WMO GREENHOUSE GAS BULLETIN No. 14 | 22 November 2018 The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2017 ISSN 2078-0796 Measurements of the atmospheric abundance of the chlorofluorocarbon CFC-11, a potent greenhouse gas GHG and a stratospheric ozone-depleting substance ODS regulated under the Montreal Protocol on Substances that Deplete the Ozone Layer, show that since 2012 its rate of decline has slowed to roughly two thirds of its rate of decline during the preceding decade [1, 2]. The most likely cause of this slowing is increased emissions associated with production of CFC-11 in eastern Asia. This discovery illustrates the importance of long-term measurements of atmospheric composition, such as are carried out under the auspices of the Global Atmosphere Watch GAW Programme of WMO, in providing effective support and additional constraints for emissions-control legislation. The Montreal Protocol was designed to protect the stratospheric ozone layer by restricting the production of ODSs such as CFCs. As a consequence, CFC-11 trichlorofluoromethane, or CCl 3 F production reported under the Montreal Protocol declined to zero by 2010. As CFC-11 was phased out, its atmospheric abundance peaked in the early 1990s and then declined in a manner largely consistent with declining production combined with residual emissions of CFC-11 gradually escaping from stored “banks” in existing products and equipment. Atmospheric measurements of CFC-11 made by independent global networks show that since 2012 the rate of decrease in atmospheric CFC-11 has slowed to roughly two thirds of the rate that was observed between 2002 and 2012 [1, 2]. These global trends are shown in the left graph of the figure for the Advanced Global Atmospheric Gases Experiment AGAGE; shown in black and the National Oceanic and Atmospheric Administration NOAA; shown in red measurement networks. Also shown in the inset to this graph is the trend that was predicted in 2014 by WMO blue dashed assuming adherence to the Montreal Protocol [3]. Modelling results lead to the robust conclusion that these changes are predominately related to increased CFC-11 emissions rather than to other possible causes such as changing atmospheric transport. This conclusion is supported by recent increases in the northern to southern hemisphere difference in atmospheric concentration levels. Correlations between elevated abundances of CFC-11 and other measured gases further suggest that these increases originate from emissions in eastern Asia [1]. Separate CFC-11 emission trends resulting from model calculations taken from the 2018 WMO ozone assessment [2], based on data from each of the global measurement networks AGAGE black and NOAA red, are shown in the graph on the right of the figure. They are contrasted to CFC-11 production as reported under the Montreal Protocol green. These results show a levelling off of CFC-11 emissions around 2005, followed by an emission increase of about 15 after 2012. Emission scenario projections for the years 2006 and 2012 based on atmospheric data, reported production and releases from banks are shown as dots and dashes grey, respectively. This work demonstrates the importance of long-term measurements of atmospheric composition, such as are carried out under the auspices of the GAW Programme, in providing observation-based ination to support national emission inventories, especially in the context of agreements to address anthropogenic climate change, as well as for the recovery of the stratospheric ozone layer. WEATHER CLIMATE WATER 270 260 250 240 230 220 210 200 190 180 170 160 CFC-11 ppt 2015 2010 2005 2000 1995 1990 1985 1980 YearAGAGENOAAWMO 2014 245 240 235 230 225 220 CFC-11 ppt 2015 2010 Atmospheric CFC-11 Global Trends Derived emissions AGAGE observations NOAA observations 2002–2012 mean Emission projections Starting in 2006 Starting in 2012 Reported production CFC-11 Annual Emissions and Production Annual emission or production Gg yr -1 120 0 20 40 60 80 100 140 1995 2000 2005 2010 2015 Year Unexpected Increases in Global Emissions of CFC-11cutive summary The latest analysis of observations from the WMO GAW Programme shows that globally averaged surface mole fractions 1calculated from this in situ network for carbon dioxide CO 2 , methane CH 4 and nitrous oxide N 2 O reached new highs in 2017, with CO 2at 405.5 0.1 ppm 2 , CH 4at 1859 2 ppb 3and N 2 O at 329.9 0.1 ppb. These values constitute, respectively, 146, 257 and 122 of pre- industrial before 1750 levels. The increase in CO 2from 2016 to 2017 was smaller than that observed from 2015 to 2016 and practically equal to the average growth rate over the last decade. The influence of the El Nio event that peaked in 2015 and 2016 and contributed to the increased growth rate during that period sharply declined in 2017. For CH 4 , the increase from 2016 to 2017 was lower than that observed from 2015 to 2016 but practically equal to the average over the last decade. For N 2 O, the increase from 2016 to 2017 was higher than that observed from 2015 to 2016 and practically equal to the average growth rate over the past 10 years. The NOAA Annual Greenhouse Gas Index AGGI [4] shows that from 1990 to 2017 radiative forcing by long-lived GHGs LLGHGs increased by 41, with CO 2accounting for about 82 of this increase. Overview of the GAW in situ network observations for 2017 This fourteenth WMO Greenhouse Gas Bulletin reports atmospheric abundances and rates of change of the most important LLGHGs – CO 2 , CH 4and N 2 O – and provides a summary of the contributions of other gases. These three, together with CFC-12 and CFC-11, account for approximately 96 4of radiative forcing due to LLGHGs Figure 1. The GAW Programme http//www.wmo.int/gaw coordinates systematic observations and analysis of GHGs and other trace species. Sites where GHGs have been measured in the last decade are shown in Figure 2. Measurement data are reported by participating countries and archived and distributed by the WMO World Data Centre for Greenhouse Gases WDCGG at the Japan Meteorological Agency. The results reported here by WDCGG for the global average and growth rate are slightly different from results reported by NOAA for the same years [6] due to differences in the *Assuming a pre-industrial mole fraction of 278 ppm for CO 2 , 722 ppb for CH 4and 270 ppb for N 2 O. Figure 1. Atmospheric radiative forcing, relative to 1750, of LLGHGs and the 2017 update of the NOAA AGGI [4] CO 2 CH 4 N 2 O Global abundance in 2017 405.50.1 ppm 18592 ppb 329.90.1 ppb 2017 abundance relative to year 1750 * 146 257 122 2016–2017 absolute increase 2.2 ppm 7 ppb 0.9 ppb 2016–2017 relative increase 0.55 0.38 0.27 Mean annual absolute increase of last 10 years 2.24 ppm yr –1 6.9 ppb yr –1 0.93 ppb yr –1 Table 1. Global annual surface mean abundances 2017 and trends of key GHGs from the WMO GAW global GHG observational network. Units are dry-air mole fractions, uncertainties are 68 confidence limits [5], and the averaging is described in [7]. The numbers of stations used for the analyses are 129 for CO 2 , 126 for CH 4and 96 for N 2 O. 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 Annual Greenhouse Gas Index AGGI 2015 2010 2005 2000 1995 1990 1985 1980 Year 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Radiative Forcing W m -2 AGGI 2017 1.41 CO 2 CH 4 N 2 O CFC-12 CFC-11 minor gases 2 Ground-based Aircraft Ship GHG comparison sites Figure 2. The GAW global network for CO 2in the last decade. The network for CH 4is similar.stations used, differences in the averaging procedure and a slightly different time period for which the numbers are representative. WDCGG follows the procedure described in detail in [7]. Table 1 provides globally averaged atmospheric abundances of the three major LLGHGs in 2017 and changes in their abundances since 2016 and 1750. Data from mobile stations blue triangles and orange diamonds in Figure 2, with the exception of NOAA sampling in the eastern Pacific, are not used for this global analysis. The three GHGs shown in Table 1 are closely linked to anthropogenic activities and also interact strongly with the biosphere and the oceans. Predicting the evolution of the atmospheric content of GHGs requires quantitative understanding of their many sources, sinks and chemical transations in the atmosphere. Observations from GAW provide invaluable constraints on the budgets of these and other LLGHGs, and they are used to support emission inventories preparation and uate satellite retris of LLGHG column averages. The Integrated Global Greenhouse Gas Ination System IG 3 IS, promoted by WMO, provides further insights on the sources of GHGs on the national and sub-national level. Some examples of the ination that is delivered by the IG 3 IS projects can be found in the central insert of this Bulletin. The NOAA AGGI [4] in 2017 was 1.41, representing a 41 increase in total radiative forcing 4by all LLGHGs since 1990 and a 1.6 increase from 2016 to 2017 Figure 1. The total radiative forcing by all LLGHGs in 2017 3.062 W m -2 corresponds to an equivalent CO 2mole fraction of 493 ppm [4]. Relative contributions of the other gases in the total radiative forcing since pre-industrial time are presented in Figure 3. Carbon dioxide Carbon dioxide is the single most important anthropogenic GHG in the atmosphere, contributing approximately 66 4of the radiative forcing by LLGHGs. It is responsible for approximately 82 4of the increase in radiative forcing 15-minor CFC-11 CFC-12 N 2 O CH 4 CO 2 2.013, 66 0.124, 4 0.057 , 2 0.163, 5 0.195, 6 0.509 17 Figure 3. Increase in 2017 in global radiative forcing since pre-industrial times resulting from increased atmospheric burden of the most important LLGHGs, expressed in W m -2and relative to the total increase from all GHGs of 3.062 W m -2[4]. Year N 2 O growth rate ppb/yr 0.0 0.5 1.0 1.5 2.01985 1990 1995 2000 2005 2010 2015 b16001650170017501800185019001985 1990 1995 2000 2005 2010 2015 Year CH 4mole fraction ppb a Year CH 4growth rate ppb/yr -5051015201985 1990 1995 2000 2005 2010 2015 b Year CO 2growth rate ppm/yr 0.0 1.0 2.0 3.0 4.01985 1990 1995 2000 2005 2010 2015 b3003053103153203253303351985 1990 1995 2000 2005 2010 2015 Year N 2 O mole fraction ppb a3403503603703803904004101985 1990 1995 2000 2005 2010 2015 Year CO 2mole fraction ppm a Figure 4. Globally averaged CO 2mole fraction a and its growth rate b from 1984 to 2017. Increases in successive annual means are shown as the shaded columns in b. The red line in a is the monthly mean with the seasonal variation removed; the blue dots and line depict the monthly averages. Observations from 129 stations have been used for this analysis. Figure 5. Globally averaged CH 4mole fraction a and its growth rate b from 1984 to 2017. Increases in successive annual means are shown as the shaded columns in b. The red line in a is the monthly mean with the seasonal variation removed; the blue dots and line depict the monthly averages. Observations from 126 stations have been used for this analysis. Figure 6. Globally averaged N 2 O mole fraction a and its growth rate b from 1984 to 2017. Increases in successive annual means are shown as the shaded columns in b. The red line in a is the monthly mean with the seasonal variation removed; in this plot it is overlapping with the blue dots and line that depict the monthly averages. Observations from 96 stations have been used for this analysis. 3 Continued on page 64 ATMOSPHERIC OBSERVATIONS AND ANALYSIS IN SUPPORT OF GHG EMISSION MITIGATION – EXAMPLE PROJECTS OF THE GAW IG 3 IS PROGRAMME 1. Atmospheric measurements reveal strong forest carbon sink in New Zealand By Sara Mikaloff-Fletcher National Institute of Water and Atmospheric Research Ltd, New Zealand and Jocelyn Turnbull GNS Science, New Zealand Net CO 2uptake from land use, land-use change and forestry currently offsets approximately 30 of New Zealand’s GHG emissions [10]. These land carbon sinks played a key role in meeting New Zealand’s past GHG emission targets under the United Nations Framework Convention on Climate Change UNFCCC, and they are expected to be a major component of the nation’s strategy for future GHG mitigation. New Zealand’s National Inventory Report NIR estimates forest carbon uptake based on tree diameter and height measurements at a national network of study sites, and allometric equations that infer carbon mass from these measurements. This approach, which is required by current Intergovernmental Panel on Climate Change IPCC guidelines [11], has substantial uncertainty. Atmospheric CO 2observations and inverse model simulations [12], illustrated in Figure 8, suggest that New Zealand’s forest carbon sink may far exceed estimates from the NIR [10] and land process models [12]. Furthermore, the atmospheric observations reveal significant interannual variability that is not detected by the NIR ology. This study combined in situ observations of atmospheric CO 2at a network of sites with a high-resolution atmospheric model. The spatial pattern of the sink suggests that much of this missing carbon uptake occurs in Fiordland, a high rainfall region dominated by indigenous forests. The research team of New Zealand is launching a new research programme to further uate the processes that drive this sink. Through close engagement with users in the carbon accounting, land management and policy communities, this nationally funded programme will support the IG 3 IS mission to provide a bridge between science and policy for GHG monitoring and emission estimation. 2. Use of atmospheric observations of greenhouse gases to in the United Kingdom national inventory By Alistair Manning UK Met Office To support the emission estimates that follow the IPCC protocol “bottom-up” [11] and are reported annually to UNFCCC, the United Kingdom uses a completely independent “top-down” [13] for ining on its GHG emission estimates. The uses a combination of atmospheric observations and modelling, and the results are also reported annually in the United Kingdom National Inventory Report to UNFCCC. Significant differences in the emissions estimated utilizing the two approaches are used by the United Kingdom Government Department of Business, Energy and Industrial Strategy BEIS to identify areas worthy of further investigation. 2010 2011 2012 2013 180 160 140 120 100 80 60 40 20 0 Tg CO 2yr -1NZ Inventory 2015 Inversion 2011-2013 mean CO 2ux distribution in kg CO 2m -2yr -1 36S 39S 42S 45S 168E 171E 174E 177E 05 -5           Figure 9. United Kingdom-funded DECC network of observation sites Figure 8. Geographic distribution o