Properties of the mixing layer height retrieved from ceilometer measurements in Slovakia and its relationship to the air pollutant concentrations

被引:0
作者
Duy-Hieu Nguyen
Dušan Štefánik
Tereza Šedivá
Chitsan Lin
机构
[1] National Kaohsiung University of Science and Technology,Ph.D. Program in Maritime Science and Technology, College of Maritime
[2] Slovak Hydrometeorological Institute,Faculty of Mathematics, Physics and Informatics
[3] Comenius University in Bratislava,Department of Marine Environmental Engineering
[4] National Kaohsiung University of Science and Technology,undefined
来源
Environmental Science and Pollution Research | 2023年 / 30卷
关键词
Atmospheric boundary layer; Ceilometer measurements; Correlation analysis; Diurnal variation; Mixing layer height;
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学科分类号
摘要
Mixing layer height (MLH) is an important meteorological parameter for air quality since it significantly affects ground-level pollution in the atmosphere. This study examined the properties of the MLH on diurnal and seasonal timescales over a 3-year period (2020–2022) using high temporal resolution measurements from eight Vaisala CL31 ceilometers situated around Slovakia. Hourly averaged MLH data was retrieved from the BL-View software using merged method. The highest daily maxima for the MLH occurred mostly in summer and spring, while the lowest values occurred predominantly during winter and autumn. The average MLH daily maximum in summer was 2229 m, and just 859 m in winter. During summer, the spatial distribution of the MLH daily maxima was more uniform compared to winter, when the air masses within the individual valleys did not mix well. Correlations between ground-level pollutant concentrations and hourly mean/daily mean MLH were analyzed. The highest correlation, R≈0.6, was found for O3. For PM10, PM2.5, and NOx, the anticorrelations with MLH were found with maximum in winter (R ≈ − 0.3 for hourly data and R ≈ − 0.5 for daily mean data) but no relation in summer. Lastly, the ceilometer MLH was compared to the radiosonde retrieved MLH for various cloud covers. Our analysis is based on an extensive set of empirical data, which can improve the accuracy and effectiveness of meteorological and atmospheric chemistry models. The findings can support air pollution forecasting and warning systems, providing valuable insights for policymakers and researchers.
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页码:115666 / 115682
页数:16
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