Abstract
Over urban areas in Hungary, the annual average PM10 concentrations are not frequently higher than 40 µg m–3. Despite the mitigation efforts of the local governments, the annual number of exceedances of the daily limit of 50 µg m–3 is higher than what is outlined in EU Directive No 2008/50/EC. The goal of the present study is to assess the characteristics of the temporal (annual, seasonal, daily) variations in PM10 concentrations in selected Hungarian cities with large populations, where most of the exceedances have been reported. The impacts of meteorological conditions on the measured PM10 concentrations and their temporal variations are also evaluated. An important aspect of studying the trends of air pollution is that the tendencies depend not only on the emissions of certain pollutants but also on the meteorological conditions in the area of interest. To analyse emission-related trends, the meteorological signal must be removed from the data series. In this study, the Kolmogorov-Zurbenko (KZ) filter was used for this type of trend separation. Moreover, multiple nonlinear regression analysis was used to find relationships between the PM10 concentration and several meteorological parameters. The goal of this analysis is to estimate the expected daily mean PM10 concentration values. The results of this analysis demonstrate that the regression equation can provide an adequate method for PM pollution forecasting. In addition to the hourly PM10 concentrations and basic meteorological data, global radiation and boundary layer height were considered in the characterization process.
Highlights
Publisher: Taiwan Association for Aerosol Research ISSN: 1680-8584 print ISSN: 2071-1409 onlineCopyright: The Author(s)
We can conclude that the PM10 values are generally the highest in Miskolc and lowest in Pécs, while Budapest is characterized by an intermediate level of air pollution
Hungary was part of both events that had an effect on the annual average PM10 concentrations in 2017
Summary
Particulate matter (PM) is one of the most critical atmospheric pollutants since it has negative impacts on human health and on environmental issues such as visibility, infrastructure, and ecosystems (Horvath, 1995; Lim et al, 2012; Fang et al, 2013; Kuzmichev and Loboyko, 2016; Tidblad et al, 2017; De Marco et al, 2019). It is a challenge to reduce PM emissions (EU Directive, 2016) and the associated risks to human health from exposure to PM. A better understanding of the status of and trends in air quality in Europe is crucial to support European, national, and regional governments in policy-making and implementation, as well as to improve the tools of air quality assessment and management (Guerreiro et al, 2014)
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