Atmospheric carbon dioxide (CO2) concentration has risen since the industrial revolution, reaching record highs year after year, and is projected to continue rising. The global average concentration of CO2 has risen from 280 parts per million (ppm) to over 400 ppm over the last 150 years alone. CO2 is sourced from not only fossil fuel use, but also from an increasing population world-wide in combination with a reduction of foliage. Indoor air quality (IAQ) suffers as a result of poor circulation, and buildings have been shown to accumulate air toxics such as CO2 at greater levels than outdoors. Standards permit increases in CO 2 indoors in relationship to outdoor baseline levels, thus permitting an ever-increasing level of CO2 indoors. Although high concentrations of CO2 have been associated with perceptions of poor air quality, symptoms of illness, slow work performance, and absence from work or school, such as in cases of sick building syndrome (SBS), these effects have been assumed to be due to other air toxics that accompanied high CO2 levels in buildings.
New studies in low-to-moderate CO2 exposure in the range of 1,000–2,500 ppm challenge this assumption, and report negative impacts to proof-reading tasks, with further research in the same study series conducted with more sensitive cognitive function tests illustrating an impact on decision-making performance (Allen et al., 2015; Satish et al., 2012). With such broad human-occupied space impacts, IAQ factors such as CO2 cut across all socioeconomic categories, and cries out for innovative solutions.
The proposed approach in this thesis provides a framework for assessing IAQ data on the human health impacts of long-term IAQ exposures, both indoor and outdoor, with a sensor network designed to provide accessible real-time data visualizations to building occupants. Only outdoor air quality data is currently available from organizations such as the Environmental Protection Agency (EPA). With a new concept of “connected buildings,” equipped with IAQ monitoring made available by the proposed air quality sensor network, a new IAQ data stream can be merged with existing outdoor air quality monitoring station data streams such as those from the EPA.
The goal of this research is to enable IAQ data acquisition on a continuous basis towards better informed decisions for industrial development, enactment of standards, ecological policy for architectural development, and individual’s exposures, through consolidation of air quality metrics that combine real0time output from outdoor and indoor built environments that can be reviewed at-a-glance. The indoor distributed wireless sensor network (IDWSN) has been designed and produced to meet the needs of continuous real-time data monitoring while populating a database used to moderate IAQ remediation systems and real-time visualization interfaces to keep human occupants of a building informed.
|Commitee:||Rempel, Alexandra, Xiang, Ning|
|School:||Rensselaer Polytechnic Institute|
|School Location:||United States -- New York|
|Source:||MAI 56/05M(E), Masters Abstracts International|
|Subjects:||Agricultural engineering, Public health, Sustainability|
|Keywords:||Carbon dioxide, Distributed wireless sensor networks, Indoor air quality, Lighting, Photosynthesis, Remediation|
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