ID: 1193
/ SES-D6: 1
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Oral presentation
ONSITE
Topics: 1b. Indoor air quality, health and wellbeing - Psychology of IAQ perceptionKeywords: Natural ventilation, balanced mechanical ventilation, indoor air pollution index, perception score
Measured and perceived IEQ under different ventilation strategies in Swedish classrooms
Blanka Cabovská1, Natalia G. Vasquez2, Despoina Teli1, Jan-Olof Dalenbäck1, Gabriel Bekö2, Pawel Wargocki2, Lars Ekberg1,3, Sarka Langer1,4
1Chalmers University of Technology, Department of Architecture and Civil Engineering, Sweden; 2International Centre for Indoor Environment and Energy, Department of Civil Engineering, Technical University of Denmark, Denmark; 3CIT Energy Management AB, Sweden; 4IVL Swedish Environmental Research Institute, Environmental Chemistry, Sweden
ID: 1297
/ SES-D6: 2
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Topics: 1b. Indoor air quality, health and wellbeing - Psychology of IAQ perception, 3. Thermal comfortKeywords: Occupant satisfaction, Indoor environmental quality, Secondary school, Mixed-effect models
Driving factors of occupants’ satisfaction with IEQ in a school building
Quinten Carton1, Jakub Kolarik2, Hilde Breesch1
1KU Leuven, Department of Civil Engineering, Building Physics and Sustainable Design, Ghent Technology Campus, Belgium; 2Department of Civil Engineering, Technical University of Denmark, Kongens Lyngby, Denmark
ID: 1227
/ SES-D6: 3
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Topics: 1b. Indoor air quality, health and wellbeing - Psychology of IAQ perceptionKeywords: School. perception, citizen science, well-being, pupils
The indoor environment in Danish classrooms and its assocation with pupil wellbeing and performance
Jørn Toftum, Geo Clausen
Technical University of Denmark, Denmark
ID: 1278
/ SES-D6: 4
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Topics: 1a. Indoor air quality, health and wellbeing - Biologicals, gaseous, particlesKeywords: endocrine disruptors; indoor air quality; schools; children; neurocognitive development
Endocrine disruptors and child neurodevelopment – research questions and study design of EDC(Mind)2 project
Joana Madureira1,2,3, Maria do Carmo Pereira4,5, João João Paulo Teixeira1,2,3,, Dagmar Dzúrová6, Ivete Afonso7, Stefano Bonassi8, Hans Verhagen9, Lídia Morawska10, Klara Slezakova4,5
1Environmental Health Department, National Institute of Health, Porto, Portugal; 2EPIUnit-Institute of Public Health, University of Porto, Portugal; 3Laboratory for Integrative and Translational Research in Population Health (ITR), Porto, Portugal; 4Faculty of Engineering, University of Porto, Portugal; 5ALiCE, Faculty of Engineering, University of Porto, Porto, Portugal; 6Department of Social Geography and Regional Development, Faculty of Science, Charles University, Prague, Czech Republic; 7Department of Pediatric Endocrinology, Metabolism and Nutrition, Hospital Pedro Hispano, Matosinhos, Portugal; 8IRCCS San Rafaele, Pisana, Italy; 9Food Safety & Nutrition Consultancy, The Netherlands; 10School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia
ID: 1679
/ SES-D6: 5
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ONSITE
Topics: 1a. Indoor air quality, health and wellbeing - Biologicals, gaseous, particles, 5a. Monitoring of indoor air quality - VOCs, and other gaseous contaminants, 5b. Monitoring of indoor air quality - Particles, fibres, 5c. Monitoring of indoor air quality - Analytics and sensors, 9c. Sustainable and healthy building - Intelligent design and solutionsKeywords: Indoor air quality, intelligent solutions, stove hood, gas sensors, particulate matter
Smart stove hood with embedded sensors: a student project
Guillem Domènech-Gil, Jennifer Silander, Linda Skoglund, Bastien Bégon, Olivia Grönlund Falk, Märta Håkansson, Victor Rutberg, Felix Valentin, Martin Forsgren, Shiqi Guo, Tristan Dettke, Wuji Lyu, Zahra Mohammadianrasnani, Amaia B. Ortega Santos, Jose G. Martinez, Jens Eriksson, Donatella Puglisi
Sensor and Actuator Systems, Department of Physics, Chemistry and Biology, Linköping University, Sweden
ID: 1125
/ SES-D6: 6
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Topics: 5a. Monitoring of indoor air quality - VOCs, and other gaseous contaminants, 5b. Monitoring of indoor air quality - Particles, fibres, 5c. Monitoring of indoor air quality - Analytics and sensors, 13b. Others - Special applicationsKeywords: low-cost sensors, machine learning, prediction, ventilation control
Can machine learning predict high-concentration events before they happen?
Jordan Clark, Ahmad Mohammadshirazi, Rajiv Ramnath
The Ohio State University, United States of America
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