Browsing by Author "Lunt, Mark F."
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Item Open Access Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights(The Royal Society, 2021-12-06) MOYA/ZWAMPS Team; Nisbet, Euan; Allen, Grant; Fisher, Rebecca E.; France, James L.; Lee, James D.; Lowry, David; Andrade, Marcos F.; Bannan, Thomas J.; Barker, Patrick; Bateson, Prudence; Bauguitte, Stéphane J.-B.; Bower, Keith N.; Broderick, Tim J.; Chibesakunda, Francis; Cain, Michelle; Cozens, Alice E.; Daly, Michael C.; Ganesan, Anita L.; Jones, Anna E.; Lambakasa, Musa; Lunt, Mark F.; Mehra, Archit; Moreno, Isabel; Pasternak, Dominika; Palmer, Paul I.; Percival, Carl J.; Pitt, Joseph R.; Riddle, Amber J.; Rigby, Matthew; Shaw, Jacob T.; Stell, Angharad C.; Vaughan, Adam R.; Warwick, Nicola J.; Wilde, Shona E.We report methane isotopologue data from aircraft and ground measurements in Africa and South America. Aircraft campaigns sampled strong methane fluxes over tropical papyrus wetlands in the Nile, Congo and Zambezi basins, herbaceous wetlands in Bolivian southern Amazonia, and over fires in African woodland, cropland and savannah grassland. Measured methane δ13CCH4 isotopic signatures were in the range −55 to −49‰ for emissions from equatorial Nile wetlands and agricultural areas, but widely −60 ± 1‰ from Upper Congo and Zambezi wetlands. Very similar δ13CCH4 signatures were measured over the Amazonian wetlands of NE Bolivia (around −59‰) and the overall δ13CCH4 signature from outer tropical wetlands in the southern Upper Congo and Upper Amazon drainage plotted together was −59 ± 2‰. These results were more negative than expected. For African cattle, δ13CCH4 values were around −60 to −50‰. Isotopic ratios in methane emitted by tropical fires depended on the C3 : C4 ratio of the biomass fuel. In smoke from tropical C3 dry forest fires in Senegal, δ13CCH4 values were around −28‰. By contrast, African C4 tropical grass fire δ13CCH4 values were −16 to −12‰. Methane from urban landfills in Zambia and Zimbabwe, which have frequent waste fires, had δ13CCH4 around −37 to −36‰. These new isotopic values help improve isotopic constraints on global methane budget models because atmospheric δ13CCH4 values predicted by global atmospheric models are highly sensitive to the δ13CCH4 isotopic signatures applied to tropical wetland emissions. Field and aircraft campaigns also observed widespread regional smoke pollution over Africa, in both the wet and dry seasons, and large urban pollution plumes. The work highlights the need to understand tropical greenhouse gas emissions in order to meet the goals of the UNFCCC Paris Agreement, and to help reduce air pollution over wide regions of Africa. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.Item Open Access A measurement-based verification framework for UK greenhouse gas emissions: an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) project(Elsevier, 2018-08-17) Palmer, Paul I.; O'Doherty, Simon; Allen, Grant; Bower, Keith; Bösch, Hartmut; Chipperfield, Martyn P.; Connors, Sarah; Dhomse, Sandip; Feng, Liang; Finch, Douglas P.; Gallagher, Martin W.; Gloor, Emanuel; Gonzi, Siegfried; Harris, Neil R. P.; Helfter, Carole; Humpage, Neil; Kerridge, Brian; Knappett, Diane; Jones, Roderic L.; Le Breton, Michael; Lunt, Mark F.; Manning, Alistair J.; Matthiesen, Stephan; Muller, Jennifer B. A.; Mullinger, Neil; Nemitz, Eiko; O'Shea, Sebastian; Parker, Robert J.; Percival, Carl J.; Pitt, Joseph; Riddick, Stuart N.; Rigby, Matthew; Sembhi, Harjinder; Siddans, Richard; Skelton, Robert L.; Smith, Paul; Sonderfeld, Hannah; Stanley, Kieran; Stavert, Ann R.; Wenger, Angelina; White, Emily; Wilson, Christopher; Young, DickonWe describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.