Long-term Characterization of Urban PM10 in Hungary
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/...
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| Format: | Article |
| Language: | English |
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Springer
2021-06-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.210048 |
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| author | Zita Ferenczi Kornélia Imre Mónika Lakatos Ágnes Molnár László Bozó Emese Homolya András Gelencsér |
| author_facet | Zita Ferenczi Kornélia Imre Mónika Lakatos Ágnes Molnár László Bozó Emese Homolya András Gelencsér |
| author_sort | Zita Ferenczi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-58204a86a2c44ea0926bc87a9269b4e2 |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-58204a86a2c44ea0926bc87a9269b4e22025-02-09T12:21:11ZengSpringerAerosol and Air Quality Research1680-85842071-14092021-06-01211011510.4209/aaqr.210048Long-term Characterization of Urban PM10 in HungaryZita Ferenczi0Kornélia Imre1Mónika Lakatos2Ágnes Molnár3László Bozó4Emese Homolya5András Gelencsér6Hungarian Meteorological ServiceELKH-PE Air Chemistry Research GroupHungarian Meteorological ServiceELKH-PE Air Chemistry Research GroupHungarian Meteorological ServiceHungarian Meteorological ServiceELKH-PE Air Chemistry Research GroupAbstract 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.https://doi.org/10.4209/aaqr.210048PM10Cold season episodeRegression analysisKolmogorov-Zurbenko (KZ) filter |
| spellingShingle | Zita Ferenczi Kornélia Imre Mónika Lakatos Ágnes Molnár László Bozó Emese Homolya András Gelencsér Long-term Characterization of Urban PM10 in Hungary Aerosol and Air Quality Research PM10 Cold season episode Regression analysis Kolmogorov-Zurbenko (KZ) filter |
| title | Long-term Characterization of Urban PM10 in Hungary |
| title_full | Long-term Characterization of Urban PM10 in Hungary |
| title_fullStr | Long-term Characterization of Urban PM10 in Hungary |
| title_full_unstemmed | Long-term Characterization of Urban PM10 in Hungary |
| title_short | Long-term Characterization of Urban PM10 in Hungary |
| title_sort | long term characterization of urban pm10 in hungary |
| topic | PM10 Cold season episode Regression analysis Kolmogorov-Zurbenko (KZ) filter |
| url | https://doi.org/10.4209/aaqr.210048 |
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