From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey
Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learni...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/4/1320 |
| _version_ | 1797296991267454976 |
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| author | Tugce Pekdogan Mihaela Tinca Udriștioiu Hasan Yildizhan Arman Ameen |
| author_facet | Tugce Pekdogan Mihaela Tinca Udriștioiu Hasan Yildizhan Arman Ameen |
| author_sort | Tugce Pekdogan |
| collection | DOAJ |
| description | Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM<sub>1</sub>, PM<sub>2.5</sub>, PM<sub>10</sub>) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from −0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (−0.241 in Romania and −0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality. |
| first_indexed | 2024-03-07T22:13:49Z |
| format | Article |
| id | doaj.art-354b0b707959412e85376a498a76f67c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-07T22:13:49Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-354b0b707959412e85376a498a76f67c2024-02-23T15:34:10ZengMDPI AGSensors1424-82202024-02-01244132010.3390/s24041320From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and TurkeyTugce Pekdogan0Mihaela Tinca Udriștioiu1Hasan Yildizhan2Arman Ameen3Department of Architecture, Faculty of Architecture and Design, Adana Alparslan Türkeş Science and Technology University, Adana 46278, TurkeyDepartment of Physics, Faculty of Sciences, University of Craiova, 200585 Craiova, RomaniaDepartment of Energy Systems Engineering, Adana Alparslan Türkeş Science and Technology University, Adana 46278, TurkeyDepartment of Building Engineering, Energy Systems and Sustainability Science, University of Gävle, 801 76 Gävle, SwedenAir pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM<sub>1</sub>, PM<sub>2.5</sub>, PM<sub>10</sub>) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from −0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (−0.241 in Romania and −0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality.https://www.mdpi.com/1424-8220/24/4/1320air pollutionstatistical analysismonitoringPM sensorsecosystems |
| spellingShingle | Tugce Pekdogan Mihaela Tinca Udriștioiu Hasan Yildizhan Arman Ameen From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey Sensors air pollution statistical analysis monitoring PM sensors ecosystems |
| title | From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey |
| title_full | From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey |
| title_fullStr | From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey |
| title_full_unstemmed | From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey |
| title_short | From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey |
| title_sort | from local issues to global impacts evidence of air pollution for romania and turkey |
| topic | air pollution statistical analysis monitoring PM sensors ecosystems |
| url | https://www.mdpi.com/1424-8220/24/4/1320 |
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