Influences of wind and precipitation on different-sized particulate matter concentrations (PM2.5, PM10, PM2.5–10)

Zhang, Boen; Jiao, Limin; Xu, Gang; Zhao, Shenghui; Tang, Xin; Zhou, Yue; Gong, Chen

doi:10.1007/s00703-017-0526-9

Cited by 111 publications

(64 citation statements)

References 42 publications

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“…Previous study showed that the scavenging efficiency of urban aerosol is higher than that of rural, remote continental, and marine aerosol, especially remote continental and marine aerosol (Mircea et al, ). Dong et al () and B. Zhang, Jiao, et al () showed that the efficiency of precipitation scavenging to PM 2.5‐10 was more than twice as that to PM 2.5 . The precipitation amount also shows a great influence on scavenging efficiency (Han et al, ; Luan et al, ; Mircea et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing

Sun

Zhao

et al. 2019

Earth and Space Science

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Using hourly observation data of precipitation and PM2.5 at 12 sites in Beijing from 2015 to 2017, this study investigates the impacts of different types of precipitation on PM2.5 mass concentration, along with the characteristics of precipitation and PM2.5. There were totally 91–123 precipitation events annually, 69.7–79.4% of which has precipitation amount less than 5 mm. By investigating the differences of PM2.5 mass concentration between 1 hr after and before the precipitation events, this study finds distinct impacts of different types of precipitation on PM2.5 mass concentration. For precipitation events with amount of 0.1–0.5 mm, PM2.5 mass concentration increased with precipitation amount with a rate of 0.85 μg/m3 per 0.1 mm. For precipitation events with amount of 0.5–10 mm, there was no clear relationship between precipitation amount and PM2.5 mass concentration. For precipitation events with amount larger than 10 mm, PM2.5 mass concentration decreased with precipitation amount with a rate of 0.17 μg/m3 per 1 mm. Further analysis shows that weak precipitation less than 10 mm increased PM10, and heavy precipitation larger than 10 mm decreased PM10. The aerosol amount also affects the response of PM2.5 to precipitation, with weak pollution prone to increase with precipitation and heavy pollution prone to decrease with precipitation. Likely mechanisms are discussed, which include the aerosol hygroscopic growth and gas‐particle conversion that increase aerosol amount and precipitation scavenging that decreases aerosol amount. Shortly, the mechanisms that increase (decrease) aerosol amount more probably dominate when precipitation is light (heavy).

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Section: Introductionmentioning

confidence: 99%

“…Moreover, wind speed has different impacts on fine and coarse particles. It was shown that the fine PM concentrations decreased gradually with the increase of wind speed, while coarse PM concentrations would increase due to dust resuspension under strong winds (X. Li, Feng, et al, ; B. Zhang, Jiao, et al, ; Zhou et al, ).…”

Section: Introductionmentioning

confidence: 99%

Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing

Sun

Zhao

et al. 2019

Earth and Space Science

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“…In addition, the effects of wind are complex and can take many different forms. For example, weak/calm wind (i.e., stagnation) can lead to the local trapping and accumulation of pollution (Lv et al, 2017), whereas high-speed wind may favor PM resuspension and thus increase coarse PM concentrations (Zhang et al, 2018a) or quickly disperse local air pollutants (Gietl and Klemm, 2009). Furthermore, wind from different directions can introduce cleaner or more polluted air masses (Wang et al, 2017).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Influences of a Quasi-stationary Front on Particulate Matter in the Low-latitude Plateau Region in China

Fan

Li³

et al. 2021

Aerosol Air Qual. Res.

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A comprehensive assessment of the main pollution characteristics of particulate matter (PM) in the low-latitude plateau (LoLaP) region in China by utilizing observation and reanalysis data and statistical methods is presented to reveal influences of the Kunming quasi-stationary front (KMQSF) on PM concentration in LoLaP in winter. It is found that the location and intensity of the KMQSF significantly influenced the distribution pattern of PM and induced high concentrations in some areas in LoLaP region in a typical pollution event in 2016. Furthermore, all the KMQSF synoptic weathers over LoLaP region from 2014-2019 were investigated and classified into 9 Patterns, which led to different air pollution patterns in LoLaP region. When the KMQSF moved westward from middle LoLaP, the PM could be transported to west part of LoLaP by the easterly wind, which led to the daily mean PM10 and PM2.5 concentrations increase in Kunming, a central city in the west part of LoLaP, at the same time, high concentrations of PM10 and PM2.5 maintained in Guiyang, a central city locating in the east part of LoLaP. When the KMQSF gradually retreated from west part of LoLaP to east part, the PM in Kunming decreased with a strengthening of the westerly, and the PM in Guiyang further increased with a decrease of the planetary boundary layer (PBL) height and boundary layer dissipation (BLD). When the KMQSF disappeared, the formation of calm inversion pollution could be caused, including a shallow PBL and weak BLD in whole LoLaP, which induced the highest daily mean PM10 and PM2.5 concentrations both in the two central cities in all patterns.

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“…The effects of different parameters on the data accuracy of PM concentrations were approached in several papers. The influence of wind and precipitation on different-sized particulate matter concentrations were investigated in paper [16], showing that the effects of atmospheric conditions differ, depending on the size of the particulate matter. The increase in wind speed can decrease the concentrations of fine PM, while decreasing the concentrations of coarse PMs.…”

Section: Related Workmentioning

confidence: 99%

An Algorithm to Improve Data Accuracy of PMs Concentration Measured with IoT Devices

Bălănescu¹,

Suciu²,

Dobrea³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Air pollution is responsible for increased morbidity and mortality due to respiratory problems mainly caused by long term exposure. Although the emissions of principal air pollutants are highly regulated, there is a lack of information about the real extent of personal exposure for an accurate health impact assessment. To tackle these challenges, local air pollution measurements and citizen involvement based on the small IoT devices became necessary. The Tel-MonAer platform is based on IoT devices and Edge/Cloud computing technologies and allows the (near) real-time monitoring of Particulate Matter air pollutants considering the complex chemistry and influence of various parameters (i.e. air humidity, wind speed, temperature). The aim of this paper is the assessment of the influence that air humidity has on the PM concentrations measured with IoT devices based on laser beam technologies. The results showed that in order to increase the accuracy of PM concentrations values a threshold value for relative humidity of 80% needs to be considered. When humidity values are below 80%, the PM concentration values are considered valid, while for values over the threshold, a specific correction algorithm needs to be applied. This paper presents the correction algorithm (based on the type of sensor and humidity) and the testing results (an increase of at least 2.5 times of the correlation coefficient between the corrected and reference values).

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Influences of wind and precipitation on different-sized particulate matter concentrations (PM2.5, PM10, PM2.5–10)

Cited by 111 publications

References 42 publications

Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing

Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing

Influences of a Quasi-stationary Front on Particulate Matter in the Low-latitude Plateau Region in China

An Algorithm to Improve Data Accuracy of PMs Concentration Measured with IoT Devices

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Influences of wind and precipitation on different-sized particulate matter concentrations (PM2.5, PM10, PM2.5–10)

Cited by 111 publications

References 42 publications

Distinct Impacts of Light and Heavy Precipitation on PM2.5 Mass Concentration in Beijing

Distinct Impacts of Light and Heavy Precipitation on PM2.5 Mass Concentration in Beijing

Influences of a Quasi-stationary Front on Particulate Matter in the Low-latitude Plateau Region in China

An Algorithm to Improve Data Accuracy of PMs Concentration Measured with IoT Devices

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Product

Resources

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Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing

Distinct Impacts of Light and Heavy Precipitation on PM_2.5 Mass Concentration in Beijing