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Development of CO2 Concentration Prediction Tool for Improving Office Indoor Air Quality Considering Economic Cost
Energies ; 15(9):3232, 2022.
Article in English | MDPI | ID: covidwho-1820214
ABSTRACT
Ventilation is becoming increasingly important to improve indoor air quality and prevent the spread of COVID-19. This study analyzed the indoor air quality of office spaces, where occupants remain for extended periods, among multi-use facilities with an increasing need for ventilation system application. A 'tool for office space CO2 prediction and indoor air quality improvement recommendation';was developed. The research method was divided into four steps. Step 1 Analysis of indoor air quality characteristics in office spaces was carried out with a questionnaire survey and indoor air quality experiment. Based on the CO2 concentration, which was found to be a problem in the indoor air quality experiment in the office space, Step 2 CO2 concentration prediction tool for office spaces, which requires inputs of regional and spatial factors and architectural and equipment elements, was developed. In Step 3 Development and verification of prediction tool considering economic feasibility, the cost of energy recovery ventilation systems based on the invoices of the energy recovery ventilation manufacturers was analyzed. In Step 4 Energy recovery ventilation proposal and indoor CO2 forecast, Office Space B, which can accommodate up to 15 people, was derived as an example of the proposed tool. As a result of the prediction, the optimal air volume of the energy recovery ventilation was determined according to the 'office CO2 prediction and indoor air quality improvement recommendations';. This study introduced simple tools, which can be used by non-experts, that are capable of showing changes in indoor air quality, CO2 concentration and cost according to activities.

Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Energies Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Type of study: Prognostic study Language: English Journal: Energies Year: 2022 Document Type: Article