Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters
Surface ozone is usually measured in national networks, including the monitoring of gaseous components important for determining air quality and the short-term forecast of surface ozone. Here we consider the option of forecasting surface ozone based on measurements of only surface ozone and several...
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| Format: | Article |
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MDPI AG
2023-03-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/14/4/670 |
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| author | Izabela Pawlak Alnilam Fernandes Janusz Jarosławski Krzysztof Klejnowski Aleksander Pietruczuk |
| author_facet | Izabela Pawlak Alnilam Fernandes Janusz Jarosławski Krzysztof Klejnowski Aleksander Pietruczuk |
| author_sort | Izabela Pawlak |
| collection | DOAJ |
| description | Surface ozone is usually measured in national networks, including the monitoring of gaseous components important for determining air quality and the short-term forecast of surface ozone. Here we consider the option of forecasting surface ozone based on measurements of only surface ozone and several weather parameters. This low-cost configuration can increase the number of locations that provide short-term surface ozone forecast important to local communities. 24 h prediction of the 1-h averaged concentration of surface ozone were presented for rural (Belsk, 20.79° E, 51.84° N) and suburban site (Racibórz, 18.19° E, 50.08° N) in Poland for the period 2018–2021 via simple statistical models dealing with a limited number of predictors. Multiple linear regression (MLR) and artificial neural network (ANN) models were examined separately for each season of the year using temperature, relative humidity, an hour of the day, and 1-day lagged surface ozone values. The performance of ANN (with R<sup>2</sup> = 0.81 in Racibórz versus R<sup>2</sup> = 0.75 at Belsk) was slightly better than the MLR model (with R<sup>2</sup> = 0.78 in Racibórz versus R<sup>2</sup> = 0.71 at Belsk). These statistical models were compared with advanced chemical–transport models provided by the Copernicus Atmosphere Monitoring Service. Despite the simplicity of the statistical models, they showed better performance in all seasons, with the exception of winter. |
| first_indexed | 2024-03-11T05:14:57Z |
| format | Article |
| id | doaj.art-5f49434701de4a5b9117de2782abbb49 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T05:14:57Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-5f49434701de4a5b9117de2782abbb492023-11-17T18:17:08ZengMDPI AGAtmosphere2073-44332023-03-0114467010.3390/atmos14040670Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input ParametersIzabela Pawlak0Alnilam Fernandes1Janusz Jarosławski2Krzysztof Klejnowski3Aleksander Pietruczuk4Institute of Geophysics, Polish Academy of Sciences, 01-452 Warszawa, PolandInstitute of Geophysics, Polish Academy of Sciences, 01-452 Warszawa, PolandInstitute of Geophysics, Polish Academy of Sciences, 01-452 Warszawa, PolandInstitute of Environmental Engineering, Polish Academy of Sciences, 41-819 Zabrze, PolandInstitute of Geophysics, Polish Academy of Sciences, 01-452 Warszawa, PolandSurface ozone is usually measured in national networks, including the monitoring of gaseous components important for determining air quality and the short-term forecast of surface ozone. Here we consider the option of forecasting surface ozone based on measurements of only surface ozone and several weather parameters. This low-cost configuration can increase the number of locations that provide short-term surface ozone forecast important to local communities. 24 h prediction of the 1-h averaged concentration of surface ozone were presented for rural (Belsk, 20.79° E, 51.84° N) and suburban site (Racibórz, 18.19° E, 50.08° N) in Poland for the period 2018–2021 via simple statistical models dealing with a limited number of predictors. Multiple linear regression (MLR) and artificial neural network (ANN) models were examined separately for each season of the year using temperature, relative humidity, an hour of the day, and 1-day lagged surface ozone values. The performance of ANN (with R<sup>2</sup> = 0.81 in Racibórz versus R<sup>2</sup> = 0.75 at Belsk) was slightly better than the MLR model (with R<sup>2</sup> = 0.78 in Racibórz versus R<sup>2</sup> = 0.71 at Belsk). These statistical models were compared with advanced chemical–transport models provided by the Copernicus Atmosphere Monitoring Service. Despite the simplicity of the statistical models, they showed better performance in all seasons, with the exception of winter.https://www.mdpi.com/2073-4433/14/4/670surface ozoneforecaststatistical modelschemistry–transport modelsair quality |
| spellingShingle | Izabela Pawlak Alnilam Fernandes Janusz Jarosławski Krzysztof Klejnowski Aleksander Pietruczuk Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters Atmosphere surface ozone forecast statistical models chemistry–transport models air quality |
| title | Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters |
| title_full | Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters |
| title_fullStr | Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters |
| title_full_unstemmed | Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters |
| title_short | Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters |
| title_sort | comparison of 24 h surface ozone forecast for poland cams models vs simple statistical models with limited number of input parameters |
| topic | surface ozone forecast statistical models chemistry–transport models air quality |
| url | https://www.mdpi.com/2073-4433/14/4/670 |
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