We present the first spatially resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of ~10‰ between northern high‐latitude (mean −67.8‰) and tropical (mean −56.7‰) wetlands and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high‐latitude seasonal cycle, and smaller trend over the period 2000–2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals.

Large-scale epidemiological studies have shown a close correlation between adverse human health effects and exposure to ambient particulate matter (PM). The oxidative potential (OP) of ambient PM has been implicated in inducing toxic effects associated with PM exposure. In particular, reactive oxygen species (ROS), either bound to PM or generated by particulate components in vivo, substantially contribute to the OP and therefore toxicity of PM by lowering antioxidant concentrations in the lung, which can subsequently lead to oxidative stress, inflammation, and disease. Traditional methods for measuring aerosol OP are labor intensive and have poor time resolution, with significant delays between aerosol collection and ROS analysis. These methods may underestimate ROS concentrations in PM because of the potentially short lifetime of some ROS species; therefore, continuous online, highly time-resolved measurement of ROS components in PM is highly advantageous. In this work, we develop a novel online method for measuring aerosol OP based on ascorbic acid chemistry, an antioxidant prevalent in the lung, thus combining the advantages of continuous online measurement with a physiologically relevant assay. The method limit of detection is estimated for a range of atmospherically important chemical components such as Cu­(II) 0.22 ± 0.03 μg m–3, Fe­(II) 47.8 ± 5.5 μg m–3, Fe­(III) 0.63 ± 0.05 μg m–3, and secondary organic aerosol 41.2 ± 6.9 μg m–3, demonstrating that even at this early stage of development, the online method is capable of measuring the OP of PM in polluted urban environments and smog chamber studies.

We report methane isotopologue data from aircraft and ground measurements in Africa and South America. Aircraft campaigns sampled strong methane fluxes over tropical papyrus wetlands in the Nile, Congo and Zambezi basins, herbaceous wetlands in Bolivian southern Amazonia, and over fires in African woodland, cropland and savannah grassland. Measured methane δ 13 C CH 4 isotopic signatures were in the range −55 to −49‰ for emissions from equatorial Nile wetlands and agricultural areas, but widely −60 ± 1‰ from Upper Congo and Zambezi wetlands. Very similar δ 13 C CH 4 signatures were measured over the Amazonian wetlands of NE Bolivia (around −59‰) and the overall δ 13 C CH 4 signature from outer tropical wetlands in the southern Upper Congo and Upper Amazon drainage plotted together was −59 ± 2‰. These results were more negative than expected. For African cattle, δ 13 C CH 4 values were around −60 to −50‰. Isotopic ratios in methane emitted by tropical fires depended on the C3 : C4 ratio of the biomass fuel. In smoke from tropical C3 dry forest fires in Senegal, δ 13 C CH 4 values were around −28‰. By contrast, African C4 tropical grass fire δ 13 C CH 4 values were −16 to −12‰. Methane from urban landfills in Zambia and Zimbabwe, which have frequent waste fires, had δ 13 C CH 4 around −37 to −36‰. These new isotopic values help improve isotopic constraints on global methane budget models because atmospheric δ 13 C CH 4 values predicted by global atmospheric models are highly sensitive to the δ 13 C CH 4 isotopic signatures applied to tropical wetland emissions. Field and aircraft campaigns also observed widespread regional smoke pollution over Africa, in both the wet and dry seasons, and large urban pollution plumes. The work highlights the need to understand tropical greenhouse gas emissions in order to meet the goals of the UNFCCC Paris Agreement, and to help reduce air pollution over wide regions of Africa. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Abstract. Nitrous oxide is a potent greenhouse gas (GHG) and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions, which includes prior emissions with truncated Gaussian distributions and Gaussian model errors, in order to examine the drivers of the atmospheric surface growth rate. We show that both emissions and climatic variability are key drivers of variations in the surface nitrous oxide growth rate between 2011 and 2020. We derive increasing global nitrous oxide emissions, which are mainly driven by emissions between 0 and 30∘ N, with the highest emissions recorded in 2020. Our mean global total emissions for 2011–2020 of 17.2 (16.7–17.7 at the 95 % credible intervals) Tg N yr−1, comprising of 12.0 (11.2–12.8) Tg N yr−1 from land and 5.2 (4.5–5.9) Tg N yr−1 from ocean, agrees well with previous studies, but we find that emissions are poorly constrained for some regions of the world, particularly for the oceans. The prior emissions used in this and other previous work exhibit a seasonal cycle in the extra-tropical Northern Hemisphere that is out of phase with the posterior solution, and there is a substantial zonal redistribution of emissions from the prior to the posterior. Correctly characterizing the uncertainties in the system, for example in the prior emission fields, is crucial for deriving posterior fluxes that are consistent with observations. In this hierarchical inversion, the model-measurement discrepancy and the prior flux uncertainty are informed by the data, rather than solely through “expert judgement”. We show cases where this framework provides different plausible adjustments to the prior fluxes compared to inversions using widely adopted, fixed uncertainty constraints.

We present the first spatially resolved distribution of the δ D-CH 4 signature of wetland methane emissions and assess its impact on atmospheric δ D-CH 4 . The δ D-CH 4 signature map is derived by relating δ D-H 2 O of precipitation to measured δ D-CH 4 of methane wetland emissions at a variety of wetland types and locations. This results in strong latitudinal variation in the wetland δ D-CH 4 source signature. When δ D-CH 4 is simulated in a global atmospheric model, little difference is found in global mean, inter-hemispheric difference and seasonal cycle if the spatially varying δ D-CH 4 source signature distribution is used instead of a globally uniform value. This is because atmospheric δ D-CH 4 is largely controlled by OH fractionation. However, we show that despite these small differences, using atmospheric records of δ D-CH 4 to infer changes in the wetland emissions distribution requires the use of the more accurate spatially varying δ D-CH 4 source signature. We find that models will only be sensitive to changes in emissions distribution if spatial information can be exploited through the spatially resolved source signatures. In addition, we also find that on a regional scale, at sites measuring excursions of δ D-CH 4 from background levels, substantial differences are simulated in atmospheric δ D-CH 4 if using spatially varying or uniform source signatures. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 1)’.

Abstract. We present a method to efficiently approximate the response of atmospheric-methane mole fraction and δ13C–CH4 to changes in uncertain emission and loss parameters in a three-dimensional global chemical transport model. Our approach, based on Gaussian process emulation, allows relationships between inputs and outputs in the model to be efficiently explored. The presented emulator successfully reproduces the chemical transport model output with a root-mean-square error of 1.0 ppb and 0.05 ‰ for hemispheric-methane mole fraction and δ13C–CH4, respectively, for 28 uncertain model inputs. The method is shown to outperform multiple linear regression because it captures non-linear relationships between inputs and outputs as well as the interaction between model input parameters. The emulator was used to determine how sensitive methane mole fraction and δ13C–CH4 are to the major source and sink components of the atmospheric budget given current estimates of their uncertainty. We find that our current knowledge of the methane budget, as inferred through hemispheric mole fraction observations, is limited primarily by uncertainty in the global mean hydroxyl radical concentration and freshwater emissions. Our work quantitatively determines the added value of measurements of δ13C–CH4, which are sensitive to some uncertain parameters to which mole fraction observations on their own are not. However, we demonstrate the critical importance of constraining isotopic initial conditions and isotopic source signatures, small uncertainties in which strongly influence long-term δ13C–CH4 trends because of the long timescales over which transient perturbations propagate through the atmosphere. Our results also demonstrate that the magnitude and trend of methane mole fraction and δ13C–CH4 can be strongly influenced by the combined uncertainty in more minor components of the atmospheric budget, which are often fixed and assumed to be well-known in inverse-modelling studies (e.g. emissions from termites, hydrates, and oceans). Overall, our work provides an overview of the sensitivity of atmospheric observations to budget uncertainties and outlines a method which could be employed to account for these uncertainties in future inverse-modelling systems.

Abstract. We present a method to efficiently approximate the response of atmospheric methane mole fraction and δ13C-CH4 to changes in uncertain emission and loss parameters in a three-dimensional global chemical transport model. Our approach, based on Gaussian process emulation, allows relationships between inputs and outputs in the model to be efficiently explored. The presented emulator successfully reproduces the chemical transport model output with a root-mean-square error of 1.2 ppb and 0.06 ‰ for hemispheric methane mole fraction and δ13C-CH4, respectively, for 28 uncertain model inputs. The method is shown to outperform multiple linear regression, because it captures non-linear relationships between inputs and outputs, as well as the interaction between model input parameters. The emulator was used to determine how sensitive methane mole fraction and δ13C-CH4 are to the major source and sink components of the atmospheric budget, given current estimates of their uncertainty. We find that our current knowledge of the methane budget, as inferred through hemispheric mole fraction observations, is limited primarily by uncertainty in the global mean hydroxyl radical concentration and emissions from fresh water. Our work quantitatively determines the added value of measurements of δ13C-CH4, which are sensitive to some uncertain parameters that mole fraction observations on their own are not. However, we demonstrate the critical importance of constraining isotopic initial conditions and isotopic source signatures, small uncertainties in which strongly influence long-term δ13C-CH4 trends, because of the long timescales over which transient perturbations propagate through the atmosphere. Our results also demonstrate that the magnitude and trend of methane mole fraction and δ13C-CH4 can be strongly influenced by the combined uncertainty of more minor components of the atmospheric budget, which are often fixed and assumed to be well-known in inverse modelling studies (e.g. emissions from termites, hydrates, and oceans). Overall, our work provides an overview of the sensitivity of atmospheric observations to budget uncertainties and outlines a method which could be employed to account for these uncertainties in future inverse modelling systems.

<p>We present the first spatially varying map of the δD-CH<sub>4 </sub>signature of wetland methane emissions and model its impact on atmospheric δD-CH<sub>4</sub>. The δD-CH<sub>4</sub> signature map is derived by relating the δD-H<sub>2</sub>O of precipitation to the measured δD-CH<sub>4</sub> of methane wetland emissions at a variety of wetland types and locations. Since the δD-H<sub>2</sub>O of precipitation is highly latitude-dependent, including this spatial variation has the potential to have a large impact on the distribution of δD-CH<sub>4</sub> observed in the atmosphere. This latitude-dependence means that wetland emissions at different latitudes can have very different impacts on atmospheric δD-CH<sub>4</sub>, which could provide a useful way to constrain the location of wetland methane emissions in future inverse modelling studies. Here, we assess the implications for model studies on the differences that arise by treating δD-CH<sub>4</sub> wetland source signatures as globally uniform rather than accounting for the large spatial variation. We also assess the potential for δD-CH<sub>4</sub> to provide an independent constraint on wetland emissions over the more abundant and widely measured δ<sup>13</sup>C-CH<sub>4</sub>.</p>