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Veröffentlichung Top-down estimates of European CH4 and N2O emissions based on four different inverse models(2015)European CH4and N2O emissions are estimated for 2006 and 2007 using four inverse modelling systems, based on different global and regional Eulerian and Lagrangian transport models. This ensemble approach is designed to provide more realistic estimates of the overall uncertainties in the derived emissions, which is particularly important for verifying bottom-up emission inventories. We use continuous observations from 10 European stations (including 5 tall towers) for CH4and 9 continuous stations for N2O, complemented by additional European and global discrete air sampling sites. The available observations mainly constrain CH4and N2O emissions from north-western and eastern Europe. The inversions are strongly driven by the observations and the derived total emissions of larger countries show little dependence on the emission inventories used a priori. Three inverse models yield 26-56% higher total CH4emissions from north-western and eastern Europe compared to bottom-up emissions reported to the UNFCCC, while one model is close to the UNFCCC values. In contrast, the inverse modelling estimates of European N2O emissions are in general close to the UNFCCC values, with the overall range from all models being much smaller than the UNFCCC uncertainty range for most countries. Our analysis suggests that the reported uncertainties for CH4 emissions might be underestimated, while those for N2O emissions are likely overestimated. Quelle: http://www.scopus.comVeröffentlichung Comparison of a laser methane detector with the GreenFeed and two breath analysers for on-farm measurements of methane emissions from dairy cows(2018) Sorg, Diana; Difford, G.F.; Mühlbach, S.To measure methane (CH4) emissions from cattle on-farm, a number of methods have been developed. Combining measurements made with different methods in one data set could lead to an increased power of further analyses. Before combining the measurements, their agreement must be evaluated. We analysed data obtained with a handheld laser methane detector (LMD) and the GreenFeed system (GF), as well as data obtained with LMD and Fourier Transformed Infrared (FTIR) and Non-dispersive Infrared (NDIR) breath analysers (sniffers) installed in the feed bin of automatic milking systems. These devices record short-term breath CH4 concentrations from cows and make it possible to estimate daily CH4 production in g/d which is used for national CH4 emission inventories and genetic studies. The CH4 is released by cows during eructation and breathing events, resulting in peaks of CH4 concentrations during a measurement which represent the respiratory cycle. For LMD, the average CH4 concentration of all peaks during the measurement (P_MEAN in ppm * meter) was compared with the average daily CH4 production (g/d) measured by GF on 11 cows. The comparison showed a low concordance correlation coefficient (CCC; 0.02) and coefficient of individual agreement (CIA; 0.06) between the methods. The repeated measures correlation (rp) of LMD and GF, which can be seen as a proxy for the genetic correlation, was, however, relatively strong (0.66). Next, based on GF, a prediction equation for estimating CH4 in g/d (LMD_cal) using LMD measurements was developed. LMD_cal showed an improved agreement with GF (CCC = 0.22, CIA = 0.99, rp = 0.74). This prediction equation was used to compare repeated LMD measurements (LMD_val in g/d) with CH4 (g/d) measured with FTIR (n = 34 cows; Data Set A) or NDIR (n = 39 cows; Data Set B) sniffer. A low CCC (A: 0.28; B: 0.17), high CIA (A: 0.91; B: 0.87) and strong rp (A: 0.57; B: 0.60) indicated that there was some agreement and a minimal re-ranking of the cows between sniffer and LMD. Possible sources of disagreement were cow activity (LMD: standing idle; sniffer: eating and being milked) and the larger influence of wind speed on LMD measurement. The LMD measurement was less repeatable (0.14â€Ì0.27) than the other techniques studied (0.47â€Ì0.77). Nevertheless, GF, LMD and the sniffers ranked the cows similarly. The LMD, due to its portability and flexibility, could be used to study CH4 emissions on herd or group level, as a validation tool, or to strengthen estimates of genetic relationships between small-scale research populations. © 2018 Elsevier B.V.Veröffentlichung Comparison of methods to measure methane for use in genetic evaluation of dairy cattle(2019) Garnsworthy, Philip C.; Difford, Gareth F.; Bell, Matthew J.; Sorg, DianaPartners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF6) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the "true" value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available. Quelle: VerlagsinformationVeröffentlichung A pragmatic protocol for characterising errors in atmospheric inversions of methane emissions over Europe(2021) Szénási, Barbara; Berchet, Antoine; Broquet, Grégoire; Kiesow, AnjaThis study aims at estimating errors to be accounted for in atmospheric inversions of methane (CH4) emissions at the European scale. Four types of errors are estimated in the concentration space over the model domain and at selected measurement sites. Furthermore, errors in emission inventories are estimated at country and source sector scales. A technically ready method is used, which is implemented by running a set of simulations of hourly CH4 mixing ratios for 2015 using two area-limited transport models at three horizontal resolutions with multiple data sets of emissions and boundary and initial conditions as inputs. The obtained error estimates provide insights into how these errors could be treated in an inverse modelling system for inverting CH4 emissions over Europe. The main results show that sources of transport errors may better be controlled alongside the emissions, which differs from usual inversion practices. The average total concentration error is estimated at 29†ppb. The assessed error of total CH4 emissions is 22% and emission errors are heterogeneous at sector (23-49%) and country scales (16-124%), with largest errors occurring in the waste sector due to uncertainties in activity data and emission factors and in Finland due to uncertainties in natural wetland emissions. © 2021 The Author(s).Veröffentlichung On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2(2022) Bastos, Ana; Ciais, Philippe; Sitch, Stephen; Günther, DirkThe Global Stocktake (GST), implemented by the Paris Agreement, requires rapid developments in the capabilities to quantify annual greenhouse gas (GHG) emissions and removals consistently from the global to the national scale and improvements to national GHG inventories. In particular, new capabilities are needed for accurate attribution of sources and sinks and their trends to natural and anthropogenic processes. On the one hand, this is still a major challenge as national GHG inventories follow globally harmonized methodologies based on the guidelines established by the Intergovernmental Panel on Climate Change, but these can be implemented differently for individual countries. Moreover, in many countries the capability to systematically produce detailed and annually updated GHG inventories is still lacking. On the other hand, spatially-explicit datasets quantifying sources and sinks of carbon dioxide, methane and nitrous oxide emissions from Earth Observations (EO) are still limited by many sources of uncertainty. While national GHG inventories follow diverse methodologies depending on the availability of activity data in the different countries, the proposed comparison with EO-based estimates can help improve our understanding of the comparability of the estimates published by the different countries. Indeed, EO networks and satellite platforms have seen a massive expansion in the past decade, now covering a wide range of essential climate variables and offering high potential to improve the quantification of global and regional GHG budgets and advance process understanding. Yet, there is no EO data that quantifies greenhouse gas fluxes directly, rather there are observations of variables or proxies that can be transformed into fluxes using models. Here, we report results and lessons from the ESA-CCI RECCAP2 project, whose goal was to engage with National Inventory Agencies to improve understanding about the methods used by each community to estimate sources and sinks of GHGs and to evaluate the potential for satellite and in-situ EO to improve national GHG estimates. Based on this dialogue and recent studies, we discuss the potential of EO approaches to provide estimates of GHG budgets that can be compared with those of national GHG inventories. We outline a roadmap for implementation of an EO carbon-monitoring program that can contribute to the Paris Agreement. © 2023 BioMed Central