Analysis of the Temporal Distribution Characteristics of PM2.5 Concentration and Risk Evaluation of Its Inhalation Exposure.

Abstract

PM2.5 poses a threat to human health. It is important to evaluate the potential risk of PM2.5 inhalation exposure when people are located in different spatiotemporal activity locations. In this study, the PM2.5 concentration was detected by the atmospheric cruise monitoring system (ACMS), a new detection technology used for city-wide PM2.5 concentration monitoring. People were divided into eight categories of five typical activity patterns, including rest (R), sedentary behavior (SB), light physical activity (LPA), moderate physical activity (MPA), and vigorous physical activity (VPA). The PM2.5 inhalation exposure risk was then estimated for these typical activities. The research results showed that the time sequence data of the ACMS had a similar tendency to change as those of the traditional air quality monitoring stations (AQMS). Although both passed the stationarity test, the relative error (RE) of the monthly average PM2.5 concentration between the ACMS and AQMS was 7.5-14%. RE was usually lower when the individual air quality index (IAQI) of PM2.5 was higher. Otherwise, RE was higher. The research results also showed that PM2.5 exposure was positively correlated with PM2.5 concentration, respiration rate, and human activity patterns. Because adults had a higher monthly average potential exposure (MAPE) than minors and that males had a higher MAPE than females. The potential exposure generated by LPA and MPA reached 50.76% of the total potential exposure (TPE). VPA brought about a 14.7% increase in the TPE. The research findings are helpful to understand the temporal distribution characteristics of PM2.5 concentrations and guide the potential risk evaluation of PM2.5 inhalation exposure.