The relationships between personal PM exposures for elderly populations and indoor and outdoor concentrations for three retirement center scenarios

Personal exposures, indoor and outdoor concentrations, and questionnaire data were collected in three retirement center settings, supporting broader particulate matter (PM) -health studies of elderly populations. The studies varied geographically and temporally, with populations studied in Baltimore, MD in the summer of 1998, and Fresno, CA in the winter and spring of 1999. The sequential nature of the studies and the relatively rapid review of the mass concentration data after each segment provided the opportunity to modify the experimental designs, including the information collected from activity diary and baseline questionnaires and influencing factors (e.g., heating, ventilation, and air-conditioning (HVAC) system operation, door and window openings, air exchange rate) measurements. This paper highlights both PM2.5 and PM10 personal exposure data and interrelationships across the three retirement center settings, and identifies the most probable influencing factors. The current limited availability of questionnaire results, and chemical speciation data beyond mass concentration for these studies, provided only limited capability to estimate personal exposures from models and apportion the personal exposure collections to their sources. The mean personal PM2.5 exposures for the elderly in three retirement centers were found to be consistently higher than the paired apartment concentrations by 50% to 68%, even though different facility types and geographic locations were represented. Mean personal - to - outdoor ratios were found to 0.70, 0.82, and 1.10, and appeared to be influenced by the time doors and windows were open and aggressive particle removal by the HVAC systems. Essentially identical computed mean PM2.5 personal clouds of 3 mug/m(3) were determined for two of the studies. The proposed significant contributing factors to these personal clouds were resuspended particles from carpeting, collection of body dander and clothing fibers, personal proximity to open doors and windows, and elevated PM levels in nonapartment indoor microenvironments.