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2
Assessing residential PM concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors.利用众包传感器以高时空分辨率评估住宅 PM 浓度和渗透因子。
Proc Natl Acad Sci U S A. 2023 Dec 12;120(50):e2308832120. doi: 10.1073/pnas.2308832120. Epub 2023 Dec 4.
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Evaluating the Performance of Low-Cost PM Sensors in Mobile Settings.评估低成本颗粒物传感器在移动环境中的性能。
Environ Sci Technol. 2023 Oct 17;57(41):15401-15411. doi: 10.1021/acs.est.3c04843. Epub 2023 Oct 3.
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Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis.移动环境空气质量监测的关键主题、趋势和驱动因素:系统评价和荟萃分析。
Environ Sci Technol. 2023 Jul 4;57(26):9427-9444. doi: 10.1021/acs.est.2c06310. Epub 2023 Jun 21.
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Identifying optimal co-location calibration periods for low-cost sensors.确定低成本传感器的最佳共置校准周期。
Atmos Meas Tech. 2023;16(1):169-179. doi: 10.5194/amt-16-169-2023. Epub 2023 Jan 13.
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An analysis of degradation in low-cost particulate matter sensors.低成本颗粒物传感器的降解分析。
Environ Sci Atmos. 2023 Feb 3;3:521-536. doi: 10.1039/d2ea00142j.
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空气质量传感器专家齐聚:可信数据的当前质量保证考量

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

作者信息

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

机构信息

United States Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711, United States.

United States Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina 27711, United States.

出版信息

ACS EST Air. 2024 Sep 17;1(10):1203-1214. doi: 10.1021/acsestair.4c00125.

DOI:10.1021/acsestair.4c00125
PMID:39502563
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11534011/
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.

摘要

空气传感器可以提供有价值的非监管和补充数据,因为它们可以以较低的成本大量部署,并安置在远离监管空气监测站的偏远地区。空气传感器存在一些固有局限性,在收集和解释数据之前必须了解这些局限性。其中许多局限性本质上是机械性的,这需要技术进步。然而,有一些已记录在案的质量保证(QA)方法可以提高数据质量。这些方法包括实验室和现场评估以定量评估性能、应用校正以提高精度和准确性,以及对已部署空气质量传感器的状态或健康状况进行主动管理。本文总结了利益相关者(如制造商、研究人员、空气机构)在美国环境保护局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,并确定了最紧迫的需求。这些需求包括QA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的文档记录。使用空气传感器的社区成员需要培训和资源、及时的数据、可获取的QA方法,以及与其他利益相关者分担责任。除了确定至关重要的下一步措施外,这项工作还提供了一套旨在改进和统一空气传感器QA的常见QA和QC行动,这将使不同领域和专业水平的利益相关者能够有效地利用空气传感器数据来保护人类健康。