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The primary aims of this study were to use the CH4(a) isotopic composition (δ13C) of in-flight atmospheric air (IFAA) samples to assess where the bottom–up (BU) inventory developed specifically for the region was well characterised and to identify gaps in the BU inventory (missing sources or over- and underestimated source categories). Secondary aims were to investigate whether IFAA samples collected downwind of predominantly similar inventory sources were useable for characterising the isotopic signature of CH4 sources (δ13C) and to identify mitigation opportunities.
IFAA samples were collected between 100–350 m above ground level (m a.g.l.) over a 2-week period in September 2018. For each IFAA sample the 2 h back-trajectory footprint area was determined using the NOAA HYSPLIT atmospheric trajectory modelling application. IFAA samples were gathered into sets, where the 2 h upwind BU inventory had > 50 % attributable to a single predominant CH4 source (CSG, grazing cattle, or cattle feedlots). Keeling models were globally fitted to these sets using multiple regression with shared parameters (background-air CH4(b) and δ13C).
For IFAA samples collected from 250–350 m a.g.l. altitude, the best-fit δ13C signatures compare well with the ground observation: CSG δ13C of −55.4 ‰ (confidence interval (CI) 95 % ± 13.7 ‰) versus δ13C of −56.7 ‰ to −45.6 ‰; grazing cattle δ13C of −60.5 ‰ (CI 95 % ± 15.6 ‰) versus −61.7 ‰ to −57.5 ‰. For cattle feedlots, the derived δ13C (−69.6 ‰, CI 95 % ± 22.6 ‰), was isotopically lighter than the ground-based study (δ13C from −65.2 ‰ to −60.3 ‰) but within agreement given the large uncertainty for this source. For IFAA samples collected between 100–200 m a.g.l. the δ13C signature for the CSG set (−65.4 ‰, CI 95 % ± 13.3 ‰) was isotopically lighter than expected, suggesting a BU inventory knowledge gap or the need to extend the population statistics for CSG δ13C signatures. For the 100–200 m a.g.l. set collected over grazing cattle districts the δ13C signature (−53.8 ‰, CI 95 % ± 17.4 ‰) was heavier than expected from the BU inventory. An isotopically light set had a low δ13C signature of −80.2 ‰ (CI 95 % ± 4.7 ‰). A CH4 source with this low δ13C signature has not been incorporated into existing BU inventories for the region. Possible sources include termites and CSG brine ponds. If the excess emissions are from the brine ponds, they can potentially be mitigated. It is concluded that in-flight atmospheric δ13C measurements used in conjunction with endmember mixing modelling of CH4 sources are powerful tools for BU inventory verification.