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)’.