R/pas_enhanceRawData.R
In MazamaScience/AirSensor2: Process and Display Data from Air Quality Sensors
Defines functions
pas_enhanceRawData
Documented in
pas_enhanceRawData
#' @export
#' @importFrom rlang .data
#'
#' @title Enhance synoptic data from PurpleAir
#'
#' @description Enhance raw synoptic data from PurpleAir to create an improved
#' dataframe compatible with the \pkg{MazamaLocationUtils} package.
#'
#' Steps include:
#'
#' 1) Replace variable names with more consistent, human readable names.
#'
#' 2) Add spatial metadata for each sensor including:
#' \itemize{
#' \item{timezone -- Olson timezone}
#' \item{countryCode -- ISO 3166-1 alpha-2}
#' \item{stateCode -- ISO 3166-2 alpha-2}
#' }
#'
#' 3) Convert data types from character to \code{POSIXct} and \code{numeric}.
#'
#' 4) Add additional metadata items:
#' \itemize{
#' \item{sensorManufacturer = "PurpleAir"}
#' }
#'
#' Limiting spatial searches by country can greatly speed up the process of
#' enhancement. This is performed by providing a vector of ISO country codes to
#' the \code{countryCodes} argument. By default, no subsetting is performed.
#'
#' Users may further improve performance by also specifying \code{stateCodes}
#' when \code{countryCodes} is limited to a single country.
#'
#' When a single US state is specified, named \code{counties} may be specified
#' to further speed up performance.
#'
#' @param pas_raw Dataframe returned by \link{pas_downloadParseRawData}.
#' @param countryCodes ISO 3166-1 alpha-2 country codes used to subset the data.
#' @param stateCodes ISO-3166-2 alpha-2 state codes used to subset the data.
#' @param counties US county names or 5-digit FIPS codes used to subset the data.
#'
#' @return Enhanced dataframe of synoptic PurpleAir data.
#'
#' @seealso \link{pas_downloadParseRawData}
#'
#' @references \href{https://www2.purpleair.com}{PurpleAir}
#' @references \href{https://api.purpleair.com/}{PurpleAir API}
#' @references \href{https://www2.purpleair.com/policies/terms-of-service}{PurpleAir Terms of service}
#' @references \href{https://www2.purpleair.com/pages/license}{PurpleAir Data license}
#' @references \href{https://www2.purpleair.com/pages/attribution}{PurpleAir Data Attribution}
#'
pas_enhanceRawData <- function(
pas_raw = NULL,
countryCodes = "US",
stateCodes = NULL,
counties = NULL
) {
# ----- Validate Parameters --------------------------------------------------
MazamaCoreUtils::stopIfNull(pas_raw)
MazamaCoreUtils::stopIfNull(countryCodes)
if ( !is.data.frame(pas_raw) )
stop("parameter 'pas_raw' parameter is not a dataframe")
# Guarantee uppercase codes
countryCodes <- toupper(countryCodes)
# Validate countryCodes
if ( any(!(countryCodes %in% countrycode::codelist$iso2c)) )
stop("parameter 'countryCodes' has values that are not recognized as ISO-2 country codes")
if ( !is.null(stateCodes) ) {
if ( is.null(countryCodes) ) {
stop("'stateCodes' can only be used when also specifying a single country with 'countryCodes'")
} else if ( length(countryCodes) != 1 ) {
stop("please limit 'countryCodes' to a single country when using 'stateCodes'")
}
if ( !is.null(counties) ) {
if ( length(stateCodes) != 1 ) {
stop("please limit 'stateCodes' to a single state when using 'counties'")
}
}
}
if ( !"longitude" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'longitude' column as required by pas_enhanceRawData()")
}
if ( !"latitude" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'latitude' column as required by pas_enhanceRawData()")
}
if ( !"location_type" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'location_type' column as required by pas_enhanceRawData()")
}
# ----- Harmonize table ------------------------------------------------------
# > dplyr::glimpse(pas_raw, width = 75)
# Rows: 1,999
# Columns: 37
# $ sensor_index <chr> "453", "131585", "131611", "131707", "896", …
# $ last_modified <dttm> 2019-09-04 21:14:11, 2022-01-29 19:14:34, 2…
# $ date_created <dttm> 2016-11-07 18:24:07, 2021-10-05 22:00:29, 2…
# $ last_seen <dttm> 2023-02-18 00:47:35, 2023-02-18 00:47:48, 2…
# $ private <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ name <chr> "LRAPA-Oakridge City Hall", "1907 ZE Outside…
# $ icon <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ location_type <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ model <chr> "PA-II", "PA-II-SD", "PA-II", "PA-II-SD", "P…
# $ hardware <chr> "2.0+1M+BME280+PMSX003-B+PMSX003-A", "2.0+OP…
# $ led_brightness <dbl> 25, 35, 35, 35, 35, 35, 15, 35, 35, 35, 35, …
# $ firmware_version <chr> "6.06b", "7.02", "7.02", "7.02", "6.06b", "7…
# $ firmware_upgrade <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
# $ rssi <dbl> -63, -66, -75, -47, -74, -90, -88, -73, -65,…
# $ uptime <dbl> 3112, 68034, 6028, 10397, 3646, 11740, 25, 5…
# $ pa_latency <dbl> 221, 256, 458, 514, 219, 308, NA, 250, 234, …
# $ memory <dbl> 16136, 16064, 15768, 16320, 15872, 16120, 31…
# $ position_rating <dbl> 5, 5, 5, 0, 5, 0, 5, 5, 5, 5, 5, 0, 5, 2, 5,…
# $ latitude <dbl> 43.74751, 45.49798, 42.30729, 48.81992, 48.9…
# $ longitude <dbl> -122.4567, -122.6099, -122.8396, -119.1847, …
# $ altitude <dbl> 1229, 233, 1650, 3650, 160, 663, 185, 190, 2…
# $ channel_state <chr> "3", "3", "3", "3", "3", "3", "3", "3", "3",…
# $ channel_flags <chr> "1", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ channel_flags_manual <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ channel_flags_auto <chr> "1", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ confidence <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ confidence_auto <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ confidence_manual <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ humidity <dbl> 32, 37, 19, 31, 57, 69, 56, 49, 50, 57, 56, …
# $ temperature <dbl> 56, 61, 62, 72, 52, 49, 53, 55, 54, 51, 52, …
# $ pressure <dbl> 978.10, 1017.26, 961.68, 889.75, 1017.72, 10…
# $ pm2.5_10minute <dbl> 0.0, 12.1, 0.0, 1.8, 5.0, 4.8, 6.3, 2.2, 5.4…
# $ pm2.5_30minute <dbl> 0.0, 12.0, 0.0, 3.9, 6.0, 4.6, 4.8, 1.6, 3.8…
# $ pm2.5_60minute <dbl> 0.0, 12.8, 0.4, 7.2, 6.7, 3.7, 5.8, 1.8, 3.8…
# $ pm2.5_6hour <dbl> 0.0, 22.8, 5.4, 8.2, 10.0, 1.6, 9.2, 7.0, 9.…
# $ pm2.5_24hour <dbl> 0.0, 25.2, 6.1, 5.9, 10.6, 1.6, 11.8, 10.9, …
# $ pm2.5_1week <dbl> 0.0, 16.7, 5.4, 8.6, 10.6, 2.0, 14.9, 12.8, …
pas <- pas_raw
# Go through each step and only perform action if that parameter exists
# * Harmonize basic fields
# Privacy
if ( "private" %in% names(pas) ) {
pas$privacy <- dplyr::if_else(pas$private == "0", "public", "private", as.character(NA))
pas$private <- NULL
}
# sensorManufacturer
pas$sensorManufacturer <- "PurpleAir"
# deviceID
# sensor_index is guaranteed to exist
pas$deviceID = paste0("pa.", pas$sensor_index)
# location_type is guaranteed to exist
pas$location_type = dplyr::if_else(pas$location_type == "0", "outside", "inside", as.character(NA))
# elevation
if ( "altitude" %in% names(pas) ) {
pas$elevation = round(pas$altitude * 0.3048) # convert from feet to meters
} else {
pas$elevation = as.numeric(NA)
}
# Remove unwanted fields
if ( "icon" %in% names(pas) ) {
pas$icon <- NULL
}
# * Add core metadata -----
# NOTE: precision = 9 results in a precision of ~2 meters
pas <-
pas %>%
MazamaLocationUtils::table_addCoreMetadata(precision = 9) %>%
# Unique identifier
dplyr::mutate(
deviceDeploymentID = paste0(.data$locationID, "_", .data$deviceID),
locationName = .data$name
)
# TODO: This step can be removed when AirMonitor gets upgraded to replace
# TODO: 'zip' with 'postalCode'.
if ( !"zip" %in% names(pas) ) {
pas$zip <- pas$postalCode
}
if ( !"postalCode" %in% names(pas) ) {
pas$postalCode <- pas$zip
}
# Put 'deviceDeploymentID' and 'deviceID' in front
startingIDs <- c("deviceDeploymentID", "deviceID", "locationID")
otherColumns <- setdiff(names(pas), startingIDs)
orderedColumns <- c(startingIDs, otherColumns)
pas <- pas %>% dplyr::select(dplyr::all_of(orderedColumns))
# ----- Add spatial metadata -------------------------------------------------
# * countryCode -----
pas$countryCode <-
MazamaSpatialUtils::getCountryCode(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = FALSE # No buffering needed with the EEZ dataset
)
# Limit to valid countryCodes
pas <-
pas %>%
dplyr::filter(!is.na(.data$countryCode))
# * stateCode -----
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$stateCode <-
MazamaSpatialUtils::getStateCode(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# Limit to valid stateCodes
if ( !is.null(stateCodes) ) {
pas <-
pas %>%
dplyr::filter(.data$stateCode %in% stateCodes)
}
# * countyName -----
if ( length(countryCodes) == 1 && countryCodes[1] == "US" ) {
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$countyName <-
MazamaSpatialUtils::getUSCounty(
longitude = pas$longitude,
latitude = pas$latitude,
stateCodes = stateCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# Limit to valid counties
if ( !is.null(counties) ) {
counties <- as.character(counties)
# Convert from FIPS to countyName
if ( stringr::str_detect(counties[1], "[0-9]{5}") ) {
counties <-
MazamaSpatialUtils::US_countyFIPSToName(
state = stateCodes,
countyFIPS = counties
)
}
# Handle input inconsistencies
counties <-
stringr::str_to_title(counties) %>%
stringr::str_replace(" County", "")
# Limit to valid counties
pas <-
pas %>%
dplyr::filter(.data$countyName %in% counties)
}
}
# * timezone -----
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$timezone <-
MazamaSpatialUtils::getTimezone(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# ----- Return ---------------------------------------------------------------
# Add the "PurpleAir_synoptic" class name
class(pas) <- union("PurpleAir_synoptic", class(pas))
return(pas)
}
MazamaScience/AirSensor2 documentation built on Oct. 31, 2024, 1:39 a.m.
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Defines functions pas_enhanceRawData
Documented in pas_enhanceRawData
#' @export
#' @importFrom rlang .data
#'
#' @title Enhance synoptic data from PurpleAir
#'
#' @description Enhance raw synoptic data from PurpleAir to create an improved
#' dataframe compatible with the \pkg{MazamaLocationUtils} package.
#'
#' Steps include:
#'
#' 1) Replace variable names with more consistent, human readable names.
#'
#' 2) Add spatial metadata for each sensor including:
#' \itemize{
#' \item{timezone -- Olson timezone}
#' \item{countryCode -- ISO 3166-1 alpha-2}
#' \item{stateCode -- ISO 3166-2 alpha-2}
#' }
#'
#' 3) Convert data types from character to \code{POSIXct} and \code{numeric}.
#'
#' 4) Add additional metadata items:
#' \itemize{
#' \item{sensorManufacturer = "PurpleAir"}
#' }
#'
#' Limiting spatial searches by country can greatly speed up the process of
#' enhancement. This is performed by providing a vector of ISO country codes to
#' the \code{countryCodes} argument. By default, no subsetting is performed.
#'
#' Users may further improve performance by also specifying \code{stateCodes}
#' when \code{countryCodes} is limited to a single country.
#'
#' When a single US state is specified, named \code{counties} may be specified
#' to further speed up performance.
#'
#' @param pas_raw Dataframe returned by \link{pas_downloadParseRawData}.
#' @param countryCodes ISO 3166-1 alpha-2 country codes used to subset the data.
#' @param stateCodes ISO-3166-2 alpha-2 state codes used to subset the data.
#' @param counties US county names or 5-digit FIPS codes used to subset the data.
#'
#' @return Enhanced dataframe of synoptic PurpleAir data.
#'
#' @seealso \link{pas_downloadParseRawData}
#'
#' @references \href{https://www2.purpleair.com}{PurpleAir}
#' @references \href{https://api.purpleair.com/}{PurpleAir API}
#' @references \href{https://www2.purpleair.com/policies/terms-of-service}{PurpleAir Terms of service}
#' @references \href{https://www2.purpleair.com/pages/license}{PurpleAir Data license}
#' @references \href{https://www2.purpleair.com/pages/attribution}{PurpleAir Data Attribution}
#'
pas_enhanceRawData <- function(
pas_raw = NULL,
countryCodes = "US",
stateCodes = NULL,
counties = NULL
) {
# ----- Validate Parameters --------------------------------------------------
MazamaCoreUtils::stopIfNull(pas_raw)
MazamaCoreUtils::stopIfNull(countryCodes)
if ( !is.data.frame(pas_raw) )
stop("parameter 'pas_raw' parameter is not a dataframe")
# Guarantee uppercase codes
countryCodes <- toupper(countryCodes)
# Validate countryCodes
if ( any(!(countryCodes %in% countrycode::codelist$iso2c)) )
stop("parameter 'countryCodes' has values that are not recognized as ISO-2 country codes")
if ( !is.null(stateCodes) ) {
if ( is.null(countryCodes) ) {
stop("'stateCodes' can only be used when also specifying a single country with 'countryCodes'")
} else if ( length(countryCodes) != 1 ) {
stop("please limit 'countryCodes' to a single country when using 'stateCodes'")
}
if ( !is.null(counties) ) {
if ( length(stateCodes) != 1 ) {
stop("please limit 'stateCodes' to a single state when using 'counties'")
}
}
}
if ( !"longitude" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'longitude' column as required by pas_enhanceRawData()")
}
if ( !"latitude" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'latitude' column as required by pas_enhanceRawData()")
}
if ( !"location_type" %in% names(pas_raw) ) {
stop("Parameter 'pas_raw' does not have a 'location_type' column as required by pas_enhanceRawData()")
}
# ----- Harmonize table ------------------------------------------------------
# > dplyr::glimpse(pas_raw, width = 75)
# Rows: 1,999
# Columns: 37
# $ sensor_index <chr> "453", "131585", "131611", "131707", "896", …
# $ last_modified <dttm> 2019-09-04 21:14:11, 2022-01-29 19:14:34, 2…
# $ date_created <dttm> 2016-11-07 18:24:07, 2021-10-05 22:00:29, 2…
# $ last_seen <dttm> 2023-02-18 00:47:35, 2023-02-18 00:47:48, 2…
# $ private <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ name <chr> "LRAPA-Oakridge City Hall", "1907 ZE Outside…
# $ icon <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ location_type <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ model <chr> "PA-II", "PA-II-SD", "PA-II", "PA-II-SD", "P…
# $ hardware <chr> "2.0+1M+BME280+PMSX003-B+PMSX003-A", "2.0+OP…
# $ led_brightness <dbl> 25, 35, 35, 35, 35, 35, 15, 35, 35, 35, 35, …
# $ firmware_version <chr> "6.06b", "7.02", "7.02", "7.02", "6.06b", "7…
# $ firmware_upgrade <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
# $ rssi <dbl> -63, -66, -75, -47, -74, -90, -88, -73, -65,…
# $ uptime <dbl> 3112, 68034, 6028, 10397, 3646, 11740, 25, 5…
# $ pa_latency <dbl> 221, 256, 458, 514, 219, 308, NA, 250, 234, …
# $ memory <dbl> 16136, 16064, 15768, 16320, 15872, 16120, 31…
# $ position_rating <dbl> 5, 5, 5, 0, 5, 0, 5, 5, 5, 5, 5, 0, 5, 2, 5,…
# $ latitude <dbl> 43.74751, 45.49798, 42.30729, 48.81992, 48.9…
# $ longitude <dbl> -122.4567, -122.6099, -122.8396, -119.1847, …
# $ altitude <dbl> 1229, 233, 1650, 3650, 160, 663, 185, 190, 2…
# $ channel_state <chr> "3", "3", "3", "3", "3", "3", "3", "3", "3",…
# $ channel_flags <chr> "1", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ channel_flags_manual <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ channel_flags_auto <chr> "1", "0", "0", "0", "0", "0", "0", "0", "0",…
# $ confidence <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ confidence_auto <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ confidence_manual <dbl> 0, 100, 100, 100, 100, 100, 100, 100, 100, 1…
# $ humidity <dbl> 32, 37, 19, 31, 57, 69, 56, 49, 50, 57, 56, …
# $ temperature <dbl> 56, 61, 62, 72, 52, 49, 53, 55, 54, 51, 52, …
# $ pressure <dbl> 978.10, 1017.26, 961.68, 889.75, 1017.72, 10…
# $ pm2.5_10minute <dbl> 0.0, 12.1, 0.0, 1.8, 5.0, 4.8, 6.3, 2.2, 5.4…
# $ pm2.5_30minute <dbl> 0.0, 12.0, 0.0, 3.9, 6.0, 4.6, 4.8, 1.6, 3.8…
# $ pm2.5_60minute <dbl> 0.0, 12.8, 0.4, 7.2, 6.7, 3.7, 5.8, 1.8, 3.8…
# $ pm2.5_6hour <dbl> 0.0, 22.8, 5.4, 8.2, 10.0, 1.6, 9.2, 7.0, 9.…
# $ pm2.5_24hour <dbl> 0.0, 25.2, 6.1, 5.9, 10.6, 1.6, 11.8, 10.9, …
# $ pm2.5_1week <dbl> 0.0, 16.7, 5.4, 8.6, 10.6, 2.0, 14.9, 12.8, …
pas <- pas_raw
# Go through each step and only perform action if that parameter exists
# * Harmonize basic fields
# Privacy
if ( "private" %in% names(pas) ) {
pas$privacy <- dplyr::if_else(pas$private == "0", "public", "private", as.character(NA))
pas$private <- NULL
}
# sensorManufacturer
pas$sensorManufacturer <- "PurpleAir"
# deviceID
# sensor_index is guaranteed to exist
pas$deviceID = paste0("pa.", pas$sensor_index)
# location_type is guaranteed to exist
pas$location_type = dplyr::if_else(pas$location_type == "0", "outside", "inside", as.character(NA))
# elevation
if ( "altitude" %in% names(pas) ) {
pas$elevation = round(pas$altitude * 0.3048) # convert from feet to meters
} else {
pas$elevation = as.numeric(NA)
}
# Remove unwanted fields
if ( "icon" %in% names(pas) ) {
pas$icon <- NULL
}
# * Add core metadata -----
# NOTE: precision = 9 results in a precision of ~2 meters
pas <-
pas %>%
MazamaLocationUtils::table_addCoreMetadata(precision = 9) %>%
# Unique identifier
dplyr::mutate(
deviceDeploymentID = paste0(.data$locationID, "_", .data$deviceID),
locationName = .data$name
)
# TODO: This step can be removed when AirMonitor gets upgraded to replace
# TODO: 'zip' with 'postalCode'.
if ( !"zip" %in% names(pas) ) {
pas$zip <- pas$postalCode
}
if ( !"postalCode" %in% names(pas) ) {
pas$postalCode <- pas$zip
}
# Put 'deviceDeploymentID' and 'deviceID' in front
startingIDs <- c("deviceDeploymentID", "deviceID", "locationID")
otherColumns <- setdiff(names(pas), startingIDs)
orderedColumns <- c(startingIDs, otherColumns)
pas <- pas %>% dplyr::select(dplyr::all_of(orderedColumns))
# ----- Add spatial metadata -------------------------------------------------
# * countryCode -----
pas$countryCode <-
MazamaSpatialUtils::getCountryCode(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = FALSE # No buffering needed with the EEZ dataset
)
# Limit to valid countryCodes
pas <-
pas %>%
dplyr::filter(!is.na(.data$countryCode))
# * stateCode -----
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$stateCode <-
MazamaSpatialUtils::getStateCode(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# Limit to valid stateCodes
if ( !is.null(stateCodes) ) {
pas <-
pas %>%
dplyr::filter(.data$stateCode %in% stateCodes)
}
# * countyName -----
if ( length(countryCodes) == 1 && countryCodes[1] == "US" ) {
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$countyName <-
MazamaSpatialUtils::getUSCounty(
longitude = pas$longitude,
latitude = pas$latitude,
stateCodes = stateCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# Limit to valid counties
if ( !is.null(counties) ) {
counties <- as.character(counties)
# Convert from FIPS to countyName
if ( stringr::str_detect(counties[1], "[0-9]{5}") ) {
counties <-
MazamaSpatialUtils::US_countyFIPSToName(
state = stateCodes,
countyFIPS = counties
)
}
# Handle input inconsistencies
counties <-
stringr::str_to_title(counties) %>%
stringr::str_replace(" County", "")
# Limit to valid counties
pas <-
pas %>%
dplyr::filter(.data$countyName %in% counties)
}
}
# * timezone -----
# Suppress annoying 'Discarded datum Unknown' messages
suppressWarnings({
pas$timezone <-
MazamaSpatialUtils::getTimezone(
longitude = pas$longitude,
latitude = pas$latitude,
countryCodes = countryCodes,
allData = FALSE,
useBuffering = TRUE
)
})
# ----- Return ---------------------------------------------------------------
# Add the "PurpleAir_synoptic" class name
class(pas) <- union("PurpleAir_synoptic", class(pas))
return(pas)
}
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