Re-Evaluation of the UK’s HFC-134a Emissions Inventory Based on Atmospheric Observations

Independent verification of national greenhouse gas inventories is a vital measure for cross-checking the accuracy of emissions data submitted to the United Nations Framework Convention on Climate Change (UNFCCC). We infer annual UK emissions of HFC-134a from 1995 to 2012 using atmospheric observations and an inverse modeling technique, and compare with the UK’s annual UNFCCC submission. By 2010, the inventory is almost twice as large as our estimates, with an “emissions gap” equating to 3.90 (3.20–4.30) Tg CO₂e. We evaluate the RAC (Refrigeration and Air-Conditioning) model, a bottom up model used to quantify UK emissions from refrigeration and air-conditioning sectors. Within mobile air-conditioning (MAC), the largest RAC sector and most significant UK source (59%), we find a number of assumptions that may be considered oversimplistic and conservative; most notably the unit refill rate. Finally, a Bayesian approach is used to estimate probable inventory inputs required for minimization of the emissions discrepancy. Our top-down estimates provide only a weak constraint on inventory model parameters and consequently, we are unable to suggest discrete values. However, a significant revision of the MAC servicing rate, coupled with a reassessment of non-RAC aerosol emissions, are required if the discrepancy between methods is to be reduced

Consumption of CH3Cl, CH3Br, and CH3I and emission of CHCl3, CHBr3, and CH2Br2 from the forefield of a retreating Arctic glacier

The Arctic is one of the most rapidly warming regions of the Earth, with predicted temperature increases of 5–7 ∘C and the accompanying extensive retreat of Arctic glacial systems by 2100. Retreating glaciers will reveal new land surfaces for microbial colonisation, ultimately succeeding to tundra over decades to centuries. An unexplored dimension to these changes is the impact upon the emission and consumption of halogenated organic compounds (halocarbons). Halocarbons are involved in several important atmospheric processes, including ozone destruction, and despite considerable research, uncertainties remain in the natural cycles of some of these compounds. Using flux chambers, we measured halocarbon fluxes across the glacier forefield (the area between the present-day position of a glacier's ice-front and that at the last glacial maximum) of a high-Arctic glacier in Svalbard, spanning recently exposed sediments (<10 years) to approximately 1950-year-old tundra. Forefield land surfaces were found to consume methyl chloride (CH3Cl) and methyl bromide (CH3Br), with both consumption and emission of methyl iodide (CH3I) observed. Bromoform (CHBr3) and dibromomethane (CH2Br2) have rarely been measured from terrestrial sources but were here found to be emitted across the forefield. Novel measurements conducted on terrestrial cyanobacterial mats covering relatively young surfaces showed similar measured fluxes to the oldest, vegetated tundra sites for CH3Cl, CH3Br, and CH3I (which were consumed) and for CHCl3 and CHBr3 (which were emitted). Consumption rates of CH3Cl and CH3Br and emission rates of CHCl3 from tundra and cyanobacterial mat sites were within the ranges reported from older and more established Arctic tundra elsewhere. Rough calculations showed total emissions and consumptions of these gases across the Arctic were small relative to other sources and sinks due to the small surface area represented by glacier forefields. We have demonstrated that glacier forefields can consume and emit halocarbons despite their young age and low soil development, particularly when cyanobacterial mats are present

UK greenhouse gas measurements at two new tall towers for aiding emissions verification

Abstract. Under the UK focused Greenhouse gAs and Uk and Global Emissions (GAUGE) project, two new tall tower greenhouse gas (GHG) observation sites were established in the 2013/2014 Northern Hemispheric winter. These sites were located at two existing telecommunications towers, Heathfield (HFD) and Bilsdale (BSD), utilised a combination of cavity ring-down spectroscopy (CRDS) and gas chromatography (GC) to measure key GHGs (CO2, CH4, CO, N2O and SF6). Measurements were made at multiple intake heights on each tower. The inclusion of the two additional tower stations within the existing UK Deriving Emissions linked to Climate Change (DECC) network of four stations was found to reduce the uncertainty of CH4 UK emission estimates by between 10–20 %. CO2 and CH4 dry mole fractions were calculated from either CRDS measurements of wet air which were post corrected with an instrument specific empirical correction or samples dried to between 0.05 and 0.3 % H2O using a Nafion dryer, with a smaller correction applied for the residual H2O. The impact of these two drying strategies was examined. Drying with a Nafion drier was not found to have a significant effect on the observed CH4 mole fraction; however, Nafion drying did cause a 0.02 µmol mol−1 CO2 bias. This bias was stable with sample CO2 mole fractions between 373 and 514 µmol mol−1 and for sample H2O up to 3.5 %. As the calibration and standard gases are treated in the same manner, this error is mostly calibrated out with the residual error below the World Meteorological Organization’s (WMO) reproducibility requirements. Of more concern was the error associated with both default factory and empirical instrument specific water correction algorithms. These corrections are relatively stable and reproducible for samples with H2O between 0.2 and 2.5 %, CO2 between 345 and 449 µmol mol−1 and CH4 between 1743 and 2145 nmol mol−1. However, the residual errors in these corrections increase to &gt; 0.05 µmol mol−1 for CO2 and &gt; 1 nmol mol−1 for CH4 (greater than the WMO internal reproducibility guidelines) at higher humidities and for samples with very low ( </jats:p

Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion

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.</p

Changing trends and emissions of hydrochlorofluorocarbons (HCFCs) and their hydrofluorocarbon (HFCs) replacements

United States. National Aeronautics and Space Administration (NAG5-12669)United States. National Aeronautics and Space Administration (NNX07AE89G)United States. National Aeronautics and Space Administration (NNX11AF17G)United States. National Aeronautics and Space Administration (NNX16AC98G

Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion

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.</p