Abstract
Abstract. A new analytical inversion method has been developed to determine the regional and global emissions of long-lived atmospheric trace gases. It exploits in situ measurement data from three global networks and builds on backward simulations with a Lagrangian particle dispersion model. The emission information is extracted from the observed concentration increases over a baseline that is itself objectively determined by the inversion algorithm. The method was applied to two hydrofluorocarbons (HFC-134a, HFC-152a) and a hydrochlorofluorocarbon (HCFC-22) for the period January 2005 until March 2007. Detailed sensitivity studies with synthetic as well as with real measurement data were done to quantify the influence on the results of the a priori emissions and their uncertainties as well as of the observation and model errors. It was found that the global a posteriori emissions of HFC-134a, HFC-152a and HCFC-22 all increased from 2005 to 2006. Large increases (21%, 16%, 18%, respectively) from 2005 to 2006 were found for China, whereas the emission changes in North America (−9%, 23%, 17%, respectively) and Europe (11%, 11%, −4%, respectively) were mostly smaller and less systematic. For Europe, the a posteriori emissions of HFC-134a and HFC-152a were slightly higher than the a priori emissions reported to the United Nations Framework Convention on Climate Change (UNFCCC). For HCFC-22, the a posteriori emissions for Europe were substantially (by almost a factor 2) higher than the a priori emissions used, which were based on HCFC consumption data reported to the United Nations Environment Programme (UNEP). Combined with the reported strongly decreasing HCFC consumption in Europe, this suggests a substantial time lag between the reported time of the HCFC-22 consumption and the actual time of the HCFC-22 emission. Conversely, in China where HCFC consumption is increasing rapidly according to the UNEP data, the a posteriori emissions are only about 40% of the a priori emissions. This reveals a substantial storage of HCFC-22 and potential for future emissions in China. Deficiencies in the geographical distribution of stations measuring halocarbons in relation to estimating regional emissions are also discussed in the paper. Applications of the inversion algorithm to other greenhouse gases such as methane, nitrous oxide or carbon dioxide are foreseen for the future.
Highlights
Over the past few decades, halocarbons have been used for refrigeration, as solvents, aerosol propellants, for foam blowing and for many other applications
The HFC and HCFC data used in our inversions come from the three in situ atmospheric measurement networks listed in Table 1: Advanced Global Atmospheric Gases Experiment (AGAGE) (Prinn et al, 2000); System for Observation of Halogenated Greenhouse Gases in Europe (SOGE) (Greally et al, 2007); and Japanese National Institute for Environmental Studies (NIES) (Yokouchi et al, 2006)
The method is based on 20 d backward simulations from a number of measurement stations using a Lagrangian particle dispersion model
Summary
Over the past few decades, halocarbons have been used for refrigeration, as solvents, aerosol propellants, for foam blowing and for many other applications. The uncertainty treatment allows, for the first time in regional-scale inversions of halocarbon emissions, to use data from several stations concurrently. The HFC and HCFC data used in our inversions come from the three in situ atmospheric measurement networks listed in Table 1: Advanced Global Atmospheric Gases Experiment (AGAGE) (Prinn et al, 2000); System for Observation of Halogenated Greenhouse Gases in Europe (SOGE) (Greally et al, 2007); and Japanese National Institute for Environmental Studies (NIES) (Yokouchi et al, 2006). The choice of the 20 d length of the backward simulations was motivated by the fact that the value for the inversion of every additional simulation day decreases rapidly with time backward This has three reasons: 1) Since we were using data from surface stations, the total emission sensitivity in the footprint layer per day of backward calculation is largest www.atmos-chem-phys.net/9/1597/2009/. That the baseline as defined below depends on the duration of the simulation: longer simulations result in a lower baseline, as more emissions are directly accounted for
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