Real-time analysis of T cell receptors in naive cells in vitro and in vivo reveals flexibility in synapse and signaling dynamics

Real-time imaging defines the dynamics of TCR and T cell motility during early T cell activation in lymph nodes

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods

Recent and future trends in synthetic greenhouse gas radiative forcing

Atmospheric measurements show that emissions of hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons are now the primary drivers of the positive growth in synthetic greenhouse gas (SGHG) radiative forcing. We infer recent SGHG emissions and examine the impact of future emissions scenarios, with a particular focus on proposals to reduce HFC use under the Montreal Protocol. If these proposals are implemented, overall SGHG radiative forcing could peak at around 355 mW m[superscript −2] in 2020, before declining by approximately 26% by 2050, despite continued growth of fully fluorinated greenhouse gas emissions. Compared to “no HFC policy” projections, this amounts to a reduction in radiative forcing of between 50 and 240 mW m[superscript −2] by 2050 or a cumulative emissions saving equivalent to 0.5 to 2.8 years of CO2 emissions at current levels. However, more complete reporting of global HFC emissions is required, as less than half of global emissions are currently accounted for.Natural Environment Research Council (Great Britain) (Advanced Research Fellowship NE/I021365/1)United States. National Aeronautics and Space Administration (Upper Atmospheric Research Program Grant NNX11AF17G)United States. National Oceanic and Atmospheric Administratio

Radon: a universal baseline indicator at sites with contrasting physical settings

The primary goal of World Meteorological Organisation Global Atmosphere Watch (WMO‐GAW) baseline stations is systematic global monitoring of chemical composition of the atmosphere, requiring a reliable, consistent and unambiguous approach for the identification of baseline air. Premier stations in the GAW baseline network span a broad range of physical settings, from remote marine to high‐altitude continental sites, necessitating carefully tailored site‐specific requirements for baseline sampling, data selection, and analysis. Radon‐222 is a versatile and unambiguous terrestrial tracer, widely‐used in transport and mixing studies. Since the majority of anthropogenic pollution sources also have terrestrial origins, radon has become a popular addition to the ‘baseline selection toolkit’ at numerous GAW stations as a proxy for ‘pollution potential’. In the past, detector performance and postprocessing methods necessitated the adoption of a relaxed (e.g. 100 mBq m‐3) radon threshold for minimal terrestrial influence, intended to be used in conjunction with other baseline criteria and analysis procedures, including wind speed, wind direction, particle number, outlier rejection and filtering. However, recent improvements in detector sensitivity, stability and post‐processing procedures have reduced detection limits below 10 mBq m‐3 at Cape Grim and to 25 mBq m‐3 at other baseline stations. Consequently, for suitably sensitive instruments (such as the ANSTO designed and built two‐filter dual‐flow‐loop detectors), radon concentrations alone can be used to unambiguously identify air masses that have been removed from terrestrial sources (at altitude or over ice), or in equilibrium with the ocean surface, for periods of >2‐3 weeks (radon ≤ 40 mBq m‐3). Potentially, radon observations alone can thus provide a consistent and universal (site independent) means for baseline identification. Furthermore, for continental sites with complex topography and meteorology, where true ‘baseline’ conditions may never occur, radon can be used to indicate the least terrestrially‐perturbed air masses, and provide a means by which to apply limits to the level of ‘acceptable terrestrial influence’ for a given application. We demonstrate the efficacy of the radon‐based selection at a range of sites in contrasting physical settings, including: Cape Grim (Tasmania), Cape Point (South Africa), Mauna Loa (Hawaii), Jungfraujoch (Switzerland) and Schneefernerhaus (Germany).Bureau of Meteorology and CSIRO Oceans and Atmosphere,Climate Science Centre

TransCom N2O model inter-comparison - Part 2:Atmospheric inversion estimates of N2O emissions

This study examines N2O emission estimates from five different atmospheric inversion frameworks based on chemistry transport models (CTMs). The five frameworks differ in the choice of CTM, meteorological data, prior uncertainties and inversion method but use the same prior emissions and observation data set. The posterior modelled atmospheric N2O mole fractions are compared to observations to assess the performance of the inversions and to help diagnose problems in the modelled transport. Additionally, the mean emissions for 2006 to 2008 are compared in terms of the spatial distribution and seasonality. Overall, there is a good agreement among the inversions for the mean global total emission, which ranges from 16.1 to 18.7 TgN yr(-1) and is consistent with previous estimates. Ocean emissions represent between 31 and 38% of the global total compared to widely varying previous estimates of 24 to 38%. Emissions from the northern mid- to high latitudes are likely to be more important, with a consistent shift in emissions from the tropics and subtropics to the mid- to high latitudes in the Northern Hemisphere; the emission ratio for 0-30A degrees N to 30-90A degrees N ranges from 1.5 to 1.9 compared with 2.9 to 3.0 in previous estimates. The largest discrepancies across inversions are seen for the regions of South and East Asia and for tropical and South America owing to the poor observational constraint for these areas and to considerable differences in the modelled transport, especially inter-hemispheric exchange rates and tropical convective mixing. Estimates of the seasonal cycle in N2O emissions are also sensitive to errors in modelled stratosphere-to-troposphere transport in the tropics and southern extratropics. Overall, the results show a convergence in the global and regional emissions compared to previous independent studies

Towards a universal “baseline” characterisation of air masses for high- and low-altitude observing stations using Radon-222

We demonstrate the ability of atmospheric radon concentrations to reliably and unambiguously identify local and remote terrestrial influences on an air mass, and thereby the potential for alteration of trace gas composition by anthropogenic and biogenic processes. Based on high accuracy (lower limit of detection 10–40 mBq m–3), high temporal resolution (hourly) measurements of atmospheric radon concentration we describe, apply and evaluate a simple two-step method for identifying and characterising constituent mole fractions in baseline air. The technique involves selecting a radon-based threshold concentration to identify the “cleanest” (least terrestrially influenced) air masses, and then performing an outlier removal step based on the distribution of constituent mole fractions in the identified clean air masses. The efficacy of this baseline selection technique is tested at three contrasting WMO GAW stations: Cape Grim (a coastal low-altitude site), Mauna Loa (a remote high-altitude island site), and Jungfraujoch (a continental high-altitude site). At Cape Grim and Mauna Loa the two-step method is at least as effective as more complicated methods employed to characterise baseline conditions, some involving up to nine steps. While it is demonstrated that Jungfraujoch air masses rarely meet the baseline criteria of the more remote sites, a selection method based on a variable monthly radon threshold is shown to produce credible “near baseline” characteristics. The seasonal peak-to-peak amplitude of recent monthly baseline CO2 mole fraction deviations from the long-term trend at Cape Grim, Mauna Loa and Jungfraujoch are estimated to be 1.1, 6.0 and 8.1 ppm, respectively

T-Cell activation: a queuing theory analysis at low agonist density

We analyze a simple linear triggering model of the T-cell receptor (TCR) within the framework of queuing theory, in which TCRs enter the queue upon full activation and exit by downregulation. We fit our model to four experimentally characterized threshold activation criteria and analyze their specificity and sensitivity: the initial calcium spike, cytotoxicity, immunological synapse formation, and cytokine secretion. Specificity characteristics improve as the time window for detection increases, saturating for time periods on the timescale of downregulation; thus, the calcium spike (30 s) has low specificity but a sensitivity to single-peptide MHC ligands, while the cytokine threshold (1 h) can distinguish ligands with a 30% variation in the complex lifetime. However, a robustness analysis shows that these properties are degraded when the queue parameters are subject to variation—for example, under stochasticity in the ligand number in the cell-cell interface and population variation in the cellular threshold. A time integration of the queue over a period of hours is shown to be able to control parameter noise efficiently for realistic parameter values when integrated over sufficiently long time periods (hours), the discrimination characteristics being determined by the TCR signal cascade kinetics (a kinetic proofreading scheme). Therefore, through a combination of thresholds and signal integration, a T cell can be responsive to low ligand density and specific to agonist quality. We suggest that multiple threshold mechanisms are employed to establish the conditions for efficient signal integration, i.e., coordinate the formation of a stable contact interface

Composition of Clean Marine Air and Biogenic Influences on VOCs during the MUMBA Campaign

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO2 (391.0 ± 0.6 ppm), CH4 (1760.1 ± 0.4 ppb), N2O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O3 (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C8H10 aromatics (23 ± 6 ppt) and C9H12 aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport model simulations of the atmosphere in this poorly sampled region of the world. © 2019 The Author

Exploring causes of interannual variability in the seasonal cycles of tropospheric nitrous oxide

Seasonal cycles in the mixing ratios of tropospheric nitrous oxide (N[subscript 2]O) are derived by detrending long-term measurements made at sites across four global surface monitoring networks. The detrended monthly data display large interannual variability, which at some sites challenges the concept of a "mean" seasonal cycle. In the Northern Hemisphere, correlations between polar winter lower stratospheric temperature and detrended N[subscript 2]O data, around the month of the seasonal minimum, provide empirical evidence for a stratospheric influence, which varies in strength from year to year and can explain much of the interannual variability in the surface seasonal cycle. Even at sites where a strong, competing, regional N[subscript 2]O source exists, such as from coastal upwelling at Trinidad Head, California, the stratospheric influence must be understood to interpret the biogeochemical signal in monthly mean data. In the Southern Hemisphere, detrended surface N[subscript 2]O monthly means are correlated with polar spring lower stratospheric temperature in months preceding the N[subscript 2]O minimum, providing empirical evidence for a coherent stratospheric influence in that hemisphere as well, in contrast to some recent atmospheric chemical transport model (ACTM) results. Correlations between the phasing of the surface N[subscript 2]O seasonal cycle in both hemispheres and both polar lower stratospheric temperature and polar vortex break-up date provide additional support for a stratospheric influence. The correlations discussed above are generally more evident in high-frequency in situ data than in data from weekly flask samples. Furthermore, the interannual variability in the N[subscript 2]O seasonal cycle is not always correlated among in situ and flask networks that share common sites, nor do the mean seasonal amplitudes always agree. The importance of abiotic influences such as the stratospheric influx and tropospheric transport on N[subscript 2]O seasonal cycles suggests that, at sites remote from local sources, surface N[subscript 2]O mixing ratio data by themselves are unlikely to provide information about seasonality in surface sources, e.g., for atmospheric inversions, unless the ACTMs employed in the inversions accurately account for these influences. An additional abioitc influence is the seasonal ingassing and outgassing of cooling and warming surface waters, which creates a thermal signal in tropospheric N[subscript 2]O that is of particular importance in the extratropical Southern Hemisphere, where it competes with the biological ocean source signal.United States. National Aeronautics and Space Administration (grant NNX08AB48G