Articles | Volume 22, issue 19
https://doi.org/10.5194/acp-22-12945-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-12945-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Oct 2022
Research article |
| 10 Oct 2022
| 10 Oct 2022
Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion
School of Geographical Sciences, University of Bristol, Bristol, UK
Michael Bertolacci
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Andrew Zammit-Mangion
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Matthew Rigby
School of Chemistry, University of Bristol, Bristol, UK
Paul J. Fraser
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Australia
Christina M. Harth
Scripps Institution of Oceanography, University of California, San Diego, USA
Paul B. Krummel
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Australia
National Oceanic and Atmospheric Administration, Earth System Research Laboratory, Boulder, USA
University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, USA
Manfredi Manizza
Scripps Institution of Oceanography, University of California, San Diego, USA
Jens Mühle
Scripps Institution of Oceanography, University of California, San Diego, USA
Simon O'Doherty
School of Chemistry, University of Bristol, Bristol, UK
Ronald G. Prinn
Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, USA
Ray F. Weiss
Scripps Institution of Oceanography, University of California, San Diego, USA
Dickon Young
University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, USA
Anita L. Ganesan
CORRESPONDING AUTHOR
School of Geographical Sciences, University of Bristol, Bristol, UK
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Cited
9 citations as recorded by crossref.
- Mechanistic insight into the N2O + O(1D,3P) reaction: role of post-CCSD(T) corrections and non-adiabatic effects V. Anand & P. Kumar 10.1039/D3CP03830K
- Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion A. Stell et al. 10.5194/acp-22-12945-2022
- Current investigations on global N2O emissions and reductions: Prospect and outlook R. Feng & Z. Li 10.1016/j.envpol.2023.122664
- China's anthropogenic N2O emissions with analysis of economic costs and social benefits from reductions in 2022 R. Feng et al. 10.1016/j.jenvman.2024.120234
- A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes L. Resplandy et al. 10.1029/2023GB007803
- The environmental burden of inhalation A. de Boer 10.1016/j.ejps.2024.106893
- Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers B. Giechaskiel et al. 10.3390/technologies12030032
- A Sensitivity Study of a Bayesian Inversion Model Used to Estimate Emissions of Synthetic Greenhouse Gases at the European Scale S. Annadate et al. 10.3390/atmos15010051
- Diversity and Activity of Soil N2O-Reducing Bacteria Shaped by Urbanization L. Yang et al. 10.1021/acs.est.4c01750
9 citations as recorded by crossref.
- Mechanistic insight into the N2O + O(1D,3P) reaction: role of post-CCSD(T) corrections and non-adiabatic effects V. Anand & P. Kumar 10.1039/D3CP03830K
- Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion A. Stell et al. 10.5194/acp-22-12945-2022
- Current investigations on global N2O emissions and reductions: Prospect and outlook R. Feng & Z. Li 10.1016/j.envpol.2023.122664
- China's anthropogenic N2O emissions with analysis of economic costs and social benefits from reductions in 2022 R. Feng et al. 10.1016/j.jenvman.2024.120234
- A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes L. Resplandy et al. 10.1029/2023GB007803
- The environmental burden of inhalation A. de Boer 10.1016/j.ejps.2024.106893
- Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers B. Giechaskiel et al. 10.3390/technologies12030032
- A Sensitivity Study of a Bayesian Inversion Model Used to Estimate Emissions of Synthetic Greenhouse Gases at the European Scale S. Annadate et al. 10.3390/atmos15010051
- Diversity and Activity of Soil N2O-Reducing Bacteria Shaped by Urbanization L. Yang et al. 10.1021/acs.est.4c01750
Latest update: 20 Nov 2024
Short summary
Nitrous oxide is a potent greenhouse gas and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions. We derive increasing global nitrous oxide emissions over 2011–2020, which are mainly driven by emissions between 0° and 30°N, with the highest emissions recorded in 2020.
Nitrous oxide is a potent greenhouse gas and ozone-depleting substance, whose atmospheric...
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