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  11. Multi-scenario Pm2.5 Distribution And Dynamic Exposure Assessment Of University Community Residents: Development And Application Of Intelligent Health Risk Management System Integrated Low-cost Sensors

Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors

Changhong Ou1, Fei Li1, Jingdong Zhang1

  • 1Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China.

Environment International
|March 9, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

A new Internet of Things (IoT) system, EnvironMax+, accurately assessed daily PM2.5 exposure in different scenarios. Residential settings were most significant, with closing windows impacting indoor air quality.

Area of Science:

  • Environmental Science
  • Public Health
  • Sensor Technology

Background:

  • Particulate Matter 2.5 (PM2.5) exposure is influenced by exposure scenarios and human behavior.
  • Accurate assessment of dynamic PM2.5 exposure is crucial for health management.
  • Existing methods may not fully capture real-time, multi-scenario exposures.

Purpose of the Study:

  • To develop and validate an Internet of Things (IoT) system, EnvironMax+, for assessing dynamic residential PM2.5 exposure.
  • To quantify PM2.5 concentrations across various exposure scenarios (residential, public, outdoor, catering) and resident groups.
  • To identify key behavioral factors influencing indoor PM2.5 contamination.

Main Methods:

  • Utilized low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models for real-time PM2.5 estimation.
Keywords:
Dynamic exposure riskExposure behavior investigationInternet of ThingsLow-cost sensors

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  • Integrated a mobile application (Air Health Management - AHM) for automatic collection of resident activity trajectories.
  • Employed questionnaires to investigate residents' indoor activity patterns and time-activity budgets.

    • Main Results:

    • The residential scenario accounted for approximately 60% of daily exposure time.
    • Closing windows was identified as the most significant factor affecting indoor PM2.5 levels.
    • Annual average PM2.5 concentrations followed the order: residential < public < outdoor < catering scenarios.
    • Outdoor PM2.5 concentrations were generally higher than indoor levels (5-10 μg/m³ difference) except in catering scenarios.
    • Population-weighted average exposure was 37.1 μg/m³, 78% of the outdoor average.
    • Exposure levels varied significantly among resident groups, with cooks experiencing the highest concentrations.

    Conclusions:

    • The developed IoT system effectively assesses multi-scenario PM2.5 exposure.
    • Residential exposure and specific behaviors like closing windows are critical determinants of overall exposure.
    • Understanding scenario-specific and group-specific exposures is vital for targeted air quality and health management strategies.
    PM2.5