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Global Journal of Engineering and Technology Advances
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Research & review articles are invited for publication in September 2026 (Vol. 28, Issue 3) || Submission: up to 28th September || Editorial decision: within 48 hrs.

Dynamic indoor air quality management for energy-efficient buildings without compromising health

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  • Dynamic indoor air quality management for energy-efficient buildings without compromising health

Olayinka Enitan Adedoyin *

Ogun State Ministry of Housing, Ogun State, Nigeria.
 
Research Article
Global Journal of Engineering and Technology Advances, 2024, 19(02), 185–199.
Article DOI: 10.30574/gjeta.2024.19.2.0093
DOI url: https://doi.org/10.30574/gjeta.2024.19.2.0093
Received on 18 April 2024 revised on 23 May 2024; accepted on 29 May 2024
 
As global efforts intensify to reduce building energy consumption and carbon footprints, contemporary architectural design trends increasingly favor airtight construction and mechanical ventilation systems. While such strategies improve thermal efficiency, they also heighten the risk of trapping indoor pollutants, moisture, and bioaerosols, thereby compromising occupants’ health. This tension between sustainability and wellbeing is particularly acute in rapidly urbanizing regions where infrastructure, environmental monitoring, and building standards are inconsistent. Lagos provides a compelling case: widespread reliance on low-cost air conditioners, intermittent power supply, and diesel generators leads occupants to seal windows to retain cooled air and reduce noise and fumes. The result is a dynamic indoor air environment where pollutant concentrations fluctuate with energy use patterns, ventilation behaviors, and external fuel emissions. This study proposes a dynamic indoor air quality (IAQ) management framework that leverages real-time sensing, adaptive ventilation controls, and data-driven airflow modeling to maintain healthy indoor environments without undermining energy efficiency. The framework incorporates low-cost sensor networks to monitor temperature, humidity, particulate matter, volatile organic compounds, and carbon dioxide levels. Machine learning algorithms predict pollutant accumulation under varying occupancy and power conditions, triggering targeted ventilation cycles or filtration adjustments to reduce contaminant loads. This adaptive strategy supports intermittent power scenarios common in Lagos while minimizing unnecessary energy expenditure. By bridging environmental engineering, public health, and sustainability design, this approach demonstrates that energy-efficient buildings need not compromise occupant wellness. Instead, intelligent IAQ management offers a viable path toward resilient, healthy, and resource-conscious urban living. The findings contribute to sustainable development discourse by emphasizing that “green” buildings must actively protect the air their occupants breathe.
 
Indoor air quality; Energy-efficient buildings; Adaptive ventilation; Urban health; Low-cost sensors; Sustainable architecture
 
https://gjeta.com/sites/default/files/fulltext_pdf/GJETA-2024-0093.pdf

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Olayinka Enitan Adedoyin. Dynamic indoor air quality management for energy-efficient buildings without compromising health. Global Journal of Engineering and Technology Advances, 2024, 19(2), 185-199. Article DOI: https://doi.org/10.30574/gjeta.2024.19.2.0093

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