Developing a methodology to predict PM10 concentrations in urban areas using Generalized Linear Models.

Garcia, JM, Teodoro, F, Cerdeira, R, Coelho, LM, Kumar, P and Carvalho, MG (2016) Developing a methodology to predict PM10 concentrations in urban areas using Generalized Linear Models. Environ Technol. pp. 1-34.

Preview	Text Joao_Kumar (2016)_Env Tech PM10 Method.pdf - Accepted version Manuscript Available under License : See the attached licence file. Download (505kB) | Preview
Preview	Text (licence) SRI_deposit_agreement.pdf Available under License : See the attached licence file. Download (33kB) | Preview

Abstract

A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the Generalized Linear Models (GLM). 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 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 model 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 model with values of air temperature above 25 °C compared with model considering all range of air temperatures and with 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 this data is not available by measurements from air quality monitoring stations or other acquisition means.

Item Type:	Article
Subjects :	Civil and Environmental Engineering
Divisions :	Faculty of Engineering and Physical Sciences > Civil and Environmental Engineering
Authors :	Name Email ORCID Garcia, JM Teodoro, F Cerdeira, R Coelho, LM Kumar, P Carvalho, MG
Date :	7 March 2016
Identification Number :	10.1080/09593330.2016.1149228
Uncontrolled Keywords :	Generalized linear methods, Methodology, PM10, SPSS,  Outdoor air quality
Related URLs :	Author
Additional Information :	The Version of Record of this manuscript has been published and is available in Environmental Technology March 2016 http://www.tandfonline.com/ 10.1080/09593330.2016.1149228
Depositing User :	Symplectic Elements
Date Deposited :	16 Mar 2016 11:50
Last Modified :	17 Mar 2017 02:08
URI:	http://epubs.surrey.ac.uk/id/eprint/810173

Actions (login required)

View Item

Downloads