Monitoring and Prediction of Particulate Matter (PM2.5 and PM10) around the Ipbeja Campus

被引:3
|
作者
Silva, Flavia Matias Oliveira [1 ]
Alexandrina, Eduardo Carlos [2 ]
Pardal, Ana Cristina [1 ]
Carvalhos, Maria Teresa [1 ]
Lui, Elaine Schornobay [3 ]
机构
[1] Polytech Inst Beja, P-7800000 Beja, Portugal
[2] Univ Fed Mato Grosso, Dept Min Engn, BR-78060900 Varzea Grande, MT, Brazil
[3] Fed Technol Univ Parana, Dept Engn, BR-85884000 Francisco Beltrao, PR, Brazil
关键词
particulate matter; air quality; neural networks; NARX;
D O I
10.3390/su142416892
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 mu g/m(3) for PM10 and 52 mu g/m(3) 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.
引用
收藏
页数:9
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