Air quality modeling in the Oviedo urban area (NW Spain) by using multivariate adaptive regression splines.
Environ Sci Pollut Res Int
; 22(9): 6642-59, 2015 May.
Article
in En
| MEDLINE
| ID: mdl-25414030
ABSTRACT
The aim of this research work is to build a regression model of air quality by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (northern Spain) at a local scale. To accomplish the objective of this study, the experimental data set made up of nitrogen oxides (NO x ), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and dust (PM10) was collected over 3 years (2006-2008). The US National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of these numerical calculations, using the MARS technique, conclusions of this research work are exposed.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Cities
/
Air Pollutants
/
Air Pollution
/
Models, Theoretical
Type of study:
Diagnostic_studies
/
Prognostic_studies
Country/Region as subject:
Europa
Language:
En
Journal:
Environ Sci Pollut Res Int
Journal subject:
SAUDE AMBIENTAL
/
TOXICOLOGIA
Year:
2015
Type:
Article