R/pat_createPATimeseriesObject.R
pat_createPATimeseriesObject.Rd
The 'data' dataframe is converted from 'long format' with temporal resolution of seconds to 'wide format' with temporal resolution in minutes. In the process, the following columns of data are omitted:
pm1_0_atm
pm2_5_atm
pm10_0_atm
pat_createPATimeseriesObject(pat_raw = NULL)
pat_raw | Raw PurpleAir timeseries data from |
---|
List with original meta
and restructured data
elements
"pa_timeseries" list of time series PurpleAir data
On January 13, 2020 the PurpleAir FAQ "Whsat's the difference between CF_1 and CF_ATM?" contained the following text:
The CF_ATM and CF_1 values are calculated from the particle count data with a proprietary algorithm developed by the PMS5003 laser counter manufacturer, PlanTower. The specifics of the calculation are not available to the public (or us for that matter). However, to convert the particle count data (um/dl) to a mass concentration (ug/m3) they must use an average particle density. They do provide 2 different mass concentration conversion options; CF_1 uses the "average particle density" for indoor particulate matter and CF_ATM uses the "average particle density" for outdoor particulate matter. Depending on the density of the particles you are measuring the sensor could appear to read "high" or "low". Some groups have developed conversion factors to convert the data from the sensor to match the unique average particle density within their airshed.
https://www2.purpleair.com/community/faq
if (FALSE) { library(AirSensor) initializeMazamaSpatialUtils() pat_raw <- pat_downloadParseRawData( label = 'North Bend Weather', pas = example_pas, startdate = 20180908 ) pat <- pat_createPATimeseriesObject(pat_raw) pat_multiPlot(pat) }