Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments
Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments
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DOI：
10.5194/amt-12-4643-2019
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发表时间：
2019-08-30
影响因子：
3.8
通讯作者：
Jones, Roderic L.
中科院分区：
文献类型：
--
作者：
Chatzidiakou, Lia;Krause, Anika;Jones, Roderic L.
对个人暴露于空气污染的不准确量化导致健康估计出现误差和偏差，严重限制了全世界流行病学研究的因果推断。经济实惠的小型化空气污染传感器技术的快速发展为解决这一限制提供了潜力，通过在前所未有的空间和时间分辨率的大规模研究中捕捉日常生活中个人暴露的高度可变性。然而，新的传感技术是否适合科学和政策目的仍然令人关切。在本文中，我们描述了便携式个人空气质量监测仪（PAM）的性能，该监测仪集成了多个微型传感器，用于测量氮氧化物（NOx）、一氧化碳（CO）、臭氧（O-3）和颗粒物（PM），以及温度、相对湿度、加速度、噪声和GPS传感器。总体而言，空气污染传感器在不同季节和不同地理环境的室外、室内和通勤微环境中表现出较高的再现性(平均（R)优于柱状图(2)= 0.93,min-max: 0.80-1.00），与标准仪器(平均（R)优于柱状图(2)= 0.82,min-max: 0.54-0.99）。本研究的一个重要结果是，PAM的误差明显小于基于稀疏分布的室外固定监测站估算个人暴露时引入的误差。因此，这里展示的新型传感技术可以通过提供大规模高分辨率可靠的暴露度量来调查空气污染对健康影响的潜在机制，从而彻底改变健康研究。
The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NOx), carbon monoxide (CO), ozone (O-3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (mean (R) over bar (2) = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (mean (R) over bar (2) = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.