Our project brings about increased innovation regarding the model of modern air purifiers and filtration systems by expounding on their potential by using existing smart air purifier models integrated with photo catalytic oxidation, this modified device is meant to deliver clean air in indoor spaces.
Since current governments are easing lockdown restrictions, various industry sectors will be revived causing a sudden increase in air pollution, caused by aerosol emissions and Volatile Organic Compounds (VOCs). Moreover, Jantuten (2007) said that a high concentration of outdoor pollutants like Nitrogen Oxide (NO2), Carbon Monoxide (CO) and other VOCs will likely influence indoor air quality. These pollutants were reported to induce respiratory and cardiac problems in our body. By installing air purifiers, along with stringent enclosure qualities and improved ventilation system designs, such influences can be avoided. In order for air purifiers to be sustainable, augmenting its energy use as dependent to observed air quality indexes improves its performance while saving power.
To analyze the extent of the idea of having a smart and portable air purifying system, data sets from the NASA Giovanni Data Portal were analyzed, including CO and NO2 columns, Aerosol Movement, Air Temperature, and Relative Humidity to analyze trends in air quality in a certain area. After concluding from the datasets that the values are dynamic (meaning at times concentrations in a certain area is 0 while at other times it reaches the threshold air quality), a need for integrating IoT data into an air purifying device was needed to improve its power usage. Using an existing model by Idziak and Gojtowski (2019) while integrating a photo catalytic oxidative device similar to the air cleaning technology in the ISS (ERASMUS, 2010) and the Spacs Shuttle Columbia Mission in 1995 (NASA, 2015), an air purifying device was modeled with FreeCAD for better visualization of where the components shall be put. Development of the application which is to be used to observe IoT and Atmospheric Processes derived from NASA Earthdata API was done using Thunkable, and Indoor IoT data sensing shall be powered by an Arduino UNO module.
Idziak P, Gojtowski M. 2019. Smart air purifier suitable for small public spaces. ITM Conf. 28 (2019). https://doi.org/10.1051/itmconf/20192801015
Jantuten M. 2007. Effect of outdoor generated pollutants on indoor air quality and health. Proceedings of Clima 2007 Wellbeing Indoors. 2007: 21-28.
NASA. 2015. Charged Particles Kill Pathogens and Round Up Dust. Spinoff 2015. 2015: 92-93. Retrieved from: https://ntrs.nasa.gov/search.jsp?R=20150003556 2020-05-30T14:16:30+00:00Z
ERASMUS. 2010. Environmental Control and Life Support System (ESA-HSO-COU-030). European Space Agency.
OMI OMAEROs. 2020. Aerosol Optical Depth 342.5nm daily 0.23 deg. NASA Giovanni Data Portal. March - April 2020. https://giovanni.gsfc.nasa.gov/
MERRA-2 Model M2SDNXSLV. 2020. 2-meter air temperature - daily min daily 0.5 x 0.625 deg. NASA Giovanni Data Portal. March - April 2020. https://giovanni.gsfc.nasa.gov/
AIRS AIRS3STD. 2020. Carbon Monoxide, Mole Fraction in Air (Daytime/Ascending, AIRS-only) daily 1 deg. Giovanni Data Portal. March 2020. https://giovanni.gsfc.nasa.gov/
OMI OMNO2d. 2020. NO2 Tropospheric Column (30% Cloud Screened) daily 0.25 deg. NASA Giovanni Data Portal. March 2020. https://giovanni.gsfc.nasa.gov/