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.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 February 2016.
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#13,459,901
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Outputs from Environmental Technology
#471
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#143,946
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Outputs of similar age from Environmental Technology
#11
of 30 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,421 research outputs from this source. They receive a mean Attention Score of 1.5. This one has done well, scoring higher than 79% of its peers.
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We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
