Granger Causality Analysis of Air Pollutants and Meteorological Parameters

This study investigated the relationships between air pollutants (PM10, SO2, NO2, O3, CO) and meteorological parameters (wind speed, relative humidity, ambient temperature) across urban, suburban, and industrial areas in Malaysia from 2017 to 2021. Using data from six monitoring stations, this research employed descriptive analysis, trend analysis, and Granger causality testing to uncover complex interactions. The results revealed distinct patterns: suburban areas showed strong ambient temperature-ozone (p-value = 0.0063) and relative humidity–nitrogen dioxide relationships (p-value = 0.0411); industrial zones exhibited bidirectional causality between SO2 and PM10 and had a strong nitrogen dioxide–PM10 relationship (p-value = 0.0292); urban areas exhibited complex multi-pollutant interactions. Notably, the 2020 Movement Control Order significantly improved air quality. This research provides crucial insights for targeted air quality management strategies, contributing to public health improvements and aligning with global sustainability goals.

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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.3390/eesp2025033006
Citations
7
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
5.59
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Granger Causality Analysis of Air Pollutants and Meteorological Parameters

Norazian Mohamed Noor, Ahmad Zia Ul–Saufie, Zulkifli Rais, Norazrin Ramli et al.
7 citations
Air Quality Monitoring and Forecasting
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article

Granger Causality Analysis of Air Pollutants and Meteorological Parameters

Norazian Mohamed Noor, Ahmad Zia Ul–Saufie, Zulkifli Rais, Norazrin Ramli, Hazrul Abdul Hamid, Mohd Khairul Nizam Mahmad, Wong Yee Ping
article en
7 citations

Abstract

This study investigated the relationships between air pollutants (PM10, SO2, NO2, O3, CO) and meteorological parameters (wind speed, relative humidity, ambient temperature) across urban, suburban, and industrial areas in Malaysia from 2017 to 2021. Using data from six monitoring stations, this research employed descriptive analysis, trend analysis, and Granger causality testing to uncover complex interactions. The results revealed distinct patterns: suburban areas showed strong ambient temperature-ozone (p-value = 0.0063) and relative humidity–nitrogen dioxide relationships (p-value = 0.0411); industrial zones exhibited bidirectional causality between SO2 and PM10 and had a strong nitrogen dioxide–PM10 relationship (p-value = 0.0292); urban areas exhibited complex multi-pollutant interactions. Notably, the 2020 Movement Control Order significantly improved air quality. This research provides crucial insights for targeted air quality management strategies, contributing to public health improvements and aligning with global sustainability goals.

Universiti Sains Malaysia (MY), Universiti Malaysia Perlis (MY), Universiti Teknologi MARA (MY)
Climate action
Openalex Percentile: Top 4%
Air Quality Monitoring and Forecasting
5.59
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