1:45pm - 2:00pmMO3-3: 1
Assessing the response of indoor air quality sensors in longitudinal studies – implications of sensor drift and source variations for exposure misclassification
Michael Hedges1, Anja H Tremper1, Diana Varaden1, Benjamin M. Barratt1,2, Frank J. Kelly1,2, David C. Green1,2
1Imperial College, United Kingdom; 2NIHR HPRU in Environmental Exposures and Health, Imperial College, London, United Kingdon
The WellHome study focused on indoor air quality inside and outside over 100 homes in London to identify dominant air pollution exposures across the indoor:outdoor continuum. Air quality measurements were sampled in three rooms in each house during two 4-week campaigns using 60 small sensors. To ensure comparability between homes a robust quality assurance calibration program was designed to account for source specificity for home activities. Our findings demonstrate significant drift in pollutant responses for the sensors and by challenging the sensors with different PM2.5 sources we showed that the PM2.5 sensors had a lower sensivitivity to some indoor sources.
2:00pm - 2:15pmMO3-3: 2
Low-cost air quality data collection using sensors and student science in Ethiopia
Johannes Dirk Dingemanse1,2, Afework Tademe1, Wegene Negesse Debele3
1Arba Minch University, Ethiopia; 2Lund University, Sweden; 3Ethiopian Meteorology Institute, Adama Branch
In low-income countries, resource shortages limit student training and research opportunities. At Arba Minch University, Ethiopia, low-cost sensor (LCS) development and research with students (student science) addressed this challenge for air quality research. A locally developed PM2.5 sensor system was validated at ambient and indoor locations, showing strong intra-correlation (r≥0.97) and accuracy versus gravimetric methods (r≥0.95). More than 50,000 hours of data across 16 locations were collected, 7,048 of which by undergraduate students. LCS development and student science provided local training and reliable data at costs under €1,500, making air quality research more accessible to Ethiopian universities.
2:15pm - 2:30pmMO3-3: 3
Long-term aerosol measurements of the Alphasense OPC-N3 in arctic regions: Sensor performance and corrections
Kilian Schneiders1, Lasse Moormann2, Sylvain Dupont3, Daniel Koenen1, Jan Rabe1, Pavla Dagsson-Waldhauserová4,5, Kerstin Schepanski6, Agnesh Panta1, Martina Klose7, Hannah Meyer7, Cristina González-Flórez8,9, Adolfo González-Romero4, Xavier Querol10, Andres Alastuey10, Jesús Yus-Díez10,11,12, Carlos Pérez García-Pando8,13, Konrad Kandler1
1Technical University Darmstadt, Institute of Applied Geosciences, Darmstadt, Germany; 2Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany; 3INRAE, Bordeaux Sciences Agro, ISPA, Villenave d’Ornon, France; 4Agricultural University of Iceland, Environmental Sciences, Reykjavik, Iceland; 5Czech University of Life Sciences, Prague, Czech Republic; 6Freie Universität Berlin, Institute of Meteorology, Berlin, Germany; 7Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research – Troposphere Research (IMKTRO), Karlsruhe, Germany; 8Barcelona Supercomputing Center (BSC), Barcelona, Spain; 9Danish Meteorological Institute (DMI), Copenhagen, Denmark; 10Institute of Environmental Assessment and Water Research – Consejo Superior de Investigaciones Científicas (IDAEA-CSIC), Barcelona, Spain; 11Grup de Meteorologia, Departament de Física Aplicada, Universitat de Barcelona, Spain; 12Center for Atmospheric Research, University of Nova Gorica, Slovenia; 13Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
With the decrease of electronic component prices, powerful yet low-cost optical particle counters (OPCs) gain in popularity. Sensor performance and long-term accuracy must be evaluated in order to maintain data quality. During a measurement campaign focusing on Arctic dust emission (HiLDA), we deployed seven measurement stations, equiped with four Alphasense OPC-N3 low-cost OPCs. In this work, we present a correction scheme for cross-dependencies of the measured data and different aging effects.
2:30pm - 2:45pmMO3-3: 4
Novel approaches in ambient air quality assessment and prediction using mobile low-cost sensor measurements and citizen involvement (The RI-URBANS project)
Dimitrios Bousiotis1, Arunik Baruah2,3, Seny Damayanti1, Roy Harrison1, Francis Pope1
1University of Birmingham, United Kingdom; 2University of Modena and Reggio Emilia, Italy; 3University School for Advanced Studies IUSS Pavia, Italy
Low-cost sensors (LCS) can complement the current air pollution measuring network by increasing the density of the measurements collected. This additional data can be used to provide crucial information, which can be used to improve the air quality for everyone. With data collected using LCS and novel methodologies we managed to generate information which expand our understanding of air pollution, the sources driving it and their range of effect in a spatial resolution that was not possible before. Furthermore, by testing different ML methodologies we managed to fill spatial and temporal air quality data gaps and predict their future trends.
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