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Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression

The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations: COVID-19 cases in Cheras were positively associated with relative...

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Main Authors: Salsabila, Norin Binta, Jalaludin, Juliana, Suhaimi, Nur Faseeha, Wan Mansor, Wan Nurdiyana, Sumantri, Arif
Format: Article
Published: Taylor and Francis Ltd. 2024
Online Access:http://psasir.upm.edu.my/id/eprint/113951/
https://www.tandfonline.com/doi/full/10.1080/09603123.2024.2390479
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spelling my.upm.eprints.1139512025-02-05T07:31:08Z http://psasir.upm.edu.my/id/eprint/113951/ Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression Salsabila, Norin Binta Jalaludin, Juliana Suhaimi, Nur Faseeha Wan Mansor, Wan Nurdiyana Sumantri, Arif The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations: COVID-19 cases in Cheras were positively associated with relative humidity (RH) and carbon monoxide (CO) but negatively with ozone (O₃) and RH in different years. In Kelapa Gading, COVID-19 cases were positively correlated with pollutants like sulfur dioxide (SO₂) and CO, while ambient temperature (AT) showed a negative correlation. The enforcement of social restrictions notably reduced air pollution, affecting COVID-19 spread. Predictive models for PM2.5 levels using robust regression techniques showed strong performance in Kuala Lumpur (R² > 0.9) but exhibited overfitting tendencies in Jakarta, suggesting the need for a longer study period for more accurate results. Taylor and Francis Ltd. 2024-08 Article PeerReviewed Salsabila, Norin Binta and Jalaludin, Juliana and Suhaimi, Nur Faseeha and Wan Mansor, Wan Nurdiyana and Sumantri, Arif (2024) Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression. International Journal of Environmental Health Research. pp. 1-22. ISSN 0960-3123; eISSN: 1369-1619 https://www.tandfonline.com/doi/full/10.1080/09603123.2024.2390479 10.1080/09603123.2024.2390479
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations: COVID-19 cases in Cheras were positively associated with relative humidity (RH) and carbon monoxide (CO) but negatively with ozone (O₃) and RH in different years. In Kelapa Gading, COVID-19 cases were positively correlated with pollutants like sulfur dioxide (SO₂) and CO, while ambient temperature (AT) showed a negative correlation. The enforcement of social restrictions notably reduced air pollution, affecting COVID-19 spread. Predictive models for PM2.5 levels using robust regression techniques showed strong performance in Kuala Lumpur (R² > 0.9) but exhibited overfitting tendencies in Jakarta, suggesting the need for a longer study period for more accurate results.
format Article
author Salsabila, Norin Binta
Jalaludin, Juliana
Suhaimi, Nur Faseeha
Wan Mansor, Wan Nurdiyana
Sumantri, Arif
spellingShingle Salsabila, Norin Binta
Jalaludin, Juliana
Suhaimi, Nur Faseeha
Wan Mansor, Wan Nurdiyana
Sumantri, Arif
Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
author_facet Salsabila, Norin Binta
Jalaludin, Juliana
Suhaimi, Nur Faseeha
Wan Mansor, Wan Nurdiyana
Sumantri, Arif
author_sort Salsabila, Norin Binta
title Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
title_short Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
title_full Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
title_fullStr Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
title_full_unstemmed Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression
title_sort predictions of pm2.5 using air pollutants and meteorological factors with covid-19 cases in malaysia and indonesia: a comparative study using feature selection and robust regression
publisher Taylor and Francis Ltd.
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/113951/
https://www.tandfonline.com/doi/full/10.1080/09603123.2024.2390479
_version_ 1823534619410038784
score 13.239859

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