Embedded System Application for Establishing Variability and the Relationship Between Meteorological Parameters and Particulate Matter Pollution in a Lagos Site

Authors

  • Oduwole F. Odubanjo
    Federal College of Education (Technical), Akoka
  • Tolulope O. Aluko
    Federal College of Education (Technical), Akoka
  • Ayotunde A. Ajayi
    Federal College of Education (Technical), Akoka
  • Peter Babatunde
    Federal College of Education (Technical), Akoka

Keywords:

PM Pollution, Meteorological Parameters, Embedded System, Correlation Analysis, Environmental Health

Abstract

Air pollution from particulate matter (PM) remains a major environmental and public health concern, particularly in rapidly urbanizing cities. This study investigated the variability of PM (PM1, PM2.5, and PM10) and their relationship with meteorological parameters in Lagos, Nigeria, using a low-cost embedded monitoring system. Data were collected continuously over a two-year period (May 2021–April 2023) at two-minute intervals, providing one of the longest continuous PM datasets reported for Lagos. Results revealed distinct diurnal and seasonal patterns, with concentrations consistently higher at night and during the dry season. Temperature, relative humidity, atmospheric pressure, and wind speed showed significant inverse relationships with PM across all size fractions, with humidity and wind speed emerging as the strongest predictors. However, regression analysis indicated modest explanatory power (R² = 0.280 for PM2.5 and R² = 0.201 for PM10), suggesting that local emission sources have a dominant influence. Comparison with air quality benchmarks showed substantial exceedances. The daily mean concentration of PM2.5 (37.39 µg/m³) exceeded the WHO 24-hour guideline (15 µg/m³) and marginally exceeded the U.S. NAAQS limit (35 µg/m³). In contrast, PM10 (43.88 µg/m³) remained below the WHO guideline (45 µg/m³) and well within the Nigerian NESREA 24-hour limit (150 µg/m³). The study is limited by its single-site design, which may constrain spatial generalization. Nonetheless, the findings highlight elevated health risks from fine particulates in Lagos and demonstrate the effectiveness of low-cost embedded systems for long-term urban air quality assessment, supporting their integration into regulatory and public health strategies.

Author Biographies

Oduwole F. Odubanjo

Dr. O. F. Odubanjo is a chief lecturer from the Physics Education department of the Federal College of Education (Technical), Akoka. He has over twenty years' experience teaching physics at the tertiary education level. He specialises in Atmospheric Physics

Tolulope O. Aluko

Dr. Tolu Aluko is a principal lecturer in the Physics Education department of the Federal College of Education (Tech.) Akoka, Lagos. She possesses over eighteen years of teaching and research experience in both science and science education. She specializes in radiation and health physics.

Ayotunde A. Ajayi

Dr. A. A. Ajayi is a chief lecturer in the Physics Education department of the Federal College of Education (Technical), Akoka, Lagos. He has over thirty years of teaching experience and research in both science and science education. He specializes in theoretical & condensed matter physics.

Peter Babatunde

Mr. Peter Babatunde is a principal lecturer in physics education department of the federal College of Education (technical), Akoka, Lagos. He has over eighteen years teaching experience in Physics at the tertiary education level. He specialises in Geophysics. 

Dimensions

Betts, A. (2015). Boundary layer (atmospheric) and air pollution | Diurnal cycle (pp. 319–323). Academic Press. https://doi.org/10.1016/B978-0-12-382225-3.00135-3 DOI: https://doi.org/10.1016/B978-0-12-382225-3.00135-3

Bittner, A. S., Cross, E. S., Hagan, D. H., Malings, C., Lipsky, E., & Grieshop, A. P. (2022). Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi. Atmospheric Measurement Techniques, 15(11), 3353–3376. https://doi.org/10.5194/amt-15-3353-2022 DOI: https://doi.org/10.5194/amt-15-3353-2022

Cheng, Y., Yang, M., Xie, S., Liu, J., & Zheng, S. (2024). Research on the impact of air temperature and wind speed on ventilation in university dormitories under different wind directions (Northeast China). Buildings, 14(2), 361. https://doi.org/10.3390/buildings14020361 DOI: https://doi.org/10.3390/buildings14020361

Danlami, D., Idris, S., Thlakma, R. S., & Gwandum, G. S. (2019). The spatio-temporal variations of wind speed during harmattan season in northeastern Nigeria. Geosfera Indonesia, 4(2). https://doi.org/10.19184/GEOSI.V4I2.11474 DOI: https://doi.org/10.19184/geosi.v4i2.11474

Emekwuru, N., & Ejohwomu, O. (2023). Temperature, humidity and air pollution relationships during a period of rainy and dry seasons in Lagos, West Africa. Climate, 11(5), 113. https://doi.org/10.3390/cli11050113 DOI: https://doi.org/10.3390/cli11050113

Gantt, B., Owen, R. C., & Watkins, N. (2021). Characterizing nitrogen oxides and fine particulate matter near major highways in the United States using the National Near-Road Monitoring Network. Environmental Science & Technology, 55(5), 2831–2838. https://doi.org/10.1021/acs.est.0c05851 DOI: https://doi.org/10.1021/acs.est.0c05851

Guo, C.-Y., Pan, W.-C., Chen, M.-J., Tsai, C.-W., Chen, N.-T., & Su, H.-J. (2014). When are we most vulnerable to temperature variations in a day? PLoS ONE, 9(12), e113195. https://doi.org/10.1371/journal.pone.0113195 DOI: https://doi.org/10.1371/journal.pone.0113195

Hadei, M., Yarahmadi, M., Jonidi, A., Farhadi, M., Hashemi, S. S., & Emam, B. (2019). Effects of meteorological variables and holidays on the concentrations of PM10, PM2.5, O3, NO2, SO2, & CO in Tehran (2014–2018). Journal of Air Pollution and Health, 4(1), 1–14. https://doi.org/10.18502/japh.v4i1.599 DOI: https://doi.org/10.18502/japh.v4i1.599

Hamanaka, R. B., & Mutlu, G. M. (2018). Particulate matter air pollution: Effects on the cardiovascular system. Frontiers in Endocrinology, 9, 680. https://doi.org/10.3389/fendo.2018.00680 DOI: https://doi.org/10.3389/fendo.2018.00680

Hoinka, K.-P. (2007). Semi-diurnal pressure fluctuation in the ERA40 data. Meteorologische Zeitschrift, 16(3), 255–260. https://doi.org/10.1127/0941-2948/2007/0213 DOI: https://doi.org/10.1127/0941-2948/2007/0213

Jayamurugan, R., Kumaravel, B., Palanivelraja, S., & Chocklingam, M. P. (2013). Influence of temperature, relative humidity and seasonal variability on ambient air quality in a coastal urban area. International Journal of Atmospheric Sciences, 2013, 1–7. https://doi.org/10.1155/2013/264046 DOI: https://doi.org/10.1155/2013/264046

Khalis, M., Toure, A. B., El Badisy, I., Khomsi, K., Najmi, H., Bouaddi, O., Marfak, A., Al-Delaimy, W. K., Berraho, M., & Nejjari, C. (2022). Relationship between meteorological and air quality parameters and COVID-19 in Casablanca region, Morocco. International Journal of Environmental Research and Public Health, 19(9), 4989. https://doi.org/10.3390/ijerph19094989 DOI: https://doi.org/10.3390/ijerph19094989

Kliengchuay, W., Cooper, M. A., Worakhunpiset, S., & Tantrakarnapa, K. (2018). Relationships between meteorological parameters and particulate matter in Mae Hong Son province, Thailand. International Journal of Environmental Research and Public Health, 15(12), 2801. https://doi.org/10.3390/ijerph15122801 DOI: https://doi.org/10.3390/ijerph15122801

Lala, M. A., Onwunzo, C. S., Adesina, O. A., & Sonibare, J. A. (2023). Particulate matters pollution in selected areas of Nigeria: Spatial analysis and risk assessment. Case Studies in Chemical and Environmental Engineering, 7, 100288. https://doi.org/10.1016/j.cscee.2022.100288 DOI: https://doi.org/10.1016/j.cscee.2022.100288

Li, Y., Li, J., Xu, S., Li, J., He, J., & Huang, J. (2023). Diurnal variation in the near-global planetary boundary layer height from satellite-based CATS lidar: Retrieval, evaluation, and influencing factors. Remote Sensing of Environment, 299, 113847. https://doi.org/10.1016/j.rse.2023.113847 DOI: https://doi.org/10.1016/j.rse.2023.113847

Liguang, L., Ziqi, Z., Hongbo, W., Yangfeng, W., Ningwei, L., Xiaolan, L., & Yanjun, M. (2020). Concentrations of four major air pollutants among ecological functional zones in Shenyang, Northeast China. Atmosphere, 11(10), 1070. https://doi.org/10.3390/atmos11101070 DOI: https://doi.org/10.3390/atmos11101070

Liu, J., He, C., Si, Y., Li, B., Wu, Q., Ni, J., Zhao, Y., Hu, Q., Du, S., Lu, Z., Jin, J., & Xu, C. (2024). Toward better and healthier air quality: Global PM2.5 and O3 pollution status and risk assessment based on the new WHO air quality guidelines for 2021. Global Challenges, 8(3). DOI: https://doi.org/10.1002/gch2.202300258

Mage, J. O., & Agber, J. N. (2017). Temperature variability, intensity of wind speed and visibility during harmattan in Makurdi Town, Nigeria. Journal of Research in National Development, 15(1). https://doi.org/10.4314/JORIND.V15I1

Marticorena, B., Chatenet, B., Rajot, J. L., Traoré, S., Coulibaly, M., Diallo, A., Koné, I., Maman, A., Ndiaye, T., & Zakou, A. (2010). Temporal variability of mineral dust concentrations over West Africa: Analyses of a pluriannual monitoring from the AMMA. Atmospheric Chemistry and Physics, 10(18), 8899–8915. https://doi.org/10.5194/ACP-10-8899-2010 DOI: https://doi.org/10.5194/acp-10-8899-2010

Nathaniel, M. W., & Xiaoli. (2020). Air quality levels and health risk assessment of particulate matters in Abuja Municipal Area, Nigeria. Atmosphere, 11(18), 817. https://doi.org/10.3390/atmos11080817 DOI: https://doi.org/10.3390/atmos11080817

National Environmental Standards and Regulations Enforcement Agency (NESREA). National Environmental (Air Quality Control) Regulations, S.I No. 88 2021 (Amended). https://www.nesrea.gov.ng/

Ngele, S. O., Elom, N. I., Nwofe, P. A., Agbo, P. E., Ogah, A. O., & Ehiri, R. C. (2015). Diurnal variation of ambient air pollutants concentration in two motor parks in Ebonyi State, Nigeria. Advances in Environmental Biology, 9(23), 271–278. http://www.aensiweb.com/AEB/

Owoade, O. K., Olise, F. S., Ogundele, L. T., Fawole, O. G., & Olaniyi, H. B. (2012). Correlation between particulate matter concentrations and meteorological parameters at a site in Ile-Ife, Nigeria. Ife Journal of Science, 14(1), 83–93. https://scholar.oauife.edu.ng/sites/default/files/ijs/files/owoade.pdf

Si, M., Xiong, Y., Du, S., & Du, K. (2020). Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods. Atmospheric Measurement Techniques, 13(4), 1693–1706. https://doi.org/10.5194/amt-13-1693-2020 DOI: https://doi.org/10.5194/amt-13-1693-2020

Subramanian, R., & Garland, R. M. (2021). Low-cost sensors for air quality research—The powerful potential and challenges in Africa. Clean Air Journal, 31(1). https://doi.org/10.17159/caj/2021/31/1.11274 DOI: https://doi.org/10.17159/caj/2021/31/1.11274

Pope, F. D., Gatari, M., Ng'ang'a, D., Poynter, A., & Blake, R. (2018). Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors. Atmospheric Chemistry and Physics, 18, 15403–15418. https://doi.org/10.5194/acp-18-15403-2018 DOI: https://doi.org/10.5194/acp-18-15403-2018

Sulaymon, I. D., Zhang, Y., Hopke, P. K., Ye, F., Gong, K., Mao, J., & Hu, J. (2023). Modeling PM2.5 during severe atmospheric pollution episode in Lagos, Nigeria: Spatiotemporal variations, source apportionment, and meteorological influences. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2022JD038360 DOI: https://doi.org/10.22541/essoar.167151994.44872973/v1

Taylor, A. C., Beare, R. J., & Thomson, D. J. (2011). H14-154 dispersion by transitional atmospheric boundary layers. In Proceedings of the 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes.

Theogene, I., Abubakar, S., & Jean, P. N. (2020). Establishing the relationship between meteorological parameters and criteria pollutants concentration in Delhi. International Journal of Science and Research Methodology, 15(1), 30–44. https://ssrn.com/abstract=3800806

Udina, M., Soler, M. R., Olid, M., Jiménez-Esteve, B., & Bech, J. (2020). Pollutant vertical mixing in the nocturnal boundary layer enhanced by density currents and low-level jets: Two representative case studies. Boundary-Layer Meteorology, 174(2), 203–230. https://doi.org/10.1007/S10546-019-00483-Y DOI: https://doi.org/10.1007/s10546-019-00483-y

United States Environmental Protection Agency. (2022). Particulate matter (PM) basics. https://www.epa.gov/pm-pollution/particulate-matter-pm-basics

World Health Organization. (2020). WHO ambient (outdoor) air pollution. https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and health

Yang, Q., Yuan, Q., Li, T., Shen, H., & Zhang, L. (2017). The relationships between PM2.5 and meteorological factors in China: Seasonal and regional variations. International Journal of Environmental Research and Public Health, 14(12), 1510. https://doi.org/10.3390/ijerph14121510 DOI: https://doi.org/10.3390/ijerph14121510

Yansui, L., Yang, Z., & Jiaxin, L. (2020). Exploring the relationship between air pollution and meteorological conditions in China under environmental governance. Scientific Reports, 10, 14518. https://doi.org/10.1038/s41598-020-71338-7 DOI: https://doi.org/10.1038/s41598-020-71338-7

Yorkor, B., Lenton, T. G., & Ugbebor, J. N. (2017). The role of meteorology for seasonal variation in Nigeria air pollution level in Eleme, Rivers State Nigeria. Journal of Scientific Research and Report, 17(3), 1–17. https://doi.org/10.9734/JSRR/2017/36613 DOI: https://doi.org/10.9734/JSRR/2017/36613

Zhang, H., Wang, Y., Hu, J., Ying, Q., & Hu, X. M. (2015). Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environmental Research, 140, 242–254. https://doi.org/10.1016/j.envres.2015.04.004 DOI: https://doi.org/10.1016/j.envres.2015.04.004

Zhou, C., & Wang, K. (2017). Contrasting daytime and nighttime precipitation variability between observations and eight reanalysis products from 1979 to 2014 in China. Journal of Climate, 30(16), 6443–6464. https://doi.org/10.1175/JCLI-D-16-0702.1 DOI: https://doi.org/10.1175/JCLI-D-16-0702.1

Zhu, T., Wan, W., Liu, J., Xue, T., Gong, J., & Zhang, S. (2022). Insights into the new WHO Global Air Quality Guidelines. Kexue Tongbao, 67(6). https://doi.org/10.1360/tb-2021-1128 DOI: https://doi.org/10.1360/TB-2021-1128

Published

2025-12-31

How to Cite

Embedded System Application for Establishing Variability and the Relationship Between Meteorological Parameters and Particulate Matter Pollution in a Lagos Site. (2025). Nigerian Journal of Theoretical and Environmental Physics, 3(4), 32-44. https://doi.org/10.62292/njtep.v3i4.2025.101

How to Cite

Embedded System Application for Establishing Variability and the Relationship Between Meteorological Parameters and Particulate Matter Pollution in a Lagos Site. (2025). Nigerian Journal of Theoretical and Environmental Physics, 3(4), 32-44. https://doi.org/10.62292/njtep.v3i4.2025.101

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