Developing a methodology to predict PM10 concentrations in urban areas using Generalized Linear Models
| Autor: | Luis Coelho, Prashant Kumar, João Garcia, R. Cerdeira, Maria da Graça Carvalho, F. Teodoro |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Generalized linear model
Engineering 010504 meteorology & atmospheric sciences media_common.quotation_subject Air pollution 010501 environmental sciences medicine.disease_cause Atmospheric sciences Poisson distribution 01 natural sciences Wind speed symbols.namesake Air Pollution medicine Environmental Chemistry Relative humidity Waste Management and Disposal Air quality index 0105 earth and related environmental sciences Water Science and Technology media_common Air Pollutants Variables business.industry Outdoor air quality Environmental engineering General Medicine symbols Linear Models Particulate Matter business Environmental Monitoring |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) Agência para a Sociedade do Conhecimento (UMIC)-FCT-Sociedade da Informação instacron:RCAAP |
| Popis: | 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 acity (Barreiro) of Portugal. The model uses air pollution and meteorological data from thePortuguese 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 themodel 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 info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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