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Synergistic Green Technologies for Sustainable Indoor Air Quality Management

2026-08-02 · SciEn Conference Series Engineering

One-line summary

A solar energy research paper on Synergistic Green Technologies for Sustainable Indoor Air Quality Management.

Engineering notes

Engineering notes will be added by the Power for Solar editorial team.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

Indoor air pollution (IAP) poses a significant global health burden, particularly in developing nations. This paper presents a novel, sustainable framework for managing indoor air quality (IAQ) by synergistically integrating solar-powered liquid desiccant air filtration with active phytoremediation. Conventional technologies are often energy-intensive and produce waste, while natural solutions like phytoremediation have limitations in efficacy and speed. The proposed system utilizes a triethylene glycol (TEG) solution in a counter-flow tray contactor for simultaneous dehumidification and removal of volatile organic compounds (VOCs) and particulate matter (PM), powered entirely by photovoltaic cells. Furthermore, the system is augmented with a selection of indoor plants known for their high efficacy in removing specific pollutants, creating a bio-regenerative buffer zone. A detailed technical methodology for sizing the system components, including the contactor, regenerator, and solar array, is provided. Analysis indicates the potential for the system to remove over 90% of toluene and 80% of PM 2.5, while selected plants can reduce residual formaldehyde and benzene levels by up to 80% within 12 hours. This synergistic approach not only aligns technological innovation with natural processes to promote human health and environmental sustainability but also demonstrates significant economic viability through drastically reduced operational costs compared to conventional, grid-dependent systems. Furthermore, the framework's adaptability is enhanced by a proposed Model Predictive Control (MPC) system, offering a path for dynamic, autonomous operation based on real-time IoT feedback.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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