Your browser doesn't support javascript.
loading
An hourly PM10 diagnosis model for the Bilbao metropolitan area using a linear regression methodology.
González-Aparicio, I; Hidalgo, J; Baklanov, A; Padró, A; Santa-Coloma, O.
Afiliación
  • González-Aparicio I; Energy and Environmental Division, TECNALIA Research and Innovation, Edificio 700, C/Geldo, 48160 Derio, Spain. iratxe.gonzalez@tecnalia.com
Environ Sci Pollut Res Int ; 20(7): 4469-83, 2013 Jul.
Article en En | MEDLINE | ID: mdl-23247520
There is extensive evidence of the negative impacts on health linked to the rise of the regional background of particulate matter (PM) 10 levels. These levels are often increased over urban areas becoming one of the main air pollution concerns. This is the case on the Bilbao metropolitan area, Spain. This study describes a data-driven model to diagnose PM10 levels in Bilbao at hourly intervals. The model is built with a training period of 7-year historical data covering different urban environments (inland, city centre and coastal sites). The explanatory variables are quantitative-log [NO2], temperature, short-wave incoming radiation, wind speed and direction, specific humidity, hour and vehicle intensity-and qualitative-working days/weekends, season (winter/summer), the hour (from 00 to 23 UTC) and precipitation/no precipitation. Three different linear regression models are compared: simple linear regression; linear regression with interaction terms (INT); and linear regression with interaction terms following the Sawa's Bayesian Information Criteria (INT-BIC). Each type of model is calculated selecting two different periods: the training (it consists of 6 years) and the testing dataset (it consists of 1 year). The results of each type of model show that the INT-BIC-based model (R(2) = 0.42) is the best. Results were R of 0.65, 0.63 and 0.60 for the city centre, inland and coastal sites, respectively, a level of confidence similar to the state-of-the art methodology. The related error calculated for longer time intervals (monthly or seasonal means) diminished significantly (R of 0.75-0.80 for monthly means and R of 0.80 to 0.98 at seasonally means) with respect to shorter periods.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Diagnostic_studies / Prognostic_studies / Qualitative_research País/Región como asunto: Europa Idioma: En Revista: Environ Sci Pollut Res Int Asunto de la revista: SAUDE AMBIENTAL / TOXICOLOGIA Año: 2013 Tipo del documento: Article País de afiliación: España Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Diagnostic_studies / Prognostic_studies / Qualitative_research País/Región como asunto: Europa Idioma: En Revista: Environ Sci Pollut Res Int Asunto de la revista: SAUDE AMBIENTAL / TOXICOLOGIA Año: 2013 Tipo del documento: Article País de afiliación: España Pais de publicación: Alemania