Abstract
Rapid growth in global energy consumption has raised concern on the environmental impacts such as ozone layer depletion and climate change. Enclosed space, such as commercial buildings, accounts for about 40% of global energy consumption and the demand is constantly increasing due to increasing population, urbanization, and economic development. The energy demands in the building sector calls for strategic measures to develop energy efficient technologies. This paper presents a strategy to decrease energy demands inside buildings by proposing a ventilation system which regulates the enclosed air quality resulting in reduced air conditioning. The system consists of multiple adsorption beds with zeolite 13X monoliths for CO2 removal, and silica gel for humidity control, inside the enclosed space. The air conditioning system results in decrease in energy requirement and improvement in economics by 55% as compared with conventional ventilation system. The model is scaled up to the size comparable with total office inventory of New York City, and the reduction in carbon emissions by introducing the air composition control system for New York City is equivalent to replacing 57 million incandescent light bulbs by LEDs. This paper concludes that the air conditioning system proposed in this study results in the improvement in performance as compared to a conventional ventilation system and could reduce energy consumption inside commercial buildings.
Recommended Citation
A. Sinha et al., "Reduced Building Energy Consumption by Combined Indoor CO2 and H2O Composition Control," Applied Energy, vol. 322, article no. 119526, Elsevier, Sep 2022.
The definitive version is available at https://doi.org/10.1016/j.apenergy.2022.119526
Department(s)
Chemical and Biochemical Engineering
Keywords and Phrases
Adsorption processes; Air conditioning system; Building energy consumption; Carbon footprint
International Standard Serial Number (ISSN)
0306-2619
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 Elsevier, All rights reserved.
Publication Date
15 Sep 2022
Comments
National Science Foundation, Grant CBET-1336386