Joint Research Centre

Abstract. The present paper reviews existing knowledge with regard to Organic Aerosol (OA) of importance for global climate modelling and defines critical gaps needed to reduce the involved uncertainties. All pieces required for the representation of OA in a global climate model are sketched out with special attention to Secondary Organic Aerosol (SOA): The emission estimates of primary carbonaceous particles and SOA precursor gases are summarized. The up-to-date understanding of the chemical formation and transformation of condensable organic material is outlined. Knowledge on the hygroscopicity of OA and measurements of optical properties of the organic aerosol constituents are summarized. The mechanisms of interactions of OA with clouds and dry and wet removal processes parameterisations in global models are outlined. This information is synthesized to provide a continuous analysis of the flow from the emitted material to the atmosphere up to the point of the climate impact of the produced organic aerosol. The sources of uncertainties at each step of this process are highlighted as areas that require further studies.

Carbon Cycle and Climate Change As climate change accelerates, it is important to know the likely impact of climate change on the carbon cycle (see the Perspective by Reich ). Gross primary production (GPP) is a measure of the amount of CO 2 removed from the atmosphere every year to fuel photosynthesis. Beer et al. (p. 834 , published online 5 July) used a combination of observation and calculation to estimate that the total GPP by terrestrial plants is around 122 billion tons per year; in comparison, burning fossil fuels emits about 7 billion tons annually. Thirty-two percent of this uptake occurs in tropical forests, and precipitation controls carbon uptake in more than 40% of vegetated land. The temperature sensitivity (Q10) of ecosystem respiratory processes is a key determinant of the interaction between climate and the carbon cycle. Mahecha et al. (p. 838 , published online 5 July) now show that the Q10 of ecosystem respiration is invariant with respect to mean annual temperature, independent of the analyzed ecosystem type, with a global mean value for Q10 of 1.6. This level of temperature sensitivity suggests a less-pronounced climate sensitivity of the carbon cycle than assumed by recent climate models.

Atmospheric nitrogen (N) deposition is a recognized threat to plant diversity in temperate and northern parts of Europe and North America. This paper assesses evidence from field experiments for N deposition effects and thresholds for terrestrial plant diversity protection across a latitudinal range of main categories of ecosystems, from arctic and boreal systems to tropical forests. Current thinking on the mechanisms of N deposition effects on plant diversity, the global distribution of G200 ecoregions, and current and future (2030) estimates of atmospheric N-deposition rates are then used to identify the risks to plant diversity in all major ecosystem types now and in the future. This synthesis paper clearly shows that N accumulation is the main driver of changes to species composition across the whole range of different ecosystem types by driving the competitive interactions that lead to composition change and/or making conditions unfavorable for some species. Other effects such as direct toxicity of nitrogen gases and aerosols, long-term negative effects of increased ammonium and ammonia availability, soil-mediated effects of acidification, and secondary stress and disturbance are more ecosystem- and site-specific and often play a supporting role. N deposition effects in mediterranean ecosystems have now been identified, leading to a first estimate of an effect threshold. Importantly, ecosystems thought of as not N limited, such as tropical and subtropical systems, may be more vulnerable in the regeneration phase, in situations where heterogeneity in N availability is reduced by atmospheric N deposition, on sandy soils, or in montane areas. Critical loads are effect thresholds for N deposition, and the critical load concept has helped European governments make progress toward reducing N loads on sensitive ecosystems. More needs to be done in Europe and North America, especially for the more sensitive ecosystem types, including several ecosystems of high conservation importance. The results of this assessment show that the vulnerable regions outside Europe and North America which have not received enough attention are ecoregions in eastern and southern Asia (China, India), an important part of the mediterranean ecoregion (California, southern Europe), and in the coming decades several subtropical and tropical parts of Latin America and Africa. Reductions in plant diversity by increased atmospheric N deposition may be more widespread than first thought, and more targeted studies are required in low background areas, especially in the G200 ecoregions.

Abstract Human activity and related land use change are the primary cause of accelerated soil erosion, which has substantial implications for nutrient and carbon cycling, land productivity and in turn, worldwide socio-economic conditions. Here we present an unprecedentedly high resolution (250 × 250 m) global potential soil erosion model, using a combination of remote sensing, GIS modelling and census data. We challenge the previous annual soil erosion reference values as our estimate, of 35.9 Pg yr −1 of soil eroded in 2012, is at least two times lower. Moreover, we estimate the spatial and temporal effects of land use change between 2001 and 2012 and the potential offset of the global application of conservation practices. Our findings indicate a potential overall increase in global soil erosion driven by cropland expansion. The greatest increases are predicted to occur in Sub-Saharan Africa, South America and Southeast Asia. The least developed economies have been found to experience the highest estimates of soil erosion rates.

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric\nlifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).\nFor the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 TgCH4 yr-1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 TgCH4 yr-1 or 60% is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 TgCH4 yr-1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 TgCH4 yr-1 larger than our estimate for the previous decade (2000–2009), and 24 TgCH4 yr-1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30% larger global emissions (737 TgCH4 yr-1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼65% of the global budget, <30◦N) compared to mid-latitudes (∼30 %, 30–60◦ N) and high northern latitudes (∼4 %, 60–90◦N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.\nSome of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 TgCH4 yr-1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 TgCH4 yr-1 by 8 TgCH4 yr-1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5% compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.\nThe data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al.,\n2020) and from the Global Carbon Project

This Handbook aims to provide a guide for constructing and using composite indicators for policy makers, academics, the media and other interested parties. While there are several types of composite indicators, this Handbook is concerned with those which compare and rank country performance in areas such as industrial competitiveness, sustainable development, globalisation and innovation. The Handbook aims to contribute to a better understanding of the complexity of composite indicators and to an improvement of the techniques currently used to build them. In particular, it contains a set of technical guidelines that can help constructors of composite indicators to improve the quality of their outputs. It has been prepared jointly by the OECD (the Statistics Directorate and the Directorate for Science, Technology and Industry) and the Applied Statistics and Econometrics Unit of the Joint Research Centre of the European Commission in Ispra, Italy. Primary authors from the JRC are Michela Nardo, Michaela Saisana, Andrea Saltelli and Stefano Tarantola. Primary authors from the OECD are Anders Hoffmann and Enrico Giovannini. Editorial assistance was provided by Candice Stevens, Gunseli Baygan and Karsten Olsen. The research is partly funded by the European Commission, Research Directorate, under the project KEI (Knowledge Economy Indicators), Contract FP6 No. 502529. In the OECD context, the work has benefitted from a grant from the Danish government. The views expressed are those of the authors and should not be regarded as stating an official position of either the European Commission or the OECD.

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Abstract. The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks.

Consolidated tables showing an extensive listing of the highest independently confirmed efficiencies for solar cells and modules are presented. Guidelines for inclusion of results into these tables are outlined and new entries since July 2014 are reviewed. Copyright © 2014 John Wiley & Sons, Ltd.

Abstract. We present and discuss a new dataset of gridded emissions covering the historical period (1850–2000) in decadal increments at a horizontal resolution of 0.5° in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models are used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.

Abstract. We present a new data set of annual historical (1750–2014) anthropogenic chemically reactive gases (CO, CH4, NH3, NOx, SO2, NMVOCs), carbonaceous aerosols (black carbon – BC, and organic carbon – OC), and CO2 developed with the Community Emissions Data System (CEDS). We improve upon existing inventories with a more consistent and reproducible methodology applied to all emission species, updated emission factors, and recent estimates through 2014. The data system relies on existing energy consumption data sets and regional and country-specific inventories to produce trends over recent decades. All emission species are consistently estimated using the same activity data over all time periods. Emissions are provided on an annual basis at the level of country and sector and gridded with monthly seasonality. These estimates are comparable to, but generally slightly higher than, existing global inventories. Emissions over the most recent years are more uncertain, particularly in low- and middle-income regions where country-specific emission inventories are less available. Future work will involve refining and updating these emission estimates, estimating emissions' uncertainty, and publication of the system as open-source software.

Free-flowing rivers (FFRs) support diverse, complex and dynamic ecosystems globally, providing important societal and economic services. Infrastructure development threatens the ecosystem processes, biodiversity and services that these rivers support. Here we assess the connectivity status of 12 million kilometres of rivers globally and identify those that remain free-flowing in their entire length. Only 37 per cent of rivers longer than 1,000 kilometres remain free-flowing over their entire length and 23 per cent flow uninterrupted to the ocean. Very long FFRs are largely restricted to remote regions of the Arctic and of the Amazon and Congo basins. In densely populated areas only few very long rivers remain free-flowing, such as the Irrawaddy and Salween. Dams and reservoirs and their up- and downstream propagation of fragmentation and flow regulation are the leading contributors to the loss of river connectivity. By applying a new method to quantify riverine connectivity and map FFRs, we provide a foundation for concerted global and national strategies to maintain or restore them.

urban populations. We begin by defining the state of the art, explaining the science of smart cities. We define six scenarios based on new cities badging themselves as smart, older cities regenerating themselves as smart, the development of science parks, tech cities, and technopoles focused on high technologies, the development of urban services using contemporary ICT, the use of ICT to develop new urban intelligence functions, and the development of online and mobile forms of participation. Seven project areas are then proposed: Integrated Databases for the Smart City, Sensing, Networking and the Impact of New Social Media, Modelling Network Performance, Mobility and Travel Behaviour, Modelling Urban Land Use, Transport and Economic Interactions, Modelling Urban Transactional Activities in Labour and Housing Markets, Decision Support as Urban Intelligence, Participatory Governance and Planning Structures for the Smart City. Finally we anticipate the paradigm shifts that will occur in this research and define a series of key demonstrators which we believe are important to progressing a science of smart cities.

Global nitrogen fixation contributes 413 Tg of reactive nitrogen (Nr) to terrestrial and marine ecosystems annually of which anthropogenic activities are responsible for half, 210 Tg N. The majority of the transformations of anthropogenic Nr are on land (240 Tg N yr(-1)) within soils and vegetation where reduced Nr contributes most of the input through the use of fertilizer nitrogen in agriculture. Leakages from the use of fertilizer Nr contribute to nitrate (NO3(-)) in drainage waters from agricultural land and emissions of trace Nr compounds to the atmosphere. Emissions, mainly of ammonia (NH3) from land together with combustion related emissions of nitrogen oxides (NOx), contribute 100 Tg N yr(-1) to the atmosphere, which are transported between countries and processed within the atmosphere, generating secondary pollutants, including ozone and other photochemical oxidants and aerosols, especially ammonium nitrate (NH4NO3) and ammonium sulfate (NH4)2SO4. Leaching and riverine transport of NO3 contribute 40-70 Tg N yr(-1) to coastal waters and the open ocean, which together with the 30 Tg input to oceans from atmospheric deposition combine with marine biological nitrogen fixation (140 Tg N yr(-1)) to double the ocean processing of Nr. Some of the marine Nr is buried in sediments, the remainder being denitrified back to the atmosphere as N2 or N2O. The marine processing is of a similar magnitude to that in terrestrial soils and vegetation, but has a larger fraction of natural origin. The lifetime of Nr in the atmosphere, with the exception of N2O, is only a few weeks, while in terrestrial ecosystems, with the exception of peatlands (where it can be 10(2)-10(3) years), the lifetime is a few decades. In the ocean, the lifetime of Nr is less well known but seems to be longer than in terrestrial ecosystems and may represent an important long-term source of N2O that will respond very slowly to control measures on the sources of Nr from which it is produced.

A recently completed research program (TREES) employing the global imaging capabilities of Earth-observing satellites provides updated information on the status of the world's humid tropical forest cover. Between 1990 and 1997, 5.8 +/- 1.4 million hectares of humid tropical forest were lost each year, with a further 2.3 +/- 0.7 million hectares of forest visibly degraded. These figures indicate that the global net rate of change in forest cover for the humid tropics is 23% lower than the generally accepted rate. This result affects the calculation of carbon fluxes in the global budget and means that the terrestrial sink is smaller than previously inferred.

Abstract A new global land cover database for the year 2000 (GLC2000) has been produced by an international partnership of 30 research groups coordinated by the European Commission's Joint Research Centre. The database contains two levels of land cover information—detailed, regionally optimized land cover legends for each continent and a less thematically detailed global legend that harmonizes regional legends into one consistent product. The land cover maps are all based on daily data from the VEGETATION sensor on‐board SPOT 4, though mapping of some regions involved use of data from other Earth observing sensors to resolve specific issues. Detailed legend definition, image classification and map quality assurance were carried out region by region. The global product was made through aggregation of these. The database is designed to serve users from science programmes, policy makers, environmental convention secretariats, non‐governmental organizations and development‐aid projects. The regional and global data are available free of charge for all non‐commercial applications from http://www.gvm.jrc.it/glc2000. Acknowledgements The JRC with the endorsement and support of the VEGETATION programme partners coordinated the GLC2000 project. The S1 data were kindly made available under the terms of the VEGA 2000 initiative. The involvement of all GLC2000 partners is gratefully acknowledged. The number in front of their name refers to the geographic window displayed in figure 1. A full list of individuals is provided in Bartholomé et al. (Citation2002). The authors are particularly indebted to the members of the Global Vegetation Unit of the JRC who contributed the GLC2000 project: F. Achard, S. Bartalev, C. Carmona‐Moreno, V. Gond, S. Kolmert, M. Massart, P. Mayaux, M. Merlotti, H. Eva, S. Fritz, B. Glénat, J.‐M. Grégoire, A. Hartley, H.‐J. Stibig, A. Tournier and P. Vogt. 1. (1) US Geological Survey, Sioux Falls, USA: T. Loveland, Z. Zhu, C. Giri.2. (1) Canadian Center for Remote Sensing, Ottawa, Canada: R. Latifovic.3. (10) Institute for Remote Sensing Applications, Beijing, China: Wu B, Xu W.4. (global) CNES, Toulouse, France: H. Jeanjean, G. Saint.5. (3) Lab. de teledeteccion aplicada, Univ. Nacional Agraria, La Molina, Peru: V. Barrena Arroyo.6. (global) VITO, Mol, Belgium: D. Van Speybroeck.7. (7) Centre AGRHYMET, Niamey, Niger: A. Nonguierma.8. (5c) METEO, Toulouse, France: J.‐L. Champeaux.9. (7, global) UNEP/GRID, Geneva, Switzerland: R. Witt, C. Ten Oever.10. (7) Centre de Suivi Ecologique, Dakar, Senegal: O. Diallo.11. (3) INTA, Castelar/Buenos Aires, Argentina: C. di Bella.12. (7) CSIR, Pretoria, South Africa: C. Pretorius.13. (global) Africover, Nairobi, Kenya: A. di Gregorio.14. (5b, 7) Environnemétrie et Géomatique Un. Cath., Louvain‐la‐Neuve, Belgium: P. Defourny, C. Vancutsem, J.‐F. Pekel.15. (3) Ecoforca: Campinas/Sao Paulo, Brazil: A. Dorado, E. de Miranda.16. (3) CIRAD, Forêts, Cayenne/Guyanne, France: V. Gond.17. (12) Institut Pertanian, Bogor, Indonesia: U. R. Wasrin.18. (9) Indian Institute for Remote Sensing, Dehradun UP, India: P. S. Roy, S. Gupta.19. (global, 17) FAO, Roma, Italy: He C. J. Latham, M. Cherlet.20. (8a) Alterra, Wageningen, The Netherland: C. A. Mucher, E. De Badts.21. (6) Metria, Stockholm, Sweden: S. Olovsson, B. Olsson, M. Ledwith.22. (3) Corolab Humboldt, Caracas, Venezuela: O. Huber.23. (5) Instituto de Sciencias de la tierra, Barcelona, Spain: A. Lobo.24. (11) CEReS, Chiba, Japan: R. Tateishi.25. (10) University of New Hampshire, Durham, USA: X. Xiao.26. (7) Tropical Research Institute, Lisbon, Portugal M. J. De Perestrelo, J. Pereira, A. I. Cabral.27. (14) Centre for Ecology and Productivity, Moscow, Russia: D. Ershov, A. Isaev.28. (5d) Dipartimento di Pianificazione, IUAV, Venice Italy, S. Griguolo.29. (3) CREAN, Cordoba, Argentina: A. C. Ravelo.30. (11) Geographical Survey Institute, Tsukuba, Japan: H. Sato.31. (10) Chinese Academy of Forestry, Beijing, China: Zhao X.32. (7) Royal Museum for Central Africa, Tervuren, Belgium: J. Lavreau.33. (7) Regional Centre for Mapping of Resources for Development, Nairobi, Kenya: W. K. Ottichilo.34. (7) Observatoire du Sahara et du Sahel, Tunis, Tunisia: C. Fezzani, W. Essahli.35. (5b) Instituto de Hidràulica, Engenharia Rural e Ambiente, Lisbon, Portugal: A. Perdigão.36. (Global, 2, 3, 4, 5d, 7, 8, 13, 15, 16, 17) Global vegetation Monitoring Unit/JRC, Ispra, Italy: E. Bartholomé, A. S. Belward, F. Achard, S. Bartalev, C. Carmona‐Moreno, H. Eva, S. Fritz, A. Hartley, P. Mayaux, H.‐J. Stibig.

Global demand for agricultural products such as food, feed, and fuel is now a major driver of cropland and pasture expansion across much of the developing world. Whether these new agricultural lands replace forests, degraded forests, or grasslands greatly influences the environmental consequences of expansion. Although the general pattern is known, there still is no definitive quantification of these land-cover changes. Here we analyze the rich, pan-tropical database of classified Landsat scenes created by the Food and Agricultural Organization of the United Nations to examine pathways of agricultural expansion across the major tropical forest regions in the 1980s and 1990s and use this information to highlight the future land conversions that probably will be needed to meet mounting demand for agricultural products. Across the tropics, we find that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This study underscores the potential consequences of unabated agricultural expansion for forest conservation and carbon emissions.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate is critical to better understand the global carboncycle, support the development of climate policies, and project futureclimate change. Here we describe and synthesize data sets and methodologies toquantify the five major components of the global carbon budget and theiruncertainties. Fossil CO2 emissions (EFOS) are based on energystatistics and cement production data, while emissions from land-use change(ELUC), mainly deforestation, are based on land use and land-use changedata and bookkeeping models. Atmospheric CO2 concentration is measureddirectly, and its growth rate (GATM) is computed from the annualchanges in concentration. The ocean CO2 sink (SOCEAN) is estimatedwith global ocean biogeochemistry models and observation-baseddata products. The terrestrial CO2 sink (SLAND) is estimated withdynamic global vegetation models. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, withfossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission(including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1(40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with aBIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low orsinks were too high). The global atmospheric CO2 concentration averaged over2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest anincrease in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %)globally and atmospheric CO2 concentration reaching 417.2 ppm, morethan 50 % above pre-industrial levels (around 278 ppm). Overall, the meanand trend in the components of the global carbon budget are consistentlyestimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadalvariability in CO2 fluxes. Comparison of estimates from multipleapproaches and observations shows (1) a persistent large uncertainty in theestimate of land-use change emissions, (2) a low agreement between thedifferent methods on the magnitude of the land CO2 flux in the northernextratropics, and (3) a discrepancy between the different methods on thestrength of the ocean sink over the last decade. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set. The data presented inthis work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

A new method for sensitivity analysis (SA) of model output is introduced. It is based on the Fourier amplitude sensitivity test (FAST) and allows the computation of the total contribution of each input factor to the output's variance. The term “total” here means that the factor's main effect, as well as all the interaction terms involving that factor, are included. Although computationally different, the very same measure of sensitivity is offered by the indices of Sobol'. The main advantages of the extended FAST are its robustness, especially at low sample size, and its computational efficiency. The computational aspects of the extended FAST are described. These include (1) the definition of new sets of parametric equations for the search-curve exploring the input space, (2) the selection of frequencies for the parametric equations, and (3) the procedure adopted to estimate the total contributions. We also address the limitations of other global SA methods and suggest that the total-effect indices are ideally suited to perform a global, quantitative, model-independent sensitivity analysis.