ALBERT

Description: Given the important role of nitrogen input from livestock systems in terrestrial nutrient cycles and the atmospheric chemical composition, it is vital to have a robust estimation of the magnitude and spatiotemporal variation in manure nitrogen production and its application to cropland across the globe. In this study, we used the dataset from the Global Livestock Impact Mapping System (GLIMS) in conjunction with country-specific annual livestock populations to reconstruct the manure nitrogen production during 1860-2014. The estimated manure nitrogen production increased from 21.4 Tg N/yr in 1860 to 131.0 Tg N/yr in 2014 with a significant annual increasing trend (0.7 Tg N/ yr, p 〈 0.01). Changes in manure nitrogen production exhibited high spatial variability and concentrated in several hotspots (e.g., Western Europe, India, northeastern China, and southeastern Australia) across the globe over the study period. In the 1860s, the northern midlatitude region was the largest manure producer, accounting for ~52 % of the global total, while low-latitude regions became the largest share (~48 %) in the most recent 5 years (2010-2014). Among all the continents, Asia accounted for over one-fourth of the global manure production during 1860-2014. Cattle dominated the manure nitrogen production and contributed ~44 % of the total manure nitrogen production in 2014, followed by goats, sheep, swine, and chickens. The manure nitrogen application to cropland accounts for less than one-fifth of the total manure nitrogen production over the study period. The 5 arcmin gridded global dataset of manure nitrogen production generated from this study could be used as an input for global or regional land surface and ecosystem models to evaluate the impacts of manure nitrogen on key biogeochemical processes and water quality. To ensure food security and environmental sustainability, it is necessary to implement proper manure management practices on cropland across the globe.

Description: Livestock manure, as recyclable sources for nitrogen (N) and phosphorus (P) in the Soil-Plant-Animal system, plays an important role in nutrient cycling. Given the agricultural benefits and environmental pollutions brought by manure, it is of great importance to estimate the spatial variations and temporal trajectories of manure production and its application in croplands of the continental United States (U.S.). Here, we developed datasets of annual animal manure N and P production and application in the continental U.S. at a 30 arc-second resolution over the period of 1860-2017. The total production of manure N and P increased from 1.4 Tg N yr-1 and 0.3 Tg P yr-1 in 1860 to 7.4 Tg N yr-1 and 2.3 Tg P yr-1 in 2017. The increasing manure nutrient production was associated with increased livestock numbers before the 1980s and enhanced livestock weights after the 1980s. The high-nutrient region mainly enlarged from the Midwest toward the Southern U.S., and became more concentrated in numerous hot spots after the 1980s. The South Atlantic-Gulf and Mid-Atlantic basins were the two critical coastal regions with high environmental risks due to the enrichment of manure nutrient production and application from the 1970s to 2010s. Our long-term manure N and P datasets provide critical information for national and regional assessments of nutrient budgets and can also serve as the input data for ecosystem and hydrological models to examine biogeochemical cycles in terrestrial and aquatic ecosystems.

Description: Production and application to soils of manure excreta from livestock production significantly perturb the global nutrient balance and result in significant greenhouse gas emissions that warm the earth's climate. Despite much attention paid to synthetic nitrogen (N) fertilizer and manure N applications to croplands, spatially-explicit, continuous time-series datasets of manure and fertilizer N inputs on pastures and rangelands are lacking. We developed three global gridded datasets at a resolution of 0.5 degree by 0.5 degree for the period 1860-2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer and N manure application rates), by combining annual and 5-arc minute spatial data on pastures and rangelands with country-level statistics on livestock manure, mineral and chemical fertilizers, and land use information for cropland and permanent meadows and pastures from the Food and Agricultural Organization database (FAOSTAT). Based on the new data products, we estimated that total N inputs, sum of manure N deposition, manure and fertilizer N application to pastures and rangelands increased globally from 15 to 101 Tg N yr-1 during 1860-2016. In particular during the period 2000-2016, livestock manure N deposition accounted for 83% of the total N inputs, whereas manure and fertilizer N application accounted 9% and 8%, respectively. At the regional scale, hotspots of manure N deposition remained largely similar during the period 1860-2016 (i.e., southern Asia, Africa, and South America), however hotspots of manure and fertilizer N application shifted from Europe to southern Asia in the early 21st century. The new three global datasets contribute to fill previous data gaps of global and regional N inputs in pastures and rangelands, improving the ability of ecosystem and biogeochemistry models to investigate the global impacts of N enrichment due to agriculture, in terms of associated greenhouse gas emissions and environmental sustainability issues.

Description: 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 enrichments, assess their impacts on the biogeochemical cycles of the planet and other living organisms, and improve nitrogen use efficiency (NUE) for sustainable development, we develop a comprehensive and synthetic dataset for anthropogenic N inputs to the terrestrial biosphere. This Harmonized Anthropogenic N Inputs (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 to present (1860-2019). The HaNi dataset includes annual rates of synthetic N fertilizer, manure application/deposition, and atmospheric N deposition in cropland, pasture, and rangeland at 5-arcmin. Specifically, the N inputs are categorized, according to the N forms and the land use, as 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 (the 1910s-2000s), and to synthetic fertilizer in the 2010s. The proportion of synthetic NH4-N fertilizer 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 climate-biosphere feedback, air pollution, water quality, and biodiversity.

Description: 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 (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (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 top-down inversions at 558 TgCH4 yr􀀀1, range 540–568. About 60% of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH4 yr􀀀1, range 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 top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions ( 64% of the global budget, 〈 30 N) as compared to mid ( 32 %, 30–60 N) and high northern latitudes ( 4 %, 60–90 N). Top-down inversions consistently infer lower emissions in China ( 58 TgCH4 yr􀀀1, range 51–72, 􀀀14 %) and higher emissions in Africa (86 TgCH4 yr􀀀1, range 73–108, C19 %) than bottom-up 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 top-down inversions than for bottom-up 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 30–40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Description: Published

Description: 697–751

Description: 6A. Geochimica per l'ambiente

Description: JCR Journal

Description: Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4/ budget over 2000– 2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from topdown studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches.The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr􀀀1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all topdown studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

Description: Published

Description: 11135–11161

Description: 6A. Geochimica per l'ambiente

Description: JCR Journal

Description: Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 531 (2016): 225-228, doi:10.1038/nature16946.

Description: The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and therefore plays an important role in regulating atmospheric composition and climate1. Anthropogenic activities such as land use change, agricultural and waste management have altered terrestrial biogenic greenhouse gas fluxes and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate warming2,3. The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively4-6, but the net biogenic greenhouse gas balance as a result of anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (BU: e.g., inventory, statistical extrapolation of local flux measurements, process-based modeling) and top-down (TD: atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981-2010 as a result of anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic CH4 and N2O emissions is about a factor of 2 larger than the cooling effect resulting from the global land CO2 uptake in the 2000s. This results in a net positive cumulative impact of the three GHGs on the planetary energy budget, with a best estimate of 3.9±3.8 Pg CO2 eq/yr (TD) and 5.4±4.8 Pg CO2 eq/yr (BU) based on the GWP 100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural CH4 and N2O emissions in particular in Southern Asia may help mitigate climate change.

Description: This research has been supported partially by National Aeronautics and 255 Space Administration (NASA) Grants (NNX08AL73G, NNX14AO73G, NNX10AU06G, NNX11AD47G, NNG04GM39C), National Science Foundation (NSF) Grants (CNH1210360; AGS 1243232; AGS-1243220). JGC was supported by the Australian Climate Change Science Program. ES was supported by NOAA Climate Program Office (award # NA13OAR4310059). CRS was supported by NASA Grants (#NNX12AP74G, #NNX10AG01A, and #NNX11AO08A). KRG was supported by NSF CAREER (AGS-0846358). RGP was supported by NASA Upper Atmosphere Research Program AGAGE Grant (NNX11AF17G to MIT).

Description: 2016-09-09