Seeing the air in detail: Hyperlocal air quality dataset collected from spatially distributed AirQo network
| dc.contributor.author | Sserunjogi, Richard | |
| dc.contributor.author | Ssematimba, Joel | |
| dc.contributor.author | Okure, Deo | |
| dc.contributor.author | Ogenrwot, Daniel | |
| dc.contributor.author | Adong, Priscilla | |
| dc.contributor.author | Muyama, Lillian | |
| dc.contributor.author | Nsimbe, Noah | |
| dc.contributor.author | Bbaale, Martin | |
| dc.contributor.author | Bainomugisha, Engineer | |
| dc.date.accessioned | 2023-01-26T21:42:52Z | |
| dc.date.available | 2023-01-26T21:42:52Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Air pollution is a major global challenge associated with an increasing number of morbidity and mortality from lung can- cer, cardiovascular and respiratory diseases, among others. However, there is scarcity of ground monitoring air quality data from Sub-Saharan Africa that can be used to quantify the level of pollution. This has resulted in limited targeted air pollution research and interventions e.g. health impacts, key drivers and sources, economic impacts, among others; ultimately hindering the establishment of effective manage- ment strategies. This paper presents a dataset of air quality observations collected from 68 spatially distributed monitor- ing stations across Uganda. The dataset includes hourly PM 2 . 5 and PM 10 data collected from low-cost air quality monitoring devices and one reference grade monitoring device over a pe- riod ranging from 2019 to 2020. This dataset contributes to- wards filling some of the data gaps witnessed over the years in ground level monitored ambient air quality in Sub-Saharan Africa and it can be useful to various policy makers and re- searchers. | en_US |
| dc.identifier.citation | Sserunjogi, R., Ssematimba, J., Okure, D., Ogenrwot, D., Adong, P., Muyama, L., ... & Bainomugisha, E. (2022). Seeing the air in detail: hyperlocal air quality dataset collected from spatially distributed AirQo network. Data in Brief, 44, 108512. https://doi.org/10.1016/j.dib.2022.108512 | en_US |
| dc.identifier.uri | https://doi.org/10.1016/j.dib.2022.108512 | |
| dc.identifier.uri | https://nru.uncst.go.ug/handle/123456789/7303 | |
| dc.language.iso | en | en_US |
| dc.publisher | Data in Brief | en_US |
| dc.subject | Air quality dataset | en_US |
| dc.subject | Sub-Saharan Africa | en_US |
| dc.subject | Air pollution | en_US |
| dc.subject | PM 2 . 5 | en_US |
| dc.subject | PM 10 | en_US |
| dc.subject | Particulate matter | en_US |
| dc.title | Seeing the air in detail: Hyperlocal air quality dataset collected from spatially distributed AirQo network | en_US |
| dc.type | Article | en_US |