Stable isotopic analysis of atmospheric methane by infrared spectroscopy by use of diode laser difference-frequency generation

An infrared absorption spectrometer has been constructed to measure the stable isotopic composition of atmospheric methane samples. The spectrometer employs periodically poled lithium niobate to generate 15 μW of tunable difference-frequency radiation from two near-infrared diode lasers that probe the ν3 rotational-vibrational band of methane at 3.4 μm. To enhance the signal, methane is extracted from 25 l of air by use of a cryogenic chromatographic column and is expanded into the multipass cell for analysis. A measurement precision of 12‰ is demonstrated for both δ13C and δD

What atmospheric oxygen measurements can tell us about the global carbon cycle

This paper explores the role that measurements of changes in atmospheric oxygen, detected through changes in the O2/N2 ratio of air, can play in improving our understanding of the global carbon cycle. Simple conceptual models are presented in order to clarify the biological and physical controls on the exchanges of O2, CO2, N2, and Ar across the air‐sea interface and in order to clarify the relationships between biologically mediated fluxes of oxygen across the air‐sea interface and the cycles of organic carbon in the ocean. Predictions of large‐scale seasonal variations and gradients in atmospheric oxygen are presented. A two‐dimensional model is used to relate changes in the O2/N2 ratio of air to the sources of oxygen from terrestrial and marine ecosystems, the thermal ingassing and outgassing of seawater, and the burning of fossil fuel. The analysis indicates that measurements of seasonal variations in atmospheric oxygen can place new constraints on the large‐scale marine biological productivity. Measurements of the north‐south gradient and depletion rate of atmospheric oxygen can help determine the rates and geographical distribution of the net storage of carbon in terrestrial ecosystems

Reducing errors on estimates of the carbon uptake period based on time series of atmospheric CO2

Long, high-quality time series measurements of atmospheric greenhouse gases show interannual variability in the measured seasonal cycles. These changes can be analyzed to better understand the carbon cycle and the impact of climate drivers. However, nearly all discrete measurement records contain gaps and have noise due to the influence of local fluxes or synoptic variability. To facilitate analysis, filtering and curve-fitting techniques are often applied to these time series. Previous studies have recognized that there is inherent uncertainty associated with this curve fitting and the choice of a given mathematical method might introduce biases. Since uncertainties are seldom propagated to the metrics under study, this can lead to misinterpretation of the signal. In this study, we present a novel curve fitting method and an ensemble-based approach that allows the uncertainty of the metrics to be quantified. We apply it here to the Northern Hemisphere CO2 dry air mole fraction time series. We use this ensemble-based approach to analyze different seasonal cycle metrics, namely the onset, termination, and duration of the carbon uptake period (CUP), i.e., the time of the year when the CO2 uptake is greater than the CO2 release. Previous studies have diagnosed CUP based on the dates on which the detrended, zero-centered seasonal cycle curve switches from positive to negative (the downward zero-crossing date) and vice versa (upward zero-crossing date). However, we find that the upward zero-crossing date is sensitive to the skewness of the CO2 seasonal cycle during the net carbon release period. Hence, we propose an alternative method to estimate the onset and termination of the CUP based on a threshold defined in terms of the first-derivative of the CO2 seasonal cycle (First-derivative threshold (FDT) method). Further, using the ensemble-based approach and an additional curve fitting algorithm, we show that (a) the uncertainty of the studied metrics is smaller using the FDT method than when estimated using the timing of the zero-crossing dates, and (b) the onset and termination dates derived with the FDT-method provide more robust results, irrespective of the curve-fitting method applied to the data. The code is made freely available under a Creative Commons-BY license, along with the documentation in this paper

Non-monotonic dynamics and crosstalk in signaling pathways and their implications for pharmacology

Currently, drug discovery approaches commonly assume a monotonic dose-response relationship. However, the assumption of monotonicity is increasingly being challenged. Here we show that for two simple interacting linear signaling pathways that carry two different signals with different physiological responses, a non-monotonic input-output relation can arise with simple network topologies including coherent and incoherent feed-forward loops. We show that non-monotonicity of the response functions has severe implications for pharmacological treatment. Fundamental constraints are imposed on the effectiveness and toxicity of any drug independent of its chemical nature and selectivity due to the specific network structure

Reducing errors on estimates of the carbon uptake period based on time series of atmospheric CO2

High-quality, long-time-series measurements of atmospheric greenhouse gases show interannual variability in the measured seasonal cycles. These changes can be analyzed to better understand the carbon cycle and the impact of climate drivers. However, nearly all discrete measurement records contain gaps and have noise due to the influence of local fluxes or synoptic variability. To facilitate analysis, filtering and curve-fitting techniques are often applied to these time series. Previous studies have recognized that there is an inherent uncertainty associated with this curve fitting, and the choice of a given mathematical method might introduce biases. Since uncertainties are seldom propagated to the metrics under study, this can lead to misinterpretation of the signal. In this study, we use an ensemble-based approach to quantify the uncertainty of the derived seasonal cycle metrics. We apply it to CO2 dry-air mole fraction time series from flask measurements in the Northern Hemisphere. We use this ensemble-based approach to analyze the carbon uptake period (CUP: the time of the year when the CO2 uptake is greater than the CO2 release): its onset, termination and duration. Previous studies have diagnosed CUP based on the dates on which the detrended, zero-centered seasonal cycle curve switches from positive to negative (the downward zero-crossing date, DZCD) and vice versa (upward zero-crossing date, UZCD). However, the UZCD is sensitive to the skewness of the CO2 seasonal cycle during the net carbon release period. Hence, we develop an alternative method proposed by Barlow et al. (2015) to estimate the onset and termination of the CUP based on a threshold defined in terms of the first derivative of the CO2 seasonal cycle. Using the ensemble approach, we arrive at a tighter constraint to the threshold by considering the annual uncertainty; we call this the ensemble of first derivative (EFD) method. Further, using the EFD approach and an additional curve-fitting algorithm, we show that (a) the uncertainty of the studied metrics is smaller using the EFD method than when approximated using the timing of the zero-crossing date (ZCD), and (b) the onset and termination dates derived with the EFD method provide more robust results, irrespective of the curve-fitting method applied to the data

Investigating Alaskan Methane and Carbon Dioxide Fluxes Using Measurements from the CARVE Tower

Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Because the near-surface atmosphere integrates surface fluxes over large ( ∼ 500–1000 km) scales, atmospheric monitoring of carbon dioxide (CO2) and methane (CH4) mole fractions in the daytime mixed layer is a promising method for detecting change in the carbon cycle throughout boreal Alaska. Here we use CO2 and CH4 measurements from a NOAA tower 17 km north of Fairbanks, AK, established as part of NASA\u27s Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), to investigate regional fluxes of CO2 and CH4 for 2012–2014. CARVE was designed to use aircraft and surface observations to better understand and quantify the sensitivity of Alaskan carbon fluxes to climate variability. We use high-resolution meteorological fields from the Polar Weather Research and Forecasting (WRF) model coupled with the Stochastic Time-Inverted Lagrangian Transport model (hereafter, WRF-STILT), along with the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), to investigate fluxes of CO2 in boreal Alaska using the tower observations, which are sensitive to large areas of central Alaska. We show that simulated PolarVPRM–WRF-STILT CO2 mole fractions show remarkably good agreement with tower observations, suggesting that the WRF-STILT model represents the meteorology of the region quite well, and that the PolarVPRM flux magnitudes and spatial distribution are generally consistent with CO2 mole fractions observed at the CARVE tower. One exception to this good agreement is that during the fall of all 3 years, PolarVPRM cannot reproduce the observed CO2 respiration. Using the WRF-STILT model, we find that average CH4 fluxes in boreal Alaska are somewhat lower than flux estimates by Chang et al. (2014) over all of Alaska for May–September 2012; we also find that enhancements appear to persist during some wintertime periods, augmenting those observed during the summer and fall. The possibility of significant fall and winter CO2 and CH4 fluxes underscores the need for year-round in situ observations to quantify changes in boreal Alaskan annual carbon balance

Atmospheric O2/N2 changes, 1993-2002: Implications for the partitioning of fossil fuel CO2 sequestration

Improvements made to an established mass spectrometric method for measuring changes in atmospheric O2/N2 are described. With the improvements in sample handling and analysis, sample throughput and analytical precision have both increased. Aliquots from duplicate flasks are repeatedly measured over a period of 2 weeks, with an overall standard error in each flask of 3-4 per meg, corresponding to 0.6-0.8 ppm O2 in air. Records of changes in O2/N2 from six global sampling stations (Barrow, American Samoa, Cape Grim, Amsterdam Island, Macquarie Island, and Syowa Station) are presented. Combined with measurements Of CO2 from the same sample flasks, land and ocean carbon uptake were calculated from the three sampling stations with the longest records (Barrow, Samoa, and Cape Grim). From 1994-2002, We find the average CO2 uptake by the ocean and the land biosphere was 1.7 ± 0.5 and 1.0 ± 0.6 GtC yr -1 respectively; these numbers include a correction of 0.3 Gt C yr-l due to secular outgassing of ocean O2. Interannual variability calculated from these data shows a strong land carbon source associated with the 1997-1998 El Niño event, supporting many previous studies indicating that high atmospheric growth rates observed during most El Niño events reflect diminished land uptake. Calculations of interannual variability in land and ocean uptake are probably confounded by non-zero annual air sea fluxes of O2. The origin of these fluxes is not yet understood. Copyright 2005 by the American Geophysical Union

Atmospheric potential oxygen: New observations and their implications for some atmospheric and oceanic models

Measurements of atmospheric O2/N2 ratios and CO2 concentrations can be combined into a tracer known as atmospheric potential oxygen (APO ≈ O2/N2 + CO2) that is conservative with respect to terrestrial biological activity. Consequently, APO reflects primarily ocean biogeochemistry and atmospheric circulation. Building on the work of Stephens et al. (1998), we present a set of APO observations for the years 1996-2003 with unprecedented spatial coverage. Combining data from the Princeton and Scripps air sampling programs, the data set includes new observations collected from ships in the low-latitude Pacific. The data show a smaller interhemispheric APO gradient than was observed in past studies, and different structure within the hemispheres. These differences appear to be due primarily to real changes in the APO field over time. The data also show a significant maximum in APO near the equator. Following the approach of Gruber et al. (2001), we compare these observations with predictions of APO generated from ocean O2 and CO2 flux fields and forward models of atmospheric transport. Our model predictions differ from those of earlier modeling studies, reflecting primarily the choice of atmospheric transport model (TM3 in this study). The model predictions show generally good agreement with the observations, matching the size of the interhemispheric gradient, the approximate amplitude and extent of the equatorial maximum, and the amplitude and phasing of the seasonal APO cycle at most stations. Room for improvement remains. The agreement in the interhemispheric gradient appears to be coincidental; over the last decade, the true APO gradient has evolved to a value that is consistent with our time-independent model. In addition, the equatorial maximum is somewhat more pronounced in the data than the model. This may be due to overly vigorous model transport, or insufficient spatial resolution in the air-sea fluxes used in our modeling effort. Finally, the seasonal cycles predicted by the model of atmospheric transport show evidence of an excessive seasonal rectifier in the Aleutian Islands and smaller problems elsewhere. Copyright 2006 by the American Geophysical Union

Upward revision of global fossil fuel methane emissions based on isotope database

Methane has the second-largest global radiative forcing impact of anthropogenic greenhouse gases after carbon dioxide, but our understanding of the global atmospheric methane budget is incomplete. The global fossil fuel industry (production and usage of natural gas, oil and coal) is thought to contribute 15 to 22 per cent of methane emissions to the total atmospheric methane budget. However, questions remain regarding methane emission trends as a result of fossil fuel industrial activity and the contribution to total methane emissions of sources from the fossil fuel industry and from natural geological seepage, which are often co-located. Here we re-evaluate the global methane budget and the contribution of the fossil fuel industry to methane emissions based on long-term global methane and methane carbon isotope records. We compile the largest isotopic methane source signature database so far, including fossil fuel, microbial and biomass-burning methane emission sources. We find that total fossil fuel methane emissions (fossil fuel industry plus natural geological seepage) are not increasing over time, but are 60 to 110 per cent greater than current estimates owing to large revisions in isotope source signatures. We show that this is consistent with the observed global latitudinal methane gradient. After accounting for natural geological methane seepage, we find that methane emissions from natural gas, oil and coal production and their usage are 20 to 60 per cent greater than inventories. Our findings imply a greater potential for the fossil fuel industry to mitigate anthropogenic climate forcing, but we also find that methane emissions from natural gas as a fraction of production have declined from approximately 8 per cent to approximately 2 per cent over the past three decades.Published88-916A. Geochimica per l'ambienteJCR Journa