MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting
Air pollution is a significant global issue, being one of the leading causes of chronic diseases affecting the respiratory and neurological systems, and resulting in millions of deaths each year. Additionally, the scarcity of air quality sensors, due to their high cost, limits the availability of ac...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10908821/ |
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| author | Alejandra Abalo-Garcia Sergio Hernandez-Garcia Ivan Ramirez Emanuele Schiavi |
| author_facet | Alejandra Abalo-Garcia Sergio Hernandez-Garcia Ivan Ramirez Emanuele Schiavi |
| author_sort | Alejandra Abalo-Garcia |
| collection | DOAJ |
| description | Air pollution is a significant global issue, being one of the leading causes of chronic diseases affecting the respiratory and neurological systems, and resulting in millions of deaths each year. Additionally, the scarcity of air quality sensors, due to their high cost, limits the availability of accurate data. In this study, we present a dataset that combines air quality and meteorological variables, with data sourced from the historical records of the Community of Madrid. Furthermore, we propose several baseline methods for this dataset. We then validate these baseline methods using another reference dataset, outperforming previous state-of-the-art methods. All the code and data is available in <uri>https://github.com/capo-urjc/MPD.git</uri>. |
| format | Article |
| id | doaj-art-a298b08f504147e3bb50141ff643138d |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-a298b08f504147e3bb50141ff643138d2025-08-20T01:58:00ZengIEEEIEEE Access2169-35362025-01-0113412824129910.1109/ACCESS.2025.354703810908821MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution ForecastingAlejandra Abalo-Garcia0https://orcid.org/0009-0002-0100-0961Sergio Hernandez-Garcia1https://orcid.org/0000-0001-7254-9594Ivan Ramirez2https://orcid.org/0000-0001-5985-5271Emanuele Schiavi3https://orcid.org/0000-0002-2790-307XComputer Science and Statistics Department, Universidad Rey Juan Carlos, Madrid, SpainComputer Science and Statistics Department, Universidad Rey Juan Carlos, Madrid, SpainComputer Science and Statistics Department, Universidad Rey Juan Carlos, Madrid, SpainMaterials Science and Engineering and Electronic Technology Department, Applied Mathematics, Universidad Rey Juan Carlos, Madrid, SpainAir pollution is a significant global issue, being one of the leading causes of chronic diseases affecting the respiratory and neurological systems, and resulting in millions of deaths each year. Additionally, the scarcity of air quality sensors, due to their high cost, limits the availability of accurate data. In this study, we present a dataset that combines air quality and meteorological variables, with data sourced from the historical records of the Community of Madrid. Furthermore, we propose several baseline methods for this dataset. We then validate these baseline methods using another reference dataset, outperforming previous state-of-the-art methods. All the code and data is available in <uri>https://github.com/capo-urjc/MPD.git</uri>.https://ieeexplore.ieee.org/document/10908821/Air quality predictiondeep learningmachine learningneural networkspollution prediction |
| spellingShingle | Alejandra Abalo-Garcia Sergio Hernandez-Garcia Ivan Ramirez Emanuele Schiavi MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting IEEE Access Air quality prediction deep learning machine learning neural networks pollution prediction |
| title | MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting |
| title_full | MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting |
| title_fullStr | MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting |
| title_full_unstemmed | MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting |
| title_short | MPD: A Meteorological and Pollution Dataset: A Comprehensive Study of Machine and Deep Learning Methods for Air Pollution Forecasting |
| title_sort | mpd a meteorological and pollution dataset a comprehensive study of machine and deep learning methods for air pollution forecasting |
| topic | Air quality prediction deep learning machine learning neural networks pollution prediction |
| url | https://ieeexplore.ieee.org/document/10908821/ |
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