A dataset containing environmental health risk factors from the EPA's EJSCREEN environment justice index for census tracts in Maryland. Values are calculated based on aggregations of risk factors, then given as percentiles. Columns starting with "d" are adjusted for one of two different definitions of vulnerable populations. The original dataset, ejscreen, was mistakenly described as the national percentiles, but is actually state-level percentiles, i.e. the percentiles of values within the state of Maryland only. To make nationwide percentiles available without breaking any code, the nationwide percentiles are in a separate dataframe called ej_natl. Both datasets have the same format.
Format
For both ejscreen and ej_natl, a data frame with 19175 rows and 5 variables:
- tract
Character. The tract FIPS code.
- indicator
Factor. The environmental health risk factor, such as proximity to water treatment or air pollution-related cancers.
- value_ptile
Integer. The nationwide percentile of indexed values.
- d2_ptile
Integer. The percentile of indexed values scaled based on a two-factor demographic index (percent low-income and percent people of color).
- d5_ptile
Integer. The percentile of indexed values scaled based on a five-factor demographic index (percent low-income, unemployment rate, percent limited English, percent without high school diploma, low life expectancy).
An object of class tbl_df (inherits from tbl, data.frame) with 19175 rows and 5 columns.
Source
Environmental Protection Agency (EPA) EJSCREEN Environment Justice Index. Data portal, definitions, and methodology are available at https://www.epa.gov/ejscreen/technical-information-about-ejscreen
Examples
head(ejscreen)
#> # A tibble: 6 × 5
#> tract indicator value_ptile d2_ptile d5_ptile
#> <chr> <fct> <int> <int> <int>
#> 1 24001000100 pm25 6 7 9
#> 2 24001000100 ozone 0 0 0
#> 3 24001000100 diesel 3 5 5
#> 4 24001000100 air_cancer 0 0 0
#> 5 24001000100 air_respiratory 0 0 0
#> 6 24001000100 releases_to_air 65 44 73