Analysis of PM10 Levels in Silao, Mexico
Research Mentor(s)
Kimihiro Noguchi
Description
The state of Guanajuato in Mexico is known for its rapidly growing automotive industry over the last few decades. As a consequence, a declined air quality and its potential adverse health effects in the state have become a concern. A useful measure of the air pollution present in a city is called PM10, which refers to matter generally less than 10 micrometers in diameter. To determine whether there had been a significant mean shift in monthly average PM10 levels from 2010 to 2019 in the city of Silao, Guanajuato, we utilized change-point analysis, which is also known as regime shift analysis. As the PM10 levels are temporally correlated, we relied on a modern computational approach known as bootstrap for reliable statistical inference. In particular, we generated bootstrap samples by combining the estimated sinusoidal seasonality with simulated ARMA(1,1) processes in the model residuals. Based on our approach, we confirmed that the increase in the monthly average PM10 levels between 2016 and 2017 was statistically significant.
Document Type
Event
Start Date
May 2022
End Date
May 2022
Location
Carver Gym (Bellingham, Wash.)
Department
CSE - Mathematics
Genre/Form
student projects; posters
Type
Image
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.
Language
English
Format
application/pdf
Analysis of PM10 Levels in Silao, Mexico
Carver Gym (Bellingham, Wash.)
The state of Guanajuato in Mexico is known for its rapidly growing automotive industry over the last few decades. As a consequence, a declined air quality and its potential adverse health effects in the state have become a concern. A useful measure of the air pollution present in a city is called PM10, which refers to matter generally less than 10 micrometers in diameter. To determine whether there had been a significant mean shift in monthly average PM10 levels from 2010 to 2019 in the city of Silao, Guanajuato, we utilized change-point analysis, which is also known as regime shift analysis. As the PM10 levels are temporally correlated, we relied on a modern computational approach known as bootstrap for reliable statistical inference. In particular, we generated bootstrap samples by combining the estimated sinusoidal seasonality with simulated ARMA(1,1) processes in the model residuals. Based on our approach, we confirmed that the increase in the monthly average PM10 levels between 2016 and 2017 was statistically significant.