Time Series Comparisons, Model Code, and a Demo Dataset for SIBaR: A New Method for Background Quantification and Removal from Mobile Air Pollution Measurements

Blake Actkinson; Katherine Ensor; Robert J. Griffin

doi:10.5281/zenodo.5022589

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Time Series Comparisons, Model Code, and a Demo Dataset for SIBaR: A New Method for Background Quantification and Removal from Mobile Air Pollution Measurements

Blake Actkinson, Katherine Ensor and Robert J. Griffin

Zenodo

06/24/2021

DOI: https://doi.org/10.5281/zenodo.5022589

Abstract

Air Pollution, Data Analysis, Time Series Analysis, Hidden Markov Models

Time series comparisons between SIBaR, Brantley, and Apte background signals for all 312 time series in the Houston mobile monitoring campaign. Additionally, a R script demo (DemoData.R) of the SIBaR partitioning step on the demo datatset (DemoData.csv).

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Title: Time Series Comparisons, Model Code, and a Demo Dataset for SIBaR: A New Method for Background Quantification and Removal from Mobile Air Pollution Measurements
Creators: Blake Actkinson - Rice University
Katherine Ensor - Rice University
Robert J. Griffin - Rice University
Publisher: Zenodo
Academic Unit: College of Engineering
Language: English
Resource Type: Dataset
DOI: https://doi.org/10.5281/zenodo.5022589
Record Identifier: 9914511634001301