Modelling of ambient air PM2.5 concentration for air quality assessment
creativework.keywords | Air quality assessment, Mathematical modelling, PM10, PM2.5 | |
creativework.publisher | University of Chemical Technology and Metallurgyjournal@uctm.edu | en |
dc.contributor.author | Nikolova Y. | |
dc.contributor.author | Ilieva N. | |
dc.contributor.author | Sokolovski E. | |
dc.date.accessioned | 2024-07-16T11:16:46Z | |
dc.date.accessioned | 2024-07-16T11:18:00Z | |
dc.date.available | 2024-07-16T11:16:46Z | |
dc.date.available | 2024-07-16T11:18:00Z | |
dc.date.issued | 2015-01-01 | |
dc.description.abstract | During the last decade special attention to the fine particles up to 2,5 μm (PM2.5) is being paid. PM2.5 is treated as a particular pollutant with strong negative impacton human health. In Bulgaria, the levels of PM2.5 are measured only at 9 monitoring stations. Therefore effective air quality monitoring regarding this pollutant can not be expected. In many cases particulate matter with aerodynamic diameter up to 10 μm (PM10) and PM2.5 have common origin. That is why it can be assumed that their concentrations in the air are related. Measured data from two of the monitoring stations ``Kopitoto`` (background) and ``Krasno Selo`` (traffic related) have been investigated. It was established that a strong correlation for ``Krasno Selo`` station exists. Conversely, for ``Kopitoto`` station the correlation is rather weak. A mathematical model has been worked out for calculation of PM2.5 concentration using PM10 concentration data. The model demonstrates good accuracy for urban background and traffic related monitoring stations. | |
dc.identifier.issn | 1314-7978 | |
dc.identifier.issn | 1314-7471 | |
dc.identifier.scopus | SCOPUS_ID:84921715586 | en |
dc.identifier.uri | https://rlib.uctm.edu/handle/123456789/1080 | |
dc.language.iso | en | |
dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84921715586&origin=inward | |
dc.title | Modelling of ambient air PM2.5 concentration for air quality assessment | |
dc.type | Article | |
oaire.citation.issue | 1 | |
oaire.citation.volume | 50 |