Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

摘要

We present inverse modelling (top-down) estimates of European methane (CH) emissions for 2006–2012 based on a new quality-controlled and harmonized in-situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH emissions of 26.7 (20.2–29.7) Tg CH yr (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH emissions reported to UNFCCC (bottom-up, based on statistical data and emissions factors) amount to only 21.3 Tg CH yr (2006) to 18.8 Tg CH yr (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH Inter-comparison of Models Project (WETCHIMP) total wetland emissions of 4.3 (2.3–8.2) CH yr from EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH emissions with maxima in summer, while anthropogenic CH emissions are assumed to have much lower seasonal variability. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH compared to the background, integrated over the entire boundary layer and over the lower troposphere. This analysis identifies regional biases for several models at the aircraft profile sites in France, Hungary and Poland.