Rodes C E, Lawless P A, Evans G F, Sheldon L S, Williams R W, Vette A F, Creason J P, Walsh D
Research Triangle Institute, P.O. Box 12194, Research Triangle Park, North Carolina 27709, USA.
J Expo Anal Environ Epidemiol. 2001 Mar-Apr;11(2):103-15. doi: 10.1038/sj.jea.7500155.
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 micrograms/m3 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.
在三个退休中心环境中收集了个人暴露量、室内外浓度以及问卷调查数据，为更广泛的老年人群颗粒物（PM）与健康研究提供了支持。这些研究在地理和时间上存在差异，研究对象包括1998年夏季在马里兰州巴尔的摩以及1999年冬春季节在加利福尼亚州弗雷斯诺的人群。研究的连续性以及每一部分之后对质量浓度数据的相对快速审查，提供了修改实验设计的机会，包括从活动日记和基线问卷收集的信息以及对影响因素（如供暖、通风和空调（HVAC）系统运行、门窗开启、空气交换率）的测量。本文重点介绍了三个退休中心环境中的PM2.5和PM10个人暴露数据及其相互关系，并确定了最可能的影响因素。由于目前这些研究的问卷结果有限，且除质量浓度外的化学形态数据也有限，因此从模型估算个人暴露量以及将个人暴露量收集分配到其来源的能力也很有限。尽管涵盖了不同的设施类型和地理位置，但三个退休中心老年人的平均个人PM2.5暴露量始终比配对的公寓浓度高50%至68%。个人与室外的平均比值分别为0.70、0.82和1.10，似乎受到门窗开启时间以及HVAC系统强力去除颗粒物的影响。两项研究确定的计算得出的平均PM2.5个人云浓度基本相同，均为3微克/立方米。这些个人云的主要促成因素包括地毯扬起的颗粒物、人体皮屑和衣物纤维的聚集、个人靠近门窗以及非公寓室内微环境中升高的PM水平。
