Publications

Abstract. 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 17.5±2.1 Tg CH4 yr−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 (0.8±55 % 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. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

This paper reviews the many criticisms that Integrated Assessment Models (IAMs)—the bedrock of mitigation analysis—have received in recent years. Critics have asserted that there is a lack of transparency around model structures and input assumptions, a lack of credibility in those input assumptions that are made visible, an over-reliance on particular technologies and an inadequate representation of real-world policies and processes such as innovation and behaviour change. The paper then reviews the proposals and actions that follow from these criticisms, which fall into three broad categories: scrap the models and use other techniques to set out low-carbon futures; transform them by improving their representation of real-world processes and their transparency; and supplement them with other models and approaches. The article considers the implications of each proposal, through the particular lens of how it would explore the role of a key low-carbon technology—bioenergy with carbon capture and storage (BECCS), to produce net negative emissions. The paper concludes that IAMs remain critically important in mitigation pathways analysis, because they can encompass a large number of technologies and policies in a consistent framework, but that they should increasingly be supplemented with other models and analytical approaches.

Summary Understanding the response of soil organic carbon (SOC) to environmental and management factors is necessary for estimating the potential of soils to sequester atmospheric carbon. Changes over time in the amount and distribution of SOC fractions with different turnover rates can be estimated by means of soil SOC models such as RothC, which typically consider two to five SOC pools. Ideally, these pools should correspond to measurable SOC fractions. The aim of this study was to test the relationship between SOC pools used in RothC and fractions separated through a fractionation procedure. A total of 123 topsoil samples from agricultural sites (arable land, grassland and alpine pasture) across Switzerland were used. A combination of physical and chemical methods resulted in two sensitive (particulate organic matter and dissolved organic carbon), two slow (carbon associated to clay and silt or stabilized in aggregates) and one passive (oxidation‐resistant carbon) SOM fractions. These fractions were compared with the estimated equilibrium model pools when the corresponding soils were modelled with RothC. Analysis revealed strong correlations between SOC in measured fractions and modelled pools. Spearman’s rank correlation coefficients varied between 0.82 for decomposable plant materials (DPM), 0.76 for resistant plant materials (RPM), 0.99 for humified organic matter (HUM) and biomass (BIO), and 0.73 for inert organic matter (IOM). The results show that the proposed fractionation procedure can be used with minor adaptations to identify measurable SOC fractions, which can be used to initialize and evaluate RothC for a wide range of site conditions.

Abstract The livestock sector contributes considerably to global greenhouse gas emissions ( GHG ). Here, for the year 2007 we examined GHG emissions in the EU 27 livestock sector and estimated GHG emissions from production and consumption of livestock products; including imports, exports and wastage. We also reviewed available mitigation options and estimated their potential. The focus of this review is on the beef and dairy sector since these contribute 60% of all livestock production emissions. Particular attention is paid to the role of land use and land use change ( LULUC ) and carbon sequestration in grasslands. GHG emissions of all livestock products amount to between 630 and 863 Mt CO 2 e, or 12–17% of total EU 27 GHG emissions in 2007. The highest emissions aside from production, originate from LULUC , followed by emissions from wasted food. The total GHG mitigation potential from the livestock sector in Europe is between 101 and 377 Mt CO 2 e equivalent to between 12 and 61% of total EU 27 livestock sector emissions in 2007. A reduction in food waste and consumption of livestock products linked with reduced production, are the most effective mitigation options, and if encouraged, would also deliver environmental and human health benefits. Production of beef and dairy on grassland, as opposed to intensive grain fed production, can be associated with a reduction in GHG emissions depending on actual LULUC emissions. This could be promoted on rough grazing land where appropriate.

This dataset contains all data (in csv format) linked to the figures from the ESSD submitted paper: <strong>"The consolidated European synthesis of CH₄ and N₂O emissions for EU27 and UK: 1990-2017"</strong> Petrescu,A. M. R., Qiu,C., Ciais,P., Thompson, R.L.,Peylin, P., McGrath, M. J., Solazzo,E.,Janssens-Maenhout, G,Tubiello, F. N., Bergamaschi, P., Brunner, D., Peters, G. P., Höglund-Isaksson, L., Regnier, P., Lauerwald, R., Bastviken, D.,Tsuruta, A.,Winiwarter, W.,Patra, P. K., Kuhnert, M., Orregioni, G. D., Crippa, M.,Saunois, M.,Perugini, L., Markkanen, T.,Aalto, T.,Groot Zwaaftink, C. D., Yao, Y., Wilson, C.,Conchedda, G., Günther, D., Leip,A., Smith,P., Haussaire,J.-M., Leppänen, A., Manning, A. J., McNorton, J., Brockmann, P., and Dolman, A. J.: The consolidated European synthesis of CH₄ and N₂O emissions for EU27 and UK: 1990-2017, Earth Syst. Sci. Data Discuss., essd-2020-367, in review, 2020.

Abstract The effect of liming on the flow of recently photosynthesized carbon to rhizosphere soil was studied using 13 CO 2 pulse labelling, in an upland grassland ecosystem in Scotland. The use of 13 C enabled detection, in the field, of the effect of a 4‐year liming period of selected soil plots on C allocation from plant biomass to soil, in comparison with unlimed plots. Photosynthetic rates and carbon turnover were higher in plants grown in limed soils than in those from unlimed plots. Higher δ 13 C‰ values were detected in shoots from limed plants than in those from unlimed plants in samples clipped within 15 days of the end of pulse labelling. Analysis of the aboveground plant production corresponding to the 4‐year period of liming indicated that the standing biomass was higher in plots that received lime. Lower δ 13 C‰ values in limed roots compared with unlimed roots were found, whereas no significant difference was detected between soil samples. Extrapolation of our results indicated that more C has been lost through the soil than has been gained via photosynthetic assimilation because of pasture liming in Scotland during the period 1990–1998. However, the uncertainty associated with such extrapolation based on this single study is high and these estimates are provided only to set our findings in the broader context of national soil carbon emissions.

Abstract Accurate estimation of the greenhouse gas (GHG) mitigation potential of bioenergy crops requires the integration of a significant component of spatially varying information. In particular, crop yield and soil carbon (C) stocks are variables which are generally soil type and climate dependent. Since gaseous emissions from soil C depend on current C stocks, which in turn are related to previous land management it is important to consider both previous and proposed future land use in any C accounting assessment. We have conducted a spatially explicit study for England and Wales, coupling empirical yield maps with the RothC soil C turnover model to simulate soil C dynamics. We estimate soil C changes under proposed planting of four bioenergy crops, Miscanthus ( Miscanthus × giganteus ), short rotation coppice (SRC) poplar ( Populus trichocarpa Torr. &amp; Gray × P. trichocarpa , var. Trichobel), winter wheat, and oilseed rape. This is then related to the former land use – arable, pasture, or forest/seminatural, and the outputs are then assessed in the context of a life cycle analysis (LCA) for each crop. By offsetting emissions from management under the previous land use, and considering fossil fuel C displaced, the GHG balance is estimated for each of the 12 land use change transitions associated with replacing arable, grassland, or forest/seminatural land, with each of the four bioenergy crops. Miscanthus and SRC are likely to have a mostly beneficial impact in reducing GHG emissions, while oilseed rape and winter wheat have either a net GHG cost, or only a marginal benefit. Previous land use is important and can make the difference between the bioenergy crop being beneficial or worse than the existing land use in terms of GHG balance.