A Prediction of PM10 Air Contamination Using Multiple Linear Regression-Reference-Cited by-同舟云学术

A Prediction of PM10 Air Contamination Using Multiple Linear Regression

Published:2024-02-06 Issue: Volume: Page:
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Author:

Kumar Lokesh¹,Kumar Gaurav¹

Affiliation:

1. NAS College

Abstract

Abstract Sufficient assessment of air contaminants, mainly Particulate Matter, is necessary for effective and persuasive management of air quality. Numerous elements influence PM prediction, therefore it is essential to incorporate the most appropriate input variables to provide the most dependable forecasts. This work used the multiple linear regression technique to select the most appropriate variables for the model. The concentration of PM10 in this work is determined by measuring the amounts of nitrogen dioxide (NO2), air quality index (AQI), and sulfur dioxide (SO2).

Publisher

Research Square Platform LLC

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