New Methodology to Evaluate and Optimize Indoor Ventilation Based on Rapid Response Sensors
The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS)...
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Published in | Sensors (Basel, Switzerland) Vol. 24; no. 5; p. 1657 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
04.03.2024
MDPI |
Subjects | |
Online Access | Get full text |
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Summary: | The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space-obtained from CO
experimental RRS measurements and the characteristics of and activity in the space-and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1424-8220 1424-8220 |
DOI: | 10.3390/s24051657 |