title: A comparison of strategies for estimation of ultrafine particle number concentrations in urban air pollution monitoring networks.
abstract: We propose three estimation strategies (local, remote and mixed) for ultrafine particles (UFP) at three sites in an urban air pollution monitoring network. Estimates are obtained through Gaussian process regression based on concentrations of gaseous pollutants (NOx, O3, CO) and UFP. As local strategy, we use local measurements of gaseous pollutants (local covariates) to estimate UFP at the same site. As remote strategy, we use measurements of gaseous pollutants and UFP from two independent sites (remote covariates) to estimate UFP at a third site. As mixed strategy, we use local and remote covariates to estimate UFP. The results suggest: UFP can be estimated with good accuracy based on NOx measurements at the same location; it is possible to estimate UFP at one location based on measurements of NOx or UFP at two remote locations; the addition of remote UFP to local NOx, O3 or CO measurements improves models' performance.
authors: VITO, Flemish Institute for Technological Research, Boeretang 200, B-2400 Mol, Belgium. Electronic address: reggente@gmail.com.
authors: Matteo
authors: M
authors: Reggente
authors: VITO, Flemish Institute for Technological Research, Boeretang 200, B-2400 Mol, Belgium.
authors: Jan
authors: J
authors: Peters
authors: VITO, Flemish Institute for Technological Research, Boeretang 200, B-2400 Mol, Belgium.
authors: Jan
authors: J
authors: Theunis
authors: VITO, Flemish Institute for Technological Research, Boeretang 200, B-2400 Mol, Belgium.
authors: Martine
authors: M
authors: Van Poppel
authors: Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium.
authors: Michael
authors: M
authors: Rademaker
authors: Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium.
authors: Bernard
authors: B
authors: De Baets
authors: Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Science (FEPS), University of Surrey, GU2 7XH, United Kingdom; Environmental Flow (EnFlo) Research Centre, FEPS, University of Surrey, GU2 7XH, United Kingdom.
authors: Prashant
authors: P
authors: Kumar
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000379:methods*; D015386:Hazardous Substances; D008962:Models, Theoretical; D052638:Particulate Matter / Q000032:analysis*; D012044:Regression Analysis; D012828:Silicones
chemical_list: D000393:Air Pollutants; D015386:Hazardous Substances; D052638:Particulate Matter; D012828:Silicones
keywords: Gaussian process regression; Pollution monitoring network; Statistical modelling; Ultrafine particles estimation; Urban air pollution