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We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (Gt CO 2 eq. yr -1), corresponding to 31 % (range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 Gt CO 2 eq. yr -1 ; emissions from land use change, due to deforestation and peatland degradation, were 3.5 Gt CO 2 eq. yr -1 ; and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 Gt CO 2 eq. yr -1. Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and post-production processes emitted the most CO 2 (3.9 Gt CO 2 yr -1), preceding land use change (3.3 Gt CO 2 yr -1) and farm gate (1.2 Gt CO 2 yr -1) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 Mt CH 4 yr -1) and of nitrous oxide (7.8 Mt N 2 O yr -1). Pre- and post-production processes were also significant emitters of methane (49 Mt CH 4 yr -1), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 Gt CO 2 eq. yr -1). They also more than doubled in non-Annex I parties (to 3.5 Gt CO 2 eq. yr -1), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 Mt CO 2 eq. yr -1), the USA (700 Mt CO 2 eq. yr -1) and the EU-27 (600 Mt CO 2 eq. yr -1). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO 2 gases within the farm gate and on CO 2 mitigation from land use change. The information used in this work is available as open data with DOI 10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM ; FAO, 2021a), with annual updates. [ABSTRACT FROM AUTHOR]

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO 2), 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 CO 2 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 (CO 2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO 2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO 2 emissions (including cement production) account for 2624 Tg CO 2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO 2). The inversion reports 2700 Tg CO 2 (± 480 Tg CO 2), which is well in line with the national inventories. Over 2011–2015, the CO 2 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 C yr -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 "CO 2 flux" obtained from different approaches. The referenced datasets related to figures are visualized at 10.5281/zenodo.4626578 (Petrescu et al., 2020a). [ABSTRACT FROM AUTHOR]

National, regional and global CO 2 emissions and removals from forests were estimated for the period 1990–2020 using as input the country reports of the Global Forest Resources Assessment 2020. The new Food and Agriculture Organization of the United Nations (FAO) estimates, based on a simple carbon stock change approach, update published information on net emissions and removals from forests in relation to (a) net forest conversion and (b) forest land. Results show a significant reduction in global emissions from net forest conversion over the study period, from a mean of 4.3 in 1991–2000 to 2.9 Gt CO 2 yr -1 in 2016–2020. At the same time, forest land was a significant carbon sink globally but decreased in strength over the study period, from -3.5 to -2.6 Gt CO 2 yr -1. Combining net forest conversion with forest land, our estimates indicated that globally forests were a small net source of CO 2 to the atmosphere on average during 1990–2020, with mean net emissions of 0.4 Gt CO 2 yr -1. The exception was the brief period 2011–2015, when forest land removals counterbalanced emissions from net forest conversion, resulting in a global net sink of -0.7 Gt CO 2 yr -1. Importantly, the new estimates allow for the first time in the literature the characterization of forest emissions and removals for the decade just concluded, 2011–2020, showing that in this period the net contribution of forests to the atmosphere was very small, i.e., a sink of less than -0.2 Gt CO 2 yr -1 – an estimate not yet reported in the literature. This near-zero balance was nonetheless the result of large global fluxes of opposite sign, namely net forest conversion emissions of 3.1 Gt CO 2 yr -1 counterbalanced by net removals on forest land of -3.3 Gt CO 2 yr -1. Finally, we compared our estimates with data independently reported by countries to the United Nations Framework on Climate Change, indicating close agreement between FAO and country emissions and removals estimates. Data from this study are openly available via the Zenodo portal (Tubiello, 2020), with DOI 10.5281/zenodo.3941973, as well as in the FAOSTAT (Food and Agriculture Organization Corporate Statistical Database) emissions database (FAO, 2021a). [ABSTRACT FROM AUTHOR]

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (~biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (T-D, exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories, and data-driven approaches (B-U, including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by T-D inversions at 558 & Tg & CH4 & yr-1 (range [540-568]). About 60 & % of global emissions are anthropogenic (range [50-65 & %]). B-U approaches suggest larger global emissions (736 & Tg & CH4 & yr-1 [596-884]) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the T-D budget, it is likely that some of the individual emissions reported by the B-U approaches are overestimated, leading to too large global emissions. Latitudinal data from T-D emissions indicate a predominance of tropical emissions (~64 & % of the global budget, < & 30° & N) as compared to mid (~32 & %, 30° & N-60° & N) and high northern latitudes (~ & 4 & %, 60° & N-90° & N). T-D inversions consistently infer lower emissions in China (~58 & Tg & CH4 & yr-1 [51-72], -14 & %) and higher emissions in Africa (86 & Tg & CH4 & yr-1 [73-108], +19 & %) than B-U values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for T-D inversions than for B-U inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute for 30-40 & % on the estimated range for wetland emissions. Other priorities for improving the methane budget include: i) the development of process-based models for inland-water emissions, ii) the intensification of methane observations at local scale (flux measurements) to constrain B-U land surface models, and at regional scale (surface networks and satellites) to constrain T-D inversions, iii) improvements in the estimation of atmospheric loss by OH, and iv) improvements of the transport models integrated in T-D inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/Global_Methane_Budget_2016). [ABSTRACT FROM AUTHOR]

Using newly available data from the 2015 Forest Resources Assessment (FRA), we refined the information, currently available through the IPCC AR5 and FAOSTAT, on recent trends in global and regional net CO 2 emissions and removals from forest land, including from net forest conversion (used as a proxy for deforestation) and forest remaining forest. The new analysis is based on the simplified forest carbon stock method of the FAOSTAT Emissions database, equivalent to a Tier 1, Approach 1 IPCC methodology, limited to biomass carbon stocks. Our results indicated that CO 2 emissions from net forest conversion decreased significantly, from an average of 4.0 Gt CO 2 yr −1 during 2001–2010 to 2.9 Gt CO 2 yr −1 during 2011–2015. More than half of the estimated reductions over the last five years, some 0.6 Gt CO 2 yr −1 , took place in Brazil. Detailed analyses further indicated that remaining forests continued to function as a net carbon sink globally, with an average net removal of −2.2 Gt CO 2 yr −1 during 2001–2010, and −2.1 Gt CO 2 yr −1 during 2011–2015. Annex I Parties represented the bulk of this sink, contributing 60% of the total in 2011–2015, down from 65% in 2001–2010. Compared to previous FAOSTAT assessments for the period 2001–2010, based on the 2010 FRA and published in the IPCC AR5, the use of FRA 2015 data led to estimates of net forest conversion that were consistent with previous ones (4.0 vs. 3.8 Gt CO 2 yr −1 ), while the estimated forest sinks were 22% larger (−2.2 vs. −1.8 Gt CO 2 yr −1 ). The net contribution of forests to anthropogenic forcing based on FRA2015 data was thus smaller than previously estimated by the IPCC AR5. Finally, we separated for the first time net emissions and removals from forest land into a sink component and a degradation component. Results indicated that, contrary to CO 2 emissions from deforestation, CO 2 emissions from forest degradation increased significantly, from 0.4 Gt CO 2 yr −1 in the 1990s, to 1.1 Gt CO 2 yr −1 in 2001–2010 and 1.0 Gt CO 2 yr −1 in 2011–2015. Emissions from forest degradation were thus one-fourth of those from deforestation in 2001–2010, increasing to one-third in 2011–2015. [ABSTRACT FROM AUTHOR]

Abstract: Recent conclusions that new free-air carbon dioxide enrichment (FACE) data show a much lower crop yield response to elevated CO2 than thought previously – casting serious doubts on estimates of world food supply in the 21st century – are found to be incorrect, being based in part on technical inconsistencies and lacking statistical significance. First, we show that the magnitude of crop response to elevated CO2 is rather similar across FACE and non-FACE data-sets, as already indicated by several previous comprehensive experimental and modeling analyses, with some differences related to which “ambient” CO2 concentration is used for comparisons. Second, we find that results from most crop model simulations are consistent with the values from FACE experiments. Third, we argue that lower crop responses to elevated CO2 of the magnitudes in question would not significantly alter projections of world food supply. We conclude by highlighting the importance of a better understanding of crop response to elevated CO2 under a variety of experimental and modeling settings, and suggest steps necessary to avoid confusion in future meta-analyses and comparisons of experimental and model data. [Copyright &y& Elsevier]

Several crop models may be used to simulate the effects of elevated CO2 on crop productivity. Yet no summary exists in the literature attempting to describe differences among models and how simulations might differ under climate change conditions. We provide an introductory review focusing on simulating the impacts of elevated CO2 on crops. We describe and discuss modeling approaches, component modules, applications to climate change and model validation and inter-comparison studies. By searching the recent peer-reviewed literature from 1995 to present, we found that about 20% of published crop modeling studies have focused on climate change impacts. About half of these studies explicitly analyzed the effects of elevated CO2 on crop growth and yield. Our analysis further suggested that the crop models that have been used the most in climate change assessments are also those that have been evaluated the least using available data from elevated CO2 experiments. Based on our review, we identify a set of recommendations aimed at improving our confidence in predictions of crop production under elevated CO2 and climate change conditions. These include continued model evaluation with existing field experiment data; increased focus on limiting factors such as pest, weeds, and disease; and attention to temporal and spatial scaling issues. [Copyright &y& Elsevier]