The hydroxyl radical (OH) is a key oxidant involved in the removal of air pollutants and greenhouse gases from the atmosphere1,2,3. The ratio of Northern Hemispheric to Southern Hemispheric (NH/SH) OH concentration is important for our understanding of emission estimates of atmospheric species such as nitrogen oxides and methane4,5,6. It remains poorly constrained, however, with a range of estimates from 0.85 to 1.4 (refs 4, 7,8,9,10). Here we determine the NH/SH ratio of OH with the help of methyl chloroform data (a proxy for OH concentrations) and an atmospheric transport model that accurately describes interhemispheric transport and modelled emissions. We find that for the years 2004–2011 the model predicts an annual mean NH–SH gradient of methyl chloroform that is a tight linear function of the modelled NH/SH ratio in annual mean OH. We estimate a NH/SH OH ratio of 0.97 ± 0.12 during this time period by optimizing global total emissions and mean OH abundance to fit methyl chloroform data from two surface-measurement networks and aircraft campaigns11,12,13. Our findings suggest that top-down emission estimates of reactive species such as nitrogen oxides in key emitting countries in the NH that are based on a NH/SH OH ratio larger than 1 may be overestimated.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Levy, H. Normal atmosphere: large radical and formaldehyde concentrations predicted. Science 173, 141–143 (1971)
Crutzen, P. J. in Tropospheric Ozone: Regional and Global Scale Interactions (ed. Isaksen, I. S. A. ) 3–11 (Reidel, 1988)
World Meteorological Organization. Scientific Assessment of Ozone Depletion: 2010. (Global Ozone Research and Monitoring Project, Report no. 52, 2011)
Naik, V. et al. Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Atmos. Chem. Phys. 13, 5277–5298 (2013)
Miyazaki, K. et al. Global NOx emission estimates derived from an assimilation of OMI tropospheric NO2 columns. Atmos. Chem. Phys. 12, 2263–2288 (2012)
Patra, P. K. et al. TransCom model simulations of CH4 and related species: linking transport, surface flux and chemical loss with CH4 variability in the troposphere and lower stratosphere. Atmos. Chem. Phys. 11, 12813–12837 (2011)
Brenninkmeijer, C. A. M. et al. Interhemispheric asymmetry in OH abundance inferred from measurements of atmospheric 14CO. Nature 356, 50–52 (1992)
Montzka, S. A. et al. New observational constraints for atmospheric hydroxyl on global and hemispheric scales. Science 288, 500–503 (2000)
Krol, M. C. & Lelieveld, J. Can the variability in tropospheric OH be deduced from measurements of 1,1,1-trichloroethane (methyl chloroform)? J. Geophys. Res. 108, 4125 (2003)
Prinn, R. G. et al. Evidence for variability of atmospheric hydroxyl radicals over the past quarter century. Geophys. Res. Lett. 32, L07809 (2005)
Prinn, R. G. et al. A history of chemically and radiatively important gases in air deduced from ALE/GAGE/AGAGE. J. Geophys. Res. 115, 17751–17792 (2000)
Montzka, S. A. et al. Small interannual variability of global atmospheric hydroxyl. Science 331, 67–69 (2011)
Wofsy, S. C. et al. HIAPER Pole-to-Pole Observations (HIPPO): fine grained, global scale measurements for determining rates for transport, surface emissions, and removal of climatologically important atmospheric gases and aerosols. Phil. Trans. R. Soc. A 369, 2073–2086 (2011)
Kanaya, Y. et al. Chemistry of OH and HO2 radicals observed at Rishiri Island, Japan, in September 2003: missing daytime sink of HO2 and positive nighttime correlations with monoterpenes. J. Geophys. Res. 112, D11308 (2007)
Lelieveld, J. et al. Atmospheric oxidation capacity sustained by a tropical forest. Nature 452, 737–740 (2008)
Hofzumahaus, A. et al. Amplified trace gas removal in the troposphere. Science 324, 1702–1704 (2009)
Elshorbany, Y. F. et al. HOx budgets during HOxComp: A case study of HOx chemistry under NOx-limited conditions. J. Geophys. Res. 117, D03307 (2012)
Krol, M. C. et al. Global OH trend inferred from methyl chloroform measurements. J. Geophys. Res. 103, 10697–10711 (1998)
Prinn, R. G. et al. Evidence for significant variations of atmospheric hydroxyl radicals in the last two decades. Science 292, 1882–1888 (2001)
Krol, M. C. et al. What can 14CO measurements tell us about OH? Atmos. Chem. Phys. 8, 5033–5044 (2008)
Sudo, K. et al. CHASER: a global chemical model of the troposphere. 1. Model description. J. Geophys. Res. 107, 4339 (2002)
Patra, P. K. et al. Transport mechanisms for synoptic, seasonal and interannual SF6 variations and ‘age’ of air in troposphere. Atmos. Chem. Phys. 9, 1209–1225 (2009)
Spivakovsky, C. et al. Three-dimensional climatological distribution of tropospheric OH: update and evaluation. J. Geophys. Res. 105, 8931–8980 (2000)
McCulloch, A. & Midgley, P. M. The history of methyl chloroform emissions: 1951–2000. Atmos. Environ. 35, 5311–5319 (2001)
EDGAR4.2. Emission Database for Global Atmospheric Research (EDGAR), release version 4.2. (European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency, 2011)
Rigby, M. et al. Re-evaluation of the lifetimes of the major CFCs and CH3CCl3 using atmospheric trends. Atmos. Chem. Phys. 13, 2691–2702 (2013)
Maiss, M. et al. Sulfur hexafluoride—a powerful new atmospheric tracer. Atmos. Environ. 30, 1621–1629 (1996)
Waugh, D. W. et al. Tropospheric SF6: age of air from the northern hemisphere mid-latitude surface. J. Geophys. Res. 118, 11429–11441 (2013)
Mao, J. et al. Radical loss in the atmosphere from Cu–Fe redox coupling in aerosols. Atmos. Chem. Phys. 13, 509–519 (2013)
Taraborrelli, D. et al. Hydroxyl radical buffered by isoprene oxidation over tropical forests. Nature Geosci. 5, 190–193 (2012)
Onogi, K. et al. The JRA-25 reanalysis. J. Meteorol. Soc. Jpn. 85, 369–432 (2007)
Takigawa, M. et al. Simulation of ozone and other chemical species using a Center for Climate System Research/National Institute for Environmental Studies atmospheric GCM with coupled stratospheric chemistry. J. Geophys. Res. 104, 14003–14018 (1999)
Xie, P. & Arkin, P. A. Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Am. Meteorol. Soc. 78, 2539–2558 (1997)
Levin, I. et al. The global SF6 source inferred from long-term high precision atmospheric measurements and its comparison with emission inventories. Atmos. Chem. Phys. 10, 2655–2662 (2010)
Sander, S. P. et al. Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies: Evaluation Number 17 (Jet Propulsion Laboratory Publication 10-6, California Institute of Technology, 2011)
Prather, M. J. Lifetimes and time-scales in atmospheric chemistry. Phil. Trans. R. Soc. A 365, 1705–1726 (2007)
Miller, B. R. et al. A sample preconcentration and GC/MS detector system for in situ measurements of atmospheric trace halocarbons, hydrocarbons, and sulfur compounds. Anal. Chem. 80, 1536–1545 (2008)
Hyson, P. et al. A two-dimensional transport simulation model for trace atmospheric constituents. J. Geophys. Res. 85, 4443–4456 (1980)
Jacob, D. J. et al. Atmospheric distribution of 85Kr simulated with a General Circulation Model. J. Geophys. Res. 92, 6614–6626 (1987)
Levin, I. & Hesshaimer, V. Refining of atmospheric transport model entries by the globally observed passive tracer distributions of 85krypton and sulfur hexafluoride (SF6). J. Geophys. Res. 101, 16745–16755 (1996)
Lintner, B. R. et al. Seasonal circulation and Mauna Loa CO2 variability. J. Geophys. Res. 111, D13104 (2006)
Fraser, P. J. et al. Tropospheric methane in the mid-latitudes of in the southern hemisphere. J. Atmos. Chem. 1, 125–135 (1984)
Nakazawa, T. et al. Temporal and spatial variations of upper tropospheric and lower stratospheric carbon dioxide. Tellus 43B, 106–117 (1991)
Sawa, Y. et al. Aircraft observation of the seasonal variation in the transport of CO2 in the upper atmosphere. J. Geophys. Res. 117, D05305 (2012)
Holmes, C. D. et al. Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions. Atmos. Chem. Phys. 13, 285–302 (2013)
Murray, L. T., Logan, J. A. & Jacob, D. J. Interannual variability in tropical tropospheric ozone and OH: the role of lightning. J. Geophys. Res. 118, 11468–11480 (2013)
Miyazaki, K. et al. Global lightning NOx production estimated by an assimilation of multiple satellite data sets. Atmos. Chem. Phys. 14, 3277–3305 (2014)
Maione, M. et al. Estimates of European emissions of methyl chloroform using a Bayesian inversion method. Atmos. Chem. Phys. Discuss. 14, 8209–8256 (2014)
We thank the HIPPO science team and the crew and support staff at the NCAR Research Aviation Facility, and all the laboratory staff working for AGAGE and NOAA measurement networks. This work is partly supported by the Japan Society for the Promotion of Science/Grants-in-Aid for Scientific Research (KAKENHI) Kiban-A (grant no. 22241008) and Ministry of Education, Culture, Sports, Science and Technology (MEXT) Arctic GRENE projects. NCAR is sponsored by the National Science Foundation (NSF). HIPPO was supported by NSF grants ATM-0628575, ATM-0628519, ATM-0628388 ATM-0628452 and ATM-1036399, by NASA award NNX11AF36G, and by NCAR. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF, NOAA or NASA. M.C.K. is supported by EU FP7 project PEGASOS. AGAGE is supported principally by NASA grants to Massachusetts Institute of Technology (NNX11AF17G) and Scripps Institution of Oceanography (NNX11AF16G) and also by NOAA and the CSIRO. Mace Head is supported by the Department of Energy and Climate Change, award GA0201. We thank the CSIRO Oceans and Atmosphere Flagship and the Bureau of Meteorology for Cape Grim project funding. NOAA flask measurements are supported in part by NOAA’s Climate Program Office and its Atmospheric, Chemistry, Carbon Cycle and Climate Program.
The authors declare no competing financial interests.
Extended data figures and tables
Extended Data Figure 1 Latitude–height distributions of zonal-mean OH and CH3CCl3 lifetime in the troposphere.
Results are shown for two months in distinct seasons, January (left column) and July (middle column), and annual mean (right column) for ACTM_0.99 OH (a), ACTM_1.26 OH (b) and ACTM_9.99 CH3CCl3 (c) lifetime. The vertical model coordinate is defined by sigma-pressure = (P − Ptop)/P0, where P, Ptop and P0 are pressure at a given model level, model top level and model surface layer, respectively. Although there is overall agreement for the seasonal variations and spatial gradients, the annual mean NH/SH OH ratio is ∼26% higher for ACTM_1.26 than for ACTM_0.99. The higher OH in the NH for ACTM_1.26 is caused mainly by greater OH amounts near the Earth’s surface over the regions of active air pollution chemistry, such as industrialized Asia, Europe and North America. The difference in annual mean NH/SH OH ratio between ACTM_1.26 and ACTM_0.99 diminishes at a sigma-pressure height of 0.5 (mid-troposphere) and above. Note that the CH3CCl3 lifetime in the lower troposphere over the tropical latitudes of the summer hemisphere can be shorter than 2 years, which is of the same order of magnitude as the interhemispheric exchange time of 1.3 years in ACTM6,22. Thus both chemistry and transport in the troposphere are expected to influence the meridional distributions of CH3CCl3. The monthly (at 0.5° S in January and 7.3° N in July) and annual (4.2° N) locations of the ITCZ determined from the dynamical and chemical equators are marked approximately by a vertical line in a and b.
Extended Data Figure 2 Longitude–latitude distributions of CH3CCl3 emissions, trends in global total emissions and CH3CCl3 global lifetimes in ACTM_0.99, and sensitivity of the MHD–CGO CH3CCl3 difference to the NH/SH emission ratio.
a, b, The ‘Control’ CH3CCl3 emission case uses interannually varying spatial distributions until 1999, and the 1999 spatial distribution for all later years (a, top row), and the UNEP emission distribution depends on country reports for each year (b). There is an order of magnitude difference in colour scales for 1995 and 2005/2010. Although the UNEP-based maps show no emissions over Europe, the atmospheric observations suggest continued emissions of CH3CCl3 up to and including 2011 (ref. 48). Thus we continued to use the 1990s emission map for 2000 and later years in the Control case. The surface observation site numbers are shown in b. c, Global total CH3CCl3 emissions are shown in comparison with ref. 26 (Extended Data Table 1), and agree within 0.8 Gg per year or 13% on average during 2000–2009. Lifetimes of CH3CCl3 are estimated by using two different methods (black line, τSS = burden/loss; red line, d(burden)/dt = emission − burden/τtotal). The total lifetimes are adjusted for CH3CCl3 loss on the oceanic surface for this comparison plot. d, The global total emissions of SF6, scaled to ref. 34, and HFC-134a (EDGAR4.2) as used in the ACTM simulations (Methods). The SF6 and HFC-134a emissions distributions are from the EDGAR4.2 emission database25. e, The observed MHD–CGO difference is shown as horizontal lines at 0.39 p.p.t. for GC–MD and 0.44 p.p.t. for Medusa instruments, which suggests that generally a solution exists for simulating MHD–CGO differences for ACTM_0.99 at a NH/SH emission ratio of >10 (the ‘Control’ case is shown by the vertical line at ∼16.6). We have used monthly mean model output for this plot; therefore no distinction between Medusa and GC–MD sampling times can be made for model results (unlike in Fig. 4). The ACTM simulated symbols at the right end of each line correspond to all emissions in the NH (NH/SH ratio = ∞) and are not scaled on the x axis. No solution can be achieved for ACTM_1.26 for the Control global CH3CCl3 emissions. Because the NH/SH emission ratios are in the range 17–40 for UNEP-based emissions for the 2000s, we find the ACTM_0.99 MHD–CGO concentration differences to be in good agreement with those observed (Fig. 1b, inset).
Extended Data Figure 3 Longitude–latitude distributions of simulated CH3CCl3, and comparisons of simulated and measured CH3CCl3 variations at NOAA HATS sites.
a, b, The right column is for annual mean concentration and the left two columns are for two distinct months: January and July. Results are presented for the lowest model level for 2010, considering ‘Control’ global emissions and annual mean OH concentrations. Variable colour scales are used to account for the decrease in CH3CCl3 concentrations. Offsets (indicated at the bottom of each panel in b) are subtracted from the CH3CCl3 ACTM_1.26 run to match colour shading over Antarctica for ACTM_0.99 and ACTM_1.26 runs. The distributions of SF6 with decreasing concentrations from NH to SH (not shown) are controlled by emission distributions and atmospheric transport, whereas those for CH3CCl3 are governed by the loss due to chemical reaction with tropospheric OH, transport and emissions. c, d, Monthly mean concentrations at four representative sites (left column) and inter-site differences with respect to PSA for ALT, KUM, SMO and SPO (middle column), and for BRW, THD, MHD and NWR (right column). ACTM_0.99 (c) and ACTM_1.26 (d) simulation results for the ‘Control’ global emissions. All measurements are monthly means derived from the NOAA flask network.
Extended Data Figure 4 Relationship between lifetime and emission change for simulating the observed decay in CH3CCl3 concentration and the NH–SH CH3CCl3 gradient.
a, Implied emissions calculated for different lifetimes of CH3CCl3 (by decreasing or increasing the loss rates by 10%, 20% or 30% with respect to a ‘Control’ loss case corresponding to a lifetime of 4.9 years). Because both the emissions and burden change with time, no general conclusion can be drawn, apart from the linearity between lifetime (primarily governed by the OH abundance) and implied or required global total emissions for simulating the observed concentration decay rates. b, As a, but all values scaled with respect to the control value. This allows us to conclude that there is a range of global emission and global OH values that can successfully simulate the observed global decline in CH3CCl3 mixing ratio over time that are a constant relative adjustment to the ‘control’ global emissions and global mean OH concentrations. The ACTM results for a +30% to −30% change in chemical loss (CL) and simultaneous +117% to −117% change in global total emissions (E), respectively, are shown for ACTM_0.99 (c) and for ACTM_1.26 (d) in comparison with the measurements (2004–2011). The 2004–2011 average of MHD–CGO and ALT–PSA differences and peak-to-trough seasonal cycle amplitudes are summarized in Fig. 2.
Extended Data Figure 5 State of weather during the five HIPPO campaigns, and representativeness of HIPPO measurements over the central Pacific Ocean.
a, Locations of HIPPO profiles, with flight tracks marked by research flight (RF) numbers during each of the five HIPPO campaigns, plotted with rainfall rates33. The onward transects, from the Arctic to the Antarctic, over the Central Pacific Ocean are used in here. Although data from selected flights over the central Pacific Ocean are used here, each of the HIPPO campaigns consisted of a series of 10–14 flights in the Pacific region spanning 67° S–87° N (from north of Alaska to south of New Zealand). Measurement periods for the HIPPO campaigns are 8–30 January 2009, 31 October–22 November 2009, 24 March–16 April 2010, 14 June–11 July 2011 and 9 August–9 September 2011. The pentad-mean CMAP rainfall rates are provided by NOAA/OAR/ESRL PSD, Boulder, Colorado, USA (http://www.esrl.noaa.gov/psd). b, c, As a check for representativeness of HIPPO over the central Pacific Ocean, we show comparisons of ACTM_0.99 simulated zonal mean (shaded) seasonal cycles of CH3CCl3 (b) and SF6 (c) at the surface with those simulated for three different longitudes (contour lines) (top row, central Pacific Ocean; middle row, central Atlantic Ocean; bottom row, central Indian Ocean). The zonal mean values for both CH3CCl3 and SF6 agree to within 0.1 p.p.t. with those at 180° E, suggesting that HIPPO measurements of these gases over the central Pacific represent zonal averages. The differences between the zonal mean values and those at different longitude regions decrease with increasing altitude. The zonal differences between different sectors are governed primarily by the emissions; for example, larger differences between the zonal mean are observed for the Indian Ocean sector at ∼30° N for SF6 (d, bottom row) owing to Indian emissions. The zonal differences for CH3CCl3 are apparent but are less distinct because the surface emissions are small over the selected longitudes (see Extended Data Fig. 2).
a–h, Measurements from the PANTHER GC-ECD (left column) and ACTM simulations (right column) for January (HIPPO 1), June–July (HIPPO 4), August–September (HIPPO 5) and November (HIPPO 2) over the central Pacific (research flight no. 2-8). All the data are binned and averaged at intervals of 2.5° latitude and 1 km altitude. The white areas indicate no flights at those latitudes and altitudes (no PANTHER measurements were conducted during HIPPO 3). Although data from selected flights are shown here, each of the HIPPO campaigns consisted of a series of 10–14 flights in the Pacific region spanning 67° S–87° N from north of Alaska to south of New Zealand (Extended Data Fig. 5a). i–r, Latitudinal (i–m; 1–3 km average) and vertical (n–r; 1–3 km average to 5–7 km average) SF6 gradients simulated by ACTM using emissions from EDGAR4.2 (extended for 2009–2011) and measured during the five HIPPO campaigns. The y-axis range of 0.8 p.p.t. is fixed for all the panels in the left column to show the meridional gradients, but the absolute values differ to account for the increase in concentration from January 2009 to September 2011. A 0.1 p.p.t. offset is added to the simulated SF6 concentrations for better comparison with the observations. Because SF6 is an inert tracer in the troposphere, an arbitrary offset does not affect our interpretation of model interhemispheric transport. The altitude range of 1–3 km is chosen here, as opposed to 1–4 km in Fig. 2, for obtaining representative vertical gradients because the number of observations decreases significantly above 7 km.
Extended Data Figure 7 Estimation of of NH/SH OH ratios from the relationships of the NH–SH CH3CCl3 gradient with NH/SH OH ratio.
a–d, Comparisons of Mace Head to Cape Grim gradients in CH3CCl3 as measured by AGAGE and simulated by nine cases of ACTM with varying NH/SH ratios of OH, but for only the ‘Control’ global emissions and OH concentration scenario. The results for ACTM_0.99, with OH modified using a sine (latitude) function (Extended Data Table 2b), are shown in the top row, and those for mixing the ACTM_0.99 and ACTM_1.26 OH fields are shown in the bottom row. Time series at monthly mean intervals are shown in the left column, and annual means in the right column. Most of the observed differences between MHD and CGO (symbols) lie above the ACTM_0.99 simulated line, and towards simulations using NH/SH OH ratios of less than 1. The first 3 years of simulations are considered as model spin-up and are not used to calculate statistics. e, f, Similar to Fig. 4, but for AGAGE GC–MD observations for different years between 2004 and 2011 (e) and using HIPPO observations below 4 km during individual campaigns (f) for the ‘Control’ global emissions and global OH concentrations (right). This figure shows the changes in MHD (NH)–CGO (SH) CH3CCl3 gradients because of the decrease in emissions with time. We show only the averaged (2004–2011) results in Fig. 4 of the main text by sampling the model results at the time of measurements to avoid any bias from the changing NH–SH CH3CCl3 gradients. The HIPPO NH–SH CH3CCl3 gradients are for the hemispheres separated at the Equator, whereas the results in Fig. 4 separate the hemispheres using data in the latitudes polewards of 30°, to avoid the tropical region so as to estimate a NH/SH OH ratio that is more comparable with those estimated from the surface sites chosen for comparison (for example MHD and CGO). The cross and plus symbols mark the location of NH–SH CH3CCl3 concentration difference for deriving the NH/SH OH ratio. The calculated NH/SH (separated at the Equator) OH ratio is 1.01 ± 0.16 averaged over five HIPPO campaigns (1.07, 1.05, 0.85, 1.24 and 0.87 for HIPPO 1–5, respectively, during January 2009, October–November 2009, March–April 2010, June–July 2011 and August–September 2011). The large variability (±0.16) between the HIPPO campaigns is caused by the seasonal cycle in OH and transport as well as uncertainties in emissions.
About this article
Cite this article
Patra, P., Krol, M., Montzka, S. et al. Observational evidence for interhemispheric hydroxyl-radical parity. Nature 513, 219–223 (2014). https://doi.org/10.1038/nature13721
Discrepancy between simulated and observed ethane and propane levels explained by underestimated fossil emissions
Nature Geoscience (2018)
Tropospheric OH and stratospheric OH and Cl concentrations determined from CH4, CH3Cl, and SF6 measurements
npj Climate and Atmospheric Science (2018)
Nature Climate Change (2017)
Paleo-Perspectives on Potential Future Changes in the Oxidative Capacity of the Atmosphere Due to Climate Change and Anthropogenic Emissions
Current Pollution Reports (2015)