airnow_createMonitorObjects: Obain AirNow data and create ws_monitor objects

In MazamaScience/PWFSLSmoke: Utilities for Working with Air Quality Monitoring Data

Obain AirNow data and create ws_monitor objects

Description

This function uses the airnow_downloadParseData function to download monthly dataframes of AirNow data and restructures that data into a format that is compatible with the PWFSLSmoke package ws_monitor data model.

AirNow data parameters include at least the following list:

1. BARPR

2. BC

3. CO

4. NO

5. NO2

6. NO2Y

7. NO2X

8. NOX

9. NOOY

10. OC

11. OZONE

12. PM10

13. PM2.5

14. PRECIP

15. RHUM

16. SO2

17. SRAD

18. TEMP

19. UV-AETH

20. WD

21. WS

Setting parameters=NULL will generate a separate ws_monitor object for each of the above parameters.

Usage

airnow_createMonitorObjects(
  parameters = NULL,
  startdate = strftime(lubridate::now(tzone = "UTC"), "%Y%m%d", tz = "UTC"),
  hours = 24,
  zeroMinimum = TRUE,
  addGoogleMeta = TRUE
)

Arguments

parameters	vector of names of desired pollutants or NULL for all pollutants
startdate	desired start date (integer or character representing YYYYMMDD[HH])
hours	desired number of hours of data to assemble
zeroMinimum	logical specifying whether to convert negative values to zero
addGoogleMeta	logicial specifying wheter to use Google elevation and reverse geocoding services

Value

List where each element contains a ws_monitor object for a unique parameter (e.g: "PM2.5", "NOX").

Note

As of 2017-12-17, it appears that hourly data are available only for 2016 and not for earlier years.

See Also

airnow_createDataDataframes

airnow_createMetaDataframes

Examples

## Not run: 
# Fail gracefully if any resources are not available
try({

monList <- airnow_createMonitorObjects(c("PM2.5"), 20190625)
pm25 <- monList$PM2.5
o3 <- monList$O3

}, silent = FALSE)

## End(Not run)

MazamaScience/PWFSLSmoke documentation built on July 3, 2023, 11:03 a.m.