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基于大气观测的英国 HFC-134a 排放清单再评估。

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

机构信息

Atmospheric Chemistry Research Group, University of Bristol , Bristol BS8 1TS, U.K.

Met Office Hadley Centre, Exeter EX1 3PB, U.K.

出版信息

Environ Sci Technol. 2016 Oct 18;50(20):11129-11136. doi: 10.1021/acs.est.6b03630. Epub 2016 Sep 30.

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 COe. 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.

摘要

独立验证各国温室气体清单是对向联合国气候变化框架公约(UNFCCC)提交的排放数据进行准确性交叉检查的重要措施。我们使用大气观测和反演模型推断了 1995 年至 2012 年英国 HFC-134a 的年排放量,并将其与英国的年度 UNFCCC 提交数据进行了比较。到 2010 年,清单几乎是我们估计的两倍,“排放差距”相当于 3.90(3.20-4.30)Tg COe。我们评估了 RAC(制冷和空调)模型,这是一个用于量化制冷和空调部门英国排放量的自下而上的模型。在移动空调(MAC)中,这是最大的 RAC 部门和最重要的英国排放源(59%),我们发现了一些可能被认为过于简单和保守的假设;最显著的是单位补充率。最后,采用贝叶斯方法来估计最小化排放差异所需的清单输入的可能值。我们的自上而下的估计对清单模型参数的约束作用很弱,因此,我们无法提出离散的值。然而,如果要减少方法之间的差异,则需要对 MAC 服务率进行重大修订,并重新评估非 RAC 气溶胶排放。

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