The seasonality of meteorology significantly influences the distribution of atmospheric pollution that have harmful effect on human, environment and economy. Similarly, Ethiopia has erratic seasons, this can impact air pollution. Thus, this study focused on intercomparison of PurpleAir PM2.5 measurement at Addis Ababa city. The existing data processed by R software. Accordingly, the finding show that, during the rainy season, PM2.5 levels exhibit a consistent pattern with concentrations peaking in the early night and reaching their lowest at midday. At Black Lion Hospital (BLH), peak concentrations extend to midday due to due to heavy traffic and cross-sectional jams to travel commercial areas. In contrast, during the semi-rainy and dry seasons, PM2.5 levels peak in the early morning and decrease by midday. Hourly variations in PM2.5 concentrations could be influenced by factors such as temperature inversion, wind, relative humidity, and solar intensity, alongside transportation and industrial activities. Analysis reveals that a significant proportion of the seasonal hourly mean trend during the rainy season, vary in between 30 µg/m3 to 50 µg/m3 of the hourly data while 15 µg/m3 to 40 µg/m3 of data in both the semi-rainy and dry seasons also surpass these guidelines. Despite the general reduction in pollution levels due to rain, the rainy season still contributes to elevated PM2.5 concentrations, posing substantial risks to human health, the environment, and development activities. The monthly mean pattern further highlights a peak in PM2.5 concentrations during the rainy season, underscoring the complex dynamics of air quality. This finding emphasizes the need for targeted strategies to manage pollution throughout the year. The finding suggest that, expand air quality monitoring, and reduce traffic emissions, strengthen industrial regulations and increase public awareness. It may relevance for air quality management strategies for local and regional governments.
Published in | International Journal of Environmental Monitoring and Analysis (Volume 12, Issue 6) |
DOI | 10.11648/j.ijema.20241206.11 |
Page(s) | 141-148 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Seasonality, Comparison, PurpleAir, PM2.5, Addis Ababa
[1] | Manisalidis, I., Stavropoulou, E., Stavropoulos, A., & Bezirtzoglou, E. (2020). Environmental and health impacts of air pollution: A review. Frontiers in Public Health, 8. |
[2] | Kulkarni, S. H., et al. (2019). The impact of monsoons on air pollution in Southern Asia and its associated human health effects. Atmospheric Chemistry and Physics, 19(6), 4155-4178. |
[3] | Shah, M. H., & Shaheen, N. (2010). Seasonal behaviours in elemental composition of atmospheric aerosols collected in Islamabad, Pakistan. Atmospheric Research, 95(2), 210-223. |
[4] | Chandra, B. P., et al. (2020). Wintertime pollution events over northern India: Possible linkages to aerosols and weather patterns. Journal of Geophysical Research: Atmospheres, 125(1), e2019JD031742. |
[5] | Sicard P, Paoletti E, Agathokleous E, Araminienė V, Proietti C, Coulibaly F, De Marco A. Ozone weekend effect in cities: Deep insights for urban air pollution control. Environ Res. PMID: 32919964; PMCID: PMC7483290. |
[6] | Kalabokas, P. D., et al. (2015). Seasonal variation of ozone in the boundary layer and free troposphere in the Eastern Mediterranean: A 7-year analysis (2006–2012). Atmospheric Chemistry and Physics, 15(14), 8127-8148. |
[7] | Peron, A., Graus, M., Striednig, M., Lamprecht, C., Wohlfahrt, G., & Karl, T. (2024). Deciphering anthropogenic and biogenic contributions to selected NMVOC emissions in an urban area. EGUsphere, 2024, 1-33. |
[8] | Segele, Z. T., & Lamb, P. J. (2005). Characterization and variability of Kiremt rainy season over Ethiopia. Meteorology and Atmospheric Physics, 89(1-4), 153-180. |
[9] | Korecha, D., & Barnston, A. G. (2007). Predictability of June–September rainfall in Ethiopia. Monthly Weather Review, 135(2), 628-650. |
[10] | Bekele, F., & Bewket, W. (2013). Climate variability and change in the Rift Valley and Blue Nile Basin, Ethiopia: Local knowledge, impacts and adaptation. African Journal of Environmental Science and Technology, 7(5), 347-355. |
[11] | National Meteorological Agency of Ethiopia (NMA). (2010). Rainfall and temperature variability in Addis Ababa. NMA Ethiopia Report. |
[12] | Bewket, W. (2009). Rainfall variability and crop production in Ethiopia: Case study in the Central Rift Valley and Addis Ababa. Ethiopian Journal of Development Research, 31(1). |
[13] | Conway, D. (2000). The climate and hydrology of Addis Ababa, Ethiopia. Geographical Journal, 166(1), 49-62. |
[14] | Bulto, T. W., & Werku, B. C. (2022). Air quality and health in Ethiopia. In Air Quality and Health. IntechOpen. |
[15] | Barkjohn, K. K., Gantt, B., & Clements, A. L. (2021). Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor. Atmospheric Measurement Techniques, 14(6), 4617–4637. |
[16] |
World Health Oorganization Air quality guidelines, 2021. from
https://www.who.int/news-room/feature-stories/detail/what-are-the-who-air-quality-guidelines |
[17] | Alaran, A. J., O’Sullivan, N., Tatah, L., Sserunjogi, R., & Okello, G. (2024). Air pollution (PM2.5) and its meteorology predictors in Kampala and Jinja cities, in Uganda. Environmental Science: Atmospheres. |
[18] | Dasgupta, S., Lall, S. V., & Wheeler, D. (2020). Traffic, air pollution, and distributional impacts in Dar es Salaam: A spatial analysis with new satellite data. World Bank Policy Research Working Paper, (9185). |
[19] | Fenta, H. M., Zewotir, T. T., Naidoo, S., Naidoo, R. N., & Mwambi, H. (2024). Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches. Scientific Reports, 14(1), 15801. |
[20] | Salah, M., Moursy, F., Soliman, E., & Gamal, G. (2023). Assessing the potential impacts of climate change on droughts in East Africa using CORDEX-CORE regional climate models' simulations: A focus on Tanzania. Contributions to Geophysics and Geodesy, 53(3), 271-300. |
[21] | Shiferaw, A. B., Kumie, A., & Tefera, W. (2023). The spatial and temporal variation of fine particulate matter pollution in Ethiopia: Data from the Atmospheric Composition Analysis Group (1998–2019). PLOS ONE, 18(3), e0283457. |
[22] | Keil, C., Kassa, H., Brown, A., Kumie, A., & Tefera, W. (2010). Inhalation Exposures to Particulate Matter and Carbon Monoxide during Ethiopian Coffee Ceremonies in Addis Ababa: A Pilot Study. Journal of Environmental and Public Health, 2010, 213960. |
[23] | Singh, A., Gatari, M. J., Kidane, A. W., Alemu, Z. A., Derrick, N., Webster, M. J.,... & Pope, F. D. (2021). Air quality assessment in three East African cities using calibrated low-cost sensors with a focus on road-based hotspots. Environmental Research Communications, 3(7), 075007. |
[24] | Amegah, A. K., Yeboah, K., Owusu, V., Afriyie, L., Kyere-Gyeabour, E., Appiah, D. C. & Mudu, P. (2023). Socio-demographic and neighbourhood factors influencing urban green space use and development at home: A population-based survey in Accra, Ghana. PLOS ONE, 18(6), e0286332. |
[25] | Thangavel, P., Park, D. and Lee, Y.-C., 2022. Recent insights into particulate matter (PM2. 5)-mediated toxicity in humans: an overview. International journal of environmental research and public health, 19(12): 7511.0. |
[26] | Etyemezian, V., Tesfaye, M., Yimer, A., Chow, J. C., Mesfin, D., Nega, T., Nikolich, G., Watson, J. G., & Wondmagegn, M. (2005). Results from a pilot-scale air quality study in Addis Ababa, Ethiopia. Atmospheric Environment, 39(40), 7849–7860. |
[27] | Bulto, T. W. (2020). Impact of Open Burning Refuse on Air Quality: In the Case of “Hidar Sitaten” at Addis Ababa, Ethiopia. Environmental Health Insights, 14, 1178630220943204. |
APA Style
Redi, T. (2024). Seasonal Inter-comparison of Fine Particulate Matter (PM2.5) Over Addis Ababa, Ethiopia. International Journal of Environmental Monitoring and Analysis, 12(6), 141-148. https://doi.org/10.11648/j.ijema.20241206.11
ACS Style
Redi, T. Seasonal Inter-comparison of Fine Particulate Matter (PM2.5) Over Addis Ababa, Ethiopia. Int. J. Environ. Monit. Anal. 2024, 12(6), 141-148. doi: 10.11648/j.ijema.20241206.11
AMA Style
Redi T. Seasonal Inter-comparison of Fine Particulate Matter (PM2.5) Over Addis Ababa, Ethiopia. Int J Environ Monit Anal. 2024;12(6):141-148. doi: 10.11648/j.ijema.20241206.11
@article{10.11648/j.ijema.20241206.11, author = {Tofikk Redi}, title = {Seasonal Inter-comparison of Fine Particulate Matter (PM2.5) Over Addis Ababa, Ethiopia }, journal = {International Journal of Environmental Monitoring and Analysis}, volume = {12}, number = {6}, pages = {141-148}, doi = {10.11648/j.ijema.20241206.11}, url = {https://doi.org/10.11648/j.ijema.20241206.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20241206.11}, abstract = {The seasonality of meteorology significantly influences the distribution of atmospheric pollution that have harmful effect on human, environment and economy. Similarly, Ethiopia has erratic seasons, this can impact air pollution. Thus, this study focused on intercomparison of PurpleAir PM2.5 measurement at Addis Ababa city. The existing data processed by R software. Accordingly, the finding show that, during the rainy season, PM2.5 levels exhibit a consistent pattern with concentrations peaking in the early night and reaching their lowest at midday. At Black Lion Hospital (BLH), peak concentrations extend to midday due to due to heavy traffic and cross-sectional jams to travel commercial areas. In contrast, during the semi-rainy and dry seasons, PM2.5 levels peak in the early morning and decrease by midday. Hourly variations in PM2.5 concentrations could be influenced by factors such as temperature inversion, wind, relative humidity, and solar intensity, alongside transportation and industrial activities. Analysis reveals that a significant proportion of the seasonal hourly mean trend during the rainy season, vary in between 30 µg/m3 to 50 µg/m3 of the hourly data while 15 µg/m3 to 40 µg/m3 of data in both the semi-rainy and dry seasons also surpass these guidelines. Despite the general reduction in pollution levels due to rain, the rainy season still contributes to elevated PM2.5 concentrations, posing substantial risks to human health, the environment, and development activities. The monthly mean pattern further highlights a peak in PM2.5 concentrations during the rainy season, underscoring the complex dynamics of air quality. This finding emphasizes the need for targeted strategies to manage pollution throughout the year. The finding suggest that, expand air quality monitoring, and reduce traffic emissions, strengthen industrial regulations and increase public awareness. It may relevance for air quality management strategies for local and regional governments. }, year = {2024} }
TY - JOUR T1 - Seasonal Inter-comparison of Fine Particulate Matter (PM2.5) Over Addis Ababa, Ethiopia AU - Tofikk Redi Y1 - 2024/11/29 PY - 2024 N1 - https://doi.org/10.11648/j.ijema.20241206.11 DO - 10.11648/j.ijema.20241206.11 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 141 EP - 148 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20241206.11 AB - The seasonality of meteorology significantly influences the distribution of atmospheric pollution that have harmful effect on human, environment and economy. Similarly, Ethiopia has erratic seasons, this can impact air pollution. Thus, this study focused on intercomparison of PurpleAir PM2.5 measurement at Addis Ababa city. The existing data processed by R software. Accordingly, the finding show that, during the rainy season, PM2.5 levels exhibit a consistent pattern with concentrations peaking in the early night and reaching their lowest at midday. At Black Lion Hospital (BLH), peak concentrations extend to midday due to due to heavy traffic and cross-sectional jams to travel commercial areas. In contrast, during the semi-rainy and dry seasons, PM2.5 levels peak in the early morning and decrease by midday. Hourly variations in PM2.5 concentrations could be influenced by factors such as temperature inversion, wind, relative humidity, and solar intensity, alongside transportation and industrial activities. Analysis reveals that a significant proportion of the seasonal hourly mean trend during the rainy season, vary in between 30 µg/m3 to 50 µg/m3 of the hourly data while 15 µg/m3 to 40 µg/m3 of data in both the semi-rainy and dry seasons also surpass these guidelines. Despite the general reduction in pollution levels due to rain, the rainy season still contributes to elevated PM2.5 concentrations, posing substantial risks to human health, the environment, and development activities. The monthly mean pattern further highlights a peak in PM2.5 concentrations during the rainy season, underscoring the complex dynamics of air quality. This finding emphasizes the need for targeted strategies to manage pollution throughout the year. The finding suggest that, expand air quality monitoring, and reduce traffic emissions, strengthen industrial regulations and increase public awareness. It may relevance for air quality management strategies for local and regional governments. VL - 12 IS - 6 ER -