通过透明数据生成过程分类推进独立空气质量传感器测量的框架

IF 8.4 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

npj Climate and Atmospheric Science Pub Date : 2025-07-29 DOI:10.1038/s41612-025-01161-2

Sebastian Diez, Thomas J. Bannan, Miriam Chacón-Mateos, Pete M. Edwards, Valerio Ferracci, Doğuşhan Kılıç, Alastair C. Lewis, Carl Malings, Nicholas A. Martin, Olalekan Popoola, Colleen Rosales, Sean Schmitz, Philipp Schneider, Erika von Schneidemesser

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引用次数: 0

摘要

我们提出了空气质量传感器衍生数据的操作定义和分类框架，从而帮助用户解释和选择适合其应用的数据产品。我们专注于区分独立传感器测量（ISM）与其他数据产品，强调透明度和可追溯性。为制造商、学术界和标准化机构提供了采用这些定义的建议，促进数据产品的差异化，并激励开发更强大、更可靠的传感器硬件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A framework for advancing independent air quality sensor measurements via transparent data generating process classification

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A framework for advancing independent air quality sensor measurements via transparent data generating process classification

We propose operational definitions and a classification framework for air quality sensor-derived data, thereby aiding users in interpreting and selecting suitable data products for their applications. We focus on differentiating independent sensor measurements (ISM) from other data products, emphasizing transparency and traceability. Recommendations are provided for manufacturers, academia, and standardization bodies to adopt these definitions, fostering data product differentiation and incentivizing the development of more robust, reliable sensor hardware.

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来源期刊

npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science

CiteScore

8.80

自引率

3.30%

发文量

审稿时长

21 weeks

期刊介绍： npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.