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Methane (CH4) is a potent greenhouse gas with a warming potential 84 times that of carbon dioxide (CO2) over a 20-year period. Atmospheric CH4 concentrations have been rising since the nineteenth century but the cause of large increases post-2007 is disputed. Tropical wetlands are thought to account for ∼20% of global CH4 emissions, but African tropical wetlands are understudied and their contribution is uncertain. In this work, we use the first airborne measurements of CH4 sampled over three wetland areas in Zambia to derive emission fluxes. Three independent approaches to flux quantification from airborne measurements were used: Airborne mass balance, airborne eddy-covariance, and an atmospheric inversion. Measured emissions (ranging from 5 to 28 mg m−2 hr−1) were found to be an order of magnitude greater than those simulated by land surface models (ranging from 0.6 to 3.9 mg m−2 hr−1), suggesting much greater emissions from tropical wetlands than currently accounted for. The prevalence of such underestimated CH4 sources may necessitate additional reductions in anthropogenic greenhouse gas emissions to keep global warming below a threshold of 2°C above preindustrial levels.

Arctic wetlands and surrounding ecosystems are both a significant source of methane (CH4) and a sink of carbon dioxide (CO2) during summer months. However, precise quantification of this regional CH4source and CO2sink remains poorly characterized. A research flight using the UK Facility for Airborne Atmospheric Measurement was conducted in July 2019 over an area (approx. 78 000 km2) of mixed peatland and forest in northern Sweden and Finland. Area-averaged fluxes of CH4and carbon dioxide were calculated using an aircraft mass balance approach. Net CH4fluxes normalized to wetland area ranged between 5.93 ± 1.87 mg m−2 h−1and 4.44 ± 0.64 mg m−2 h−1(largest to smallest) over the region with a meridional gradient across three discrete areas enclosed by the flight survey. From largest to smallest, net CO2sinks ranged between −513 ± 74 mg m−2 h−1and −284 ± 89 mg m−2 h−1and result from net uptake of CO2by vegetation and soils in the biosphere. A clear gradient of decreasing bulk and area-averaged CH4flux was identified from north to south across the study region, correlated with decreasing peat bog land area from north to south identified from CORINE land cover classifications. While N2O mole fraction was measured, no discernible gradient was measured over the flight track, but a minimum flux threshold using this mass balance method was calculated. Bulk (total area) CH4fluxes determined via mass balance were compared with area-weighted upscaled chamber fluxes from the same study area and were found to agree well within measurement uncertainty. The mass balance CH4fluxes were found to be significantly higher than the CH4fluxes reported by many land-surface process models compiled as part of the Global Carbon Project. There was high variability in both flux distribution and magnitude between the individual models. This further supports previous studies that suggest that land-surface models are currently ill-equipped to accurately capture carbon fluxes inthe region.This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Appropriate techniques to quantify greenhouse gas emission reductions in cities over time are necessary to monitor the progress of these efforts and effectively inform continuing mitigation. We introduce a scaling factor (SF) method that combines aircraft measurements and dispersion modeling to estimate urban emissions and apply it to 9 nongrowing season research aircraft flights around New York City (NYC) in 2018–2020. This SF approach uses a weighting function to focus on an area of interest while still accounting for upwind emissions. We estimate carbon dioxide (CO2) emissions from NYC and the Greater New York Area (GNA) and compare to nested inversion analyses of the same data. The average calculated CO2 emission rates for NYC and the GNA, representative of daytime emissions for the flights, were (49 ± 16) kmol/s and (144 ± 44) kmol/s, respectively (uncertainties reported as ±1σ variability across the 9 flights). These emissions are within ∼15% of an inversion analysis and agree well with inventory estimates. By using an ensemble, we also investigate the variability introduced by several sources and find that day-to-day variability dominates the overall variability. This work investigates and demonstrates the capability of an SF method to quantify emissions specific to particular areas of interest.

Cities are greenhouse gas emission hot spots, making them targets for emission reduction policies. Effective emission reduction policies must be supported by accurate and transparent emissions accounting. Top-down approaches to emissions estimation, based on atmospheric greenhouse gas measurements, are an important and complementary tool to assess, improve, and update the emission inventories on which policy decisions are based and assessed. In this study, we present results from 9 research flights measuring CO2 and CH4 around New York City during the nongrowing seasons of 2018–2020. We used an ensemble of dispersion model runs in a Bayesian inverse modeling framework to derive campaign-average posterior emission estimates for the New York–Newark, NJ, urban area of (125 ± 39) kmol CO2 s–1 and (0.62 ± 0.19) kmol CH4 s–1 (reported as mean ± 1σ variability across the nine flights). We also derived emission estimates of (45 ± 18) kmol CO2 s–1 and (0.20 ± 0.07) kmol CH4 s–1 for the 5 boroughs of New York City. These emission rates, among the first top-down estimates for New York City, are consistent with inventory estimates for CO2 but are 2.4 times larger than the gridded EPA CH4 inventory, consistent with previous work suggesting CH4 emissions from cities throughout the northeast United States are currently underestimated.

Hydraulic fracturing (fracking) is a short phase in unconventional oil and natural gas (O&G) development. Before fracking there is a lengthy period of preparation, which can represent a significant proportion of the well lifecycle. Extensive infrastructure is delivered onto site, leading to increased volumes of heavy traffic, energy generation and construction work on site. Termed the “pre-operational” period, this is rarely investigated as air quality evaluations typically focus on the extraction phase. In this work we quantify the change in air pollution during pre-operational activities at a shale gas exploration site near Kirby Misperton, North Yorkshire, England. Baseline air quality measurements were made two years prior to any shale gas activity and were used as a training dataset for random forest (RF) machine learning models. The models allowed for a comparison between observed air quality during the pre-operational phase and a counterfactual business as usual (BAU) prediction. During the pre-operational phase a significant deviation from the BAU scenario was observed. This was characterised by significant enhancements in NOx and a concurrent reduction in O3, caused by extensive additional vehicle movements and the presence of combustion sources such as generators on the well pad. During the pre-operational period NOx increased by 274 % and O3 decreased by 29 % when compared to BAU model values. There was also an increase in primary emissions of NO2 during the pre-operational phase which may have implications for the attainment of ambient air quality standards in the local surroundings. Unconventional O&G development remains under discussion as a potential option for improving the security of supply of domestic energy, tensioned however against significant environmental impacts. Here we demonstrate that the preparative work needed to begin fracking elevates air pollution in its own right, a further potential disbenefit that should be considered.

The atmospheric methane (CH 4 ) burden is rising sharply, but the causes are still not well understood. One factor of uncertainty is the importance of tropical CH 4 emissions into the global mix. Isotopic signatures of major sources remain poorly constrained, despite their usefulness in constraining the global methane budget. Here, a collection of new δ 13 C CH 4 signatures is presented for a range of tropical wetlands and rice fields determined from air samples collected during campaigns from 2016 to 2020. Long-term monitoring of δ 13 C CH 4 in ambient air has been conducted at the Chacaltaya observatory, Bolivia and Southern Botswana. Both long-term records are dominated by biogenic CH 4 sources, with isotopic signatures expected from wetland sources. From the longer-term Bolivian record, a seasonal isotopic shift is observed corresponding to wetland extent suggesting that there is input of relatively isotopically light CH 4 to the atmosphere during periods of reduced wetland extent. This new data expands the geographical extent and range of measurements of tropical wetland and rice δ 13 C CH 4 sources and hints at significant seasonal variation in tropical wetland δ 13 C CH 4 signatures which may be important to capture in future global and regional models. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’.

Nitrous oxide (N 2O) is a potent greenhouse gas that is currently the third largest contributor to anthropogenic radiative forcing. It is also a strong ozone depleting substance. Given this importance, mitigation of N 2O emissions remains important and sources must be understood in greater detail. In this study, in situ measurements of N 2O alongside a variety of other trace gases and aerosols were made from a ground-based air quality observation site in an urban environment of Fallowfield, Manchester, United Kingdom over a period of 12 months between October 2020 and October 2021. N 2O mole fraction was observed to be poorly correlated with other atmospheric pollutant tracers during the measurement period, with little evidence of co-enhancement (and therefore common source relationships) between N 2O and other local pollutant trace gases and aerosol. Large N 2O enhancements (> 400 ppb above background) over short time scales (< 2 min) were seen with no co-enhancement of other trace gases and aerosol concentrations, suggesting discrete N 2O sources in the near vicinity of the measurement site. Measured N 2O concentrations showed a consistent temporal pattern over day, week, and year timescales with consistently large weekend enhancements observed between the hours of 18:00 and 02:00 local time, suggesting the source of N 2O may be associated with night-time recreational use by nearby residents. These weekend-night-time temporal patterns were not correlated with other trace gases measured at the same location. Analysis of the air transport history of N 2O measurements showed high mean nocturnal mole fractions originating from the west and south-west of the observation site, suggesting that emissions may have originated from nearby areas of student accommodation and dense areas of private housing to the west. This study finds evidence for a detectable recreational N 2O source that appears to be dominant over other potential N 2O sources for the area studied. Further study is needed to quantify the local and national emission rates of this potentially increasing atmospheric pollution source, and to compare the magnitude of this source to other locations within the UK. The study demonstrates an important need to assess and validate National Atmospheric Emission Inventory (NAEI) estimates for recreational N 2O emissions.

Airborne sampling of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), and nitrous oxide (N2O) mole fractions was conducted during field campaigns targeting fires over Senegal in February and March 2017, and Uganda in January 2019. The majority of fire plumes sampled were close to, or directly over burning vegetation, with the exception of two longer-range flights over the West African Atlantic seaboard, (100–300 km from source) where the continental outflow of biomass burning emissions from a wider area of West Africa was sampled. Fire Emission Factors (EFs) and modified combustion efficiencies (MCEs) were estimated from the enhancements in measured mole fractions. For the Senegalese fires, mean EFs and corresponding one-standard deviation variabilities, in units of g per kg of dry fuel were 1.8 (± 0.06) for CH4, 1633 (± 56.4) for CO2 and 679 (± 1.6) for CO, with a mean MCE of 0.94 (± 0.005). For the Ugandan fires, mean EFs (in units of g kg−1) were 3.1 (± 0.1) for CH4, 1610 (± 54.9) for CO2 and 78 (± 1.9) for CO, with a mean modified combustion efficiency of 0.93 (± 0.004). A mean N2O EF of 0.08 (± 0.002) g kg−1 is also reported for one flight over Uganda; issues with temperature control of the instrument optical bench prevented N2O EFs from being obtained for other flights over Uganda. This study has provided new datasets of African biomass burning EFs and MCEs for two distinct study regions, in which both have been studied little by aircraft measurement previously. These results highlight the important intracontinental variability of biomass burning trace gas emissions, and can be used to better constrain future biomass burning emission budgets. More generally, these results highlight the importance of regional and fuel-type variability when attempting to spatially scale biomass burning emissions. Further work to constrain EFs at more local scales and for more specific (and quantifiable) fuel types will serve to improve global estimates of biomass burning emissions of climate-relevant gases.

This paper describes the development of a new sampling and measurement method to infer methane flux using proxy measurements of CO