Diez Sebastian, Lacy Stuart, Urquiza Josefina, Edwards Pete
Centro de Investigación en Tecnologías para la Sociedad, Universidad del Desarrollo, Santiago, CP, 7550000, Chile.
Wolfson Atmospheric Chemistry Laboratories, University of York, York, YO10 5DD, UK.
Sci Data. 2024 Aug 21;11(1):904. doi: 10.1038/s41597-024-03767-2.
The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO, O, CO, CO), particulate matter (PM, PM, PM), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors' data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset's utility and reliability.
QUANT研究是迄今为止对商业空气质量传感器系统进行的最广泛的开放获取评估。这项全面的研究在三年时间里,对英国三个城市地点的14家制造商生产的49个系统进行了评估。由此产生的开放获取数据集记录了多种气体(一氧化氮、二氧化氮、臭氧、一氧化碳、二氧化碳)、颗粒物(细颗粒物、可吸入颗粒物、粗颗粒物)以及关键气象参数(湿度、温度、大气压力)的高时间分辨率测量值。通过参考监测器的数据以及来自三个地点的传感器制造商的校准产品,该数据集的质量和范围得到了提升。这个可公开获取的数据集是一个强大且透明的资源,详细说明了数据收集所使用的方法以及确保数据集完整性的程序。它为广泛的利益相关者提供了一个有价值的工具,用于分析空气质量传感器在实际环境中的性能。政策制定者可以利用这些数据来完善传感器部署指南并制定标准化协议,而制造商可以将其用作技术创新和产品认证的基准。此外,该数据集为英国实践准则的制定提供了支持,并对其中一家参与公司进行了认证,凸显了该数据集的实用性和可靠性。