Quantifying Personal Exposure to Spatio-Temporally Distributed Air Pollutants using Mobile Sensors

Air Pollution these days is one of the most significant problems worldwide and understanding the spatio-temporal nature of pollutants is still a challenge. Besides, knowing the concentration of pollutants in the ambient air, estimating the personal inhalation and exposure of an individual to air pollution is equally important. In this paper, we have primarily worked on devising a personal inhalation model to estimate the exposure of an individual to air pollution keeping into account the activity performed by the user and his personal health using mobile handheld sensors. Our results show that the inhalation dosage increased by 78% for CO (Carbon Monoxide) and 28.41% for PM2.5 (Particulate Matter with diameter less than 2.5 micrometers), when a person switches his/her activity from walking to running. By using the results obtained from our proposed model, the sensitive groups like patients with respiratory and cardiovascular diseases, small children, pregnant women etc can quantify the pollutants inhaled and hence manage their lifestyle.

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