ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION

This study investigates the relationships between air pollutants (PM10, SO2, NO2, O-3, 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 a...

詳細記述

書誌詳細
出版年:INTERNATIONAL JOURNAL OF CONSERVATION SCIENCE
主要な著者: Abd Rais, Zulkifli; Ramli, Norazrin; Noor, Norazian Mohamed; Hamid, Hazrul Abdul; Ul-saufie, Ahmad Zia; Mahmad, Mohd Khairul Nizam
フォーマット: 論文
言語:English
出版事項: Romanian Inventors Forum 2025
主題:
Art
オンライン・アクセス:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001440748600009
author Abd Rais
Zulkifli; Ramli
Norazrin; Noor
Norazian Mohamed; Hamid
Hazrul Abdul; Ul-saufie
Ahmad Zia; Mahmad
Mohd Khairul Nizam
spellingShingle Abd Rais
Zulkifli; Ramli
Norazrin; Noor
Norazian Mohamed; Hamid
Hazrul Abdul; Ul-saufie
Ahmad Zia; Mahmad
Mohd Khairul Nizam
ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
Art
author_facet Abd Rais
Zulkifli; Ramli
Norazrin; Noor
Norazian Mohamed; Hamid
Hazrul Abdul; Ul-saufie
Ahmad Zia; Mahmad
Mohd Khairul Nizam
author_sort Abd Rais
spelling Abd Rais, Zulkifli; Ramli, Norazrin; Noor, Norazian Mohamed; Hamid, Hazrul Abdul; Ul-saufie, Ahmad Zia; Mahmad, Mohd Khairul Nizam
ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
INTERNATIONAL JOURNAL OF CONSERVATION SCIENCE
English
Article
This study investigates the relationships between air pollutants (PM10, SO2, NO2, O-3, 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 PM(10 )and O(3 )in Nilai and Shah Alam. Meanwhile, Pearson correlation highlighted strong linear relationships, such as the positive correlation between PM(10 )and wind speed in Shah Alam and the negative correlation between humidity and O(3 )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.
Romanian Inventors Forum
2067-533X
2067-8223
2025
16
1
10.36868/IJCS.2025.01.09
Art

WOS:001440748600009
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001440748600009
title ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
title_short ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
title_full ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
title_fullStr ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
title_full_unstemmed ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
title_sort ANALYSIS OF AIR POLLUTION IN MALAYSIA: IMPLICATIONS FOR ENVIRONMENTAL CONSERVATION USING GRANGER CAUSALITY AND PEARSON CORRELATION
container_title INTERNATIONAL JOURNAL OF CONSERVATION SCIENCE
language English
format Article
description This study investigates the relationships between air pollutants (PM10, SO2, NO2, O-3, 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 PM(10 )and O(3 )in Nilai and Shah Alam. Meanwhile, Pearson correlation highlighted strong linear relationships, such as the positive correlation between PM(10 )and wind speed in Shah Alam and the negative correlation between humidity and O(3 )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.
publisher Romanian Inventors Forum
issn 2067-533X
2067-8223
publishDate 2025
container_volume 16
container_issue 1
doi_str_mv 10.36868/IJCS.2025.01.09
topic Art
topic_facet Art
accesstype
id WOS:001440748600009
url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001440748600009
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