Evaluation of Long-Term Performance of Six PM2.5 Sensor Types

Sensors, Год журнала: 2025, Номер 25(4), С. 1265 - 1265

Опубликована: Фев. 19, 2025

From July 2019 to January 2021, six models of PM2.5 air sensors were operated at seven quality monitoring sites across the U.S. in Arizona, Colorado, Delaware, Georgia, North Carolina, Oklahoma, and Wisconsin. Common PM sensor data issues identified, including repeat zero measurements, false high outliers, baseline shift, varied relationships between monitor, relative humidity (RH) influences. While these are often easy identify during colocation, they more challenging or correct deployment since it is hard differentiate real pollution events malfunctions. Air may exhibit wildly different performances even if have same similar internal components. Commonly used RH corrections still variable bias by hour day seasonally. Most show promise achieving Environmental Protection Agency (EPA) performance targets, findings here can be improve their reliability further. This evaluation generated a robust dataset colocated monitor data, making publicly available along with results presented this paper, we hope will an asset community understanding validating new methods.

Язык: Английский

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Influence of seasonal variation on spatial distribution of PM2.5 concentration using low-cost sensors

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 196(12)

Опубликована: Ноя. 21, 2024

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High-Accuracy Pm2.5 Retrieval Based on Satellite Remote Sensing and Hierarchical Machine Learning Model

Опубликована: Янв. 1, 2024

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Язык: Английский

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High-accuracy full-coverage PM _2.5 retrieval from 2014 to 2023 over China based on satellite remote sensing and hierarchical deep learning model

International Journal of Digital Earth, Год журнала: 2024, Номер 17(1)

Опубликована: Сен. 23, 2024

Язык: Английский

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