Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model
Biochar amendment to soils is regarded as the potential practice to mitigate climate change while also increasing yields. However, geographical differences in the effects of biochar on cereal production and greenhouse gas emissions are not well understood at the global scale. Random forest, a classi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | Current Research in Environmental Sustainability |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666049023000324 |
| _version_ | 1797382888987033600 |
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| author | Xiangrui Xu Tong Li Kun Cheng Qian Yue Genxing Pan |
| author_facet | Xiangrui Xu Tong Li Kun Cheng Qian Yue Genxing Pan |
| author_sort | Xiangrui Xu |
| collection | DOAJ |
| description | Biochar amendment to soils is regarded as the potential practice to mitigate climate change while also increasing yields. However, geographical differences in the effects of biochar on cereal production and greenhouse gas emissions are not well understood at the global scale. Random forest, a classic machine learning algorithm, was employed to reveal the drivers of geographical differences in the effects of biochar on cereals yield and greenhouse gas emissions. The potential for yield increases and greenhouse gas emission reduction was predicted in this study. The results indicate that nitrogen fertilizer rate is the most important factor determining the impact of biochar on cereal yield, while biochar application rate strongly affected greenhouse gas emissions. Globally, the maximum increase in cereal crop yields under biochar application was 14.1%. To achieve the largest increment globally, recommended values of biochar application, mineral nitrogen application rate and pyrolysis temperature were predicted to be around 36.3 t ha−1, 193.7 kg N ha−1 and 420 °C, respectively. The maximum reductions of methane and nitrous oxide emissions from paddy fields around the world were 21.6% and 31.0%, and from maize and wheat fields 35.7% and 36.1%, respectively. Although biochar can potentially improve yields while reducing greenhouse gas emissions worldwide under proper management, the performance of biochar showed great heterogeneity. |
| first_indexed | 2024-03-08T21:11:56Z |
| format | Article |
| id | doaj.art-f57400750f2742a8ac770e8a13695742 |
| institution | Directory Open Access Journal |
| issn | 2666-0490 |
| language | English |
| last_indexed | 2024-03-08T21:11:56Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Current Research in Environmental Sustainability |
| spelling | doaj.art-f57400750f2742a8ac770e8a136957422023-12-22T05:34:16ZengElsevierCurrent Research in Environmental Sustainability2666-04902024-01-017100239Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning modelXiangrui Xu0Tong Li1Kun Cheng2Qian Yue3Genxing Pan4Institute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China; School of Spatial Design and Planning, Hangzhou City University, 51 Huzhou Street, Hangzhou, Zhejiang 310000, China; Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UKInstitute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, ChinaInstitute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China; Corresponding author at: Institute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agriculture University, 1 Weigang, Nanjing, Jiangsu 210095, China.Key Laboratory for Crop and Animal Integrated Farming of Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, ChinaInstitute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, ChinaBiochar amendment to soils is regarded as the potential practice to mitigate climate change while also increasing yields. However, geographical differences in the effects of biochar on cereal production and greenhouse gas emissions are not well understood at the global scale. Random forest, a classic machine learning algorithm, was employed to reveal the drivers of geographical differences in the effects of biochar on cereals yield and greenhouse gas emissions. The potential for yield increases and greenhouse gas emission reduction was predicted in this study. The results indicate that nitrogen fertilizer rate is the most important factor determining the impact of biochar on cereal yield, while biochar application rate strongly affected greenhouse gas emissions. Globally, the maximum increase in cereal crop yields under biochar application was 14.1%. To achieve the largest increment globally, recommended values of biochar application, mineral nitrogen application rate and pyrolysis temperature were predicted to be around 36.3 t ha−1, 193.7 kg N ha−1 and 420 °C, respectively. The maximum reductions of methane and nitrous oxide emissions from paddy fields around the world were 21.6% and 31.0%, and from maize and wheat fields 35.7% and 36.1%, respectively. Although biochar can potentially improve yields while reducing greenhouse gas emissions worldwide under proper management, the performance of biochar showed great heterogeneity.http://www.sciencedirect.com/science/article/pii/S2666049023000324BiocharYieldGreenhouse gasMachine learningClimate change |
| spellingShingle | Xiangrui Xu Tong Li Kun Cheng Qian Yue Genxing Pan Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model Current Research in Environmental Sustainability Biochar Yield Greenhouse gas Machine learning Climate change |
| title | Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model |
| title_full | Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model |
| title_fullStr | Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model |
| title_full_unstemmed | Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model |
| title_short | Geographical differences in the effect of biochar on crop yield and greenhouse gas emissions – A global simulation based on a machine learning model |
| title_sort | geographical differences in the effect of biochar on crop yield and greenhouse gas emissions a global simulation based on a machine learning model |
| topic | Biochar Yield Greenhouse gas Machine learning Climate change |
| url | http://www.sciencedirect.com/science/article/pii/S2666049023000324 |
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