### Section 2.0 Spatial Framework



## 2-1 

# 2.0 Spatial Framework

The data collection effort for the representative national data set centers around the collection of site-based data for a representative sample of 201 nonhazardous industrial waste management facilities, along with the national and regional data necessary to complement this site-based data set. The 3MRA modeling system uses site-based modeling to provide spatial distributions of contaminants in a prespecified radius of interest around Industrial D facilities with land-based WMUs. To support this strategy, the data collection effort included mapping the modeled facilities nationally (using GIS), providing a spatial frame-of-reference around each facility within the AOI for the analysis, and collecting site-based and regional data within this framework.



# 2.1 Modeled Sites The 201 sites in the representative national data set are a random sample from EPA’s 1985 Screening Survey of Industrial Subtitle D Establishments (Westat, 1987), also referred to as the Industrial D Screening Survey or Industrial D. This survey was designed to characterize nonhazardous (RCRA Subtitle D) waste management practices for 17 industry groups and four land-based WMU types: landfills, waste piles, LAUs, and surface impoundments. Data from this survey have been used to represent Industrial D facility locations and WMU characteristics in a variety of RCRA regulatory initiatives. Although the Industrial D data are more than 10 years old, they represent the largest consistent set of data available on Industrial D WMU locations, dimensions, and waste volumes. Information on the survey design, response rates, and overall data quality and completeness may be found in Westat (1987), Clickner (1988), and Clickner and Craig (1988). The Industrial D screening survey contacted 15,844 industrial facilities. Of those, 2,850 reported that they managed waste in a landfill, LAU, surface impoundment, or waste pile. To adequately represent the 17 industry groups, EPA randomly selected 201 sites from these 2,850 facilities (see Section 3.0 for more details on site selection). Appendix 2A at the end of this section lists the 201 facilities by their industry group and shows the number of WMU types at each facility. The basic assumption for this analysis is that these data are representative of the types, characteristics, and locations of nonhazardous industrial WMUs.



# 2.2 Site Locations The Industrial D Screening Survey contained only address and zip code locations for the sampled facilities. Although zip code centroids were adequate for previous uses of the Industrial D data, the site-based data collection for the 3MRA modeling system required more accurate locations. Results of a pilot study showed that locational accuracy could have a great impact on the data collected around a site, especially for population and land use data. Because zip code

### Section 2.0 Spatial Framework

1 

### Because aerated tanks were not included in the Industria l D screening survey data, a tank is placed at every Industrial D site with a surface impoundment (see Section 3) ; thus, every surface impoundment site has at least two settings, surface impoundment and aerated tank.



## 2-2 centroid locations can be off by 2 km or more, facilities can be displaced from urban to rural settings or vice versa. Accuracy of the site location information was improved through a variety of techniques, including the following:



## # Matching facilities to EPA’s Location Reference Tables (LRT) from the Envirofacts database to obtain the Agency’s most reliable location,



## # Identifying zip code centroids using GIS software (for sites that could not be matched to the LRT), and



## # Visually placing sites using interactive ArcView software based on land use, WMU features (e.g., large surface impoundments), and topographic maps (when available). Appendix 2A provides the best locations obtained for each of the 201 Industrial D facilities. Appendix 2B describes the facility location effort in detail, including the source for each location and the rationale for every manual site location adjustment. In essence, the effort helped to ensure that all Industrial D locations used in the representative national data set are a reasonable representation of current and future industrial nonhazardous waste management facilities. 

# 2.3 Settings and Area of Interest (AOI) Based on sensitivity analysis results for the Air Module, EPA has defined the AOI for the representative national data set as the area encompassed by a circle defined by a 2 km radius extending from the corner of a square WMU. Many Industrial D sites have multiple WMU types; when this occurs, multiple AOIs and “settings” are defined. A setting is the basic modeling unit for the 3MRA modeling system and is defined as each unique WMU type/site combination. Thus, a site with a landfill and a waste pile would constitute two settings. There are 419 unique site/WMU settings across the 201 sites selected for therepresentative national data set. Each of these settings is modeled independently and all sitebased data are passed to the 3MRA modeling system with a unique setting identification number, Setting_ID. The Setting_ID is simply the WMU type present in the Industrial D data 1 

## (landfill, waste pile, LAU, surface impoundment, and/or aerated tank) plus the seven-digit Industrial D Site ID. Thus, if Industrial D site 1234567 has a landfill and a waste pile present, it would have two settings: LF1234567 and WP1234567. Appendix 2A includes the WMU types present at each of the Industrial D facility sites; a full list of the 419 settings included in the representative national data set is provided in the Appendices to Section 3.

### Section 2.0 Spatial Framework



## 2-3 

# 2.4 Regional Assignments Regional assignments, including meteorologi cal station, USGS hydrologic region, and ground water class, are necessary so that the 3MRA modeling system can assign the correct regional data to each site/setting. Meteorological station and USGS hydrologic region (Seaber et al., 1987) were assigned using GIS overlays as described in Section 4.0 and Section 6.0, respectively. Assignment of ground water class (i .e., hydrogeologic setting) is described in U.S. EPA (1996). Appendix 2A provides these regional assignments for all 201 Industrial D facilities. 

# 2.5 Site Layout, Spatial Data Layers, and Grid Database Collection of site-based data for the representative national data set centered around the use of GIS technology (ArcInfo and ArcView software) to create several key spatial data layers for each site/WMU setting, as shown in Figure 2-1. These key areas are



## # Human receptor points , defined by U.S. Census block centroids (residents) and randomly placed farms based on block group (beef and dairy farmers), agricultural census, and land use data (see Section 9.0). These serve as points to calculate exposure concentrations in various media and to estimate risks to human receptors.



## # Ecological habitats , areas with assigned ecological receptors, defined by land use and other ecologically relevant data (see Section 13.0). These areas perform a similar function as the human receptor points for ecological receptors.



## # Watersheds , delineated using digital elevation models (DEMs) of topography or manually, based on Reach File (RF) stream networks (see Section 5.0). Watershed subbasins provide the input data and output spatial framework necessary to model contaminant deposition, erosion, and overland transport, as well as resultant soil concentrations, in the LAU, Waste Pile, and Watershed Modules.



## # Waterbodies (lakes, streams, and wetlands), defined by DEMs, RF data, land use data, and/or the National Wetlands Inventory (NWI; see Section 5.0). These provide the input data and output spatial framework necessary to model contaminant deposition, fate, and transport and the resulting water column and sediment concentrations in streams and lakes. In the GIS, each of these spatial data layers is composed of two-dimensional (2-D) polygons, with the exception of streams, which are defined by one-dimensional (1-D) vectors (stream reaches). Because these polygon coverages could not be exported directly to the 3MRA modeling system, each spatial data layer was defined in terms of a base grid composed of 100 × 100 m cells, which roughly correspond to the minimum resolution of several site-specific data types (i.e., land use, topographic, and soil).

### Section 2.0 Spatial Framework



## 2-4 Figure 2-1. Site-based spatial overlays for the 3MRA modeling system spatial framework.

### Section 2.0 Spatial Framework



## 2-5 This base grid (or x,y coordinate system) serves as the basis for defining receptor points at which the Air and Aquifer Modules produce contaminant concentrations (and deposition rates for the Air Module) in terms of distance and direction from the WMU contaminant source. To provide the 3MRA modeling system’s SLP with the data necessary to specify air points, spatial data are passed to the system using this site coordinate system for the following data layers:



## # Watersheds 

## # Waterbodies 

## # Farms 

## # Human receptor points 

## # Wells (human receptor points with drinking water wells) 

## # Ecological habitats. These data are passed as six separate data tables within the “grid” database, along with the Setting_ID and the necessary index (e.g., watershed number). Figure 2-2 shows the structure of these data tables. The site coordinate system uses x,y coordinates (in meters) relative to a 0,0 georeference point, which is defined as the facility centroid. The 3MRA modeling system also requires specification of the georeference point using latit ude and longitude in the Universal Transverse Mercator (UTM) coordinate system. This requires conversion of the Albers meters GIS coordinates to UTM. The grid tables are created using GIS by overlaying coverage of spatial data (e.g., watersheds) with the standard grid. If the centroid of a grid cell intersected a polygon, it receives the identifier for that polygon (see Figure 2-3). The resulting table from this overlay is passed on to the database processors as the table of grid cell IDs that represent that spatial feature. The database processors then use the standard grid table of x,y points to convert the real-world UTM coordinates to a set of x,y points centered about 0,0.

### Section 2.0 Spatial Framework



## 2-6 ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE AquWell

ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE Farm

ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE Habitat

ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE HumRcp

ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE WBNRch

ID LONG Setting_ID TEXT(9) (IE) LocX DOUBLE (IE) LocY DOUBLE (IE) LocZ DOUBLE Index1 INT (IE) Index2 INT (IE) Fraction DOUBLE WSSub 

# Table Structure for 3MRA Grid Database

Figure 2-2. Table format and content for the 3MRA modeling system grid database.

Figure 2-3. Transfer of watershed polygons to 100 × 100 m template grid.

### Section 2.0 Spatial Framework



## 2-7 A template grid was created to cover the largest AOI of the 419 site/WMU settings. This way, only one grid needed to be created for use with all the sites. The largest WMU from the 201 selected sites (1,618,800 m 2 

## at site 0431912) was used to define the template grid for the example data set. Because the template grid was created the same way for each site (centered on the site location) the cell centroid x,y coordinates were always the same delta x and delta y from the site centroid (0,0). As a result, only one grid definition file needed to be created. The grid definition file consisted of the cell address, the x distance, and the y distance. A cell’s UTM coordinates can be determined by simply adding the x and y distance from the grid definition file to the facility centroid UTM coordinates. Cell ordering starts at 1 in the upper left corner and works its way across horizontally and then down. 

# 2.6 Quality Assurance/Quality Control General QA/QC of the spatial aspects of the data collection and processing effort included checks to ensure accuracy of facility location, proper registration (alignment) of GIS coverages, proper placement of grid templates, a nd accurate transfer of grid information to the 3MRA modeling system grid database. These QC activities included



## # Visual review of each facility/WMU location and manual relocation as necessary to ensure reasonable location prior to GIS processing of spatial data (see Appendix 2B),



## # Automatic regeneration of the grid template for a site prior to GIS postprocessing of spatial data to ensure proper correspondence with the facility centroid,



## # Generation and visual review of thumbnail images of all spatial data for every site to ensure accurate registration and collocation of all data layers, and



## # Visual checks of a subset of sites in the grid database against original GIS coverages to ensure accurate data processing and transfer. QA/QC of specific data layers (i.e., human receptors, habitats, watersheds, and waterbodies) is discussed in the section describing data collection for each data type.



# 2.7 Issues and Uncertainties Overall, one of the most significant general uncertainties with the spatial data in therepresentative national data set is the accuracy of facility location and its impacts on the sitebased data collected around each site. Appendix 2B discusses such locational uncertainties in some detail. However, these locational uncertainties are likely to be significant only in terms of a site-specific analysis at certain sites, and 3MRA modeling system is site-based, not site-specific. EPA believes that the location review and adjust ment efforts described in Appendix 2B resulted in site locations representative of current and future locations of Industrial D WMUs, and, as such, these locations are adequate and appropriate for a nationwide site-based analysis. EPA

### Section 2.0 Spatial Framework



## 2-8 emphasizes that the site-based data collected for the 3MRA representative national data set are not intended to be used for site-specific risk assessments. Other issues and uncertainties associated with specific site-based data layers are found in the sections of this report discussing each data type.



# 2.8 References Clickner, Robert. 1988. “Sampling weights for the industrial Subtitle D screening survey.” Memorandum to Zubair Saleem (U.S. Environmental Protection Agency) from Robert Clickner (Westat, Inc.), Rockville, MD. July 28. Clickner, Robert P., and Jim Craig. n.d. Using Business Establishment Size in an Environmental Survey (Unpublished). Seaber, P. R., F. P. Kapinos, and G. L. Knapp. 1987. Hydrologic Unit Maps . U.S. Geological Survey Water-Supply Paper 2294. Washington, DC: U.S. Government Printing Office. U.S. EPA (Environmental Protection Agency). 1996. EPA’s Composite Model for Leachate Migration with Transformation Products; EPACMTP: Background Document for Metals. Volume 1: Methodology. Washington, DC: U.S. Environmental Protection Agency, Office of Solid Waste. Westat, Inc. 1987. Screening Survey of Industrial Subtitle D Establishments

. Draft Final Report. Prepared for the U.S. Environmental Protection Agency. Rockville, MD: Westat, Inc. December.

### Appendix 2A 201 Industrial D Waste Management Sit es Used in the Representative National Data Set



## 2-9 

# Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data Set

Table 2A-1. 201 Industrial D Waste Management Sites Used in the Example 3MRA Data Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11

### Appendix 2A 201 Industrial D Waste Management Sit es Used in the Representative National Data Set



## 2-10 This page intentionally left blank.

## 2-11 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetTable 2A-1. 201 Industrial D Waste Management SitesUsed in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU Type1 - Organic Chemicals0130207 IA Rural 41.399742 -91.06297 Moline, IL Upper Mississippi Bedded Sedimentary Rock WP0136703 NM Rural 35.19942 -103.71577 Amarillo, TX Arkansas-White-Red Alluvial Basins Valleys and Fans AT, LAU, SI0131207 NY Urban 43.079444 -79.008889 Buffalo, NY Great Lakes Bedded Sedimentary Rock AT, SI0114001 PA Urban 40.49308 -80.07914 Pittsburgh, PA Ohio Bedded Sedimentary Rock WP0131508 TN Urban 36.52501 -82.53999 Bristol, TN Tennessee Bedded Sedimentary Rock AT, LF, SI, WP0131104 WI Rural 42.66416 -89.05569 Rockford, IL Upper Mississippi Bedded Sedimentary Rock AT, SI2 - Primary Iron and Steel0233603 AL Rural 33.541515 -86.543034 Huntsville, AL South Atlantic-Gulf Bedded Sedimentary Rock LF0232705 GA Rural 34.1769 -84.81757 Atlanta, GA SouthAtlantic-Gulf Bedded Sedimentary Rock AT, SI0231610 IL Urban 41.73503 -87.54159 Chicago, IL Great Lakes Bedded Sedimentary Rock AT, SI0231002 IN Rural 40.192049 -84.981029 Dayton, OH Ohio Till and Till Over Outwash LF0235301 IN Urban 39.9335 -85.38004 Indianapolis, IN Ohio Till and Till Over Outwash LF0231911 MI Urban 43.447145 -83.920814 Flint, MI Great Lakes Bedded Sedimentary Rock WP0231914 MI Urban 42.256748 -83.135334 Detroit, MI Great Lakes Bedded Sedimentary Rock AT, SI0231106 NJ Rural 40.11836 -74.81713 Philadelphia, PA Mid-Atlantic Sand and Gravel LF0221207 OH Urban 40.292475 -84.162526 Dayton, OH Ohio Bedded Sedimentary Rock WP0223504 OH Urban 40.850867 -81.763907 Akron/Canton, OH Ohio Sand and Gravel LAU, LF, WP0232415 OH Urban 41.457226 -81.688288 Cleveland, OH GreatLakes Bedded Sedimentary Rock AT, SI, WP0232402 PA Urban 39.970278 -75.815833 Wilmington, DE Mid-Atlantic Metamorphic and Igneous AT, LF, SI0232501 PA Rural 41.26468 -80.4838 Youngstown, OH Ohio Bedded Sedimentary Rock LF, WP0234904 PA Rural 41.02221 -75.19536 Allentown, PA Mid-Atlantic Bedded Sedimentary Rock LF0220102 SC Urban 32.834906 -79.948129 Charleston, SC South Atlantic-Gulf Bedded Sedimentary Rock WP0232313 TX Rural 32.43605 -95.36401 Shreveport, LA Texas-Gulf Bedded Sedimentary Rock AT, LF, SI, WP0231407 TX Rural 32.46527 -97.02675 Fort Worth, TX Texas-Gulf Bedded Sedimentary Rock LF0233601 VA Urban 38.064696 -78.874709 Roanoke, VA Mid-Atlantic Bedded Sedimentary Rock AT, SI0232305 VT Rural 43.969506 -72.689212 Burlington, VT NewEngland Unconsolidatedand SemiconsolidatedShallow AquifersWP0224002 WI Urban 43.86402 -91.22462 Moline, IL Upper Mississippi Bedded Sedimentary Rock WP(continued)

## 2-12 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)3 - Fertilizer and Agricultural Chemicals0331006 AR Rural 34.563889 -90.652778 Memphis, TN Lower Mississippi Alluvial Basins Valleys and Fans AT, SI0332707 FL Rural 27.88554 -81.94815 Tampa, FL South Atlantic-Gulf Bedded Sedimentary Rock LF, WP0314202 NY Urban 42.711063 -73.671455 Albany, NY Mid-Atlantic Sand and Gravel LF0332811 OH Urban 40.59397 -83.10857 Columbus, OH Ohio Bedded Sedimentary Rock WP0331902 OK Rural 36.439167 -99.468611 Dodge City, KS Arkansas-White-Red Unconsolidated and SemiconsolidatedShallow AquifersAT, SI, WP0321802 OR Rural 45.615336 -122.7105 Portland, OR Pacific Northwest Alluvial Basins Valleys and Fans AT, SI, WP0332104 TX Rural 35.642778 -101.42694 Amarillo, TX Arkansas-White-Red Unconsolidated and SemiconsolidatedShallow AquifersAT, LAU, SI,WP0312301 VA Rural 38.42827 -78.94495 Roanoke, VA Mid-Atlantic Bedded Sedimentary Rock AT, LAU, SI4 - Electric Power Generation0432011 AL Rural 34.703889 -87.118889 Huntsville, AL Tennessee Bedded Sedimentary Rock LF0434505 CA Rural 32.847146 -115.56736 Phoenix, AZ California Sand and Gravel AT, SI0435510 IL Rural 40.27633 -90.08052 Peoria, IL Upper Mississippi Bedded Sedimentary Rock AT, LAU, SI0433201 IN Rural 41.21534 -87.0191 South Bend, IN Upper Mississippi Till and Till Over Outwash AT, LF, SI0431912 KS Rural 38.35827 -94.63423 Kansas City, MOMissouri Bedded Sedimentary Rock AT, LF, SI0432716 MN Rural 47.261 -93.674 Duluth, MN Upper Mississippi Bedded Sedimentary Rock AT, SI0433408 MT Rural 45.892 -106.632 Miles City, MT Missouri Alluvial Basins Valleys and Fans AT, SI0434804 NC Rural 35.38401 -78.07439 Raleigh-Durham, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI0436007 NC Rural 35.5871 -79.04772 Raleigh-Durham, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI0436108 NC Rural 35.18328 -81.01201 Charlotte, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI0430108 NE Rural 40.36094 -95.64231 Kansas City, MO Missouri Alluvial Basins Valleys and Fans AT, SI, WP0430412 OH Rural 41.78825 -81.14677 Cleveland, OH GreatLakes Bedded Sedimentary Rock AT, LF, SI0432106 PA Rural 40.79771 -75.11741 Allentown, PA Mid-Atlantic Bedded Sedimentary Rock AT, SI0433204 SC Rural 33.330278 -79.357222 Charleston, SC South Atlantic-Gulf Unconsolidated and SemiconsolidatedShallow AquifersAT, SI0433404 WY Rural 42.0824 -104.94946 Cheyenne, WY Missouri Alluvial Basins Valleys and Fans AT, LF, SI5 - Plastic and Resins Manufacturer0534504 GA Urban 33.84175 -84.23034 Atlanta, GA SouthAtlantic-Gulf Metamorphic and Igneous AT, SI0531301 IL Rural 39.84983 -89.27569 Springfield, IL Upper Mississippi Bedded Sedimentary Rock AT, SI(continued)

## 2-13 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)0530901 OH Rural 41.372916 -82.542933 Cleveland, OH GreatLakes Unconsolidatedand SemiconsolidatedShallow AquifersAT, LAU, SI0531502 OH Urban 39.03921 -82.62841 Huntington, WV Ohio Unconsolidated and SemiconsolidatedShallow AquifersAT, SI0531702 TX Rural 35.66336 -101.45024 Amarillo, TX Arkansas-White-Red Unconsolidated and SemiconsolidatedShallow AquifersLF0531902 TX Urban 29.72675 -95.13189 Houston, TX Texas-Gulf Sand and Gravel AT, SI6 - Inorganic Chemicals0622902 AZ Rural 31.935764 -111.0029 Tucson, AZ Lower Colorado Alluvial Basins Valleys and Fans AT, SI0625002 GA Rural 32.2 -81.166667 Savannah, GA South Atlantic-Gulf Bedded Sedimentary Rock AT, LF, SI0634001 GA Rural 34.13254 -84.77666 Atlanta, GA SouthAtlantic-Gulf Bedded Sedimentary Rock AT, SI0613402 IL Urban 38.586459 -90.176488 St. Louis, MO Upper Mississippi Bedded Sedimentary Rock AT, SI0621902 KS Rural 38.03371 -97.97337 Wichita, KS Arkansas-White-Red Alluvial Basins Valleys and Fans AT, SI0631903 LA Urban 30.23167 -93.27781 Lake Charles, LA Lower Mississippi Sand and Gravel AT, LF, SI0635301 NV Urban 36.04434 -114.99514 Las Vegas, NV Lower Colorado Bedded Sedimentary Rock AT, SI0632608 OR Rural 45.56941 -122.7448 Portland, OR Pacific Northwest Alluvial Basins Valleys and Fans AT, LF, SI0620401 TX Urban 29.758611 -95.176389 Houston, TX Texas-Gulf Sand and Gravel AT, SI0621603 TX Rural 29.701746 -95.082965 Houston, TX Texas-Gulf Sand and Gravel AT, SI0625501 TX Rural 29.99645 -94.96404 Houston, TX Texas-Gulf Sand and Gravel LAU0631701 TX Rural 29.71475 -95.07624 Houston, TX Texas-Gulf Sand and Gravel LAU0632003 TX Rural 32.437778 -94.688889 Shreveport, LA Texas-Gulf Bedded Sedimentary Rock AT, LF, SI0632606 TX Rural 35.48185 -101.0562 Amarillo, TX Arkansas-White-Red Unconsolidated and SemiconsolidatedShallow AquifersAT, LF, SI0620604 UT Rural 40.7375 -111.98814 Salt Lake City, UT Great Basin Alluvial Basins Valleys and Fans AT, SI7 - Stone, Clay, Glass, and Concrete0713705 AZ Rural 32.833 -111.734 Phoenix, AZ Lower Colorado Alluvial Basins Valleys and Fans AT, LF, SI0715216 CA Urban 33.89933 -117.82175 Los Angeles, CA California Coastal Beaches WP0731411 CA Rural 37.091066 -120.24545 Fresno, CA California Sand and Gravel WP0732405 CA Urban 37.65484 -121.02633 Sacramento, CA California Sand and Gravel WP0733203 CA Rural 37.71502 -121.49048 Sacramento, CA California Sand and Gravel AT, SI0722503 CO Urban 39.807664 -105.00613 Boulder, CO Missouri Bedded Sedimentary Rock AT, SI(continued)

## 2-14 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)0720803 FL Rural 27.07543 -82.38693 Tampa, FL South Atlantic-Gulf Coastal Beaches AT, LAU, LF, SI0722107 FL Rural 26.87084 -82.00256 Tampa, FL South Atlantic-Gulf Coastal Beaches WP0722505 FL Urban 25.99577 -80.18024 Miami, FL South Atlantic-Gulf Bedded Sedimentary Rock AT, SI0730502 IL Urban 39.00298 -87.748337 Evansville, IN Ohio Bedded Sedimentary Rock AT, SI, WP0731514 IL Rural 42.38881 -87.81145 Chicago, IL Great Lakes Bedded Sedimentary Rock AT, LF, SI0732510 IL Rural 41.61892 -88.20404 Chicago, IL Upper Mississippi Bedded Sedimentary Rock WP0716701 IN Rural 38.06725 -87.26451 Evansville, IN Ohio Till and Till Over Outwash AT, SI0735309 KS Rural 37.2165 -95.69048 Tulsa, OK Arkansas-White-Red Bedded Sedimentary Rock AT, LF, SI0733302 KY Urban 37.64289 -84.78751 Lexington, KY Ohio Bedded Sedimentary Rock AT, SI, WP0731412 MA Rural 42.5495 -71.51555 Boston, MA New England Metamorphic and Igneous AT, SI, WP0720506 ME Rural 44.65533 -67.71774 Portland, ME New England Sand and Gravel WP0721305 MI Urban 42.27879 -83.12807 Detroit, MI Great Lakes Bedded Sedimentary Rock WP0724301 MS Rural 34.786143 -89.449686 Memphis, TN Lower Mississippi Sand and Gravel WP0724206 NC Rural 35.77042 -80.60004 Greensboro, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI, WP0731507 NC Rural 34.74411 -79.39153 Raleigh-Durham, NC SouthAtlantic-Gulf Unconsolidated and SemiconsolidatedShallow AquifersAT, SI, WP0733501 NC Rural 35.37242 -82.48649 Asheville, NC Tennessee Metamorphic and Igneous AT, SI0724909 ND Rural 48.14514 -103.65068 Miles City, MT Missouri Unconsolidated and SemiconsolidatedShallow AquifersWP0731501 NJ Urban 40.43103 -74.23553 Newark, NJ Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, SI0734604 NJ Urban 39.78529 -74.91227 Philadelphia, PA Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersWP0722705 NY Urban 42.10712 -75.89799 Binghamton, NY Mid-Atlantic Sand and Gravel LF0731111 NY Urban 42.15282 -77.0767 Binghamton, NY Mid-Atlantic Sand and Gravel AT, SI0733210 OH Rural 40.6764 -80.8992 Akron/Canton, OH Ohio Bedded Sedimentary Rock AT, LF, SI0713618 OR Urban 43.21486 -123.32816 Medford, OR Pacific Northwest Bedded Sedimentary Rock AT, SI0715007 PA Urban 40.14299 -75.30585 Philadelphia, PA Mid-Atlantic Metamorphic and Igneous WP0724804 PA Rural 40.326449 -75.322167 Allentown, PA Mid-Atlantic Bedded Sedimentary Rock WP0731405 PA Rural 40.05671 -76.57743 Wilmington, DE Mid-Atlantic Bedded Sedimentary Rock AT, SI0731703 PA Rural 40.17826 -75.5409 Philadelphia, PA Mid-Atlantic Bedded Sedimentary Rock LF(continued)

## 2-15 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)0732110 PA Urban 41.347859 -75.747582 Wilkes-Barre, PA Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersLF0733404 PA Rural 41.42468 -78.53219 Williamsport, PA Mid-Atlantic Bedded Sedimentary Rock LF, WP0733606 PA Rural 40.10934 -75.23637 Philadelphia, PA Mid-Atlantic Metamorphic and Igneous AT, SI, WP0723607 TX Rural 30.77008 -98.67221 Austin, TX Texas-Gulf Bedded Sedimentary Rock AT, SI0730914 TX Rural 30.32381 -97.29387 Austin, TX Texas-Gulf Bedded Sedimentary Rock AT, LF, SI, WP0730407 WV Rural 39.01759 -80.29334 Pittsburgh, PA Ohio Bedded Sedimentary Rock AT, LF, SI8 - Pulp and Paper Industry0830601 AL Rural 33.32008 -86.36476 Huntsville, AL South Atlantic-Gulf Metamorphic and Igneous LF0831406 AL Rural 32.45003 -87.97949 Meridian, MS South Atlantic-Gulf Sand and Gravel AT, LF, SI0831904 GA Rural 30.69851 -83.30035 Macon, GA South Atlantic-Gulf Bedded Sedimentary Rock AT, LAU, LF, SI0832904 GA Rural 33.992562 -83.77019 Athens, GA South Atlantic-Gulf Metamorphic and Igneous AT, SI0832903 LA Rural 30.70787 -91.33987 Baton Rouge, LA Lower Mississippi Sand and Gravel AT, SI, WP0831102 ME Urban 44.55504 -69.62128 Portland, ME New England Metamorphic and Igneous WP0826707 NC Rural 36.150715 -80.278929 Greensboro, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI0833001 NC Rural 35.549 -82.879 Asheville, NC Tennessee Metamorphic and Igneous LF0830903 NY Rural 44.15678 -74.98347 Burlington, VT Great Lakes Sand and Gravel AT, LF, SI0832909 OH Urban 39.518638 -84.40415 Dayton, OH Ohio Sand and Gravel AT, SI0832510 PA Rural 41.39016 -75.82027 Wilkes-Barre, PA Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, SI, WP0834009 PA Rural 40.06089 -75.26093 Philadelphia, PA Mid-Atlantic Metamorphic and Igneous AT, SI0832304 WI Urban 44.495 -88.04 Green Bay, WI Great Lakes Sand and Gravel LF, WP0833007 WI Rural 45.04 -87.725 Green Bay, WI Great Lakes Sand and Gravel AT, LF, SI9 - Primary Nonferrous Metals0923004 MI Rural 42.816435 -85.663736 Grand Rapids, MI Great Lakes Till and Till Over Outwash WP0930205 NC Rural 35.410833 -80.115556 Greensboro, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI, WP0932507 PA Urban 40.633611 -76.186944 Allentown, PA Mid-Atlantic Bedded Sedimentary Rock AT, SI, WP0932103 SC Rural 33.787222 -81.113889 Columbia, SC South Atlantic-Gulf Sand and Gravel AT, LF, SI, WP0930702 TX Rural 30.548 -97.066 Austin, TX Texas-Gulf Bedded Sedimentary Rock AT, LF, SI0932903 TX Rural 28.663 -96.542 Houston, TX Texas-Gulf Sand and Gravel AT, LF, SI0933704 VA Rural 36.66662 -82.06086 Bristol, TN Tennessee Bedded Sedimentary Rock AT, SI(continued)

## 2-16 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)0930301 WA Rural 45.73123 -120.69753 Yakima, WA Pacific Northwest Unconsolidatedand SemiconsolidatedShallow AquifersAT, LF, SI, WP0932509 WA Rural 48.45497 -117.88196 Spokane, WA Pacific Northwest Till and Till Over Outwash AT, LF, SI, WP10 - Food and Kindred Products1032715 AL Rural 33.96811 -85.96986 Huntsville, AL South Atlantic-Gulf Bedded Sedimentary Rock AT, SI1033202 AR Urban 35.425999 -94.329485 Tulsa, OK Arkansas-White-Red Bedded Sedimentary Rock LAU1034805 AR Rural 35.7646 -91.644757 Springfield, MO Arkansas-White-Red Bedded Sedimentary Rock AT, SI1013209 CA Rural 36.40229 -119.13225 Fresno, CA California Sand and Gravel AT, SI1031507 CA Rural 36.94798 -120.072 Fresno, CA California Sand and Gravel AT, SI1033114 DE Rural 38.719722 -75.289444 Atlantic City, NJ Mid-Atlantic Sand and Gravel AT, SI1014805 GA Rural 30.919 -84.616 Tallahassee, FL South Atlantic-Gulf Bedded Sedimentary Rock LF1034005 GA Rural 34.19171 -83.9055 Athens, GA South Atlantic-Gulf Metamorphic and Igneous LAU, WP1035405 ID Rural 43.61545 -116.60928 Boise, ID Pacific Northwest Unconsolidatedand SemiconsolidatedShallow AquifersAT, SI1031503 KS Rural 38.781171 -97.635899 Wichita, KS Missouri Alluvial Basins Valleys and Fans LAU1033107 MI Urban 44.735499 -85.625005 Muskegon, MI Great Lakes Till and Till Over Outwash AT, SI1033602 MI Rural 42.42 -85.643 Grand Rapids, MI Great Lakes Till and Till Over Outwash AT, LAU, SI1035117 MO Rural 39.24038 -94.4163 Kansas City, MO Missouri Alluvial Basins Valleys and Fans AT, SI1034406 MS Rural 33.36092 -91.11143 Jackson, MS Lower Mississippi Alluvial Basins Valleys and Fans AT, SI1032802 NC Rural 35.69275 -79.16879 Raleigh-Durham, NC South Atlantic-Gulf Metamorphic and Igneous AT, LAU, LF, SI1012203 NY Rural 40.942 -72.616 New York, NY Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, LF, SI, WP1023705 NY Rural 42.893111 -76.985194 Rochester, NY Great Lakes Sand and Gravel AT, SI1034210 NY Rural 42.3996 -77.25326 Binghamton, NY Great Lakes Sand and Gravel AT, LAU, SI1015510 TX Rural 33.07983 -99.57937 Lubbock, TX Texas-Gulf Alluvial Basins Valleys and Fans LF1035508 UT Rural 41.924522 -111.81336 Pocatello, ID Great Basin Alluvial Basins Valleys and Fans AT, LAU, SI1010805 WA Urban 46.04296 -118.32333 Pendleton, OR Pacific Northwest Unconsolidatedand SemiconsolidatedShallow AquifersLAU11 - Water Treatment1131802 CA Rural 38.859145 -120.66389 Sacramento, CA California Metamorphic and Igneous LAU1131103 LA Urban 29.952305 -90.07619 New Orleans, LA LowerMississippi Other (Not Classifiable) AT, SI(continued)

## 2-17 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)1134405 MO Rural 39.67715 -91.40255 Columbia, MO Upper Mississippi Sand and Gravel LAU1133902 SC Urban 34.50069 -82.02097 Greenville, SC South Atlantic-Gulf Metamorphic and Igneous LAU1122705 VA Rural 37.221 -82.285 Bristol, TN Ohio Bedded Sedimentary Rock AT, SI1120904 VT Rural 44.44519 -73.22743 Burlington, VT Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, SI12 - Petroleum Refining1233101 CA Urban 33.764167 -118.28333 Los Angeles, CA California Sand and Gravel AT, SI1236810 CA Urban 33.931111 -118.06694 Los Angeles, CA California Sand and Gravel WP1236652 CT Rural 41.556 -72.756 Hartford, CT New England Bedded Sedimentary Rock AT, SI1221704 FL Urban 27.904372 -82.76268 Tampa, FL South Atlantic-Gulf Bedded Sedimentary Rock AT, SI, WP1212301 MA Rural 42.138844 -71.077019 Boston, MA New England Metamorphic and Igneous AT, SI1230517 MD Rural 39.505833 -76.889444 Baltimore, MD Mid-Atlantic Metamorphic and Igneous AT, SI1230111 MT Rural 45.65188 -108.75652 Billings, MT Missouri Alluvial Basins Valleys and Fans AT, SI1230919 NY Urban 42.66174 -73.74344 Albany, NY Mid-Atlantic Sand and Gravel WP1236637 NY Rural 41.09491 -73.95553 New York, NY Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, SI1235205 OK Rural 34.81205 -96.67695 Oklahoma City, OK Arkansas-White-Red Bedded Sedimentary Rock AT, SI, WP1223404 PA Urban 40.071935 -75.295648 Philadelphia, PA Mid-Atlantic Metamorphic and Igneous AT, SI1236820 PA Rural 41.785 -76.36 Binghamton, NY Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersAT, SI1231705 SC Rural 32.93092 -79.83102 Charleston, SC South Atlantic-Gulf Bedded Sedimentary Rock AT, LAU, SI1230206 TN Rural 35.27079 -89.97744 Memphis, TN Lower Mississippi Alluvial Basins Valleys and Fans AT, SI1231101 TN Rural 35.087243 -90.080785 Memphis, TN Lower MississippiAlluvial Basins Valleys and Fans AT, LAU, SI1236732 WV Rural 37.793 -81.206 Roanoke, VA Ohio Bedded Sedimentary Rock WP13 - Rubber and Miscellaneous Products1331103 AL Urban 34.0079 -85.97295 Huntsville, AL South Atlantic-Gulf Bedded Sedimentary Rock AT, SI1333701 OH Urban 41.24763 -80.80961 Youngstown, OH OhioUnconsolidated and SemiconsolidatedShallow AquifersWP1333001 SC Rural 34.196944 -79.580833 Columbia, SC South Atlantic-Gulf Sand and Gravel LAU14 - Transportation Equipment1415407 AZ Urban 33.49474 -112.04027 Phoenix, AZ Lower Colorado Alluvial Basins Valleys and Fans WP(continued)

## 2-18 Appendix 2A 201 Industrial D Waste Management Sites Used in the Representative National Data SetSiteID StateUrban/RuralaLatitude LongitudeMeteorologicStationbWater ResourcesRegioncGround Water ClassdWMU TypeTable 2A-1. (continued)1430602 CA Urban 37.405945 -122.02725 San Francisco, CA California Coastal Beaches AT, SI1434022 CA Urban 33.809808 -118.33645 Los Angeles, CA California Sand and Gravel AT, SI1430404 IN Urban 39.737695 -86.215746 Indianapolis, IN Ohio Sand and Gravel AT, SI1430107 KS Urban 37.62436 -97.280161 Wichita, KS Arkansas-White-Red Alluvial Basins Valleys and Fans AT, LF, SI1434802 SC Urban 34.01779 -80.98919 Columbia, SC South Atlantic-Gulf Sand and Gravel AT, SI1435317 TX Rural 30.10278 -94.09169 Port Arthur, TX Texas-Gulf Sand and Gravel LF1431515 UT Rural 40.66357 -112.0865 Salt Lake City, UT Great Basin Alluvial Basins Valleys and Fans AT, SI1421506 WA Urban 47.49002 -122.19757 Seattle, WA Pacific Northwest Till and Till Over Outwash WP15 - Selected Chemical and Allied Products1522504 DE Rural 39.602886 -75.66059 Wilmington, DE Mid-Atlantic Metamorphic and Igneous LAU1530808 MI Rural 42.116201 -83.190811 Detroit, MI Great Lakes Bedded Sedimentary Rock AT, SI1530605 TX Rural 29.97179 -94.21806 Port Arthur, TX Texas-Gulf Sand and Gravel AT, LF, SI1532401 VT Rural 43.9799 -73.09228 Burlington, VT Mid-Atlantic Unconsolidated and SemiconsolidatedShallow AquifersWP16 - Textile Manufacturing1633404 AZ Rural 33.431667 -112.36 Phoenix, AZ Lower Colorado Alluvial Basins Valleys and Fans AT, SI1633405 CT Rural 41.55905 -73.40906 Hartford, CT New England Metamorphic and Igneous AT, SI1621808 GA Rural 33.30623 -84.567245 Atlanta, GA South Atlantic-Gulf Metamorphic and Igneous AT, LAU, SI1630106 GA Rural 34.954444 -83.379167 Asheville, NC Tennessee Metamorphic and Igneous AT, LF, SI, WP1631701 NC Rural 35.573 -77.039 Raleigh-Durham, NC SouthAtlantic-Gulf Bedded Sedimentary Rock AT, LAU, SI1632106 NM Urban 32.27424 -106.74707 El Paso, TX Rio Grande Alluvial Basins Valleys and Fans AT, LAU, SI1632703 SC Rural 34.50029 -81.61482 Greenville, SC South Atlantic-Gulf Metamorphic and Igneous LF1635404 SC Rural 34.783889 -82.687222 Asheville, NC South Atlantic-Gulf Metamorphic and Igneous AT, SI1630401 TN Urban 35.984199 -83.913239 Knoxville, TN Tennessee Bedded Sedimentary Rock WP17 - Leather and Leather Products1721603 OR Rural 45.359719 -122.83344 Portland, OR Pacific Northwest Bedded Sedimentary Rock AT, SIaBased on land use (see Section 4).bMeteorologic station assignment (see Section 4).cUSGS first level of classification for hydrologic units (Seaber et al., 1987; see Section 6).dEPACMTP ground water setting (U.S. EPA, 1996).

### Appendix 2B Facility Location



## 2-19 

# Appendix 2B Facility Location

### Appendix 2B Facility Location



## 2-20 This page intentionally left blank

### Appendix 2B Facility Location



## 2-21 

# Appendix 2B. Facility Location

Because the accuracy of the facility location directly affects the accuracy of site-based data collected for a site, an effort was conducted to collect the best locations possible. In previous modeling applications, Industrial D facilities were located using the centroid of the zip codes contained in the 1985 Screening Survey of Industrial Subtitle D Establishments (Westat, 1987), which does not contain facility latitude/long itude. However, the 3MRA modeling system relies heavily on a site-based modeling approach, and accurate facility locations are critical. To address the need for more accurate site locations, the locations of the 201 Industrial D facilities included in the representative national data set were improved through a variety of techniques, including the following:



## # Matching facilities to EPA’s Location Reference Tables (LRT) from the EnviroFacts database to obtain the Agency’s best location,



## # Zip-code centroids using GIS software, and



## # Visual placement using interactive ArcView software based on land use, WMU features (e.g., large surface impoundments as waterbodies), and topographic maps (when available). The remainder of this appendix describes the source for each improved location and the rationale for every site location adjustment. In essence, this effort helped to ensure that all Industrial D locations used in the representative national data set are a reasonable representation of current and future industrial nonhazardous waste management facilities.



# 2B.1 Data Sources The locational improvement effort began with EPA’s LRT database, which is accessible via EPA’s Envirofacts Web site. The following information was extracted from that Web site. Additional information on LRT data can be found at http://www.epa.gov/enviro/html/ lrt/lrt_over.html. The LRT database serves as a repository for information collected as a result of EPA’s 1991 Locational Data Policy (LDP). The primary objective of the LDP is to identify, collect, verify, store, and maintain an accurate, consistently documented set of locational data for entities of environmental concern. A secondary objective is to support the infrastructure needed to manage these data in a manner that yields integration across national, regional, tribal, and state systems. The intent is to support EPA’s movement toward data integration based on location, thereby promoting the use of EPA’s data resources for a wide array of cross-media analysis.

### Appendix 2B Facility Location



## 2-22 The LRT component of Envirofacts contains data extracted from the Section Seven Tracking System (SSTS), the National Compliance Database (NCDB), the Federal Facility Information System (FFIS), the PCB-Handler Ac tivity Data System (PADS), and five program systems in Envirofacts:



## # Aerometric Information Retrieval System (AIRS)/AIRS Facility Subsystem (AIRS/AFS),



## # Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Information System (CERCLIS),



## # Permit Compliance System (PCS),



## # Resource Conservation Recovery Act Information System (RCRIS), and



## # Toxics Release Inventory System (TRIS). These data were geocoded and loaded into the LRT. Envirofacts records in the LRT are updated monthly as part of the Envirofacts refresh. LRT includes Method Accuracy Descripti on (MAD) codes that provide positional accuracy for each location and are assigned by method. These include derived, provided, and default values. Table 2B-1 shows the MAD codes and their level of accuracy. Table 2B-1. Method Codes and Accuracy Values Assigned in LRT

Method code Description Accuracy (m) I1 Manual interpolation—map 2.2 to 27.4 (varies) I2 Manual interpolation—photo 2.2 to 27.4 (varies) A1 Address matching—house number 150 A4 Address matching—nearest intersection 1,000 AO Address matching—other 1,000 Z4 ZIP+4 code-Centroid 1,000 A6 Address matching—digitized (computer-mapping) 2,000

Z2 ZIP+2 code-Centroid (averaging multiple street segments; about size of census block group) 6,000 Z1 ZIP code-Centroid 11,000



# 2B.2 Review of Locational Accuracy Additional information on the accuracy of the LRT locations was obtained during the 3MRA modeling system data collection pilot. Facility front gate locations were obtained using global positioning system (GPS) technology and compar ed to zip code centroid and the best LRT

### Appendix 2B Facility Location



## 2-23 locations available for five Industrial D fac ilities. Significant conclusions drawn from these comparisons are the following:



## # At Site A (urban setting), an I1 “facility centroid” location was available from LRT. In this case, the LRT location provided a more accurate location for the onsite WMUs (surface impoundments) than did the front gate GPS location.



## # At Site B (rural setting), only a zip code centroid location was available from LRT. In this case, the inaccuracy of the zip code centroid would have resulted in asignificant difference in population estimates within the area of interest. The zipcode-based area overlapped a nearby town, resulting in a population estimate for the NW quadrant more than an order of magnitude higher than the estimate that would result from the GPS front gate location.



## # Site C (rural industrial setting) had three facilities nearby. LRT facility centroid locations for each of these were somewhat offset from the GPS front gate locations; in one case, the LRT facility centroid was in a swamp across a large river from the facility. In this case, the GPS locations provided better estimates of WMU locations than the best available LRT locations. In summary, even the better I1 locations can be somewhat inaccurate, and zip code centroid locations can significantly over- or underestimate population around a site. Based on this experience, a site relocation effort was developed to find, for each facility modeled, reasonable locations that represent likely locations for industrial Subtitle D waste management units (WMUs). 

# 2B.3 Automated LRT Matching through Envirofacts (2,850 Sites) Figure 2B-1 illustrates the automated methodology used to obtain LRT locations for the entire database of 2,850 Industrial D facilities. This involved using largely automated methods to match facilities in the Industrial D Screening Survey to EPA facility IDs and to obtain the best LRT locations for each facility. The methodology included



## # Matching Industrial D Dun and Bradstreet (DUNS) numbers to EPAIDs in Envirofacts databases with DUNS numbers (TRIS, FINDS, and AIRS/AFS),



## # Developing DUNS-based “pseudo-EPAIDs” for Industrial D facilities and matching to PCS and other Envirofacts data tables, and



## # Automated and manual matching of Industrial D facility zip code and address to Envirofacts LRT data.

### Appendix 2B Facility Location



## 2-24 Industrial D Screening

Survey (2,850 sites) "best" location (1,861 sites) Manual Review - eliminate duplicates, spurious locations - QC Locational Reference Tables - EPA ID - address - locations (with accuracy) FINDS TRIS AIRS AFS FINDS PCS

"pseudo" EPA ID

PCS

Envirofacts "crosswalk"

tables address matching software

LRT database automatic, manual matching name, address, zip code street address

DUNS EPA ID & other program ID's

EPA ID (not implemented to date)

(1,376 sites)

(474 sites)

(70 sites) (155 sites)

(1,515 non-zip code locations)

EPA ID, location (387 sites) address match location



## Figure 2B-1. Automated process for improving Industrial D site locations using Envirofacts locational data.

Table 2B-2 shows the results of this effort. Almost 1,900 of 2,850 Industrial D facilities were matched to EPA IDs, which enabled assignment of “better-than-zip-code” locations to over 1,500 facilities in the Industrial D database.

Table 2B-2. Number of Industrial D Sites Matched to LRT Locations

Method Accuracy (m) No. Sites

I1, I2 2.2–2.6 20.3–27.4 >150 53 483

3 A1 150 819 A4, AO, Z4 1,000 80 A6 2,000 75 Z2 6,000 33 Z1 11,000 339 Total 1,885

### Appendix 2B Facility Location



## 2-25 

# 2B.4 Address Matching and Manual Techniques: 201 Sites Once the 201 Industrial D sites were selected for the representative national data set, additional effort was made to get improved locations for those 201 sites. These efforts included



## # Manual matching through the Envirofacts query form was done for sites in the 201 that were not already matched to Envirofacts locations. This resulted in an additional 45 sites matched to EPA IDs.



## # Using a table of all available EPA IDs, for 181 of the 201 sites, to query the Envirofacts database to ensure that the best location was obtained for the sites from the LRT. This resulted in 12 new locations being added to the database as well as a few more accurate locations for sites already with LRT locations.



## # Filling in remaining sites (without LRT locations) with zip code centroid latitude and longitudes using the ESRI ArcView Da ta Disk (data from a Geographic Data Technology, Inc., 1995 database). Table 2B-3 shows the method and accuracies of the 201 site locations, including 66 locations based on 5-digit zip codes. 

# 2B.5 Manual Location Review and Adjustment During the initial watershed delineations of the sites, it became apparent that some locations would cause problems in the data collection process if they were not moved. Some locations put WMUs in rivers or other waterbodies. Other sites ended up in areas of inappropriate land use (e.g., large surface impoundments in residential land use areas). To ensure that all sites were in reasonable locations with respect to land use, GIS coverages imported for data collection (incl uding GIRAS land use, RF3 and NWI waterbodies, and zip code coverages), DeLorme topographic road atlases, and digital USGS topographic quadrangles (where available) were used to review all site locations and adjust inappropriate locations to better locations. In some cases, usually with large surface impoundments, the actual WMUs could be found using the various wa terbody coverages provided by GIS or on the topographic maps. Attachment 2B-1 (at the end of this appendix) shows the sites moved from the initial locations described above to the final locations used for data gathering, including an explanation of why each site was moved. 

# 2B.6 Quality Assurance/Quality Control QA/QC activities for this effort included automated matching of zip codes and addresses between the Industrial D and LRT data to identify spurious facility locations and duplicate locations, which were then screened manually to eliminate duplicates and mismatched data. Manual checks of the matched sites (using facility name, address, and zip code comparisons) were conducted to verify the automated matching process. Whenever zip codes or addresses did not agree, manual verification was conducted. A manual review of all site locations using the GIS coverages was also done to identify sites that needed to be moved to more appropriate locations.

### Appendix 2B Facility Location



## 2-26 Table 2B-3. 201 Site Location Method and Accuracy

Method Accuracy (m) No. Sites I1 2.2–2.6 20.3–27.4 8 43 A1 150 71 A4, AO, Z4 1,000 7 A6 2,000 6 Z2 6,000 2 Z1 11,000 31 Zip Code Centroid 33 Total 201



# 2B.7 Issues and Uncertainties Uncertainties associated with the Industrial D facility locations include the following:



## # For some sites, problems were encountered even with the most accurate locations from the Envirofacts LRT data. As shown in Attachment 2B-1, even a few facilities with accuracies of 150 meters or less had to be moved due to problems with the original location. One site with an LRT locational accuracy of 2 to 3 m (an I1 location) needed to be moved 10,047 m to remove the facility from a large bay that entirely covered the 2 km radius.



## # While every attempt was made to move poorly located sites to the best locations possible, there was still no way to know exactly where the actual facility was located. Some facilities with only zip code centroid locations were moved to suitable land use (based on professional judgment) within a rather large zip code district. However, these uncertainties should be considered in the context of the intended nationwide use of the 3MRA modeling system; although site-based data are the basis for the representative national data set, and the site-based data are determined by where each site is located, the representative national data set is not intended to support site-specific analysis. Within this context, the 201 facilities and their locations as presented herein were derived to adequately represent likely locations of Industrial D facilities across the nation.

### Appendix 2B Facility Location



## 2-27 Attachment 2B-1. Initial and Final Industrial D Facility Locations and Distances Moved a

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes 0114001 40.492134 -80.080149 A1 40.49308 -80.07914 135.72 WMU in river; moved due north to island center 0130207 41.399742 -91.06297 A1 41.399742 -91.06297 0.00 0131104 42.655934 -89.062147 Z4 42.66416 -89.05569 1059.31 move d site to appropriate land use (LU) 0131207 43.079444 -79.008889 I1 43.079444 -79.00889 0.00 0131508 36.519722 -82.540556 I1 36.52501 -82.53999 594.48 moved WMU to within LU (I1 location likely NPDES discharge point) 0136703 35.200897 -103.719283 A6 35.19942 -103.7158 357.65 m oved large LAU to be between streams 0220102 32.834906 -79.948129 A1 32.834906 -79.94813 0.00 0221207 40.292475 -84.162526 A1 40.292475 -84.16253 0.00 0223504 40.850867 -81.763907 A1 40.850867 -81.76391 0.00 0224002 43.864918 -91.22621 A1 43.86402 -91.22462 162.00 s light adjustment for waterbody 0231002 40.192049 -84.981029 A1 40.192049 -84.98103 0.00 0231106 40.116667 -74.816667 I1 40.11836 -74.81713 193.67 moved site to center of tailings pile on topo. map 0231407 32.466028 -97.027776 A1 32.46527 -97.02675 127.86 move d LF SSE to within industrial LU (also based on topo. map) 0231610 41.733878 -87.540879 A1 41.73503 -87.54159 141.64 moved WMU behind buildings on topo. map 0231911 43.447145 -83.920814 A1 43.447145 -83.92081 0.00 0231914 42.256748 -83.135334 A1 42.256748 -83.13533 0.00 0232305 43.969506 -72.689212 Z1 43.969506 -72.68921 0.00 0232313 32.436111 -95.366111 I1 32.43605 -95.36401 196.64 move d site to move large landfill out of town (residential land use) 0232402 39.970278 -75.815833 I1 39.970278 -75.81583 0.00 0232415 41.457226 -81.688288 A1 41.457226 -81.68829 0.00 0232501 41.26461 -80.482964 A4 41.26468 -80.4838 69.94 m oved site out of residential neighborhood; 0232705 34.240689 -84.809157 A4 34.1769 -84.81757 7171.98 moved site to small industrial LU W of town 0233601 38.064696 -78.874709 A1 38.064696 -78.87471 0.00 0233603 33.541515 -86.543034 A1 33.541515 -86.54303 0.00 0234904 41.068123 -75.147684 Z1 41.02221 -75.19536 6498.84 move d site to likely LF location on topo. map 0235301 39.921 -85.366 Z1* 39.9335 -85.38004 1837.45 move d site to industrial LU NE of town 0312301 38.434 -78.994 Z1* 38.42827 -78.94495 4289.95 moved site to off Hwy 736 N of town (from Ind. D address) 0314202 42.711063 -73.671455 A1 42.711063 -73.67146 0.00 0321802 45.615336 -122.710504 A1 45.615336 -122.7105 0.00 0331006 34.563889 -90.652778 I1 34.563889 -90.65278 0.00 (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-28 0331902 36.439167 -99.468611 I1 36.439167 -99.46861 0.00 0332104 35.642778 -101.426944 I1 35.642778 -101.4269 0.00 0332707 27.888056 -81.947778 I1 27.88554 -81.94815 280. 16 moved site out of lake 0332811 40.592668 -83.105517 A1 40.59397 -83.10857 294.82 move d site out of residential area 0430108 40.398046 -95.717525 Z1 40.36094 -95.64231 7573.94 move d site to best road atlas location (Ind. D address) 0430412 41.766961 -81.16979 Z2 41.78825 -81.14677 3046.87 m oved to better address-match location 0431912 38.334461 -94.756131 Z1 38.35827 -94.63423 10885.75 moved site to industrial LU in RF3 lake (this is the surface impoundment [SI]) 0432011 34.703889 -87.118889 I1 34.703889 -87.11889 0.00 0432106 40.7975 -75.107778 I1 40.79771 -75.11741 806.40 move d site to lake (SI) from RF3 0432716 47.263003 -93.680131 Z1 47.261 -93.674 516.49 moved site to utility LU; RF3 feature is SI 0433201 41.179782 -87.058589 Z1 41.21534 -87.0191 5161.87 moved site to centroid of SI lakes in RF3 0433204 33.330278 -79.357222 I1 33.330278 -79.35722 0.00 0433404 42.014132 -105.017647 Z1 42.0824 -104.9495 9472.82 site moved to utility LU & RF3 lake (SI) of right size 0433408 45.87786 -106.61743 Z1 45.892 -106.632 1935.62 m oved to suitable (industrial) LU 0434505 32.847146 -115.567363 A1 32.847146 -115.5674 0.00 0434804 35.3775 -78.101944 I1 35.38401 -78.07439 2586.56 moved site to actual SI (NWI lake) 0435510 40.277643 -90.010646 Z1 40.27633 -90.08052 5892.10 move d site to road atlas location (Ind. D address) 0436007 35.540833 -78.989722 I1 35.5871 -79.04772 7347.30 moved site to actual SI (RF3 lake) 0436108 35.189167 -81.012222 I1 35.18328 -81.01201 659.05 move d to actual SI location (NWI lake) 0530901 41.372916 -82.542933 A1 41.372916 -82.54293 0.00 0531301 39.85 -89.251 Z1* 39.84983 -89.27569 2093.84 m oved site (Z1*) to only ind. LU w/in zip 0531502 39.040041 -82.62848 A1 39.03921 -82.62841 93.33 Site moved out of residential area 0531702 35.720214 -101.244738 Z1 35.66336 -101.4502 19502.38 m oved to likely LF on topo. map; RF3 “lakes” surrounding new point (these are SIs) 0531902 29.711 -95.159 Z1* 29.72675 -95.13189 3150.39 move d to ind LU, SI locations from topo. map 0534504 33.843732 -84.233559 A1 33.84175 -84.23034 369.48 moved site to just within nearest industrial LU 0613402 38.586459 -90.176488 A1 38.586459 -90.17649 0.00 0620401 29.758611 -95.176389 I1 29.758611 -95.17639 0.00 0620604 40.736238 -111.96209 A1 40.7375 -111.9881 2186.42 huge SI, perfect area match with GIRAS/ RF3 lake; moved to lake centroid (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-29 0621603 29.701746 -95.082965 A1 29.701746 -95.08297 0.00 0621902 38.027 -98.087 Z1* 38.03371 -97.97337 9908.45 moved to nearest Ind LU 0622902 31.935764 -111.0029 A1 31.935764 -111.0029 0.00 0625002 32.2 -81.166667 I1 32.2 -81.16667 0.00 0625501 30.016308 -94.913917 Z1 29.99645 -94.96404 5309.60 m oved 5 mi SW on hwy 90 (Ind. D address) 0631701 29.708333 -95.075 I1 29.71475 -95.07624 721.65 moved site off stream to likely LAU location (cropland LU) 0631903 30.235833 -93.264444 I1 30.23167 -93.27781 1365.25 move d site to likely RF3 feature (SI; delete feature from waterbodies) 0632003 32.437778 -94.688889 I1 32.437778 -94.68889 0.00 0632606 35.422342 -100.838567 Z1 35.48185 -101.0562 20685.82 move d site to actual SI location (RF3&GIRAS) 0632608 45.570556 -122.743056 I1 45.56941 -122.7448 186.44 m oved site away from river w/in Ind. LU 0634001 34.187 -84.82 Z1* 34.13254 -84.77666 7265.34 move d to likely RF3 lake (SI - don’t include as waterbody) 0635301 36.036 -114.972 Z1* 36.04434 -114.9951 2267.53 m oved to ind. LU within zip 0713618 43.223 -123.366 Z1* 43.21486 -123.3282 3191.00 moved site to nearest ind. LU within zip 0713705 32.720908 -111.917603 Z1 32.833 -111.734 21184.13 m oved to approximate location of Peters Rd. (Ind D address) 0715007 40.124 -75.33 Z1* 40.14299 -75.30585 2947.51 moved site to likely land use (cemetery on topo. map) 0715216 33.888 -117.8 Z1* 33.89933 -117.8218 2364.58 m oved site to nearest ind. LU 0716701 38.067291 -87.264515 A1 38.06725 -87.26451 4.61 move d WMU to be within ind. LU 0720506 44.67 -67.753 Z1* 44.65533 -67.71774 3233.55 move d site to approx. Ind D address NE of town (no suitable LU) 0720803 27.097 -82.436 Z1* 27.07543 -82.38693 5441. 92 moved site to suitable LU 0721305 42.277826 -83.129062 A1 42.27879 -83.12807 135.00 moved site to industrial LU 0722107 26.824 -81.955 Z1* 26.87084 -82.00256 7015.78 moved site to industrial LU 0722503 39.807664 -105.006125 A1 39.807664 -105.0061 0.00 0722505 26.022 -80.189 Z1* 25.99577 -80.18024 3012.60 moved site to industrial LU 0722705 42.146 -75.886 Z1* 42.10712 -75.89799 4458.57 moved to industrial LU 0723607 30.723 -98.653 Z1* 30.77008 -98.67221 5545.12 moved site to “gravel pit” N of town (topo. map) 0724206 35.790146 -80.610776 Z1 35.77042 -80.60004 2408.95 move d site to actual WMU location (NWI feature is SI; don’t make a waterbody) 0724301 34.786143 -89.449686 A1 34.786143 -89.44969 0.00 0724804 40.326449 -75.322167 AO 40.326449 -75.32217 0.00 0724909 48.146 -103.603 Z1* 48.14514 -103.6507 3581.00 m oved site to likely land use W of town (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-30 0730407 38.969558 -80.228076 Z2 39.01759 -80.29334 7768.27 move d site to industrial LU outside of town 0730502 39.00298 -87.748337 A1 39.00298 -87.74834 0.00 0730914 30.301356 -97.385637 Z1 30.32381 -97.29387 9157.41 move d to industrial LU ~5 mi. SW of town (Ind D address) 0731111 42.128812 -77.037595 Z1 42.15282 -77.0767 4185.44 moved site to industrial LU in town 0731405 40.055278 -76.574722 I1 40.05671 -76.57743 279. 59 moved to industrial LU 0731411 37.091066 -120.245446 A1 37.091066 -120.2454 0.00 0731412 42.5513 -71.531023 A1 42.5495 -71.51555 1278.84 moved site to “barren” LU near A1 location 0731501 40.443889 -74.244722 I1 40.43103 -74.23553 1634.79 move d site to industrial LU within zip 0731507 34.746389 -79.388333 I1 34.74411 -79.39153 386.37 site moved to actual SI location (RF3 lake) 0731514 42.399 -87.855 Z1* 42.38881 -87.81145 3740.34 site moved to road atlas location on Lake MI 0731703 40.177199 -75.541599 A4 40.17826 -75.5409 132. 71 moved WMU out of river 0732110 41.347859 -75.747582 A1 41.347859 -75.74758 0.00 0732405 37.625 -121.006 Z1* 37.65484 -121.0263 3787.02 site moved to likely LU 0732510 41.61767 -88.20255 A6 41.61892 -88.20404 186.44 s ite moved to nearby ind. LU 0733203 37.721859 -121.494389 A1 37.71502 -121.4905 839.03 moved to ind. LU near A1 location 0733210 40.6764 -80.8992 Z1 40.6764 -80.8992 0.00 0733302 37.647 -84.775 Z1* 37.64289 -84.78751 1186.46 move d site to suitable LU in zip 0733404 41.426111 -78.526667 I1 41.42468 -78.53219 485.30 I1 is NPDES discharge pt; moved to likely LF site on topo. map 0733501 35.37606 -82.51622 Z1 35.37242 -82.48649 2708.85 moved to ind. LU within town from Ind. D address 0733606 40.108 -75.28 Z1* 40.10934 -75.23637 3689.65 move d site to between waste pile & old SI on topo. map 0734604 39.779 -74.931 Z1* 39.78529 -74.91227 1739.07 moved site to nearest ind. LU within zip 0735309 37.216505 -95.692613 A6 37.2165 -95.69048 187.51 slight move to best LU 0826707 36.150715 -80.278929 A1 36.150715 -80.27893 0.00 0830601 33.267 -86.338 Z1* 33.32008 -86.36476 6422.69 moved site to ind. LU in town from Ind. D address 0830903 44.213889 -74.989167 I1 44.15678 -74.98347 6382.38 moved LF out of waterbody 0831102 44.555278 -69.624444 I1 44.55504 -69.62128 252.20 moved WMU from river (I1) to adjacent industrial LU 0831406 32.449444 -87.973333 I1 32.45003 -87.97949 579.49 site moved to SI (RF3 lake) location (don’t include these in WB network) 0831904 30.75545 -83.307766 Z1 30.69851 -83.30035 6367.95 site moved to SI feature on topo map and industrial LU (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-31 0832304 44.493659 -88.036783 A1 44.495 -88.04 295.74 moved site to be within industrial LU 0832510 41.3925 -75.826111 I1 41.39016 -75.82027 550.95 move d site out of river into SIlooking feature on topo. map 0832903 30.709444 -91.32 I1 30.70787 -91.33987 1906.75 m oved to RF3 lake (SI) locations (don’t connect these) 0832904 33.992562 -83.77019 A1 33.992562 -83.77019 0.00 0832909 39.518638 -84.40415 A1 39.518638 -84.40415 0.00 0833001 35.535278 -82.841111 I1 35.549 -82.879 3735.88 I1 location is plant, not landfill; located landfill at one of the actual landfills using permit information 0833007 45.054396 -87.74886 A1 45.04 -87.725 2467.96 m oved landfill to suitable LU and topo. map location 0834009 40.058116 -75.264293 Z1 40.06089 -75.26093 421.26 move d to SI location on topo. map; do not included squarish SIs to the NE 0923004 42.816435 -85.663736 A1 42.816435 -85.66374 0.00 0930205 35.410833 -80.115556 I1 35.410833 -80.11556 0.00 0930301 45.732222 -120.698056 I1 45.73123 -120.6975 117.56 moved WMU slightly to fit w/in ind. LU 0930702 30.553889 -97.051111 I1 30.548 -97.066 1568.46 move d site to industrial area near plant; note strip mine LU. 0932103 33.787222 -81.113889 I1 33.787222 -81.11389 0.00 0932507 40.633611 -76.186944 I1 40.633611 -76.18694 0.00 0932509 48.474695 -117.946123 A1 48.45497 -117.882 5262.34 moved s ite to nearest ind. LU in zip 0932903 28.645833 -96.561111 I1 28.663 -96.542 2666.46 moved WMU to area accommodating SI & LF (island likely location for SI, but square WMU won’t fit; Sis & LFs in vicinity of new location) 0933704 36.75667 -82.035833 Z1 36.66662 -82.06086 10328.64 m oved to ind. LU along Hwy. 11 (Ind D address) 1010805 46.061 -118.332 Z1* 46.04296 -118.3233 2111.80 move d LAU to agricultural LU to S, near commercial LU 1012203 40.941444 -72.495694 I1 40.942 -72.616 10047.53 I1 location in bay/estuary (entire AOI); used directory listing to locate 1013209 36.431 -119.092 Z1* 36.40229 -119.1323 4809.48 m oved to approx. location on road atlas (Ind D address) 1014805 30.905339 -84.601838 A1 30.919 -84.616 2032.06 move d to likely LU (mining) using atlas & LU coverage 1015510 33.158 -99.731 Z1* 33.07983 -99.57937 16548.04 move d site to suitable land use “on lake Stamford” (Ind D address) 1023705 42.893111 -76.985194 I1 42.893111 -76.98519 0.00 1031503 38.781171 -97.635899 A1 38.781171 -97.6359 0.00 (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-32 1031507 36.947928 -120.072999 A1 36.94798 -120.072 88.33 moved site to RF3 lake (SI; delete this feature, large SI) 1032715 33.970556 -85.972222 I1 33.96811 -85.96986 348.80 move d site to NWI lakes (SIs; do not incorporate these into waterbody network) 1032802 35.769 -79.175 Z1* 35.69275 -79.16879 8554.84 m oved site to actual SI location (LU& map, Ind D address); do not connect feature as waterbody 1033107 44.735499 -85.625005 A1 44.735499 -85.62501 0.00 1033114 38.719722 -75.289444 I1 38.719722 -75.28944 0.00 1033202 35.425999 -94.329485 A1 35.425999 -94.32949 0.00 1033602 42.421948 -85.649703 A1 42.42 -85.643 589.81 moved large LAU to between streams 1034005 34.191708 -83.900498 A1 34.19171 -83.9055 457.53 m oved LAU to agricultural area next to industrial area 1034210 42.443997 -77.196368 Z1 42.3996 -77.25326 6803.01 move d to atlas location of Ind D facility 1034406 33.333096 -91.109649 A6 33.36092 -91.11143 3111.08 move d WMU to small SI (RF3 lake near Miss. R; do not connect) 1034805 35.7646 -91.644757 A1 35.7646 -91.64476 0.00 1035117 39.240922 -94.416439 A1 39.24038 -94.4163 61.89 moved WMU to just within industrial area to SE 1035405 43.617953 -116.611829 A6 43.61545 -116.6093 346.39 moved site (A6) to nearest ind. LU along RR 1035508 41.924522 -111.813356 A1 41.924522 -111.8134 0.00 1120904 44.484 -73.22 Z1* 44.44519 -73.22743 4363.87 m oved to correct street address using atlas 1122705 37.221 -82.285 Z1* 37.221 -82.285 0.00 1131103 29.952305 -90.07619 A1 29.952305 -90.07619 0.00 1131802 38.859145 -120.663889 A1 38.859145 -120.6639 0.00 1133902 34.501 -82.027 Z1* 34.50069 -82.02097 550.46 moved to industrial LU 1134405 39.679462 -91.402836 A1 39.67715 -91.40255 260.23 m oved LAU S to likely location based on address, LU 1212301 42.138844 -71.077019 A1 42.138844 -71.07702 0.00 1221704 27.904372 -82.76268 A1 27.904372 -82.76268 0.00 1223404 40.071935 -75.295648 AO 40.071935 -75.29565 0.00 1230111 45.654698 -108.756506 Z1 45.65188 -108.7565 313.07 move d site out of river S of town 1230206 35.273275 -89.982701 A1 35.27079 -89.97744 550.02 moved WMU to industrial LU 1230517 39.505833 -76.889444 I1 39.505833 -76.88944 0.00 1230919 42.65287 -73.74868 Z1 42.66174 -73.74344 1079.43 moved site to suitable LU within zip 1231101 35.087243 -90.080785 A1 35.087243 -90.08079 0.00 1231705 32.959089 -79.882761 Z1 32.93092 -79.83102 5744.84 move d to suitable LU within zip (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-33 1233101 33.764167 -118.283333 I1 33.764167 -118.2833 0.00 1235205 34.796771 -96.78958 Z1 34.81205 -96.67695 10363.02 move d site N of airport on highway (Ind D address) 1236637 41.096887 -73.973995 Z1 41.09491 -73.95553 1554.58 moved site into correct zip code & suitable LU 1236652 41.556617 -72.755285 Z4 41.556 -72.756 90.95 move d site to within “barren” LU 1236732 37.793 -81.206 Z1* 37.793 -81.206 0.00 1236810 33.931111 -118.066944 I1 33.931111 -118.0669 0.00 1236820 41.785179 -76.359912 Z1 41.785 -76.36 21.31 moved site to ind/”barren” LU with SIs (RF3 lakes; do not connect as waterbodies) 1331103 34.006675 -85.97306 A1 34.0079 -85.97295 137.27 m oved to within industrial LU 1333001 34.196944 -79.580833 I1 34.196944 -79.58083 0.00 1333701 41.242234 -80.904287 Z1 41.24763 -80.80961 7896.26 moved to ind. LU in town (Ind D address) 1415407 33.51 -112.03 Z1* 33.49474 -112.0403 1950.03 s ite moved to industrial land use within zip 1421506 47.488603 -122.197347 A1 47.49002 -122.1976 157.46 moved site inside adjacent industrial LU 1430107 37.62436 -97.280161 A1 37.62436 -97.28016 0.00 1430404 39.737695 -86.215746 A1 39.737695 -86.21575 0.00 1430602 37.405945 -122.027249 A1 37.405945 -122.0272 0.00 1431515 40.66357 -112.086499 A6 40.66357 -112.0865 0.00 1434022 33.809808 -118.336446 A1 33.809808 -118.3364 0.00 1434802 34.026 -81.005 Z1* 34.01779 -80.98919 1715.34 move d to industrial LU within zip 1435317 30.089252 -94.09914 A1 30.10278 -94.09169 1664.00 move d site to likely “waste pile” feature on topo. map 1522504 39.602886 -75.66059 A1 39.602886 -75.66059 0.00 1530605 30.029167 -94.271111 I1 29.97179 -94.21806 8166.03 move d site to industrial LU using Ind D address 1530808 42.116201 -83.190811 A1 42.116201 -83.19081 0.00 1532401 44.001412 -73.188314 Z1 43.9799 -73.09228 8042.02 move d to road atlas location (Ind D address) 1621808 33.30623 -84.567245 A1 33.30623 -84.56725 0.00 1630106 34.954444 -83.379167 I1 34.954444 -83.37917 0.00 1630401 35.984199 -83.913239 A1 35.984199 -83.91324 0.00 1631701 35.547778 -77.076944 I1 35.573 -77.039 4426.85 moved site to best possible location out of river; DEMs won’t work (flat site) 1632106 32.272848 -106.617001 Z1 32.27424 -106.7471 12191.53 move d to mixed LU in Ind D town (continued)

## Attachment 2B-1. (continued) Appendix 2B Facility Location

Site ID Initial Latitude Initial Longitude Collection Method b Final Latitude Final Longitude Distance (m) Comments/Notes



## 2-34 1632703 34.498358 -81.616269 A1 34.50029 -81.61482 253.19 m oved site to “commercial & services” LU 1633404 33.431667 -112.36 I1 33.431667 -112.36 0.00 1633405 41.56 -73.408889 I1 41.55905 -73.40906 107.25 moved site slightly to within suitable LU 1635404 34.783889 -82.687222 I1 34.783889 -82.68722 0.00 1721603 45.359719 -122.833438 A1 45.359719 -122.8334 0.00

a Initial locations derived from Envirofacts LRT tables, addre ss matching (using Industrial D address data), or zip code

centroids (using Industrial D zip codes). Final locations dete rmined using manual review and relocation, as necessary.

b Z1* indicates zip code location based on I ndustrial D zip code; all other initial loca tions from Envirofacts location reference

tables: A1, A6 = address-match; I1 = manua l map interpolation; Z1 = zip code centroid (5-digit); Z4 = zip code centroid (9- digit).