Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 ...lockdowns(1). Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr−1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr−1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr−1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns(2). From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr−1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr−1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings(3,4,) our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge(5).
Our understanding and quantification of global soil nitrous oxide (N2O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and ...natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO2 concentration, on global soil N2O emissions for the period 1861–2016 using a standard simulation protocol with seven process‐based terrestrial biosphere models. Results suggest global soil N2O emissions have increased from 6.3 ± 1.1 Tg N2O‐N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N2O‐N/year in the recent decade (2007–2016). Cropland soil emissions increased from 0.3 Tg N2O‐N/year to 3.3 Tg N2O‐N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N2O emissions since the 1970s. However, US cropland N2O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N2O emissions appear to have decreased by 14%. Soil N2O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N2O‐N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO2 concentration reduced soil N2O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N2O emissions, this study recommends several critical strategies for improving the process‐based simulations.
The ensemble of terrestrial biosphere models indicates that global soil N2O emissions have increased from 6.3 ± 1.1 Tg N2O‐N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N2O‐N/year in the recent decade (2007–2016). Cropland soil emissions increased from 0.3 Tg N2O‐N/year to 3.3 Tg N2O‐N/year over the same period, accounting for 82% of the total increase, among which 54% attributes to nitrogen fertilizer application. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N2O emissions since the 1970s. However, European cropland N2O emissions appear to have decreased by 14%.
The Lagrangian particle dispersion model FLEXPART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point ...sources, such as those released after an accident in a nuclear power plant.
Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community.
Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash,
and it has also been used to study the atmospheric branch of the water cycle.
Given suitable meteorological input data, it can be used for scales from dozens of meters to global.
In particular, inverse modeling based on source–receptor relationships from FLEXPART has become widely used.
In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS).
Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software.
The model code has also been parallelized using the Message Passing Interface (MPI).
We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles.
The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup.
A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density.
FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source.
The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented.
FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for
many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements.
To our knowledge, to date FLEXPART is the only model with that capability.
Furthermore, the temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing for more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane.
Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format.
In this paper, we describe these new developments.
Moreover, we present some tools for the preparation of the meteorological input data and for processing FLEXPART output data, and we briefly report on alternative FLEXPART versions.
Nitrous oxide (N
O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N
O concentrations have contributed to ...stratospheric ozone depletion
and climate change
, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N
O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N
O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N
O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N
O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N
O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N
O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N
O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N
O emissions exceeds some of the highest projected emission scenarios
, underscoring the urgency to mitigate N
O emissions.
THE GLOBAL N₂O MODEL INTERCOMPARISON PROJECT Tian, Hanqin; Yang, Jia; Lu, Chaoqun ...
Bulletin of the American Meteorological Society,
06/2018, Letnik:
99, Številka:
6
Journal Article
Recenzirano
Odprti dostop
Nitrous oxide (N₂O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and ...spatiotemporal patterns of N₂O fluxes and the key drivers of N₂O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N₂O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N₂O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N₂O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N₂O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N₂O dynamics; and 3) provide a benchmarking estimate of N₂O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N₂O estimation derived from the NMIP is a key component of the global N₂O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative.
We present methane (CH4) flux estimates for 2005 to 2013 from a Bayesian inversion focusing on the high northern latitudes (north of 50° N). Our inversion is based on atmospheric transport modelled ...by the Lagrangian particle dispersion model FLEXPART and CH4 observations from 17 in situ and five discrete flask-sampling sites distributed over northern North America and Eurasia. CH4 fluxes are determined at monthly temporal resolution and on a variable grid with maximum resolution of 1° × 1°. Our inversion finds a CH4 source from the high northern latitudes of 82 to 84 Tg yr−1, constituting ∼ 15 % of the global total, compared to 64 to 68 Tg yr−1 (∼ 12 %) in the prior estimates. For northern North America, we estimate a mean source of 16.6 to 17.9 Tg yr−1, which is dominated by fluxes in the Hudson Bay Lowlands (HBL) and western Canada, specifically the province of Alberta. Our estimate for the HBL, of 2.7 to 3.4 Tg yr−1, is close to the prior estimate (which includes wetland fluxes from the land surface model, LPX-Bern) and to other independent inversion estimates. However, our estimate for Alberta, of 5.0 to 5.8 Tg yr−1, is significantly higher than the prior (which also includes anthropogenic sources from the EDGAR-4.2FT2010 inventory). Since the fluxes from this region persist throughout the winter, this may signify that the anthropogenic emissions are underestimated. For northern Eurasia, we find a mean source of 52.2 to 55.5 Tg yr−1, with a strong contribution from fluxes in the Western Siberian Lowlands (WSL) for which we estimate a source of 19.3 to 19.9 Tg yr−1. Over the 9-year inversion period, we find significant year-to-year variations in the fluxes, which in North America, and specifically in the HBL, appear to be driven at least in part by soil temperature, while in the WSL, the variability is more dependent on soil moisture. Moreover, we find significant positive trends in the CH4 fluxes in North America of 0.38 to 0.57 Tg yr−2, and northern Eurasia of 0.76 to 1.09 Tg yr−2. In North America, this could be due to an increase in soil temperature, while in North Eurasia, specifically Russia, the trend is likely due, at least in part, to an increase in anthropogenic sources.
Key Points
Reducing methane emissions is key to limiting warming to 1.5 or 2.0°C in emission pathways to 2050
The climate response of wetland methane emissions is an important uncertainty in how much ...anthropogenic emissions will need to be reduced
Atmospheric observations and inverse modeling are crucial to monitoring emission reduction measures and changes in wetland emissions
A novel method for atmospheric network design is presented, which is based on information theory. The method does not require
calculation of the posterior uncertainty (or uncertainty reduction) and ...is
therefore computationally more efficient than methods that require this. The algorithm is demonstrated in two examples: the first looks at designing a network for monitoring CH4 sources using observations of the stable carbon isotope ratio in CH4 (δ13C), and the second looks at designing a network for monitoring fossil fuel emissions of CO2 using observations of the radiocarbon isotope ratio in CO2 (Δ14CO2).
This paper presents the results of BC inversions at high northern latitudes (> 50° N) for the 2013-2015 period. A sensitivity analysis was performed to select the best representative species for BC ...and the best a priori emission dataset. The same model ensemble was used to assess the uncertainty of the a posteriori emissions of BC due to scavenging and removal and due to the use of different a priori emission inventory. A posteriori concentrations of BC simulated over Arctic regions were compared with independent observations from flight and ship campaigns showing, in all cases, smaller bias, which in turn witnesses the success of the inversion. The annual a posteriori emissions of BC at latitudes above 50° N were estimated as 560±171 kt yr.sup.-1, significantly smaller than in ECLIPSEv5 (745 kt yr.sup.-1 ), which was used and the a priori information in the inversions of BC. The average relative uncertainty of the inversions was estimated to be 30 %.
Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO.sub.2 into the atmosphere. The development of dense in situ surface ...observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006-2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale.
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