We present Δ14CO2 observations and related greenhouse gas measurements at a background site in Ireland (Mace Head, MHD) and a tall tower site in the east of the UK (Tacolneston, TAC) that is more ...strongly influenced by fossil fuel sources. These observations have been used to calculate the contribution of fossil fuel sources to the atmospheric CO2 mole fractions; this can be done, as emissions from fossil fuels do not contain 14CO2 and cause a depletion in the observed Δ14CO2 value. The observations are compared to simulated values. Two corrections need to be applied to radiocarbon-derived fossil fuel CO2 (ffCO2): one for pure 14CO2 emissions from nuclear industry sites and one for a disequilibrium in the isotopic signature of older biospheric emissions (heterotrophic respiration) and CO2 in the atmosphere. Measurements at both sites were found to only be marginally affected by 14CO2 emissions from nuclear sites. Over the study period of 2014–2015, the biospheric correction and the correction for nuclear 14CO2 emissions were similar at 0.34 and 0.25 ppm ffCO2 equivalent, respectively. The observed ffCO2 at the TAC tall tower site was not significantly different from simulated values based on the EDGAR 2010 bottom-up inventory. We explored the use of high-frequency CO observations as a tracer offfCO2 by deriving a constant ratio of CO enhancements to ffCO2 ratio for the mix of UK fossil fuel sources. This ratio was found to be 5.7 ppb ppm-1, close to the value predicted using inventories and the atmospheric model of 5.1 ppb ppm-1. The TAC site, in the east of the UK, was strategically chosen to be some distance from pollution sources so as to allow for the observation of well-integrated air masses. However, this distance from pollution sources and the large measurement uncertainty in 14CO2 lead to a large overall uncertainty in the ffCO2, being around 1.8 ppm compared to typical enhancements of 2 ppm.
Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and ...how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions.In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions.We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development.
Atmospheric trace gas inversions often attempt to attribute fluxes to a high-dimensional grid using observations. To make this problem computationally feasible, and to reduce the degree of ...under-determination, some form of dimension reduction is usually performed. Here, we present an objective method for reducing the spatial dimension of the parameter space in atmospheric trace gas inversions. In addition to solving for a set of unknowns that govern emissions of a trace gas, we set out a framework that considers the number of unknowns to itself be an unknown. We rely on the well-established reversible-jump Markov chain Monte Carlo algorithm to use the data to determine the dimension of the parameter space. This framework provides a single-step process that solves for both the resolution of the inversion grid, as well as the magnitude of fluxes from this grid. Therefore, the uncertainty that surrounds the choice of aggregation is accounted for in the posterior parameter distribution. The posterior distribution of this transdimensional Markov chain provides a naturally smoothed solution, formed from an ensemble of coarser partitions of the spatial domain. We describe the form of the reversible-jump algorithm and how it may be applied to trace gas inversions. We build the system into a hierarchical Bayesian framework in which other unknown factors, such as the magnitude of the model uncertainty, can also be explored. A pseudo-data example is used to show the usefulness of this approach when compared to a subjectively chosen partitioning of a spatial domain. An inversion using real data is also shown to illustrate the scales at which the data allow for methane emissions over north-west Europe to be resolved.
Abstract During 1997, two new viruses were isolated from outbreaks of disease that occurred in horses, donkeys, cattle and sheep in Peru. Genome characterization showed that the virus isolated from ...horses (with neurological disorders, 78% fatality) belongs to a new species the Peruvian horse sickness virus (PHSV), within the genus Orbivirus , family Reoviridae . This represents the first isolation of PHSV, which was subsequently also isolated during 1999, from diseased horses in the Northern Territory of Australia (Elsey virus, ELSV). Serological and molecular studies showed that PHSV and ELSV are very similar in the serotype-determining protein (99%, same serotype). The second virus (Rioja virus, RIOV) was associated with neurological signs in donkeys, cattle, sheep and dogs and was shown to be a member of the species Yunnan orbivirus (YUOV). RIOV and YUOV are also almost identical (97% amino acid identity) in the serotype-determining protein. YUOV was originally isolated from mosquitoes in China.
Role of atmospheric oxidation in recent methane growth Rigby, Matthew; Montzka, Stephen A.; Prinn, Ronald G. ...
Proceedings of the National Academy of Sciences - PNAS,
05/2017, Letnik:
114, Številka:
21
Journal Article
Recenzirano
Odprti dostop
The growth in global methane (CH₄) concentration, which had been ongoing since the industrial revolution, stalled around the year 2000 before resuming globally in 2007. We evaluate the role of the ...hydroxyl radical (OH), the major CH₄ sink, in the recent CH₄ growth. We also examine the influence of systematic uncertainties in OH concentrations on CH₄ emissions inferred from atmospheric observations. We use observations of 1,1,1-trichloroethane (CH₃CCl₃), which is lost primarily through reaction with OH, to estimate OH levels as well as CH₃CCl₃ emissions, which have uncertainty that previously limited the accuracy of OH estimates. We find a 64–70% probability that a decline in OH has contributed to the post-2007 methane rise. Our median solution suggests that CH₄ emissions increased relatively steadily during the late 1990s and early 2000s, after which growth was more modest. This solution obviates the need for a sudden statistically significant change in total CH₄ emissions around the year 2007 to explain the atmospheric observations and can explain some of the decline in the atmospheric 13CH₄/12CH₄ ratio and the recent growth in C₂H₆. Our approach indicates that significant OH-related uncertainties in the CH₄ budget remain, and we find that it is not possible to implicate, with a high degree of confidence, rapid global CH₄ emissions changes as the primary driver of recent trends when our inferred OH trends and these uncertainties are considered.
The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting correlations among ...amino acid compositions at different sequence positions can be exploited to infer spatial contacts within the tertiary protein structure. Crucial to this inference is the ability to disentangle direct and indirect correlations, as accomplished by the recently introduced direct-coupling analysis (DCA). Here we develop a computationally efficient implementation of DCA, which allows us to evaluate the accuracy of contact prediction by DCA for a large number of protein domains, based purely on sequence information. DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global structure of the contact map for the majority of the protein domains examined. Furthermore, our analysis captures clear signals beyond intradomain residue contacts, arising, e.g., from alternative protein conformations, ligand-mediated residue couplings, and interdomain interactions in protein oligomers. Our findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, contingent on the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.
Genetic switches are critical components of developmental circuits. Because temperate bacteriophages are vastly abundant and greatly diverse, they are rich resources for understanding the mechanisms ...and evolution of switches and the molecular control of genetic circuitry. Here, we describe a new class of small, compact, and simple switches that use site-specific recombination as the key decision point. The phage attachment site attP is located within the phage repressor gene such that chromosomal integration results in removal of a C-terminal tag that destabilizes the virally encoded form of the repressor. Integration thus not only confers prophage stability but also is a requirement for lysogenic establishment. The variety of these self-contained integration-dependent immunity systems in different genomic contexts suggests that these represent ancestral states in switch evolution from which more-complex switches have evolved. They also provide a powerful toolkit for building synthetic biological circuits.
► Bacteriophages are described in which integration is required for immunity ► Proteolytic control of phage integrase and repressor determines infection outcomes ► Integration-dependent genetic switches are tools for synthetic genetic circuits ► Integration-dependent immunity gives insight into genetic switch evolution
Theory and climate modelling suggest that the sensitivity of Earth's climate to changes in radiative forcing could depend on the background climate. However, palaeoclimate data have thus far been ...insufficient to provide a conclusive test of this prediction. Here we present atmospheric carbon dioxide (CO2) reconstructions based on multi-site boron-isotope records from the late Pliocene epoch (3.3 to 2.3 million years ago). We find that Earth's climate sensitivity to CO2-based radiative forcing (Earth system sensitivity) was half as strong during the warm Pliocene as during the cold late Pleistocene epoch (0.8 to 0.01 million years ago). We attribute this difference to the radiative impacts of continental ice-volume changes (the ice-albedo feedback) during the late Pleistocene, because equilibrium climate sensitivity is identical for the two intervals when we account for such impacts using sea-level reconstructions. We conclude that, on a global scale, no unexpected climate feedbacks operated during the warm Pliocene, and that predictions of equilibrium climate sensitivity (excluding long-term ice-albedo feedbacks) for our Pliocene-like future (with CO2 levels up to maximum Pliocene levels of 450 parts per million) are well described by the currently accepted range of an increase of 1.5 K to 4.5 K per doubling of CO2.
Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols ...for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land–sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.
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