Maps

Interactive map of air monitors

Site map

library(tidyverse)
library(leaflet)

# Load site coordinates
sites <- read_csv('https://raw.githubusercontent.com/MPCA-air/aqi-watch/master/data-raw/locations.csv')

# Map sites
leaflet(sites) %>%
   addMarkers()

Add a basemap

# Add basemap
leaflet(sites) %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addMarkers()

Add pop-ups

# Add site name popup labels and dark basemap
leaflet(sites) %>%
  addProviderTiles(providers$CartoDB.DarkMatter) %>%
  addMarkers(popup = ~`Site Name`)

Creating shapefiles in R

The code below shows how to create a shapefile from air monitoring locations. This map is then joined to the Environmental Justice status for Census tracts.

library(tidyverse)
library(stringr)
library(RcppRoll)
library(lubridate)
library(car)
library(DT)

data <- read_csv('https://raw.githubusercontent.com/MPCA-air/air-methods/master/airtoxics_data_2009_2013.csv')

colnames(data) <- c("aqs_id", "poc", "param_code", "date", "conc", "null_code", "md_limit", "pollutant", "year", "cas")

dt_options <- list(scrollX = T, autoWidth = T, searching = F, ordering=F, lengthChange = F, paginate=F, info=F)


########################################################################
## Spatial join to census tracts and then left_join to EJ areas        #
########################################################################
coords <- monitoring_locations[, c("Longitude", "Latitude")]

point_source_wypoints <- SpatialPointsDataFrame(coords, 
                                                data = data, 
                                                proj4string = CRS('+proj=longlat +ellps=WGS84'))

point_source_wypoints <- spTransform(point_source_wypoints, 
                                     CRS('+proj=utm +zone=15 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0'))

census_tracts <- readOGR(dsn   = "R:/demographics", 
                         layer = "census_2010_tracts_usboc", 
                         stringsAsFactors = FALSE)

point_sources_files_geo <- point.in.poly(point_source_wypoints, census_tracts)

writeOGR(obj    = point_sources_files_geo, 
         dsn    = "X:/Programs/Air_Quality_Programs/Air Monitoring Data and Risks/0 Methods and documentation/3. Analysis methods/Web book/air-methods", 
         layer  = "airmonitors_tracts", 
         driver = "ESRI Shapefile")

point_sources_tracts_dbf <- read.dbf("X:/Programs/Air_Quality_Programs/Air Monitoring Data and Risks/0 Methods and documentation/3. Analysis methods/Web book/air-methods/airmonitors_tracts.dbf", as.is = TRUE)

ej_layers <- read.dbf("X:/Agency_Files/EJ/GIS/Shapefiles/ACS_2014_5Yr_Tract_MNPovPPC.dbf", as.is = TRUE)

ej_layers <- ej_layers[, c("GEOID", "ov50per_nw", "prp_under1")]

point_sources_tracts_ej <- left_join(point_sources_tracts_dbf, ej_layers, by = c("GEOID10"="GEOID"))

names(point_sources_tracts_ej) <- c("Facility_ID",  "Facility_Name", "Resident_Cancer_Risk", "Resident_Hazard_Quotient", "CAS", "Pollutant",  "Latitude", "Longitude", "Annual_PM25_Concentration", "STATEFP", "COUNTYF", "TRACTCE", "GEOID10", "NAME10", "NAMELSA", "MTFCC10", "FUNCSTA", "ALAND10", "AWATER1", "INTPTLA", "INTPTLO", "ov50per_nw", "prp_under1")

#Output file name (including path)
point_sources_tracts_ej <- unique(point_sources_tracts_ej)