{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:55:52Z","timestamp":1772168152307,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T00:00:00Z","timestamp":1663977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009708","name":"BERTHA\u2014The Danish Big Data Centre for Environment and Health","doi-asserted-by":"publisher","award":["NNF17OC0027864"],"award-info":[{"award-number":["NNF17OC0027864"]}],"id":[{"id":"10.13039\/501100009708","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurate calibration of low-cost gas sensors is, at present, a time consuming and difficult process. Laboratory calibration and field calibration methods are currently used, but laboratory calibration is generally discounted due to poor transferability, and field methods requiring several weeks are standard. The Enhanced Ambient Sensing Environment (EASE) method described in this article, is a hybrid of the two, combining the advantages of a laboratory calibration with the increased accuracy of a field calibration. It involves calibrating sensors inside a duct, drawing in ambient air with similar properties to the site where the sensors will operate, but with the added feature of being able to artificially increases or decrease pollutant levels, thus condensing the calibration period required. Calibration of both metal-oxide (MOx) and electrochemical (EC) gas sensors for the measurement of NO2 and O3 (0\u2013120 ppb) were conducted in EASE, laboratory and field environments, and validated in field environments. The EC sensors performed marginally better than MOx sensors for NO2 measurement and sensor performance was similar for O3 measurement, but the EC sensor nodes had less node inter-node variability and were more robust. For both gasses and sensor types the EASE calibration outperformed the laboratory calibration, and performed similarly to or better than the field calibration, whilst requiring a fraction of the time.<\/jats:p>","DOI":"10.3390\/s22197238","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T03:34:17Z","timestamp":1664163257000},"page":"7238","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Enhanced Ambient Sensing Environment\u2014A New Method for Calibrating Low-Cost Gas Sensors"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0896-6371","authenticated-orcid":false,"given":"Hugo Savill","family":"Russell","sequence":"first","affiliation":[{"name":"Department of Environmental Science, Aarhus University, DK-4000 Roskilde, Denmark"},{"name":"Danish Big Data Centre for Environment and Health (BERTHA), Aarhus University, DK-4000 Roskilde, Denmark"},{"name":"AirLabs, Nannasgade 28, DK-2200 Copenhagen N, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7681-8181","authenticated-orcid":false,"given":"Louise B\u00f8ge","family":"Frederickson","sequence":"additional","affiliation":[{"name":"Department of Environmental Science, Aarhus University, DK-4000 Roskilde, Denmark"},{"name":"Danish Big Data Centre for Environment and Health (BERTHA), Aarhus University, DK-4000 Roskilde, Denmark"},{"name":"AirLabs, Nannasgade 28, DK-2200 Copenhagen N, Denmark"}]},{"given":"Szymon","family":"Kwiatkowski","sequence":"additional","affiliation":[{"name":"AirLabs, Nannasgade 28, DK-2200 Copenhagen N, Denmark"}]},{"given":"Ana Paula Mendes","family":"Emygdio","sequence":"additional","affiliation":[{"name":"Global Center for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Surrey GU2 7XH, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2462-4411","authenticated-orcid":false,"given":"Prashant","family":"Kumar","sequence":"additional","affiliation":[{"name":"Global Center for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Surrey GU2 7XH, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7297-3851","authenticated-orcid":false,"given":"Johan Albrecht","family":"Schmidt","sequence":"additional","affiliation":[{"name":"AirLabs, Nannasgade 28, DK-2200 Copenhagen N, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0972-7735","authenticated-orcid":false,"given":"Ole","family":"Hertel","sequence":"additional","affiliation":[{"name":"Danish Big Data Centre for Environment and Health (BERTHA), Aarhus University, DK-4000 Roskilde, Denmark"},{"name":"Department of Ecoscience, Aarhus University, DK-4000 Roskilde, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3645-3955","authenticated-orcid":false,"given":"Matthew Stanley","family":"Johnson","sequence":"additional","affiliation":[{"name":"AirLabs, Nannasgade 28, DK-2200 Copenhagen N, Denmark"},{"name":"Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen \u00d8, Denmark"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/S0140-6736(17)32345-0","article-title":"The Lancet Commission on Pollution and Health","volume":"391","author":"Landrigan","year":"2018","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/S0140-6736(16)31679-8","article-title":"Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990\u20132015: A Syst. 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