{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T18:42:46Z","timestamp":1786128166086,"version":"build-2736575974"},"reference-count":48,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T00:00:00Z","timestamp":1786060800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosglobalpublichealth.org"],"crossmark-restriction":false},"short-container-title":["PLOS Glob Public Health"],"abstract":"<jats:p>\n                    This study examines the dynamics of ambient air pollutants and their meteorological determinants in Abeokuta, Nigeria. This study averaged 12 years of hourly data (2012\u20132023) for PM\n                    <jats:sub>2<\/jats:sub>\n                    .\n                    <jats:sub>5<\/jats:sub>\n                    , PM\u2081\u2080, NO\n                    <jats:sub>2<\/jats:sub>\n                    , SO\n                    <jats:sub>2<\/jats:sub>\n                    , CO, and O\n                    <jats:sub>3<\/jats:sub>\n                    , alongside six meteorological variables: temperature, relative humidity, pressure, wind speed, wind direction, and rainfall. Specifically, Particulate matter (PM\n                    <jats:sub>2.5<\/jats:sub>\n                    and PM\n                    <jats:sub>10<\/jats:sub>\n                    ) were the most dominant pollutants, consistently surpassing World Health Organisation (WHO) standards and reaching their highest concentrations during the Harmattan dry season, typically occurring between December and March. Regression analysis demonstrated moderate to strong positive correlations with temperature (R\u00b2\u2009=\u20090.48\u20130.52), while also indicating negative relationships with rainfall and humidity, thereby validating the impacts of thermal stagnation and wet scavenging processes. Furthermore, fluctuations in atmospheric pressure contributed to the buildup of pollutants during periods of stagnant air. Gaseous pollutants showed relatively weaker sensitivity; however, levels of NO\n                    <jats:sub>2<\/jats:sub>\n                    and CO increased during the hot, arid months, while O\n                    <jats:sub>3<\/jats:sub>\n                    levels rose in the late dry season. The Aggregate Air Quality Index (AAQI) values fluctuated between 39 and 51, thereby designating the air quality as \u201cmoderate.\u201d Furthermore, the Health-Risk Adjusted AQI (HAQI) revealed heightened relative risks, especially concerning PM\n                    <jats:sub>2<\/jats:sub>\n                    .\n                    <jats:sub>5<\/jats:sub>\n                    exposure, with seasonal maxima exceeding 90. These findings highlight the cumulative health impacts of particulate matter, even when gaseous pollutants remain within permissible thresholds. The results highlight the necessity for seasonally adjusted mitigation measures, including dust suppression, emission controls, and cleaner combustion technologies. Furthermore, they advocate for the incorporation of Health-Adjusted Quality Index (HAQI) metrics within air quality management systems.\n                  <\/jats:p>","DOI":"10.1371\/journal.pgph.0006683","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:44:23Z","timestamp":1786124663000},"page":"e0006683","update-policy":"https:\/\/doi.org\/10.1371\/journal.pgph.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["A long-term air quality and meteorological coupling dynamics in Abeokuta, Nigeria"],"prefix":"10.1371","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5067-9870","authenticated-orcid":true,"given":"Nathaniel Oluwatimileyin","family":"Adeniji","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob Adebayo","family":"Akinpelu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francis Olatunbosun","family":"Aweda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Solomon Oluwadara","family":"Adeola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olusanya Odunayo","family":"Jegede","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,8,7]]},"reference":[{"key":"pgph.0006683.ref001","volume-title":"WHO global air quality guidelines: Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide","author":"World Health Organization","year":"2021"},{"key":"pgph.0006683.ref002","first-page":"101010","article-title":"Spatial and temporal characteristics and the impact of meteorology on PM2.5 and O3 in four Indian cities","volume":"54","author":"AS Krishnaveni","year":"2024","journal-title":"Urban Climate"},{"key":"pgph.0006683.ref003","article-title":"Ozone pollution in China affected by climate change in a carbon-neutral scenario","volume":"51","author":"H Li","year":"2024","journal-title":"Geophysical Research Letters"},{"key":"pgph.0006683.ref004","first-page":"345","article-title":"Multidecadal ozone trends in China and implications for chemistry\u2013climate interactions","volume":"24","author":"J Mao","year":"2024","journal-title":"Atmospheric Chemistry and Physics"},{"issue":"21","key":"pgph.0006683.ref005","first-page":"7028","article-title":"A new global Air Quality Health Index based on the WHO guidelines and its application to Cape Town, South Africa","volume":"20","author":"TC Adebayo-Ojo","year":"2023","journal-title":"International Journal of Environmental Research and Public Health"},{"issue":"7","key":"pgph.0006683.ref006","first-page":"871","article-title":"Assessing air pollution in South African priority regions: Observational analysis of PM2.5, SO2, O3, NO2, and CO in conjunction with meteorological data","volume":"16","author":"N Ngcoliso","year":"2025","journal-title":"Atmosphere"},{"issue":"2","key":"pgph.0006683.ref007","first-page":"107","article-title":"Spatial distribution of particulate air pollution in Nigerian cities: Implications for human health","volume":"7","author":"SI Efe","year":"2008","journal-title":"Journal of Environmental Health Research"},{"issue":"9","key":"pgph.0006683.ref008","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1080\/10962247.2013.793627","article-title":"Characterization and source identification of airborne particulate loadings at receptor site-classes of Lagos Mega-City, Nigeria","volume":"63","author":"OK Owoade","year":"2013","journal-title":"J Air Waste Manag Assoc"},{"key":"pgph.0006683.ref009","first-page":"107","article-title":"Source apportionment of fine particulate matter in an African megacity using PMF and chemical mass balance techniques","volume":"98","author":"AM Taiwo","year":"2014","journal-title":"Atmospheric Environment"},{"issue":"3","key":"pgph.0006683.ref010","doi-asserted-by":"crossref","first-page":"035003","DOI":"10.1088\/1748-9326\/9\/3\/035003","article-title":"Explosive growth in African combustion emissions from 2005 to 2030","volume":"9","author":"C Liousse","year":"2014","journal-title":"Environ Res Lett"},{"key":"pgph.0006683.ref011","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.envres.2015.04.004","article-title":"Relationships between meteorological parameters and criteria air pollutants in three megacities in China","volume":"140","author":"H Zhang","year":"2015","journal-title":"Environ Res"},{"key":"pgph.0006683.ref012","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1016\/j.envpol.2016.09.042","article-title":"Urban air pollution in Sub-Saharan Africa: Time for action","volume":"220","author":"AK Amegah","year":"2017","journal-title":"Environ Pollut"},{"key":"pgph.0006683.ref013","unstructured":"Adefolalu DO. 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