Hoi / Li / Yuen | Air Quality Monitoring and Advanced Bayesian Modeling | Buch | 978-0-323-90266-3 | sack.de

Buch, Englisch, 330 Seiten, Format (B × H): 192 mm x 232 mm, Gewicht: 668 g

Hoi / Li / Yuen

Air Quality Monitoring and Advanced Bayesian Modeling


Erscheinungsjahr 2023
ISBN: 978-0-323-90266-3
Verlag: Elsevier - Health Sciences Division

Buch, Englisch, 330 Seiten, Format (B × H): 192 mm x 232 mm, Gewicht: 668 g

ISBN: 978-0-323-90266-3
Verlag: Elsevier - Health Sciences Division


Air Quality Monitoring and Advanced Bayesian Modeling introduces recent developments in urban air quality monitoring and forecasting. The book presents concepts, theories, and case studies related to monitoring methods of criteria air pollutants, advanced methods for real-time characterization of chemical composition of PM and VOCs, and emerging strategies for air quality monitoring. The book illustrates concepts and theories through case studies about the development of common statistical air quality forecasting models. Readers will also learn advanced topics such as the Bayesian model class selection, adaptive forecasting model development with Kalman filter, and the Bayesian model averaging of multiple adaptive forecasting models.

Hoi / Li / Yuen Air Quality Monitoring and Advanced Bayesian Modeling jetzt bestellen!

Weitere Infos & Material


1. Introduction
2. Air quality monitoring
3. Traditional statistical air quality forecasting methods
4. Advanced Bayesian air quality forecasting methods
5. Concluding remarks


Li, Yongjie
Yongjie Li is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Macau. He obtained his Ph.D. degree in Environmental Engineering from The Hong Kong University of Science and Technology (2010), after receiving a B.Sc. degree in Chemistry from Peking University (2004). He was a postdoctoral fellow at Harvard University from 2014 - 2015 before joining the University of Macau. His research interests include air pollution measurements and atmospheric chemistry. He has been working on mass spectrometric techniques for real-time air pollution measurements and chemical reactions leading to secondary pollution formation, which resulted in over 100 SCI journal articles on these topics. He teaches one undergraduate course, Environmental Engineering, and two postgraduate courses, Air Pollution Meteorology and Chemistry and Air Pollution Control. He was the recipient of the Asian Young Aerosol Scientist Award in 2022 and the China Aerosol Young Scientist Award in 2019.

Yuen, Ka Veng
Ka-Veng Yuen is a Distinguished Professor of the State Key Laboratory on Internet of Things for Smart City and Department of Civil and Environmental Engineering of the University of Macau. He received his Ph.D. in Civil Engineering from the California Institute of Technology (Caltech). His research expertise includes Bayesian inference, uncertainty quantification, system identification, structural health monitoring, reliability analysis and analysis of dynamical systems. His paper "Model selection using response measurements: Bayesian probabilistic approach" (coauthored with J.L. Beck) is one of the top 20 most cited papers among all papers published in the Journal of Engineering Mechanics (established since 1983) of the American Society of Civil Engineers.

Hoi, Ka In
Ka In Hoi obtained his bachelor degree (2000), master degree (2003), and Ph.D. (2011) in Civil Engineering at the University of Macau (UM). Starting from 2003, he joined the Department of Civil and Environmental Engineering at UM as the laboratory technician and has been researching air quality forecasting and machine learning application pertaining to Civil and Environmental Engineering. He achieved the Second Prize of Technology Invention of the Macau Science & Technology Award in 2014. Dr. Hoi has published 20 SCI journal articles. He participated 2 FDCT funded projects and 2 internal research projects of the University as the postdoctoral fellow. Now he is the laboratory technician of the Hydraulics laboratory and the Geotechnical Engineering laboratory at the University of Macau.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.