title: Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.
abstract: A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.
authors.affiliation: a Escola Superior de Tecnologia de Setúbal , Instituto Politécnico , Setúbal , Portugal.
authors.forename: J M
authors.initials: JM
authors.lastname: Garcia
authors.affiliation: a Escola Superior de Tecnologia de Setúbal , Instituto Politécnico , Setúbal , Portugal.|b CEMAT, Instituto Superior Técnico , Lisboa , Portugal.
authors.forename: F
authors.initials: F
authors.lastname: Teodoro
authors.affiliation: a Escola Superior de Tecnologia de Setúbal , Instituto Politécnico , Setúbal , Portugal.
authors.forename: R
authors.initials: R
authors.lastname: Cerdeira
authors.affiliation: a Escola Superior de Tecnologia de Setúbal , Instituto Politécnico , Setúbal , Portugal.
authors.forename: L M R
authors.initials: LM
authors.lastname: Coelho
authors.affiliation: c Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences (FEPS) , University of Surrey Guildford , Surrey , UK.|d Environmental Flow Research Centre, FEPS , University of Surrey Guildford GU2 7XH , Surrey , UK.
authors.forename: Prashant
authors.initials: P
authors.lastname: Kumar
authors.affiliation: e Instituto Superior Técnico , Lisboa , Portugal.
authors.forename: M G
authors.initials: MG
authors.lastname: Carvalho
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods*; D016014:Linear Models; D052638:Particulate Matter / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Outdoor air quality; PM10; SPSS; generalized linear methods; methodology