Quantification of methane emissions in rice paddies: A machine learning approach with rice cultivar and transplanting date DOI Open Access

Jun‐Yeong Lee,

Yun‐Gu Kang,

Ji Hoon Kim

et al.

Korean Journal of Soil Science and Fertilizer, Journal Year: 2024, Volume and Issue: 57(3), P. 331 - 343

Published: Aug. 31, 2024

Language: Английский

The First Algorithm for Mapping High-Resolution Cropland Inundation Status Throughout the Growing Season Using Swot Karin Data DOI
Yongzhe Chen, Shunlin Liang, Wenyuan Li

et al.

Published: Jan. 1, 2025

Spatiotemporal variation of croplands' inundation status significantly affects irrigation water consumption, greenhouse gas emission and crop yield. However, spatially-explicit information on regime has not been able to retrieve from publicly-available satellite data. The main challenges include the inability optical remote sensing observe beneath dense canopy strong variability SAR backscattering coefficients over inundated croplands. Here, we propose first algorithm differentiate between non-inundated, partially-inundated, fully-inundated fields throughout growing season, by leveraging coherent power retrieved KaRIn, a near-nadir-looking Interferometer onboard SWOT satellite. novelty lies in control disturbances other factors, including incidence angle, vegetation content wind speed variation, power. With these controlled, threshold different were estimated using Gaussian Mixture Models. This was performed 0.5°×0.5° area northeast China, at resolution approximately 60 m, every 7 days average season 2024. mapping results paddy clearly delineate distinct phases flooded irrigation, shallow-wet-dry or without are generally consistent with actual conditions obtained field investigations, government documents published literature. can be applied similar rice regions vegetated natural wetlands. We also adjustment schemes for this so that it adapted more complicated frequent clouds, heterogeneous cropping calendars, limited type information.

Language: Английский

Citations

0

Practical paths towards quantifying and mitigating agricultural methane emissions DOI Creative Commons
E. G. Nisbet, Martin Manning, David Lowry

et al.

Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2025, Volume and Issue: 481(2309)

Published: March 1, 2025

This review summarizes the rapid advances in direct practical methods to quantify and reduce agricultural methane emissions worldwide. Major tasks are location, identification, quantification distinction between different specific sources (often multiple emitters such as manure pools, animal housing, biodigesters landfills co-located). Emission reduction, facilitated by developing methodologies for locating hot spots, is least-cost choice action, especially from stores, controlling biomass burning. Agricultural can also be used generate electricity or, appropriate circumstances, destroyed oxidation. It may possible cut North American, East Asian European sharply rapidly. In Africa South Asia, crop waste food landfills, a source of air pollution, quickly reduced. Globally, cutting total annual third would demand reductions very approximately 75 Tg yr −1 . Apportioned type, notional cuts might 30–40 livestock manure, 5-10 rice cultivation 20 or more specifically waste.

Language: Английский

Citations

0

Impact of co-introduction of soluble potassium and nitrogen on methanotrophs DOI
Xinyue Bai, Dandan Huang, Wanli Yang

et al.

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 162171 - 162171

Published: March 1, 2025

Language: Английский

Citations

0

Methane Oxidation Rates and Efficiencies Across Four Distinct Soil Environments: Implications for Greenhouse Gas Mitigation DOI Creative Commons

Chonticha Leamdum,

Nantharat Phruksaphithak,

Sukonlarat Chanthong

et al.

ASEAN Journal of Scientific and Technological Reports, Journal Year: 2024, Volume and Issue: 28(1), P. e255939 - e255939

Published: Dec. 14, 2024

Methane oxidation by soil microorganisms is crucial in mitigating greenhouse gas emissions. This study investigated methane potential across four distinct environments through standardized laboratory enrichment cultures. Soil samples were collected from landfill-cover soils, rice fields, cattle farms, and pond sediments, with environmental parameters monitored to understand their influence on rates efficiencies. Using chromatography analysis, we quantified under controlled conditions. Statistical analysis revealed significant differences types. Landfill cover soils exhibited the highest rate of 0.39 μmol-CH₄/g-soil dry weight/h efficiency 66.5 %. Pond farm field followed 0.29, 0.28, 0.27 weight/h, respectively. Oxidation efficiencies for these ranged 46.1% 48.4%. pH organic matter content showed strong positive correlations all types, while moisture effects varied. The superior performance landfill was attributed optimal conditions stable substrate availability. enhancing efficiencies: 66.5% 75-85%, fields 60-70%, farms 47.0% 55-65%, sediments 48.4% 60-75%. Implementing optimized management strategies could reduce emissions 70-90% landfills, 30-50% agricultural systems, 40-60% aquatic compared current practices. highlights substantial biological diverse ecosystems emphasizes need targeted approaches optimize mitigation strategies.

Language: Английский

Citations

1

Quantification of methane emissions in rice paddies: A machine learning approach with rice cultivar and transplanting date DOI Open Access

Jun‐Yeong Lee,

Yun‐Gu Kang,

Ji Hoon Kim

et al.

Korean Journal of Soil Science and Fertilizer, Journal Year: 2024, Volume and Issue: 57(3), P. 331 - 343

Published: Aug. 31, 2024

Language: Английский

Citations

0