{6f1faef8-0469-4323-9734-4d584944e824} eng; USA utf8 dataset EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development - Center for Public Health and Environmental Assessment CPHEA, EnviroAtlas Geospatial Data Owner 919 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact 2025-02-13 ISO 19115 Geographic Information - Metadata ISO 19115:2003/Cor.1:2006(E) EnviroAtlas - Tacoma, WA - BenMAP Results by Block Group 2021-02-08 publication U.S. EPA Office of Research and Development (ORD) - Center for Public Health and Environmental Assessment (CPHEA) Research Triangle Park NC publisher US Environmental Protection Agency (US EPA) (additional partners are listed in Supplemental) originator This EnviroAtlas dataset demonstrates the effect of changes in pollution concentration on local populations in 526 block groups in Tacoma, Washington. The US EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) was used to estimate the incidence of adverse health effects (i.e., mortality and morbidity) and associated monetary value that result from changes in pollution concentrations for Tacoma, WA. Incidence and value estimates for the block groups are calculated using i-Tree models (www.itreetools.org), local weather data, pollution data, and U.S. Census derived population data. This dataset was produced by the US Forest Service to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. This dataset was produced the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). This dataset identifies some of the adverse health effects that can be reduced by trees in a community. The data could be used to promote awareness of the benefits that trees bring to people and the environment. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. completed EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development - Center for Public Health and Environmental Assessment (CPHEA), EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact asNeeded Ecosystem Environment theme EPA GIS Keyword Thesaurus Air Census Block Groups Communities Ecosystem Services EnviroAtlas Environment Environmental Atlas Exposure Health Human Well-being Impact Modeling Trees theme EnviroAtlas Washington Tacoma, WA place None https://edg.epa.gov/EPA_Data_License.html otherRestrictions Use Constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated. otherRestrictions Access Constraints: None PUBLIC https://project-open-data.github.io/schema/#accessLevel Standard Technical Controls eng; USA environment -122.779859 -121.889940 46.848943 47.413195 9999-01-01 This dataset was produced by the USDA Forest Service with support from The Davey Tree Expert Company. true Entity and Attribute Information Entity and Attribute Overview: For more information about EnviroAtlas data, go to https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets. The US EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) was used to estimate the incidence of adverse health effects (i.e., mortality and morbidity) and associated monetary value that result from changes in pollution concentrations. BenMAP is a Windows-based computer program that uses Geographic Information System (GIS) based data to estimate the health impacts and economic value when populations experience changes in air quality (U.S. EPA, 2012a). BenMAP was used to estimate incidence and value for ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter less than 2.5 microns (PM2.5). The model uses air quality grids to determine the change in pollution concentration, concentration-response functions to estimate the change in adverse health effects, and valuation functions to calculate the associated economic value. BenMAP was used to obtain incidence and value results for each county within the contiguous United States. The air quality grids used for this analysis were for baseline and control years (Table 1) that had the greatest change in pollution concentration based on national pollution trends (https://www.epa.gov/air-trends). The pollution concentration for the grids was interpolated from existing pollution data sets from EPA pollutant monitors using Voronoi neighborhood averaging. Several functions were used to estimate incidence and value for the common health effects of each pollutant. The concentration-response functions that were used for the analysis of each pollutant (Table 2) have several inputs including air quality metrics (e.g., 24-hour mean) and age of the population (e.g., 18-64 years old, 65-99 years old). The model was run using population statistics from the U.S. Census 2010 county dataset using an economic forecasting model described in the BenMAP user manual (Abt Associates, 2010). The health effects categories potentially had multiple estimates corresponding to different air quality metrics and age groups. Different age groups were represented because the concentration-response functions are age specific and incidence rate can vary across different age groups. Multiple estimates were pooled by either averaging the estimates using the random/fixed effects method or summing the estimates depending on which process was appropriate. In the end, a final estimate was produced to cover all possible metrics and age groups within a health category. For example, equations for 0-17, 18-64, and 65-99 age groups were summed to produce an estimate for 0-99 age group. More details on the BenMAP model are found in the literature (Davidson et al. 2007; Abt Associates, 2010; US EPA, 2012a). To estimate each individual health category incidence and dollar value effect at the block group scale, the county estimates were divided by the county population by age group and change in pollution concentration. The result was an estimate of number of incidences or dollar value per person per age group per unit of concentration for each county, similar to the procedure used in US EPA (2012b). The value for the county of the study area was then multiplied by the block group population per age group and change in pollution concentration due to trees in the block group to estimate the tree effects on incidence and value for each health category. The block group population per age group was estimated by applying the census tract age distribution to the total number of people in the block group. The dollar values for all health categories were summed to determine the total value of each pollution effect for each block group. For PM2.5 metrics, negative values occur occasionally and are due to the timing of resuspension relative to the boundary layer height (BLH). While the forest removes PM overall, it can lead to increased overall concentrations depending on when resuspension occurs. If removal occurs when the BLH is high, it has a relatively small effect on concentration. If it resuspends some of the particles when the BLH is low, it can increase concentrations more than it decreased concentrations. ----TABLES:---- (TABLE 1) YEARS USED FOR AIR QUALITY GRID CREATION: Pollutant: O3, Baseline: 2002, Control: 2004; Pollutant: NO2, Baseline: 2000, Control: 2007; Pollutant: SO2, Baseline: 2000, Control: 2007; Pollutant: PM2.5, Baseline: 2000, Control: 2006. (TABLE 2) CONCENTRATION-RESPONSE FUNCTIONS USED FOR POLLUTANT ANALYSES: PM2.5-Acute Bronchitis: Dockery et al., 1996. PM2.5-Acute Myocardial Infarction: Peters et al., 2001; Pope et al., 2006; Sullivan et al., 2005; Zanobetti and Schwartz, 2006; Zanobetti et al., 2009. PM2.5-Acute Respiratory Symptoms: Ostro and Rothschild, 1989. PM2.5-Asthma Exacerbation: Mar et al., 2004; Ostro et al., 2001. PM2.5-Chronic Bronchitis; Abbey et al., 1995. PM2.5-Emergency Room Visits, Respiratory: Mar et al., 2010; Norris et al., 1999; Slaughter et al., 2005 PM2.5-Hospital Admissions, Cardiovascular: Bell et al., 2008; Moolgavkar, 2000; Moolgavkar, 2003; Peng et al., 2008; Peng et al., 2009; Zanobetti et al., 2009. PM2.5-Hospital Admissions, Respiratory: Zanobetti et al., 2009; Ito, 2003; Moolgavkar, 2003. PM2.5-Lower Respiratory Symptoms: Schwartz and Neas, 2000. PM2.5-Mortality: Woodruff et al., 2006; Krewski et al., 2009; Laden et al., 2006; Pope et al., 2002; Woodruff et al., 1997. PM2.5-Upper Respiratory Symptoms: Pope et al., 1991. PM2.5-Work Loss Days: Ostro, 1987. NO2-Hospital Admissions, Respiratory: Luginaah et al., 2005; Fung et al., 2006; Yang et al., 2003. NO2-Emergency Room Visits, Respiratory: Ito et al., 2007; Peel et al., 2005; NYDOH, 2006. NO2-Asthma Exacerbation: Delfino et al., 2002; O'Connor et al., 2008; Schildcrout et al., 2006; Mortimer et al., 2002. NO2-Acute Respiratory Symptoms: Schwartz et al., 1994. O3-Acute Respiratory Symptoms: Ostro and Rothschild, 1989. O3-Emergency Room Visits, Respiratory: Peel et al., 2005; Wilson et al., 2005. O3-Hospital Admissions, Respiratory: Burnett et al., 2001; Schwartz, 1995. O3-Mortality: Bell et al., 2005; Levy et al., 2005. O3-School Loss Days: Gilliland et al., 2001; Chen et al., 2000. SO2-Acute Respiratory Symptoms: Schwartz et al., 1994. SO2-Asthma Exacerbation: Mortimer et al., 2002; O'Connor et al., 2008; Schildcrout et al., 2006. SO2-Emergency Room Visits, Respiratory: NYDOH, 2006; Peel et al., 20005; Michaud et al., 2004; Ito et al., 2007; Wilson et al., 2005. SO2-Hospital Admissions, Respiratory: Fung et al., 2006; Luginaah et al., 2005; Schwartz et al., 1996; Yang et al., 2003. ----REFERENCES:---- Abbey, D.E., B.E. Ostro, F. Petersen, and R.J. Burchette. 1995. Chronic Respiratory Symptoms Associated with Estimated Long-Term Ambient Concentrations of Fine Particulates Less Than 2.5 Microns in Aerodynamic Diameter (PM2.5) and Other Air Pollutants. Journal of Exposure Analysis and Environmental Epidemiology 5(2): 137-159. Abt Associates. 2010. BenMAP Environmental Benefits Mapping and Analysis Program. Office of Air Quality Planning and Standards U.S. Environmental Protection Agency, Research Triangle Park, NC. 283 p. https://www.epa.gov/benmap/benmap-40. Last accessed May 24, 2012. Bell, M.L., F. Dominici, and J.M. Samet. 2005. A meta-analysis of time-series studies of ozone and mortality with comparison to the national morbidity, mortality, and air pollution study. Epidemiology 16 (4): 436-45. Bell, M.L., K. Ebisu, R.D. Peng, J. Walker, J.M Samet, S.L. Zeger, and F. Dominici. 2008. Seasonal and Regional Short-term Effects of Fine Particles on Hospital Admissions in 202 US Counties, 1999-2005. American Journal of Epidemiology 168(11): 1301-1310. Burnett, R.T., M. Smith-Doiron, D. Stieb, M.E. Raizenne, J.R. Brook, R.E. Dales, J.A. Leech, S. Cakmak, and D. Krewski. 2001. Association between ozone and hospitalization for acute respiratory diseases in children less than 2 years of age. American Journal of Epidemiology 153 (5): 444-52. Chen, L., B. L. Jennison, W. Yang, and S. T. Omaye. 2000. Elementary school absenteeism and air pollution. Inhalation Toxicology 12 (11): 997-1016. Davidson, K., A. Hallberg, D. McCubbin, B. Hubbell. 2007. Analysis of PM2.5 Using the Environmental Benefits Mapping and Analysis Program (BenMAP). Journal of Toxicology and Environmental Health, Part A. 70: 332-346. Delfino, R.J., R.S. Zeiger, J.M. Seltzer, D.H. Street, and C.E. McLaren. 2002. Association of asthma symptoms with peak particulate air pollution and effect modification by anti-inflammatory medication use. Environmental Health Perspectives 110 (10): A607-17. Dockery, D.W., J. Cunningham, A.I. Damokosh, L.M. Neas, J.D. Spengler, P. Koutrakis, J.H. Ware, M. Raizenne, and F.E. Speizer. 1996. Health Effects of Acid Aerosols on North American Children - Respiratory Symptoms. Environmental Health Perspectives 104(5): 500-505. Fung, K.Y., S. Khan, D. Krewski, and Y. Chen. 2006. Association between air pollution and multiple respiratory hospitalizations among the elderly in Vancouver, Canada. Inhalation Toxicology 18 (13): 1005-11. Gilliland, F.D., K. Berhane, E.B. Rappaport, D.C. Thomas, E. Avol, W.J. Gauderman, S.J. London, H.G. Margolis, R. McConnell, K.T. Islam, and J.M. Peters. 2001. The effects of ambient air pollution on school absenteeism due to respiratory illnesses. Epidemiology 12 (1): 43-54. Ito, K., G.D. Thurston, and R.A. Silverman. 2007. Characterization of PM2.5, gaseous pollutants, and meteorological interactions in the context of time-series health effects models. Journal of Exposure Science and Environmental Epidemiology 17 Suppl 2: S45-60. 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An analysis of the association between respiratory symptoms in subjects with asthma and daily air pollution in Spokane, Washington. Inhalation Toxicology 16(13): 809-15. Michaud, J.P., J.S. Grove, and D. Krupitsky. 2004. Emergency department visits and "vog"-related air quality in Hilo, Hawai'i. Environmental Research 95 (1): 11-9. Moolgavkar, S.H. 2000. Air pollution and hospital admissions for diseases of the circulatory system in three U.S. metropolitan areas. Journal of the Air and Waste Management Association 50(7): 1199-206. Moolgavkar, S.H. 2003. Air Pollution and Daily Deaths and Hospital Admissions in Los Angeles and Cook Counties. In: Revised Analyses of Time-Series Studies of Air Pollution and Health. Health Effects Institute. Boston, MA. May. Mortimer, K.M., L.M. Neas, D.W. Dockery, S. Redline, and I.B. Tager. 2002. The effect of air pollution on inner-city children with asthma. European Respiratory Journal 19 (4): 699-705. Norris, G., S.N. Young Pong, J.Q. Koenig, T.V. 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Entity and Attribute Detail Citation: https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development - Center for Public Health and Environmental Assessment CPHEA, EnviroAtlas Geospatial Data Owner 919 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas distributor https://enviroatlas.epa.gov/download/TacWA_metrics_Mar2023_CSV_Shapes.zip download Download The URL providing direct access to the downloadable dataset. download https://enviroatlas.epa.gov/download/TacWA_metrics_Mar2023_FGDB.zip ESRI:ArcGIS API The endpoint of a web service to access the dataset (REST endpoint, WMS GetCapabilities URL, or a SOAP WSDL endpoint). webMapService https://enviroatlas.epa.gov/arcgis/rest/services/Communities/Community_BGmetrics/MapServer information Documentation URL for accessing related documents such as data dictionary, technical information about a dataset, developer documentation, etc. information https://www.epa.gov/enviroatlas/enviroatlas-data information Home Page Alternative landing page used to redirect user to a contextual, Agency-hosted "homepage" for the Dataset or API information dataset Horizontal Positional Accuracy Report Data were collected using methods that have unknown accuracy (EPA National Geospatial Data Policy [NGDP] Accuracy Tier 10). For more information, please see EPA's NGDP at https://epa.gov/geospatial/policies.html Features represented have not been tested for completeness Features represented have not been tested for completeness Tests for integrity have not been performed. This lineage was generated by the FGDC CSDGM to 19139 transformation Estimated incidence for ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter less than 2.5 microns (PM2.5) for all counties in the U.S. using the EPA's BenMAP model. 2012-02-01T00:00:00 Estimated value for ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter less than 2.5 microns (PM2.5) for all counties in the U.S. using the EPA's BenMAP model. 2012-02-01T00:00:00 BenMAP Step 1. Air Quality Grid Creation (created two air quality grids for each pollutant, one baseline year and one control year): 2012-02-01T00:00:00 -Chose grid creation method: monitor direct 2012-02-01T00:00:00 -Selected grid type: county 2012-02-01T00:00:00 -Selected pollutant (created air quality grids for NO2, SO2, O3, and PM2.5) 2012-02-01T00:00:00 -Selected interpolation method: Voronoi Neighborhood Averaging 2012-02-01T00:00:00 -From Library tab, selected monitor dataset that corresponds to selected pollutant 2012-02-01T00:00:00 -From Library tab, selected monitor library years (used 2002 and 2004 for O3, 2000 and 2007 for NO2, 2000 and 2007 for SO2, 2000 and 2006 for PM2.5) 2012-02-01T00:00:00 -Selected Go! 2012-02-01T00:00:00 BenMAP Step 2. Set Custom Parameters (repeated for each different pollutant) 2012-02-01T00:00:00 -Selected Create New Configuration 2012-02-01T00:00:00 -Selected Go! 2012-02-01T00:00:00 -Opened air quality grid baseline file created in step 1 2012-02-01T00:00:00 -Opened air quality grid control file created in step 1 2012-02-01T00:00:00 -Set Latin Hypercube Points to 10 2012-02-01T00:00:00 -Set Population DataSet to United States Census County 2012-02-01T00:00:00 -Set Population Year to 2010 2012-02-01T00:00:00 -Did not set a threshold 2012-02-01T00:00:00 -Selected Next 2012-02-01T00:00:00 -Selected desired concentration-response (CR) functions from the Available CR Functions box 2012-02-01T00:00:00 -Selected Run 2012-02-01T00:00:00 -Saved configuration results 2012-02-01T00:00:00 BenMAP Step 3. Used Results from Step 2 to Set Custom Parameters (repeated for each different pollutant) 2012-02-01T00:00:00 -Selected Create New Configuration for Aggregation, Pooling, and Valuation 2012-02-01T00:00:00 -Selected Go! 2012-02-01T00:00:00 -Opened configuration results file saved in step 2 2012-02-01T00:00:00 -Selected desired results for pooling from Available Incidence Results box 2012-02-01T00:00:00 -Selected pooling method in Select Pooling Methods box 2012-02-01T00:00:00 -Selected Next 2012-02-01T00:00:00 -Selected valuation functions from Valuation Methods box 2012-02-01T00:00:00 -Selected Advanced button 2012-02-01T00:00:00 -Under Currency and Income tab, set Inflation Dataset to EPA Standard Inflators 2012-02-01T00:00:00 -Under Currency and Income tab, set Currency Year to 2010 2012-02-01T00:00:00 -Under Currency and Income tab, set Income Growth Adjustment Dataset to EPA Standard Income Growth 2012-02-01T00:00:00 -Under Currency and Income tab, set Year to 2010 2012-02-01T00:00:00 -Selected Next 2012-02-01T00:00:00 -Saved aggregation, pooling, and valuation configuration 2012-02-01T00:00:00 BenMAP Step 4. Ran Reports (repeated for each different pollutant) 2012-02-01T00:00:00 -Selected Incidence, Valuation, QALY Results: Raw, Aggregated, and Pooled 2012-02-01T00:00:00 -Opened APV configuration results file saved in step 3 2012-02-01T00:00:00 -Chose a result type (saved reports for incidence results, pooled incidence results, valuation results, and pooled valuation results) 2012-02-01T00:00:00 -Selected OK 2012-02-01T00:00:00 -Checked desired fields to be viewed in saved report (included endpoint group, endpoint, pollutant, metric, seasonal metric, author, year, location, race, ethnicity, gender, start age, end age, population, delta, mean where applicable) 2012-02-01T00:00:00 Saved report by going to File > Save and save data as a .csv 2012-02-01T00:00:00 BenMAP Data Processing Steps 2012-03-01T00:00:00 -Compiled data into a spreadsheet that included final results for population, change in pollution concentration (delta), incidence (mean from pooled incidence results), value (mean from pooled valuation results), start age, end age, and metric for each health impact for each county in the U.S. 2012-03-01T00:00:00 -Created BenMAP incidence multiplier for each health impact by dividing incidence estimates by the change in pollution concentration and population to get a number of incidences per change in concentration per person for each county. 2012-03-01T00:00:00 -Created BenMAP value multiplier for each health impact by dividing value estimates by the change in pollution concentration and population to get a dollar value per change in concentration per person for each county. 2012-03-01T00:00:00 EnviroAtlas Final Results Processing Steps 2020-08-01T00:00:00 -Calculated change in pollution concentration as a result of trees in study area using i-Tree Eco pollution model. Change in pollution concentration was calculated based on each possible metric used in the concentration-response functions. 2020-08-01T00:00:00 -Obtained age distribution (by single years) for census tracts within study area from U.S. Census Bureau. 2020-08-01T00:00:00 -Obtained total population for census block groups contained within study area from U.S. Census Bureau. 2020-08-01T00:00:00 -Age distribution by single years is not available for census block groups. Distribution was estimated by applying the age distribution of the census tract in which the block group is located to the total number of people in the block group. Age distribution is necessary because each health impact function is based on a specific age group (derived from start and end age data). 2020-08-01T00:00:00 -Calculated incidence for each block group within study area by multiplying BenMAP incidence multiplier (for county in which block group is located) by change in pollution concentration in block group by block group population. For change in pollution concentration, the pollution metric specific to the health impact function was utilized. For block group population, the age group specific to the health impact function was utilized. 2020-08-01T00:00:00 -Calculated value for each block group within study area by multiplying BenMAP value multiplier (for county in which block group is located) by change in pollution concentration in block group by block group population. For change in pollution concentration, the pollution metric specific to the health impact function was utilized. For block group population, the age group specific to the health impact function was utilized. 2020-08-01T00:00:00 -Summed dollar values for each health category to determine total value of each pollution effect for each block group. 2020-08-01T00:00:00 -Did not sum incidence estimates because some of the health categories may overlap and this would result in double counting. 2020-08-01T00:00:00 unknown 2029-02-13 This metadata was automatically generated from the FGDC Content Standard for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2024-02-09T11:11:00 version of the FGDC CSDGM to ISO 19139 transform. EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development - Center for Public Health and Environmental Assessment CPHEA, EnviroAtlas Geospatial Data Owner 919 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact