Work

Analysis of Air Pollution in Malaysia: Implications for Environmental Conservation using Granger Causality and Pearson Correlation

Year: 2025

Type: article

Abstract: This study investigates the relationships between air pollutants (PM10, SO2, NO2, O3, CO) and meteorological factors (temperature, relative humidity, wind speed) across five states in Malaysia: Seberang Perai, Shah Alam, Nilai, Larkin and Pasir Gudang. Using time-series data from 2017 to 2021, we applied Granger causality and Pearson correlation to explore the predictive relationships and linear associations between these variables. Granger causality provided insights into temporal precedence, revealing significant predictive relationships such as temperature Granger-causing PM10 and O3 in Nilai and Shah Alam. Meanwhile, Pearson correlation highlighted strong linear relationships, such as the positive correlation between PM10 and wind speed in Shah Alam and the negative correlation between humidity and O3 across several stations. By comparing both methods, we show how combining Granger causality with Pearson correlation can enhance environmental modelling, offering a comprehensive approach to air pollution prediction. This integration provides robust insights into the dynamics of air quality, which are critical for developing effective pollution control strategies.

Source: International Journal of Conservation Science

DOI: 10.36868/ijcs.2025.01.09

Authors: Zulkifli Abd RAIS, Norazrin RAMLI, Norazian Mohamed NOOR, Hazrul Abdul HAMID, Ahmad Zia UL-SAUFIE, Mohd Khairul Nizam MAHMAD

Institutions: Universiti Malaysia Perlis, Universiti Sains Malaysia, Universiti Teknologi MARA System, Universiti Teknologi MARA

Language: English

Topic: Air Quality Monitoring and Forecasting

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: bronze

Funder: U.S. Department of Energy