Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data.

Karoline K Barkjohn, Andrea Clements, Corey Mocka, Colin Barrette, Ashley Bittner, Wyatt Champion, Brett Gantt, Elizabeth Good, Amara Holder, Berkley Hillis, Matthew S Landis, Menaka Kumar, Megan MacDonald, Eben Thoma, Tim Dye, Jan-Michael Archer, Michael Bergin, Wilton Mui, Brandon Feenstra, Michael Ogletree, Christi Chester-Schroeder, Naomi Zimmerman
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Abstract

Air sensors can provide valuable non-regulatory and supplemental data as they can be affordably deployed in large numbers and stationed in remote areas far away from regulatory air monitoring stations. Air sensors have inherent limitations that are critical to understand before collecting and interpreting the data. Many of these limitations are mechanistic in nature, which will require technological advances. However, there are documented quality assurance (QA) methods to promote data quality. These include laboratory and field evaluation to quantitatively assess performance, the application of corrections to improve precision and accuracy, and active management of the condition or state of health of deployed air quality sensors. This paper summarizes perspectives presented at the U.S. Environmental Protection Agency's 2023 Air Sensors Quality Assurance Workshop (https://www.epa.gov/air-sensor-toolbox/quality-assurance-air-sensors#QAworkshop) by stakeholders (e.g., manufacturers, researchers, air agencies) and identifies the most pressing needs. These include QA protocols, streamlined data processing, improved total volatile organic compound (TVOC) data interpretation, development of speciated VOC sensors, and increased documentation of hardware and data handling. Community members using air sensors need training and resources, timely data, accessible QA approaches, and shared responsibility with other stakeholders. In addition to identifying the vital next steps, this work provides a set of common QA and QC actions aimed at improving and homogenizing air sensor QA that will allow stakeholders with varying fields and levels of expertise to effectively leverage air sensor data to protect human health.

空气质量传感器专家会议:可信数据的当前质量保证考虑因素。
空气传感器可以提供宝贵的非监管数据和补充数据,因为它们可以以经济实惠的方式大量部署,并驻扎在远离监管空气监测站的偏远地区。空气传感器有其固有的局限性,在收集和解释数据之前了解这些局限性至关重要。其中许多局限性属于机械性质,需要技术进步。不过,目前已有成文的质量保证 (QA) 方法来提高数据质量。这些方法包括对性能进行定量评估的实验室和实地评估、应用校正以提高精度和准确性,以及对部署的空气质量传感器的状态或健康状况进行积极管理。本文总结了利益相关者(如制造商、研究人员、空气机构)在美国环保署 2023 年空气传感器质量保证研讨会 (https://www.epa.gov/air-sensor-toolbox/quality-assurance-air-sensors#QAworkshop) 上提出的观点,并确定了最迫切的需求。这些需求包括质量保证协议、简化数据处理、改进总挥发性有机化合物 (TVOC) 数据解释、开发特定挥发性有机化合物传感器以及增加硬件和数据处理文档。使用空气传感器的社区成员需要培训和资源、及时的数据、可用的质量保证方法以及与其他利益相关者共同承担责任。除了确定重要的下一步措施外,这项工作还提供了一套通用的质量保证和质量控制措施,旨在改进和统一空气传感器质量保证,使具有不同领域和专业水平的利益相关者能够有效利用空气传感器数据来保护人类健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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