Emissions of Carbon Tetrachloride (CCl4) from Europe

Carbon tetrachloride (CCl4) is a long-lived radiatively-active compound able to destroy stratospheric ozone. Due to its inclusion in the Montreal Protocol on Substances that Deplete the Ozone Layer, the last two decades have seen a sharp decrease in its large scale emissive use with a consequent decline of its atmospheric mole fractions. However, the Montreal Protocol restrictions do not apply to the use of carbon tetrachloride as feedstock for the production of other chemicals, 20 implying the risk of fugitive emissions from the industry sector. The occurrence of such unintended emissions is suggested by a significant discrepancy between global emissions as derived by reported production and feedstock usage (bottom-up emissions), and those based on atmospheric observations (top-down emissions). In order to better constrain the atmospheric budget of carbon tetrachloride, several studies based on a combination of atmospheric observations and inverse 25 modelling have been conducted in recent years in various regions of the world. This study is focused on the European scale and based on long-term high-frequency observations at three European sites, combined with a Bayesian inversion methodology. We estimated that average European emissions for 2006 -2014 were 2.3 (± 0.8) Gg yr, with an average decreasing trend of 7.3 % per year. Our analysis identified France as the main source of emissions over the whole study 30 period, with an average contribution to total European emissions of 25%. The inversion was also able to allow the localisation of emission “hot-spots” in the domain, with major source areas in Southern France, Central England (UK) and Benelux (Belgium, The Netherlands, Luxembourg), where most of industrial scale production of basic organic chemicals are located. According to our Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-326, 2016 Manuscript under review for journal Atmos. Chem. Phys. Published: 25 April 2016 c © Author(s) 2016. CC-BY 3.0 License.

results, European emissions correspond to 4.0 % of global emissions for 2006-2012. Together with 35 other regional studies, our results allow a better constraint of the global budget of carbon tetrachloride and a better quantification of the gap between top-down and bottom-up estimates.

1.Introduction
Carbon tetrachloride (CCl 4 ) is a nearly exclusively anthropogenic compound whose first uses as 40 solvent, fire extinguisher, fumigant and rodenticide date back to 1908 (Galbally, 1976;Happell et al., 2014). The rapid increase in its production occurring between the 1950s and the 1980s is linked mainly to its use as a solvent and also to the growth in the production of chlorofluorocarbons (CFCs) made from CCl 4 (Simmonds et al., 1998). This led to a significant increase in the atmospheric mixing ratios of CCl 4 , as shown by firn air analysis (Sturrock et al., 2002). The 45 tropospheric lifetime, of 26 years (SPARC 2013) to 35 years (Liang et al., 2014) is the result of the sum of three partial loss rates: loss in the stratosphere (Laube et al., 2013), degradation in the ocean (Yvon-Lewis and Butler, 2002) and degradation in the soil (Happell et al., 2014).
Main concerns about this long-lived chemical are linked to its capability to destroy the stratospheric ozone layer and as a radiatively active gas, with an ozone depleting potential (ODP) of 0.72 (Harris 50 and Wuebbles et al., 2014) and a global warming potential (GWP) of 1,730 (Myhre et al., 2013).
The inclusion of CCl 4 in the Montreal Protocol on Substances that Deplete the Ozone Layer (MP) led to a sharp decrease in CCl 4 's large scale emissive use and the consequent decline in its atmospheric mixing ratios was observed starting in the early 1990s (Fraser et al., 1994;Simmonds et al., 1998), with peak mole fractions of around 103 part per trillion (ppt) and 101 ppt in 1991 in 55 the Northern Hemisphere (NH) and Southern Hemisphere (SH), respectively (Walker et al., 2000).
In 2012 CCl 4 measured global average mole fractions were 84.2 and 85.1 ppt, as measured by the AGAGE (Advanced Global Atmospheric Gases Experiment) and NOAA-GMD (National Oceanic and Atmospheric Administration-Global Monitoring Division) ground-based sampling networks, respectively. The respective decrease rates during 2011-2012 were 1.2 and 1.6% yr -1 (Carpenter and 60 the industry sector (Simmonds et al., 1998), generation during bleaching (Odabasi et al., 2014) or emissions from a legacy of CCl 4 in old landfill (Fraser et al. 2014). 70 The persistence of such emissions is suggested by a discrepancy between global emissions as derived from reported production and feedstock usage (bottom-up emissions) and those based on atmospheric observations (top-down emissions). Assuming a total atmospheric lifetime of 26 years and the observed trend in the atmosphere, the top-down global CCl 4 emission estimates suggest for 2011-2012 global CCl 4 emissions are 57 (40-74) Gg yr -1 , a value that is at least one order of 75 magnitude higher than estimates based on industrial use (Carpenter and Reimann et al., 2014). In addition the persistence of an inter-hemispheric gradient of about 1.3 ppt (NH minus SH) since 2006, reinforces the hypothesis that CCl 4 is still emitted in the NH (Carpenter and Reimann et al., 2014). Similar results have been obtained by Liang et al. (2014), who deduced that the mean global emissions during 2000-2012 were 39 Gg yr -1 (34-45 Gg yr -1 ) with a calculated total atmospheric 80 lifetime for CCl 4 of 35 (32-37) years.
In order to better constrain the CCl 4 budget, several top-down studies have been conducted in recent years focused on the global and regional scale, the top-down approach having been recognised as an important independent verification tool for bottom-up reporting (Nisbet and Weiss, 2010;Weiss and Prinn, 2011;Lunt et al., 2015). identifying South-East Asia as being responsible of more than half of the global industrial emissions, which they estimated as 74.1 ± 4.3 Gg yr -1 (9-year average).
The role of China as a significant source region of CCl 4 has been highlighted by Vollmer et al. 90 (2009)  According to Fraser et al. (2014) top-down Australian emissions during 1996-2011 have declined 95 from 0.25-0.35 Gg yr -1 to 0.12-0.18 Gg yr -1 . In this study potential sources other than those arising from production, transport and use were identified and on the basis of an analysis of pollution episodes, were likely to be associated with contaminated soils, toxic waste treatment facilities and chlor-alkali plants. For Europe, the most recent estimates are given in the above-cited paper by Xiao et al. (2010), who reported that Europe has been responsible, over 1996-2004, for 4% of global emissions. However 110 this study, based on observations conducted at global baseline sites, does not take into account regional variations that might occur across the different European countries and that could help in identifying specific emission sources, including those unrelated to reported production.
With this aim, we conducted a study based on long-term, high-frequency CCl 4 observations carried out at three European sites combined with FLEXPART and the Bayesian inversion approach 115 developed by Seibert (2000;2001), improved by Eckhardt et al. (2008) and Stohl et al. (2009; and recently applied to derive emissions of halogenated species at the European scale (Maione et al., 2014;Graziosi et al., 2015).
Even though major source regions are likely to be located in East Asia, our results, in combination with those obtained from other regional studies, are useful in order to better assess the global budget 120 of CCl 4 and better evaluate to what extent future emissions will affect the evolution of the equivalent effective stratospheric chlorine (EESC).

Measurements 125
In Europe CCl 4 long-term, high-frequency observations of CCl 4 are available from three sites, all electron capture detection (GC-ECD), without sample enrichment . All the measurements are reported using the Scripps Institution of Oceanography (SIO), SIO-05 gravimetric primary calibration scale: ambient air measurements are routinely calibrated against whole air working standard that have been filled locally, using a bracketing technique, to override 140 short term instrumental drifts. Working standards are then referenced on a weekly basis to tertiary tank (provided and calibrated by SIO) on site for the GC-MS measurements, i.e. CMN and JFJ. For the Mace Head GC-ECD instrument the tertiary tanks are used as the working standard are prepared and regularly calibrated at SIO at least twice, at the beginning and end of the life of the tank Miller et al., 2008). For this reason the contribution of the scale transfer (calibration) 145 uncertainty to the total measurement uncertainty is minimized among stations, constraining the error estimate to the instrumental precision, calculated as the standard deviation (1σ) of the repeated working standard measurements for the covered period, that is typical for each site/setup and almost constant over the years of observation: CMN ± 0.39 ppt; JFJ ± 0.86 ppt and MHD ± 0.24 ppt. In addition, the analytical systems at the three stations are operated via the Linux-based 150 chromatography software GCWerks (gcwerks.com) developed within the AGAGE programme.

Inverse modelling
Observations have been combined with 20-days backward trajectories of the FLEXPART Lagrangian Particle Dispersion Model (Stohl et al., 2005). FLEXPART runs are based on the 155 European Centre for Medium-range Weather Forecast wind fields, using 3-hourly ERA-Interim reanalyses (analysis fields are at 00:00, 06:00, 12:00 and 18:00 UTC, and 3-h forecasts are at 03:00, 09:00, 15:00 and 21:00 UTC) with 1°x1° horizontal resolution and 91 vertical levels. The emission sensitivity map of source-receptor relationships (SRR) generated using the three European stations is reported in Fig.1. The obtained SRR combined with an a priori emission field allowed us to 160 estimate the a posteriori emission flux for the European Geographic Domain (EGD), using the Bayesian inversion technique.
With the aim of obtaining the best performance of the model in terms of correlation coefficient between the observations and the modelled time series, we tested various a priori emission field settings. The best model performance was obtained using an a priori emission field built combining 165 the emission fluxes estimated by Xiao et al. (2010) and those available at the European Pollutant ii) for the years from 2007 to 2013, the corresponding fraction of E-PRTR, on average 4.1% of total intensity a priori emission, was allocate following the geo referenced information of the same data base, while the remaining part of emission was disaggregated according to the population data density as previously described. 180 The inversion grid consists of more than 5.000 grid boxes with different horizontal resolution ranging from 0.5° by 0.5° to 2.0° by 2.0° latitude-longitude in order to assure similar weight on the

200
CCl 4 emission intensity from the EGD and emission distribution within the same domain has been estimated using the European observations and the described Bayesian inversion technique. As shown in Figure

European emissions and emission trends 210
The inversion results indicate average EGD emissions during study period of 2.3 (± 0.8) Gg yr -1 .
CCl 4 total emissions from the EGD have decreased from ~ 3.1 (± 1.2) Gg yr -1 in 2006 to ~ 1.5 (± 0.5) Gg yr -1 in 2014, corresponding to an average EGD decreasing trend of 7.3 % per year. EGD and macro-areas emission estimates for the single years are given in Table I. Such figures cannot be reconciled with potential emissions estimated from production data reported to UNEP that for 215 Europe are negative along the study period with exception of 2012 (UNEP Production data base).
Such discrepancy holds also if a 2% of fugitive emissions and a 75% of destruction efficiency are considered. Also when comparing our estimates with emissions from the industrial activities declared to the E-PRTR, we found the latter to be strongly (on average 35 times) under-estimated, reinforcing the incompleteness of available information. 220

Emission distribution within the domain
The obtained EGD a posteriori emission fluxes differ from the a priori both in intensity (as described above) and in spatial distribution.
In order to quantitatively assess the contribution to the CCl 4 overall European emissions from the 225 various countries, we have divided our domain into ten macro areas, whose extension is related to the SRR of the area (see Figure 1). Emissions from the single macro areas and the associated uncertainty (see Supplementary Material) are reported in Table 1 and in Figure 4a. Figure 4b shows the percentage contribution from the single macro areas.
Our estimates identify FR as the main emitter in the EGD all over the study period, with an average 230 contribution of 25%. Five macro areas (ES-PT > NEE > DE-AT > UK-IE > IT) contribute between 14.5 and 9.1%, while the remaining regional contributions average 5% each. Emissions from France reached the maximum in 2010. Emissions from IT, CH and from NEE show a faster decreasing trend with respect to the average EGD rate and the remaining macro areas decreased according to the overall average EGD emissions. As a result, starting from 2009, the percent contribution of 235 France is about the 30 % of total EGD emissions.  Figure 5 show the a priori (Fig. 5a) and a posteriori (Fig. 5b) Figure 5b shows how, in general, the localisation of the main declared emission sources is well captured by the inversion, as in the case of Southern France, Central England (UK) and BE-NE-LUX. According to the E-PRTR inventory, these hot-spots account for more than 90% of the industrial scale production of basic organic chemicals. The hot spots are observed even when the inversion is run using the a-priori emission field that does not 250

Emission hot spots
include the E-PRTR information on industrial emissions, indicating that the emission hot spots are not forced by the a priori flux.
In order to facilitate the comprehension of the map in Fig. 5b, we compared the E-PRTR emission fluxes with estimates from the grid cells included in the corresponding hot spot areas identified through the inversion. We found that emission fluxes for the hot spots in Southern France and 255 Central England were one order of magnitude larger than the reported ones and for BE-NE-LUX emissions five times larger than those declared in the E-PRTR inventory. These results suggest either an under-reporting of current emissions and/or the occurrence of additional sources not reported by the E-PRTR inventory and/or emissions from historical production (such as landfill) or chlor-alkali industry (Fraser et al., 2014). 260

Comparison with NAME
For comparison, we ran an alternative top down approach based on observations at MHD combined with the UK MetOffice Numerical Atmospheric dispersion Modelling Environment (NAME) to simulate the dispersion and an iterative best fit technique (the simulated annealing) to derive 265 regional emission estimates . This alternative top-down approach differs from our procedure in the dispersion model, in the inversion technique, in the absence of an a priori emission field and in the use of a single receptor. The use of a single station narrows the study area to a sub-EGD that includes eight countries in North West Europe (NWEU), i.e. BE-NE-LUX, DE, DK, FR, IE and UK. Figure 6 reports a comparison of the results obtained using the two different 270 approaches for UK only and for the NWEU domain. Overall, a fair agreement is observed, with the differences between the two estimates always within the emission uncertainty. Such encouraging results endorse the reliability of the estimated emissions.

The global perspective 275
To put European emissions in a global perspective, we compared our results with global estimates.
Global top-down emissions as derived from atmospheric measurements are available only until 2012 (Carpenter and Reimann et al., 2014). For the sake of consistency, this comparison was made considering the same time period, when we estimated EGD average emissions of 2.5 Gg yr -1 , corresponding to 4% of the global average. The plot in Fig.7 shows a comparison between the EGD 280 and the global emission trends. Over 2006-2012, the EGD estimates show an average trend -3.9% yr -1 compared with a global trend, for the same period, of -2.2% yr -1 . This suggests that European CCl 4 emission sources are weakening faster than the global ones.

Conclusions 290
Average carbon tetrachloride emissions from the European Geographic Domain during 2006-2014 derived from atmospheric observations combined with a Bayesian inversion method have been estimated at 2.3 (± 0.8) Gg yr -1 , with a decreasing rate of 7.3% per year.
When comparing emissions derived with the top-down approach with those evaluated through 295 bottom-up methods, large discrepancies are observed. Such discrepancy is expected with regard to the information contained in the UNEP database, which reports production (without allowing for stock change but quoting destruction as a negative production) and consumption for emissive uses.
On the other hand, emissions reported in the E-PRTR inventory should include measurements or estimates from industrial processes (including waste treatment) that can potentially emit CCl 4 but 300 they represent only 3% of our emission estimates. In spite of the discrepancy in the quantification of emissions, the inversion is able to localise the main source areas reported in the E-PRTR, as also observed in the United States by Hu et al. (2016). Major source areas identified in the EGD are Southern France, Central England (UK) and BE-NE-LUX, where most of industrial scale production of basic organic chemicals are located. 305 Diffusive emissions other than current industrial processes could be hypothesised. Domestic emissions due to the use of bleach-based cleaning agents have been estimated to be 20% of our Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-326, 2016 Manuscript under review for journal Atmos. Chem. Phys. Published: 25 April 2016 c Author(s) 2016. CC-BY 3.0 License. emissions for the EGD (Odabasi et al., 2014). Fraser et al. (2014) hypothesised that the emissions from Australia were from contaminated soil, toxic waste treatment and were coincident geographically with chlor-alkali production (that is, the emissions were largely from historical 310 industrial processes). Natural emissions have been found to be negligible (less than 5%) on a global scale (Butler et al, 1999;Sturrock et al., 2002). This suggests an underestimation of CCl 4 emissions from industry and/or the incompleteness of the register of declared sources and/or other sources, such as use of cleaning agents and contaminated landfills.
To summarize, this study allowed us to estimate CCl 4 emission fluxes for the European regional 320 scale independently from inventories based on bottom-up procedures. Thanks to the good sensitivity in most of the EGD, the emission field can be reconstructed with a resolution level able to show, for each country, the main inconsistencies between the national emission declarations and the estimates based on atmospheric observations. Moreover, together with other regional studies (Fraser et al., 2014;Hu et al., 2016;Vollmer et al., 2009)