Abstract
The PM(2.5) exposure risk assessment is the foundation to reduce its adverse effects. Population survey-related data have been deficient in high spatiotemporal detailed descriptions. Social media data can quantify the PM(2.5) exposure risk at high spatiotemporal resolutions. However, due to the no-sample characteristics of social media data, PM(2.5) exposure risk for older adults is absent. We proposed combining social media data and population survey-derived data to map the total PM(2.5) exposure risk. Hourly exceedance PM(2.5) exposure risk indicators based on population modeling (HEPE(pmd)) and social media data (HEPE(sm)) were developed. Daily accumulative HEPE(sm) and HEPE(psd) ranged from 0 to 0.009 and 0 to 0.026, respectively. Three peaks of HEPE(sm) and HEPE(psd) were observed at 13:00, 18:00, and 22:00. The peak value of HEPE(sm) increased with time, which exhibited a reverse trend to HEPE(psd). The spatial center of HEPE(sm) moved from the northwest of the study area to the center. The spatial center of HEPE(psd) moved from the northwest of the study area to the southwest of the study area. The expansion area of HEPE(sm) was nearly 1.5 times larger than that of HEPE(psd). The expansion areas of HEPE(psd) aggregated in the old downtown, in which the contribution of HEPE(psd) was greater than 90%. Thus, this study introduced various source data to build an easier and reliable method to map total exceedance PM(2.5) exposure risk. Consequently, exposure risk results provided foundations to develop PM(2.5) pollution mitigation strategies as well as scientific supports for sustainability and eco-health achievement.