Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, 70569 Stuttgart, Germany.
Institute of Physics and Meteorology, University of Hohenheim, 70599 Stuttgart, Germany.
Sensors (Basel). 2024 Sep 5;24(17):5767. doi: 10.3390/s24175767.
Recent advances in sensor technology for air pollution monitoring open new possibilities in the field of environmental epidemiology. The low spatial resolution of fixed outdoor measurement stations and modelling uncertainties currently limit the understanding of personal exposure. In this context, air quality sensor systems (AQSSs) offer significant potential to enhance personal exposure assessment. A pilot study was conducted to investigate the feasibility of the NO sensor model B43F and the particulate matter (PM) sensor model OPC-R1, both from Alphasense (UK), for use in epidemiological studies. Seven patients with chronic obstructive pulmonary disease (COPD) or asthma had built-for-purpose sensor systems placed inside and outside of their homes at fixed locations for one month. Participants documented their indoor activities, presence in the house, window status, and symptom severity and performed a peak expiratory flow test. The potential inhaled doses of PM and NO were calculated using different data sources such as outdoor data from air quality monitoring stations, indoor data from AQSSs, and generic inhalation rates (IR) or activity-specific IR. Moreover, the relation between indoor and outdoor air quality obtained with AQSSs, an indoor source apportionment study, and an evaluation of the suitability of the AQSS data for studying the relationship between air quality and health were investigated. The results highlight the value of the sensor data and the importance of monitoring indoor air quality and activity patterns to avoid exposure misclassification. The use of AQSSs at fixed locations shows promise for larger-scale and/or long-term epidemiological studies.
近年来，用于空气污染监测的传感器技术的进步为环境流行病学领域开辟了新的可能性。固定户外测量站的空间分辨率低和建模不确定性目前限制了对个人暴露的理解。在这种情况下，空气质量传感器系统 (AQSS) 为增强个人暴露评估提供了巨大的潜力。进行了一项试点研究，以调查来自英国 Alphasense 的 NO 传感器模型 B43F 和颗粒物 (PM) 传感器模型 OPC-R1 在流行病学研究中使用的可行性。七名患有慢性阻塞性肺疾病 (COPD) 或哮喘的患者将专门为他们设计的传感器系统放置在他们的家和户外固定位置一个月。参与者记录他们的室内活动、在室内的存在、窗户状态和症状严重程度，并进行了最大呼气流量测试。使用不同的数据源（例如空气质量监测站的室外数据、AQSS 的室内数据以及通用吸入率 (IR) 或特定活动的 IR）计算 PM 和 NO 的潜在吸入剂量。此外，还研究了使用 AQSS 获得的室内和室外空气质量之间的关系、室内源分配研究以及 AQSS 数据是否适合研究空气质量与健康之间的关系。结果强调了传感器数据的价值，以及监测室内空气质量和活动模式以避免暴露分类错误的重要性。在固定位置使用 AQSS 显示出在更大规模和/或长期流行病学研究中的潜力。
