An R interface to United States Environmental Protection Agency (EPA) Environmental Compliance History Online ('ECHO') Application Program Interface (API). 'ECHO' provides information about EPA permitted facilities, discharges, and other reporting info associated with permitted entities. Data are obtained from < https://echo.epa.gov/>.
echor downloads wastewater discharge and air emission data for EPA permitted facilities using the EPA ECHO API.
echor is on CRAN:
install.packages("echor")
Or install the development version from github:
devtools::install_github("mps9506/echor")
We can look up plants by permit id, bounding box, and numerous other parameters. I plan on providing documentation of available parameters. However, arguments can be looked up here: get_cwa_rest_services_get_facility_info
library(tidyverse)library(echor)## echoWaterGetFacilityInfo() will return a dataframe or simple features (sf) dataframe.df <- echoWaterGetFacilityInfo(output = "df",xmin = '-96.387509',ymin = '30.583572',xmax = '-96.281422',ymax = '30.640008')head(df)#> # A tibble: 6 x 26#> CWPName SourceID CWPStreet CWPCity CWPState CWPStateDistrict CWPZip#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>#> 1 ACE TOWNH~ TXR15667I 2136 CHES~ COLLEG~ TX "" 77845~#> 2 ASTIN AVI~ TXR05CE76 1770 GEOR~ COLLEG~ TX "" 77845~#> 3 AT HOME -~ TXR15591P 2301 EARL~ COLLEG~ TX "" 77845~#> 4 BEE CREEK~ TXR15647M THE SITE ~ COLLEG~ TX "" 77845#> 5 BOSSIER P~ LAG830191 3228 BARK~ BENTON LA "" 71111#> 6 BROADSTON~ TXR10F50H NW OF ATL~ BRYAN TX "" 77807#> # ... with 19 more variables: MasterExternalPermitNmbr <chr>,#> # RegistryID <chr>, CWPCounty <chr>, CWPEPARegion <chr>,#> # FacDerivedHuc <chr>, FacLat <dbl>, FacLong <dbl>,#> # CWPTotalDesignFlowNmbr <dbl>, CWPActualAverageFlowNmbr <dbl>,#> # ReceivingMs4Name <chr>, AssociatedPollutant <chr>,#> # MsgpPermitType <chr>, CWPPermitStatusDesc <chr>,#> # CWPPermitTypeDesc <chr>, CWPIssueDate <date>, CWPEffectiveDate <date>,#> # CWPExpirationDate <date>, CWPSNCStatusDate <date>,#> # CWPStateWaterBodyCode <chr>
The ECHO database can provide over 270 different columns. echor returns
a subset of these columns that should work for most users. However, you
can specify what data you want returned. Use echoWaterGetMeta()
to
return a dataframe with column numbers, names, and descriptions to
identify the columns you want returned. Then include the column numbers
as a comma seperated string in the qcolumns
argument. In the example
below, the qcolumns
argument indicates the dataframe will include
plant name, 8-digit HUC, latitute, longitude, and total design flow.
df <- echoWaterGetFacilityInfo(output = "df",xmin = '-96.387509',ymin = '30.583572',xmax = '-96.281422',ymax = '30.640008',qcolumns = '1,14,23,24,25')head(df)#> # A tibble: 6 x 6#> CWPName SourceID FacDerivedHuc FacLat FacLong CWPTotalDesignFl~#> <chr> <chr> <chr> <dbl> <dbl> <dbl>#> 1 ACE TOWNHOME TXR1566~ 12070103 30.6 -96.3 NA#> 2 ASTIN AVIATION TXR05CE~ 12070101 30.6 -96.4 NA#> 3 AT HOME - COLLE~ TXR1559~ 12070103 30.6 -96.3 NA#> 4 BEE CREEK SANIT~ TXR1564~ 12070103 30.6 -96.3 NA#> 5 BOSSIER PARISH ~ LAG8301~ 12070103 30.6 -96.3 NA#> 6 BROADSTONE TRAD~ TXR10F5~ 12070101 30.6 -96.4 NA
When returned as sf dataframes, the data is suitable for immediate spatial plotting or analysis:
library(ggmap)library(sf)library(ggrepel)## This example requires the development version of ggplot with support## for geom_sf()## and uses theme_ipsum_rc() from library(hrbrthemes)df <- echoWaterGetFacilityInfo(output = "sf",xmin = '-96.387509',ymin = '30.583572',xmax = '-96.281422',ymax = '30.640008')collegestation <- get_map(location = c(-96.387509, 30.583572,-96.281422, 30.640008),zoom = 14, maptype = "toner")##to make labels, need to map the coords and use geom_text :(## can't help but think there is an easier way to do thisdf <- df %>%mutate(coords = map(geometry, st_coordinates),coords_x = map_dbl(coords, 1),coords_y = map_dbl(coords, 2))ggmap(collegestation) +geom_sf(data = df, inherit.aes = FALSE, shape = 21,color = "darkred", fill = "darkred",size = 2, alpha = 0.25) +geom_label_repel(data = df, aes(x = coords_x, y = coords_y, label = SourceID),point.padding = .5, min.segment.length = 0.1,size = 2, color = "dodgerblue") +theme_ipsum_rc() +labs(x = "Longitude", y = "Latitude",title = "NPDES permits near Texas A&M",caption = "Source: EPA ECHO database")
Use echoGetEffluent()
or echoGetCAAPR()
to download tidy dataframes
of permitted water discharger Discharge Monitoring Report (DMR) or
permitted emitters Clean Air Act annual emissions reports.
df <- echoGetEffluent(p_id = 'TX0119407', parameter_code = '00300')df <- df %>%filter(!is.na(dmr_value_nmbr) & limit_value_type_code == "C1")ggplot(df) +geom_line(aes(monitoring_period_end_date, dmr_value_nmbr)) +theme_ipsum_rc(grid = "Y") +labs(x = "Monitoring period date",y = "Dissolved oxygen concentration (mg/l)",title = "Reported minimum dissolved oxygen concentration",subtitle = "NPDES ID = TX119407",caption = "Source: EPA ECHO")
library(echor)date()#> [1] "Fri Feb 01 20:21:37 2019"devtools::test()#> v | OK F W S | Context#>/ | 0 | core functions return expected errors- | 1 | core functions return expected errors\ | 2 | core functions return expected errors| | 3 | core functions return expected errors/ | 4 | core functions return expected errors- | 5 | core functions return expected errors\ | 6 | core functions return expected errors| | 7 | core functions return expected errors/ | 8 | core functions return expected errors- | 9 | core functions return expected errorsv | 9 | core functions return expected errors [1.1 s]#>/ | 0 | core functions return expected objects- | 1 | core functions return expected objects\ | 2 | core functions return expected objects| | 3 | core functions return expected objects/ | 4 | core functions return expected objects- | 5 | core functions return expected objects\ | 6 | core functions return expected objects| | 7 | core functions return expected objects/ | 8 | core functions return expected objects- | 9 | core functions return expected objects\ | 10 | core functions return expected objects| | 11 | core functions return expected objects/ | 12 | core functions return expected objects- | 13 | core functions return expected objectsv | 13 | core functions return expected objects [10.0 s]#>#> == Results =================================================================================================#> Duration: 11.1 s#>#> OK: 22#> Failed: 0#> Warnings: 0#> Skipped: 0
downloadDMRs()
Returns a tidy dataframe with dmr reports. (closes #38)echoGetEffluent()
uses a different API call to returns a flat dmr report (one plant at a time). Existing arguments remain the same and still returns a dataframe. (closes #37)echoGetFacilities()
and echoGetReports()
wrap the individual functions to streamline functions that users need to be familiar with. (closes #33)echoWaterGetMeta()
and echoAirGetMeta()
functions to retrieve column metadata returned by echoWaterGetFacilityInfo()
and echoAirGetFacilityInfo()
; specify columns returned by respective functions by including qcolumns argument in respective functions. (closes #28).qcolumns
argument to echoWaterGetFacilityInfo()
to ensure reasonable default columns are returned (#29).echoWaterGetFacilityInfo()
properly returns large datasets. The new internal function getDownload()
downloads the entire CSV of queried data as a dataframe (closes #27).qcolumns
argument to echoAirGetFacilityInfo()
to ensure reasonable default columns are returned (#29).echoAirGetFacilityInfo()
properly returns large datasets. The new internal function getDownload()
downloads the entire CSV of queried data as a dataframe (closes #27).echoSDWGetSystems()
downloads data for public drinking water systems.echoSDWGetMeta()
downloads metadata for columns returned by echoSDWGetSystems()
skip_on_cran()
instead of httptest::with_mock_API()
pkg::fun()
NEWS.md
file to track changes to the package.