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  • 1
    In: Earth System Science Data, Copernicus GmbH, Vol. 15, No. 10 ( 2023-10-05), p. 4295-4370
    Abstract: Abstract. Quantification of land surface–atmosphere fluxes of carbon dioxide (CO2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 926 ± 13 Tg C yr−1, while eight other BU sources report a mean value of 948 [937,961] Tg C yr−1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875 Tg C in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for −91 ± 32 Tg C yr−1, while six other BU approaches reported a mean sink of −62 [-117,-49] Tg C yr−1, and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported −69 [-152,-5] Tg C yr−1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of −73 Tg C yr−1 has a slightly smaller spread (0th–100th percentiles of [-135,+45] Tg C yr−1), and it was calculated after removing net land–atmosphere CO2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (−0.61) Tg C yr−2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000 Tg C yr−1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.8148461 (McGrath et al., 2023).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2475469-9
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  • 2
    In: Environmental Research Letters, IOP Publishing, Vol. 16, No. 6 ( 2021-06-01), p. 065007-
    Abstract: New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO 2 eq yr −1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO 2 eq yr −1 , were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO 2 eq cap −1 , with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.
    Type of Medium: Online Resource
    ISSN: 1748-9326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2021
    detail.hit.zdb_id: 2255379-4
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  • 3
    In: Global Change Biology, Wiley, Vol. 30, No. 5 ( 2024-05)
    Abstract: Nitrous oxide (N 2 O) emissions from livestock manure contribute significantly to the growth of atmospheric N 2 O, a powerful greenhouse gas and dominant ozone‐depleting substance. Here, we estimate global N 2 O emissions from livestock manure during 1890–2020 using the tier 2 approach of the 2019 Refinement to the 2006 IPCC Guidelines. Global N 2 O emissions from livestock manure increased by ~350% from 451 [368–556] Gg N year −1 in 1890 to 2042 [1677–2514] Gg N year −1 in 2020. These emissions contributed ~30% to the global anthropogenic N 2 O emissions in the decade 2010–2019. Cattle contributed the most (60%) to the increase, followed by poultry (19%), pigs (15%), and sheep and goats (6%). Regionally, South Asia, Africa, and Latin America dominated the growth in global emissions since the 1990s. Nationally, the largest emissions were found in India (329 Gg N year −1 ), followed by China (267 Gg N year −1 ), the United States (163 Gg N year −1 ), Brazil (129 Gg N year −1 ) and Pakistan (102 Gg N year −1 ) in the 2010s. We found a substantial impact of livestock productivity, specifically animal body weight and milk yield, on the emission trends. Furthermore, a large spread existed among different methodologies in estimates of global N 2 O emission from livestock manure, with our results 20%–25% lower than those based on the 2006 IPCC Guidelines. This study highlights the need for robust time‐variant model parameterization and continuous improvement of emissions factors to enhance the precision of emission inventories. Additionally, urgent mitigation is required, as all available inventories indicate a rapid increase in global N 2 O emissions from livestock manure in recent decades.
    Type of Medium: Online Resource
    ISSN: 1354-1013 , 1365-2486
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2024
    detail.hit.zdb_id: 2020313-5
    SSG: 12
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  • 4
    In: Climatic Change, Springer Science and Business Media LLC, Vol. 161, No. 3 ( 2020-08), p. 415-432
    Type of Medium: Online Resource
    ISSN: 0165-0009 , 1573-1480
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 751086-X
    detail.hit.zdb_id: 1477652-2
    SSG: 14
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  • 5
    In: Earth System Science Data, Copernicus GmbH, Vol. 14, No. 4 ( 2022-04-14), p. 1795-1809
    Abstract: Abstract. 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 CO2 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 CO2 eq. yr−1; emissions from land use change, due to deforestation and peatland degradation, were 3.5 Gt CO2 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 CO2 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 CO2 (3.9 Gt CO2 yr−1), preceding land use change (3.3 Gt CO2 yr−1) and farm gate (1.2 Gt CO2 yr−1) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 Mt CH4 yr−1) and of nitrous oxide (7.8 Mt N2O yr−1). Pre- and post-production processes were also significant emitters of methane (49 Mt CH4 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 CO2 eq. yr−1). They also more than doubled in non-Annex I parties (to 3.5 Gt CO2 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 CO2 eq. yr−1), the USA (700 Mt CO2 eq. yr−1) and the EU-27 (600 Mt CO2 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-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/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.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2475469-9
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  • 6
    In: Earth System Science Data, Copernicus GmbH, Vol. 14, No. 10 ( 2022-10-18), p. 4551-4568
    Abstract: Abstract. Excessive anthropogenic nitrogen (N) inputs to the biosphere have disrupted the global nitrogen cycle. To better quantify the spatial and temporal patterns of anthropogenic N inputs, assess their impacts on the biogeochemical cycles of the planet and the living organisms, and improve nitrogen use efficiency (NUE) for sustainable development, we have developed a comprehensive and synthetic dataset for reconstructing the History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere. The HaNi dataset takes advantage of different data sources in a spatiotemporally consistent way to generate a set of high-resolution gridded N input products from the preindustrial period to the present (1860–2019). The HaNi dataset includes annual rates of synthetic N fertilizer, manure application/deposition, and atmospheric N deposition on cropland, pasture, and rangeland at a spatial resolution of 5 arcmin × 5 arcmin. Specifically, the N inputs are categorized, according to the N forms and land uses, into 10 types: (1) NH4+-N fertilizer applied to cropland, (2) NO3--N fertilizer applied to cropland, (3) NH4+-N fertilizer applied to pasture, (4) NO3--N fertilizer applied to pasture, (5) manure N application on cropland, (6) manure N application on pasture, (7) manure N deposition on pasture, (8) manure N deposition on rangeland, (9) NHx-N deposition, and (10) NOy-N deposition. The total anthropogenic N (TN) inputs to global terrestrial ecosystems increased from 29.05 Tg N yr−1 in the 1860s to 267.23 Tg N yr−1 in the 2010s, with the dominant N source changing from atmospheric N deposition (before the 1900s) to manure N (in the 1910s–2000s) and then to synthetic fertilizer in the 2010s. The proportion of synthetic NH4+-N in fertilizer input increased from 64 % in the 1960s to 90 % in the 2010s, while synthetic NO3--N fertilizer decreased from 36 % in the 1960s to 10 % in the 2010s. Hotspots of TN inputs shifted from Europe and North America to East and South Asia during the 1960s–2010s. Such spatial and temporal dynamics captured by the HaNi dataset are expected to facilitate a comprehensive assessment of the coupled human–Earth system and address a variety of social welfare issues, such as the climate–biosphere feedback, air pollution, water quality, and biodiversity. The data are available at https://doi.org/10.1594/PANGAEA.942069 (Tian et al., 2022).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2475469-9
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  • 7
    In: Nature Food, Springer Science and Business Media LLC, Vol. 4, No. 9 ( 2023-09-21), p. 736-737
    Type of Medium: Online Resource
    ISSN: 2662-1355
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3002034-7
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  • 8
    Online Resource
    Online Resource
    Copernicus GmbH ; 2023
    In:  Earth System Science Data Vol. 15, No. 11 ( 2023-11-15), p. 4997-5015
    In: Earth System Science Data, Copernicus GmbH, Vol. 15, No. 11 ( 2023-11-15), p. 4997-5015
    Abstract: Abstract. We describe a new dataset of cropland area circa the year 2020, with global coverage and with data for 221 countries and territories and 34 regional aggregates. Data are generated from geospatial information on the agreement–disagreement characteristics of six open-access high-resolution cropland maps derived from remote sensing. The cropland area mapping (CAM) aggregation dataset provides information on (i) mean cropland area and its uncertainty, (ii) cropland area by six distinct cropland agreement classes, and (iii) cropland area by specific combinations of underlying land cover product. The results indicated that world cropland area is 1500 ± 400 Mha (mean and 95 % confidence interval), with a relative uncertainty of 25 % that increased across regions. It was 50 % in Central Asia (40 ± 20 Mha), South America (180 ± 80 Mha), and Southern Europe (40 ± 20 Mha) and up to 40 % in Australia and New Zealand (50 ± 20 Mha), Southeastern Asia (80 ± 30 Mha), and Southern Africa (16 ± 6 Mha). Conversely, cropland area was estimated with better precision, i.e., smaller uncertainties in the range 10 %–25 % in Southern Asia (230 ± 30 Mha), Northern America (200 ± 40 Mha), Northern Africa (40 ± 10 Mha), and Eastern Europe and Western Europe (40 ± 10 Mha). The new data can be used to investigate the coherence of information across the six underlying products, as well as to explore important disagreement features. Overall, 70 % or more of the estimated mean cropland area globally and by region corresponded to good agreement of underlying land cover maps – four or more. Conversely, in Africa cropland area estimates found significant disagreement, highlighting mapping difficulties in complex landscapes. Finally, the new cropland area data were consistent with FAOSTAT (FAO, 2023) in 15 out of 18 world regions, as well as for 114 out of 182 countries with a cropland area above 10 kha. By helping to highlight features of cropland characteristics and underlying causes for agreement–disagreement across land cover products, the CAM aggregation dataset may be used as a reference for the quality of country statistics and may help guide future mapping efforts towards improved agricultural monitoring. Data are publicly available at https://doi.org/10.5281/zenodo.7987515 (Tubiello et al., 2023a).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2475469-9
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  • 9
    Online Resource
    Online Resource
    Copernicus GmbH ; 2020
    In:  Earth System Science Data Vol. 12, No. 4 ( 2020-12-03), p. 3113-3137
    In: Earth System Science Data, Copernicus GmbH, Vol. 12, No. 4 ( 2020-12-03), p. 3113-3137
    Abstract: Abstract. Drainage of large areas with organic soils was conducted over the past century to free up land for agriculture. A significant acceleration of such trends was observed in recent decades in Southeast Asia, largely driven by drainage of tropical peatlands, an important category of organic soils, for cultivation of oil palm. This work presents the methods and main results of a new methodology developed for FAOSTAT, whereby the overlay of dynamic maps of land cover and the use of information about histosols allows the production of a global annual dataset of drained area and emissions over a time series, covering the period 1990–2019. This is an improvement over the existing FAO approach, which had produced only a static map of drained organic soils for the year 2000. Results indicate that drained area and emissions increased by 13 % globally since 1990, reaching 24 million hectares in 2019 of drained organic soils, with world total emissions of 830 Mt of carbon dioxide (CO2) equivalent. Of these totals, the largest contribution was from the drainage of tropical peatlands in Southeast Asia, generating nearly half of global emissions. Results were validated against national data reported by countries to the UN Climate Convention and against the well-established literature. Overall, the validation yielded a good agreement with these sources. FAOSTAT estimates explained about 60 % of the variability in official country-reported data. The predicted emissions were virtually identical – with over 90 % of explained variability – to official data from Indonesia, currently the top emitting country by drained organic soils. Also, calculated emissions factors for oil palm plantations in Indonesia and Malaysia were in the same range and very close to emissions factors derived from detailed field measurements. This validation suggests that the FAO estimates may be a useful and sound reference in support of countries reporting needs. Data are made available through open access via the Zenodo portal (Tubiello and Conchedda, 2020) with the following DOI: https://doi.org/10.5281/zenodo.3942370.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2475469-9
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  • 10
    In: Earth System Science Data, Copernicus GmbH, Vol. 14, No. 10 ( 2022-10-20), p. 4643-4666
    Abstract: Abstract. Despite an increasing attention on the role of land in meeting countries' climate pledges under the Paris Agreement, the range of estimates of carbon fluxes from land use, land-use change, and forestry (LULUCF) in available databases is very large. A good understanding of the LULUCF data reported by countries under the United Nations Framework Convention on Climate Change (UNFCCC) – and of the differences with other datasets based on country-reported data – is crucial to increase confidence in land-based climate change mitigation efforts. Here we present a new data compilation of LULUCF fluxes of carbon dioxide (CO2) on managed land, aiming at providing a consolidated view on the subject. Our database builds on a detailed analysis of data from national greenhouse gas inventories (NGHGIs) communicated via a range of country reports to the UNFCCC, which report anthropogenic emissions and removals based on the IPCC (Intergovernmental Panel on Climate Change) methodology. Specifically, for Annex I countries, data are sourced from annual GHG inventories. For non-Annex I countries, we compiled the most recent and complete information from different sources, including national communications, biennial update reports, submissions to the REDD+ (reducing emissions from deforestation and forest degradation) framework, and nationally determined contributions. The data are disaggregated into fluxes from forest land, deforestation, organic soils, and other sources (including non-forest land uses). The CO2 flux database is complemented by information on managed and unmanaged forest area as available in NGHGIs. To ensure completeness of time series, we filled the gaps without altering the levels and trends of the country reported data. Expert judgement was applied in a few cases when data inconsistencies existed. Results indicate a mean net global sink of −1.6 Gt CO2 yr−1 over the period 2000–2020, largely determined by a sink on forest land (−6.4 Gt CO2 yr−1), followed by source from deforestation (+4.4 Gt CO2 yr−1), with smaller fluxes from organic soils (+0.9 Gt CO2 yr−1) and other land uses (−0.6 Gt CO2 yr−1). Furthermore, we compare our NGHGI database with two other sets of country-based data: those included in the UNFCCC GHG data interface, and those based on forest resources data reported by countries to the Food and Agriculture Organization of the United Nations (FAO) and used as inputs into estimates of GHG emissions in FAOSTAT. The first dataset, once gap filled as in our study, results in a net global LULUCF sink of −5.4 Gt CO2 yr−1. The difference with the NGHGI database is in this case mostly explained by more updated and comprehensive data in our compilation for non-Annex I countries. The FAOSTAT GHG dataset instead estimates a net global LULUCF source of +1.1 Gt CO2 yr−1. In this case, most of the difference to our results is due to a much greater forest sink for non-Annex I countries in the NGHGI database than in FAOSTAT. The difference between these datasets can be mostly explained by a more complete coverage in the NGHGI database, including for non-biomass carbon pools and non-forest land uses, and by different underlying data on forest land. The latter reflects the different scopes of the country reporting to FAO, which focuses on area and biomass, and to UNFCCC, which explicitly focuses on carbon fluxes. Bearing in mind the respective strengths and weaknesses, both our NGHGI database and FAO offer a fundamental, yet incomplete, source of information on carbon-related variables for the scientific and policy communities, including under the Global stocktake. Overall, while the quality and quantity of the LULUCF data submitted by countries to the UNFCCC significantly improved in recent years, important gaps still remain. Most developing countries still do not explicitly separate managed vs. unmanaged forest land, a few report implausibly high forest sinks, and several report incomplete estimates. With these limits in mind, the NGHGI database presented here represents the most up-to-date and complete compilation of LULUCF data based on country submissions to UNFCCC. Data from this study are openly available via the Zenodo portal (Grassi et al., 2022), at https://doi.org/10.5281/zenodo.7190601.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2475469-9
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