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Quantifying Influences of Nocturnal Mixing on Air Quality Using an Atmospheric Radon Measurement Case Study in the City of Jinhua, China

Category: Urban Air Quality

Volume: 20 | Issue: 3 | Pages: 620-629
DOI: 10.4209/aaqr.2019.10.0506
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To cite this article:
Wang, F., Zhang, Z., Chambers, S.D., Tian, X., Zhu, R., Mei, M., Huang, Z. and Allegrini, I. (2020). Quantifying Influences of Nocturnal Mixing on Air Quality Using an Atmospheric Radon Measurement Case Study in the City of Jinhua, China. Aerosol Air Qual. Res. 20: 620-629. doi: 10.4209/aaqr.2019.10.0506.

Fenjuan Wang 1,2, Zhenyi Zhang 3, Scott D. Chambers4, Xudong Tian5, Rong Zhu1, Mei Mei1, Zhaokai Huang6, Ivo Allegrini7

  • 1 National Climate Center, China Meteorological Administration, Beijing 100081, China
  • 2 National Institute for Environmental Studies (NIES), Tsukuba, Ibaraki 305-8506, Japan
  • 3 Tsinghua University, Beijing 100084, China
  • 4 Environmental Research, ANSTO, NSW 2232, Australia
  • 5 Hangzhou Environmental Monitoring Center Station, Hangzhou, 310007, China
  • 6 Shanghai BO Monitor Environmental Technical Co., Ltd., Shanghai 200040, China
  • 7 Envint S.r.l, Montopoli di Sabina 02434, Italy

Highlights

  • Atmospheric self-cleaning ability index is corroborated by radon measurement.
  • Four-category atmospheric stability was classified using radon measurement.
  • Radon-based stability serves to screening unfavorable air quality conditions.
  • An ASI-based model is proposed to predict regional severe air pollution.

Abstract

The atmospheric mixing state and emission rates play decisive roles in public exposure to urban air pollution. This study utilizes atmospheric radon measurements taken with the SM200 “stability monitor,” which reflect changes in the atmospheric mixing state, to evaluate and forecast air quality. Using six months (March–August 2016) of atmospheric radon measurements in Jinhua, China, we classify the nocturnal atmospheric stability conditions into four distinct categories, “well-mixed”, “weakly stable”, “moderately stable”, and “most stable”, by applying a modified radon-based stability technique. We calculate the atmospheric self-cleaning ability index (ASI) and evaluate it with the four-category stability scheme, and the results confirm that the atmospheric radon measurements reliably represent the atmospheric mixing state. Analyzing PM2.5, PM10, SO2, NO2, CO, and O3 measurements from three nearby stations during the campaign, we find that the pollutant concentrations and air quality index (AQI) values assigned using the aforementioned stability scheme are consistent with the defined atmospheric mixing states. We subsequently demonstrate that the modified radon-based stability method is suitable for targeting the most unfavorable air quality conditions and determining where the emissions originated. Finally, we propose a simple ASI-based model for predicting regional severe air pollution.

Keywords

Nocturnal mixing state Atmospheric radon measurement Atmospheric self-cleaning ability Air quality prediction


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Accepted Manuscripts
DOI: 10.4209/aaqr.2019.10.0496
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