Use of Low-Cost Devices for the Control and Monitoring of CO2 Concentration in Existing Buildings after the COVID Era
Source abstract
Abstract
In the COVID-19 era, a direct relationship has been consolidated between the concentration of the pollutant carbon dioxide (CO2) and indoor disease transmission. For reducing its spread, recommendations have been established among which air renewal is a key element to improve indoor air quality (IAQ). In this study, a low-cost CO2 measurement device was designed, developed, assembled, prototyped, and openly programmed so that the IAQ can be monitored remotely. In addition, this clonic device was calibrated for correct data acquisition. In parallel, computational fluid dynamics (CFD) modeling analysis was used to study the indoor air flows to eliminate non-representative singular measurement points, providing possible locations. The results in four scenarios (cross ventilation, outdoor ventilation, indoor ventilation, and no ventilation) showed that the measurements provided by the clonic device are comparable to those obtained by laboratory instruments, with an average error of less than 3%. These data collected wirelessly for interpretation were evaluated on an Internet of Things (IoT) platform in real time or deferred. As a result, remaining lifespan of buildings can be exploited interconnecting IAQ devices with other systems (as HVAC systems) in an IoT environment. This can transform them into smart buildings, adding value to their refurbishment and modernization.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Air Quality Monitoring and Forecasting · Infection Control and Ventilation · Building Energy and Comfort Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Engineering, University of Cadiz, Av. University of Cadiz 10, 11519 Puerto Real, Spain
Project Management, Innovation and Sustainability Research Centre (PRINS), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
References (100+)
Show source-provided references
1. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China10.1016/S0140-6736(20)30183-5 ↗
2. (2021, February 17). World Health Organization. Available online: https://www.who.int/home.
3. SARS-CoV-2 RNA detection in the air and on surfaces in the COVID-19 ward of a hospital in Milan, Italy10.1016/j.scitotenv.2020.140540 ↗
4. Impact of meteorological conditions and air pollution on COVID-19 pandemic transmission in Italy10.1038/s41598-020-73197-8 ↗
5. COVID-19 diagnosis and management: A comprehensive review10.1111/joim.13091 ↗
6. (2018). European Commission Council Recommendation (EU) 2021/119 of 1 February 2021 Amending Recommendation (EU) 2020/1475 on a Coordinated Approach to the Restriction of Free Movement in Response to the COVID-19 Pandemic.
7. Preparedness, E. (2021). Commission Recommendation
8. (EU) 2021/472 of 17 March 2021 on a Common Approach to Establish a Systematic Surveillance of SARS-CoV-2 and Its Variants in Wastewaters in the EU, European Commission.
9. The European Parliament and the Council of the European Union (2021). Regulation of the European Parliament and of the Council on a Framework for the Issuance, Verification and Acceptance of Interoperable Certificates on Vaccination, Testing and Recovery to Third-Country Nationals Legally Staying or Legally Residing in the territories of Member States during the COVID-19 pandemic (Digital Green Certificate), The European Parliament and the Council of the European Union.
10. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis10.1016/S0140-6736(20)31142-9 ↗
11. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: A scoping review10.1186/s40249-020-00646-x ↗
12. Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M.G., Borelli, M., Palmisani, J., Di Gilio, A., Piscitelli, P., and Miani, A. (2020). Airborne transmission route of COVID-19: Why 2 meters/6 feet of inter-personal distance could not be enough. Int. J. Environ. Res. Public Health, 17.10.3390/ijerph17082932 ↗
13. Displacement ventilation: A viable ventilation strategy for makeshift hospitals and public buildings to contain COVID-19 and other airborne diseases
14. How can airborne transmission of COVID-19 indoors be minimised?10.1016/j.envint.2020.105832 ↗
15. COVID-19 and cities: From urban health strategies to the pandemic challenge: A decalogue of public health opportunities
16. Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents10.1016/j.jhin.2020.01.022 ↗
17. Washing hands and the face may reduce COVID-19 infection10.1016/j.mehy.2020.110261 ↗
18. Transmission of COVID-19 virus by droplets and aerosols: A critical review on the unresolved dichotomy10.1016/j.envres.2020.109819 ↗
19. Modeling the role of respiratory droplets in COVID-19 type pandemics10.1063/5.0015984 ↗
20. Review of indoor aerosol generation, transport, and control in the context of COVID-1910.1002/alr.22661 ↗
21. Environmental factors involved in SARS-CoV-2 transmission: Effect and role of indoor environmental quality in the strategy for COVID-19 infection control10.1186/s12199-020-00904-2 ↗
22. Experimental characterization of speech aerosol dispersion dynamics
23. Human health effects of air pollution10.1016/j.envpol.2007.06.012 ↗
24. (2019). Ventilation for Acceptable Indoor Air Quality (Standard No. ANSI/ASHRAE Standard 62.1-2019).
25. ASHRAE (2009). Indoor Air Quality: Best Practices for Design, Construction, and Commisionning, American Society of Heating, Refrigerating and Air-Conditioning Engineers.
26. (2006). Building Environment Design Indoor Environment. General Principles (Standard No. ISO 16813:2006).
27. (2008). Building Environment Design—Indoor Air Quality—Methods of Expressing the Quality of Indoor Air for Human Occupancy (Standard No. BS ISO 16814:2008).
28. (2007). Air Quality—Guidelines for Estimating Measurement\Nuncertainty (Standard No. EN ISO 20988:2007).
29. (2019). Indoor Air—Part 40: Indoor Air Quality Management System (Standard No. ISO 16000-40:2019).
30. American Society of Heating, Refrigerating and Air-Conditioning Engineers (2019). ASHRAE Handbook-HVAC Applications, American Society of Heating, Refrigerating and Air-Conditioning Engineers.
31. The European Environment Agency (2021, November 26). Air Index EEA Europa, Available online: https://airindex.eea.europa.eu/Map/AQI/Viewer/.
32. (2018). The European Space Agency. Eur. Air Qual. Astron. Geophys., 59, 1.5.
33. The composition of air: The first scientific data
34. Indoor air quality and thermal comfort optimization in classrooms developing an automatic system for windows opening and closing10.1016/j.enbuild.2017.01.017 ↗
35. Effect of hypoxia on the hypopnoeic and apnoeic threshold for CO2 in sleeping humans10.1111/j.1469-7793.2001.00269.x ↗
36. Ventilatory sensitivity to CO2 in hyperoxia and hypoxia in older aged humans10.1152/jappl.1993.75.5.2209 ↗
37. Carbon Dioxide Concentration in the Bedroom for Various Natural Ventilation Modes10.1088/1757-899X/603/5/052100 ↗
38. Development of indoor environmental index: Air quality index and thermal comfort index
39. Kang, J., and Hwang, K.-I. (2016). A Comprehensive Real-Time Indoor Air-Quality Level Indicator. Sustainability, 8.10.3390/su8090881 ↗
40. Domínguez-Amarillo, S., Fernández-Agüera, J., Cesteros-García, S., and González-Lezcano, R.A. (2020). Bad air can also kill: Residential indoor air quality and pollutant exposure risk during the covid-19 crisis. Int. J. Environ. Res. Public Health, 17.10.3390/ijerph17197183 ↗
41. Ten scientific reasons in support of airborne transmission of SARS-CoV-2
42. Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic10.1038/s41467-020-18922-7 ↗
43. Personal CO2 cloud: Laboratory measurements of metabolic CO2 inhalation zone concentration and dispersion in a typical office desk setting10.1038/s41370-019-0179-5 ↗
44. AENOR (2019). Enery Performance of Buildings-Ventilation for Buldings—Part 2: Interpretation of the Requiirements in EN 16798-1. Indoor Enviromental Input Parameters for Desing and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics (Module M1-6), AENOR.
45. Investigation of CO2 production depending on physical activity of students10.1080/09603123.2018.1506570 ↗
46. Carbon dioxide generation rates of different age and gender under various activity levels10.1016/j.buildenv.2020.107317 ↗
47. Soares, A., Catita, C., and Silva, C. (2020). Exploratory research of CO2, noise and metabolic energy expenditure in Lisbon commuting. Energies, 13.10.3390/en13040861 ↗
48. Exhaled CO2 as a COVID-19 infection risk proxy for different indoor environments and activities10.1021/acs.estlett.1c00183 ↗
49. Projecting the transmission dynamics of SARS-CoV-2 through the post-pandemic period
50. Smart homes and the control of indoor air quality10.1016/j.rser.2018.05.057 ↗
51. United Nations (2022, January 10). Transforming Our World: The 2030 Agenda for Sustainable Development, Available online: https://sdgs.un.org/2030agenda.
52. Indoor hospital air and the impact of ventilation on bioaerosols: A systematic review10.1016/j.jhin.2019.06.016 ↗
53. The effect of the ventilation retrofit in a school on CO2, airborne particles, and energy consumptions10.1016/j.buildenv.2019.04.001 ↗
54. Indoor air quality in green vs conventional multifamily low-income housing10.1021/es501489u ↗
55. Engaging Citizens in Air Pollution Research: Investigating the Built Environment and Indoor Air Quality and Its Impact on Quality of Life10.1061/(ASCE)AE.1943-5568.0000439 ↗
56. Wang, Y., Qiao, F., Zhou, F., and Yuan, Y. (2020). Surface Distribution of Severe Acute Respiratory Syndrome Coronavirus 2 in Leishenshan Hospital. Indoor Built Environ., 1–9.10.1177/1420326X20942938 ↗
57. Persistence of Severe Acute Respiratory Syndrome Coronavirus 2 in Aerosol Suspensions10.3201/eid2609.201806 ↗
58. Effectiveness of heating, ventilation and air conditioning system with HEPA filter unit on indoor air quality and asthmatic children’s health10.1016/j.buildenv.2009.06.010 ↗
59. Beyond ozone: Cleaning outdoor air for improved IAQ 201
60. Inter-comparison of air pollutant concentrations in different indoor environments in Hong Kong10.1016/S1352-2310(02)00176-0 ↗
61. Vardoulakis, S., Giagloglou, E., Steinle, S., Davis, A., Sleeuwenhoek, A., Galea, K.S., Dixon, K., and Crawford, J.O. (2020). Indoor exposure to selected air pollutants in the home environment: A systematic review. Int. J. Environ. Res. Public Health, 17.10.3390/ijerph17238972 ↗
62. Building energy saving techniques and indoor air quality—A dilemma
63. Design-based natural ventilation evaluation in early stage for high performance buildings10.1016/j.scs.2018.11.024 ↗
64. Effect of natural ventilation and manual airing on indoor air quality in naturally ventilated Italian classrooms10.1016/j.buildenv.2016.01.009 ↗
65. Elhadary, M.I., Alzahrani, A.M.Y., Aly, R.M.H., and Elboshy, B. (2021). A comparative study for forced ventilation systems in industrial buildings to improve the workers’ thermal comfort. Sustainability, 13.10.3390/su131810267 ↗
66. A comparative study of the effects of ventilation-purification strategies on air quality and energy consumption in Beijing, China10.1007/s12273-020-0694-2 ↗
67. Sustainable development and requirements for energy efficiency in buildings—The Korean perspectives10.1177/1420326X18764618 ↗
68. Smart ventilation energy and indoor air quality performance in residential buildings: A review10.1016/j.enbuild.2017.12.051 ↗
69. Net-zero building designs in hot and humid climates: A state-of-art10.1016/j.csite.2019.100400 ↗
70. A review of net zero energy buildings in hot and humid climates: Experience learned from 34 case study buildings10.1016/j.rser.2019.109303 ↗
71. Air quality inside a school building: Air exchange monitoring, evolution of carbon dioxide and assessment of ventilation strategies
72. Evaluation of indoor air quality in classrooms equipped with cross-flow ventilation
73. Indoor air quality, ventilation and their associations with sick building syndrome in Chinese homes10.1016/j.enbuild.2019.05.046 ↗
74. Air change rates at night in northeast Chinese homes10.1016/j.buildenv.2018.01.030 ↗
75. (2019). The Standards for Ventilation and Indoor Air Quality (Standard No. ANSI/ASHRAE Standard 62.1).
76. (2019). Ventilation and Acceptable Indoor Air Quality in Residential Buildings (Standard No. ANSI/ASHRAE Standard 62.2).
77. Ministerio de la Presidencia de España (2007). Real Decreto 1027/2007: Regulation of Thermal Installations Thermal Installations in Buildings, BOE.
78. Villanueva, F., Jiménez, E., Felisi, J.-M., Garrido, T., Fiménez, J.-L., Ródenas, M., and Muñoz, A. (2021, November 02). Guide about Affordable CO2 detectors for COVID-19 Prevention. Available online: https://bit.ly/medidoresCO2Objective.
79. Saini, J., Dutta, M., and Marques, G. (2020). Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic review. Int. J. Environ. Res. Public Health, 14.10.3390/ijerph17144942 ↗
80. Marques, G., Saini, J., Dutta, M., Kumar Singh, P., and Hong, W.-C. (2020). Indoor Air Quality Monitoring Systems for Enhanced Living Environments: A Review toward Sustainable Smart Cities. Sustainability, 12.10.3390/su12104024 ↗
81. Zhang, H., and Srinivasan, R. (2020). A Systematic Review of Air Quality Sensors, Guidelines, and Measurement Studies for Indoor Air Quality Management. Sustainability, 12.10.3390/su12219045 ↗
82. Chiesa, G., Cesari, S., Garcia, M., Issa, M., and Li, S. (2019). Multisensor IoT platform for optimising IAQ levels in buildings through a smart ventilation system. Sustainability, 11.10.3390/su11205777 ↗
83. Sun, S., Zheng, X., Villalba-Díez, J., and Ordieres-Meré, J. (2019). Indoor air-quality data-monitoring system: Long-term monitoring benefits. Sensors, 19.10.3390/s19194157 ↗
84. Benammar, M., Abdaoui, A., Ahmad, S.H.M., Touati, F., and Kadri, A. (2018). A modular IoT platform for real-time indoor air quality monitoring. Sensors, 18.10.3390/s18020581 ↗
85. Marques, G., and Pitarma, R. (2019). A cost-effective air quality supervision solution for enhanced living environments through the internet of things. Electronics, 8.10.3390/electronics8020170 ↗
86. Indoor Air Quality Assessment Using a CO2 Monitoring System Based10.1007/s10916-019-1184-x ↗
87. Experimental Measurement and Computational Simulation Analysis of Indoor Air Quality in Office—Integration of Voltage Adsorption Dust Collection Device and Energy Recovery Ventilator
88. Omidvarborna, H., Kumar, P., Hayward, J., Gupta, M., and Nascimento, E.G.S. (2021). Low-cost air quality sensing towards smart homes. Atmosphere, 12.10.3390/atmos12040453 ↗
89. A review of smart building sensing system for better indoor environment control10.1016/j.enbuild.2019.06.025 ↗
90. Sensor deployment strategy using cluster analysis of Fuzzy C-Means Algorithm: Towards online control of indoor environment’s safety and health10.1016/j.scs.2020.102190 ↗
91. CFD simulation research on residential indoor air quality10.1016/j.scitotenv.2013.11.118 ↗
92. A CFD analysis of different human breathing models and its influence on spatial distribution of indoor air parameters
93. Another look at measures of forecast accuracy10.1016/j.ijforecast.2006.03.001 ↗
94. ANN based simulation and experimental verification of analytical four- and five-parameters models of PV modules10.1016/j.simpat.2013.02.001 ↗
95. Validation and reliability of the EPIC model to simulate maize production in small-holder farming systems in tropical sub-humid West Africa and semi-arid Brazil10.1016/j.agee.2009.10.014 ↗
96. Dynamic modeling of SOFC based on a T–S fuzzy model10.1016/j.simpat.2008.02.004 ↗
97. On the use of cross-validation for time series predictor evaluation10.1016/j.ins.2011.12.028 ↗
98. A hybrid statistical method to predict wind speed and wind power10.1016/j.renene.2009.12.011 ↗
99. MIMO model of an interacting series process for Robust MPC via System Identification10.1016/j.isatra.2010.02.005 ↗
100. An R2 statistic for fixed effects in the linear mixed model10.1002/sim.3429 ↗