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Media type:
E-Article
Title:
Monitoring and Prediction of Particulate Matter (PM2.5 and PM10) around the Ipbeja Campus
Contributor:
Silva, Flavia Matias Oliveira;
Alexandrina, Eduardo Carlos;
Pardal, Ana Cristina;
Carvalhos, Maria Teresa;
Schornobay Lui, Elaine
imprint:
MDPI AG, 2022
Published in:Sustainability
Language:
English
DOI:
10.3390/su142416892
ISSN:
2071-1050
Origination:
Footnote:
Description:
<jats:p>Nowadays, most of the world’s population lives in urban centres, where air quality levels are not strictly checked; citizens are exposed to air quality levels over the limits of the World Health Organization. The interaction between the issuing and atmospheric sources influences the air quality or level. The local climate conditions (temperature, humidity, winds, rainfall) determine a greater or less dispersion of the pollutants present in the atmosphere. In this sense, this work aimed to build a math modelling prediction to control the air quality around the campus of IPBeja, which is in the vicinity of a car traffic zone. The researchers have been analysing the data from the last months, particle matter (PM10 and PM2.5), and meteorological parameters for prediction using NARX. The results show a considerable increase in particles in occasional periods, reaching average values of 135 μg/m3 for PM10 and 52 μg/m3 for PM2.5. Thus, the monitoring and prediction serve as a warning to perceive these changes and be able to relate them to natural phenomena or issuing sources in specific cases.</jats:p>