste management units (WMUs). To represent the nonhazardous waste universe for the representative national data set, EPA selected 201 industrial waste disposal sites across the United States from its 1985 screening survey of industrial Resource Conservation and Recovery Act (RCRA) Subtitle D facilities. The 3MRA modeling system uses data on human receptor types, numbers, ages, and locations within a 2-km-radius area of interest (AOI) from each WMU at each of these 201 facilities (419 settings total 1 ) to delineate exposure points of concern for individua l human risk and to weight these points in terms of the population present. Human receptor points, which include residences and farms, are one of the primary spatial data layers in this analysis. They enable human risk to be calculated spatially around a site where people are likely to be located. A geographic information system (GIS) was used to locate these points and collect human receptor numbers and characteristics (e.g., receptor types, age cohorts) for the 201 study sites. This allows the 3MRA modeling system to develop individual risk distributions around a site that are weighted by population. With a GIS, different data layers can be used together even though they may be at different scales (e.g., county-level agricultural census data, census block group data, census block data, and land use data). For the representative national data set, resident human receptor points were located and populated by census block. Farms were located and populated using census block group boundaries, subdivided by farm land use, along with county-level agricultural census data. Figure 9-1 illustrates these primary spatial data layers used in the collection of human receptor data. 

### 9.1 Parameters Collected Table 9-1 lists the human receptor variables required by the 3MRA modeling system. These include all data necessary to locate and populate the points and areas for calculating human exposure and risk, including residences and farms. These data are used primarily by the human risk module, but location and site layout information is also used by the Air, Farm Food Chain, Aquifer, and Human Exposure Modules.Section 9.0 Human Receptor Data

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### U.S. Census Block Level Data

U.S. Census Block Group

Level Data

U.S. Census GIRAS Land Use Data

Figure 9-1. Primary spatial data layers for the 3MRA modeling system human receptor data.Section 9.0 Human Receptor Data

9-3 Table 9-1. Human Receptor and Farm Input Variables

Variable Code Description Index 1 Index 2 Index 3 Human Receptor Inputs NumHumRcpType number of residential receptor types HumRcpType type of residentia l human receptor NumHumRcpType NumHumRcp number of human receptor points at a site HumRcpLocation x,y coordinate of human receptor point NumHumRcp HumRcpPopulation human receptor population Num HumRcp NumHumRcpType (4) age cohort (5) NumAquWell number of drinking water wells AquWellLocation x,y coordinate of drinking water well NumAquWell Farm Inputs NumFarmRcpType number of farm receptor types FarmRcpType type of farm receptor NumFarmRcpType NumFarm number of farm or crop areas FarmLocation x,y coordinates of farm FarmPopulation farm population NumFarm NumFarmRcpType (4) age cohort (5) FarmArea farm area (m 2 ) NumFarm FarmBlockGroup census block group for each farm NumFarm FarmNumAquWell number of wells on farm NumFarm FarmAquWellFrac fraction of farm popul ation on well Num Farm FarmNumAquWell Human Receptor Layout Inputs HumRcpAquWellIndex index of well us ed by human receptor NumHumRcp HumRepAquWellFrac fraction of human receptor population on wells NumHumRcp HumRcpWSSubIndex index of watershed o ccupied by human receptor NumHumRcp HumRcpLWSIndex index of local watershed occupied by human receptor NumHumRcp HumRcpLWSSubAreaIndex index of LWS subarea occupied by human receptor NumHumRcp NumRing number of rings to spatially average risk RingDistance distance of ring from WMU NumRing RingNumHumRcp number of human receptor points in ring no. of rings (3) RingHumRcpIndex index of human receptor point s in ring no. of rings (3) RingNumHumRcp Farm Layout Inputs FarmAquWellIndex index of well used by farm NumHumRcp FarmNumWSSub number of watersheds on farm NumFarm FarmWSSubFrac fraction of farm in each watershed on farm NumFarm FarmNumWSSub FarmWSSubIndex index of watersheds on farm NumFarm FarmNumWSSub FarmNumLWS number of local watersheds on farm NumFarm FarmLWSIndex local watershed indices on farm NumFarm FarmNumLWSSubArea FarmNumLWSSubArea number of LWS subareas on farm NumFarm FarmLWSSubAreaFrac fraction of farm in LWS subarea on farm NumFarm FarmNumLWSSubArea FarmLWSSubAreaIndex index of LWS subareas on farm NumFarm FarmNumLWSSubArea FarmNumWBNRch number of waterbodies used by farm NumFarm FarmWBNIndex index of waterbody network used by farm NumFarm FarmWBNRchIndex index of waterbody used by farm NumFarm FarmNumWBNRch FarmWBNRchFrac fraction of farm or crop ar ea impacted by reach NumFarm FarmNumWBNRch RingNumFarm number of farms in a ring NumRing RingFarmFrac fraction of a farm in a ring NumRing RingNumFarm RingFarmIndex index of a farm in a ring NumRing RingNumFarmSection 9.0 Human Receptor Data

9-4 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd Human resident and farmer population data are dimensioned on ring, receptor type, and age cohort. The 3MRA modeling system can calculate human exposure and risk for concentric rings defined by their distance (Ring Distance) from the WMU boundary. The example data set uses 500 m, 1,000 m, and 2,000 m as ring distances. For residents, the following receptor types (HumRcpType) were used in the example data set to characterize residential exposure and risk:



### # Residents 

### # Resident home gardeners 

### # Resident recreational fishers 

### # Resident home gardener/recreational fishers. For exposure and risk to farmers, the following receptor types (FarmRcpType) were used, depending on whether they are present in the county agricultural census:



### # Beef farmers 

### # Dairy farmers 

### # Beef farmer/recreational fishers 

### # Dairy farmer/recreational fishers. For each of these eight receptor types, these five age cohorts were used for the example data set:



### # Child1 (infant): younger than 1 year 

### # Child2: 1 to 5 years 

### # Child3: 6 to 11 years 

### # Child4: 12 to 19 years 

### # Adult: 20 years or older. This results in a total of 40 receptor type/age cohort combinations. Human receptor data were collected on a site-specific basis. Although site-specific data are available for most of the receptor type and land use information necessary to delineate and populate these areas, certain receptor type information (e.g., data on beef and dairy farmers, data on recreational fishers) were only available on the county or state level; these regional data were applied to the site-specific population and land use data to estimate receptor type/age cohort percentages for each subarea (as described in Section 9.3). 

### 9.2 Data Sources Human receptor data were assembled from the primary data sets shown in Table 9-2. For residents, U.S. census block data and boundary coverages were used because of their greater spatial resolution. When more detailed attributes were needed (e.g., number of people on publicwater vs. private wells), census block group level data were used. Table 9-3 summarizes sitebased or regional data sources by input parameter. Because no census data were available on home gardening practices, a national percentage of home gardeners was obtained from EPA’s Exposure Factors Handbook (U.S. EPA, 1997).Section 9.0 Human Receptor Data

9-5 Table 9-2. Primary Human Receptor Data Sets, Date, and Scale

Data/Receptor Type Data Set Date Scale

Location Industrial D Screening Survey (facilities); Envirofacts (locations) 1985 (Industrial D) 1996 (Envirofacts) 1:100,000 scale mapping

Residents Census block data STF 1B attribute data Census TIGER/line block cove rages 1990 1:100,000 scale mapping

Beef and dairy farmers, farm size Census block group data STF 3A attribute data Census TIGER/line block group c overages 1990 1:100,000 scale mapping GIRAS land use data (USGS, 1990) late 1970s to early 1980s 1:250,000 scale mapping Census of Agriculture 1987 and 1992 County level Recreational fishers National Survey of Fishing, Hunting, and Wildlife 1992 State level

9.2.1 1990 U.S. Census STF 1B Attribute Data Summary Tape File 1B (STF 1B) is a national data set of 1990 population data collected by the U.S. Bureau of the Census (U.S. Bureau of the Census, 1992b). This STF 1B production process focused on the block level for the United States. Table 9-4 lists the STF 1B data fields used in the representative national data set (STF 1B data are available online at http://www.census.gov/mp/www/rom/msrom6ac.html.)
9.2.2 1990 U.S. Census STF 3A Attribute Data Summary Tape File 3A (STF 3A) is a national data set of 1990 population and housing data collected by the U.S. Bureau of the Census (U.S. Bureau of the Census, 1992b). It consists of approximately 70 tables of data for stat es, counties, county subdivisions, places, census tract/block numbering areas (BNAs), and block groups. This STF 3A production process focused on the block group level for the United States. Subject matter of the data covers population items such as age and citizenship, as well as housing items such as rent, age of householder, and number of rooms. Table 9-5 lists the STF 3A data fields used in the representative national data set. (STF 3A data are available online at http://www.census.gov/mp/www/rom/msrom6ae.html.) 9.2.3 1990 U.S. Census TIGER/Line Block and Block Group Coverages The BL90 and BG90 layers in the EPA Spatial Data Library System (ESDLS) provide block and block group boundary coverages based on U.S. Bureau of the Census 1990 TIGER/line data in a polygon ARC/INFO coverage (U.S. EPA, 1995a,b). The 1990 TIGER/line data provide digital data for all 1990 Census map features and boundaries, the associated 1990 Census final tabulation of geographic area codes (such as 1990 Census block numbers), and the codes for the January 1, 1990, legal and statistical areas on both sides of each line segment of every mapped feature. (Additional information is available online at http://nsdi.epa.gov/nsdi/projects/bl90.htm and http://nsdi.epa.gov/nsdi/projects/bg90.htm.)Section 9.0 Human Receptor Data

9-6 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd Table 9-3. Sources of Human Receptor Data by Input Parameter

Variable Code Description Data Source Human Receptor Data NumHumRcp number of human receptor points at a site GI S overlay: census blocks and three risk rings (500 m; 1,000 m; 2,000 m) HumRcpLocation x,y coordinate of human receptor point Centroid of each census block/ring polygon within AOI HumRcpPopulation human receptor population U.S. Ce nsus STF 1B attribute data (block-level) NumAquWell number of drinking water wells U.S. Census STF 3A source of water data (block group-level) AquWellLocation x,y coordinate of dr inking water well HumRcpLocation within block group with residential wells; farm centroid HumRepAquWellFrac fraction of residences with drinking water wells U.S. Census STF3 A source of water data (block group level) Farm Data NumFarm number of farm or crop areas U.S. Census STF 3A: block groups with farms FarmLocation x,y coordinates of farm GIS overlay: master (100 x 100 m) grid and farm coverages FarmPopulation farm population U.S. Census STF 1B/STF 3A and census of agriculture data FarmArea farm area (m 2 ) Census of agriculture: median farm size FarmBlockGroup census block group for each farm U.S. Census TIGER/lin e block group coverage Human Receptor Layout Data HumRcpAquWellIndex index of well used by human receptor GIS overlay: drinking water well and receptor point coverages HumRcpWSSubIndex index of watershed occ upied by human receptor GIS overlay: wa tershed and receptor point coverages HumRcpLWSIndex index of local watershed occupied by human receptor GIS overlay: local watershed and receptor point coverages
HumRcpLWSSubAreaInde index of LWS subarea occupied by human receptor GIS overl ay: local watershed and receptor point coverages RingNumHumRcp number of human receptor points in ri ng GIS overlay: rings and receptor point coverages RingHumRcpIndex index of human receptor points in ri ng GIS overlay: rings and receptor point coverages Farm Receptor Layout Data FarmAquWellIndex index of well used by farm well at farm centroid FarmNumWSSub number of watersheds on farm GI S overlay: watershed and farm coverages FarmWSSubFrac fraction of farm in each watershed on farm GIS overlay: watershed and farm coverages FarmWSSubIndex index of watersheds on farm GI S overlay: watershed and farm coverages FarmNumLWS number of local watersheds on farm GI S overlay: local watershed and farm coverages FarmLWSIndex local watershed indices on farm GIS overlay: local watershed and farm coverages FarmNumLWSSubArea number of LWS subareas on farm GIS overlay: local watershed and farm coverages FarmLWSSubAreaFrac fraction of farm in LWS subarea on farm GIS overlay: local watershed and farm coverages FarmLWSSubAreaIndex index of LWS subareas on farm GI S overlay: local watershed and farm coverages FarmNumWBNRch number of waterbodies used by farm GIS overlay: waterbody and farm coverages FarmWBNIndex index of waterbody network used by farm GIS overlay: waterbody and farm coverages FarmWBNRchIndex index of waterbody used by fa rm GIS overlay: waterbody and farm coverages FarmWBNRchFrac fraction of farm or crop area impacted by reach GIS overlay: waterbody and farm coverages RingNumFarm number of farms in a ring GI S overlay: rings and farm coverages RingFarmFrac fraction of a farm in a ring GIS overlay: rings and farm coverages RingFarmIndex index of a farm in a ring GIS overlay: rings and farm coveragesSection 9.0 Human Receptor Data

9-7 Table 9-4. Specific STF 1B Block-Level Census Items Used to Estimate Human Receptor Populations

Item Code Item Description Item Code Item Description BL0010001 total persons BL0110014 persons 19 yr BL0020001 total families BL0110015 persons 20 yr BL0030001 total households BL0110016 persons 21 yr BL0040001 inside urbanized area BL0110017 persons 22 to 24 yr BL0040002 outside urbanized area BL0110018 persons 25 to 29 yr BL0040003 rural BL0110019 persons 30 to 34 yr BL0110001 persons younger than 1 yr BL0110020 persons 35 to 39 yr BL0110002 persons 1 and 2 yr BL0110021 persons 40 to 44 yr BL0110003 persons 3 and 4 yr BL0110022 persons 45 to 49 yr BL0110004 persons 5 yr BL0110023 persons 50 to 54 yr BL0110005 persons 6 yr BL0110024 persons 55 to 59 yr BL0110006 persons 7 to 9 yr BL0110025 persons 60 and 61 yr BL0110007 persons 10 and 11 yr BL0110026 persons 62 to 64 yr BL0110008 persons 12 and 13 yr BL0110027 persons 65 to 69 yr BL0110009 persons 14 yr BL0110028 persons 70 to 74 yr BL0110010 persons 15 yr BL0110029 persons 75 to 79 yr BL0110011 persons 16 yr BL0110030 persons 80 to 84 yr BL0110012 persons 17 yr BL0110031 persons 85 yr or older BL0110013 persons 18 yr Table 9-5. Specific STF 3A Block Group-Level Census Items Used to Estimate Human Receptor Populations

Item Code Item Description Item Code Item Description P0010001 total persons P0130011 total persons 16 yr P0060001 persons inside urbanized area P0130012 total persons 17 yr P0060002 persons outside urbanized area P0130013 total persons 18 yr P0060003 persons in rural area on fa rm P0130014 total persons 19 yr P0060004 persons in rural area not on farm P0130015 total persons 20 yr H0010001 total housing units P0130016 total persons 21 yr H0050003 housing units, rural farm P 0130017 total persons 22 to 24 yr H0230001 source of water: public system or priv ate company P0130018 total persons 25 to 29 yr H0230002 source of water: drilled individual well P0130019 total persons 30 to 34 yr (continued)Table 9-5. (continued) Section 9.0 Human Receptor Data

Item Code Item Description Item Code Item Description

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H0230003 source of water: dug individual well P0130020 total persons 35 to 39 yr H0230004 some other water source P0130021 total persons 40 to 44 yr P0130001 total persons younger than 1 yr P0130022 total persons 45 to 49 yr P0130002 total persons 1 and 2 yr P0130023 total persons 50 to 54 yr P0130003 total persons 3 and 4 yr P0130024 total persons 55 to 59 yr P0130004 total persons 5 yr P0130025 total persons 60 and 61 yr P0130005 total persons 6 yr P 0130026 total persons 62 to 64 yr P0130006 total persons 7 to 9 yr P0130027 total persons 65 to 69 yr P0130007 total persons 10 and 11 yr P0130028 total persons 70 to 74 yr P0130008 total persons 12 and 13 yr P0130029 total persons 75 to 79 yr P0130009 total persons 14 yr P 0130030 total persons 80 to 84 yr P0130010 total persons 15 yr P0130031 total persons 85 yr or older
The 1990 Census TIGER/line block and block group coverages, a subset of 1:100,000 scale data, are derived from 1990 Census TIGER/line files (U.S. Bureau of the Census, 1990). The 1990 Census TIGER/line files provide digital data for all 1990 Census map features and boundaries and the associated 1990 Census final tabulation of geographic area codes. (Additional information is available online at http://www.census.gov/geo/www/tiger/.) 9.2.4 Census of Agriculture The Census of Agriculture (U. S. Bureau of the Census, 1987, 1992a) provides periodic and comprehensive statistics about agricultural operations, production, operators, and land use. It is conducted every 5 years, for years ending in 2 and 7. Its coverage includes all operators of U.S. farms or ranches (Division A, SIC 01-02) that sold or normally would have sold $1,000 worth of agricultural products during the census year. In 1992, approximately 1.9 million operators produced $162 billion in crops and livestock. All operators provide crop acreage and quantities harvested, inventories of livestock and poultry, value of products sold, land use and ownership, irrigation activities, amount of commodity credit loans, number of hired laborers, federal program payments, and operator characteristics. Selected operators provide additional information on production expenses (including interest), fertilizer and chemical use, machinery and equipment, market value of land and buildings, and income from farm-related sources. (Additional information is available online at http://www.census.gov/econ/www/ag0100.html.) Census of Agriculture data used for the representative national data set included county-level data on beef and dairy farms (Table 9-6). For consistency with the 1990 population census data, data for 1987 and 1992 were averaged.Section 9.0 Human Receptor Data

9-9 9.2.5 National Survey of Fishing, Hunting, Wildlife, and Recreation (NSFHWAR) The 1996 National Survey of Fishing, Hunting, Wildlife, and Recreation (NSFHWAR) presents microdata records (with any information that might identify a specific person or household removed) on individuals involved in fishing, hunting, and other wildlife-associated recreational activities such as wildlife observation, photography, and feeding. Available data include the state in which these activities occurred; number of trips taken; duration of trips; and expenditures for food, lodging, transportation, and equipment. Data are broken out by urban and rural population categories, and were used to identify the percentage of urban and rural recreational fishers for each state represented by the 201 sites. The U.S. Census Bureau conducted the survey for the U.S. Fish and Wildlife Service (FWS), Department of the Interior (DOI), which prepares printed reports in this field (U. S. DOI and U. S. DOC, 1997). (Additional information is available online at http://www.census.gov/prod/3/97pubs/ fhw96nat.pdf.) 9.2.6 Exposure Factors Handbook
Volume II of the Exposure Factors Handbook (U.S. EPA, 1997) provided the data used to estimate the national fraction of home gardeners. Based on National Gardening Association survey data, Table 13-1 of the handbook indicates 38 percent of U.S. households participated in vegetable gardening in 1986. Regional variability ranged from 29 percent (for the non-Deep South) to 53 percent for the Rocky Mountain region. Urban regions showed lower gardening percentages (26 percent for cities) than rural regions, where 61 percent of households had gardens. 

### 9.3 Methodology Human receptor points and farm data were placed and processed within one Arc Macro Language (AML) batch process program for each site/WMU setting to aid in processing efficiency and speed. In the following descriptions, GIS files are referred to as “coverages” – the proprietary GIS file format used by ARC/INFO GIS software. Coverages are self-contained GIS layers that hold graphic spatial information (points, lines, polygons) as well as attribute information. Figure 9-2 charts how farm and human receptors are placed around each of the 419 WMU/site settings and attributed with the information necessary to calculate exposure and risk in the 3MRA modeling system. The programs used to process block and block group census data assumes that census data are uniformly distributed across a given bl ock or block group area. They use area-weighting to calculate the census item numbers that fall within the AOI study area for a site. For example, if the AOI boundary clips a block group so that only 10 percent falls within the AOI, then the total for all census items for that block group are multiplied by 0.1. This area-weighting method was used to calculate census numbers within the study area for both block and block group data. Because Census of Agriculture data are only available at the county level, the analysis assumes that the ratios of specific farm types to total farms at the county level apply uniformly across the entire county. This assumption allows the trends in specific farm family ratios (e.g., the percentage of farm families that are dairy farmers) to be applied to the portions of the studySection 9.0 Human Receptor Data

9-10 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd Table 9-6. Specific County-Level Census of Agriculture Items Used in Human/Farm Receptor Estimations

Item Code Item Description 10001 Farms (number) 10002 Land in farms (acres) 10003 Average size of farm (acres) 10043 Milk cows (farms) 10044 Milk cows (number) 20084 SIC–Beef cattle, except feedlots (0212) 20085 SIC–Dairy farms (024) 60021 Size of farm–1 to 9 acres (acres) 60022 Size of farm–10 to 49 acres (farms) 60023 Size of farm–10 to 49 acres (acres) 60024 Size of farm–50 to 69 acres (farms) 60025 Size of farm–50 to 69 acres (acres) 60026 Size of farm–70 to 99 acres (farms) 60027 Size of farm–70 to 99 acres (acres) 60028 Size of farm–100 to 139 acres (farms) 60029 Size of farm–100 to 139 acres (acres) 60030 Size of farm–140 to 179 acres (farms) 60031 Size of farm–140 to 179 acres (acres) 60032 Size of farm–180 to 219 acres (farms) 60033 Size of farm–180 to 219 acres (acres) 60034 Size of farm–220 to 259 acres (farms) 60035 Size of farm–220 to 259 acres (acres) 60036 Size of farm–260 to 499 acres (farms) 60037 Size of farm–260 to 499 acres (acres) 60038 Size of farm–500 to 999 acres (farms) 60039 Size of farm–500 to 999 acres (acres) 60040 Size of farm–1,000 to 1,999 acres (farms) 60041 Size of farm–1,000 to 1,999 acres (acres) 60042 Size of farm–2,000 acres or more (farms) 60043 Size of farm–2,000 acres or more (acres)Section 9.0 Human Receptor Data

9-11 Figure 9-2. Human and farm receptor GIS process flow chart.Section 9.0 Human Receptor Data

9-12 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd area that fall within a given county. In addition, the Census of Agriculture data from 1987 and 1992 were averaged together to best match the 1990 U.S. Census population data. Similarly, the state-level NSFHWAR recreational fisher data were applied uniformly across each state represented in the analysis. The following sections describe the preprocessing and AML program steps used to place and process human receptor points and farms. The primary AML programs used within the AML batch process are attached as Appendix 9-A and Appendix 9-B. 9.3.1 GIS Data Preparation/Preprocessing Data preparation and preprocessing included the following steps:



### # Downloading and processing needed block and block group coverages. Census coverages are kept by county and were downloaded from EPA's “valley” server. Census GIS coverages come with census data in separate tables and have no attributes attached, only a unique identifier for each polygon. Part of the preprocessing of the census GIS coverages included attaching the census items needed for processing to the GIS coverages. This was done with automated AML programs.



### # Creating AOI and WMU coverages for each site/WMU setting using automated AML programs. Creating a lookup table from the 1996 NSFHWAR data that includes the percentage of residences with recreational fishing licenses in urban, rural, and rural farm areas by state. For each state, recreational fisher percentages were estimated using the NSFHWAR urban and rural population breakdowns and splitting the rural population into farm and nonfarm populations using farm/nonfarm population fractions calculated from 1990 U.S. Census data. This provided state-by-state estimates of urban, rural-farm, and rural-nonfarm recreational fishers as a percentage of the total state population.



### # Importing watershed and waterbody coverages (see Section 5; note that all watershed and waterbody processing must be complete before processing a site).



### # Creating a lookup table from averaged 1987 and 1992 Census of Agriculture data that includes the median farm size and beef and dairy farm ratios for each county. Beef and dairy farm ratios are calculated as the number of beef or dairy farms divided by the total number of farms in a county. Median farm sizes were prepared for all counties containing farms for the entire country prior to human/farm processing. Median farm size was used rather than average farm size because of the general distribution of farm sizes in most counties. Large outlier farms caused the average farm size to be a poor representation of a typical, or central tendency, farm size. The Census of Agriculture represents farm sizes and numbers with irregularly sized groups and frequencies as follows:Section 9.0 Human Receptor Data

9-13 Item # Description–Size of Farm 60020 1 to 9 acres (farms) 60022 10 to 49 acres (farms) 60024 50 to 69 acres (farms) 60026 70 to 99 acres (farms) 60028 100 to 139 acres (farms) 60030 140 to 179 acres (farms) 60032 180 to 219 acres (farms) 60034 220 to 259 acres (farms) 60036 260 to 499 acres (farms) 60038 500 to 999 acres (farms) 60040 1,000 to 1,999 acres (farms) 60042 2,000 acres or more (farms) Calculation of the median farm size was automated (Appendix 9-C) using a median estimation equation from Snedecor and Cochran (1967). 9.3.2 Human Receptor and Farm Placement and Processing This program was designed to process all or a subset of all 201 sites one site/WMU setting at a time. A master point coverage of all 201 sites is maintained and holds the location of the site as well as information about the WMU sizes and types at the site. Initial steps include:



### # Selecting a site from the site coverage.



### # Using AOI coverage to find which census coverages and land use quadrangles were needed for processing. The AOI coverage was overlayed with the counties for the United States and an index of land use quadrangles. The selected counties and land use quadrangle identification numbers written to a list.



### # Using census coverages and land use quadrangles to create data layers for a site. The necessary census block, block group coverages, and land use coverages were merged together to create seamless GIS data layers for the site.



### # Creating ring coverage for the site/WMU setting. Rings were created at 500 m, 1,000 m and 2,000 m, starting from the diagonal corner of the square WMU and indexed as 1, 2, and 3, respectively.



### # Clipping census coverages with ring coverage. The clipped and unclipped census coverages were both needed for the area-weighted reapportionment of censusSection 9.0 Human Receptor Data

9-14 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd data. The clipped areas of the polygons were divided by the unclipped areas to produce the ratio applied to the census numbers.
9.3.2.1 Place and Attribute Farms
. Steps in farm placement and attribution included the following:



### # Overlaying the block group census coverage with the land use coverage.



### # For every block group that had farmers and farm-type land use (i.e, Anderson Code 21, crop and pastureland), placing a farm as follows: – From a lookup table, finding the median farm size for the county being processed. – Checking to see if the block group/farm land use polygon was smaller in area than the median farm size. If so, then the entire polygon became the farm and the program moved to the next block group. – If the block group/farm land use polygon was larger in area than the median farm size, then for the current block group, picking a random point inside the farm land use. – Calculating a radius to produce a circle with an area matching that of the median farm size. – Creating the circle and clipping it with the block group/farm land use polygon. If the resultant clipped circle still approximately matched the median farm area, then the farm was placed and the program moved to the next block group. If it didn't match, then the radius of the circle was increased by 100 m. This incremental process was repeated until the program produced a polygon that approximately matched the median farm area and was contained by the block group/farm land use polygon.



### # After processing all block groups, merging all farm polygons into one farm coverage.



### # Creating a coverage of farm centroids from the coverage of farm polygons. These were used as farm well points (i.e., the farms are assumed to have one well located at the farm centroid) and added to the drinking water well coverage (AquWell parameters in Tables 9-1 and 9-2).



### # Processing farm polygons with watersheds, local watersheds, and rings. The resultant files contained the farm index, the watershed, local watershed, or ring index and the area of their intersection. These indexes and areas were exported to the Microsoft Access database program that calculated the farm/watershed fractions, farm/local watershed fractions, and farm/ring fractions shown in Tables 9-1 and 9-2.Section 9.0 Human Receptor Data

9-15 

### # Overlaying farm polygons with the coverage of waterbodies at the site so that a nearest or impacting waterbody could be found. This was determined as the nearest second-order stream, pond, or lake to the farm.



### # Converting farm polygons to Universal Transverse Mercator (UTM) coordinates and overlaying with the master 100 by 100 m grid file to create the grid tables containing the farm x,y coordinates. 9.3.2.2 Processing Block Group Census Data
. Block group data, including the farmer population and households with wells, were processed within the GIS according to the following steps:



### # Using area weighting to calculate census item totals with the AOI.



### # Applying the beef-farms-to-total-farms ra tio and the dairy-farms-to-total-farms ratio to the total number of farmers per block group to calculate the number of beef and dairy farmers in each block group. Ratios for beef and dairy farmers were derived from the lookup table created from Census of Agriculture data (see Section 9.3.1).



### # Calculating fisher numbers using the lookup table created from NSFHWAR data (Section 9.3.2). This table included the percentage of residences with recreational fishing licenses in urban, rural, and rural farm areas by state (see Section 9.3.1). These percentages were applied to populations by category (persons in urban areas, persons in rural nonfarm areas, and persons in rural farm areas) to find total recreational fishers.



### # Calculating beef and dairy farmers/fi shers from the NSFHWAR lookup table by applying the percentage of residences with recreational fishing licenses in rural farm areas to the calculated number of beef and dairy farmers. The calculated number of beef and dairy farmers/fishers were then subtracted from the totals of beef and dairy farmers so that there was no overlap of the beef and dairy farmer populations with the beef and dairy farmer/fisher populations.



### # Calculating ratio of people on private water supplies to people on public water supplies. This block group ratio was applied to block-based human receptor points within each block group to identify points with wells (i.e., points with a nonzero ratio). The ratio fraction was passed for each receptor point as HumRcpAquFrac, as an estimate of the fraction of the population drinking from wells for each receptor point. 9.3.2.3 Processing Block Census Data
. Block census data were processed by applying the percentages and ratios calculated in the preceding steps to the U.S. Census block data. When census blocks extended across rings, the block data were fractionated into each ring/block combination based on the relative areas in each. GIS processing steps for census block data include:Section 9.0 Human Receptor Data

9-16 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd 

### # Creating human receptor points from the centroids of census blocks or census block/ring polygons created when merged block coverages were clipped by ring coverages (see Figure 9-2).



### # Applying well ratios and recreational fisher ratios to human receptor (census block centroid) points. Block group pol ygons were overlayed with the block points, and the attributes (ratios) calculated at the block group level were applied to each block point within a block group.



### # Calculating home gardener, home gardener/fisher, and resident fisher so no overlap or double counting occurred across receptor types. This is a sample of pseudo-code: home gardener = total block population * 0.38 (national fraction of households with gardens) home gardener fisher = home gardener * recreational fisher ratio resident fisher = (total block population - home gardener) * recreational fisher ratio home gardener = home gardener - home gardener fisher. The national fraction of households with gardens (0.38) was obtained from National Gardening Association data provided in Table 13-1 in Volume 2 of the Exposure Factors Handbook (U.S. EPA, 1997).



### # Calculating total residents so that all receptor types added up to the total population at the site: residents = total block population - (home gardeners + home gardeners/fishers + resident fishers + total farmers).



### # Converting human receptor points to UTM coordinates to create the human receptor location grid tables. After block data GIS processing, all data tables created were exported as Access data tables for further processing. 9.3.3 Database Processing Following GIS processing, the resulting data tables were imported into Access databases, where Structured Query Language (SQL) and Visu al Basic programs were used to prepare the final, model-ready data set according to 3MRA modeling system specifications. Database programs included the following processes:Section 9.0 Human Receptor Data

9-17 

### # Converting x,y coordinates from UTM to the site coordinate system (i.e., facility centroid =0,0) and formatting grid input files for the 3MRA site layout processor (SLP).



### # Calculating all required fractions (see Tables 9-1 and 9-3) using area data passed from GIS.



### # Splitting all receptor type population data into age cohorts based on data for each U.S. Census block.



### # Formatting and indexing all variables according to input data table specifications for the 3MRA modeling system site definition processor (SDP). The resulting data were appended to the site_variable_distribution_data tables within the 3MRA modeling system input database. Grid f iles for farms and human receptor points were sent as a separate Access database. 9.3.4 Quality Assurance/Quality Control Data sources (U.S. Census data, Census of Agriculture, Geographic Information Retrieval and Analysis System [GIRAS]) were derived from Federal data sets that have undergone quality control (QC) measures (see metadata citations in Section 9.2). QC checks performed on the representative national data set data transfer and processing activities included the following:



### # Automated programs were used to check individual block group population values in the census coverages for population outliers or mistakes in the data. The programs compared all census population type values against urban/rural status and polygon size. Values exceeding conservative threshold values were flagged and checked against other data sources and then fixed from alternate data sources.



### # A few random checks were conducted against different sources for the same data (e.g. census CD, a commercial CD of census data).



### # Manual calculations were conducted on a few test sites to verify the AML programs used in the automated processing. To expedite this QC, an Excel spreadsheet was created that repeated the calculations of the human-farm receptor GIS program (Figure 9-3). ArcView was used to extract raw data numbers for different data layers at a site: state, county, block group, and block. The raw data were manually input into the custom spreadsheet to check against the final numbers output by the GIS AMLs. Prior to application, the methodology and logic for the formulas in the spreadsheet were reviewed and checked by senior staff.



### # Farm placement was visually inspected. Because of the variability of census data overlayed with land use data, visual inspection of each site was the safest way to ensure that farms were placed correctly at every site that had farm land use andSection 9.0 Human Receptor Data

9-18 P:\7780 - OSW (Opt 3)\7780-003-030 - ACC Anal ysis\Deliverables\VerValRe port\Volume 2 - Data Coll ection\Final May_30_03\09.0 Hu man Receptor Data.wpd farmers. Automated ArcView scripts were used to create a Web page of the farms, land use data, and block group census data so that the farm placement for each site could be visually inspected (Figure 9-4). The Web page shaded all block groups with beef or dairy farmers present; these could be quickly checked against the actual farm data to ensure that farms were correctly placed within each block group.



### # Site-specific population totals from the final data set (calculated by summing receptor population data across receptor points, receptor types, and age cohorts) were compared against population totals within the 2-km AOI obtained from GIS census coverages.



### # Within the final data processing database, automated queries were applied to ensure all indexing was complete and correct, minimums and maximums were not violated, and other internal constraints were not violated (e.g., no negative receptors). Quality assurance (QA) checks were conducted to ensure that the QC activities were correctly conducted and reported. QA/QC documentation is available on request. 

### 9.4 Results Results from the human receptor and farm data collection effort are summarized in Appendix 9-D, which provides the total resident and farm population and number of farms for each of the 419 site/WMU settings. 

### 9.5 Issues and Uncertainties In general, there are few data gap issues associated with human receptor data; consistent data of an appropriate scale for a national analysis were available for all 201 sites addressed in the analysis. The primary issues and uncertainties are associated with the age of the data and the mismatches based on date and geographic scale. Not all data sources used to estimate human receptors were created at the same time or at the same scale, and most of the data are 9 years old or older (see Table 9-2). More up-to-date national data sets were not available, however. To the extent possible, scale and data discrepancies were addressed using spatial averaging and interpolation to minimize the errors incurred from using different data layers. For example, to better combine the 1990 U.S. Census data with the 1992/1987 Census of Agriculture data, the 1987 and 1992 data were averaged to create a hybrid 1990 data set. Larger scale (i.e., block group, county, and state) data were combined with the block data by assuming uniform characteristics across block groups, counties, and states. This step was necessary to allow automated processing of human receptor type and population data. Although this assumption does create some inaccuracies at individual sites, it is valid and appropriate for a national analysis.9-19 Section 9.0 Human Receptor Datafor Block Group 51165011498 2Bg Area clipped 3053047.0Bg Total area 12727946.4Area Ratio 0.2399P0060003 Area RatioP0060003B 14 * 0.2399 = 3.358173947 P0010001 - Total persons at block group levelP0060001 - Persons Inside Urbanized AreaP0060003B R_20084_1 P0060002 - Persons Outside Urbanized AreaBeef_farmer3.358173947 * 0.38298 = 1.286113458 P0060003 - Persons in rural area on farmP0060004 - Persons in rural area not on farmP0060003B R_20085_1Dairy_farmer3.358173947 * 0.12766 = 0.428704486FISHER1P is the percentage of urban people who fishedBeef_farmer fisher2p/100 FISHER2P is thepercentage of rural/farm people who fishedBeef_fisher1.286113458 * 0.3261 =0.419401599FISHER3P is the percentage of rural/nonfarm people who fishedDairy_farmer fisher2p/100Dairy_fisher0.428704486 * 0.3261 =0.139800533These numbers get applied to farmsBeef_farmer Beef_fisherBeef_farmer1.286113458 - 0.419402 =0.866712Dairy_farmer Dairy_fisherDairy_farmer0.428704486 - 0.139800533 =0.288903953total1.71481794P0060001 P0060002 FISHER1P P0060003 FISHER2P P0060004 FISHER3P P0010001rec_fisher_ratio 0 0 12.85 14 32.61 1511 17.96 15250 456.54 27137.5627594.1275.9410.180945Site 0312301 WMU Type LAURatios from Fisher.datRatios from Ag_Census.datUSER INPUT( ( ( ( ( P0060001 + P0060002 ) * $1FISHER1P ) + ( P0060003 * $1FISHER2P ) + ( P0060004 * $1FISHER3P )) / 100 ) / P0010001 )Block Group Level ProcessingFigure 9-3. QC spreadsheet for human receptor data collection.(continued)9-20 Section 9.0 Human Receptor DataSite 0312301 WMU Type LAUfor block 51165011498 213ABl Area clipped 1169137.7Bl Total area 2026919.1Area Ratio 0.5768P0010001 Area RatioBL0010001B83 * 0.57680531 = 47.87484074 BL0010001B - Total persons at block levelCALC HOME_GARD = BL0010001B * .38CALC GARD_FISHER = HOME_GARD * REC_FISHER_RATIOCALC REC_FISHER = ( BL0010001B - HOME_GARD ) * REC_FISHER_RATIOCALC HOME_GARD = HOME_GARD - GARD_FISHERCALC RESIDENTS = BL0010001B - ( ( HOME_GARD + GARD_FISHER + REC_FISHER ) )RESEL LUCODE = 21CALC RESIDENTS = RESIDENTS - ( ( BEEF_FARMER + BEEF_FISHER + DAIRY_FARMER + DAIRY_FISHER ) * ( BL0010001B / $1BL0010001B ) )BL0010001BHOME_GARD47.87484074 * 0.38 = 18.1924HOME_GARD Rec_fisher_ratioGARD_FISHER18.1924 * 0.180944918 =BL0010001B HOME_GARD Rec_fisher_ratioREC_FISHER47.87484074 - 18.1924 * 0.180944918 =5.370929.68240126HOME_GARD GARD_FISHERHOME_GARD18.1924 - 3.2918 =BL0010001B HOME_GARD GARD_FISHER REC_FISHERRESIDENTS47.87484074 - 14.9006 + 3.2918 + 5.370947.87484074 - 23.56331914 = 24.31152159RESIDENTS ( BEEF_FARMER + BEEF_FISHER + DAIRY_FARMER + DAIRY_FISHER ) BL0010001B total of all clipped blocks in block groupRESIDENTS24.31152159 -47.87484074 / 2331.714817944 0.2054714190.352346077=23.959214.90063.2918Block Level ProcessingFigure 9-3. (continued)Section 9.0 Human Receptor Data

9-21 

## 0331902, OK, 73801

Figure 9-4. Web page for visual farm QC checks.Section 9.0 Human Receptor Data

9-22 From a time-frame perspective, the data are roughly contemporaneous with the 1980s, with data ranging from pre-1980 (certain GIRAS land use data) to 1985 (Industrial D Screening Survey data) to 1990 (U.S. Census, Census of Agriculture 1987-1992 averages). Although a comprehensive review of these data for temporal consistency was not conducted, the visual observation of the land use and census coverages conducted during farm placement QC uncovered no apparent inconsistencies. The general applicability of mid-1980s data to the current analysis also should be considered a significant uncertainty in the overall analysis. The accuracy of location data of the WMU site was initially an issue, but steps were taken to find better WMU locations for the 201 sites, including address matching for 20 sites and visual inspection of all sites and their surrounding land use in order to move them to a more plausible location (i.e., moving a WMU out of a waterbody and into an industrial land use type). 

### 9.6 References
U. S. Bureau of the Census. 1987. Census of Agriculture: Geographic Area Series State and County Data. Washington, DC. U. S. Bureau of the Census. 1990. TIGER: The Coast-to-Coast Digital Map. Washington, DC. U. S. Bureau of the Census. 1992a. Census of Agriculture: Geographic Area Series State and County Data. Washington, DC. U. S. Bureau of the Census. 1992b. Census of Population and Housing: Summary Tape File on CD-ROM Technical Documentation. Washington, DC. Snedecor, George W., and William G. Cochran. 1967. Statistical Methods. 6th Edition. The Iowa State University Press, Ames, IO. U.S. DOI and U.S. DOC (Department of the Interior; Department of Commerce). 1997. 1996 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. FHW/96 NAT. U.S. Department of the Interior, Fish and Wildlife Service; U.S. Department of Commerce, Bureau of the Census. Washington, DC. Website at http://www.nctc.fws.gov/library/pubs3.html. November. U.S. EPA (Environmental Protection Agency). 1995a. 1990 Census Block Boundaries in the Conterminous U.S. Office of Informati on Resources Management, Washington, DC. U.S. EPA (Environmental Protection Agency). 1995b. 1990 Census Block Group Boundaries in the Conterminous U.S. Office of Informa tion Resources Management, Washington, DC. U.S. EPA (Environmental Protection Agency). 1997. Exposure Factors Handbook. EPA/600/P95/002Fa. U.S. Environmental Protection Agen cy, Office of Research and Development, Washington, DC. August. USGS (Geological Survey). 1990. Land Use and Land Cover Digital Data from 1:250,000- and 1:100,000-Scale Maps. Data Users Guide 4. U.S. Geological Survey, Reston, VA.Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-23 

# Appendix 9A GIS Arc Macro Language (AML) Program for Calculating Human Receptor Locations and AttributesAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-24 This page intentionally left blank.Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

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## Appendix 9A. GIS Arc Macro Language (AML) Program for Calculating Human Receptor Locations and Attributes

/*===================================================================

= /* RESEARCH TRIANGLE INSTITUTE /* CEMQA - GIS Program /* P.O. Box 12194 /* Research Triangle Park, NC 27709-2194 /*===================================================================

= /* /* PROGRAM: hwir_pop.aml /* /* PURPOSE: calculates human and farm receptor locations and attributes /* from block, block group, landuse and ag census data. /* /* INFO FILES NEEDED TO RUN: /* template_bg.dat /* template_bl.dat /* ag_census.dat /* fisher.dat /* /* ROUTINES: main /* calls get_utm /* calls getcounties /* calls append /* calls make_landuse /* calls rings /* make rings coverage /* calls clip /* clip the county covs to the aoi/rings cov... /* calls calc /* call the overlay for this bg/county combo... /* calls calc_bl /* call the overlay for this block/county combo... /* calls sumpop /* call the routine that sums up pop for each county... /* calls add_wmu /* adds the WMU coverage to the site (after the processing so people don't get put in the wmu) /* calls wrap_up /* /* getcounties /* append /* calls sum_farmAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-26 /* clip /* place_farm /* farm_points /* process_farm /* calc /* calc_bl /* sumpop /* add_wmu /* wrap_up /* calls output or output_test /* output /* output_test /* clean /* sum_farm /* rings /* /* CALLED BY: /* /* CALLS TO: /* /* GLOBAL VAR'S: /* /* INPUT FILES: /* /* OUTPUT FILES: numerous info files that get exported to Access /* cnty.txt - missing county covs /* fips.txt - fips by site-id /* /* NOTES: /* /* HISTORY: written by G. Conrad 6-10-98 originally called pigs.aml /* used in HWC project /* CONTACT: gtc@rti.org /* /* PROJECT: HWIR /*
/*===================================================================

======== &args site
&echo &on /* &if ^ [exists /files8/hwir/watershed_storage/s%site% -workspace] &then &do /* &sys echo Site %site% does not have complete watershed-waterbodies /* &returnAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-27 /* &end &sv ws_org = [show workspace] &s work-dir = /files8/hwir/census/pop &wo %work-dir% &severity &warning &ignore &severity &error &routine errorhandler /* Check for arguments &s cntypath /files8/hwir/census/stf3a/storage /* path to the block group coverages... &s bl_cntypath /files8/hwir/census/stf1b/storage /* path to the block coverages... &s data /files10/hwir/p6720-06a/data &s amls /files10/hwir/p6720-06a/amllib/system &s sitecov /files10/hwir/p6720-06a/data/site_pts_al83 &s aoi_path /files10/hwir/p6720-06a/data/aoi /* path of aoi covers &s wmu_path /files10/hwir/p6720-06a/data/sectors /* path of wmu covers &s cenpath /files8/hwir/census_storage/c%site% /* final output path for census files &if [exists /files8/hwir/watershed_storage/s%site% -workspace] &then &s outpath /files8/hwir/watershed_storage/s%site% &else &s outpath /files10/hwir/p6720-06a/data/watershed_storage/s%site% /* final output path waterbody watershed data &s us_cov /data1/base/us_covers &s storage /files10/hwir/p6720-06a/data/grids &s utm_zones /data1/base/us_covers/utm_zone_al83 /* Initialize the x & y's and remake wmu and AOI addxy %sitecov% &r %amls%/run_gen_aoi %site% &r %amls%/run_gen_wmu %site% &wo %work-dir% &echo &on /* main loops that control program - site/wmu/ring loops &sys touch progress.txt cursor pop1 declare %sitecov% point ro id_num = [quote %site%] cursor pop1 open &s site = %:pop1.id_num% &s sitex = %:pop1.x-coord% &s sitey = %:pop1.y-coord% &call get_utm /* finds utm zone for site &call getcounties /* for each site, find the counties that overlay it and run the analysis..Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-28 &call append /* append the county covs... &call make_landuse /* append the giras covs... &s type_list = lau_aver surface_imp_aver waste_pile_aver landfill_aver &do type &list %type_list% &if %type% = 'lau_aver' &then &s wmu_name = lau &if %type% = 'surface_imp_aver' &then &s wmu_name = si &if %type% = 'waste_pile_aver' &then &s wmu_name = wp &if %type% = 'landfill_aver' &then &s wmu_name = lf &s type_val = [value :pop1.[value type]] &sys echo %type_val% &if %type_val% > 0 &then &do &s rng_list = b /* a b c &do ring &list %rng_list% &call rings /* make rings coverage &call clip /* clip the county covs to the aoi/rings cov... &call place_farm /* places farm polys in lu type 21 &s i = 1 &if [exists %cenpath%/farm%wmu_name%%i% -cover] &then &do &call farm_points /* make farm centroid point for wells and nearest reach &call process_farms /* overlay farms with ws and lws &call process_farm_rings /* places farm polys over the ring coverages &end &call calc /* call the overlay for this bg/county combo... &call calc_bl /* call the overlay for this block/county combo... &call sumpop /* call the routine that sums up pop for each county... &call add_wmu /* adds the WMU coverage to the site (after the processing so people don't get put in the wmu) &call wrap_up /* output to dbf files &end &end &end &call clean /* clean any leftover coverages cursor pop1 remove &wo %ws_org% &s done [date -full] &sys echo site %site% finished at %done% >> progress.txt /*alert_me &watch &off &return /* mainAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-29 /*===================================================================

========== /* END OF PROGRAM /*===================================================================

========== /* ROUTINE errorhandler******************************************************* &routine errorhandler &severity &error &ignore &severity &warning &ignore &mess &on &wo %ws_org% cursor pop1 remove cursor id1 remove &watch &off &return &error An error has occurred in hwir_pop13.aml on site %site%\~ Last Error: %AML$MESSAGE%\~ Thread: %AML$ERRORTHREAD%\~ File: %AML$ERRORFILE%\~ Line: %AML$ERRORLINE% /* ROUTINE getcounties******************************************************** &routine getcounties /* for each site, do the overlay for the county that touches the site.... display 0 arcplot /* use arcplot reselect to get the list of counties.. reselect %us_cov%/us_cnty_al83 poly overlap %aoi_path%/aoi%site% poly &sv fips_lst = [listunique %us_cov%/us_cnty_al83 -poly fips] /* use arcplot reselect to get the list of landuse covers.. reselect %us_cov%/giras250 poly overlap %aoi_path%/aoi%site% poly &sv giras_lst = [listunique %us_cov%/giras250 -poly covername] quit /* out of arcplot /* fix the leading zero problem &s fips_list &do fips &list %fips_lst% &if [length %fips%] = 4 &then &s fips_list = %fips_list% 0%fips% &elseAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-30 &s fips_list = %fips_list% %fips% &end &s num_cntys = [token %fips_list% -count] &sys touch fips.txt &sys echo %site% [date -full] >> fips.txt &sys echo %fips_list% " " >> fips.txt
&return /* end of routine
/* ROUTINE append************************************************************* &routine append &if [exists pop%site% -cover] &then kill pop%site% all &if [exists bg_mrg -cover] &then kill bg_mrg all &if [exists bl_mrg -cover] &then kill bl_mrg all &sys echo %site% [date -full] >> cnty.txt &call sum_farm &if %num_cntys% = 1 &then &do ap clearsel %cntypath%/bg9%fips_list% poly resel %cntypath%/bg9%fips_list% poly overlap %aoi_path%/aoi%site% poly writesel bg.sel q reselect %cntypath%/bg9%fips_list% bg_mrg poly bg.sel ap clearsel %bl_cntypath%/bl9%fips_list% poly resel %bl_cntypath%/bl9%fips_list% poly overlap %aoi_path%/aoi%site% poly writesel bl.sel q reselect %bl_cntypath%/bl9%fips_list% bl_mrg poly bl.sel &end &else &do /* do block groups
&s cnt = 0 &do cnty_name &list %fips_list% &s cnt = %cnt% + 1 apAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-31 clearsel %cntypath%/bg9%cnty_name% poly resel %cntypath%/bg9%cnty_name% poly overlap %aoi_path%/aoi%site% poly writesel bg.sel q &if [exists bgtmp%cnt% -cover] &then kill bgtmp%cnt% all reselect %cntypath%/bg9%cnty_name% bgtmp%cnt% poly bg.sel &end /* make merge coverage of overlapping block groups &if [exists bg_mrg -cover] &then kill bg_mrg all mapjoin bg_mrg &do jj = 1 &to %cnt% bgtmp%jj% &end end &do jj = 1 &to %cnt% kill bgtmp%jj% all &end
/* do blocks
&s cnt = 0 &do cnty_name &list %fips_list% &s cnt = %cnt% + 1 ap clearsel %bl_cntypath%/bl9%cnty_name% poly resel %bl_cntypath%/bl9%cnty_name% poly overlap %aoi_path%/aoi%site% poly writesel bl.sel q &if [exists bltmp%cnt% -cover] &then kill bltmp%cnt% all reselect %bl_cntypath%/bl9%cnty_name% bltmp%cnt% poly bl.sel &end &if [exists bl_mrg -cover] &then kill bl_mrg all mapjoin bl_mrg &do jj = 1 &to %cnt% bltmp%jj% &end end &do jj = 1 &to %cnt% kill bltmp%jj% all &end
&end /* elseAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-32 /* move merged blocks and block groups to census_storge for QC purposes &if [exists %cenpath%/bg_mrg -cover] &then kill %cenpath%/bg_mrg all &if [exists %cenpath%/bl_mrg -cover] &then kill %cenpath%/bl_mrg all copy bg_mrg %cenpath%/bg_mrg copy bl_mrg %cenpath%/bl_mrg

&return /* end of routine
/* ROUTINE make_landuse************************************************************* &routine make_landuse /* select and merge giras landuse covers together... display 0 ap /* use arcplot reselect to get the list of landuse covers.. reselect %us_cov%/giras250 poly overlap bg_mrg poly &sv lu_lst = [listunique %us_cov%/giras250 -poly covername] q &s num_lus = [token %lu_lst% -count] &if [exists lu%site% -cover] &then kill lu%site% all &if %num_lus% = 1 &then &do ap clearsel %us_cov%/giras_covers/%lu_lst% poly resel %us_cov%/giras_covers/%lu_lst% poly overlap bg_mrg poly writesel lu.sel q reselect %us_cov%/giras_covers/%lu_lst% lu%site% poly lu.sel &end &else &do &s cnt = 0 &do lu_num &list %lu_lst% &s cnt = %cnt% + 1 ap clearsel %us_cov%/giras_covers/%lu_num% poly resel %us_cov%/giras_covers/%lu_num% poly overlap bg_mrg poly writesel lu.sel q &if [exists lutmp%cnt% -cover] &then kill lutmp%cnt% allAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-33 reselect %us_cov%/giras_covers/%lu_num% lutmp%cnt% poly lu.sel &end /* make merge coverage of overlapping landuse covers &if [exists lu%site% -cover] &then kill lu%site% all mapjoin lu%site% &do j = 1 &to %cnt% lutmp%j% &end end &do j = 1 &to %cnt% kill lutmp%j% all &end &end &if [exists lu_temp -cover] &then kill lu_temp all dissolve lu%site% lu_temp lucode poly kill lu%site% all rename lu_temp lu%site% /* add a unique identifer to the landuse polys additem lu%site%.pat lu%site%.pat lu_poly_id 4 4 I &data arc info ARC SEL LU%site%.PAT CALC LU_POLY_ID = LU%site%# Q STOP &end
&return /* end of routine /* ROUTINE clip************************************************************* &routine clip &if [exists bg_lu -cover] &then kill bg_lu all &if [exists bgl%site% -cover] &then kill bgl%site% all identity bg_mrg lu%site% bg_lu poly .1 join /* bg_lu has landuse areas and is used with bg%site% &if ^ [exists %cenpath%/bg_clp -cover] &then &do &if [exists big_aoi -cover] &then kill big_aoi all buffer %aoi_path%/aoi%site% big_aoi # # 1000 .1 poly clip bg_mrg big_aoi %cenpath%/bg_clpAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-34 kill big_aoi all &end clip bg_lu rng%site% bgl%site% /* bgl%site% is used for farm numbers - has landuse &if [exists bl%site% -cover] &then kill bl%site% all intersect bl_mrg rng%site% bl%site% poly .1 join &if [exists lu%site%b -cover] &then kill lu%site%b all clip lu%site% bg_mrg lu%site%b kill lu%site% all rename lu%site%b lu%site%
&return /* end of routine /* ROUTINE place_farm********************************************************* &routine place_farm
&s iteration = 1 &do i = 1 &to %iteration% &if ^ [exists %cenpath%/farm%wmu_name%%i% -cover] &then /* kill %cenpath%/farm%wmu_name%%i% all &r place_farms %site% %wmu_name% %i% %sitex% %sitey% &wo %cenpath% &data arc info ARC SEL [translate farm%wmu_name%%i%.pat] CALC UTM_ZONE = %utmz% Q STOP &end &wo %ws_org% &if [exists %cenpath%/info!arc!farm_grid_% wmu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_grid_%wmu_name%%i%.dat -info] &if [exists %cenpath%/info!arc!farm_ws_%wm u_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_ws_%wmu_name%%i%.dat -info] &if [exists %cenpath%/info!arc!farm_lws_%w mu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_lws_%wmu_name%%i%.dat -info] &if [exists %cenpath%/info!arc!farm_rng %ring%_%wmu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_rng%ring%_%wmu_name%%i%.dat -info]
&end
&return /* end of routineAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-35 /* ROUTINE process_farms********************************************************* &routine process_farms
&do i = 1 &to %iteration%
/* convert to utm coords &if [exists farm_utm -cover] &then kill farm_utm all &if [exists farm_temp -cover] &then kill farm_temp all project cover %cenpath%/farm%wmu_name%%i% farm_utm /data1/base/prj_files/albers83-utm%utmz%_83.prj build farm_utm &if ^ [iteminfo %storage%/grd%site% -poly x-coord -exists] &then addxy %storage%/grd%site% point identity %storage%/grd%site% farm_utm farm_temp point .001 join pullitems farm_temp.pat farm_grd.dat id_num wmu farmindex iteration cell_add x-coord y-coord end
&data arc info ARC SEL FARM_GRD.DAT RESEL FARMINDEX = 0 PURGE Y Q STOP &end &if [exists %cenpath%/info!arc!farm_grid_% wmu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_grid_%wmu_name%%i%.dat -info] copyinfo farm_grd.dat %cenpath%/farm_grid_%wmu_name%%i%.dat /* export info file to site directory &s [delete farm_grd.dat -info] &if [exists farm_utm -cover] &then kill farm_utm all &if [exists farm_temp -cover] &then kill farm_temp allAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-36 /* process the farms with watersheds and local watersheds
/* watershed &if [exists farm_ws -cover] &then kill farm_ws all &if [exists %outpath%/v2_%site% -cover] &then &do &if ^ [iteminfo %outpath%/v2_%site% -poly ws_area -exists] &then &do additem %outpath%/v2_%site%.pat %outpath%/v2_%site%.pat ws_area 4 12 f 3 &end &wo %outpath% &data arc info ARC SEL [translate v2_%site%.pat] CALC WS_AREA = AREA Q STOP &end &wo %work-dir% intersect %cenpath%/farm%wmu_name%%i% %outpath%/v2_%site% farm_ws pullitems farm_ws.pat farm_ws.dat id_num wmu iteration farmindex farmarea wshd_num ws_area area end &end
&data arc info ARC SEL FARM_WS.DAT MOVEIT [quote %site%] TO ID_NUM RESEL FARMINDEX = 0 PURGE Y Q STOP &end &if [exists %cenpath%/info!arc!farm_ws_%wm u_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_ws_%wmu_name%%i%.dat -info] copyinfo farm_ws.dat %cenpath%/farm_ws_%wmu_na me%%i%.dat /* export info file to site directory &if [exists farm_ws -cover] &then kill farm_ws allAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-37 /* local watershed display 0 arcplot clearselect %wmu_path%/cir%site%%wmu_name% poly resel %outpath%/v2_%site% poly overlap %wmu_path%/cir%site%%wmu_name% poly &sv lwses = [listunique %outpath%/v2_%site% -poly wshd_num] q &if [exists frm_lws.dat -info] &then &s d [delete frm_lws.dat -info] &do ws_num &list %lwses% &if [exists farm_lws -cover] &then kill farm_lws all &if [exists %outpath%/%wmu_name%%ws_num% -cover] &then &do &if ^ [iteminfo %outpath%/%wmu_name %%ws_num% -poly local_area -exists] &then additem %outpath%/info!arc!%wmu_name%%ws_num%.pat %outpath%/info!arc!%wmu_name%%ws_num%.pat local_area 4 12 f 3 &wo %outpath% &data arc info ARC SEL [translate %wmu_name%%ws_num%.pat] CALC LOCAL_AREA = AREA Q STOP &end &wo %work-dir% &if ^ [iteminfo %outpath%/%wmu_name %%ws_num% -poly wshd_num -exists] &then &do additem %outpath%/info!arc!%wmu_name%%ws_num%.pat %outpath%/info!arc!%wmu_name%%ws_num%.pat wshd_num 3 3 i &wo %outpath% &data arc info ARC SEL [translate %wmu_name%%ws_num%.pat] CALC WSHD_NUM = %ws_num% Q STOP &end &wo %work-dir% &end intersect %cenpath%/farm%wmu_name%%i% %outpath%/%wmu_name%%ws_num% farm_lws &if [exists farm_lws_tmp.dat -info] &then &s d [delete farm_lws_tmp.dat -info] pullitems farm_lws.pat farm_lws_tmp.dat id_num wmu iteration farmindex farmareaAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-38 wshd_num local_num local_area area end &end
&data arc info ARC SEL FARM_LWS_TMP.DAT MOVEIT [quote %site%] TO ID_NUM RESEL FARMINDEX = 0 PURGE Y Q STOP &end &if ^ [exists frm_lws.dat -info] &then copyinfo farm_lws_tmp.dat frm_lws.dat &else &do &data arc info arc SEL [translate farm_lws_tmp.dat] MERGE INTO [translate frm_lws.dat] ON ID_NUM UNSORTED Q STOP &end &end
&end /* do additem frm_lws.dat frm_lws.dat farm_lws_index 3 3 i # farmindex /* redo index nums so there aren't any missing places ************************** &s i_cnt = 1 cursor id1 declare frm_lws.dat info rw cursor id1 open &do &while %:id1.AML$NEXT% &s :id1.farm_lws_index = %i_cnt% &s i_cnt = %i_cnt% + 1 cursor id1 next &end cursor id1 remove &if [exists %cenpath%/info!arc!farm_lws_%w mu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_lws_%wmu_name%%i%.dat -info]Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-39 copyinfo frm_lws.dat %cenpath%/farm_lws_%wmu_name%%i%.dat /* export info file to site directory &if [exists farm_lws -cover] &then kill farm_lws all
&end
&return /* end of routine
/* ROUTINE farm_points*********************************************************** &routine farm_points
&do i = 1 &to %iteration% &if [exists farm_pts -cover] &then kill farm_pts all &if [exists farm_pts_utm -cover] &then kill farm_pts_utm all centroidlabels %cenpath%/farm%wmu_name%%i% inside ae ec %cenpath%/farm%wmu_name%%i% label sel all put farm_pts q /*&data arc info /*ARC /*SEL FARM_PTS.PAT /*CALC INDEX = FARM_PTS-ID /*Q STOP /*&end /* process imp_reach_idx &if [exists tmp_re -cover] &then kill tmp_re all &if [exists tmp_re_clp -cover] &then kill tmp_re_clp all &if [exists farm%wmu_name%_re -cover] &then kill farm%wmu_name%_re all

ap clearsel %outpath%/reaches line resel %outpath%/reaches line value > 1 resel %outpath%/reaches line rch_num > 0 writesel reach.sel q reselect %outpath%/reaches tmp_re line reach.sel clip tmp_re %aoi_path%/aoi%site% tmp_re_clp line build tmp_re_clp lineAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-40 kill tmp_re all near farm_pts tmp_re_clp line 2000 farm%wmu_name%_re
&data arc info ARC SEL [translate farm%wmu_name%_re.pat] RELATE TMP_RE_CLP.AAT 1 by TMP_RE_CLP# CALC IMP_REACH_IDX = $1RCH_NUM Q STOP &end &if [exists %cenpath%/farm%wmu_name%_re -cover] &then kill %cenpath%/farm%wmu_name%_re all copy farm%wmu_name%_re %cenpath%/farm%wmu_name%_re &wo %cenpath% &data arc info ARC SEL [translate farm%wmu_name%_re.pat] LIST FARMINDEX SEL [translate farm%wmu_name%%i%.pat] LIST FARMINDEX RELATE [translate farm%wmu_name%_re.pat] 2 by FARMINDEX CALC IMP_REACH_IDX = $2IMP_REACH_IDX Q STOP &end &if [exists tmp_re -cover] &then kill tmp_re all &if [exists tmp_re_clp -cover] &then kill tmp_re_clp all &if [exists farm%wmu_name%_re -cover] &then kill farm%wmu_name%_re all &if [exists %cenpath%/farm%wmu_name%_re -cover] &then kill %cenpath%/farm%wmu_name%_re all &wo %ws_org%

/* convert to utm coords project cover farm_pts farm_pts_utm /data1 /base/prj_files/albers83-utm%utmz%_83.prj addxy farm_pts_utm kill farm_pts all &if [exists %cenpath%/farm_pts_%wmu_name%%i%.dat -info] &then &s d [delete %cenpath%/farm_pts_%wmu_name%%i%.dat -info] pullitems farm_pts_utm.pat %cenpath%/farm_pts_%wmu_name%%i%.datAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-41 id_num wmu iteration farmindex farmarea x-coord y-coord end kill farm_pts_utm all &end
&return /* end of routine
/* ROUTINE process_farm_rings******************************************************* &routine process_farm_rings
&do i = 1 &to %iteration% &if [exists farm_rng -cover] &then kill farm_rng all &if [exists rng%site% -cover] &then &do intersect %cenpath%/farm%wmu_name%%i% rng%site% farm_rng pullitems farm_rng.pat farm_rng.dat id_num wmu iteration farmindex farmarea ring_id area end &end
&data arc info ARC SEL FARM_RNG.DAT MOVEIT [quote %site%] TO ID_NUM RESEL FARMINDEX = 0 PURGE Y Q STOP &end &if [exists %cenpath%/info!arc!farm_rng %ring%_%wmu_name%%i%.dat -info] &then &s d [delete %cenpath%/info!arc!farm_rng%ring%_%wmu_name%%i%.dat -info]Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-42 copyinfo farm_rng.dat %cenpath%/farm_rng%ring%_%wmu_name%%i%.dat /* export info file to site directory &if [exists farm_rng -cover] &then kill farm_rng all
&end
&return /* end of routine /* ROUTINE calc_bl************************************************************ &routine calc_bl /* perform the calculations joinitem bl%site%.pat template_bl.dat ~ bl%site%.pat $recno pop100 /* do a frequency on the original block groups so we have just one population /* value for each block group... &if [exists bl_mrg.frq -info] &then &s d [delete bl_mrg.frq -info]
&sv alllist = 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 ~ 23 24 25 26 27 28 29 30 31 frequency bl_mrg.pat bl_mrg.frq STCNTRBLK P0010001 P0020001 P0030001 P0040001 P0040002 P0040003 P0040004 P0050001 P0050002 P0060001 P0060002 P0060003 P0060004 P0060005 &do t &list %alllist% P01100%t% &end end area endAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-43 &data arc info ARC SEL BL%site%.PAT RESELECT LW = '99' NSEL RELATE BL_MRG.FRQ 1 by STCNTRBLK ordered CALC BL0010001B = $1P0010001 * ( AREA / $1AREA ) CALC BL0020001B = $1P0020001 * ( AREA / $1AREA ) CALC BL0030001B = $1P0030001 * ( AREA / $1AREA ) CALC BL0040001B = $1P0040001 * ( AREA / $1AREA ) CALC BL0040002B = $1P0040002 * ( AREA / $1AREA ) CALC BL0040003B = $1P0040003 * ( AREA / $1AREA ) CALC BL0040004B = $1P0040004 * ( AREA / $1AREA ) CALC BL0050001B = $1P0050001 * ( AREA / $1AREA ) CALC BL0050002B = $1P0050002 * ( AREA / $1AREA ) CALC BL0060001B = $1P0060001 * ( AREA / $1AREA ) CALC BL0060002B = $1P0060002 * ( AREA / $1AREA ) CALC BL0060003B = $1P0060003 * ( AREA / $1AREA ) CALC BL0060004B = $1P0060004 * ( AREA / $1AREA ) &do Z &list %alllist% CALC BL01100%Z%B = $1P01100%Z% * ( AREA / $1AREA ) &end SEL BL%site%.PAT MOVEIT [quote %site%] TO SITE-ID MOVEIT [quote %wmu_name%] TO WMU_SETTING RESELECT LW = '99' NSEL MOVEIT STCNTRBLK TO BL-ID MOVEIT AREA TO P_AREA RESELECT LW = '99' MOVEIT 'W' TO BL-ID Q STOP &end
&return /* end of routine
/* ROUTINE calc************************************************************ &routine calc /* perform the calculations joinitem bgl%site%.pat template_bg.dat ~ bgl%site%.pat $recno land/water /* do a frequency on the original block groups so we have just one population /* value for each block group... &if [exists bg_lu.frq -info] &thenAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-44 &s d [delete bg_lu.frq -info]
&sv alllist = 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 ~ 23 24 25 26 27 28 29 30 31 &sv tlist = 02 03 04 05 06 07 08 09 10 11 12 13 14 frequency bg_lu.pat bg_lu.frq stcntrbg p0010001 /* Total persons p0060001 /* Persons Inside Urbanized Area p0060002 /* Persons Outside Urbanized Area p0060003 /* Persons in rural area on farm p0060004 /* Persons in rural area not on farm p0780009 /* Employed persons: Farming, forestry, and Fishing Ocupations h0010001 /* Total Housing Units h0050003 /* Housing Units, Rural Farm h0230001 /* Source of water: Public system or private company h0230002 /* Source of water: Drilled individual well h0230003 /* Source of water: Dug individual well h0230004 /* Some other water source &do t &list %alllist% p01300%t% /* Total Persons 1 through 85 & older &end end area end &sv ag_list = 39 40 41 42 43 44 45 46 47 48 49 50 additem bgl%site%.pat bgl%site%.pat farm_rat 8 12 f 6 &do fip &list %fips_list% &s st [substr %fip% 1 2] &s cny [substr %fip% 3 3] &sys echo %st% &sys echo %cny%
&data arc info ARC SEL BG_LU.FRQ SORT ON STCNTRBG SEL AG_CENSUS.DAT RESELECT ST = [QUOTE %st%] AND COU = [QUOTE %cny%] CALC $NUM1 = R_TOTFARM CALC $NUM2 = R_39_1 CALC $NUM3 = R_41_1 CALC $NUM4 = R_43_1Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-45 CALC $NUM5 = R_45_1 CALC $NUM6 = R_20084_1 /* Ratio SIC Beef cattle, except feedlots - was R_47_1 CALC $NUM7 = R_20085_1 /* Ratio SIC-Dairy farms - was R_49_1 CALC $NUM8 = R_40_39 CALC $NUM9 = R_42_41 /* Ratio Beef cows (number) to Beef cows (farms) CALC $NUM10 = R_44_43 /* Ratio Milk cows (number) to Milk cows (farms) CALC $NUM11 = R_46_45 CALC $NUM12 = R_48_47 CALC $NUM13 = R_50_49 CALC $NUM14 = R_PROD SEL BGL%site%.PAT RESEL COUNTY = [QUOTE %cny%] RESELECT LAND/WATER = 'L' RELATE BG_LU.FRQ 1 by STCNTRBG CALC P0010001B = $1P0010001 * ( AREA / $1AREA ) CALC P0060001B = $1P0060001 * ( AREA / $1AREA ) CALC P0060002B = $1P0060002 * ( AREA / $1AREA ) CALC P0060003B = $1P0060003 * ( AREA / $1AREA ) CALC P0060004B = $1P0060004 * ( AREA / $1AREA ) CALC P0780009B = $1P0780009 * ( AREA / $1AREA ) CALC H0010001B = $1H0010001 * ( AREA / $1AREA ) CALC H0050003B = $1H0050003 * ( AREA / $1AREA ) CALC H0230001B = $1H0230001 * ( AREA / $1AREA ) CALC H0230002B = $1H0230002 * ( AREA / $1AREA ) CALC H0230003B = $1H0230003 * ( AREA / $1AREA ) CALC H0230004B = $1H0230004 * ( AREA / $1AREA ) SEL BGL%site%.PAT CALC FARM_RAT = 0 RESELECT P0010001B GT 0 CALC FARM_RAT = P0060003B / P0010001B SEL BGL%site%.PAT RESELECT LAND/WATER = 'L' RELATE BG_LU.FRQ 1 by STCNTRBG &do z &list %alllist% CALC P13%Z% = $1P01300%Z% * ( AREA / $1AREA ) &end &do z &list %alllist% CALC P13%Z%F = P13%Z% * FARM_RAT &end &do z &list %alllist% CALC P13%Z%C = P13%Z%F * $NUM2 &end &do z &list %alllist% CALC P13%Z%B = P13%Z%F * $NUM6 /* USED TO BE $NUM3 OR R_41_1 &end &do z &list %alllist% CALC P13%Z%M = P13%Z%F * $NUM7 /* USED TO BE $NUM4 OR R_43_1Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-46 &end &do z &list %alllist% CALC P13%Z%P = P13%Z%F * $NUM14 &end CALC TOT_FARM = H0050003B * $NUM1 CALC AG39 = TOT_FARM * $NUM2 CALC AG40 = TOT_FARM * $NUM8 CALC AG41 = TOT_FARM * $NUM3 CALC AG42 = TOT_FARM * $NUM9 CALC AG43 = TOT_FARM * $NUM4 CALC AG44 = TOT_FARM * $NUM10 CALC AG45 = TOT_FARM * $NUM5 CALC AG46 = TOT_FARM * $NUM11 CALC AG47 = TOT_FARM * $NUM6 CALC AG48 = TOT_FARM * $NUM12 CALC AG49 = TOT_FARM * $NUM7 CALC AG50 = TOT_FARM * $NUM13 CALC PROD_FARM = TOT_FARM * $NUM14 CALC AG20084 = TOT_FARM * $NUM6 CALC AG20085 = TOT_FARM * $NUM7 RESELECT H0010001B GT 0 CALC WELL_RAT = ( H0230002B + H 0230003B + H0230004B ) / H0010001B /* ratio of private wells to total households SEL BGL%site%.PAT RESELECT LAND/WATER = 'L' RELATE FISHER.DAT 3 by STATE CALC BEEF_FARMER = P0060003B * $NUM6 CALC DAIRY_FARMER = P0060003B * $NUM7 CALC BEEF_FISHER = ( ( P0060003B * $3FISHER2P ) / 100 ) * $NUM6 CALC DAIRY_FISHER = ( ( P0060003B * $3FISHER2P ) / 100 ) * $NUM7 CALC BEEF_FARMER = BEEF_FARMER - BEEF_FISHER CALC DAIRY_FARMER = DAIRY_FARMER - DAIRY_FISHER CALC P1301P = P0060001 CALC P1302P = P0060002 CALC P1303P = $3FISHER1P CALC P1304P = P0060003 CALC P1305P = $3FISHER2P CALC P1306P = P0060004 CALC P1307P = $3FISHER3P CALC P1308P = P0010001 CALC P1309P = P0010001B RESELECT P0010001 GT 0 CALC REC_FISHER = ( ( ( ( ( P0060001 + P0060002 ) * $3FISHER1P ) + ( P0060003 * $3FISHER2P ) + ( P0060004 * $3FISHER3P ) ) / 100 ) / P0010001 ) SEL BGL%site%.PAT RESELECT H0010001B GT 0Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-47 CALC WELL_RAT = ( H0230002B + H 0230003B + H0230004B ) / H0010001B /* ratio of private wells to total households Q STOP &end

&if [exists %cenpath%/bgl_%wmu_name% -cover] &then kill %cenpath%/bgl_%wmu_name% all copy bgl%site% %cenpath%/bgl_%wmu_name% /* cursor temp1 declare BGL%site%.PAT info ro stcntrbg = '420710111 4' and lucode = 21 /* cursor temp1 open /* &do &while %:temp1.AML$NEXT% /* &sys echo HOME_GARD %:temp1.HOME_GARD% /* &sys echo REC_FISHER %:temp1.REC_FISHER% /* &sys echo GARD_FISHER %:temp1.GARD_FISHER% /* &sys echo BEEF_FARMER %:temp1.BEEF_FARMER% /* &sys echo BEEF_FISHER %:temp1.BEEF_FISHER% /* &sys echo DAIRY_FARMER %:temp1.DAIRY_FARMER% /* &sys echo DAIRY_FISHER %:temp1.DAIRY_FISHER% /* &sys echo P0010001 %:temp1.P0010001% /* cursor temp1 next /* &end /* cursor temp1 remove /* FISHER1P is the percentage of urban people who fished /* FISHER2P is the percentage of rural/farm people who fished /* FISHER3P is the percentage of rural/nonfarm people who fished
&end
&return /* end of routine
/* ROUTINE sumpop************************************************************* &routine sumpop
&data arc info ARC SEL BGL%site%.PAT MOVEIT [quote %site%] TO SITE-ID MOVEIT [quote %wmu_name%] TO WMU_SETTING RESELECT LAND/WATER = 'L' MOVEIT STCNTRBG TO BG-ID CALC AGE1 = P1301 CALC AGE1-5 = P1302 + P1303 + P1304 CALC AGE6-11 = P1305 + P1306 + P1307Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-48 CALC AGE12-19 = P1308 + P1309 + P1310 + P1311 + P1312 + P1313 + P1314 CALC AGE20- = P1315 + P1316 + P1317 + P1318 + P1319 + P1320 + P1321 + P1322 ~ + P1323 + P1324 + P1325 + P1326 + P1327 + P1328 + P1329 + P1330 + P1331 RESELECT LAND/WATER = 'W' MOVEIT 'W' TO BG-ID Q STOP &end &s pop_list = C B M P &do p &list %pop_list%
&data arc info ARC SEL BGL%site%.PAT RESELECT LAND/WATER = 'L' CALC AGE1%p% = P1301%p% CALC AGE1-5%p% = P1302%p% + P1303%p% + P1304%p% CALC AGE6-11%p% = P1305%p% + P1306%p% + P1307%p% CALC AGE12-19%p% = P1308%p% + P1309%p% + P1310%p% + P1311%p% + P1312%p% + P1313%p% + P1314%p% CALC AGE20-%p% = P1315%p% + P1316%p% + P1317%p% + P1318%p% + P1319%p% + P1320%p% + P1321%p% + P1322%p% ~ + P1323%p% + P1324%p% + P1325%p% + P1326%p% + P1327%p% + P1328%p% + P1329%p% + P1330%p% + P1331%p% Q STOP &end
&end
&return /* end of routine
/* ROUTINE add_wmu************************************************************* &routine add_wmu &s dolist = bl bgl &do x &list %dolist% &if [exists %x%temp2 -cover] &then kill %x%temp2 all identity %x%%site% %wmu_path%/wmu%site%%wmu_name% %x%temp2 poly .1 join dropitem %x%temp2.pat %x%temp2.pat %x%%site%# %x%%site%-id end kill %x%%site% all rename %x%temp2 %x%%site%Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-49 &end
&return /* end of routine
/* ROUTINE wrap_up************************************************************* &routine wrap_up /* convert the labelpoints to a point cover, project it to UTM and add the coords to the pat &if [exists bl_points -cover] &then kill bl_points all &if [exists bl_points_utm -cover] &then kill bl_points_utm all &if [exists bl_pnts_tmp -cover] &then kill bl_pnts_tmp all
centroidlabels bl%site% inside ae ec bl%site% label sel lw = 99 nsel put bl_points q &data arc info ARC SEL BGL%site%.PAT ALTER P0010001,TOTAL_BG_POP,,,,,,,, Q STOP &end

/* add wells and rec fisher to receptor points identity bl_points bgl%site% bl_pnts_tmp point kill bl_points all dropitem bl_pnts_tmp.pat bl_pnts_tmp.pat bl_points# bl_points-id end rename bl_pnts_tmp bl_points /* add wshd ids to points identity bl_points %outpath%/v2_%site% bl_pnts_tmp point kill bl_points all dropitem bl_pnts_tmp.pat bl_pnts_tmp.pat bl_points# bl_points-idAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-50 end rename bl_pnts_tmp bl_points /* add local wshd ids to points display 0 arcplot clearselect %wmu_path%/cir%site%%wmu_name% poly resel %outpath%/v2_%site% poly overlap %wmu_path%/cir%site%%wmu_name% poly &sv lwses = [listunique %outpath%/v2_%site% -poly wshd_num] q &s good_lwses &do ws_num &list %lwses% &if [exists %outpath%/%wmu_name%%ws_num% -cover] &then &do &if ^ [iteminfo %outpath%/%wmu_name %%ws_num% -poly local_area -exists] &then additem %outpath%/info!arc!%wmu_name%%ws_num%.pat %outpath%/info!arc!%wmu_name%%ws_num%.pat local_area 4 12 f 3 local_num &wo %outpath% &data arc info ARC SEL [translate %wmu_name%%ws_num%.pat] CALC LOCAL_AREA = AREA Q STOP &end &wo %work-dir% &if ^ [iteminfo %outpath%/%wmu_name %%ws_num% -poly wshd_num -exists] &then &do additem %outpath%/info!arc!%wmu_name%%ws_num%.pat %outpath%/info!arc!%wmu_name%%ws_num%.pat wshd_num 3 3 i &wo %outpath% &data arc info ARC SEL [translate %wmu_name%%ws_num%.pat] CALC WSHD_NUM = %ws_num% Q STOP &end &wo %work-dir% &end &s good_lwses = %good_lwses% %ws_num% &end &end &if [exists alllws -cover] &then kill alllws all mapjoin alllws &do j &list %good_lwses%Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-51 %outpath%/%wmu_name%%j% &end end identity bl_points alllws bl_pnts_tmp point kill bl_points all dropitem bl_pnts_tmp.pat bl_pnts_tmp.pat bl_points# bl_points-id end rename bl_pnts_tmp bl_points &if [exists bl_points.frq -info] &then &s d [delete bl_points.frq -info] frequency BL_POINTS.PAT bl_points.frq STCNTRBG end BL0010001B end
&data arc info ARC SEL BL_POINTS.PAT CALC BR_INDEX = BL_POINTS-ID MOVEIT [quote %ring% ] TO RING_SCEN CALC AGE1 = BL0110001B CALC AGE1-5 = BL0110002B + BL0110003B + BL0110004B CALC AGE6-11 = BL0110005B + BL0110006B + BL0110007B CALC AGE12-19 = BL0110008B + BL0110009B + BL0110010B + BL0110011B + BL0110012B + BL0110013B + BL0110014B CALC AGE20- = BL0110015B + BL0110016B + BL0110017B + BL0110018B + BL0110019B CALC AGE20- = AGE20- + BL0110020B + BL0110021B + BL0110022B + BL0110023B CALC AGE20- = AGE20- + BL0110024B + BL0110025B + BL0110026B + BL0110027B CALC AGE20- = AGE20- + BL0110028B + BL0110029B + BL0110030B + BL0110031B RELATE BL_POINTS.FRQ 1 by STCNTRBG RESEL BL0010001B GT 0 CALC HOME_GARD = BL0010001B * .38 CALC GARD_FISHER = HOME_GARD * REC_FISHER CALC REC_FISHER = ( BL0010001B - HOME_GARD ) * REC_FISHER CALC HOME_GARD = HOME_GARD - GARD_FISHER CALC RESIDENTS = BL0010001B - ( ( HOME_GARD + GARD_FISHER + REC_FISHER ) ) RESEL LUCODE = 21 CALC RESIDENTS = RESIDENTS - ( ( BEEF_FARMER + BEEF_FISHER + DAIRY_FARMER + DAIRY_FISHER ) * ( BL0010001B / $1BL0010001B ) ) Q STOPAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-52 &end /*Help to check calcs for residents /* cursor temp1 declare BL_POINTS.PAT info ro bl-id = '482339509 553A' /* cursor temp1 open /* &do &while %:temp1.AML$NEXT% /* &sys echo HOME_GARD %:temp1.HOME_GARD% /* &sys echo REC_FISHER %:temp1.REC_FISHER% /* &sys echo GARD_FISHER %:temp1.GARD_FISHER% /* &sys echo BEEF_FARMER %:temp1.BEEF_FARMER% /* &sys echo BEEF_FISHER %:temp1.BEEF_FISHER% /* &sys echo DAIRY_FARMER %:temp1.DAIRY_FARMER% /* &sys echo DAIRY_FISHER %:temp1.DAIRY_FISHER% /* &sys echo BL0010001B %:temp1.BL0010001B% /* &sys echo P0010001 %:temp1.P0010001% /* &sys echo TOTAL_BG_POP %:temp1.TOTAL_BG_POP% /* &sys echo RESIDENTS %:temp1.RESIDENTS% /* cursor temp1 next /* &end /* cursor temp1 remove
/* convert to utm coords project cover bl_points bl_points_utm /data1 /base/prj_files/albers83-utm%utmz%_83.prj addxy bl_points_utm kill bl_points all &if [exists %cenpath%/p1%ring%%wmu_name%.pop -info] &then &s d [delete %cenpath%/p1%ring%%wmu_name%.pop -info] pullitems bl_points_utm.pat %cenpath%/p1%ring%%wmu_name%.pop BR_INDEX P_AREA SITE-ID WMU_SETTING RING_SCEN RING_ID BL-ID UTM_ZONE X-COORD Y-COORD WELL_RAT RESIDENTS REC_FISHER GARD_FISHER HOME_GARD WSHD_NUMAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-53 LOCAL_NUM AGE1 AGE1-5 AGE6-11 AGE12-19 AGE20- BL0010001B BL0020001B BL0030001B BL0040001B BL0040002B BL0040003B BL0040004B BL0050001B BL0050002B BL0060001B BL0060002B BL0060003B BL0060004B BL0060005B &do t &list %alllist% BL01100%t%B &end end kill bl_points_utm all /* redo index nums so there aren't any missing places ************************** &wo %cenpath% /* clean up point with no humans or watersheds &data arc info ARC SEL [translate p1%ring%%wmu_name%.pop] RESEL WSHD_NUM = 0 PURGE Y SEL [translate p1%ring%%wmu_name%.pop] RESEL BL0010001B = 0 PURGE Y Q STOP &end &s i_cnt = 1 cursor id1 declare p1%ring%%wmu_name%.pop info rwAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-54 cursor id1 open &do &while %:id1.AML$NEXT% &s :id1.br_index = %i_cnt% &s :id1.utm_zone = %utmz% &s i_cnt = %i_cnt% + 1 cursor id1 next &end cursor id1 remove
&wo %work-dir%
/* &data arc info /* ARC /* SEL P1%site%.POP /* RESEL $RECNO = 1 /* PURGE /* Y /* Q STOP /* &end
/***************************************************************************** **** /* add bgl numbers to farm polys /* &call trim_bgl echo %i% &do i = 1 &to %iteration% &if [exists %cenpath%/frmbl%wmu_name%%i% -cover] &then kill %cenpath%/frmbl%wmu_name%%i% all &if [exists %cenpath%/farm%wmu_name%%i% -cover] &then &do identity %cenpath%/farm%wmu_name%%i% bgl%site% %cenpath%/frmbl%wmu_name%%i% /* process farm data &wo %cenpath% &if [exists frmbl%wmu_name%%i%.pop -inf o] &then &s d [frmbl%wmu_name%%i%.pop -info] pullitems frmbl%wmu_name%%i%.pat frmbl%wmu_name%%i%.pop AREA id_num wmu iteration farmindex farmareaAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-55 SITE-ID WMU_SETTING BG-ID imp_reach_idx P0010001B P0060001B P0060002B P0060003B P0060004B P0780009B H0010001B H0050003B well_rat TOT_FARM BEEF_FARMER DAIRY_FARMER BEEF_FISHER DAIRY_FISHER AGE1 AGE1-5 AGE6-11 AGE12-19 AGE20- AGE1F AGE1-5F AGE6-11F AGE12-19F AGE20-F /* AGE1C /* AGE1-5C /* AGE6-11C /* AGE12-19C /* AGE20-C AGE1B AGE1-5B AGE6-11B AGE12-19B AGE20-B AGE1M AGE1-5M AGE6-11M AGE12-19M AGE20-M /* AGE1P /* AGE1-5P /* AGE6-11P /* AGE12-19PAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-56 /* AGE20-P /* AG39 /* AG40 /* AG41 AG42 /* NUM BEEF COWS /* AG43 AG44 /* NUM DAIRY COWS /* AG45 /* AG46 /* PROD_FARM AG41 /* NUM BEEF FARMS - OLD WAY AG43 /* NUM DAIRY FARMS - OLD WAY AG20084 /* NUM BEEF FARMS AG20085 /* NUM DAIRY FARMS LAND/WATER end
&data arc info ARC SEL [translate frmbl%wmu_name%%i%.pop] RESEL LAND/WATER = 'W' PURGE Y SEL [translate frmbl%wmu_name%%i%.pop] RESEL AREA LT 0 PURGE Y Q STOP &end dropitem frmbl%wmu_name%%i%.pop frmbl%wmu_name%%i%.pop LAND/WATER
&end
&wo %work-dir% &end &call output
&return /* end of routine /* ROUTINE output************************************************************ &routine output &if [exists %cenpath%/p1%ring%%site%%wmu_name% -cover] &then kill %cenpath%/p1%ring%%site%%wmu_name% allAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-57 &if [exists p1%ring%%site%%wmu_name% -cover] &then kill p1%ring%%site%%wmu_name% all rename bl%site% p1%ring%%site%%wmu_name% copy p1%ring%%site%%wmu_name% %cenpath%/p1%ring%%site%%wmu_name% &if [exists p1%ring%%site%%wmu_name% -cover] &then kill p1%ring%%site%%wmu_name% all &if [exists p2%ring%%site%%wmu_name% -cover] &then kill p2%ring%%site%%wmu_name% all /* output rings****************** &if [exists %cenpath%/r%ring%%site%%wmu_name% -cover] &then kill %cenpath%/r%ring%%site%%wmu_name% all copy rng%site% %cenpath%/r%ring%%site%%wmu_name% kill rng%site% all
&return /* end of routine
/* ROUTINE clean************************************************************ &routine clean &if [exists bg%site% -cover] &then kill bg%site% all &if [exists bgl%site% -cover] &then kill bgl%site% all &if [exists bl%site% -cover] &then kill bl%site% all &if [exists lu%site% -cover] &then kill lu%site% all &if [exists bg_mrg -cover] &then kill bg_mrg all &if [exists bl_mrg -cover] &then kill bl_mrg all &if [exists bg_lu -cover] &then kill bg_lu all &if [exists cen_tmp -cover] &then kill cen_tmp all &if [exists rng%site% -cover] &then kill rng%site% all &if [exists cnty_temp.sum -info] &then &s d [delete cnty_temp.sum -info] &if [exists farm_utm -cover] &then kill farm_utm all &if [exists farm_temp -cover] &then kill farm_temp all &if [exists farm_rng -cover] &then kill farm_rng all &if [exists farm_lws -cover] &then kill farm_lws all &if [exists alllws -cover] &then kill alllws all &if [exists farm_ws -cover] &then kill farm_ws all &if [exists farm_pts -cover] &then kill farm_pts all &if [exists farm_pts_utm -cover] &then kill farm_pts_utm all &s d [delete farm_grd.dat -info] &if [exists big_aoi -cover] &then kill big_aoi all &if [exists bl_points.frq -info] &then &s d [delete bl_points.frq -info] &sys rm xx*Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-58 &return /* end of routine
/* ROUTINE sum_farm************************************************************ &routine sum_farm &do fip &list %fips_list% &if ^ [exists %cntypath%/bg9%fip% -cover] &then &do &s message = There was a problem with site %site% in hwir_pop. Youre missing %cntypath%/bg9%fip% &sys echo "missing the bg cover for county %fip%. re-do site %site%" &call alert &if [exists cnty_temp.sum -info] &then &s d [delete cnty_temp.sum -info] statistics %cntypath%/bg9%fip%.pat cnty_temp.sum LAND/WATER sum H0050003 end &s st [substr %fip% 1 2] &s cny [substr %fip% 3 3]
&data arc info ARC SELECT AG_CENSUS.DAT RESELECT ST = [QUOTE %st%] AND COU = [QUOTE %cny%] RELATE CNTY_TEMP.SUM 1 BY LAND/WATER CALC T_HU_FARM = $1SUM-H0050003 Q STOP &end
&data arc info ARC SELECT AG_CENSUS.DAT RESELECT T_HU_FARM GT 0 CALC R_TOTFARM = AG010001 / T_HU_FARM Q STOP &end &if [exists cnty_temp.sum -info] &then &s d [delete cnty_temp.sum -info] &end
&return /* end of routine /* ROUTINE rings************************************************************ &routine ringsAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-59 &if [exists rng%site% -cover] &then kill rng%site% all &if [exists rng%site%c -cover] &then kill rng%site%c all &s area = %type_val% &s x_cen = %:pop1.x-coord% &s y_cen = %:pop1.y-coord% /* get into arcedit display 9 arcedit
/* find the side of the wmu based on area &s hside = [sqrt %area%] / 2 &s corner = %hside% * [sqrt 2] &if %ring% = 'a' &then &s ring_list = 100 200 300 500 750 1000 1500 2000 &if %ring% = 'b' &then &s ring_list = 500 1000 2000 &if %ring% = 'c' &then &s ring_list = 250 500 1000 2000 createcover rng%site% /files10/hwir/p6720-06a/amllib/system/template ef arc /* generate dce or circle coord keyboard arctype circle add &do rings &list %ring_list% 2,%x_cen%,%y_cen% 2,%x_cen%,[calc %y_cen% + %corner% + %rings%] &end 9 /* save the new coverage and quit ae save quit /* clean the coverage clean rng%site% rng%site%c 0 .1
/* create labelsAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-60 createlabels rng%site%c 0 build rng%site%c /* clean up kill rng%site% all rename rng%site%c rng%site% additem rng%site%.pat rng%site%.pat ring_id 1 1 I
&s counter = 0 ae ec rng%site% poly &do rings &list %ring_list% &s counter = %counter% + 1 sel %x_cen%,[calc %y_cen% + %corner% + %rings% - 50] calc ring_id = %counter% &end

save quit &return /* end of routine /* ROUTINE alert************************************************************ &routine alert &sys touch test_mail &sys echo "mailx gtc << EOF" >> test_mail &sys echo %message% >> test_mail &sys echo "EOF" >> test_mail chmod +x test_mail &if [exists /rti/gtc/bin/test_mail -file] &then rm /rti/gtc/bin/test_mail mv test_mail /rti/gtc/bin/test_mail test_mail &return /* end of routine /* ROUTINE get_utm************************************************************ &routine get_utm display 0 arcplot clearselect %utm_zones% poly clearselect %sitecov% point resel %sitecov% points id_num = [quote %site%]Appendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-61 resel %utm_zones% poly overlap %sitecov% point &s utmz = [show select %utm_zones% poly 1 item utm_zone] q &return /* end of routineAppendix 9A GIS AML Program for Calcula ting Human Receptor Locations and Attributes

9-62 This page intentionally left blankAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-63 

# Appendix 9B GIS Arc Macro Language (AML) Program for Placing FarmsAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-64 This page intentionally left blankAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-65 

## Appendix 9B. GIS Arc Macro Language (AML) Program for Placing Farms

/*===================================================================

= /* RESEARCH TRIANGLE INSTITUTE /* CEMQA - GIS Program /* P.O. Box 12194 /* Research Triangle Park, NC 27709-2194 /*===================================================================

= /* /* PROGRAM: place_farms.aml /* &echo &on &args fsite fwmu_name fi fx fy &severity &warning &ignore &severity &error &routine errorhandler &sv ws_org = [show workspace] &s work-dir = /files8/hwir/census/pop &wo %work-dir% &s cenpath /files8/hwir/census_storage/c%fsite% &s wmu_path /files10/hwir/p6720-06a/data/sectors /* path of wmu covers &s aoi_path /files10/hwir/p6720-06a/data/aoi /* path of aoi covers &call place_farm
&return
/***************************************************************************** * /* ROUTINE errorhandler******************************************************* &routine errorhandler &severity &error &ignore &severity &warning &ignoreAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-66 &mess &on &wo %ws_org% cursor frm1 remove cursor frm2 remove cursor frm3 remove cursor tmp remove &sys echo An error has occured on site %fsite% &return &error An error has occurred in place_farms.aml. \~ Last Error: %AML$MESSAGE%\~ Thread: %AML$ERRORTHREAD%\~ File: %AML$ERRORFILE%\~ Line: %AML$ERRORLINE%
/***************************************************************************** * /***************************************************************************** * /***************************************************************************** * /* ROUTINE place_farm********************************************************* &routine place_farm &sys touch test.txt /* test for land application unit - add wmu if not lau &if %fwmu_name% <> 'lau' &then &do &if [exists bgl_tmp -cover] &then kill bgl_tmp all erase bgl%fsite% %wmu_path%/wmu%fsite%%fwmu_name% bgl_tmp poly .1 &end &else &do &if [exists bgl_tmp -cover] &then kill bgl_tmp all copy bgl%fsite% bgl_tmp &end

&call make_points
/******************************remove later &do j = 1 &to 40 &if [exists frm%j% -cover] &then kill frm%j% all &end
/* make the farms here &if [exists %cenpath%/farm%fwmu_name%%fi% -cover] &then kill %cenpath%/farm%fwmu_name%%fi% allAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-67 &if [exists bg_frq.dat -info] &th en &s [delete bg_frq.dat -info] frequency bgl_tmp.pat bg_frq.dat stcntrbg end end
&s index = 0 &s farms_exist = .false. cursor frm1 declare bg_frq.dat info ro cursor frm1 open &do &while %:frm1.AML$NEXT% &s tmp = %:frm1.stcntrbg% &if ^ [null %tmp%] &then &do &sys echo %tmp% &s sta = [substr [extract 1 %tmp%] 1 2] &s cnt = [substr [extract 1 %tmp%] 3 3] cursor frm2 declare us_size_ct.dat info ro st = [quote %sta%] and cou = [quote %cnt%] cursor frm2 open &s med = %:frm2.median% cursor frm2 remove cursor frm3 declare ag_census.dat info ro st = [quote %sta%] and cou = [quote %cnt%] cursor frm3 open &s beef_farms = %:frm3.AG020084% &s dairy_farms = %:frm3.AG020085% cursor frm3 remove &if %beef_farms% > 0 or %dairy_farms% > 0 &then &do /* figure radius from median acreage (meters) &s r = %med% * 43560 &s r = %r% / 10.76391 &s aream = %r% &s r = %r% / 3.1415927 &s r = [sqrt %r%] &ty %r%

ap clearsel bgl_tmp poly resel bgl_tmp poly area > [calc %aream% / 2] resel bgl_tmp poly stcntrbg = [quote %tmp%] resel bgl_tmp poly lucode = 21 resel bgl_tmp poly land/water = 'L' resel bgl_tmp poly h0050003 > 0Appendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-68 &s selected = [before [show select bgl_tmp poly] ,]
&if %selected% > 1 &then resel bgl_tmp poly random 1
&if %selected% < 1 &then &do clearsel bgl_tmp poly resel bgl_tmp poly area > 50000 resel bgl_tmp poly stcntrbg = [quote %tmp%] resel bgl_tmp poly lucode = 21 resel bgl_tmp poly land/water = 'L' resel bgl_tmp poly h0050003 > 0 &s selected = [before [show select bgl_tmp poly] ,]
&if %selected% > 1 &then resel bgl_tmp poly random 1 &end
&if %selected% < 1 &then &do clearsel bgl_tmp poly resel bgl_tmp poly stcntrbg = [quote %tmp%] resel bgl_tmp poly lucode = 21 resel bgl_tmp poly land/water = 'L' resel bgl_tmp poly h0050003 > 0 &s selected = [before [show select bgl_tmp poly] ,] &if %selected% > 1 &then resel bgl_tmp poly random 1 &s selected = [before [show select bgl_tmp poly] ,]
&end
writesel farm.sel q &if [exists farm_tmp -cover] &then kill farm_tmp all &if %selected% > 0 &then &do reselect bgl_tmp farm_tmp poly farm.sel &s index = %index% + 1 &s farms_exist = .true. &end /* &else &s farms_exist = .false. &if [exists farm_tmp.pat -info] &then &do cursor frm2 declare farm_tmp.pat info ro $recno = 2 cursor frm2 openAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-69 &s farea = %:frm2.area% cursor frm2 remove
/* test for smaller &if %farea% < %aream% &then &do copy farm_tmp frm%index% &sys echo created frm%index% >> test.txt &end
&else &do ap clearsel tmp_pts point resel tmp_pts point overlap farm_tmp poly resel tmp_pts point random 1 writesel farmpt.sel q &if [exists farm_pt -cover] &then kill farm_pt all reselect tmp_pts farm_pt point farmpt.sel

ap clearsel farm_tmp poly resel farm_tmp poly overlap tmp_pts point writesel onefarm.sel q &if [exists farm_tmp2 -cover] &then kill farm_tmp2 all reselect farm_tmp farm_tmp2 poly onefarm.sel kill farm_tmp all rename farm_tmp2 farm_tmp &s right_size = .false. &s tmp_r = %r% &do &until %right_size% &if [exists farm_pt_buf -cover] &then kill farm_pt_buf all &if [exists farm_pt_buf2 -cover] &then kill farm_pt_buf2 all buffer farm_pt farm_pt_buf # # %tmp_r% .1 point build farm_pt_buf clip farm_pt_buf farm_tmp farm_pt_buf2 cursor frm2 declare farm_pt_buf2.pat info ro $recno = 2 cursor frm2 open &s buf_area = %:frm2.area% cursor frm2 remove &if [calc %buf_area% + 100] > %aream% &then &s right_size = .true. &s tmp_r = %tmp_r% + 10 &endAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-70 copy farm_pt_buf2 frm%index% &sys echo created frm%index% >> test.txt &end &end &end /* check for beef and dairy exist &end /* bg not null cursor frm1 next &end /* do loop cursor frm1 remove /* put all farm polys into 1 file
lc &listlocal &if [exists farm%fwmu_name%%fi% -cover] &then kill farm%fwmu_name%%fi% all /* combine all the farms into 1 coverage &s it_exists = .false.
&if %index% > 0 &then &do &if %index% = 1 &then copy frm1 farm%fwmu_name%%fi% &else &do &do j = 1 &to %index% &if [exists frm%j% -cover] &then &do &if %j% = 1 &then copy frm1 farm%fwmu_name%%fi% &else &do ae &if [exists farm%fwmu_name%%fi% -cover] &then &s it_exists = .true. ec frm%j% poly sel all put farm%fwmu_name%%fi% &if %it_exists% &then y quit &end &end &end &end /* 236 &end /* 233 &if %farms_exist% &then &do clean farm%fwmu_name%%fi% &call attribute_farmAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-71 &end
/* clean &do j = 1 &to 20 &if [exists frm%j% -cover] &then kill frm%j% all &end &if [exists farm_pt -cover] &then kill farm_pt all &if [exists farm_pt_buf -cover] &then kill farm_pt_buf all &if [exists farm_pt_buf2 -cover] &then kill farm_pt_buf2 all &if [exists bgl_tmp -cover] &then kill bgl_tmp all &if [exists farm_tmp -cover] &then kill farm_tmp all &if [exists farm_tmp2 -cover] &then kill farm_tmp2 all &if [exists tmp_pts -cover] &then kill tmp_pts all
&return /* end of routine
/* ROUTINE attribute_farm********************************************************* &routine attribute_farm &if ^ [iteminfo farm%fwmu_name%%fi% - poly farmindex -exists] &then &do additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat farmindex 3 3 i additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat farmarea 4 12 f 3 additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat iteration 3 3 i additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat id_num 7 7 c additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat wmu 3 3 c additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat utm_zone 3 3 i additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat imp_reach_idx 4 4 I additem farm%fwmu_name%%fi%.pat farm%fwmu_name%%fi%.pat ratio 4 12 f 4
/* &data arc info /* ARC /* SEL [translate farm%fwmu_name%%fi%.pat] /* CALC RATIO = AREA / PERIMETER /* RESEL AREA LT 0 /* PURGE /* Y /* SEL [translate farm%fwmu_name%%fi%.pat] /* CALC FARMAREA = AREA /* CALC ITERATION = %fi% /* MOVEIT [quote %fsite%] TO ID_NUM /* MOVEIT [quote %fwmu_name%] TO WMU /* Q STOP /* &endAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-72 &s i_cnt = 1 cursor tmp declare farm%fwmu_name%%fi% poly rw area > 0 cursor tmp open &do &while %:tmp.AML$NEXT% &s :tmp.ratio = %:tmp.area% / ( %:tmp.perimeter% / 4 ) ** 2 &if %:tmp.area% > 20000 &then &do /* ( ^ ( %:tmp.ratio% < .4 and %:tmp.area% < 40000 ) ) or ( %:tmp.area% > 20000 ) &s :tmp.farmindex = %i_cnt% &s i_cnt = %i_cnt% + 1 &end cursor tmp next &end cursor tmp remove

ap clearsel farm%fwmu_name%%fi% poly resel farm%fwmu_name%%fi% poly farmindex < 1 and area > 0 &s selected = [before [show select farm%fwmu_name%%fi% poly] ,] clearsel farm%fwmu_name%%fi% poly resel farm%fwmu_name%%fi% poly farmindex > 0 &s pselected = [before [show select farm%fwmu_name%%fi% poly] ,] q

ae display 0 ec farm%fwmu_name%%fi% poly sel farmindex > 0 nsel &if %selected% > 0 &then delete sel all &if %pselected% > 0 &then &do calc farmarea = area calc iteration = %fi% moveit [quote %fsite%] to id_num moveit [quote %fwmu_name%] to wmu &end save q &end &if %pselected% > 0 &then copy farm%fwmu_name%%fi% %cenpath%/farm%fwmu_name%%fi%
&return /* end of routineAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-73 /* ROUTINE make_points********************************************************* &routine make_points &if [exists tmp_pts -cover] &then kill tmp_pts all

ae display 0 ec /files10/hwir/p6720-06a/data/supergrid/grd_at00 labels coo key sel all put tmp_pts ec tmp_pts labels sel all move 1,0,0 1,%fx%,%fy% save q build tmp_pts point
&return /* end of routineAppendix 9B GIS Arc Macro Language (AML) Program for Placing Farms

9-74 This page intentionally left blankAppendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-75 

# Appendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm SizeAppendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-76 This page intentionally left blankAppendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-77 

## Appendix 9C. GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

/*===================================================================

= /* RESEARCH TRIANGLE INSTITUTE /* CEMQA - GIS Program /* P.O. Box 12194 /* Research Triangle Park, NC 27709-2194 /*===================================================================

= /* /* PROGRAM: make_median.aml /* /* PURPOSE: calculates the median from irregularly grouped farm size /* catagories for each county in the ag census. /* /* INFO FILES NEEDED TO RUN: /* us_size_ct.dat /* FARM_SIZE_ITEMS.DAT /* /* ROUTINES: /* /* CALLED BY: /* /* CALLS TO: /* /* GLOBAL VAR'S: /* /* INPUT FILES: /* /* OUTPUT FILES: us_size_ct.dat /* /* NOTES: /* /* HISTORY: written by G. Conrad 10-25-98 /* /* CONTACT: gtc@rti.org /* /* PROJECT: HWIRAppendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-78 /*
/*===================================================================

======== &echo &on /* &args site &sv ws_org = [show workspace] &severity &warning &ignore &severity &error &routine errorhandler &sys touch errors_med.txt cursor pnt1 declare us_size_ct.dat info rw /* fips = [quote %site%] cursor pnt1 open &do &while %:pnt1.AML$NEXT% &s g = %:pnt1.P010001% / 2 &s cum_freq = 0.0 cursor pnt2 declare FARM_SIZE_ITEMS.DAT info ro cursor pnt2 open &s count = 1 &do &while %:pnt2.AML$NEXT% &sys echo [value :pnt1.[value :pnt2.ag_item]] &s cum_freq = %cum_freq% + [value :pnt1.[value :pnt2.ag_item]] &s tmp = %cum_freq% - %g% /* XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX &if %cum_freq% gt %g% and %:pnt2.lower% gt 1 &then &do &s low = %:pnt2.lower% &s up = %:pnt2.upper% &s intv = %:pnt2.interval% &s prev = %cum_freq% - [value :pnt1.[value :pnt2.ag_item]] &s g = %g% - %prev% &s f = [value :pnt1.[value :pnt2.ag_item]] &if %f% gt 0 &then &s :pnt1.median = %low% + ( ( %g% * %intv% ) / %f% ) &else &sys echo Problem with %:pnt1.st% %:pnt1.cou% >> errors_med.txt cursor pnt2 12 cursor pnt2 next &end &else cursor pnt2 next &s count = %count% + 1 &endAppendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-79 cursor pnt2 remove cursor pnt1 next &end cursor pnt1 remove &wo %ws_org% /*alert_me &return /* main

ITEMS in us_size_ct.dat /* 60001 Farms, (number) /* 60002 Land in farms, (acres) /* 60003 Average size of farm, (acres) /* 60020 Size of farm-1 to 9 acres, (farms) /* 60021 Size of farm-1 to 9 acres, (acres) /* 60022 Size of farm-10 to 49 acres, (farms) /* 60023 Size of farm-10 to 49 acres, (acres) /* 60024 Size of farm-50 to 69 acres, (farms) /* 60025 Size of farm-50 to 69 acres, (acres) /* 60026 Size of farm-70 to 99 acres, (farms) /* 60027 Size of farm-70 to 99 acres, (acres) /* 60028 Size of farm-100 to 139 acres, (farms) /* 60029 Size of farm-100 to 139 acres, (acres) /* 60030 Size of farm-140 to 179 acres, (farms) /* 60031 Size of farm-140 to 179 acres, (acres) /* 60032 Size of farm-180 to 219 acres, (farms) /* 60033 Size of farm-180 to 219 acres, (acres) /* 60034 Size of farm-220 to 259 acres, (farms) /* 60035 Size of farm-220 to 259 acres, (acres) /* 60036 Size of farm-260 to 499 acres, (farms) /* 60037 Size of farm-260 to 499 acres, (acres) /* 60038 Size of farm-500 to 999 acres, (farms) /* 60039 Size of farm-500 to 999 acres, (acres) /* 60040 Size of farm-1,000 to 1,999 ac,(farms) /* 60041 Size of farm-1,000 to 1,999 ac,(acres) /* 60042 Size of farm-2,000 ac or more, (farms) /* 60043 Size of farm-2,000 ac or more, (acres)

/* FARM_SIZE_ITEMS.DAT /* Ag_item Lower Upper Interval /* P060020 1 9 9 /* P060022 10 49 39 /* P060024 50 69 19 /* P060026 70 99 29 /* P060028 100 139 39Appendix 9C GIS Arc Macro Language (AML) Program for Calculating Median Farm Size

9-80 /* P060030 140 179 39 /* P060032 180 219 39 /* P060034 220 259 39 /* P060036 260 499 239 /* P060038 500 999 499 /* P060040 1000 1999 999 /* P060042 2000 2999 999

/*===================================================================

======= /* END OF PROGRAM /*===================================================================

======= /* ROUTINE errorhandler**************************************** &routine errorhandler &severity &error &ignore &severity &warning &ignore &mess &on &wo %ws_org% cursor pnt1 remove cursor pnt2 remove &return &error An error has occurred in make_median.aml. \~ Last Error: %AML$MESSAGE%\~ Thread: %AML$ERRORTHREAD%\~ File: %AML$ERRORFILE%\~ Line: %AML$ERRORLINE%Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

9-81 

# Appendix 9D Human Receptor Data for the Representative National Data Set: 201 Sites and 419 Settings

Table 9D-1. Human Receptor Data for the Representative National Data Set: 201 Sites and 419 Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-83Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

9-82 This page intentionally left blankAppendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

9-83 Table 9D-1. Human Receptor Data for the Representative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population 114001 WP0114001 320 15,295 0 130207 WP0130207 134 3,232 5 0.87 131104 SI0131104 226 7,065 2 0.86 131104 AT0131104 226 7,065 2 0.86 131207 SI0131207 139 7,188 0 131207 AT0131207 139 7,188 0 131508 LF0131508 280 11,453 0 131508 WP0131508 195 7,378 0 131508 SI0131508 210 7,851 0 131508 AT0131508 210 7,851 0 136703 LA0136703 128 1,346 2 2.26 136703 SI0136703 94 864 2 2.06 136703 AT0136703 94 864 2 2.06 220102 WP0220102 122 9,010 0 221207 WP0221207 345 13,692 2 0.13 223504 LF0223504 186 6,088 1 2.49 223504 WP0223504 203 6,493 1 2.79 223504 LA0223504 201 6,432 1 2.74 224002 WP0224002 164 6,020 0 231002 LF0231002 101 1,957 3 2.07 231106 LF0231106 221 7,691 0 231407 LF0231407 30 308 2 4.37 231610 SI0231610 321 35,125 0 231610 AT0231610 321 35,125 0 231911 WP0231911 302 9,236 0 231914 SI0231914 340 21,982 0 231914 AT0231914 340 21,982 0 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-84 232305 WP0232305 20 154 1 1.99 232313 LF0232313 62 859 1 6.40 232313 WP0232313 54 744 1 4.89 232313 SI0232313 54 723 1 4.71 232313 AT0232313 54 723 1 4.71 232402 LF0232402 327 12,868 1 0.14 232402 SI0232402 302 12,036 1 0.06 232402 AT0232402 302 12,036 1 0.06 232415 WP0232415 280 21,342 0 232415 SI0232415 279 21,313 0 232415 AT0232415 279 21,313 0 232501 LF0232501 220 6,340 0 232501 WP0232501 218 6,260 0 232705 SI0232705 206 5,937 4 5.34 232705 AT0232705 206 5,937 4 5.34 233601 SI0233601 282 7,513 0 233601 AT0233601 282 7,513 0 233603 LF0233603 237 5,081 1 0.34 234904 LF0234904 173 4,086 0 235301 LF0235301 472 13,525 3 2.54 312301 LA0312301 88 1,614 6 49.73 312301 SI0312301 85 1,518 4 44.45 312301 AT0312301 85 1,518 4 44.45 314202 LF0314202 259 16,715 0 321802 WP0321802 17 794 0 321802 SI0321802 16 773 0 321802 AT0321802 16 773 0 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-85 331006 SI0331006 123 4,240 3 0.14 331006 AT0331006 123 4,240 3 0.14 331902 WP0331902 26 357 2 0.65 331902 SI0331902 26 364 2 0.43 331902 AT0331902 26 364 2 0.43 332104 WP0332104 71 2,220 0 332104 LA0332104 117 3,670 0 332104 SI0332104 75 2,384 0 332104 AT0332104 75 2,384 0 332707 LF0332707 48 572 0 332707 WP0332707 57 809 0 332811 WP0332811 334 16,011 0 430108 WP0430108 9 10 2 0.69 430108 SI0430108 9 10 2 0.68 430108 AT0430108 9 10 2 0.68 430412 LF0430412 37 1,061 1 0.82 430412 SI0430412 36 986 1 0.76 430412 AT0430412 36 986 1 0.76 431912 LF0431912 16 13 2 2.71 431912 SI0431912 16 23 2 3.52 431912 AT0431912 16 23 2 3.52 432011 LF0432011 6 59 2 0.60 432106 SI0432106 56 519 3 5.93 432106 AT0432106 56 519 3 5.93 432716 SI0432716 9 8 2 0.27 432716 AT0432716 9 8 2 0.27 433201 LF0433201 14 143 1 0.17 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-86 433201 SI0433201 19 192 2 0.17 433201 AT0433201 19 192 2 0.17 433204 SI0433204 23 468 0 433204 AT0433204 23 468 0 433404 LF0433404 50 373 2 7.70 433404 SI0433404 49 384 2 7.86 433404 AT0433404 49 384 2 7.86 433408 SI0433408 102 3,284 0 433408 AT0433408 102 3,284 0 434505 SI0434505 178 4,819 2 1.35 434505 AT0434505 178 4,819 2 1.35 434804 SI0434804 37 992 3 0.23 434804 AT0434804 37 992 3 0.23 435510 LA0435510 43 569 2 0.26 435510 SI0435510 48 616 3 0.29 435510 AT0435510 48 616 3 0.29 436007 SI0436007 36 145 2 0.10 436007 AT0436007 36 145 2 0.10 436108 SI0436108 63 1,593 0 436108 AT0436108 63 1,593 0 530901 LA0530901 74 1,912 4 0.18 530901 SI0530901 67 1,665 2 0.10 530901 AT0530901 67 1,665 2 0.10 531301 SI0531301 33 412 1 0.03 531301 AT0531301 33 412 1 0.03 531502 SI0531502 165 3,841 3 0.31 531502 AT0531502 165 3,841 3 0.31 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-87 531702 LF0531702 87 2,469 0 531902 SI0531902 5 126 0 531902 AT0531902 5 126 0 534504 SI0534504 147 11,159 0 534504 AT0534504 147 11,159 0 613402 SI0613402 62 3,912 0 613402 AT0613402 62 3,912 0 620401 SI0620401 101 3,099 0 620401 AT0620401 101 3,099 0 620604 SI0620604 18 106 0 620604 AT0620604 18 106 0 621603 SI0621603 17 1,166 0 621603 AT0621603 17 1,166 0 621902 SI0621902 37 625 2 1.13 621902 AT0621902 37 625 2 1.13 622902 SI0622902 32 851 0 622902 AT0622902 32 851 0 625002 LF0625002 1 7 0 625002 SI0625002 1 7 0 625002 AT0625002 1 7 0 625501 LA0625501 18 53 1 6.81 631701 LA0631701 5 78 0 631903 LF0631903 37 599 0 631903 SI0631903 61 1,165 0 631903 AT0631903 61 1,165 0 632003 LF0632003 12 147 2 0.27 632003 SI0632003 13 159 2 0.27 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-88 632003 AT0632003 13 159 2 0.27 632606 LF0632606 12 52 1 0.61 632606 SI0632606 13 53 1 0.64 632606 AT0632606 13 53 1 0.64 632608 LF0632608 215 6,403 0 632608 SI0632608 180 5,372 0 632608 AT0632608 180 5,372 0 634001 SI0634001 45 1,052 2 1.17 634001 AT0634001 45 1,052 2 1.17 635301 SI0635301 133 7,527 0 635301 AT0635301 133 7,527 0 713618 SI0713618 209 5,856 0 713618 AT0713618 209 5,856 0 713705 LF0713705 25 279 0 713705 SI0713705 25 271 0 713705 AT0713705 25 271 0 715007 WP0715007 208 13,385 0 715216 WP0715216 182 13,225 0 716701 SI0716701 110 3,289 1 0.12 716701 AT0716701 110 3,289 1 0.12 720506 WP0720506 35 267 1 0.01 720803 LF0720803 147 6,518 1 0.02 720803 LA0720803 138 6,341 1 0.02 720803 SI0720803 131 6,045 1 0.02 720803 AT0720803 131 6,045 1 0.02 721305 WP0721305 266 15,554 0 722107 WP0722107 54 986 2 0.13 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-89 722503 SI0722503 165 5,709 0 722503 AT0722503 165 5,709 0 722505 SI0722505 395 22,261 0 722505 AT0722505 395 22,261 0 722705 LF0722705 379 23,693 0 723607 SI0723607 102 934 1 0.02 723607 AT0723607 102 934 1 0.02 724206 WP0724206 41 430 1 3.59 724206 SI0724206 42 441 1 3.68 724206 AT0724206 42 441 1 3.68 724301 WP0724301 92 4,168 1 0.06 724804 WP0724804 307 12,470 3 1.31 724909 WP0724909 177 4,622 0 730407 LF0730407 19 365 3 0.46 730407 SI0730407 19 344 2 0.27 730407 AT0730407 19 344 2 0.27 730502 WP0730502 361 6,839 3 0.68 730502 SI0730502 362 6,830 3 0.67 730502 AT0730502 362 6,830 3 0.67 730914 LF0730914 36 387 4 8.37 730914 WP0730914 38 387 4 7.94 730914 SI0730914 35 376 4 8.08 730914 AT0730914 35 376 4 8.08 731111 SI0731111 350 9,329 0 731111 AT0731111 350 9,329 0 731405 SI0731405 100 2,337 3 3.90 731405 AT0731405 100 2,337 3 3.90 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-90 731411 WP0731411 36 153 2 4.67 731412 WP0731412 75 1,943 1 0.05 731412 SI0731412 102 2,457 2 0.09 731412 AT0731412 102 2,457 2 0.09 731501 SI0731501 259 14,092 0 731501 AT0731501 259 14,092 0 731507 WP0731507 14 165 2 0.03 731507 SI0731507 19 296 3 0.04 731507 AT0731507 19 296 3 0.04 731514 LF0731514 71 3,024 0 731514 SI0731514 46 1,855 0 731514 AT0731514 46 1,855 0 731703 LF0731703 261 12,461 4 1.03 732110 LF0732110 406 11,978 0 732405 WP0732405 335 17,883 3 2.25 732510 WP0732510 119 3,550 1 0.23 733203 SI0733203 22 174 2 0.08 733203 AT0733203 22 174 2 0.08 733210 LF0733210 60 235 2 6.46 733210 SI0733210 57 258 2 7.22 733210 AT0733210 57 258 2 7.22 733302 WP0733302 143 6,166 3 3.98 733302 SI0733302 143 6,160 3 3.97 733302 AT0733302 143 6,160 3 3.97 733404 LF0733404 122 4,563 0 733404 WP0733404 107 3,891 0 733501 SI0733501 108 3,508 1 0.77 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-91 733501 AT0733501 108 3,508 1 0.77 733606 WP0733606 118 5,156 0 733606 SI0733606 93 3,685 0 733606 AT0733606 93 3,685 0 734604 WP0734604 192 6,488 1 0.003 735309 LF0735309 222 4,099 4 5.72 735309 SI0735309 203 3,780 4 5.47 735309 AT0735309 203 3,780 4 5.47 826707 SI0826707 126 11,258 0 826707 AT0826707 126 11,258 0 830601 LF0830601 22 133 1 0.32 830903 LF0830903 20 30 0 830903 SI0830903 16 17 0 830903 AT0830903 16 17 0 831102 WP0831102 297 12,528 0 831406 LF0831406 6 27 2 0.14 831406 SI0831406 7 23 2 0.10 831406 AT0831406 7 23 2 0.10 831904 LF0831904 62 804 2 0.07 831904 LA0831904 89 1,248 2 0.96 831904 SI0831904 69 930 2 0.66 831904 AT0831904 69 930 2 0.66 832304 LF0832304 616 28,951 0 832304 WP0832304 292 12,380 0 832510 WP0832510 43 900 2 0.24 832510 SI0832510 41 926 2 0.29 832510 AT0832510 41 926 2 0.29 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-92 832903 WP0832903 7 10 1 0.06 832903 SI0832903 9 15 1 0.07 832903 AT0832903 9 15 1 0.07 832904 SI0832904 47 987 3 4.41 832904 AT0832904 47 987 3 4.41 832909 SI0832909 329 13,261 3 2.36 832909 AT0832909 329 13,261 3 2.36 833001 LF0833001 148 2,388 4 5.90 833007 LF0833007 74 1,396 2 0.31 833007 SI0833007 50 893 2 0.23 833007 AT0833007 50 893 2 0.23 834009 SI0834009 86 4,303 0 834009 AT0834009 86 4,303 0 923004 WP0923004 69 3,331 4 3.44 930205 WP0930205 86 1,612 3 0.36 930205 SI0930205 88 1,623 3 0.39 930205 AT0930205 88 1,623 3 0.39 930301 LF0930301 10 12 0 930301 WP0930301 10 12 0 930301 SI0930301 11 13 0 930301 AT0930301 11 13 0 930702 LF0930702 7 8 1 0.12 930702 SI0930702 8 9 1 0.14 930702 AT0930702 8 9 1 0.14 932103 LF0932103 46 469 1 0.18 932103 WP0932103 45 457 1 0.18 932103 SI0932103 46 458 1 0.18 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-93 932103 AT0932103 46 458 1 0.18 932507 WP0932507 261 7,911 0 932507 SI0932507 262 7,940 0 932507 AT0932507 262 7,940 0 932509 LF0932509 45 419 3 0.34 932509 WP0932509 41 383 2 1.28 932509 SI0932509 48 394 2 1.30 932509 AT0932509 48 394 2 1.30 932903 LF0932903 16 519 0 932903 SI0932903 18 662 0 932903 AT0932903 18 662 0 933704 SI0933704 55 1,396 3 7.21 933704 AT0933704 55 1,396 3 7.21 1010805 LA1010805 299 7,546 3 1.75 1012203 LF1012203 69 2,041 2 0.02 1012203 WP1012203 69 2,041 2 0.02 1012203 SI1012203 69 2,079 2 0.02 1012203 AT1012203 69 2,079 2 0.02 1013209 SI1013209 48 174 2 2.02 1013209 AT1013209 48 174 2 2.02 1014805 LF1014805 50 1,289 1 0.05 1015510 LF1015510 12 54 1 0.03 1023705 SI1023705 118 3,100 2 2.53 1023705 AT1023705 118 3,100 2 2.53 1031503 LA1031503 68 2,281 2 0.17 1031507 SI1031507 331 11,409 3 2.44 1031507 AT1031507 331 11,409 3 2.44 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-94 1032715 SI1032715 123 2,282 1 1.04 1032715 AT1032715 123 2,282 1 1.04 1032802 LF1032802 46 344 2 0.01 1032802 LA1032802 51 426 2 0.01 1032802 SI1032802 46 344 2 0.01 1032802 AT1032802 46 344 2 0.01 1033107 SI1033107 143 5,089 0 1033107 AT1033107 143 5,089 0 1033114 SI1033114 39 401 1 0.01 1033114 AT1033114 39 401 1 0.01 1033202 LA1033202 161 4,578 1 0.44 1033602 LA1033602 147 3,819 3 1.10 1033602 SI1033602 56 1,368 2 0.17 1033602 AT1033602 56 1,368 2 0.17 1034005 WP1034005 43 884 3 1.10 1034005 LA1034005 51 1,053 3 1.58 1034210 LA1034210 63 677 2 0.63 1034210 SI1034210 50 401 2 0.61 1034210 AT1034210 50 401 2 0.61 1034406 SI1034406 21 299 0 0.00 1034406 AT1034406 21 299 0 0.00 1034805 SI1034805 288 4,465 2 7.38 1034805 AT1034805 288 4,465 2 7.38 1035117 SI1035117 224 10,023 1 1.68 1035117 AT1035117 224 10,023 1 1.68 1035405 SI1035405 87 2,279 2 4.58 1035405 AT1035405 87 2,279 2 4.58 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-95 1035508 LA1035508 99 2,158 2 9.61 1035508 SI1035508 88 1,965 2 6.99 1035508 AT1035508 88 1,965 2 6.99 1120904 SI1120904 94 4,744 1 0.07 1120904 AT1120904 94 4,744 1 0.07 1122705 SI1122705 37 390 0 1122705 AT1122705 37 390 0 1131103 SI1131103 647 44,352 0 1131103 AT1131103 647 44,352 0 1131802 LA1131802 4 10 0 1133902 LA1133902 260 6,376 0 1134405 LA1134405 115 2,010 2 2.68 1212301 SI1212301 99 5,899 0 1212301 AT1212301 99 5,899 0 1221704 WP1221704 275 17,833 0 1221704 SI1221704 264 17,621 0 1221704 AT1221704 264 17,621 0 1223404 SI1223404 274 13,441 0 1223404 AT1223404 274 13,441 0 1230111 SI1230111 41 451 3 3.09 1230111 AT1230111 41 451 3 3.09 1230206 SI1230206 33 430 1 1.71 1230206 AT1230206 33 430 1 1.71 1230517 SI1230517 47 2,004 4 1.55 1230517 AT1230517 47 2,004 4 1.55 1230919 WP1230919 306 23,989 0 1231101 LA1231101 141 7,728 0 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-96 1231101 SI1231101 136 7,293 0 1231101 AT1231101 136 7,293 0 1231705 LA1231705 35 494 1 0.05 1231705 SI1231705 33 482 1 0.05 1231705 AT1231705 33 482 1 0.05 1233101 SI1233101 146 18,106 0 1233101 AT1233101 146 18,106 0 1235205 WP1235205 60 1,200 2 3.49 1235205 SI1235205 60 1,202 2 3.51 1235205 AT1235205 60 1,202 2 3.51 1236637 SI1236637 135 5,913 0 1236637 AT1236637 135 5,913 0 1236652 SI1236652 70 3,288 1 0.02 1236652 AT1236652 70 3,288 1 0.02 1236732 WP1236732 157 7,614 0 1236810 WP1236810 184 23,054 0 1236820 SI1236820 29 378 2 0.35 1236820 AT1236820 29 378 2 0.35 1331103 SI1331103 250 7,584 0 1331103 AT1331103 250 7,584 0 1333001 LA1333001 30 177 3 0.11 1333701 WP1333701 373 16,604 0 1415407 WP1415407 409 26,816 0 1421506 WP1421506 266 13,733 0 1430107 LF1430107 93 6,611 0 1430107 SI1430107 63 5,222 0 1430107 AT1430107 63 5,222 0 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-97 1430404 SI1430404 157 5,345 0 1430404 AT1430404 157 5,345 0 1430602 SI1430602 77 10,089 0 1430602 AT1430602 77 10,089 0 1431515 SI1431515 8 7 0 1431515 AT1431515 8 7 0 1434022 SI1434022 252 32,104 0 1434022 AT1434022 252 32,104 0 1434802 SI1434802 441 15,558 0 1434802 AT1434802 441 15,558 0 1435317 LF1435317 195 3,650 0 1522504 LA1522504 42 1,088 2 1.29 1530605 LF1530605 21 165 1 5.30 1530605 SI1530605 20 145 1 4.78 1530605 AT1530605 20 145 1 4.78 1530808 SI1530808 76 4,351 0 1530808 AT1530808 76 4,351 0 1532401 WP1532401 35 833 1 0.20 1621808 LA1621808 95 1,032 1 1.40 1621808 SI1621808 81 920 1 1.25 1621808 AT1621808 81 920 1 1.25 1630106 LF1630106 46 305 3 0.09 1630106 WP1630106 45 275 3 0.08 1630106 SI1630106 46 287 3 0.08 1630106 AT1630106 46 287 3 0.08 1630401 WP1630401 493 17,343 0 1631701 LA1631701 150 3,340 3 0.09 (continued)Table 9D-1. (continued) Appendix 9D Human Receptor Data for the Represen tative National Data Set: 201 Sites and 419 Settings

Site ID Setting_ID Number of Human Receptor Points Total Human Receptor Population Number of Beef and Dairy Farms Total Beef and Dairy Farm Population

9-98 1631701 SI1631701 73 1,586 2 0.02 1631701 AT1631701 73 1,586 2 0.02 1632106 LA1632106 222 13,509 3 0.25 1632106 SI1632106 200 11,669 3 0.15 1632106 AT1632106 200 11,669 3 0.15 1632703 LF1632703 117 2,271 0 1633404 SI1633404 151 10,553 2 0.69 1633404 AT1633404 151 10,553 2 0.69 1633405 SI1633405 85 4,321 2 0.49 1633405 AT1633405 85 4,321 2 0.49 1635404 SI1635404 167 3,316 1 0.10 1635404 AT1635404 167 3,316 1 0.10 1721603 SI1721603 111 3,384 3 5.15 1721603 AT1721603 111 3,384 3 5.15