Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors
Abstract Low-cost sensors were deployed at five locations in a growing, semi-urban settlement in southwest Nigeria between June 8 and July 31, 2018 to measure particulate matter (PM2.5 and PM10), gaseous pollutants (CO, NO, NO2, O3 and CO2), and meteorological variables (air temperature, relative hu...
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| Format: | Article |
| Language: | English |
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Springer
2021-07-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.200598 |
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| author | Oyediran Kayode Owoade Pelumi Olaitan Abiodun Opeyemi R. Omokungbe Olusegun Gabriel Fawole Felix Samuel Olise Olalekan O. M. Popoola Roderic L. Jones Philip K. Hopke |
| author_facet | Oyediran Kayode Owoade Pelumi Olaitan Abiodun Opeyemi R. Omokungbe Olusegun Gabriel Fawole Felix Samuel Olise Olalekan O. M. Popoola Roderic L. Jones Philip K. Hopke |
| author_sort | Oyediran Kayode Owoade |
| collection | DOAJ |
| description | Abstract Low-cost sensors were deployed at five locations in a growing, semi-urban settlement in southwest Nigeria between June 8 and July 31, 2018 to measure particulate matter (PM2.5 and PM10), gaseous pollutants (CO, NO, NO2, O3 and CO2), and meteorological variables (air temperature, relative humidity, wind speed and wind-direction). The spatial and temporal variations of measured pollutants were determined, and the probable sources of pollutants were inferred using conditional bivariate probability function (CBPF). Hourly PM2.5 and PM10 concentrations ranged from 20.7 ± 0.7 to 36.3 ± 1.6 µg m–3 and 47.5 ± 1.5 to 102.9 ± 5.6 µg m–3, respectively. Hourly gaseous pollutant concentrations ranged from 348 ± 132 to 542 ± 200 ppb CO, 21.5 ± 7.2 ppb NO2 and 57.5 ± 11.3 to 64.4 ± 14.0 ppb O3. Kruskal-Wallis ANOVA on ranks determined statistically significant spatial differences in the hourly-average pollutant concentrations. Diel variation analyses indicated that CO2, PM2.5, and PM10 peaked in the early hours of most days, O3 at noon while NO, NO2, and CO peaked in the evening. Most pollutants were of anthropogenic origins and exhibited the highest contributions from the southwest at most sampling locations. There were strong similarities between pollutants source contribution at two of the monitoring sites that were in residential areas with a frequently used paved road. Mitigation strategies need to be established to avoid further deterioration of ambient air quality that negatively affect public health. |
| format | Article |
| id | doaj-art-1b03b65ed9404101b09fdf405c7a5a4d |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2021-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-1b03b65ed9404101b09fdf405c7a5a4d2025-02-09T12:21:20ZengSpringerAerosol and Air Quality Research1680-85842071-14092021-07-01211011810.4209/aaqr.200598Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost SensorsOyediran Kayode Owoade0Pelumi Olaitan Abiodun1Opeyemi R. Omokungbe2Olusegun Gabriel Fawole3Felix Samuel Olise4Olalekan O. M. Popoola5Roderic L. Jones6Philip K. Hopke7Environmental Pollution Laboratory, Department of Physics and Engineering Physics, Obafemi Awolowo UniversityEnvironmental Pollution Laboratory, Department of Physics and Engineering Physics, Obafemi Awolowo UniversityEnvironmental Pollution Laboratory, Department of Physics and Engineering Physics, Obafemi Awolowo UniversityEnvironmental Pollution Laboratory, Department of Physics and Engineering Physics, Obafemi Awolowo UniversityEnvironmental Pollution Laboratory, Department of Physics and Engineering Physics, Obafemi Awolowo UniversityDepartment of Chemistry, University of CambridgeDepartment of Chemistry, University of CambridgeInstitute for a Sustainable Environment, Clarkson UniversityAbstract Low-cost sensors were deployed at five locations in a growing, semi-urban settlement in southwest Nigeria between June 8 and July 31, 2018 to measure particulate matter (PM2.5 and PM10), gaseous pollutants (CO, NO, NO2, O3 and CO2), and meteorological variables (air temperature, relative humidity, wind speed and wind-direction). The spatial and temporal variations of measured pollutants were determined, and the probable sources of pollutants were inferred using conditional bivariate probability function (CBPF). Hourly PM2.5 and PM10 concentrations ranged from 20.7 ± 0.7 to 36.3 ± 1.6 µg m–3 and 47.5 ± 1.5 to 102.9 ± 5.6 µg m–3, respectively. Hourly gaseous pollutant concentrations ranged from 348 ± 132 to 542 ± 200 ppb CO, 21.5 ± 7.2 ppb NO2 and 57.5 ± 11.3 to 64.4 ± 14.0 ppb O3. Kruskal-Wallis ANOVA on ranks determined statistically significant spatial differences in the hourly-average pollutant concentrations. Diel variation analyses indicated that CO2, PM2.5, and PM10 peaked in the early hours of most days, O3 at noon while NO, NO2, and CO peaked in the evening. Most pollutants were of anthropogenic origins and exhibited the highest contributions from the southwest at most sampling locations. There were strong similarities between pollutants source contribution at two of the monitoring sites that were in residential areas with a frequently used paved road. Mitigation strategies need to be established to avoid further deterioration of ambient air quality that negatively affect public health.https://doi.org/10.4209/aaqr.200598Temporal variationLow-cost sensorsParticulate matterCBPFSource identification |
| spellingShingle | Oyediran Kayode Owoade Pelumi Olaitan Abiodun Opeyemi R. Omokungbe Olusegun Gabriel Fawole Felix Samuel Olise Olalekan O. M. Popoola Roderic L. Jones Philip K. Hopke Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors Aerosol and Air Quality Research Temporal variation Low-cost sensors Particulate matter CBPF Source identification |
| title | Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors |
| title_full | Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors |
| title_fullStr | Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors |
| title_full_unstemmed | Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors |
| title_short | Spatial-temporal Variation and Local Source Identification of Air Pollutants in a Semi-urban Settlement in Nigeria Using Low-cost Sensors |
| title_sort | spatial temporal variation and local source identification of air pollutants in a semi urban settlement in nigeria using low cost sensors |
| topic | Temporal variation Low-cost sensors Particulate matter CBPF Source identification |
| url | https://doi.org/10.4209/aaqr.200598 |
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