sensortoolkit.model

The sensortoolkit.model subpackage contains modules for applying or creating correction methods for sensor data. Methods include the U.S.-Wide Correction Equation developed by Barkjohn et al. 2021 1 for the PurpleAir PA-II and modules for calculating or applying a general linear correction equation based on the ordinary least-squares regression between sensor (dependent variable) and reference (independent variable) measurements.

Clicking on each module below will open a page with a detailed description and list of functions included within the module.

sensortoolkit.model._apply_correction

This module contains a method for applying a linear correction to an individual sensor dataset based off the ordinary least-squares regression between collocated sensor and FRM/FEM measurements.

sensortoolkit.model._purpleair_uscorrection

This module contains methods for applying correction equations specific to the PurpleAir PA-II sensor.

sensortoolkit.model._sensor_ols

This module contains a method for computing the ordinary least-squares (OLS) regression between collocated sensor and FRM/FEM reference measurements.

Footnotes

1

Barkjohn, K. K., Gantt, B., and Clements, A. L.: Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor, Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, 2021.