Future prediction of biogas potential and CH4 emission with boosting algorithms : the case of cattle, small ruminant, and poultry manure from Turkey
© 2024. The Author(s)..
Animal waste can be converted into a renewable energy source using biogas technology. This process has an impact on greenhouse gas emissions and is a sustainable source of energy for countries. It can reduce the effects of climate change and protect the planet for future generations. Tier1 and tier2 approaches are commonly used in the literature to calculate emissions factors. With boosting algorithms, this study estimated each animal category's biogas potential and CH4 emissions (tier1 and tier2 approach) for 2004-2021 in all of Turkey's provinces. Two different scenarios were created in the study. For scenario-1, the years 2020-2021 were predicted using data from 2004 to 2019, while for scenario-2, the years 2022-2024 were predicted using data from 2004 to 2021. According to the scenario-1 analysis, the eXtreme Gradient Boosting Regressor (XGBR) algorithm was the most successful algorithm with an R2 of 0.9883 for animal-based biogas prediction and 0.9835 and 0.9773 for animal-based CH4 emission predictions (tier1 and tier2 approaches) for the years 2020-2021. When the mean absolute percentage error was evaluated, it was found to be relatively low at 0.46%, 1.07%, and 2.78%, respectively. According to the scenario-2 analysis, the XGBR algorithm predicted the log10 values of the animal-based biogas potential of five major cities in Turkey for the year 2024, with 11.279 for Istanbul, 12.055 for Ankara, 12.309 for Izmir, 11.869 for Bursa, and 12.866 for Antalya. In the estimation of log10 values of CH4 emission, the tier1 approach yielded estimates of 3.080, 3.652, 3.929, 3.411, and 3.321, respectively, while the tier2 approach yielded estimates of 1.810, 2.806, 2.757, 2.552 and 2.122, respectively.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:31 |
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| Enthalten in: |
Environmental science and pollution research international - 31(2024), 16 vom: 05. Apr., Seite 24461-24479 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Pence, Ihsan [VerfasserIn] |
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| Links: |
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| Themen: |
Animal waste |
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| Anmerkungen: |
Date Completed 08.04.2024 Date Revised 17.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1007/s11356-024-32666-7 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © 2024. The Author(s). | ||
| 520 | |a Animal waste can be converted into a renewable energy source using biogas technology. This process has an impact on greenhouse gas emissions and is a sustainable source of energy for countries. It can reduce the effects of climate change and protect the planet for future generations. Tier1 and tier2 approaches are commonly used in the literature to calculate emissions factors. With boosting algorithms, this study estimated each animal category's biogas potential and CH4 emissions (tier1 and tier2 approach) for 2004-2021 in all of Turkey's provinces. Two different scenarios were created in the study. For scenario-1, the years 2020-2021 were predicted using data from 2004 to 2019, while for scenario-2, the years 2022-2024 were predicted using data from 2004 to 2021. According to the scenario-1 analysis, the eXtreme Gradient Boosting Regressor (XGBR) algorithm was the most successful algorithm with an R2 of 0.9883 for animal-based biogas prediction and 0.9835 and 0.9773 for animal-based CH4 emission predictions (tier1 and tier2 approaches) for the years 2020-2021. When the mean absolute percentage error was evaluated, it was found to be relatively low at 0.46%, 1.07%, and 2.78%, respectively. According to the scenario-2 analysis, the XGBR algorithm predicted the log10 values of the animal-based biogas potential of five major cities in Turkey for the year 2024, with 11.279 for Istanbul, 12.055 for Ankara, 12.309 for Izmir, 11.869 for Bursa, and 12.866 for Antalya. In the estimation of log10 values of CH4 emission, the tier1 approach yielded estimates of 3.080, 3.652, 3.929, 3.411, and 3.321, respectively, while the tier2 approach yielded estimates of 1.810, 2.806, 2.757, 2.552 and 2.122, respectively | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Animal waste | |
| 650 | 4 | |a Environmental effect | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Methane | |
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| 650 | 7 | |a Manure |2 NLM | |
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| 700 | 1 | |a Cesmeli, Melike Siseci |e verfasserin |4 aut | |
| 700 | 1 | |a Akyüz, Ali |e verfasserin |4 aut | |
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