Improved quantification of Chinese carbon fluxes using CO2/CO correlations in Asian outflow

[1] We use observed CO2:CO correlations in Asian outflow from the TRACE-P aircraft campaign (February–April 2001), together with a three-dimensional global chemical transport model (GEOS-CHEM), to constrain specific components of the east Asian CO2 budget including, in particular, Chinese emissions. The CO2/CO emission ratio varies with the source of CO2 (different combustion types versus the terrestrial biosphere) and provides a characteristic signature of source regions and source type. Observed CO2/CO correlation slopes in east Asian boundary layer outflow display distinct regional signatures ranging from 10–20 mol/mol (outflow from northeast China) to 80 mol/mol (over Japan). Model simulations using best a priori estimates of regional CO2 and CO sources from Streets et al. [2003] (anthropogenic), the CASA model (biospheric), and Duncan et al. [2003] (biomass burning) overestimate CO2 concentrations and CO2/CO slopes in the boundary layer outflow. Constraints from the CO2/CO slopes indicate that this must arise from an overestimate of the modeled regional net biospheric CO2 flux. Our corrected best estimate of the net biospheric source of CO2 from China for March–April 2001 is 3200 Gg C/d, which represents a 45 % reduction of the net flux from the CASA model. Previous analyses of the TRACE-P data had found that anthropogenic Chinese C

Towards understanding the variability in biospheric CO2 fluxes:Using FTIR spectrometry and a chemical transport model to investigate the sources and sinks of carbonyl sulfide and its link to CO2

Understanding carbon dioxide (CO2) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO2 in the atmosphere. Atmospheric inversions based on CO2 concentration measurements alone can only determine net biosphere fluxes, but not differentiate between photosynthesis (uptake) and respiration (production). Carbonyl sulfide (OCS) could provide an important additional constraint: it is also taken up by plants during photosynthesis but not emitted during respiration, and therefore is a potential means to differentiate between these processes. Solar absorption Fourier Transform InfraRed (FTIR) spectrometry allows for the retrievals of the atmospheric concentrations of both CO2 and OCS from measured solar absorption spectra. Here, we investigate co-located and quasi-simultaneous FTIR measurements of OCS and CO2 performed at five selected sites located in the Northern Hemisphere. These measurements are compared to simulations of OCS and CO2 using a chemical transport model (GEOS-Chem). The coupled biospheric fluxes of OCS and CO2 from the simple biosphere model (SiB) are used in the study. The CO2 simulation with SiB fluxes agrees with the measurements well, while the OCS simulation reproduced a weaker drawdown than FTIR measurements at selected sites, and a smaller latitudinal gradient in the Northern Hemisphere during growing season when comparing with HIPPO (HIAPER Pole-to-Pole Observations) data spanning both hemispheres. An offset in the timing of the seasonal cycle minimum between SiB simulation and measurements is also seen. Using OCS as a photosynthesis proxy can help to understand how the biospheric processes are reproduced in models and to further understand the carbon cycle in the real world

Error Correlation Between CO2 and CO as Constraint for CO2 Flux Inversions Using Satellite Data

Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.Earth and Planetary SciencesEngineering and Applied Science

Precision Requirements for Space-based XCO2 Data

Precision requirements have been determined for the column-averaged CO2 dry air mole fraction (X(sub CO2)) data products to be delivered by the Orbiting Carbon Observatory (OCO). These requirements result from an assessment of the amplitude and spatial gradients in X(sub CO2), the relationship between X(sub CO2) precision and surface CO2 flux uncertainties calculated from inversions of the X(sub CO2) data, and the effects of X,,Z biases on CO2 flux inversions. Observing system simulation experiments and synthesis inversion modeling demonstrate that the OCO mission design and sampling strategy provide the means to achieve the X(sub CO2) precision requirements. The impact of X(sub CO2) biases on CO2 flux uncertainties depend on their spatial and temporal extent since CO2 sources and sinks are inferred from regional-scale X(sub CO2) gradients. Simulated OCO sampling of the TRACE-P CO2 fields shows the ability of X(sub CO2) data to constrain CO2 flux inversions over Asia and distinguish regional fluxes from India and China

COVID-19: UK frontline intensivists' emerging learning.

The Intensive Care Society held a webinar on 3 April 2020 at which representatives from 11 of the most COVID-19 experienced hospital trusts in England and Wales shared learning around five specific topic areas in an open forum. This paper summarises the emerging learning and practice shared by those frontline clinicians

CD28 between tolerance and autoimmunity: The side effects of animal models [version 1; referees: 2 approved]

Regulation of immune responses is critical for ensuring pathogen clearance and for preventing reaction against self-antigens. Failure or breakdown of immunological tolerance results in autoimmunity. CD28 is an important co-stimulatory receptor expressed on T cells that, upon specific ligand binding, delivers signals essential for full T-cell activation and for the development and homeostasis of suppressive regulatory T cells. Many in vivo mouse models have been used for understanding the role of CD28 in the maintenance of immune homeostasis, thus leading to the development of CD28 signaling modulators that have been approved for the treatment of some autoimmune diseases. Despite all of this progress, a deeper understanding of the differences between the mouse and human receptor is required to allow a safe translation of pre-clinical studies in efficient therapies. In this review, we discuss the role of CD28 in tolerance and autoimmunity and the clinical efficacy of drugs that block or enhance CD28 signaling, by highlighting the success and failure of pre-clinical studies, when translated to humans

Evaluating Oceanic Uptake of Atmospheric CCl4: A Combined Analysis of Model Simulations and Observations

We provide new estimates of the air‐sea flux of CCl4 using simulations from a global ocean biogeochemistry model (NEMO‐PlankTOM) in combination with depth‐resolved CCl4 observations from global oceanic databases. Estimates of global oceanic CCl4 uptake are derived from a range of model analyses, including prescribed parameterizations using reported values on hydrolysis and degradation, and analyses optimized using the global observational databases. We evaluate the sensitivity of our results to uncertainties in air‐sea gas exchange parameterization, estimation period, and circulation processes. Our best constrained estimate of ocean CCl4 uptake for the period 1996–2000 is 20.1 Gg/year (range 16.6–22.7), corresponding to estimates of the partial atmospheric lifetime with respect to ocean uptake of 124 (110–150) years. This new oceanic lifetime implies higher emissions of CCl4 than currently estimated and therefore a larger missing atmospheric source of CCl4

The impacts of ocean acidification on marine trace gases and the implications for atmospheric chemistry and climate

Surface ocean biogeochemistry and photochemistry regulate ocean–atmosphere fluxes of trace gases critical for Earth’s atmospheric chemistry and climate. The oceanic processes governing these fluxes are often sensitive to the changes in ocean pH (or pCO2) accompanying ocean acidification (OA), with potential for future climate feedbacks. Here, we review current understanding (from observational, experimental and model studies) on the impact of OA on marine sources of key climate-active trace gases, including dimethyl sulfide (DMS), nitrous oxide (N2O), ammonia and halocarbons. We focus on DMS, for which available information is considerably greater than for other trace gases. We highlight OA-sensitive regions such as polar oceans and upwelling systems, and discuss the combined effect of multiple climate stressors (ocean warming and deoxygenation) on trace gas fluxes. To unravel the biological mechanisms responsible for trace gas production, and to detect adaptation, we propose combining process rate measurements of trace gases with longer term experiments using both model organisms in the laboratory and natural planktonic communities in the field. Future ocean observations of trace gases should be routinely accompanied by measurements of two components of the carbonate system to improve our understanding of how in situ carbonate chemistry influences trace gas production. Together, this will lead to improvements in current process model capabilities and more reliable predictions of future global marine trace gas fluxes

Precision requirements for space-based XCO2 data

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): D10314, doi:10.1029/2006JD007659.Precision requirements are determined for space-based column-averaged CO2 dry air mole fraction (XCO2) data. These requirements result from an assessment of spatial and temporal gradients in XCO2, the relationship between XCO2 precision and surface CO2 flux uncertainties inferred from inversions of the XCO2 data, and the effects of XCO2 biases on the fidelity of CO2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these XCO2 data precision requirements.This work was supported by the Orbiting Carbon Observatory (OCO) project through NASA’s Earth System Science Pathfinder (ESSP) program. SCO and JTR were supported by a NASA IDS grant (NAG5-9462) to JTR