Real-Time Low-Cost Personal Monitoring for Exposure to PM2.5 among Asthmatic Children: Opportunities and Challenges

Abstract

This study aims to evaluate the accuracy and effectiveness of real-time personal monitoring of exposure to PM concentrations using low-cost sensors, in comparison to conventional data collection method based on fixed stations. PM2.5 data were measured every 5 min using a low-cost sensor attached to a bag carried by 47 asthmatic children living in the Seoul Metropolitan area between November 2019 and March 2020, along with the real-time GPS location, temperature, and humidity. The mobile sensor data were then matched with station-based hourly PM2.5 data using the time and location. Despite some uncertainty and inaccuracy of the sensor data, similar temporal patterns were found between the two sources of PM2.5 data on an aggregate level. However, average PM2.5 concentrations via personal monitoring tended to be lower than those from the fixed stations, particularly when the subjects were indoors, during nighttime, and located farther from the fixed station. On an individual level, a substantial discrepancy is observed between the two PM2.5 data sources while staying indoors. This study provides guidance to policymakers and researchers on improving the feasibility of personal monitoring via low-cost mobile sensors as an alternative or supplement to the conventional station-based monitoring.

Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries

“…Their study demonstrates the successful use of GPS-attached Pocket PM 2.5 sensors for mobile sensing and continuous measurement. In Seoul, Korea, the personal PM 2.5 exposures of 47 asthmatic children were investigated with an emphasis on comparing the accuracy and effectiveness of the real-time personal monitoring using LCPMS (PICO, model: PMM-130) to those obtained from monitoring stations [103]. They found that average PM 2.5 concentrations measured by personal monitoring were lower than those measured by the monitoring stations, especially when the individuals were indoors, at night, and much further away from the monitoring station.…”

Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring

“…For these aims, we compared the routine ambient air quality monitoring data provided by the Korean Ministry of Environment titled "Air Korea" with new sensor-based air monitoring data from the Korea Testing & Research Institute (KTR). For the Air Korea data, PM 2.5 concentrations were measured by the standard β-ray measurement method at 5 min intervals and then aggregated into hourly averages through statistical processing before being stored in a database [18]. This government-grade air monitoring station provides relatively accurate data but is expensive to run due to high installation and maintenance costs [19].…”