Articles | Volume 22, issue 3 
            
                
                    
            
            
            https://doi.org/10.5194/acp-22-1861-2022
                    © Author(s) 2022. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-1861-2022
                    © Author(s) 2022. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Input-adaptive linear mixed-effects model for estimating alveolar lung-deposited surface area (LDSA) using multipollutant datasets
                                            Institute for Atmospheric and Earth System Research/Physics,  Faculty
of Science, University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Helsinki Institute of Sustainability Science, Faculty of Science,
University of Helsinki, Helsinki, Finland
                                        
                                    Martha A. Zaidan
                                            Institute for Atmospheric and Earth System Research/Physics,  Faculty
of Science, University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Helsinki Institute of Sustainability Science, Faculty of Science,
University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Joint International Research Laboratory of Atmospheric and Earth
System Sciences,  School of Atmospheric Sciences, Nanjing University, Nanjing
210023, China
                                        
                                    Jarkko V. Niemi
                                            Helsinki Region Environmental Services Authority (HSY), P.O. Box 100,
00066 Helsinki, Finland
                                        
                                    Erkka Saukko
                                            Pegasor Oy, 33100 Tampere, Finland
                                        
                                    Hilkka Timonen
                                            Atmospheric Composition Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
                                        
                                    Anu Kousa
                                            Helsinki Region Environmental Services Authority (HSY), P.O. Box 100,
00066 Helsinki, Finland
                                        
                                    Joel Kuula
                                            Atmospheric Composition Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
                                        
                                    Topi Rönkkö
                                            Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, Finland
                                        
                                    Ari Karppinen
                                            Atmospheric Composition Research, Finnish Meteorological Institute,
00560 Helsinki, Finland
                                        
                                    Sasu Tarkoma
                                            Department of Computer Science, Faculty of Science, University of
Helsinki, Helsinki, Finland
                                        
                                    Markku Kulmala
                                            Institute for Atmospheric and Earth System Research/Physics,  Faculty
of Science, University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Joint International Research Laboratory of Atmospheric and Earth
System Sciences,  School of Atmospheric Sciences, Nanjing University, Nanjing
210023, China
                                        
                                    Tuukka Petäjä
                                            Institute for Atmospheric and Earth System Research/Physics,  Faculty
of Science, University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Joint International Research Laboratory of Atmospheric and Earth
System Sciences,  School of Atmospheric Sciences, Nanjing University, Nanjing
210023, China
                                        
                                    Tareq Hussein
CORRESPONDING AUTHOR
                                            
                                    
                                            Institute for Atmospheric and Earth System Research/Physics,  Faculty
of Science, University of Helsinki, Helsinki, Finland
                                        
                                    
                                            Department of Physics, the University of Jordan, Amman 11942, Jordan
                                        
                                    Data sets
SmartSMEAR – About University of Helsinki https://smear.avaa.csc.fi/
Open data Helsinki Region Environmental Services HSY https://www.hsy.fi/avoindata
Short summary
                    We developed an input-adaptive mixed-effects model, which was automatised to select the best combination of input variables, including up to three fixed effect variables and three time indictors as random effect variables. We tested the model to estimate lung-deposited surface area (LDSA), which correlates well with human health. The results show the inclusion of time indicators improved the sensitivity and the accuracy of the model so that it could serve as a network of virtual sensors.
                    We developed an input-adaptive mixed-effects model, which was automatised to select the best...
                    
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