title: Assessment of ultrafine particles and noise measurements using fuzzy logic and data mining techniques.
abstract: This study focuses on correlations between total number concentrations, road traffic emissions and noise levels in an urban area in the southwest of Spain during the winter and summer of 2009. The high temporal correlation between sound pressure levels, traffic intensity, particle number concentrations related to traffic, black carbon and NOx concentrations suggests that noise is linked to traffic emissions as a main source of pollution in urban areas. First, the association of these different variables was studied using PreFuRGe, a computational tool based on data mining and fuzzy logic. The results showed a clear association between noise levels and road-traffic intensity for non-extremely high wind speed levels. This behaviour points, therefore, to vehicular emissions being the main source of urban noise. An analysis for estimating the total number concentration from noise levels is also proposed in the study. The high linearity observed between particle number concentrations linked to traffic and noise levels with road traffic intensity can be used to calculate traffic related particle number concentrations experimentally. At low wind speeds, there are increases in noise levels of 1 dB for every 100 vehicles in circulation. This is equivalent to 2000 cm(-3) per vehicle in winter and 500 cm(-3) in summer. At high wind speeds, wind speed could be taken into account. This methodology allows low cost sensors to be used as a proxy for total number concentration monitoring in urban air quality networks.
authors.affiliation: Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Center for Research in Sustainable Chemistry CIQSO, University of Huelva, 21071 Huelva, Spain. Electronic address: rocio.fernandez@dgeo.uhu.es.
authors.forename: R
authors.initials: R
authors.lastname: Fernández-Camacho
authors.affiliation: Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Center for Research in Sustainable Chemistry CIQSO, University of Huelva, 21071 Huelva, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Brito Cabeza
authors.affiliation: Department of Information Technology, Engineering School, University of Huelva, Ctra. Palos de la Frontera, 21819 Palos Fra, Huelva, Spain.
authors.forename: J
authors.initials: J
authors.lastname: Aroba
authors.affiliation: Department of Electronic Engineering, Informatics Systems and Automation, Engineering School, University of Huelva, Ctra. Palos de la Frontera, 21819 Palos Fra, Huelva, Spain.
authors.forename: F
authors.initials: F
authors.lastname: Gómez-Bravo
authors.affiliation: Izaña Atmospheric Research Centre, AEMET Joint Research Unit to CSIC "Studies on Atmospheric Pollution", La Marina 20, planta 6, Santa Cruz de Tenerife, E38071 Canary Islands, Spain.
authors.forename: S
authors.initials: S
authors.lastname: Rodríguez
authors.affiliation: Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Center for Research in Sustainable Chemistry CIQSO, University of Huelva, 21071 Huelva, Spain.
authors.forename: J
authors.initials: J
authors.lastname: de la Rosa
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data*; D057225:Data Mining; D004784:Environmental Monitoring / Q000379:methods*; D017143:Fuzzy Logic; D009622:Noise; D052638:Particulate Matter / Q000032:analysis*; D013030:Spain
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Data mining; Fuzzy logic; Noise; Total number concentration; Traffic