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

Authors: Say, Dan S; Manning, Alistair J; O'Doherty, Simon; Rigby, Matthew; Young, Dickon; Grant, Aoife;

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

Abstract

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.

Country
United Kingdom
Related Organizations
Keywords

Air Pollutants, United Nations, Climate Change, Air Conditioning, Bayes Theorem

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
Green
hybrid