#' @export
#' @importFrom MazamaCoreUtils logger.trace logger.debug logger.warn logger.error
#'
#' @title Apply Quality Control to raw WRCC EBAM tibble
#'
#' @param tbl Single site titbble created by \code{wrcc_parseData()}.
#' @param valid_Longitude Range of valid Longitude values.
#' @param valid_Latitude Range of valid Latitude values.
#' @param remove_Lon_zero Logical specifying removal of rows where Longitude == 0.
#' @param remove_Lat_zero Logical specifying removal of rows where Latitude == 0.
#' @param valid_Flow Range of valid Flow values.
#' @param valid_AT Range of valid AT values.
#' @param valid_RHi Range of valid RHi values.
#' @param valid_Conc Range of valid ConcHr values.
#' @param flagAndKeep Logical specifying flagging, rather than removal, of bad
#' data during the QC process.
#'
#' @description Perform various QC measures on WRCC EBAM data.
#'
#' Any numeric values matching the following are converted to \code{NA}
#' \itemize{
#' \item{\code{x < -900}}
#' \item{\code{x == -9.9899}}
#' \item{\code{x == 99999}}
#' }
#'
#' The following columns of data are tested against valid ranges:
#' \itemize{
#' \item{\code{Flow}}
#' \item{\code{AT}}
#' \item{\code{RHi}}
#' \item{\code{ConcHr}}
#' }
#'
#' A \code{POSIXct datetime} column (UTC) is also added based on \code{DateTime}.
#'
#' @return Cleaned up tibble of WRCC monitor data.
#' @seealso \code{\link{wrcc_qualityControl}}
wrcc_EBAMQualityControl <- function(
tbl,
valid_Longitude = c(-180, 180),
valid_Latitude = c(-90, 90),
remove_Lon_zero = TRUE,
remove_Lat_zero = TRUE,
valid_Flow = c(16.7*0.95, 16.7*1.05),
valid_AT = c(-Inf, 45),
# NOTE: 2021-07-07 Update RHi from 45 -> 50 as per conversation with Pete Lahm
valid_RHi = c(-Inf, 50),
# NOTE: Update ConcHr from 984 -> 5000 as per conversation with Mike Broughton
valid_Conc = c(-Inf, 5000),
flagAndKeep = FALSE
) {
logger.debug(" ----- wrcc_EBAMQualityControl() ----- ")
# TODO: What about Alarm?
# NOTE: > names(tbl)
# NOTE: [1] "DateTime" "GPSLat" "GPSLon" "Type" "SerialNumber" "ConcRT"
# NOTE: [7] "Misc1" "AvAirFlw" "AvAirTemp" "RelHumidity" "Misc2" "SensorIntAT"
# NOTE: [13] "SensorIntRH" "WindSpeed" "WindDir" "BatteryVoltage" "Alarm" "monitorName"
# NOTE: [19] "monitorType"
monitorName <- tbl$monitorName[1]
# ----- Missing Values -------------------------------------------------------
# Handle various missing value flags (lots of variants of -99x???)
tbl[tbl < -900] <- NA
tbl[tbl == -9.9899] <- NA
tbl[tbl == 99999] <- NA
# ----- Setup for flagAndKeep argument utility -------------------------------
if ( flagAndKeep ) {
# verb for logging messages
verb <- "Flagging"
tbl$rowID <- as.integer(rownames(tbl))
# duplicate tbl and add columns for flags
tblFlagged <- tbl
tblFlagged$QCFlag_anyBad <- FALSE
tblFlagged$QCFlag_reasonCode <- NA
tblFlagged$QCFlag_badLon <- FALSE
tblFlagged$QCFlag_badLat <- FALSE
tblFlagged$QCFlag_badType <- FALSE # no type info for ESAMs
tblFlagged$QCFlag_badFlow <- FALSE
tblFlagged$QCFlag_badAT <- FALSE
tblFlagged$QCFlag_badRHi <- FALSE
tblFlagged$QCFlag_badConcHr <- FALSE
tblFlagged$QCFlag_badDateAndTime <- FALSE
tblFlagged$QCFlag_duplicateHr <- FALSE
} else {
# verb for logging messages
verb <- "Discarding"
}
# ----- Location -------------------------------------------------------------
# Latitude and longitude must be in range
if ( remove_Lon_zero ) {
goodLonMask <- !is.na(tbl$GPSLon) & (tbl$GPSLon >= valid_Longitude[1]) & (tbl$GPSLon <= valid_Longitude[2]) & (tbl$GPSLon != 0)
} else {
goodLonMask <- !is.na(tbl$GPSLon) & (tbl$GPSLon >= valid_Longitude[1]) & (tbl$GPSLon <= valid_Longitude[2])
}
if ( remove_Lat_zero ) {
goodLatMask <- !is.na(tbl$GPSLat) & (tbl$GPSLat >= valid_Latitude[1]) & (tbl$GPSLat <= valid_Latitude[2]) & (tbl$GPSLat != 0)
} else {
goodLatMask <- !is.na(tbl$GPSLat) & (tbl$GPSLat >= valid_Latitude[1]) & (tbl$GPSLat <= valid_Latitude[2])
}
badRows <- !(goodLonMask & goodLatMask)
badRowCount <- sum(badRows)
if ( badRowCount > 0 ) {
logger.trace(paste(verb, "%s rows with invalid location information"), badRowCount)
badLocations <- paste('(', tbl$GPSLon[badRows], ',', tbl$GPSLat[badRows], ')', sep = '')
logger.trace("Bad locations: %s", paste0(badLocations, collapse = ", "))
if ( flagAndKeep ) {
# apply flags
tblFlagged$QCFlag_badLon[tbl$rowID[!goodLonMask]] <- TRUE
tblFlagged$QCFlag_badLat[tbl$rowID[!goodLatMask]] <- TRUE
tblFlagged$QCFlag_anyBad <- tblFlagged$QCFlag_anyBad | tblFlagged$QCFlag_badLon | tblFlagged$QCFlag_badLat
# apply reason codes
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodLonMask]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodLonMask]], "badLon")
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodLatMask]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodLatMask]], "badLat")
}
}
tbl <- tbl[goodLonMask & goodLatMask,]
# ----- Time -----------------------------------------------------------------
# Add a POSIXct datetime based on YYmmddHHMM DateTime
tbl$datetime <- MazamaCoreUtils::parseDatetime(paste0('20', tbl$DateTime), timezone = "UTC")
if ( flagAndKeep ) {
# TODO: Unable to get datetime moved from tbl to tblFlagged without timezone and/or display getting messed up.
# For now just duplicating the calculation, then assigning row values to NA after the fact for rows that were
# removed from tbl prior to calculating datetime above. Clean up later if possible.
tblFlagged$datetime <- MazamaCoreUtils::parseDatetime(paste0('20', tblFlagged$DateTime), timezone = "UTC")
tblFlagged$datetime[ which(!(tblFlagged$rowID %in% tbl$rowID)) ] <- NA
}
# ----- Type -----------------------------------------------------------------
# Type: 0=E-BAM PM2.5, 1=E-BAM PM10, 9=E-Sampler. We only want PM2.5 measurements
goodTypeMask <- !is.na(tbl$Type) & (tbl$Type == 0)
badRows <- !goodTypeMask
badRowCount <- sum(badRows)
if ( badRowCount > 0 ) {
logger.trace(paste(verb, "%s rows with invalid Type information"), badRowCount)
logger.trace("Bad Types: %s", paste0(sort(unique(tbl$Type[badRows]), na.last = TRUE), collapse = ", "))
if ( flagAndKeep ) {
# apply flags
tblFlagged$QCFlag_badType[tbl$rowID[!goodTypeMask]] <- TRUE
tblFlagged$QCFlag_anyBad <- tblFlagged$QCFlag_anyBad | tblFlagged$QCFlag_badType
# apply reason code
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodTypeMask]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodTypeMask]], "badType")
}
}
tbl <- tbl[goodTypeMask,]
if (nrow(tbl) < 1) {
logger.warn("No valid PM2.5 data for %s", monitorName)
}
# Leland Tarnay QC for E-BAM -------------------------------------------------
# NOTE: 2022-09-07 Conversation with Amber Ortega: Newer E-BAMs can be run
# NOTE: at a flow rate of 12.5. So either ~16.7 or ~12.5 should be considered
# NOTE: valid. I didn't want to modify the function signature to support this
# NOTE: So I'm just adding it in here.
goodFlow1 <- !is.na(tbl$AvAirFlw) & tbl$AvAirFlw >= valid_Flow[1] & tbl$AvAirFlw <= valid_Flow[2]
goodFlow2 <- !is.na(tbl$AvAirFlw) & tbl$AvAirFlw >= 12.5*0.95 & tbl$AvAirFlw <= 12.5*1.05
goodFlow <- goodFlow1 | goodFlow2
goodAT <- !is.na(tbl$AvAirTemp) & tbl$AvAirTemp >= valid_AT[1] & tbl$AvAirTemp <= valid_AT[2]
goodRHi <- !is.na(tbl$SensorIntRH) & tbl$SensorIntRH >= valid_RHi[1] & tbl$SensorIntRH <= valid_RHi[2]
goodConcHr <- !is.na(tbl$ConcRT) & tbl$ConcRT >= valid_Conc[1] & tbl$ConcRT <= valid_Conc[2]
gooddatetime <- !is.na(tbl$datetime) & tbl$datetime < lubridate::now(tzone = "UTC") # saw a future date once
logger.trace("Flow has %s missing or out of range values", sum(!goodFlow))
if (sum(!goodFlow) > 0) logger.trace("Bad Flow values: %s", paste0(sort(unique(tbl$AvAirFlw[!goodFlow]), na.last = TRUE), collapse = ", "))
logger.trace("AT has %s missing or out of range values", sum(!goodAT))
if (sum(!goodAT) > 0) logger.trace("Bad AT values: %s", paste0(sort(unique(tbl$AvAirTemp[!goodAT]), na.last = TRUE), collapse = ", "))
logger.trace("RHi has %s missing or out of range values", sum(!goodRHi))
if (sum(!goodRHi) > 0) logger.trace("Bad RHi values: %s", paste0(sort(unique(tbl$SensorIntRH[!goodRHi]), na.last = TRUE), collapse = ", "))
logger.trace("Conc has %s missing or out of range values", sum(!goodConcHr))
if (sum(!goodConcHr) > 0) logger.trace("Bad Conc values: %s", paste0(sort(unique(tbl$ConcRT[!goodConcHr]), na.last = TRUE), collapse = ", "))
logger.trace("datetime has %s missing or out of range values", sum(!gooddatetime))
if (sum(!gooddatetime) > 0) logger.trace("Bad datetime values: %s", paste0(sort(unique(tbl$datetime[!gooddatetime]), na.last = TRUE), collapse = ", "))
goodMask <- goodFlow & goodAT & goodRHi & goodConcHr & gooddatetime
badQCCount <- sum(!goodMask)
if ( badQCCount > 0 ) {
logger.trace(paste(verb,"%s rows because of QC logic"), badQCCount)
if ( flagAndKeep ) {
# apply flags
tblFlagged$QCFlag_badFlow[tbl$rowID[!goodFlow]] <- TRUE
tblFlagged$QCFlag_badAT[tbl$rowID[!goodAT]] <- TRUE
tblFlagged$QCFlag_badRHi[tbl$rowID[!goodRHi]] <- TRUE
tblFlagged$QCFlag_badConcHr[tbl$rowID[!goodConcHr]] <- TRUE
tblFlagged$QCFlag_badDateAndTime[tbl$rowID[!gooddatetime]] <- TRUE
tblFlagged$QCFlag_anyBad <- (tblFlagged$QCFlag_anyBad | tblFlagged$QCFlag_badFlow | tblFlagged$QCFlag_badAT |
tblFlagged$QCFlag_badRHi | tblFlagged$QCFlag_badConcHr | tblFlagged$QCFlag_badDateAndTime)
# apply reason codes
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodFlow]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodFlow]], "badFlow")
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodAT]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodAT]], "badAT")
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodRHi]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodRHi]], "badRHi")
tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodConcHr]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!goodConcHr]], "badConcHr")
tblFlagged$QCFlag_reasonCode[tbl$rowID[!gooddatetime]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[!gooddatetime]], "badDateAndTime")
}
}
tbl <- tbl[goodMask,]
# ----- Duplicate Hours ------------------------------------------------------
# For hours with multiple records, discard all but the one with the latest processing date/time
# NOTE: Current setup for this section assumes that the last entry will be the latest one. May
# NOTE: want to build in functionality to ensure that the latest is picked if more than one exists
# NOTE: (for example, if the data is not in order by timestamp for whatever reason)
dupHrMask <- duplicated(tbl$datetime, fromLast = TRUE)
dupHrCount <- sum(dupHrMask)
uniqueHrMask <- !dupHrMask
if ( dupHrCount > 0 ) {
logger.trace(paste(verb, "%s duplicate time entries"), dupHrCount)
logger.trace("Duplicate Hours (may be >1 per timestamp): %s", paste0(sort(unique(tbl$TimeStamp[dupHrMask])), collapse = ", "))
if ( flagAndKeep ) {
# apply flags
tblFlagged$QCFlag_duplicateHr[tbl$rowID[dupHrMask]] <- TRUE
tblFlagged$QCFlag_anyBad <- tblFlagged$QCFlag_anyBad | tblFlagged$QCFlag_duplicateHr
# apply reason code
tblFlagged$QCFlag_reasonCode[tbl$rowID[dupHrMask]] <- paste(tblFlagged$QCFlag_reasonCode[tbl$rowID[dupHrMask]], "duplicateHr")
}
}
tbl <- tbl[uniqueHrMask,]
# ----- More QC --------------------------------------------------------------
# Lift negative concentrations to zero
tbl$ConcRT[tbl$ConcRT < 0] <- 0
if ( flagAndKeep ) {
logger.trace("Retaining %d rows of measurements; %d bad rows flagged", nrow(tbl), sum(tblFlagged$QCFlag_anyBad))
} else {
logger.trace("Retaining %d rows of validated measurements", nrow(tbl))
}
# ----- Final cleanup --------------------------------------------------------
if ( flagAndKeep ) {
tblFlagged$QCFlag_reasonCode <- stringr::str_sub(tblFlagged$QCFlag_reasonCode, 3)
tblFlagged$QCFlag_reasonCode <- stringr::str_trim(tblFlagged$QCFlag_reasonCode)
tbl <- tblFlagged
tbl$rowID <- NULL
}
# ----- Return ---------------------------------------------------------------
return(tbl)
}
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