Bias detection of \(PM_{2.5}\) monitor readings using hidden dynamic geostatistical calibration model

Accurate and reliable data stream plays an important role in air quality assessment. Air pollution data collected from monitoring networks, however, could be biased due to instrumental error or other interventions, which covers up the real pollution status and misleads policy making. In this study,...

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Veröffentlicht in:	arXiv.org 2019-01
Hauptverfasser:	Wang, Yaqiong, Xu, Minya, Huang, Hui, Chen, Songxi
Format:	Artikel
Sprache:	eng
Schlagworte:	Air pollution Air quality Bias Calibration Data transmission Geostatistics Mathematical models Parameter estimation Pollution monitoring Quality assessment Stations Stream pollution
Online-Zugang:	Volltext
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