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Elvidge, EL, Bonisch H, Brenninkmeijer CAM, Engel A, Fraser PJ, Gallacher E, Langenfelds R, Muhle J, Oram DE, Ray EA, Ridley AR, Rockmann T, Sturges WT, Weiss RF, Laube JC.  2018.  Evaluation of stratospheric age of air from CF4, C2F6, C3F8, CHF3, HFC-125, HFC-227ea and SF6; implications for the calculations of halocarbon lifetimes, fractional release factors and ozone depletion potentials. Atmospheric Chemistry and Physics. 18:3369-3385.   10.5194/acp-18-3369-2018   AbstractWebsite

In a changing climate, potential stratospheric circulation changes require long-term monitoring. Stratospheric trace gas measurements are often used as a proxy for stratospheric circulation changes via the "mean age of air" values derived from them. In this study, we investigated five potential age of air tracers - the perfluorocarbons CF4, C2F6 and C3F8 and the hydrofluorocarbons CHF3 (HFC-23) and HFC-125 - and compare them to the traditional tracer SF6 and a (relatively) shorter-lived species, HFC-227ea. A detailed uncertainty analysis was performed on mean ages derived from these "new" tracers to allow us to confidently compare their efficacy as age tracers to the existing tracer, SF6. Our results showed that uncertainties associated with the mean age derived from these new age tracers are similar to those derived from SF6, suggesting that these alternative compounds are suitable in this respect for use as age tracers. Independent verification of the suitability of these age tracers is provided by a comparison between samples analysed at the University of East Anglia and the Scripps Institution of Oceanography. All five tracers give younger mean ages than SF6, a discrepancy that increases with increasing mean age. Our findings qualitatively support recent work that suggests that the stratospheric lifetime of SF6 is significantly less than the previous estimate of 3200 years. The impact of these younger mean ages on three policy-relevant parameters - stratospheric lifetimes, fractional release factors (FRFs) and ozone depletion potentials - is investigated in combination with a recently improved methodology to calculate FRFs. Updates to previous estimations for these parameters are provided.

Wells, KC, Millet DB, Bousserez N, Henze DK, Griffis TJ, Chaliyakunnel S, Dlugokencky EJ, Saikawa E, Xiang G, Prinn RG, O'Doherty S, Young D, Weiss RF, Dutton GS, Elkins JW, Krummel PB, Langenfelds R, Steele LP.  2018.  Top-down constraints on global N2O emissions at optimal resolution: application of a new dimension reduction technique. Atmospheric Chemistry and Physics. 18:735-756.   10.5194/acp-18-735-2018   AbstractWebsite

We present top-down constraints on global monthly N2O emissions for 2011 from a multi-inversion approach and an ensemble of surface observations. The inversions employ the GEOS-Chem adjoint and an array of aggregation strategies to test how well current observations can constrain the spatial distribution of global N2O emissions. The strategies include (1) a standard 4D-Var inversion at native model resolution (4 degrees x 5 degrees), (2) an inversion for six continental and three ocean regions, and (3) a fast 4D-Var inversion based on a novel dimension reduction technique employing randomized singular value decomposition (SVD). The optimized global flux ranges from 15.9 TgNyr(-1) (SVD-based inversion) to 17.5-17.7 TgNyr(-1) (continental-scale, standard 4D-Var inversions), with the former better capturing the extratropical N2O background measured during the HIAPER Pole-to-Pole Observations (HIPPO) airborne campaigns. We find that the tropics provide a greater contribution to the global N2O flux than is predicted by the prior bottom-up inventories, likely due to underestimated agricultural and oceanic emissions. We infer an overestimate of natural soil emissions in the extratropics and find that predicted emissions are seasonally biased in northern midlatitudes. Here, optimized fluxes exhibit a springtime peak consistent with the timing of spring fertilizer and manure application, soil thawing, and elevated soil moisture. Finally, the inversions reveal a major emission underestimate in the US Corn Belt in the bottom-up inventory used here. We extensively test the impact of initial conditions on the analysis and recommend formally optimizing the initial N2O distribution to avoid biasing the inferred fluxes. We find that the SVD-based approach provides a powerful framework for deriving emission information from N2O observations: by defining the optimal resolution of the solution based on the information content of the inversion, it provides spatial information that is lost when aggregating to political or geographic regions, while also providing more temporal information than a standard 4D-Var inversion.

Jeong, SG, Newman S, Zhang JS, Andrews AE, Bianco L, Bagley J, Cui XG, Graven H, Kim J, Salameh P, LaFranchi BW, Priest C, Campos-Pineda M, Novakovskaia E, Sloop CD, Michelsen HA, Bambha RP, Weiss RF, Keeling R, Fischer ML.  2016.  Estimating methane emissions in California's urban and rural regions using multitower observations. Journal of Geophysical Research-Atmospheres. 121:13031-13049.   10.1002/2016jd025404   AbstractWebsite

We present an analysis of methane (CH4) emissions using atmospheric observations from 13 sites in California during June 2013 to May 2014. A hierarchical Bayesian inversion method is used to estimate CH4 emissions for spatial regions (0.3 degrees pixels for major regions) by comparing measured CH4 mixing ratios with transport model (Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport) predictions based on seasonally varying California-specific CH4 prior emission models. The transport model is assessed using a combination of meteorological and carbon monoxide (CO) measurements coupled with the gridded California Air Resources Board (CARB) CO emission inventory. The hierarchical Bayesian inversion suggests that state annual anthropogenic CH4 emissions are 2.42 +/- 0.49 Tg CH4/yr (at 95% confidence), higher (1.2-1.8 times) than the current CARB inventory (1.64 Tg CH4/yr in 2013). It should be noted that undiagnosed sources of errors or uncaptured errors in the model-measurement mismatch covariance may increase these uncertainty bounds beyond that indicated here. The CH4 emissions from the Central Valley and urban regions (San Francisco Bay and South Coast Air Basins) account for similar to 58% and 26% of the total posterior emissions, respectively. This study suggests that the livestock sector is likely the major contributor to the state total CH4 emissions, in agreement with CARB's inventory. Attribution to source sectors for subregions of California using additional trace gas species would further improve the quantification of California's CH4 emissions and mitigation efforts toward the California Global Warming Solutions Act of 2006 (Assembly Bill 32).

Thompson, RL, Ishijima K, Saikawa E, Corazza M, Karstens U, Patra PK, Bergamaschi P, Chevallier F, Dlugokencky E, Prinn RG, Weiss RF, O'Doherty S, Fraser PJ, Steele LP, Krummel PB, Vermeulen A, Tohjima Y, Jordan A, Haszpra L, Steinbacher M, Van der Laan S, Aalto T, Meinhardt F, Popa ME, Moncrieff J, Bousquet P.  2014.  TransCom N2O model inter-comparison - Part 2: Atmospheric inversion estimates of N2O emissions. Atmospheric Chemistry and Physics. 14:6177-6194.   10.5194/acp-14-6177-2014   AbstractWebsite

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.

Thompson, RL, Chevallier F, Crotwell AM, Dutton G, Langenfelds RL, Prinn RG, Weiss RF, Tohjima Y, Nakazawa T, Krummel PB, Steele LP, Fraser P, O'Doherty S, Ishijima K, Aoki S.  2014.  Nitrous oxide emissions 1999 to 2009 from a global atmospheric inversion. Atmospheric Chemistry and Physics. 14:1801-1817.   10.5194/acp-14-1801-2014   AbstractWebsite

N2O surface fluxes were estimated for 1999 to 2009 using a time-dependent Bayesian inversion technique. Observations were drawn from 5 different networks, incorporating 59 surface sites and a number of ship-based measurement series. To avoid biases in the inverted fluxes, the data were adjusted to a common scale and scale offsets were included in the optimization problem. The fluxes were calculated at the same resolution as the transport model (3.75 degrees longitude x 2.5 degrees latitude) and at monthly time resolution. Over the 11-year period, the global total N2O source varied from 17.5 to 20.1 Tg a(-1) N. Tropical and subtropical land regions were found to consistently have the highest N2O emissions, in particular in South Asia (20 +/- 3% of global total), South America (13 +/- 4 %) and Africa (19 +/- 3 %), while emissions from temperate regions were smaller: Europe (6 +/- 1 %) and North America (7 +/- 2 %). A significant multi-annual trend in N2O emissions (0.045 Tg a(-2) N) from South Asia was found and confirms inventory estimates of this trend. Considerable interannual variability in the global N2O source was observed (0.8 Tg a(-1) N, 1 standard deviation, SD) and was largely driven by variability in tropical and subtropical soil fluxes, in particular in South America (0.3 Tg a(-1) N, 1 SD) and Africa (0.3 Tg a(-1) N, 1 SD). Notable variability was also found for N2O fluxes in the tropical and southern oceans (0.15 and 0.2 Tg a(-1) N, 1 SD, respectively). Interannual variability in the N2O source shows some correlation with the El Nino-Southern Oscillation (ENSO), where El Nino conditions are associated with lower N2O fluxes from soils and from the ocean and vice versa for La Nina conditions.

Weiss, RF, Prinn RG.  2011.  Quantifying greenhouse-gas emissions from atmospheric measurements: a critical reality check for climate legislation. Philosophical Transactions of the Royal Society a-Mathematical Physical and Engineering Sciences. 369:1925-1942.   10.1098/rsta.2011.0006   AbstractWebsite

Emissions reduction legislation relies upon 'bottom-up' accounting of industrial and biogenic greenhouse-gas (GHG) emissions at their sources. Yet, even for relatively well-constrained industrial GHGs, global emissions based on 'top-down' methods that use atmospheric measurements often agree poorly with the reported bottom-up emissions. For emissions reduction legislation to be effective, it is essential that these discrepancies be resolved. Because emissions are regulated nationally or regionally, not globally, top-down estimates must also be determined at these scales. High-frequency atmospheric GHG measurements at well-chosen station locations record 'pollution events' above the background values that result from regional emissions. By combining such measurements with inverse methods and atmospheric transport and chemistry models, it is possible to map and quantify regional emissions. Even with the sparse current network of measurement stations and current inverse-modelling techniques, it is possible to rival the accuracies of regional 'bottom-up' emission estimates for some GHGs. But meeting the verification goals of emissions reduction legislation will require major increases in the density and types of atmospheric observations, as well as expanded inverse-modelling capabilities. The cost of this effort would be minor when compared with current investments in carbon-equivalent trading, and would reduce the volatility of that market and increase investment in emissions reduction.

Nevison, CD, Mahowald NM, Weiss RF, Prinn RG.  2007.  Interannual and seasonal variability in atmospheric N2O. Global Biogeochemical Cycles. 21   10.1029/2006gb002755   AbstractWebsite

The increase in atmospheric N2O observed over the last century reflects large- scale human perturbations to the global nitrogen cycle. High- precision measurements of atmospheric N2O over the last decade reveal subtle signals of interannual variability (IAV) superimposed upon the more prominent growth trend. Anthropogenic sources drive the underlying growth in N2O, but are probably too monotonic to explain most of the observed IAV. The causes of both seasonal and interannual variability in atmospheric N2O are explored on the basis of comparisons of a 1993 - 2004 atmospheric transport simulation to observations of N2O at five stations of the Advanced Global Atmospheric Gases Experiment (AGAGE). The complementary tracers chlorofluorocarbons (CFCs) 11 and 12 and SF6 also are examined. The model simulation does not include a stratospheric sink and thus isolates the effects of surface sources and tropospheric transport. Both model and observations yield correlations in seasonal and interannual variability among species, but only in a few cases are model and observed variability correlated to each other. The results suggest that tropospheric transport contributes substantially to observed variability, especially at Samoa station. However, some features of observed variability are not explained by the model simulation and appear more consistent with a stratospheric influence. At Mace Head, Ireland, N2O and CFC growth rate anomalies are weakly correlated to IAV in polar winter lower stratospheric temperature, a proxy for the strength of the mean meridional stratospheric circulation. Seasonal and interannual variability in the natural sources of N2O may also contribute to observed variability in atmospheric N2O.

Nevison, CD, Keeling RF, Weiss RF, Popp BN, Jin X, Fraser PJ, Porter LW, Hess PG.  2005.  Southern Ocean ventilation inferred from seasonal cycles of atmospheric N2O and O2/N2 at Cape Grim, Tasmania. Tellus Series B-Chemical and Physical Meteorology. 57:218-229.   10.1111/j.1600-0889.2005.00143.x   AbstractWebsite

The seasonal cycle of atmospheric N(2)O is derived from a 10-yr observational record at Cape Grim, Tasmania (41 degrees S, 145 degrees E). After correcting for thermal and stratospheric influences, the observed atmospheric seasonal cycle is consistent with the seasonal outgassing of microbially produced N(2)O from the Southern Ocean, as predicted by an ocean biogeochemistry model coupled to an atmospheric transport model (ATM). The model-observation comparison suggests a Southern Ocean N(2)O source of similar to 0.9 Tg N yr(-1) and is the first study to reproduce observed atmospheric seasonal cycles in N(2)O using specified surface sources in forward ATM runs. However, these results are sensitive to the thermal and stratospheric corrections applied to the atmospheric N(2)O data. The correlation in subsurface waters between apparent oxygen utilization (AOU) and N(2)O production (approximated as the concentration in excess of atmospheric equilibrium Delta N(2)O) is exploited to infer the atmospheric seasonal cycle in O(2)/N(2) due to ventilation of O(2)-depleted subsurface waters. Subtracting this cycle from the observed, thermally corrected seasonal cycle in atmospheric O(2)/N(2) allows the residual O(2)/N(2) signal from surface net community production to be inferred. Because N(2)O is only produced in subsurface ocean waters, where it is correlated to O(2) consumption, atmospheric N(2)O observations provide a methodology for distinguishing the surface production and subsurface ventilation signals in atmospheric O(2)/N(2), which have previously been inseparable.