Soil NO emissions modelling using artificial neural network-Reference-Cited by-同舟云学术

Soil NO emissions modelling using artificial neural network

Published:2007-01 Issue:3 Volume:59 Page:502-513
ISSN:1600-0889
Container-title:Tellus B: Chemical and Physical Meteorology
language:en
Short-container-title:Tellus B: Chemical and Physical Meteorology

Author:

Delon Claire¹,SerçA Dominique¹,Boissard Christophe²,Dupont Richard¹,Dutot Alain²,Laville Patricia³,De Rosnay Patricia⁴,Delmas Robert¹

Affiliation:

1. Laboratoire d’Aérologie, 14 avenue E. Belin, 31400 Toulouse, France

2. Laboratoire Interuniversitaire des Syst`emes Atmosphériques, 94010 Créteil, France

3. INRA, EGC, 78830 Thiverval-Grignon, France

4. CESBIO, 31400 Toulouse, France

Publisher

Informa UK Limited

Subject

Atmospheric Science

Link

https://www.tandfonline.com/doi/pdf/10.1111/j.1600-0889.2007.00254.x

Reference30 articles.

1. Enhanced biogenic emissions of nitric oxide and nitrous oxide following surface biomass burning

2. Bertram, T. H., Heckel, A., Richter, A., Burrows, J. P and Cohen, R. C. 2005. Satellite measurements of daily variations in soil NOx emis-sions. Geophys. Res. Lett. 32, 10.1029/2005GL024640.

3. Emissions of N2O and NO from fertilized fields: Summary of available measurement data

4. Modeling global annual N2O and NO emissions from fertilized fields

5. Butterbach-Bahl, K., Kock, M., Willibald, G., Hewett, B., Buhagiar, S., Papen and co-authors. 2004. Temporal variations of fluxes of NO, NO2, N20, CO2 and CH4 in a tropical rain forest ecosystem. Global Biogeochem. Cycles 18, GB3012, 10.1029/2004GB002243.

Cited by 47 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancing agroecosystem modelling of nitrogen losses with machine learning;Earth Critical Zone;2024-06

2. Modeling of CO2 Emissions of Soils under Newly Established, Non-Irrigated and Irrigated Urban Turfgrass Management in SE of Turkey;Eurasian Soil Science;2023-07-18

3. Modelling carbon dioxide emissions under a maize-soy rotation using machine learning;Biosystems Engineering;2021-12

4. New approach for predicting nitrification and its fraction of N2O emissions in global terrestrial ecosystems;Environmental Research Letters;2021-03-01

5. Modeling soil enzyme activity using easily measured variables: Heuristic alternatives;Applied Soil Ecology;2021-01