Auflistung nach Autor:in "McGrath, Matthew Joseph"

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The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990-2019
(2023) Petrescu, Ana Maria Roxana; Qiu, Chunjing; McGrath, Matthew Joseph; Günther, Dirk
Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990-2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015-2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr-1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr-1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5Ì2.1Tg CH4 y -1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr-1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr-1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH-HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr-1. For N2O emissions, over the 2015-2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr-1, close to the NGHGI data (0.8Ì55% Tg N2O yr-1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr-1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. © Author(s) 2023
The consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990-2020
(2023) McGrath, Matthew Joseph; Petrescu, Ana Maria Roxana; Peylin, Philippe; Günther, Dirk
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990-2018
(2021) Petrescu, Ana Maria Roxana; McGrath, Matthew Joseph; Andrew, Robbie M.; Günther, Dirk
Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990-2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 TgCO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588(+/- 463 TgCO2). The inversion reports 2700 TgCO2(+/- 480 TgCO2), which is well in line with the national inventories. Over 2011-2015, the CO2 land sources and sinks from NGHGI estimates report -90 Tg C yr-1 +/- 30 Tg C yr-1 while all other BU approaches report a mean sink of -98 Tg Cyr-1 (+/- 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr-1 +/- 400 Tg C yr-1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of "CO2 flux" obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a). © Author(s) 2021